Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-28T13:05:06.448Z Has data issue: false hasContentIssue false

References

Published online by Cambridge University Press:  20 October 2020

Elliot Murphy
Elliot Murphy
Affiliation:
University College London
Get access
Type
Chapter
Information
The Oscillatory Nature of Language , pp. 249 - 318
Publisher: Cambridge University Press
Print publication year: 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abe, K. & Watanabe, D. (2011). Songbirds possess the spontaneous ability to discriminate syntactic rules. Nature Neuroscience 14(8): 1067–1074.Google Scholar
Abel, T. J., Rhone, A. E., Nourski, K. V., Ando, T. K., Oya, H., Kovach, C. K., Kawasaki, H., Howard III, M. A., & Tranel, D. (2016). Beta modulation reflects name retrieval in the human anterior temporal lobe: an intracranial recording study. Journal of Neurophysiology 115(6): 3052–3061.Google Scholar
Abels, K. (2013). Comments on Hornstein. Mind & Language 28(4): 421–429.Google Scholar
Aboitiz, F. (2012). Gestures, vocalizations, and memory in language origins. Frontiers in Evolutionary Neuroscience 4: 2.Google Scholar
Aboitiz, F. (2017). A Brain for Speech: A View from Evolutionary Neuroanatomy. London: Palgrave Macmillan.Google Scholar
Abraham, A., von Cramon, D. Y., & Schubotz, R. I. (2008). Meeting George Bush versus meeting Cinderella: the neural response when telling apart what is real from what is fictional in the context of our reality. Journal of Cognitive Neuroscience 20: 965–976.Google Scholar
Abutalebi, J. & Cappa, S. F. (2008). Language disorders. In Cappa, S. F., Abutalebi, J., Démonet, J.-F., Fletcher, P. C., & Garrard, P. (eds.). Cognitive Neurology: A Clinical Textbook. Oxford: Oxford University Press. 43–66.Google Scholar
Ackermann, H. & Ziegler, W. (2010). Brain mechanisms underlying speech motor control. In Hardcastle, W. J., Laver, J., & Gibbon, F. E. (eds.). The Handbook of Phonetic Sciences. 2nd ed. Malden, MA: Wiley-Blackwell. 202–250.Google Scholar
Ackermann, H. & Ziegler, W. (2013). A ‘birdsong perspective’ on human speech production. In Bolhuis, J. J. & Everaert, M. (eds.). Birdsong, Speech, and Language: Exploring the Evolution of Mind and Brain. Cambridge, MA: MIT Press. 331–352.Google Scholar
Acsády, L. (2017). The thalamic paradox. Nature Neuroscience 20: 901–902.CrossRefGoogle ScholarPubMed
Adams, N. E., Teige, C., Mollo, G., Karapanagiotidis, T., Cornelissen, P. L., Smallwood, J., Traub, R. D., Jefferies, E., & Whittington, M. A. (2019). Theta/delta coupling across cortical laminae contributes to semantic cognition. Journal of Neurophysiology 121(4): 1150–1161.Google Scholar
Adger, D. (2013). A Syntax of Substance. Cambridge, MA: MIT Press.Google Scholar
Adger, D. (2017). A Memory Architecture for Merge. Ms. Queen Mary University of London. ling.auf.net/lingbuzz/003440.Google Scholar
Adger, D. (2019a). Language Unlimited: The Science behind Our Most Creative Power. Oxford: Oxford University Press.Google Scholar
Adger, D. (2019b). Linguistic Representations: A Note on Terminology vs. Ontology. Ms. Queen Mary University of London. ling.auf.net/lingbuzz/004616.Google Scholar
Adger, D. & Svenonius, P. (2011). Features in minimalist syntax. In Boeckx, C. (ed.). The Handbook of Linguistic Minimalism. Oxford: Blackwell. 27–51.Google Scholar
Ainsworth, M., Lee, S., Cunningham, M. O., Roopun, A. K., Traub, R. D., Kopell, N. J., & Whittington, M. A. (2011). Dual gamma rhythm generators control interlaminar synchrony in auditory cortex. Journal of Neuroscience 31: 17040–17051.Google Scholar
Akam, T. & Kullmann, D. M. 2014. Oscillatory multiplexing of population codes for selective communication in the mammalian brain. Nature Reviews Neuroscience 15: 111–122.Google Scholar
Akimoto, Y., Takahashi, H., Gunji, A., Kaneko, Y., Asano, M., Matsuo, J. et al. (2017). Alpha band event related desynchronization underlying social situational context processing during irony comprehension: a magnetoencephalography source localization study. Brain and Language 175: 42–46.Google Scholar
Akiyama, M., Tero, A., Kawasaki, M., Nishiura, Y., & Yamaguchi, Y. (2017). Theta-alpha EEG phase distributions in the frontal area for dissociation of visual and auditory working memory. Scientific Reports 7: 42776.Google Scholar
Alcalá-López, D., Smallwood, J., Jefferies, E., Van Overwalle, F., Vogeley, K., Mars, R. B., Turetsky, B. I., Laird, A. R., Fox, P.T., Eickhoff, S.B., & Bzdok, D. (2018). Computing the social brain connectome across systems and states. Cerebral Cortex 28(7): 2207–2232.CrossRefGoogle ScholarPubMed
Alexander, D. M., Nikolaev, A. R., Jurica, P., Zvyagintsev, M., Mathiak, K., & van Leeuwen, C. (2016). Global neuromagnetic cortical fields have non-zero velocity. PloS ONE 11(3): e0148413.Google Scholar
Alexandrou, A. M., Saarinen, T., Mäkelä, S., Kujala, J., & Salmelin, R. (2017). The right hemisphere is highlighted in connected natural speech production and perception. NeuroImage 152: 623–638.Google Scholar
Allen, K. & Monyer, H. (2015). Interneuron control of hippocampal oscillations. Current Opinion in Neurobiology, 31: 81–87.Google Scholar
Amalric, M. & Dehaene, S. (2018). Cortical circuits for mathematical knowledge: evidence for a major subdivision within the brain’s semantic networks. Philosophical Transactions of the Royal Society B 373: 20160515.Google Scholar
Amalric, M. & Dehaene, S. (2019). A distinct cortical network for mathematical knowledge in the human brain. NeuroImage 189: 19–31.Google Scholar
Amundson, R. (1998). Typology reconsidered: two doctrines on the history of evolutionary biology. Biology and Philosophy 13: 153–177.Google Scholar
Amundson, R. (2006). EvoDevo as cognitive psychology. Biological Theory 1(1): 10–11.Google Scholar
Amzica, F. (2002). In vivo electrophysiological evidences for cortical neuron-glia interactions during slow (<1 Hz) and paroxysmal sleep oscillations. Journal of Physiology Paris 96(3–4): 209–219.Google Scholar
Anderson, F., Anjum, R. L., & Rocca, E. (2019). Philosophical bias is the one bias that science cannot avoid. eLife 8: e44929.Google Scholar
Anderson, M. L. (2016). Précis of After Phrenology: Neural Reuse and the Interactive Brain. Behavioral and Brain Sciences 39: e120.Google Scholar
Andics, A. & Miklósi, Á. (2018). Neural processes of vocal social perception: dog-human comparative fMRI studies. Neuroscience and Biobehavioral Reviews 85: 54–64.Google Scholar
Antzoulatos, E. G. & Miller, E. K. (2016). Synchronous beta rhythms of frontoparietal networks support only behaviorally relevant representations. eLife 5: e17822.Google Scholar
Arbib, M. A. (ed.). (2006). From Action to Language via the Mirror Neuron System. Cambridge: Cambridge University Press.Google Scholar
Ardila, A., Bernal, B., & Rosselli, M. (2016). Why Broca’s area damage does not result in classical Broca’s aphasia. Frontiers in Human Neuroscience 10: 249.Google Scholar
Armeni, K., Willems, R. M., van den Bosch, A., & Schoffelen, J.-M. (2019). Frequency-specific brain dynamics related to prediction during language comprehension. NeuroImage 198: 283–295.Google Scholar
Arnal, L. H., Doelling, K. B., & Poeppel, D. (2014). Delta-beta coupled oscillations underlie temporal prediction accuracy. Cerebral Cortex 25: 3077–3085.Google Scholar
Aronov, D., Nevers, R., & Tank, D. W. (2017). Mapping of a non-spatial dimension by the hippocampal-entorhinal circuit. Nature 543: 719–722.CrossRefGoogle ScholarPubMed
Artoni, F., d’Orio, P., Catricalà, E., Conca, F., Bottoni, F., Pelliccia, V., Sartori, I., Lo Russo, G., Cappa, S. F., Micera, S., & Moro, A. (2019). Electrophysiological correlates of syntactic structures. bioRxiv. http://dx.doi.org/10.1101/660415Google Scholar
Aru, J., Aru, J., Priesemann, V., Wibral, M., Lana, L., Pipa, G., Singer, W., & Vicente, R. (2015). Untangling cross-frequency coupling in neuroscience. Current Opinion in Neurobiology 31: 51–61.Google Scholar
Asano, E. & Gotman, J. (2016). Is electrocorticography-based language mapping ready to replace stimulation? Neurology 86(13): 1174–1176.Google Scholar
Assaneo, M. F. & Poeppel, D. (2018). The coupling between auditory and motor cortices is rate-restricted: evidence for an intrinsic speech-motor rhythm. Science Advances 4: eaao3842.CrossRefGoogle ScholarPubMed
Atasoy, S., Donnelly, I., & Pearson, J. (2016). Human brain networks function in connectome-specific harmonic waves. Nature Communications 7: 10340.CrossRefGoogle ScholarPubMed
Attaheri, A., Kikuchi, Y., Milne, A. E., Wilson, B., Alter, K., & Petkov, C. I. (2015). EEG potentials associated with artificial grammar learning in the primate brain. Brain & Language 148: 74–80.Google Scholar
Attal, Y. & Schwartz, D. (2013). Assessment of subcortical source localization using deep brain activity imaging model with minimum norm operators: a MEG study. PLoS ONE 8(3): e59856.Google Scholar
Aumann, T. D. & Prut, Y. (2015). Do sensorimotor β-oscillations maintain muscle synergy representations in primary motor cortex? Trends in Neuroscience 38(2): 77–85.Google Scholar
Axmacher, N. (2016). A useful code for sequences. Nature Neuroscience 19(10): 1276–1277.CrossRefGoogle ScholarPubMed
Axmacher, N., Henseler, M. M., Jensen, O., Weinreich, I., Elger, C. E., & Fell, J. (2010). Cross-frequency coupling supports multi-item working memory in the human hippocampus. PNAC 107: 3228–3233.Google Scholar
Babiloni, C., Babiloni, F., Carducci, F., Cincotti, F., Cocozza, G., Del Percio, C., Moretti, D. V., & Rossini, P. M. (2002). Human cortical electroencephalography (EEG) rhythms during the observation of simple aimless movements: a high-resolution EEG study. NeuroImage 17: 559–572.Google Scholar
Backus, A. R., Schoffelen, J.-M., Szebényi, S., Hanslmayr, S., & Doeller, C. F. (2016). Hippocampal-prefrontal theta oscillations support memory integration. Current Biology 26(4): 450–457.Google Scholar
Baddeley, A., Eysenck, M. W., & Anderson, A. C. (2014). Memory. 2nd ed. Abingdon, Psychology Press.Google Scholar
Badin, A-S., Fermani, F., & Greenfield, S. A. (2017). The features and functions of neuronal assemblies: possible dependency on mechanisms beyond synaptic transmission. Frontiers in Neural Circuits 10: 114.Google Scholar
Badre, D. & Wagner, A. D. (2007). Left ventrolateral prefrontal cortex and the cognitive control of memory. Neuropsychologia 45(13): 2883–2901.Google Scholar
Baggio, G., Cherubini, P., Pischedda, D., Blumenthal, A., Haynes, J-D., & Reverberi, C. (2016). Multiple neural representations of elementary logical connectives. NeuroImage 135: 300–310.Google Scholar
Bahramisharif, A., Jensen, O., Jacobs, J., & Lisman, J. (2018). Serial representation of items during working memory maintenance at letter-selective cortical sites. PLoS Biology 16(8): e2003805.Google Scholar
Bahramisharif, A., Mazaheri, A., Levar, N., Schuurman, P. R., Figee, M., & Denys, D. (2016). Deep brain stimulation diminishes cross-frequency coupling in obsessive-compulsive disorder. Biological Psychiatry 80(7): e57–58.Google Scholar
Baillet, S. (2017). Magnetoencephalography for brain electrophysiology and imaging. Nature Neuroscience 20: 327–333.Google Scholar
Bakker, I., MacGregor, L. J., Pulvermüller, F., & Shtyrov, Y. (2013). Past tense in the brain’s time: neurophysiological evidence for dual-route processing of past-tense verbs. NeuroImage 71: 187–195.Google Scholar
Balaban, H. & Luria, R. (2016). Object representations in visual working memory change according to the task context. Cortex 81: 1–13.Google Scholar
Balari, S. & Lorenzo, G. (2013). Computational Phenotypes: Towards an Evolutionary Developmental Biolinguistics. Oxford: Oxford University Press.Google Scholar
Balari, S., Boeckx, C., & Lorenzo, G. (2012). On the feasibility of biolinguistics: Koster’s word-based challenge and our ‘natural computation’ alternative. Biolinguistics 6(2): 205–21.Google Scholar
Balezeau, F., Wilson, B., Gallardo, G., Dick, F., Hopkins, W., Anwander, A., Friederici, A. D., Griffiths, T. D., & Petkov, C. I. (2020). Primate auditory prototype in the evolution of the arcuate fasciculus. Nature Neuroscience 23: 611–614.Google Scholar
Bartolo, R., Prado, L., & Merchant, H. (2014). Information processing in the primate basal ganglia during sensory-guided and internally driven rhythmic tapping. Journal of Neuroscience 34: 3910–3923.Google Scholar
Bartolo, R. & Merchant, H. (2015). β oscillations are linked to the initiation of sensory-cued movement sequences and the internal guidance of regular tapping in the monkey. The Journal of Neuroscience 35(11): 4635–4640.Google Scholar
Bartos, M., Vida, I., & Jonas, P. (2007). Synaptic mechanisms of synchronized gamma oscillations in inhibitory interneuron networks. Nature Reviews Neuroscience 8: 45–56.Google Scholar
Başar, E. (2006). The theory of the whole-brain-network. International Journal of Psychophysiology 60: 133–138.Google Scholar
Başar, E. & Stampfer, H. G. (1985). Important associations among EEG-dynamics, event related potentials, short-term memory and learning. International Journal of Neuroscience 26: 161–180.Google Scholar
Bassett, D. S. & Sporns, O. (2017). Network neuroscience. Nature Neuroscience 20(3): 353–364.Google Scholar
Bastiaanse, R. & Thompson, C. K. (eds.) (2012). Perspectives on Agrammatism. London: Psychology Press.Google Scholar
Bastiaansen, M. & Hagoort, P. (2015). Frequency-based segregation of syntactic and semantic unification during online sentence level language comprehension. Journal of Cognitive Neuroscience 27(11): 2095–2107.Google Scholar
Bastiaansen, M., Van Berkum, J. J., & Hagoort, P. (2002). Event-related theta power increases in the human EEG during online sentence processing. Neuroscience Letters 323: 13–16.Google Scholar
Bastiaansen, M. C. M., Magyari, L., & Hagoort, P. (2010). Syntactic unification operations are reflected in oscillatory dynamics during on-line sentence comprehension. Journal of Cognitive Neuroscience 22: 1333–1347.Google Scholar
Bastiaansen, M. C. M., van der Linden, Marieke., ter Keurs, M., Dijkstra, T., & Hagoort, P. (2005). Theta responses are involved in lexical-semantic retrieval during language processing. Journal of Cognitive Neuroscience 17(3): 530–541.Google Scholar
Bastos, A. M., Martin Usrey, W., Adams, R. A., Mangun, G. R., Fries, P., Friston, K. J. (2012). Canonical microcircuits for predictive coding. Neuron 76: 695–711.Google Scholar
Bastos, A. M., Vezoli, J., & Fries, P. (2015). Communication through coherence with inter-areal delays. Current Opinion in Neurobiology 31: 173–180.Google Scholar
Bates, E. (1999). Plasticity, localization and language development. Broman, S.H., & Fletcher, J.M. (Eds.). The Changing Nervous System: Neurobehavioral Consequences of Early Brain Disorders. Oxford: Oxford University Press. 214–253.Google Scholar
Bates, E., Benigni, L., Bretherton, I., Camaioni, L., & Volterra, V. (1979). The Emergence of Symbols: Cognition and Communication in Infancy. New York: Academic Press.Google Scholar
Bauer, A.-K. R., Bleichner, M. G., Jaeger, M., Thorne, J. D., & Debener, S. (2018). Dynamic phase alignment of ongoing auditory cortex oscillations. NeuroImage 167: 396–407.Google Scholar
Bays, P. M. (2015). Spikes not slots: noise in neural populations limits working memory. Trends in Cognitive Sciences 19: 431–438.Google Scholar
Bechtel, W. (1994). Levels of description and explanation in cognitive science. Minds and Machines 4: 1–25.Google Scholar
Beese, C., Meyer, L., Vassileiou, B., Friederici, A. D. (2017). Temporally and spatially distinct theta oscillations dissociate a language-specific from a domain-general processing mechanism across the age trajectory. Scientific Reports 7(1): 11202.Google Scholar
Bell, P. T. & Shine, J. M. (2016). Subcortical contributions to large-scale network communication. Neuroscience and Biobehavioral Reviews 71: 313–322.Google Scholar
Bellmund, J. L. S., Gärdenfors, P., Moser, E. I., & Doeller, C. F. (2018). Navigating cognition: spatial codes for human thinking. Science 362: eaat6766.Google Scholar
Belluscio, M. A., Mizuseki, K., Schmidt, R., Kempter, R., & Buzsáki, G. (2012). Cross-frequency phase-phase coupling between θ and γ oscillations in the hippocampus. Journal of Neuroscience 32: 423–435.Google Scholar
Bemis, D. K. & Pylkkänen, L. (2013). Basic linguistic composition recruits the left anterior temporal lobe and left angular gyrus during both listening and reading. Cerebral Cortex 23: 1859–1873.Google Scholar
Benítez-Burraco, A. & Boeckx, C. (2015). Possible functional links among brain- and skull-related genes selected in modern humans. Frontiers in Psychology 6: 794. DOI:10.3389/fpsyg.2015.00794Google Scholar
Benítez-Burraco, A., Mineiro, A., & Castro-Caldas, A. (2014). The emergence of modern communication in primates: a computational approach. In Pina, M., & Gontier, N. (eds.). The Evolution of Social Communication in Primates: A Multidisciplinary Approach. Cham: Springer. 289–311.Google Scholar
Benítez-Burraco, A. & Murphy, E. (2016). The oscillopathic nature of language deficits in autism: from genes to language evolution. Frontiers in Human Neuroscience 10: 120.Google Scholar
Benítez-Burraco, A., & Murphy, E. (2019). Why brain oscillations are improving our understanding of language. Frontiers in Behavioral Neuroscience 13: 190.CrossRefGoogle ScholarPubMed
Benson-Amram, S., Dantzer, B., Stricker, G., Swanson, E. M., & Holekamp, K. E. (2015). Brain size predicts problem-solving ability in mammalian carnivores. PNAS 113(9): 2532–2537.Google Scholar
Berger, H. (1929). Uber das elektrenephalogramm des menschen. Archiv für Psychiatrie und Nervenkrankheiten 87: 527–570.Google Scholar
Berger, J. I., Gander, P. E., Kumar, S., Banks, M. I., Nourski, K. V., Oya, H., Kawasaki, H., Howard III, M. A., & Griffiths, T. D. (2019). Oscillatory correlates of auditory working memory in human intracranial EEG. Poster presented at the 49th Meeting of the Society for Neuroscience, Chicago, 19–23 October.Google Scholar
Bergmann, T. O. & Born, J. (2017). Phase-amplitude coupling: a general mechanism for memory processing and synaptic plasticity? Neuron 97: 10–13.Google Scholar
Bergson, H. (1911). Creative Evolution. London: H. Holt.Google Scholar
Berkeley, G. (1992). “The Analyst”. 1734. Reprinted in Jesseph, D. M. “De Motu and The Analyst: A Modern Edition, with Introductions and Commentary”. London: Kluwer Academic Publishers Dordrecht.Google Scholar
Bertossa, R. (2011). Morphology and behaviour: functional links in development and evolution. Philosophical Transactions of the Royal Society B 366: 2056–68.Google Scholar
Berwick, R. C. (2017). A feeling for the phenotype. In McGilvray, J. (ed.). The Cambridge Companion to Chomsky. 2nd ed. Cambridge: Cambridge University Press. 87–109.Google Scholar
Berwick, R. C. & Chomsky, N. (2016). Why Only Us: Language and Evolution. Cambridge, MA: MIT Press.Google Scholar
Beukema, P. & Verstynen, T. (2018). Predicting and binding: interacting algorithms supporting the consolidation of sequential motor skills. Current Opinion in Behavioral Sciences 20: 98–103.Google Scholar
Bhattasali, S., Hale, J., Pallier, C., Brennan, J. R., Luh, W-M., & Spreng, R. N. (2018). Differentiating phrase structure parsing and memory retrieval in the brain. Proceedings of the Society for Computation in Linguistics (SCiL) 2018 74–80.Google Scholar
Bianchi, S., Stimpson, C. D., Duka, T., Larsen, M. D., Janssen, W. G., Collins, Z., Bauernfeind, A. L., Schapiro, S. J., Baze, W. B., McArthur, M. J., Hopkins, W. D., Wildman, D. E., Lipovich, L., Kazuwa, C. W., Jacobs, B., Hof, P. R., & Sherwood, C. C. (2013). Synaptogenesis and development of pyramidal neuron dendritic morphology in the chimpanzee neocortex resembles humans. PNAS 110(Supplement 2): 10395–10401.Google Scholar
Biasiucci, A., Franceschiello, B., & Murray, M. M. (2019). Electroencephalography. Current Biology 29: R80-R85.Google Scholar
Bichakjian, B. H. (2017). Language evolution: how language was built and made to evolve. Language Sciences 63: 119–129.Google Scholar
Billeke, P., Ossandon, T., Stockle, M., Perrone-Bertolotti, M., Kahane, P., Lachaux, J.-P., & Fuentealba, P. (2017). Brain state-dependent recruitment of high-frequency oscillations in the human hippocampus. Cortex 94: 87–99.Google Scholar
Binder, J. R. & Desai, R. H. (2011). The neurobiology of semantic memory. Trends in Cognitive Sciences 15: 527–536.Google Scholar
Binder, J. R., Desai, R. H., Graves, W. W., & Conant, L. L. (2009). Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cerebral Cortex 19: 2767–2796.Google Scholar
Binney, R. J., Embleton, K. V., Jefferies, E., Parker, G. J., & Ralph, M. A., (2010). The ventral and inferolateral aspects of the anterior temporal lobe are crucial in semantic memory: evidence from a novel direct comparison of distortion-corrected fMRI, rTMS, and semantic dementia. Cerebral Cortex 20: 2728–2738.Google Scholar
Bitar, M. & Barry, G. (2018). Multiple innovations in genetic and epigenetic mechanisms cooperate to underpin human brain evolution. Molecular Biology and Evolution 35(2): 263–268.Google Scholar
Blank, I., Duff, M. C., Brown-Schmidt, S., & Fedorenko, E. (2016a). Expanding the language network: domain-specific hippocampal recruitment during high-level linguistic processing. bioRxiv. https://doi.org/10.1101/091900Google Scholar
Blank, I., Balewski, Z., Mahowald, K., & Fedorenko, E. (2016b). Syntactic processing is distributed across the language system. NeuroImage 127: 307–323.Google Scholar
Bloom, H. (1997). The Anxiety of Influence: A Theory of Poetry. 2nd ed. Oxford: Oxford University Press.Google Scholar
Blümel, A. (2017). Exocentric root declaratives: evidence from V2. In Bauke, L. & Blümel, A. (eds.). Labels and Roots. Berlin: Walter de Gruyter. 263–289.Google Scholar
Boeckx, C. (2011). Approaching paramaters from below. In Di Sciullo, A. M. & Boeckx, C. (eds.). The Biolinguistic Enterprise: New Perspectives on the Evolution and Nature of the Human Language Faculty. Oxford: Oxford University Press. 205–221.Google Scholar
Boeckx, C. (2013). Merge: biolinguistic considerations. English Linguistics 30(2): 463–484.Google Scholar
Boeckx, C. (2014a). Elementary Syntactic Structures: Prospects of a Feature-Free Syntax. Cambridge: Cambridge University Press.Google Scholar
Boeckx, C. (2014b). Our brain’s language-readiness. El País. 7 February.Google Scholar
Boeckx, C. (2017). A conjecture about the neural basis of recursion in light of descent with modification. Journal of Neurolinguistics 43(B): 193–198.Google Scholar
Boeckx, C. & Benítez -Burraco, A. (2014a). The shape of the human language-ready brain. Frontiers in Psychology 5: 282.Google Scholar
Boeckx, C. & Benítez-Burraco, A. (2014b). Globularity and language-readiness: generating new predictions by expanding the set of genes of interest. Frontiers in Psychology 5: 1324.Google Scholar
Boeckx, C. & Fujita, K. (2014). Syntax, actions, comparative cognitive science, and Darwinian thinking. Frontiers in Psychology 5: 627.Google Scholar
Boeckx, C. & Grohmann, K. K. (2007). The Biolinguistics manifesto. Biolinguistics 1: 1–8.Google Scholar
Boeckx, C. & Theofanopoulou, C. (2015). Cognitive phylogenies, the Darwinian logic of descent, and the inadequacy of cladistic thinking. Frontiers in Cell and Developmental Biology 3: 64.Google Scholar
Bohsali, A. A., Triplett, W., Sudhyadhom, A., Gullett, J. M., McGregor, K., FitzGerald, D. B., Mareci, T., White, K., & Crosson, B. (2015). Broca’s area – thalamic connectivity. Brain and Language 141: 80–88.Google Scholar
Bolhuis, J. & Wynne, C. D. L. (2009). Can evolution explain how minds work? Nature 458(7240): 832–833.Google Scholar
Bolhuis, J. J., Beckers, G. J. L., Huybregts, M. A. C., Berwick, R. C., & Everaert, M. B. H. (2018) Meaningful syntactic structure in songbird vocalizations? PLoS Biology 16(6): e2005157.Google Scholar
Bolhuis, J. J. & Gahr, M. (2006). Neural mechanisms of birdsong memory. Nature Reviews Neuroscience 7: 347–357.Google Scholar
Bolhuis, J. J. Tattersall, I., Chomsky, N., & Berwick, R. C. (2014). How could language have evolved? PLoS ONE 12: e1001934.Google Scholar
Bolker, J. A. (2008). Developing a history of evo‐devo. BioScience 58: 461–463.Google Scholar
Bonhage, C. E., Meyer, L., Gruber, T., Friederici, A. D., & Mueller, J. L. (2017). Oscillatory EEG dynamics underlying automatic chunking during sentence processing. NeuroImage 152: 647–657.Google Scholar
Bornkessel, I., Zysset, S., Friederici, A. D., von Cramon, D., & Schlesewsky, M. (2005). Who did what to whom? The neural basis of argument hierarchies during language comprehension. NeuroImage 26(1): 221–233.Google Scholar
Bornkessel-Schlesewsky, I., Schlesewsky, M., & Small, S. L. (2014). Implementation is crucial but must be neurobiologically grounded. Comment on ‘Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition’ by W. Tecumseh Fitch. Physics of Life Reviews 11: 365–366.Google Scholar
Bosman, C. A., Lansink, C. S., & Pennartz, C. M. A. (2014). Functions of gamma-band synchronization in cognition: from single circuits to functional diversity across cortical and subcortical systems. European Journal of Neuroscience 39: 1982–1999.Google Scholar
Bosman, C. A., Womelsdorf, T., Desimone, R., & Fries, P. (2009). A microsaccadic rhythm modulates gamma-band synchronization and behavior. Journal of Neuroscience 29: 9471–9480.Google Scholar
Bota, M., Sporns, O., & Swanson, LW. (2015). Architecture of the cerebral cortical association connectome underlying cognition. PNAS 112: E2093-101.Google Scholar
Bouchard, K .E. & Chang, E. F. (2014). Neural decoding of spoken vowels from human sensory-motor cortex with high-density electrocorticography. Conf Proc IEEE Eng Med Biol Soc 6782–6785.Google Scholar
Boucher, V. J., Gilbert, A. C., & Jemel, B. (2019). The role of low-frequency neural oscillations in speech processing: revisiting delta entrainment. Journal of Cognitive Neuroscience 31(8): 1205–1215.Google Scholar
Bradley, C. R., Siskind, J. M., & Wilbur, R. B. (2017). Neural representation of minimal syntactic units. Annual Conference on Cognitive Computational Neuroscience (CCN), New York. 6–8 September.Google Scholar
Bradshaw, A. R., Thompson, P. A., Wilson, A. C., Bishop, D. V. M., & Woodhead, Z. V. J. (2017). Measuring language lateralisation with different language tasks: a systematic review. PeerJ 5: e3929.Google Scholar
Bragin, A., Jando, G., Nadasdy, Z., Hetke, J., Wise, K., & Buzsáki, G. (1995). Gamma (40–100 Hz) oscillation in the hippocampus of the behaving rat. Journal of Neuroscience 15: 47–60.Google Scholar
Brandon, M. P., Koenig, J., Leutgeb, J. K., & Leutgeb, S. (2014). New and distinct hippocampal place codes are generated in a new environment during septal inactivation. Neuron 82: 789–796.Google Scholar
Brennan, J. R. & Martin, A. E. (2019). Delta-gamma phase-locking indexes composition of predicates. Poster presented at 23rd Annual Meeting of the Cognitive Neuroscience Society, San Fransisco, 23–26 March.Google Scholar
Brennan, J. R. & Pylkkänen, L. (2017). MEG evidence for incremental sentence composition in the anterior temporal lobe. Cognitive Science 41(S6): 1515–1531.Google Scholar
Brennan, J. R., Stabler, E. P., Van Wagenen, S. E., Luh, W.-M., & Hale, J. T. (2016). Abstract linguistic structure correlates with temporal activity during naturalistic comprehension. Brain & Language 157–158: 81–94.Google Scholar
Bressler, S. L. & Menon, V. (2010). Large-scale brain networks in cognition: emerging methods and principles. Trends in Cognitive Sciences 14: 277–290.Google Scholar
Bressler, S. L. & Richter, C. G. (2015). Interareal oscillatory synchronization in top-down neocortical processing. Current Opinion in Neurobiology 31: 62–66.Google Scholar
Brilmayer, I., Sassenhagen, J., Bornkessel-Schlesewsky, I., & Schlesewsky, M. (2017). Domain-general neural correlates of dependency formation: using complex tones to simulate language. Cortex 93: 50–67.Google Scholar
Brincat, S. L. & Miller, E. K. (2015). Frequency-specific hippocampal-prefrontal interactions during associative learning. Nature Neuroscience 18(4): 576–581.Google Scholar
Brodbeck, C., Gwilliams, L., & Pylkkänen, L. (2016). Language in context: MEG evidence for modality-general and -specific responses to reference resolution. eNeuro 3(6): e0145–16.2016.Google Scholar
Brookes, M. J., Groom, M. J., Liuzzi, L., Hill, R. M., Smith, H. J. F., Briley, P. M., Hall, E. L., Hunt, B. A. E. et al. (2018). Altered temporal stability in dynamic neural networks underlies connectivity changes in neurodevelopment. NeuroImage 174: 563–575.Google Scholar
Brookes, M. J., Liddle, E. B., Hale, J. R., Woolrich, M. W., Luckhoo, H., Liddle, P. F., & Morris, P. G. (2012). Task induced modulation of neural oscillations in electrophysiological brain networks. NeuroImage 63: 1918–1930.Google Scholar
Brookshire, G., Lu, J., Nusbaum, H. C., Goldin-Meadow, S., & Casasanto, D. (2017). Visual cortex entrains to sign language. PNAS 114(24): 6352–6357.CrossRefGoogle ScholarPubMed
Brown, J. W. (2014). The tale of the neuroscientists and the computer: why mechanistic theory matters. Frontiers in Neuroscience 8: 349.Google Scholar
Bruner, E. (2004). Geometric morphometrics and paleoneurology: brain shape evolution in the genus homo. Journal of Human Evolution 47(5): 279–303.Google Scholar
Bruner, E. & Gleeson, B. T. (2019). Body cognition and self-domestication in human evolution. Frontiers in Psychology 10: 1111.Google Scholar
Bruner, E., Preuss, T. M., Chen, X., & Rilling, J. K. (2017). Evidence for expansion of the precuneus in human evolution. Brain Structure and Function 222(2):1053–1060.Google Scholar
Brunetti, E., Maldonado, P. E., & Aboitiz, F. (2013). Phase synchronization of delta and theta oscillations increase during the detection of relevant lexical information. Frontiers in Psychology 4: 308.Google Scholar
Bryant, K. L. & Preuss, T. M. (2018). A comparative perspective on the human temporal lobe. In Bruner, E., Ogihara, N., & Tanabe, H. (eds.). Digital Endocasts: From Skulls to Brains. Replacement of Neanderthals by Modern Humans Series. Tokyo: Springer.Google Scholar
Buffalo, E. A., Fries, P., Landman, R., Buschman, T. J., & Desimone, R. (2011). Laminar differences in gamma and alpha coherence in the ventral stream. PNAS 108: 11262–11267.Google Scholar
Buffat, S., Plantier, J., Roumes, C., & Lorenceau, J. (2013). Repetition blindness for natural images of objects with viewpoint changes. Frontiers in Psychology 3: 622.Google Scholar
Bufill, E. & Carbonell, E. (2004). Are symbolic behavior and neuroplasticity an example of gene-culture evolution? Revista de Neurologia 39: 48–55.Google Scholar
Bulut, T., Hung, Y. H., Tzeng, O., & Wu, D. H. (2017). Neural correlates of processing sentences and compound words in Chinese. PLoS ONE 12(12): e0188526.Google Scholar
Burgaleta, M., Sanjuán, A., Ventura-Campos, N., Sebastian-Galles, N., & Ávila, C. (2016). Bilingualism at the core of the brain. Structural differences between bilinguals and monolinguals revealed by subcortical shape analysis. NeuroImage 125: 437–445.Google Scholar
Burgess, N. & Hitch, G. J. (1992). Towards a network model of the articulatory loop. Journal of Memory and Language 31(4): 429–460.Google Scholar
Büring, D. (2015). Unalternative semantics. Proceedings of SALT 25: 550–575.Google Scholar
Burkhardt, P. & Sprecher, S. G. (2017). Evolutionary origin of synapses and neurons – bridging the gap. Bioessays 39: 1700024.Google Scholar
Burnett, D. (2016). The Idiot Brain. London: Faber & Faber.Google Scholar
Buschman, T. J. & Miller, E. K. (2007). Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices. Science 315: 1860–1862.Google Scholar
Bush, D. & Burgess, N. (2019). Neural oscillations: phase coding in the absence of rhythmicity. Current Biology 29: R50–R70.Google Scholar
Buzsáki, G. (2006). Rhythms of the Brain. Oxford: Oxford University Press.Google Scholar
Buzsáki, G. (2010). Neural syntax: cell assemblies, synapsembles, and readers. Neuron 68: 362–385.Google Scholar
Buzsáki, G. & Draguhn, A. (2004). Neuronal oscillations in cortical networks. Science 304: 1926–1929.Google Scholar
Buzsáki, G. & Freeman, W. (2015). Editorial overview: brain rhythms and dynamic coordination. Current Opinion in Neurobiology 31: v–ix.Google Scholar
Buzsáki, G. & Llinás, R. (2017). Space and time in the brain. Science 358: 482–485.Google Scholar
Buzsáki, G. & Wang, W.-J. (2012). Mechanisms of gamma oscillations. Annual Review of Neuroscience 35: 203–225.Google Scholar
Buzsáki, G., Logothetis, N., & Singer, W. (2013). Scaling brain size, keeping timing: evolutionary preservation of brain rhythms. Neuron 80: 751–764.Google Scholar
Bybee, J. L. (2011). Domain-general processes as the basis for grammar. In Gibson, K. R. & Tallerman, M. (eds.). The Oxford Handbook of Language Evolution. Oxford: Oxford University Press. 528–536.Google Scholar
Byrne, R. W. & Russon, A. E. (1998). Learning by imitation: a hierarchical approach. Behavioral and Brain Sciences 21: 667–721.Google Scholar
Cai, D. J., Aharoni, D., Shuman, T., Shobe, J., Biane, J., Song, W., Wei, B. et al. (2016). A shared neural ensemble links distinct memories encoded close in time. Nature 534: 115–118.Google Scholar
Calabrese, A. & Woolley, S. M. N. (2015). Coding principles of the canonical cortical microcircuit in the avian brain. PNAS 112(11): 3517–3522.Google Scholar
Campion, G. & Elliot-Smith, G. (1934). The Neural Basis of Thought. New York: Harcourt Brace Jovanovich.Google Scholar
Cannon, J., McCarthy, M. M., Lee, S., Lee, J., Börgers, C., Whittington, M. A., & Kopell, N. (2014). Neurosystems: brain rhythms and cognitive processing. European Journal of Neuroscience 39(5): 705–719.Google Scholar
Canolty, R. T. & Knight, R. T. (2010). The functional role of cross-frequency coupling. Trends in Cognitive Sciences 14: 506–515.Google Scholar
Canolty, R. T., Edwards, E., Dalal, S. S., Soltani, M., Nagarajan, S. S., Kirsch, H. E., Berger, M. S., Barbaro, N. M., & Knight, R. T. (2006). High gamma power is phase-locked to theta oscillations in human neocortex. Science 313: 1626–1628.Google Scholar
Canolty, R. T., Ganguly, K., Kennerley, S. W., Cadieu, C. F., Koepsell, K., Wallis, J. D., & Carmena, J. M. (2010). Oscillatory phase coupling coordinates anatomically dispersed functional cell assemblies. PNAS 107(40): 17356–17361.Google Scholar
Cao, H., Dixson, L., Meyer-Lindenberg, A., & Tost, H. (2016). Functional connectivity measures as schizophrenia intermediate phenotypes: advances, limitations, and future directions. Current Opinion in Neurobiology 36: 7–14.Google Scholar
Cardin, J. A., Palmer, L. A., & Contreras, D. (2005). Stimulus-dependent γ (30–50 Hz) oscillations in simple and complex fast rhythmic bursting cells in primary visual cortex. Journal of Neuroscience 25: 5339–5350.Google Scholar
Carracedo, L. M., Kjeldsen, H., Cunnington, L., Jenkins, A., Schofield, I., Cunningham, M. O. et al. (2013). A neocortical delta rhythm facilitates reciprocal interlaminar interactions via nested theta rhythms. Journal of Neuroscience 33: 10750–10761.Google Scholar
Carroll, S. B. (2006). The Making of the Fittest: DNA and the Ultimate Forensic Record of Evolution. New York: W.W. Norton.Google Scholar
Carstairs-McCarthy, A. (2010). The Evolution of Morphology. Oxford: Oxford University Press.Google Scholar
Castejon, C. & Nuñez, A. (2016). Cortical neural computation by discrete results hypothesis. Frontiers in Neural Circuits 10: 81.Google Scholar
Catani, M. & Bambini, V. (2014). Amodel for social communication and language evolution and development (SCALED). Current Opinion in Neurobiology 28: 165–171.Google Scholar
Catani, M., Mesulam, M. M., Jakobsen, E., Malik, F., Martersteck, A., Wieneke, C., Thompson, C. K., Thiebaut de Schotten, M., Dell’Acqua, F., Weintraub, S., & Rogalski, E. (2013). A novel frontal pathway underlies verbal fluency in primary progressive aphasia. Brain 136: 2619–2628.Google Scholar
Catchpole, C. K., & Slater, P. J. B. (2008). Bird Song: Biological Themes and Variations. Cambridge: Cambridge University Press.Google Scholar
Caton, R. (1875). The electric currents of the brain. British Medical Journal 2: 278.Google Scholar
Cecchetto, C. & Donati, C. (2015). (Re)labeling. Cambridge, MA: MIT Press.Google Scholar
Cervenka, M. C., Boatman-Reich, D. F., Ward, J., Franaszczuk, P. J., & Crone, N. E. (2011). Language mapping in multilingual patients: electrocorticography and cortical stimulation during naming. Frontiers in Human Neuroscience 5: 13.Google Scholar
Chacko, R. V., Kim, B., Woo Jung, S., Daitch, A. L., Roland, J. L., Metcalf, N. V., Corbetta, M., Shulman, G. L., & Leuthardt, E. C. (2018). Distinct phase-amplitude couplings distinguish cognitive processes in human attention. NeuroImage 175: 111–121.Google Scholar
Chaieb, L., Leszczynski, M., Axmacher, N., Höhne, M., Elger, C. E., & Fell, J. (2015). Theta-gamma phase-phase coupling during working memory maintenance in the human hippocampus. Cognitive Neuroscience 6: 149–157.Google Scholar
Chaitin, G. (1977). Algorithmic information theory. IBM Journal of Research and Development 21: 350–359.Google Scholar
Chang, A., Bosnyak, D. J., & Trainor, L. J. (2016). Unpredicted pitch modulates beta oscillatory power during rhythmic entrainment to a tone sequence. Frontiers in Psychology 7: 327.Google Scholar
Chang, Le. & Tsao, D. Y. (2017). The code for facial identity in the primate brain. Cell 169: 1013–1028.Google Scholar
Chao, Z. C., Takaura, K., Wang, L., Fujii, N., & Dehaene, S. (2018). Large-scale cortical networks for hierarchical prediction and prediction error in the primate brain. Neuron 100: 1252–1266.Google Scholar
Chapeton, J. I., Haque, R., Wittig, J. H. Jr., Inati, S. K., & Zaghloul, K. A. (2019). Large-scale communication in the human brain is rhythmically modulated through alpha coherence. Current Biology 29: 1–11.Google Scholar
Charvet, C. J., Hof, P. R., Raghanti, M. A., van der Kouwe, A. J., Sherwood, C. C., & Takahashi, E. (2016). Combining diffusion magnetic resonance tractography with stereology highlights increased cross-cortical integration in primates. Journal of Comparative Neurology 525(5): 1075–1093.Google Scholar
Chen, C. C., Kiebel, S. J., & Friston, K. J. (2008). Dynamic causal modelling of induced responses. NeuroImage 41(4): 1293–1312.Google Scholar
Chen, L., Junjie, W., Yongben, F., Kang, H., & Feng, L. (2019). Neural substrates of word category information as the basis of syntactic processing. Human Brain Mapping 40(2): 451–464.Google Scholar
Chen, L., Lambon Ralph, M. A., & Rogers, T. T. (2017). A unified model of human semantic knowledge and its disorders. Nature Human Behaviour 1: 39.Google Scholar
Cherniak, C. (1994). Philosophy and computational neuroanatomy. Philosophical Studies 73: 89–107.Google Scholar
Cherniak, C. (2010). Brain wiring optimization and non-genomic nativism. In Piattelli-Palmarini, M., Salaburu, P., & Uriagereka, J. (eds.). Of Minds and Language: A Dialogue with Noam Chomsky in the Basque Country. Oxford: Oxford University Press. 108–119.Google Scholar
Chiarello, C. (2003). Parallel systems for processing language: hemispheric complementarity in the normal brain. In Banich, M. T. & Mack, M. (eds.). Mind, Brain, and Language: Multidisciplinary Perspectives. Mahwah, NJ: Lawrence Erlbaum Associates. 229–47.Google Scholar
Chklovskii, D. B., Schikorski, T., & Stevens, C. F. (2002). Wiring optimization in cortical circuits. Neuron 34: 341–347.Google Scholar
Chomsky, N. (1956a). On the limits of finite-state description. Quarterly Progress Report 42: 65–65.Google Scholar
Chomsky, N. (1956b). Three models for the description of language. IRE Transactions on Information Theory 2: 113–124.Google Scholar
Chomsky, N. (1957). Syntactic Structures. The Hague: Mouton.Google Scholar
Chomsky, N. (1959). On certain formal properties of grammars. Information and Control 2: 137–167.Google Scholar
Chomsky, N. (1963). Formal properties of grammars. In Luce, R. D., Bush, R. R., & Galanter, E. (eds.). Handbook of Mathematical Psychology. Vol. 2. New York: Wiley. 323–418.Google Scholar
Chomsky, N. (1965). Aspects of the Theory of Syntax. Cambridge, MA: MIT Press.Google Scholar
Chomsky, N. (1968). Quine’s empirical assumptions. Synthese 19(1): 53–68.Google Scholar
Chomsky, N. (1995). The Minimalist Program. Cambridge, MA: MIT Press.Google Scholar
Chomsky, N. (1998). Comments: Galen Strawson, Mental Reality. Philosophy and Phenomenological Research 58(2): 437–441.Google Scholar
Chomsky, N. (2000). New Horizons in the Study of Language and Mind. Cambridge: Cambridge University Press.Google Scholar
Chomsky, N. (2001a). Derivation by phase. Kenstowicz, M. (ed.). Ken Hale: A Life in Language. Cambridge, MA: MIT Press. 1–52.Google Scholar
Chomsky, N. (2001b). Beyond explanatory adequacy. MIT Occasional Papers in Linguistics 20: 1–28.Google Scholar
Chomsky, N. (2005). Three factors in language design. Linguistic Inquiry 36(1): 1–22.Google Scholar
Chomsky, N. (2008). On phases. Freidin, R., Otero, C. P., & Zubizarreta, M. L. (eds.). Foundational Issues in Linguistic Theory: Essays in Honor of Jean-Roger Vergnaud. Cambridge, MA: MIT Press. 133–166.Google Scholar
Chomsky, N. (2010). Some simple evo devo theses: how true might they be for language? In Larson, R. K., Déprez, V., & Yamakido, H. (eds.). The Evolution of Human Language: Biolinguistic Perspectives. Cambridge: Cambridge University Press. 45–62.Google Scholar
Chomsky, N. (2012). The Science of Language: Interviews with James McGilvray. Cambridge: Cambridge University Press.Google Scholar
Chomsky, N. (2013). Problems of projection. Lingua 130: 33–49.Google Scholar
Chomsky, N. (2014). Minimal recursion: exploring the prospects. In Roeper, T. & Speas, M. (eds.). Studies in Theoretical Psycholinguistics 43. Recursion: Complexity in Cognition. London: Springer. 1–15.Google Scholar
Chomsky, N. (2015a). Problems of projection: extensions. Di Domenico, E., Hamann, C., & Matteini, S. (eds.). Structures, Strategies and Beyond: Studies in Honour of Adriana Belletti. Amsterdam: John Benjamins. 1–16.Google Scholar
Chomsky, N. (2015b). Some core contested concepts. Journal of Psycholinguistic Research 44(1): 91–104.Google Scholar
Chomsky, N. (2018a). Science, mind, and limits of understanding. In Gallego, Á. J. & Martin, R. (eds.). Language, Syntax, and the Natural Sciences. Cambridge: Cambridge University Press.Google Scholar
Chomsky, N. (2018b). Mentality beyond consciousness. Caruso, G. (ed.). Ted Honderich on Consciousness, Determinism, and Humanity. London: Palgrave Macmillan. 33–46.Google Scholar
Chomsky, N. (2019a). Puzzles about phases. Franco, L. & Belliuci, G. (eds.). Linguistics Variation: Structure and Interpretation – A Feschrift in Honour of M. Rita Manzini. Berlin: Mouton de Gruyter.Google Scholar
Chomsky, N. (2019b). Lecture at MIT. April 10. http://whamit.mit.edu/2019/05/06/noam-chomskys-lectures-now-onlineGoogle Scholar
Chomsky, N., Gallego, Á. J., & Ott, D. (2019). Generative grammar and the faculty of language: insights, questions, and challenges. In Gallego, Á. J. & Ott, D. (eds.). Generative Syntax: Questions, Crossroads, and Challenges. Special issue of Catalan Journal of Linguistics, 226–261.Google Scholar
Chow, B. Y., Han, X., Dobry, A. S., Qian, X., Chuong, A. S., Li, M., Henninger, M. A., Belfort, G. M., Lin, Y., Monahan, P. E., & Boyden, E. S. (2010). High-performance genetically targetable optical neural silencing by light-driven proton pumps. Nature 463: 98–102.Google Scholar
Christiansen, M. H. & Chater, N. (2016). Creating Language: Integrating Evolution, Acquisition, and Processing. Cambridge, MA: MIT Press.Google Scholar
Christiansen, M. H. & Chater, N. (2017). Towards an integrated science of language. Nature Human Behavior 1: 0163.Google Scholar
Chuderski, A. & Andrelczyk, K. (2015). From neural oscillations to complex cognition: simulating the effect of the theta-to-gamma cycle length ratio on analogical reasoning. Cognitive Psychology 76: 78–102.Google Scholar
Chuderski, A. (2016). Fluid intelligence and the cross-frequency coupling of neuronal oscillations. Spanish Journal of Psychology 19(e91): 1–13.Google Scholar
Cinque, G. (1999). Adverbs and Functional Heads: A Cross-Linguistic Perspective. Oxford: Oxford University Press.Google Scholar
Citko, B. (2011). Symmetry in Syntax: Merge, Move, and Labels. Cambridge: Cambridge University Press.Google Scholar
Clancy, K. J., Baisley, S. K., Albizu, A., Kartvelishvili, N., Ding, M., & Li, W. (2017). Transcranial alternating current stimulation induces long-term augmentation of neural connectivity and sustained anxiety reduction. bioRxiv. http://dx.doi.org/10.1101/204222Google Scholar
Clarke, A. (2015). Dynamic information processing states revealed through neurocognitive models of object semantics. Language, Cognition and Neuroscience 30(4): 409–419.Google Scholar
Clarke, A. & Tyler, L. K. (2015). Understanding what we see: how we derive meaning from vision. Trends in Cognitive Sciences 19(11): 677–687.Google Scholar
Clarke, E., Reichard, U. H., & Zuberbühler, K. (2006). The syntax and meaning of wild gibbon songs. PLoS ONE 1(1): e73.Google Scholar
Clay, Z., Archbold, J., & Zuberbühler, K. (2015). Functional flexibility in wild bonobo vocal behaviour. PeerJ 3: e1124.Google Scholar
Clos, M., Amunts, K., Laird, A. R., Fox, P. T., & Eickhoff, S. B. (2013). Tackling the multifunctional nature of Broca’s region meta-analytically: co-activation-based parcellation of area 44. NeuroImage 83: 174–188.Google Scholar
Clouter, A., Shapiro, K. L., & Hanslmayr, S. (2017). Theta phase synchronization is the glue that binds human associative memory. Current Biology 27: 1–6.Google Scholar
Clowry, Gavin J. (2014). Seeking clues in brain development to explain the extraordinary evolution of language in humans. Language Sciences 46: 220–231.Google Scholar
Cocchi, L., Sale, M. V., Lord, A., Zalesky, A., Breakspear, M., Mattingley, J. B. (2015). Dissociable effects of local inhibitory and excitatory theta-burst stimulation on large-scale brain dynamics. Journal of Neurophysiology 113: 3375–3385.Google Scholar
Coetzee, J., Monti, M., Iacoboni, M., Wu, A., & Johnson, M. (2019). Separability of logic and language: a TMS study. Brain Stimulation 12(2): 543.Google Scholar
Cole, S. R. & Voytek, B. (2017). Brain oscillations and the importance of waveform shape. Trends in Cognitive Sciences 21(2): 137–149.Google Scholar
Colgin, L. L. (2013). Mechanisms and functions of theta rhythms. Annual Review of Neuroscience 36: 295–312.Google Scholar
Collins, J. (2015a). Naturalism without metaphysics. In Fischer, E. & Collins, J. (eds.). Experimental Philosophy, Rationalism, and Naturalism. London: Routledge. 85–109.Google Scholar
Collins, J. (2015b). Review of the minimalist program: the nature and plausibility of Chomsky’s biolinguistics by Fahad Rashed Al-Mutairi. Language 91(3): 738–740.Google Scholar
Collins, J. (2020). Conjoining meanings without losing our heads. Mind & Language 35: 224–236.Google Scholar
Comrie, B. (1992). Before complexity. In Hawkins, J. A. & Gell-Mann, M. (eds.). The Evolution of Human Language. Proceedings of the Workshop on the Evolution of Human Languages, August 1989, Santa Fe, New Mexico. Santa Fe, NM: Addison‐Wesley Publishing Company. 193–211.Google Scholar
Constantinescu, A. O., O’Reilly, J. X., & Behrens, T. E. J. (2016). Organizing conceptual knowledge in humans with a gridlike code. Science 352(6292): 1464–1468.Google Scholar
Copernicus, N. (1952). On the Revolutions of the Heavenly Spheres. Hutchins, R. M. (ed.), Great Books of the Western World. Chicago: Encyclopaedia Britannica.Google Scholar
Corcoran, A. W., Alday, P. M., Schlesewsky, M., & Bornkessel-Schlesewsky, I. (2018a). Toward a reliable, automated method of individual alpha frequency (IAF) quantification. Psychophysiology 55(7):e13064.Google Scholar
Corcoran, A. W., Pezzulo, G., & Hohwy, J. (2018b). Commentary: respiration-entrained brain rhythms are global but often overlooked. Frontiers in Systems Neuroscience 12: 25.Google Scholar
Cornélio, A. M., de Bittencourt-Navarrete, R. E., de Bittencourt Brum, R., Queiroz, C. M., & Costa, M. R. (2016). Human brain expansion during evolution is independent of fire control and cooking. Frontiers in Neuroscience 10: 167.Google Scholar
Covington, N. V. & Duff, M. C. (2016). Expanding the language network: direct contributions from the hippocampus. Trends in Cognitive Sciences 20(12): 869–870.Google Scholar
Cowan, N. (2001). The magical number 4 in short-term memory: a reconsideration of mental storage capacity. Behavioral and Brain Sciences 24(1): 87–114.Google Scholar
Cowan, N., Blume, C. L., & Saults, J. S. (2013). Attention to attributes and objects in working memory. Journal of Experimental Psychology: Learning, Memory, and Cognition 39(3): 731–747.Google Scholar
Crandall, S. R., Cruikshank, S. J., & Connors, B. W. (2015). A cortico-thalamic switch: Controlling the thalamus with dynamic synapses. Neuron 86: 768–782.Google Scholar
Crick, F. & Koch, C. (1995). Why neuroscience may be able to explain consciousness. Scientific American 273: 84–85.Google Scholar
Cross, Z. R., Kohler, M. J., Schlesewsky, M., Gaskell, M. G., & Bornkessel-Schlesewsky, I. (2018). Sleep-dependent memory consolidation and incremental sentence comprehension: computational dependencies during language learning as revealed by neuronal oscillations. Frontiers in Human Neuroscience 12: 18.Google Scholar
Cruikshank, S. J., Ahmed, O. J., Stevens, T. R., Patrick, S. L., Gonzalez, A. N., Elmaleh, M., & Connors, B. W. (2012). Thalamic control of layer 1 circuits in prefrontal cortex. Journal of Neuroscience 32(49): 17813–17823.Google Scholar
Crunelli, V., David, F., Lőrincz, M. L., & Hughes, S. W. (2015). The thalamocortical network as a single slow wave-generating unit. Current Opinion in Neurobiology 31: 72–80.Google Scholar
Cynx, J. (1990). Experimental determination of a unit of song production in the zebra finch (Taeniopygia guttata). Journal of Comparative Psychology 104: 3–10.Google Scholar
Daffertshofer, A., Ton, R., Kringelbach, M. L., Woolrich, M., & Deco, G. (2018). Distinct criticality of phase and amplitude dynamics in the resting brain. NeuroImage 180(B): 442–447.Google Scholar
Darwin, C. (1871). The Descent of Man and Selection in Relation to Sex. London: John Murray.Google Scholar
Davey, J., Thompson, H. E., Hallam, G., Karapanagiotidis, T., Murphy, C., De Caso, I., & Jefferies, E. (2016). Exploring the role of the posterior middle temporal gyrus in semantic cognition: integration of anterior temporal lobe with executive processes. NeuroImage 137: 165–177.Google Scholar
David, O., Maess, B., Eckstein, K., & Friederici, A. D. (2011). Dynamic causal modeling of subcortical connectivity of language. Journal of Neuroscience 31: 2712–2717.Google Scholar
Davidson, D. J. & Indefrey, P. (2007). An inverse relation between event-related and time frequency violation responses in sentence processing. Brain Research 1158: 81–92.Google Scholar
Davis, H. (2010). A unified analysis of relative clauses in St’at’imcets. North-West Journal of Linguistics 4: 1–43.Google Scholar
Dawkins, R. (1976). Hierarchical organization: a candidate principle for ethology. In Bateson, P. P. G. & Hinde, R. A. (eds.). Growing Points in Ethology. Cambridge: Cambridge University Press. 7–54.Google Scholar
Dawkins, R. (2006). Climbing Mount Improbable. Oxford: Oxford University Press.Google Scholar
Dawkins, R. (2015). A Brief Candle in the Dark: My Life in Science. New York: Harper Collins.Google Scholar
Dayan, P. & Abbott, L. F. (2001). Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. Cambridge, MA: MIT Press.Google Scholar
De Diego-Balaguer, R., Martinez-Alvarez, A., & Pons, F. (2016). Temporal attention as a scaffold for language development. Frontiers in Psychology 7: 44.Google Scholar
De Heer, W. A., Huth, A. G., Griffiths, T. L., Gallant, J. L., & Theunissen, F. E. (2017). The hierarchical cortical organization of human speech processing. Journal of Neuroscience 37(27): 6539–6557.Google Scholar
De Lange, S. C., van den Heuvel, M. P., & de Reus, M. A. (2016). The role of symmetry in neural networks and their Laplacian spectra. NeuroImage 141: 357–365.Google Scholar
De Pasquale, F., Della Penna, S., Snyder, A. Z., Marzetti, L., Pizzella, V., Luca Romani, G., & Corbetta, M. (2012). A cortical core for dynamic integration of functional networks in the resting human brain. Neuron 74: 753–764.Google Scholar
Dean, H. L., Hagan, M. A., & Pesaran, B. (2012). Only coherent spiking in posterior parietal cortex coordinates looking and reaching. Neuron 73(4): 829–841.Google Scholar
Deco, G., Cabral, J., Woolrich, M. W., Stevner, A. B. A., van Hartevelt, T. J., & Kringelbach, M. L. (2017). Single or multi-frequency generators in on-going brain activity: a mechanistic whole-brain model of empirical MEG data. NeuroImage 152: 538–550.Google Scholar
Deco, G., van Hartevelt, T. J., Fernandes, H. M., Stevner, A., & Kringelbach, M. L. (2017). The most relevant human brain regions for functional connectivity: evidence for a dynamical workspace of binding nodes from whole-brain computational modelling. NeuroImage 146: 197–210.Google Scholar
Dehaene, S. & Cohen, L. (2007). Cultural recycling of cortical maps. Neuron 56: 384–398.Google Scholar
Dehaene, S., Charles, L., King, J-R., & Marti, S. (2014). Toward a computational theory of conscious processing. Current Opinion in Neurobiology 25: 76–84.Google Scholar
Dehaene-Lambertz, G. (2017). The human infant brain: a neural architecture able to learn language. Psychonomic Bulletin & Review 24: 48.Google Scholar
Dehaene-Lambertz, G. & Spelke, E. S. (2015). The infancy of the human brain. Neuron 88: 93–109.Google Scholar
Deisz, R. A. & Prince, D. A. (1989). Frequency-dependent depression of inhibition in guinea-pig neocortex in vitro by GABAB receptor feed-back on GABA release. Journal of Physiology 412: 513–541.Google Scholar
Dejean, C., Arbuthnott, G., Wickens, J. R., Le Moine, C., Boraud, T. & Hyland, B. I. (2011). Power fluctuations in beta and gamma frequencies in rat globus pallidus: association with specific phases of slow oscillations and differential modulation by dopamine D1 and D2 receptors. Journal of Neuroscience 31: 6098–6107.Google Scholar
Dennett, D. (1987). The Intentional Stance. Cambridge, MA: MIT Press.Google Scholar
Dennett, D. (1995). Darwin’s Dangerous Idea: Evolution and the Meaning of Life. New York: Simon & Schuster.Google Scholar
Dennett, D. (2018). From Bacteria to Bach and Back: The Evolution of Minds. London: Penguin Books.Google Scholar
Deutscher, G. (2005). The Unfolding of Language: The Evolution of Mankind’s Greatest Invention. London: Arrow Books.Google Scholar
Di Liberto, G. M., Lalor, E. C., & Millman, R. E. (2018). Causal cortical dynamics of a predictive enhancement of speech intelligibility. NeuroImage 166: 247–258.Google Scholar
Di Sciullo, A. M., Nicolis, M., & Somesfalean, S. (2013). Evo-devo language universals. Paper presented at the International Linguists Conference 19, University of Geneva.Google Scholar
Diaz, M. T. & McCarthy, G. (2009). A comparison of brain activity evoked by single content and function words: an fMRI investigation of implicit word processing. Brain Research 1282: 38–49.Google Scholar
Ding, N. & Simon, J. Z. (2013). Adaptive temporal encoding leads to a background insensitive cortical representation of speech. Journal of Neuroscience 33(13): 5728–5735.Google Scholar
Ding, N. & Simon, J. Z. (2014). Cortical entrainment to continuous speech: functional roles and interpretations. Frontiers in Human Neuroscience 8: 311.Google Scholar
Ding, N., Melloni, L., Zhang, H., Tian, X., & Poeppel, D. (2016). Cortical tracking of hierarchical linguistic structures in connected speech. Natural Neuroscience 19: 158–164.Google Scholar
Ding, N., Melloni, L., Yang, A., Wang, Y., Zhang, W., & Poeppel, D. (2017). Characterizing neural entrainment to hierarchical linguistic units using electroencephalography (EEG). Frontiers in Human Neuroscience 11: 481.Google Scholar
Dipoppa, M. & Gutkin, B. S. (2013). Flexible frequency control of cortical oscillations enables computations required for working memory. PNAS 110(31): 12828–12833.Google Scholar
Dipoppa, M., Szwed, M., & Gutkin, B. S. (2016). Controlling working memory operations by selective gating: the roles of oscillations and synchrony. Advances in Cognitive Psychology 12(4): 209–232.Google Scholar
Dobson, C. W. & Lemon, R. E. (1979). Markov sequences in songs of American thrushes. Behaviour 68: 86–105.Google Scholar
Doelling, K. B. & Poeppel, D. (2015) Cortical entrainment to music and its modulation by expertise. PNAS 112(45),E6233–6242.Google Scholar
Doesburg, S. M., Vinette, S. A., Cheung, M. J., & Pang, E. W. (2012). Theta-modulated gamma-band synchronization among activated regions during a verb generation task. Frontiers in Psychology 3: 195.Google Scholar
Dor, D. (2017). The role of the lie in the evolution of human language. Language Sciences 63: 44–59.Google Scholar
Doumas, L. A. A., Hummel, J. E., & Sandhofer, C. M. (2008). A theory of the discovery and predication of relational concepts. Psychological Review 115: 1–43.Google Scholar
Dragoi, G. & Tonegawa, S. (2013). Selection of preconfigured cell assemblies for representation of novel spatial experiences. Philosophical Transactions of the Royal Society B 369(1635): 20120522.Google Scholar
Dubbledam, J. L. & den Boer-Visser, A. M. (2002). The central mesencephalic grey in birds: nucleus intercollicularis and substantia grisea centralis. Brain Research Bulletin 57: 349–352.Google Scholar
Dubois, J., de Berker, A. O., & Tsao, D. Y. (2015). Single-unit recordings in the macaque face patch system reveal limitations of fMRI MVPA. Journal of Neuroscience 35(6): 2791–2802.Google Scholar
Duff, M. C. & Brown-Schmidt, S. (2012). The hippocampus and the flexible use and processing of language. Frontiers in Human Neuroscience 6: 69.Google Scholar
Duffy, J. R. (2005). Motor Speech Disorders: Substrates, Differential Diagnosis, and Management. 2nd ed. St. Louis, MO: Elsevier Mosby.Google Scholar
Duncan, J. (2013). The structure of cognition: attentional episodes in mind and brain. Neuron 80: 35–50.Google Scholar
Edelman, G. M. (1989). The Remembered Present: A Biological Theory of Consciousness. New York: Basic Books.Google Scholar
Egidi, G. & Caramazza, A. (2014). Mood-dependent integration in discourse comprehension: happy and sad moods affect consistency processing via different brain networks. NeuroImage 103: 20–32.Google Scholar
Eklund, A., Nichols, T. E., & Knutsson, H. (2016). Cluster failure: why fMRI inferences for spatial extent have inflated false-positive rates. PNAS 113: 7900–7905.Google Scholar
Eliav, T., Geva-Sagiv, M., Yartsev, M. M., Finkelstein, A., Rubin, A., Las, L., & Ulanovsky, N. (2018). Nonoscillatory phase coding and synchronization in the bat hippocampal formation. Cell 175: 1–12.Google Scholar
Ellamil, M., Fox, K. C., Dixon, M. L., Pritchard, S., Todd, R. M., Thompson, E., & Christoff, K. (2016). Dynamics of neural recruitment surrounding the spontaneous arising of thoughts in experienced mindfulness practitioners. NeuroImage 136: 186–196.Google Scholar
Elmer, S. & Kühnis, J. (2016). Functional connectivity in the left dorsal stream facilitates simultaneous language translation: an EEG study. Frontiers in Human Neuroscience 10: 60.Google Scholar
Embick, D. & Poeppel, D. (2015). Towards a computational(ist) neurobiology of language: correlational, integrated and explanatory neurolinguistics. Language, Cognition and Neuroscience 30(4): 357–366.Google Scholar
Enel, P., Procyk, E., Quilodran, R., & Dominey, P. F. (2016). Reservoir computing properties of neural dynamics in prefrontal cortex. PLoS Computational Biology 12 (6): e1004967.Google Scholar
Engel, A. K. & Fries, P. (2010). Beta-band oscillations – signalling the status quo? Current Opinion in Neurobiology 20(2): 156–165.Google Scholar
Epstein, R. A., Patai, E. Z., Julian, J. B., & Spiers, H. J. (2017). The cognitive map in humans: spatial navigation and beyond. Nature Neuroscience 20(11): 1504–1513.Google Scholar
Epstein, S., Kitahara, H., & Seely, D. (2014). Labeling by minimal search: implications for successive-cyclic A-movement and the conception of the postulate ‘phase’. Linguistic Inquiry 45(3): 463–481.Google Scholar
Epstein, S. D., Kitahara, H., & Seely, T. D. (2017a). Is the faculty of language a ‘perfect solution’ to the interface systems? In McGilvray, J. (ed.). The Cambridge Companion to Chomsky. 2nd ed. Cambridge: Cambridge University Press. 50–68.Google Scholar
Epstein, S. D., Kitahara, H., & Seely, T. D. (2017b). Merge, labeling and their interactions. In Bauke, L. & Blümel, A. (eds.). (2017). Labels and Roots. Berlin: Walter de Gruyter. 17–46.Google Scholar
Esghaei, M., Mohammad Reza, D., & Stefan, T. (2015). Attention decreases phase-amplitude coupling, enhancing stimulus discriminability in cortical area MT. Frontiers in Neural Circuits 9: 82.Google Scholar
Everaert, M. B. H., Huybregts, M. A. C., Chomsky, N., Berwick, R. C., & Bolhuis, J. J. (2015). Structures, not strings: Linguistics as part of the cognitive sciences. Trends in Cognitive Sciences 19(12): 729–743.Google Scholar
Ewerdwalbesloh, J. A., Palva, S., Rösler, F., & Khader, P. H. (2016). Neural correlates of maintaining generated images in visual working memory. Human Brain Mapping 37(12): 4349–4362.Google Scholar
Farias-Virgens, M. & White, S. A. (2017). A sing-song way of vocalizing: generalization and specificity in language and birdsong. Neuron 96(5): 958–960.Google Scholar
Fecteau, S., Armony, J. L., Joanette, Y., & Belin, P. (2004). Is voice processing species-specific in human auditory cortex? An fMRI study. Neuroimage 23: 840–848.Google Scholar
Fedorenko, E. & Thompson-Schill, S. L. (2014). Reworking the language network. Trends Cognitive Sciences 18: 120–126.Google Scholar
Fedorenko, E. & Varley, R. (2016). Language and thought are not the same thing: evidence from neuroimaging and neurological patients. Annals of the New York Academy of Sciences 1369(1): 132–153.Google Scholar
Fedorenko, E., Scott, T. L., Brunner, P., Coon, W. G., Pritchett, B., Schalk, G., & Kanwisher, N. (2016). Neural correlate of the construction of sentence meaning. PNAS 113(41): E6256–E6262.Google Scholar
Fell, J. & Axmacher, N. (2011). The role of phase synchronization in memory processes. Nature Neuroscience 12: 105–118.Google Scholar
Fellner, M-C., Gollwitzer, S., Rampp, S., Kreiselmeyr, G., Bush, D., Diehl, B., Axmacher, N., Hamer, H., & Hanslmayr, S. (2019). Spectral fingerprints or spectral tilt? Evidence for distinct oscillatory signatures of memory formation. PLoS Biology 17(7): e3000403.Google Scholar
Fernández-Ruiz, A. & Oliva, A. (2016). Distributed representation of ‘what’ and ‘where’ information in the parahippocampal region. Journal of Neuroscience 36(32): 8286–8288.Google Scholar
Fernández-Ruiz, A., Oliva, A., Fermino de Oliveira, E., Rocha-Almeida, F., Tingley, D., & Buzsáki, G. (2019). Long-duration hippocampal sharp wave ripples improve memory. Science 364(6445): 1082–1086.Google Scholar
Fiebach, C. J., Schlesewsky, M., Lohmann, G., Von Cramon, D. Y., & Friederici, A. D. (2005). Revisiting the role of Broca’s area in sentence processing: syntactic integration versus syntactic working memory. Human Brain Mapping 24: 79–91.Google Scholar
Fiebach, C. J., Vos, S. H., & Friederici, A. D. (2004). Neural correlates of syntactic ambiguity in sentence comprehension for low and high span readers. Journal of Cognitive Neuroscience 16: 1562–1575.Google Scholar
Fiebelkorn, I. C., Pinsk, M. A., & Kastner, S. (2018). A dynamic interplay within the frontoparietal network underlies rhythmic spatial attention. Neuron 99: 842–853.Google Scholar
Finlay, B. L., Darlington, R. B., & Nicastro, N. (2001). Developmental structure in brain evolution. Behavioral and Brain Sciences 24: 263–278.Google Scholar
Fisher, S. E. (2016). A molecular genetic perspective on speech and language. In Hickok, G. & Small, S. (eds.). Neurobiology of Language. Amsterdam: Elsevier. 13–24.Google Scholar
Fisher, S. E. & Vernes, S. (2015). Genetics and the language sciences. Annual Review of Linguistics 1: 289–310.Google Scholar
Fitch, W. T. (2009). Prolegomena to a future science of biolinguistics. Biolinguistics 3: 283–320.Google Scholar
Fitch, W. T. (2010a). The Evolution of Language. Cambridge: Cambridge University Press.Google Scholar
Fitch, W. T. (2010b). Three meanings of ‘recursion’: key distinctions for biolinguistics. In Larson, R., Deprez, V., & Yamakido, H. (eds.). The Evolution of the Human Language Faculty: Biolinguistic Perspectives. Cambridge: Cambridge University Press. 73–90.Google Scholar
Fitch, W. T. (2014a). Toward a computational framework for cognitive biology: unifying approaches from cognitive neuroscience and comparative cognition. Physics of Life Reviews 11: 329–364.Google Scholar
Fitch, W. T. (2014b). Attending to the forest and the trees. Reply to comments on ‘Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition’. Physics of Life Reviews 11: 391–399.Google Scholar
Fitch, W. T. (2017). On externalization and cognitive continuity in language evolution. Mind & Language 32: 597–606.Google Scholar
Fitch, W. T. & Friederici, A. D. (2012). Artificial grammar learning meets formal language theory: an overview. Philosophical Transactions of the Royal Society B 367(1598): 1933–1955.Google Scholar
Fitch, W. T. & Hauser, M. (2004). Computational constraints on syntactic processing in a nonhuman primate. Science 303(337): 377–80.Google Scholar
Fitch, W. T. & Martins, M. D. (2014). Hierarchical processing in music, language, and action: Lashley revisited. Annals of the New York Academy of Sciences 1316: 87–104.Google Scholar
Fitch, W. T., de Boer, B., Mathur, N., & Ghazanfar, A. A. (2016). Monkey vocal tracts are speech-ready. Science Advances 2(12): e1600723.Google Scholar
Flanagan, S. & Goswami, U. (2018). The role of phase synchronisation between low frequency amplitude modulations in child phonology and morphology speech tasks. The Journal of the Acoustical Society of America 143: 1366–1375.Google Scholar
Florez, C. M., McGinn, R. J., Lukankin, V., Marwa, I., Sugumar, S., Dian, J. et al. (2013). In vitro recordings of human neocortical oscillations. Cerebral Cortex 25: 578–597.Google Scholar
Fogerson, P. M. & Huguenard, J. R. (2016). Tapping the breaks: cellular and synaptic mechanisms that regulate thalamic oscillations. Neuron 92: 687–704.Google Scholar
Foubet, O., Trejo, M., & Toro, R. (2019). Mechanical morphogenesis and the development of neocortical organisation. Cortex 118: 315–326.Google Scholar
Frank, S. L. & Christiansen, M. H. (2018). Hierarchical and sequential processing of language. Language, Cognition and Neuroscience 33(9): 1213–1218.Google Scholar
Frank, S. L. & Yang, J-B. (2017). Non-syntactic processing explains cortical entrainment during speech perception. Talk presented at the 30th CUNY Conference on Human Sentence Processing, Massachusetts Institute of Technology: http://tedlab.mit.edu/cuny_abstracts/12_Final_Manuscript.pdfGoogle Scholar
Frank, S. L. & Yang, J-B. (2018). Lexical representation explains cortical entrainment during speech comprehension. PLoS ONE 13(5): e0197304.Google Scholar
Frankland, S. M. & Greene, J. D. (2020). Two ways to build a thought: distinct forms of compositional semantic representation across brain regions. Cerebral Cortex doi.org/10.1093/cercor/bhaa001Google Scholar
Freedman, D. J., Riesenhuber, M., Poggio, T., & Miller, E. K. (2003). A comparison of primate prefrontal and inferior temporal cortices during visual categorization. Journal of Neuroscience 23(12): 5235–5246.Google Scholar
Freeman, W. J. (2015). Mechanism and significance of global coherence in scalp EEG. Current Opinion in Neurobiology 31: 199–205.Google Scholar
Freidin, R. (2012). A brief history of generative grammar. In Russell, G. & Fara, D. G. (eds.). The Routledge Companion to Philosophy of Language. New York: Routledge. 895–916.Google Scholar
Freiwald, W., Tsao, D. Y., & Livingston, M. S. (2009). A face feature space in the macaque temporal lobe. Nature Neuroscience 12: 1187–1196.Google Scholar
Frey, S., Mackey, S., & Petrides, M. (2014). Cortico-cortical connections of areas 44 and 45b in the macaque monkey. Brain & Language 131: 36–55.Google Scholar
Fridriksson, J., Yourganov, G., Bonilha, L., Basilakos, A., Den Ouden, D-B., & Rorden, C. (2016). Revealing the dual streams of speech processing. PNAS 113(52): 15108–15113.Google Scholar
Friederici, A. D. (2011). The brain basis of language processing: from structure to function. Physiological Reviews 91: 1357–1392.Google Scholar
Friederici, A. D. (2012). The cortical language circuit: from auditory perception to sentence comprehension. Trends in Cognitive Sciences 5: 262–268.Google Scholar
Friederici, A. D. (2016). Evolution of the neural language network. Psychonomic Bulletin & Review 41(1): 41–47.Google Scholar
Friederici, A. D. (2017). Language in Our Brain. Cambridge, MA: MIT Press.Google Scholar
Friederici, A. D., Bahlmann, J., Heim, S., Schubotz, R. I., & Anwander, A. (2006). The brain differentiates human and non-human grammars: functional localization and structural connectivity. PNAS 103: 2458–63.Google Scholar
Friederici, A. D., Chomsky, N., Berwick, R. C., Moro, A., & Bolhuis, J. J. (2017). Language, mind and brain. Nature Human Behaviour 1: 713–722.Google Scholar
Fries, P. (2009). Neuronal gamma-band synchronization as a fundamental process in cortical computation. Annual Review of Neuroscience 32: 209–224.Google Scholar
Fries, P., Womelsdorf, T., Oostenveld, R., & Desimone, R. (2008). The effects of visual stimulation and selective visual attention on rhythmic neuronal synchronization in macaque area V4. Journal of Neuroscience 28: 4823–4835.Google Scholar
Friese, U., Köster, M., Hassler, U., Martens, U., Trujillo-Barreto, N., & Gruber, T. (2013). Successful memory encoding is associated with increased cross-frequency coupling between frontal theta and posterior gamma oscillations in human scalp-recorded EEG. NeuroImage 66: 642–647.Google Scholar
Frisch, S. A., Pierrehumbert, J. B., & Broe, M. B. (2004). Similarity avoidance and the OCP. Natural Language & Linguistic Theory 22: 179–228.Google Scholar
Friston, K. (2008). Hierarchical models in the brain. PLoS Computational Biology 4(11): e1000211.Google Scholar
Friston, K. (2010). The free-energy principle: a unified brain theory? Nature Reviews Neuroscience 11: 127–138.Google Scholar
Friston, K. J., Rosch, R., Parr, T., Price, C., & Bowman, H. (2017). Deep temporal models and active inference. Neuroscience and Biobehavioral Reviews 77: 388–402.Google Scholar
Fromont, L. A., Steinhauer, K., & Royle, P. (2020). Verbing nouns and nouning verbs: using a balanced design provides ERP evidence against ‘syntax-first’ approaches to sentence processing. PLoS ONE 15(3): e0229169.Google Scholar
Fuentes, A. (2016). The extended evolutionary synthesis, ethnography, and the human Niche: toward an integrated anthropology. Current Anthropology 57(S13): S13-S26.Google Scholar
Fujioka, T., Trainor, L. J., Large, E. W., & Ross, B. (2012). Internalized timing of isochronous sounds is represented in neuromagnetic beta oscillations. Journal of Neuroscience 32(5): 1791–1802.Google Scholar
Fujita, K. (2009). A prospect for evolutionary adequacy: merge and the evolution and development of human language. Biolinguistics 3(2): 128–153.Google Scholar
Fujita, K. (2016). On certain fallacies in evolutionary linguistics and how one can eliminate them. In Fujita, K. & Boeckx, C. (eds.). Advances in Biolinguistics: The Human Language Faculty and its Biological Basis. London: Routledge. 220–237.Google Scholar
Fujita, K. (2018). Placing too much weight on animal communication can be harmful. In Cuskley, C., Flaherty, M., McCrohon, L., Little, H., Ravignani, A., & Verhoef, T. (eds.). The Evolution of Language: Proceedings of the 12th International Conference (Evolang 12). Torun: Nicolaus Copernicus University. 131–133.Google Scholar
Fukuda, T., Takahashi, J., & Tanaka, J. (1999). Tyrosine hydroxylase-immunoreactive neurons are decreased in number in the cerebral cortex of Parkinson’s disease. Neuropathology 19(1): 10–13.Google Scholar
Fukui, N. (2015). A note on weak vs. strong generation in human language. Studies in Chinese Linguistics 36(2): 59–68.Google Scholar
Fukui, N. (2017). Merge in the Mind-Brain: Essays on Theoretical Linguistics and the Neuroscience of Language. London: Routledge.Google Scholar
Fyshe, A., Sudre, G., Wehbe, L., Rafidi, N., & Mitchell, T. M. (2016). The semantics of adjective noun phrases in the human brain. bioRxiv. http://dx.doi.org/10.1101/089615Google Scholar
Gabi, M., Neves, K., Masseron, C., Ribeiro, P. F. M., Ventura-Antunes, L., Torres, L., Mota, B., & Herculano-Houzel, S. (2016). No relative expansion of the number of prefrontal neurons in primate and human evolution. PNAS 113(34): 9617–9622.Google Scholar
Gągol, A., Magnuski, M., Kroczek, B., Kałamała, P., Ociepka, M., Santarnecchi, E., & Chuderski, A. (2018). Delta-gamma coupling as a potential neurophysiological mechanism of fluid intelligence. Intelligence 66: 54–63.Google Scholar
Gallego, Á. J. & Orús, R. (2017). The physical structure of grammatical correlations: equivalences, formalizations and consequences. arXiv 1708.01525v2.Google Scholar
Gallistel, C. R. (2017a). What memory must look like. Talk presented at the Big Ideas in Cognitive Neuroscience, CNS 2017.Google Scholar
Gallistel, R. (2017b). The coding question. Trends in Cognitive Sciences 21(7): 498–508.Google Scholar
Gallistel, C. R. & King, A. P. (2009). Memory and the computational brain: Why cognitive science will transform neuroscience. Malden, MA: Wiley-Blackwell.Google Scholar
Gallistel, C. R. & Matzel, L. D. (2013). The neuroscience of learning: beyond the Hebbian synapse. Annual Review of Psychology 64: 169–200.Google Scholar
Garey, M. & Johnson, D. (1979). Computers and Intractability: A Guide to the Theory of NP-Completeness. New York: W.H. Freeman.Google Scholar
Gärtner, H.-M. & Sauerland, U. (eds.). (2007). Interfaces + Recursion = Language? Chomsky’s Minimalism and the View from Syntax-Semantics. Berlin: De Gruyter Mouton.Google Scholar
Garvert, M. M., Dolan, R. J., & Behrens, T. E. (2017). A map of abstract relational knowledge in the human hippocampal-entorhinal cortex. Elife 6: e17086.Google Scholar
Gehrig, J., Michalareas, G., Forster, M-T., Lei, J., Hok, P., Laufs, H., Senft, C., Seifert, V., Schoffelen, J-M., Hanslmayr, S., & Kell, C. A. (2019). Low frequency oscillations code speech during verbal working memory. Journal of Neuroscience 39(33): 6498–6512.Google Scholar
Genç, E., Fraenz, C., Schlüter, C., Friedrich, P., Hossiep, R., Voelkle, M. C., Ling, J. M., Güntürkün, O., & Jung, R. E. (2018). Diffusion markers of dendritic density and arborization in gray matter predict differences in intelligence. Nature Communications 9: 1905.Google Scholar
Genon, S., Reid, A., Langner, R., Amunts, K., & Eickhoff, S. B. (2019). How to characterize the function of a brain region. Trends in Cognitive Sciences 22(4): 350–364.Google Scholar
Gentner, T. Q. & Hulse, S. (1998). Perceptual mechanisms for individual vocal recognition in European starlings, Sturnus vulgaris. Animal Behavior 56: 579–594.Google Scholar
Gentner, T. Q., Fenn, K. M., Margoliash, D., & Nusbaum, H. C. (2006). Recursive syntactic pattern learning by songbirds. Nature 440: 1204–1207.Google Scholar
Geschwind, D. H. & Rakic, P. (2013). Cortical evolution: Judge the brain by its cover. Neuron 80: 633–47.Google Scholar
Ghazanfar, A. A. & Eliades, S. J. (2014). The neurobiology of primate communication. Current Opinion in Neurobiology 28: 128–135.Google Scholar
Ghirlanda, S., Lind, J., & Enquist, M. (2017). Memory for stimulus sequences: a divide between humans and other animals? Royal Society Open Science 4: 161011.Google Scholar
Giahi Saravani, A., Forseth, K. J., Tandon, N., & Pitkow, X. (2019). Dynamic brain interactions during picture naming. eNeuro 6(4): ENEURO.0472-18.2019.Google Scholar
Gibson, K. R. & Jessee, S. (1999). Language evolution and expansions of multiple neural processing areas. In King, B (ed.). The Evolution of Language: Assessing the Evidence from the Non-Human Primates. Santa Fe, NM: School for American Research. 189–228.Google Scholar
Giere, R. (2006). Perspectival pluralism. Kellert, S., Longino, H., & Waters, C. K. (eds.). Scientific Pluralism. Minneapolis: University of Minnesota Press. 167–190.Google Scholar
Gips, B., van der Eerden, J. P. J. M., & Jensen, O. (2016). A biologically plausible mechanism for neuronal coding organized by the phase of alpha oscillations. European Journal of Neuroscience 44(4): 2147–2161.Google Scholar
Giraud, A.-L. & Poeppel, D. (2012). Cortical oscillations and speech processing: emerging computational principles and operations. Nature Neuroscience 15(4): 511–517.Google Scholar
Goldin-Meadow, S. & Yang, C. (2016). Statistical evidence that a child can create a combinatorial linguistic system without external linguistic input: implications for language evolution. Neuroscience and Biobehavioral Reviews 81(B): 150–157.Google Scholar
Gollo, L. L., Roberts, J. A., & Cocchi, L. (2017). Mapping how local perturbations influence systems-level brain dynamics. NeuroImage 160: 97–112.Google Scholar
Golston, C. (2018). φ-features in animal cognition. Biolinguistics 12: 55–98.Google Scholar
Gomez, J., Barnett, M., & Grill-Spector, K. (2019). Extensive childhood experience with Pokémon suggests eccentricity drives organization of visual cortex. Nature Neuroscience 3: 611–624.Google Scholar
Gomez-Marin, A. & Mainen, Z. F. (2016). Expanding perspectives on cognition in humans, animals, and machines. Current Opinion in Neurobiology 37: 85–91.Google Scholar
Gorišek, V. R., Isoski, V. Z., Belič, A., Manouilidou, C., Koritnik, B., Bon, J., Meglič, N. P., Vrabec, M., Žibert, J., Repovš, G., & Zidar, J. (2016). Beyond aphasia: altered EEG connectivity in Broca’s patients during working memory task. Brain & Language 163: 10–21.Google Scholar
Goswami, U. (2019). Speech rhythm and language acquisition: an amplitude modulation phase hierarchy perspective. Annals of the New York Academy of Sciences 1453(1): 67–78.Google Scholar
Goswami, U. & Leong, V. (2013). Speech rhythm and temporal structure: converging perspectives? Laboratory Phonology 4(1): 67–92.Google Scholar
Goucha, T., Anwander, A., & Friederici, A. D. (2015). How language shapes the brain: cross-linguistic differences in structural connectivity. Poster presented at 45th Annual Meeting of the Society for Neuroscience (SfN 2015), Chicago, IL, USA.Google Scholar
Goucha, T. & Friederici, A. D. (2015). The language skeleton after dissecting meaning: a functional segregation within Broca’s area. NeuroImage 114(6): 294–302.Google Scholar
Goucha, T., Zaccarella, E., & Friederici, A. D. (2017). A revival of Homo loquens as a builder of labeled structures: neurocognitive considerations. Neuroscience and Biobehavioral Reviews 81: 213–224.Google Scholar
Gould, S. J. &, Vrba, E. S. (1982). Exaptation: a missing term in the science of form. Paleobiology 8, 4–15.Google Scholar
Gould, S. J. (1997). Evolution: the pleasures of pluralism. New York Review of Books, June 26.Google Scholar
Gould, S. J. (2002). The Structure of Evolutionary Theory. Cambridge, MA: Harvard University Press.Google Scholar
Goyal, A., Miller, J., Qasim, S., Watrous, A. J., Stein, J. M., Inman, C. S., Gross, R. E., Willie, J. T., Lega, B., Lin, J.-J., et al. (2018). Functionally distinct high and low theta oscillations in the human hippocampus. bioRxiv. doi.org/10.1101/498055Google Scholar
Grabot, L., Kononowicz, T. W., Dupré la Tour, T., Gramfort, A., Doyère, V., van Wassenhove, V. (2019). The strength of alpha–beta oscillatory coupling predicts motor timing precision. Journal of Neuroscience 39(17): 3277–3291.Google Scholar
Gray, A. (1982). The Neuropsychology of Anxiety: An Enquiry into the Septo-Hippocampal System. Oxford: Oxford University Press.Google Scholar
Gray, C. M. & Singer, W. (1989). Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex. PNAS 86: 1698–1702.Google Scholar
Greenhill, S. J., Wu, C.-H., Hua, X., Dunn, M., Levinson, S. C., & Gray, R. D. (2017). Evolutionary dynamics of language systems. Proceedings of the National Academy of Sciences of the United States of America 114: E8822–E8829.Google Scholar
Gregoriou, G. G., Gotts, S. J., Zhou, H., & Desimone, R. (2009). High-frequency, long-range coupling between prefrontal and visual cortex during attention. Science 324: 1207–1210.Google Scholar
Griffiths, B. J. & Fuentemilla, L. (2020). Event conjunction: how the hippocampus integrates episodic memories across event boundaries. Hippocampus 30(2): 162–171.Google Scholar
Grillner, S. (2006) Biological pattern generation: the cellular and computational logic of networks in motion. Neuron 52: 751–766.Google Scholar
Grimaldi, M. (2012). Toward a neural theory of language: old issues and new perspectives. Journal of Neurolinguistics 25: 304–327.Google Scholar
Grimaldi, M. (2019). From brain noise to syntactic structures: a formal proposal within the oscillatory rhythms perspective. Franco, L. & Lorusso, P. (eds.). Linguistic Variation: Structure and Interpreation – A Festschrift in Honour of M. Rita Manzini in Occasion of Her 60th Birthday. New York: Mouton de Gruyter.Google Scholar
Grodzinsky, Y. & Friederici, A. D. (2006). Neuroimaging of syntax and syntactic processing. Current Opinion in Neurobiology 16(2): 240–246.Google Scholar
Gross, J., Hoogenboom, N., Thut, G., Schyns, P., Panzeri, S., Belin, P., & Garrod, S. (2013). Speech rhythms and multiplexed oscillatory sensory coding in the human brain. PLoS ONE 11(12): e1001752.Google Scholar
Gu, B-M., van Rijn, H., & Meck, W. H. (2015). Oscillatory multiplexing of neural population codes for interval timing and working memory. Neuroscience and Biobehavioral Reviews 48: 160–165.Google Scholar
Guevara Erra, R., Perez Velazquez, J.L., & Rosenblum, M. (2017). Neural synchronization from the perspective of non-linear dynamics. Frontiers in Computational Neuroscience 11: 98.Google Scholar
Güntekin, B. & Başar, E. (2016). Review of evoked and event-related delta responses in the human brain. International Journal of Psychophysiology 103: 43–52.Google Scholar
Gunz, P., Neubauer, S., Golovanova, L., Doronichev, V., Maureille, B., & Hublin, J.-J. (2012). A uniquely modern human pattern of endocranial development: insights from a new cranial reconstruction of the Neandertal newborn from Mezmaiskaya. Journal of Human Evolution 62(2): 300–313.Google Scholar
Guo, W., Clause, A. R., Barth-Maron, A., & Polley, D. B. (2017). A corticothalamic circuit for dynamic switching between feature detection and discrimination. Neuron 95(1): 180–194.Google Scholar
Haber, S. N. & Calzavara, R. (2009). The cortico-basal ganglia integrative network: the role of the thalamus. Brain Research Bulletin 78: 69–74.Google Scholar
Hackett, T. A., Preuss, T. M., & Kaas, J. H. (2001). Architectonic identification of the core region in auditory cortex of macaques, chimpanzees, and humans. Journal of Comparative Neurology 441: 197–222.Google Scholar
Haegens, S., Osipova, D., Oostenveld, R., & Jensen, O. (2010). Somatosensory working memory performance in humans depends on both engagement and disengagement of regions in a distributed network. Human Brain Mapping 31(1): 26–35.Google Scholar
Hage, S. R. & Nieder, A. (2016). Dual neural network model for the evolution of speech and language. Trends in Neurosciences 39(12): 813–829.Google Scholar
Hagoort, P. (2005). On Broca, brain, and binding: a new framework. Trends in Cognitive Sciences 9: 416–423.Google Scholar
Hagoort, P. (2019). The neurobiology of language beyond single-word processing. Science 366: 55–58.Google Scholar
Hahn, T. T., Sakmann, B., & Mehta, M. R. (2006). Phase-locking of hippocampal interneurons’ membrane potential to neocortical up-down states. Nature Neuroscience 9: 1359–1361.Google Scholar
Halassa, M. M., Chen, Z., Wimmer, R. D., Brunetti, P. M., Zhao, S., Zikopoulos, B., Wang, F., Brown, E. N., & Wilson, M. A. (2014). State-dependent architecture of thalamic reticular subnetworks. Cell 158(4): 808–821.Google Scholar
Halgren, M., Fabo, D., Ulbert, I., Madsen, J. R., Erőss, L., Doyle, W. K., Devinsky, O., Schomer, D., Cash, S. S., & Halgren, E. (2017). Superficial slow rhythms integrate cortical processing in humans. Scientific Reports 8: 2055.Google Scholar
Hall, D. C. (2012). Book review: Bridget D. Samuels. Phonological Architecture: A Biolinguistic Perspective. Journal of Linguistics 48(3): 736–741.Google Scholar
Hamilton, J. D. (1994). Time Series Analysis. Princeton, NJ: Princeton University Press.Google Scholar
Handjaras, G., Ricciardi, E., Leo, A., Lenci, A., Cecchetti, L., Cosottini, M., Marotta, G., & Pietrini, P. (2016). How concepts are encoded in the human brain: a modality independent, category-based cortical organization of semantic knowledge. NeuroImage 135: 232–242.Google Scholar
Hanna, J., Mejias, S., Schelstraete, M.-A., Pulvermüller, F., Shtyrov, Y., & van der Lely, H. K. J. (2014). Early activation of Broca’s area in grammar processing as revealed by the syntactic mismatch negativity and distributed source analysis. Cognitive Neuroscience 5(2): 66–76.Google Scholar
Hanslmayr, S., Axmacher, N., & Inman, C. S. (2019). Modulating human memory via entrainment of brain oscillations. Trends in Neuroscienes 42(7): 485–499.Google Scholar
Hanslmayr, S., Matuschek, J., & Fellner, M-C. (2014). Entrainment of prefrontal beta oscillations induces an endogenous echo and impairs memory formation. Current Biology 24: 904–909.Google Scholar
Hanslmayr, S., Staresina, B. P., & Bowman, H. (2016). Oscillations and episodic memory: addressing the synchronization/desynchronization conundrum. Trends in Neurosciences 39(1): 16–25.Google Scholar
Hanslmayr, S. & Staudigl, T. (2014). How brain oscillations form memories – a processing based perspective on oscillatory subsequent memory effects. Neuroimage 85(Part 2): 648–655.Google Scholar
Hardingham, G. E., Pruunsild, P., Greenberg, M. E., & Bading, H. (2018). Lineage divergence of activity-driven transcription and evolution of cognitive ability. Nature Reviews Neuroscience 19: 9–15.Google Scholar
Harmony, T. (2013). The functional significance of delta oscillations in cognitive processing. Frontiers in Integrative Neuroscience 7: 83.Google Scholar
Harris, K. D. (2015). Cortical computation in mammals and birds. PNAS 112(11): 3184–3185.Google Scholar
Hasson, U., Egidi, G., Marelli, M., & Willems, R. M. (2018). Grounding the neurobiology of language in first principles: the necessity of non-language-centric explanations for language comprehension. Cognition 180: 135–157.Google Scholar
Hauser, M. & Watumull, J. (2017). The Universal Generative Faculty: The source of our expressive power in language, mathematics, morality, and music. Journal of Neurolinguistics 43(B): 78–94.Google Scholar
Hauser, M., Chomsky, N., & Fitch, W. T. (2002). The faculty of language: what is it, who has it, and how did it evolve? Science 298(5598): 1569–1579.Google Scholar
Hauser, M., Yang, C., Berwick, R. C., Tattersall, I., Ryan, M. J., Watumull, J., Chomsky, N., & Lewontin, R. C. (2014). The mystery of language evolution. Frontiers in Psychology 5: 401.Google Scholar
Hauser, M. D., MacNeilage, P., & Ware, M. (1996). Numerical representations in primates. PNAS 93(4): 1514–1517.Google Scholar
Hauser, M. (2016). Challenges to the what, when, and why? Biolinguistics 10: 1–6.Google Scholar
Haynes, W. I. A. & Haber, S. N. (2013). The organization of prefrontal-subthalamic inputs in primates provides an anatomical substrate for both functional specificity and integration: implications for basal ganglia models and deep brain stimulation. Journal of Neuroscience 33(11): 4804–4814.Google Scholar
Headley, D. B. & Paré, D. (2017). Common oscillatory mechanisms across multiple memory systems. npj Science of Learning 2: 1.Google Scholar
Hebb, D. O. (1949). The Organization of Behavior. New York: John Wiley & Sons.Google Scholar
Hecht, E. E., Murphy, L. E., Gutman, D. A., Votaw, J. R., Schuster, D. M., Preuss, T. M., Orban, G. A., Stout, D., & Parr, L. A. (2013). Differences in neural activation for object-directed grasping in chimpanzees and humans. Journal of Neuroscience 33(35): 14117–14134.Google Scholar
Heffner, H. E. & Heffner, R. S. (1986). Effect of unilateral and bilateral auditory cortex lesions on the discrimination of vocalizations by Japanese macaques. Journal of Neurophysiology 56: 683–701.Google Scholar
Heine, B. & Kuteva, T. (2002). On the evolution of grammatical forms. In Wray, A. (ed.). The Transition to Language. Oxford: Oxford University Press. 376–397.Google Scholar
Heinz, A. J. (2016) A unitary framework defining the functional significance of neural oscillations in the alpha frequency. PhD thesis, North Dakota State University.Google Scholar
Heinz, J., Kobele, G., & Riggle, J. (2009). Evaluating the complexity of optimality theory. Linguistic Inquiry 40: 277–288.Google Scholar
Helfrich, R. F., Fiebelkorn, I. C., Szczepanski, S. M., Lin, J. J., Parvizi, J., Knight, R. T., & Kastner, S. (2018). Neural mechanisms of sustained attention are rhythmic. Neuron 99: 854–865.Google Scholar
Helfrich, R. F. & Knight, R. T. (2016). Oscillatory dynamics of prefrontal cognitive control. Trends in Cognitive Sciences 20(12): 916–930.Google Scholar
Henderson, J. M., Choi, W., Lowder, M. W., & Ferreira, F. (2016). Language structure in the brain: a fixation-related fMRI study of syntactic surprisal in reading. NeuroImage 132: 293–300.Google Scholar
Herrmann, C. S., Strüber, D., Helfrich, R. F., & Engel, A. K. (2016). EEG oscillations: from correlation to causality. International Journal of Psychophysiology 103: 12–21.Google Scholar
Heusser, A. C., Poeppel, D., Ezzyat, Y., & Davachi, L. (2016). Episodic sequence memory is supported by a theta-gamma phase code. Nature Neuroscience 19: 1374–1380.Google Scholar
Hickok, G. (2014). The Myth of Mirror Neurons: The Real Neuroscience of Communication and Cognition. London: W.W. Norton & Company.Google Scholar
Hickok, G., Buchsbaum, B., Humphries, C., & Muftuler, T. (2003). Auditory-motor interaction revealed by fMRI: speech, music, and working memory in area Spt. Journal of Cognitive Neuroscience 15: 673–682.Google Scholar
Hickok, G., Rogalsky, C., Chen, R., Herskovits, E. H., Townsley, S., & Hillis, A. E. (2014). Partially overlapping sensorimotor networks underlie speech praxis and verbal short-term memory: evidence from apraxia of speech following acute stroke. Frontiers in Human Neuroscience 8: 649.Google Scholar
Hinaut, X. & Dominey, P. (2013). Real-time parallel processing of grammatical structure in the fronto-striatal system: a recurrent network simulation study using reservoir computing. PLoS ONE 8(2): e52946.Google Scholar
Hinzen, W. (2006). Mind Design and Minimal Syntax. Oxford: Oxford University Press.Google Scholar
Hinzen, W. (2009). The successor function + LEX = Human language? In Grohmann, K. (ed.). InterPhases: Phase-Theoretic Investigations of Linguistic Interfaces. Oxford: Oxford University Press. 25–47.Google Scholar
Hinzen, W. (2016). On the grammar of referential dependence. Studies in Logic, Grammar and Rhetoric 46(1): 11–33.Google Scholar
Hinzen, W. & Sheehan, M. (2013). The Philosophy of Universal Grammar. Oxford: Oxford University Press.Google Scholar
Hiraiwa, K. (2017). The faculty of language integrates the two core systems of number. Frontiers in Psychology 8: 351.Google Scholar
Hobhouse, L. T. (1901). Mind in Evolution. London: Macmillan.Google Scholar
Hochstein, E. (2016). Categorizing the mental. The Philosophical Quarterly 66(265): 745–759.CrossRefGoogle Scholar
Hochstein, E. (2018). Why one model is never enough: a defense of explanatory holism. Biology & Philosophy 32(6): 1105–1125.Google Scholar
Hoepfner, A. R. & Goller, F. (2013). Atypical song reveals spontaneously developing coordination between multi-modal signals in brown-headed cowbirds (Molothrus ater). PLoS ONE 8(6): e65525.Google Scholar
Holmberg, A. & Roberts, I. (2014). Parameters and three factors of language design. In Picallo, C. (ed.). Linguistic Variation in the Minimalist Framework. Oxford: Oxford University Press. 61–81.Google Scholar
Honkanen, R., Rouhinen, S., Wang, S. H., Palva, J. M., & Palva, S. (2015). Gamma oscillations underlie the maintenance of feature-specific information and the contents of visual working memory. Cerebral Cortex 25(10): 3788–3801.Google Scholar
Horgan, J. (2017). The neural code. Edge. www.edge.org/response-detail/27011Google Scholar
Hornstein, N. (2009). A Theory of Syntax: Minimal Operations and Universal Grammar. Cambridge: Cambridge University Press.Google Scholar
Hornstein, N. & Pietroski, P. (2009). Basic operations: minimal syntax-semantics. Catalan Journal of Linguistics 8: 113–139.Google Scholar
Hosaka, R., Nakajima, T., Aihara, K., Yamaguchi, Y., & Mushiake, H. (2016). The suppression of beta oscillations in the primate supplementary motor complex reflects a volatile state during the updating of action sequences. Cerebral Cortex 26(8): 3442–3452.Google Scholar
Hoshi, K. (2019). More on the relations among categorization, merge and labeling, and their nature. Biolinguistics 13: 1–21.CrossRefGoogle Scholar
Howard, S. R., Avargues-Weber, A., Garcia, J. E., Greentree, A. D., & Dyer, A. G. (2019). Numerical cognition in honeybees enables addition and subtraction. Science Advances 5: eaav0961.CrossRefGoogle ScholarPubMed
Hülsemann, M. J., Naumann, E., & Rasch, B. (2019). Quantification of phase-amplitude coupling in neuronal oscillations: comparison of phase-locking value, mean vector length, modulation index, and generalized-linear-modeling-cross-frequency-coupling. Frontiers in Neuroscience 13: 573.Google Scholar
Hume, D. (1902). An enquiry concerning human understanding. In Selby-Bigge, L. A. (ed.). Enquiries Concerning the Human Understanding and Concerning the Principles of Morals, 2nd ed. Oxford: Clarendon Press. 5–168.Google Scholar
Hunt, B. A. E., Tewarie, P. K., Mougin, O. E., Gaedes, N., Jones, D. K., Singh, K. D., Morris, P. G., Gowland, P. A., & Brookes, M. J. (2016). Reltionships between cortical myeloarchitecture and electrophysiological networks. PNAS 113(47): 13510–13515.Google Scholar
Hunter, T., Stanojević, M., & Stabler, E. P. (2019). The active-filler strategy in a move-eager left-corner minimalist grammar parser. Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics (CMCL). Association for Computational Linguistics, Minneapolis, Minnesota. 1–10.Google Scholar
Hurford, J. R. (2011). The Origins of Grammar. Oxford: Oxford University Press.Google Scholar
Hurford, J. R. (2014). The Origins of Language: A Slim Guide. Oxford: Oxford University Press.Google Scholar
Huth, A. G., de Heer, W. A., Griffiths, T. L., Theunissen, F. E., & Gallant, J. L. (2016). Natural speech reveals the semantic maps that tile human cerebral cortex. Nature 532: 453–458.Google Scholar
Huybregts, M. A. C. (2017). Phonemic clicks and the mapping asymmetry: how language emerged and speech developed. Neuroscience and Biobehavioral Reviews 81: 279–294.CrossRefGoogle ScholarPubMed
Hyafil, A., Fontolan, L., Kabdebon, C., Gutkin, B., & Giraud, A.-L. (2015). Speech encoding by coupled cortical theta and gamma oscillations. eLife 10: 7554.Google Scholar
Iaria, G. & Burles, F. (2016). Developmental topological disorientation. Trends in Cognitive Neurosciences 20(10): 720–722.Google Scholar
Idsardi, W. (2018). Why is phonology different? No recursion. In Gallego, Á. J. & Martin, R. (eds.). Language, Syntax, and the Natural Sciences. Cambridge: Cambridge University Press. 212–223.Google Scholar
Itzkovitz, S. & Alon, U. (2007). The genetic code is nearly optimal for allowing additional information within protein-coding sequences. Genome Research 17: 405–412.CrossRefGoogle ScholarPubMed
Iwabuchi, T., Nakajima, Y., & Makuuchi, M. (2019). Neural architecture of human language: hierarchical structure building is independent from working memory. Neuropsychologia 132: 107137.Google Scholar
Jackendoff, R. (2007). Language, Consciousness, Culture: Essays on Mental Structure. Massachusetts: MIT Press.Google Scholar
Jackendoff, R. (2017). In defense of theory. Cognitive Science 41(2): 185–212.Google Scholar
Jäger, G. & Rogers, J. (2012). Formal language theory: refining the Chomsky hierarchy. Philosophical Transactions of the Royal Society B 367: 1956–1970.Google Scholar
Jahanshahi, M., Obeso, I., Rothwell, J. C., & Obeso, J. A. (2015). A fronto-striato-subthalamicpallidal network for goal-directed and habitual inhibition. Nature Reviews Neuroscience 16: 719–732.Google Scholar
Jansen, B. H. & Rit, V. G. (1995). Electroencephalogram and visual-evoked potential generation in a mathematical-model of coupled cortical columns. Biological Cybernetics 73(4): 357–366.Google Scholar
Jardim-Messeder, D., Lambert, K., Noctor, S., Pestana, F. M., de Castro Leal, M. E., Bertelsen, M. F., Alagaili, A. N., Mohammad, O. B., Manger, P. R., & Herculano-Houzel, S. (2017). Dogs have the most neurons, though not the largest brain: trade-off between body mass and number of neurons in the cerebral cortex of large carnivoran species. Frontiers in Neuroanatomy 11: 118.Google Scholar
Jarvis, E., Gunturkun, O., Bruce, L., Csillag, A., Karten, H., Kuenzel, W. et al. (2005). Avian brains and a new understanding of vertebrate brain evolution. Nature Reviews Neuroscience 6: 151–159.Google Scholar
Jenkins, L. (2000). Biolinguisitcs: Exploring the Biology of Language. Cambridge: Cambridge University Press.Google Scholar
Jensen, O. & Mazaheri, A. (2010). Shaping functional architecture by oscillatory alpha activity: gating by inhibition. Frontiers in Human Neuroscience 4: 186.Google Scholar
Jensen, O., Bonnefond, M., & VanRullen, R. (2012). An oscillatory mechanism for prioritizing salient unattended stimuli. Trends in Cognitive Sciences 16(4): 200–206.Google Scholar
Jensen, O., Gelfand, J., Kounios, J., Lisman, J. E. (2002). Oscillations in the alpha band (9–12 Hz) increase with memory load during retention in a short-term memory task. Cerebral Cortex 12: 877–882.Google Scholar
Jensen, O., Gips, B., Bergmann, T. O., & Bonnefond, M. (2014). Temporal coding organized by coupled alpha and gamma oscillations prioritize visual processing. Trends in Neurosciences 37(7): 357–369.Google Scholar
Jensen, O., Idiart, M., & Lisman, J. (1996). Physiologically realistic formation of autoassociative memory in networks with theta/gamma oscillations: role of fast NMDA channels. Learning & Memory 3: 243–256.Google Scholar
Jensen, O., Spaak, E., & Park, H. (2016). Discriminating valid from spurious indices of phase-amplitude coupling. eNeuro 3(6): ENEURO.0334-16.2016.Google Scholar
Jessen, N. A., Munk, A. S. F., Lundgaard, I., & Nedergaard, M. (2015). The glymphatic system: a beginner’s guide. Neurochemical Research 40(12): 2583–2599.Google Scholar
Jiang, H., Bahramisharif, A., van Gerven, M. A. J., & Jensen, O. (2015). Measuring directionality between neuronal oscillations of different frequencies. Neuroimage 118: 359–367.Google Scholar
Jiang, X., Long, T., Cao, W., Li, J., Dehaene, S., & Wang, L. (2018). Production of supraregular spatial sequences by macaque monkeys. Current Biology 28: 1851–1859.Google Scholar
Jin, J. & Maren, S. (2015). Prefrontal-hippocampal interactions in memory and emotion. Frontiers in Systems Neuroscience 9: 170.Google Scholar
Jin, P., Zhou, T., & Ding, N. (2019). Low-frequency neural activity reflects rule-based chunking during speech. Poster presented at the 49th Meeting of the Society for Neuroscience, Chicago, 19–23 October.Google Scholar
Jin, X., Tecuapetla, F., & Costa, R. M. (2014). Basal ganglia subcircuits distinctively encode the parsing and concatenation of action sequences. Nature Neuroscience 17: 423–430.Google Scholar
Jirenhed, D.-A., Rasmussen, A., Johansson, F., & Hesslow, G. (2017). Learned response sequences in cerebellar Purkinje cells. PNAS 114(23): 6127–6132.Google Scholar
Johansson, S. (2013). Biolinguistics or psycholinguistics? Is the third factor helpful or harmful in explaining language? Biolinguistics 7: 249–275.Google Scholar
Johnson, C. D. (1972). Formal Aspects of Phonological Description. The Hague: Mouton.Google Scholar
Johnson, E. J. & Knight, R. T. (2015). Intracranial recordings and human memory. Current Opinion in Neurobiology 31: 18–25.Google Scholar
Jonas, E. & Kording, K. (2017). Could a neuroscientist understand a microprocessor? PLoS Computational Biology. doi.org/10.1371/journal.pcbi.1005268Google Scholar
Jones, E. G. (2007). The Thalamus. 2nd ed. Cambridge: Cambridge University Press.Google Scholar
Joshi, A. K. (1985). Tree adjoining grammars: how much context-sensitivity is required to provide reasonable structural descriptions? In Dowty, D. R., Karttunen, L., & Zwicky, A. M. (eds.). Natural Language Parsing. Cambridge: Cambridge University Press. 206–250.Google Scholar
Jost, K., Bryck, R. L., Vogel, E. K., & Mayr, U. (2011). Are old adults just like low working memory young adults? Filtering efficiency and age differences in visual working memory. Cerebral Cortex 21: 1147–1154.Google Scholar
Jouen, A-L., Verwey, W. B., van der Helden, J., Scheiber, C., Neveu, R., Dominey, P. F., & Ventre-Dominey, J. (2013). Discrete sequence production with and without a pause: the role of cortex, basal ganglia, and cerebellum. Frontiers in Human Neuroscience 7: 492.Google Scholar
Jung, R. E. & Haier, R. J. (2007). The parieto-frontal integration theory (P-FIT) of intelligence: converging neuroimaging evidence. Behavioral and Brain Sciences 30: 135–154.Google Scholar
Jutras, M. J., Fries, P., & Buffalo, E. A. (2013). Oscillatory activity in the monkey hippocampus during visual exploration and memory formation. PNAS 110(32): 13144–13149.Google Scholar
Kaas, J. H. & Stepniewska, I. (2015). Evolution of posterior parietal cortex and parietal-frontal networks for specific actions in primates. Journal of Comparative Neurology 524(3): 595–608.Google Scholar
Kaiser, J., Heidegger, T., Wibral, M., Altmann, C. F., & Lutzenberger, W. (2008). Distinct gamma-band components reflect the short-term memory maintenance of different sound lateralization angles. Cerebral Cortex 18: 2286–2295.Google Scholar
Kaiser, J., Rahm, B., & Lutzenberger, W. (2009). Temporal dynamics of stimulus-specific gamma-band activity components during auditory short-term memory. NeuroImage 44(1): 257–264.Google Scholar
Kamigaki, T. & Dan, Y. (2017). Delay activity of specific prefrontal interneuron subtypes modulates memory-guided behavior. Nature Neuroscience 20: 854–863.Google Scholar
Kamiński, J., Brzezicka, A., Mamelak, A. N., & Rutishauser, U. (2020). Combined phase-rate coding by persistently active neurons as a mechanism for maintaining multiple items in working memory in humans. Neuron 106(2): 256–264.Google Scholar
Kamiński, J., Brzezicka, A., & Wróbel, A. (2011). Short-term memory capacity (7 ± 2) predicted by theta to gamma cycle length ratio. Neurobiology of Learning and Memory 95(1): 19–23.Google Scholar
Kang, A. M., Constable, R. T., Gore, J. C., & Avrutin, S. (1999). An event-related fMRI study of implicit phrase-level syntactic and semantic processing. NeuroImage 10: 555–561.Google Scholar
Kaplan, R., Adhikari, M. H., Hindriks, R., Mantini, D., Murayama, Y., Logothetis, N. K., & Deco, G. (2016). Hippocampal sharp-wave ripples influence selective activation of the default mode network. Current Biology 26: 1–6.Google Scholar
Kaplan, R., Bush, D., Bonnefond, M., Bandettini, P. A., Barnes, G. R., Doeller, C. F., & Burgess, N. (2014). Medial prefrontal theta phase coupling during spatial memory retrieval. Hippocampus 24(6): 656–665.Google Scholar
Karakaş, S. & Barry, R. J. (2017). A brief historical perspective on the advent of brain oscillations in the biological and psychological disciplines. Neuroscience and Biobehavioral Reviews 75: 335–347.Google Scholar
Kastellakis, G., Silva, A. J., & Piorazi, P. (2016). Linking memories across time via neuronal and dendritic overlaps in model neurons with active dendrites. Cell Reports 17: 1491–1504.Google Scholar
Kato, T., Kuno, M., Narita, H., Zushi, M., & Fukui, N. (2014). Generalized search and cyclic derivation by phase. Sophia Linguistica 61: 203–222.Google Scholar
Katz, P. S. & Harris-Warrick, R. M. (1999). The evolution of neuronal circuits underlying species-specific behavior. Current Opinion in Neurobiology 9: 628–633.Google Scholar
Kayser, C., Wilson, C., Safaai, H., Sakata, S., & Panzeri, S. (2014). Rhythmic auditory cortex activity at multiple timescales. Journal of Neuroscience 35(20): 7750–7762.Google Scholar
Kayser, S. J., Ince, R. A., Gross, J., & Kayser, C. (2015). Irregular speech rate dissociates auditory cortical entrainment, evoked responses, and frontal alpha. Journal of Neuroscience 35(44): 14691–14701.Google Scholar
Ke, A. H. (2017). Full phase transfer. Ms. University of Michigan. 10.13140/RG.2.2.14833.79209.Google Scholar
Keene, C. S., Bladon, J., McKenzie, S., Liu, C. D., O’Keefe, J., Eichenbaum, H. (2016). Complementary functional organization of neuronal activity patterns in the perirhinal, lateral entorhinal, and medial entorhinal cortices. Journal of Neuroscience 36: 3660–3675.Google Scholar
Keitel, A., Gross, J., & Kayser, C. (2018). Perceptually relevant speech tracking in auditory and motor cortex reflects distinct linguistic features. PLOS Biology 16(3): e2004473.Google Scholar
Keitel, A., Ince, R. A. A., Gross, J., & Kayser, C. (2017). Auditory cortical delta-entrainment interacts with oscillatory power in multiple fronto-parietal networks. NeuroImage 147: 32–42.Google Scholar
Keller, G. B. & Mrsic-Flogel, T. D. (2018). Predictive processing: a canonical cortical computation. Neuron 100(2): 424–435.Google Scholar
Kelso, J. A. S., Dumas, G., & Tognoli, E. (2013). Outline of a general theory of behavior and brain coordination. Neural Networks 37: 120–131.Google Scholar
Kenet, T., Bibitchkov, D., Tsodyks, M., Grinvald, A., & Ariell, A. (2003). Spontaneously emerging cortical representations of visual attributes. Nature 425: 954–956.Google Scholar
Kenneally, C. (2007). The First Word: The Search for the Origins of Language. New York: Penguin Books.Google Scholar
Kepecs, A., Uchida, N., & Mainen, Z. F. (2006). The sniff as a unit of olfactory processing. Chemical Senses 31: 167–179.Google Scholar
Kepinska, O., de Rover, M., Caspers, J., & Schiller, N. O. (2018). Connectivity of the hippocampus and Broca’s area during acquisition of a novel grammar. NeuroImage 165: 1–10.Google Scholar
Kershenbaum, A., Bowles, A. E., Freeberg, T. M., Jin, D. Z., Lameira, A. R., & Bohn, K. (2014). Animal vocal sequences: not the Markov chains we thought they were. Proceedings of the Royal Society B 281: 20141370.Google Scholar
Kessler, K., Seymour, R. A., & Rippon, G. (2016). Brain oscillations and connectivity in autism spectrum disorders (ASD): new approaches to methodology, measurement and modelling. Neuroscience and Biobehavioral Reviews 71: 601–620.Google Scholar
Ketz, N. A., Jensen, O., & O’Reilly, R. C. (2015). Thalamic pathways underlying prefrontal cortex–medial temporal lobe oscillatory interactions. Trends in Neurosciences 38(1): 3–12.Google Scholar
Khodagholy, D., Gelinas, J. N., & Buzsáki, G. (2017). Learning-enhanced coupling between oscillations in association cortices and hippocampus. Science 358: 369–372.Google Scholar
Kielar, A., Meltzer, J., Moreno, S., Alain, C., & Bialystok, E. (2014). Oscillatory responses to semantic and syntactic violations. Journal of Cognitive Neuroscience 26: 2840–2862.Google Scholar
Kielar, A., Panamsky, L., Links, K. A., & Meltzer, J. A. (2015). Localization of electrophysiological responses to semantic and syntactic anomalies in language comprehension with MEG. NeuroImage 105: 507–524.Google Scholar
Kikuchi, Y., Attaheri, A., Wilson, B., Rhone, A. E., Nourski, K. V. et al. (2017). Sequence learning modulates neural responses and oscillatory coupling in human and monkey auditory cortex. PLoS Biology 15(4): e2000219.Google Scholar
Killingsworth, M. A. & Gilbert, D. T. (2010). A wandering mind is an unhappy mind. Science 330: 932.Google Scholar
Kingsolver, J. G. & Koehl, M. A. R. (1985). Aerodynamics, thermoregulation, and the evolution of insect wings: differential scaling and evolutionary change. Evolution 39: 488–504.Google Scholar
Kinzler, K. & Spelke, E. (2007). Core systems in human cognition. Progress in Brain Research 164: 257–64.Google Scholar
Kiran, S. & Thompson, C. K. (2019). Neuroplasticity of language networks in aphasia: advances, updates, and future challenges. Frontiers in Neurology 10: 295.Google Scholar
Kirmayer, L. J. (2017). Ontologies of life: From thermodynamics to teleonomics. Comment on ‘Answering Schrödinger’s question: A free-energy formulation’ by Maxwell James Désormeau Ramstead et al. Physics of Life Reviews. https://doi.org/10.1016/j.plrev.2017.11.022Google Scholar
Klausberger, T., Marton, L. F., O’Neill, J., Huck, J. H., Dalezios, Y., Fuentealba, P., Suen, W. Y., Papp, E., Kaneko, T., Watanabe, M., Csicsvari, J., Somogyi, P. (2005). Complementary roles of cholecystokinin- and parvalbumin-expressing GABAergic neurons in hippocampal network oscillations. Journal of Neuroscience 25(42): 9782–9793.Google Scholar
Kleen, J. K., Testorf, M. E., Roberts, D. W., Scott, R. C., Jobst, B. J., Holmes, G. L., & Lenck-Santini, P-P. (2016). Oscillation phase locking and late ERP components of intracranial hippocampal recordings correlate to patient performance in a working memory task. Frontiers in Human Neuroscience 10: 287.Google Scholar
Klimesch, W., Doppelmayr, M., Wimmer, H., Gruber, W., Rohm, D., Schwaiger, J., & Hutzler, F. (2001). Alpha and beta band power changes in normal and dyslexic children. Clinical Neurophysiology 112: 1186–1195.Google Scholar
Klimesch, W., Sauseng, P., & Hanslmayr, S. (2007). EEG alpha oscillations: the inhibition-timing hypothesis. Brain Research Reviews 53: 63–88.Google Scholar
Klimesch, W., Schack, B., Schabus, M., Doppelmayr, M., Gruber, W., & Sauseng, P. (2004). Phase-locked alpha and theta oscillations generate the P1-N1 complex and are related to memory performance. Cognitive Brain Research 19: 302–316.Google Scholar
Klostermann, F., Krugel, L. K., & Ehlen, F. (2013). Functional roles of the thalamus for language capacities. Frontiers in Systems Neuroscience 7: 32.Google Scholar
Koehler, O. (1951). Der Vogelgesang als Vorstufe von Musik und Sprache. Journal of Ornithology 93(1): 3–20.Google Scholar
Koene, R. A. & Hasselmo, M. E. (2007). First-in-first-out item replacement in a model of short-term memory based on persistent spiking. Cerebral Cortex 17: 1766–1781.Google Scholar
Kolodny, O. & Edelman, S. (2018). The evolution of the capacity for language: the ecological context and adaptive value of a process of cognitive hijacking. Philosophical Transactions of the Royal Society B 373: 20170052.Google Scholar
König, P. (1994). A method for the quantification of synchrony and oscillatory properties of neuronal. Journal of Neuroscience Methods 54: 31–37.Google Scholar
König, P., Engel, A. K., & Singer, W. (1995). Relation between oscillatory activity and long-range synchronization in cat visual cortex. PNAS 92: 290–294.Google Scholar
Konopka, G. & Roberts, T. F. (2016). Insights into the neural and genetic basis of vocal communication. Cell 164: 1269–1276.Google Scholar
Kopell, N., Börgers, C., Pervouchine, D., Malerba, P., & Tort, A. (2010). Gamma and theta rhythms in biophysical models of hippocampal circuits. In Cutsuridis, V., Graham, B. P., Cobb, S., & Vida, I. (eds.). Hippocampal Microcircuits: A Computational Modeler’s Resource Book. New York: Springer. 423–457.Google Scholar
Kopell, N. J., Gritton, H. J., Whittington, M. A., & Kramer, M. A. (2014). Beyond the connectome: the dynome. Neuron 83: 1319–1328.Google Scholar
Kopell, N. J., Kramer, M. A., Malerba, P., & Whittington, M. A. (2010). Are different rhythms good for different functions? Frontiers in Human Neuroscience 4: 187.Google Scholar
Korotkova, T., Fuchs, E. C., Ponomarenko, A., von Engelhardt, J., & Monyer, H. (2010). NMDA receptor ablation on parvalbumin-positive interneurons impairs hippocampal synchrony, spatial representations, and working memory. Neuron 68(3): 557–569.Google Scholar
Kösem, A. & van Wassenhove, V. (2016). Oscillatory neural activity controls the encoding of continuous speech. Talk presented at the 20th International Conference on Biomagnetism (BioMag 2016), Seoul.Google Scholar
Kösem, A. & van Wassenhove, V. (2017). Distinct contributions of low- and high-frequency neural oscillations to speech comprehension. Language, Cognition and Neuroscience 32(5): 536–544.Google Scholar
Kotz, S. A., Schwartze, M., & Schmidt-Kassow, M. (2009). Non-motor basal ganglia functions: a review and proposal for a model of sensory predictability in auditory language perception. Cortex 45: 982–990.Google Scholar
Koziol, L. F., Budding, D. E., & Suth, A. (2009). Subcortical Structures and Cognition: Implications for Neuropsychological Assessment. New York: Springer.Google Scholar
Krakauer, J. W., Ghazanfar, A. A., Gomez-Marin, A., MacIver, M. A., & Poeppel, D. (2017). Neuroscience needs behaviour: correcting a reductionist bias. Neuron 93: 480–490.Google Scholar
Kramer, M. A. & Eden, U. T. (2013). Assessment of cross-frequency coupling with confidence using generalized linear models. Journal of Neuroscience Methods 220(1): 64–74.Google Scholar
Kriegeskorte, N. & Storrs, K. R. (2016). Grid cells for conceptual space? Neuron 92: 280–284.Google Scholar
Kristan, W. B. Jr. (2016). Early evolution of neurons. Current Biology 26: R949–R954.Google Scholar
Kropotkin, P. (2010[1908]). Modern Science and Anarchism. Whitefish, MT: Kessinger Publishing.Google Scholar
Kucyi, A. (2018). Just a thought: how mind-wandering is represented in dynamic brain connectivity. NeuroImage 180(B): 505–514.Google Scholar
Kuhlwilm, M. & Boeckx, C. (2019). A catalog of single nucleotide changes distinguishing modern humans from archaic hominins. Scientific Reports 9: 8463.Google Scholar
Kuhnke, P., Meyer, L., Freiderici, A., & Hartwigsen, G. (2017). Left posterior inferior frontal gyrus is causally involved in reordering during sentence processing. NeuroImage 148: 254–263.Google Scholar
Kujala, J., Pammer, K., Cornelissen, P., Roebroeck, A., Formisano, E., & Salmelin, R. (2007). Phase coupling in a cerebro-cerebellar network at 8–13 Hz during reading. Cerebral Cortex 17: 1476–1485.Google Scholar
Kurth, S., Riedner, B. A., Dean, D. C., O’Muircheartaigh, J., Huber, R., Jenni, O. G., Deoni, S. C. L., & LeBourgeois, M. K. (2017). Travelling slow oscillations during sleep: a marker of brain connectivity in childhood. Sleep 40: zsx121.Google Scholar
Lachaux, J. P., Rodriguez, E., Martinerie, J., & Varela, F. J. (1999). Measuring phase synchrony in brain signals. Human Brain Mapping 8: 194–208.Google Scholar
Lakatos, I. (1970). Falsification and the methodology of scientific research programmes. In Lakatos, I. & Musgrave, A. (eds.). Criticism and the Growth of Knowledge. Cambridge: Cambridge University Press. 8–11.Google Scholar
Lakatos, P., Karmos, G., Mehta, A. D., Ulbert, I., & Schroeder, C. E. (2008). Entrainment of neuronal oscillations as a mechanism of attentional selection. Science 320(5872): 110–113.Google Scholar
Lakatos, P., Shah, A. S., Knuth, K. H., Ulbert, I., Karmos, G., & Schroeder, C. E. (2005). An oscillatory hierarchy controlling neuronal excitability and stimulus processing in the auditory cortex. Journal of Neurophysiology 94: 1904–1911.CrossRefGoogle ScholarPubMed
Lam, N. H. L., Hultén, A., Hagoort, P., & Schoffelen, J.-M. (2018). Robust neuronal oscillatory entertainment to speech displays individual variation in lateralisation. Language, Cognition and Neuroscience 33(8): 943–954.Google Scholar
Lam, N. H. L., Schoffelen, J-M., Udden, J., Hulten, A., & Hagoort, P. (2016). Neural activity during sentence processing as reflected in theta, alpha, beta, and gamma oscillations. NeuroImage 142: 43–54.Google Scholar
Lametti, D. R., Wijdenes, L. O., Bonaiuto, J., Bestmann, S., & Rothwell, J. C. (2016). Cerebellar tDCS dissociates the timing of perceptual decisions from perceptual change in speech. Journal of Neurophysiology 116: 2023–2032.Google Scholar
Lane, C., Kanjlia, S., Omaki, A., & Bedny, M. (2015). ‘Visual’ cortex of congenitally blind adults responds to syntactic movement. Journal of Neuroscience 35(37): 12859–12868.Google Scholar
Lapray, D., Lasztoczi, B., Lagler, M., Viney, T. J., Katona, L., Valenti, O., Hartwich, K., Borhegyi, Z., Somogyi, P., & Klausberger, T. (2012). Behavior-dependent specialization of identified hippocampal interneurons. Nature Neuroscience 15: 1265–1271.Google Scholar
Lara, A. H. & Wallis, J. D. (2015). The role of prefrontal cortex in working memory: a mini review. Frontiers in Systems Neuroscience 9: 173.Google Scholar
Larkum, M. (2013). A cellular mechanism for cortical associations: an organizing principle for the cerebral cortex. Trends in Neurosciences 36(3): 141–151.Google Scholar
Larson, B. (2015). Minimal search as a restriction on merge. Lingua 156: 57–69.Google Scholar
Larson-Prior, L. J., Oostenveld, R., Della Penna, S., Michalareas, G., Prior, F., Babajani-Feremi, A., Schoffelen, J. M., Marzetti, L., de Pasquale, F., Di Pompeo, F. et al. (2013). Adding dynamics to the human connectome project with MEG. NeuroImage 80: 190–201.Google Scholar
Lasnik, H. (2017). The locality of transformation movement: progress and prospects. In McGilvray, J. (ed.). The Cambridge Companion to Chomsky. 2nd ed. Cambridge: Cambridge University Press. 29–49.Google Scholar
Lau, E., Phillips, C., & Poeppel, D. (2008). A cortical network for semantics: (de)constructing the N400. Nature Reviews Neuroscience 9: 920–933.Google Scholar
Le May, M. & Geschwind, N. (1975). Hemispheric differences in the brains of great apes. Brain, Behavior, and Evolution 11: 48–52.Google Scholar
Le Van Quyen, M. & Bragin, A. (2007). Analysis of dynamic brain oscillations: methodological advances. Trends in Neurosciences 30: 365–373.Google Scholar
Lee, H., Simpson, G. V., Logothetis, N. K., & Rainer, G. (2005). Phase locking of single neuron activity to theta oscillations during working memory in monkey extrastriate visual cortex. Neuron 45: 147–156.Google Scholar
Lee, S. H., Kwan, A. C., Zhang, S., Phoumthipphavong, V., Flannery, J. G., Masmanidis, S. C., et al. (2012). Activation of specific interneurons improves V1 feature selectivity and visual perception. Nature 488: 379–383.Google Scholar
Lefebvre, J. L., Kostadinov, D., Chen, W. V., Maniatis, T., & Sanes, J. R. (2012). Protocadherins mediate dendritic self-avoidance in the mammalian nervous system. Nature 488: 517–521.Google Scholar
Leivada, E. (2017). What’s in (a) label? Neural origins and behavioural manifestations of identity avoidance in language and cognition. Biolinguistics 11.SI.Google Scholar
Lemasson, A., Outtara, K., & Zuberbühler, K. (2013). Exploring the gaps between primate calls and human language. Botha, R. & Everaert, M. (eds.). The Evolutionary Emergence of Language: Evidence and Inference. Oxford: Oxford University Press. 181–203.Google Scholar
Lenneberg, E. H. (1964). A biological perspective of language. In Lenneberg, E. H. (ed.). New Directions in the Study of Language. Cambridge, MA: MIT Press. 65–88.Google Scholar
Lenneberg, E. H. (1967). Biological Foundations of Language. New York: John Wiley & Sons.Google Scholar
Leong, V., Byrne, E., Clackson, K., Harte, N., Lam, S., Barbaro, K. D., & Wass, S. (2017). Infants’ neural oscillatory processing of theta-rate speech patterns exceeds adults’. bioRxiv. http://dx.doi.org/10.1101/108852Google Scholar
Leong, V. & Goswami, U. (2015). Acoustic-emergent phonology in the amplitude envelope of child-directed speech. PLoS ONE 10(12): 1–37.Google Scholar
Leszczynski, M., Barczak, A., Kajikawa, Y., Ulbert, I., Falchier, A., Tal, I., Haegens, S., Melloni, L., Knight, R., & Schroeder, C. (2019). Dissociation of broadband high-frequency activity and neuronal firing in the neocortex. bioRxiv. https://doi.org/10.1101/531368Google Scholar
Leszczyński, M., Fell, J., & Axmacher, N. (2015). Rhythmic working memory activation in the human hippocampus. Cell Reports 13: 1–11.Google Scholar
Leszczynski, M., Fell, J., Jensen, O., & Axmacher, N. (2017). Alpha activity in the ventral and dorsal visual stream controls information flow during working memory. bioRxiv. http://dx.doi.org/10.1101/180166Google Scholar
Letinic, K. & Rakic, P. (2001). Telencephalic origin of human thalamic gabaergic neurons. Nature Neuroscience 4: 931–936.Google Scholar
Leung, S., Mareschal, D., Rowsell, R., Simpson, D., Iaria, L., Grbic, A., & Kaufman, J. (2016). Oscillatory activity in the infant brain and the representation of small numbers. Frontiers in Systems Neuroscience 10: 4.Google Scholar
Leventhal, D. K., Gage, G. J., Schmidt, R., Pettibone, J. R., Case, A. C., & Berke, J. D. (2012). Basal ganglia beta oscillations accompany cue utilization. Neuron 73: 523–536.Google Scholar
Lever, C., Kaplan, R., & Burgess, N. (2014). The function of oscillations in the hippocampal formation. Derdikman, D. & Knierim, J. J. (eds.). Space, Time and Memory in the Hippocampal Formation. Wein: Springer. 303–350.CrossRefGoogle Scholar
Levins, R. & Lewontin, R. (1985). The Dialectical Biologist. Cambridge, MA: Harvard University Press.Google Scholar
Levitis, D. A., Lidicker, W. Z., & Freund, G. (2009). Behavioural biologists don’t agree on what constitutes behaviour. Animal Behavior 78: 103–110.Google Scholar
Lewis, A. G. & Bastiaansen, M. (2015). A predictive coding framework for rapid neural dynamics during sentence-level language comprehension. Cortex 68: 155–168.Google Scholar
Lewis, A. G., Lemhӧfer, K., Schoffelen, J.-M., & Schriefers, H. (2016). Gender agreement violations modulate beta oscillatory dynamics during sentence comprehension: a comparison of second language learners and native speakers. Neuropsychologia 89: 254–272.Google Scholar
Lewis, A. G., Schoffelen, J-M., Schriefers, H., & Bastiaansen, M. (2016). A predictive coding perspective on beta oscillations during sentence-level language comprehension. Frontiers in Human Neuroscience 10: 85.Google Scholar
Lewis, A. G., Wang, L., & Bastiaansen, M. (2015). Fast oscillatory dynamics during language comprehension: unification versus maintenance and prediction? Brain & Language 148: 51–63.Google Scholar
Lewis, D. (1969). Convention: A Philosophical Study. Cambridge: Harvard University Press.Google Scholar
Lewis, L. D., Setsompop, K., Rosen, B. R., & Polimeni, J. R. (2016). Fast fMRI can detect oscillatory neural activity in humans. PNAS 113(43): E6679–E6685.Google Scholar
Lewis, S. & Phillips, C. (2015). Aligning grammatical theories and language processing models. Journal of Psycholinguistic Research 44: 27–46.Google Scholar
Lewontin, Richard C. (1983). Gene, organism, and environment. In Bendall, D. S. (ed.). Evolution from Molecules to Men. Cambridge: Cambridge University Press. 273–285.Google Scholar
Li, M. & Tsien, J. Z. (2017). Neural code – neural self-information theory on how cell-assembly code rises from spike time and neuronal variability. Frontiers in Cellular Neuroscience 11: 236.Google Scholar
Li, X., Crow, T. J., Hopkins, W. D., Gong, Q., & Roberts, N. (2018). Human torque is not present in chimpanzee brain. NeuroImage 165: 285–293.Google Scholar
Li, X., Shao, X., Xia, J., & Xu, X. (2019). The cognitive and neural oscillatory mechanisms underlying the facilitating effect of rhythm regularity on speech comprehension. Journal of Neurolinguistics 49: 155–167.Google Scholar
Lieberman, P. (2000). Human Language and Our Reptilian Brain: The Subcortical Bases of Speech, Syntax, and Thought. Cambridge, MA: Harvard University Press.Google Scholar
Lieberman, P. (2006). Toward an Evolutionary Biology of Language. Cambridge, MA: Harvard University Press.Google Scholar
Lieberman, P. (2015). Language did not spring forth 100,000 years ago. PLoS Biology 13(2): e1002064.Google Scholar
Lightfoot, D. (2011). Natural selection-itis. In Gibson, K. R. & Tallerman, M. (eds.). The Oxford Handbook of Language Evolution. Oxford: Oxford University Press. 313–317.Google Scholar
Lightfoot, D. (2020). Born to Parse: Invention and Variation.Google Scholar
Lim, S.-J., Wöstmann, M., & Obleser, J. (2015). Selective attention to auditory memory neurally enhances perceptual precision. Journal of Neuro-science 35(49): 16094–16104.Google Scholar
Lisman, J. E. & Buzsáki, G. (2008). A neural coding scheme formed by the combined function of gamma and theta oscillations. Schizophrenia Bulletin 34(5): 974–980.Google Scholar
Lisman, J. E. & Idiart, M. A. (1995). Storage of 7 +/- 2 short-term memories in oscillatory subcycles. Science 267(5203): 1512–1515.Google Scholar
Lisman, J. E. & Jensen, O. (2013). The theta-gamma neural code. Neuron 77: 1002–1016.Google Scholar
Liu, Z., Fukunaga, M., de Zwart, J. A., & Duyn, J. H. (2010). Large-scale spontaneous fluctuations and correlations in brain electrical activity observed with magnetoencephalography. NeuroImage 51(1): 102–111.Google Scholar
Llinás, R. (2001). I of the Vortex: From Neurons to Self. Cambridge, MA: MIT Press.Google Scholar
Lobina, D. J. (2017). Recursion: A Computational Investigation into the Representation and Processing of Language. Oxford: Oxford University Press.Google Scholar
Longuet-Higgins, H. C. (1972). The algorithmic description of natural language. Proceedings of the Royal Society of London B Biological Sciences 182: 255–276.Google Scholar
Lopes-dos-Santos, V., Conde-Ocazionez, S., Nicolelis, M. A. L., Ribeiro, S. T., & Tort, A. B. L. (2011). Neuronal assembly detection and cell membership specification by principal component analysis. PLoS ONE 6(6): e20996.Google Scholar
Lourenço, J. & Bacci, A. (2017). Human-specific cortical synaptic connections and their plasticity: is that what makes us human? PLoS Biology 15(1): e2001378.Google Scholar
Lowet, E., Roberts, M. J., Bonizzi, P., Karel, J., & De Weerd, P. (2016). Quantifying neural oscillatory synchronization: a comparison between spectral coherence and phase-locking value approaches. PLoS ONE 11(1): e0146443.Google Scholar
Lu, M., Donamayor, N., Münte, T. F., & Bahlmann, J. (2017). Event-related potentials and neural oscillations dissociate level of cognitive control. Behavioural Brain Research 320: 154–164.Google Scholar
Lucas, B. & Hardin, J. (2017). Mind the (sr)GAP – roles of Slit-Robo GAPs in neurons, brains and beyond. Journal of Cell Science 130: 3965–3974.Google Scholar
Luck, S.J. (2014). An Introduction to the Event-Related Potential Technique. 2nd ed. Cambridge, MA: MIT Press.Google Scholar
Lundqvist, M., Herman, P., & Lansner, A. (2011). Theta and gamma power increases and alpha/beta power decreases with memory load in an attractor network model. Journal of Cognitive Neuroscience 23: 3008–3020.Google Scholar
Lundqvist, M., Rose, J., Herman, P., Brincat, S. L., Buschman, T. J., Miller, E. K. (2016). Gamma and beta bursts underlie working memory. Neuron 90: 1–13.Google Scholar
MacDonald, C. J., Lepage, K. Q., Eden, U. T., & Eichenbaum, H. (2011). Hippocampal ‘time cells’ bridge the gap in memory for discontiguous events. Neuron 71: 737–749.Google Scholar
Machens, C. K., Romo, R., & Brody, C. D. (2005). Flexible control of mutual inhibition: a neural model of two-interval discrimination. Science 307(5712): 1121–1124.Google Scholar
MacSweeney, M., Campbell, R., Woll, B., Brammer, M. J., Giampietro, V., David, A. S., Calvert, G. A., Machens, C. K., Romo, R., & Brody, C. D. (2005). Flexible control of mutual inhibition: a neural model of two-interval discrimination. Science 307(5712): 1121–1124.Google Scholar
Mai, G., Minett, J. W., Wang, W. S-Y. (2016). Delta, theta, beta, and gamma brain oscillations index levels of auditory sentence processing. NeuroImage 113: 516–528.Google Scholar
Maidenbaum, S., Miller, J., Stein, J. M., & Jacobs, J. (2018). Grid-like hexadirectional modulation of human entorhinal theta oscillations. PNAS 115(42): 10798–10803.Google Scholar
Maier, A., Adams, G. K., Aura, C., & Leopold, D. A. (2010). Distinct superficial and deep laminar domains of activity in the visual cortex during rest and stimulation. Front. Syst. Neurosci. 4: 31.Google Scholar
Mainen, Z. F. & Sejnowski, T. J. (1995). Reliability of spike timing in neocortical neurons. Science 268(5216): 1503–1506.Google Scholar
Makeig, S., Westerfield, M., Jung, T. P., Enghoff, S., Townsend, J., Courchesne, E., & Sejnowski, T. J. (2002). Dynamic brain sources of visual evoked responses. Science 295: 690–694.Google Scholar
Makuuchi, M., Bahlmann, J., Anwander, A., & Friederici, A. D. (2009). Segregating the core computational faculty of human language from working memory. PNAS 106: 8362–8367.Google Scholar
Malekmohammadi, M., Elias, W. J., & Pouratian, N. (2015). Human thalamus regulates cortical activity via spatially specific and structurally constrained phase-amplitude coupling. Cerebral Cortex 25: 1618–1628.Google Scholar
Mancini, S. (2018). When grammar and parsing agree. Frontiers in Psychology 9: 336.Google Scholar
Männel, C. & Friederici, A. D. (2011). Intonational phrase structure processing at different stages of syntax acquisition: ERP studies in 2‐, 3‐, and 6‐year‐old children. Developmental Science 14(4): 786–798.Google Scholar
Maris, E., Fries, P., & van Ede, F. (2016). Diverse phase relations among neuronal rhythms and their potential function. Trends in Neurosciences 39(2): 86–99.Google Scholar
Maris, E., van Vugt, M., & Kahana, M. (2011). Spatially distributed patterns of oscillatory coupling between high-frequency amplitudes and low-frequency phases in human iEEG. NeuroImage 54: 836–850.Google Scholar
Mariscal, M. G., Levin, A. R., Gabard-Durnam, L. J., Tager-Flusberg, H., & Nelson, C. A. (2019). Developmental changes in EEG phase amplitude coupling and phase preference over the first three years after birth. bioRxiv. https://doi.org/10.1101/818583Google Scholar
Marler, P. (1998). Animal communication and human language. In Jablonski, N. G. & Aiello, L. C. (eds.). The Origin and Diversification of Language. San Francisco, CA: California Academy of Sciences. 1–19.Google Scholar
Marr, D. (1982). Vision: A Computational Investigation into the Human Representation and Processing of Visual Information. New York: Freeman.Google Scholar
Marr, D. & Poggio, T. (1976). From Understanding Computation to Understanding Neural Circuitry. AI Memos (1959–2004).Google Scholar
Mars, R. B., Eichert, N., Jbabdi, S., Verhagen, L. & Rushworth, M. F. S. (2018). Connectivity and the search for specializations in the language-capable brain. Current Opinion in Behavioral Sciences 21: 19–26.Google Scholar
Martin, A. (2016). Language processing as cue integration: grounding the psychology of language in perception and neurophysiology. Frontiers in Psychology 7: 120.Google Scholar
Martin, A., & Doumas, L. A. A. (2017). A mechanism for the cortical computation of hierarchical linguistic structure. PLoS Biology 15: e2000663.Google Scholar
Martin, C. (2016). The cryptic cortex. Current Biology 26: R941–R945.Google Scholar
Martin, C. & Ravel, N. (2014). Beta and gamma oscillatory activities associated with olfactory memory tasks: different rhythms for different functional networks? Frontiers in Behavioral Neuroscience 8: 218.Google Scholar
Martins, M. D. & Villringer, A. (2018). The human arcuate fasciculus provides specific advantages to process complex sequential stimuli, not hierarchies in general. In Cuskley, C., Flaherty, M., McCrohon, L., Little, H., Ravignani, A., & Verhoef, T. (eds.). The Evolution of Language: Proceedings of the 12th International Conference (Evolang 12). Torun: Nicolaus Copernicus University. 287–289.Google Scholar
Martins, P. T. (2017). There is no place for markedness in biologically-informed phonology. In Samuels, B. D. (ed.). Beyond Markedness in Formal Phonology. Amsterdam: John Benjamins.Google Scholar
Martins, P. T. & Boeckx, C. (2014). Attention mechanisms and the mosaic evolution of speech. Frontiers in Psychology 5: 1463.Google Scholar
Martorell, J. (2018). Merging generative linguistics and psycholinguistics. Frontiers in Psychology 9: 2283.Google Scholar
Martorell, J., Morucci, P., Mancini, S., & Molinaro, N. (2020). Sentence processing: how words generate syntactic structures in the brain. PsyArXiv doi.org/10.31234/osf.io/3utpvGoogle Scholar
Mas-Herrero, E. & Marco-Pallarés, J. (2016). Theta oscillations integrate functionally segregated sub-regions of the medial prefrontal cortex. NeuroImage 143: 166–174.Google Scholar
Matchin, W. (2016). Brain and syntax: part 2. Faculty of Language, 3 September: http://facultyoflanguage.blogspot.co.uk/2016/09/brains-and-syntax-part-2.htmlGoogle Scholar
Matchin, W. (2018). A neuronal retuning hypothesis of sentence-specificity in Broca’s area. Psychonomic Bulletin & Review 25: 1682–1694.Google Scholar
Matchin, W., Hammerly, C., & Lau, E. (2017). The role of the IFG and pSTS in syntactic prediction: Evidence from a parametric study of hierarchical structure in fMRI. Cortex 88: 106–123.Google Scholar
Matchin, W. & Hickok, G. (2016). ‘Syntactic perturbation’ during production activates the right IFG, but not Broca’s area or the ATL. Frontiers in Psychology 7: 241.Google Scholar
Matchin, W. & Hickok, G. (2019). The cortical organization of syntax. To appear in Cerebral Cortex.Google Scholar
Matchin, W., Sprouse, J., & Hickok, G. (2014). A structural distance effect for backward anaphora in Broca’s area: an fMRI study. Brain and Language 138: 1–11.Google Scholar
Matsunaga, E. & Okanoya, K. (2014). Cadherins: potential regulators in the faculty of language. Current Opinion in Neurobiology 28: 28–33.Google Scholar
Mayberry, R. I., Davenport, T., Roth, A., & Halgren, E. (2018). Neurolinguistic processing when the brain matures without language. Cortex 99: 390–403.CrossRefGoogle ScholarPubMed
Mazaheri, A., Coffey-Corina, S., Mangun, G. R., Bekker, E. M., Berry, A. S., & Corbett, B. A. 2010. Functional disconnection of frontal cortex and visual cortex in attention-deficit/hyperactivity disorder. Biological Psychiatry 67: 617–623.Google Scholar
McCauley, S. M., Isbilen, E. S., & Christiansen, M. H. (2017). Chunking ability shapes sentence processing at multiple levels of abstraction. Gunzelmann, G., Howes, A., Tenbrink, T., & Davelaar, E. J. (eds.). Proceedings of the 39th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. 2681–2686.Google Scholar
McCormick, D. A., McGinley, M. J., & Salkoff, D. B. (2015). Brain state dependent activity in the cortex and thalamus. Current Opinion in Neurobiology 31: 133–140.Google Scholar
McGhee, G. (1998). Theoretical Morphology. Columbia University Press.Google Scholar
McGilchrist, I. (2010). The Master and His Emissary: The Divided Brain and the Making of the Western World. Yale University Press.Google Scholar
McGilvray, J. (2013). The philosophical foundations of biolinguistics. In Boeckx, C. & Grohmann, K. (eds.). The Cambridge Handbook of Biolinguistics Cambridge: Cambridge University Press. 22–46.Google Scholar
Medeiros, D. P. (2008). Optimal growth in phrase structure. Biolinguistics 2(3): 152–195.Google Scholar
Meltzoff, A. N. & Moore, M. K. (1997). Explaining facial imitation: a theoretical model. Early Development and Parenting 6: 179–192.Google Scholar
Mendoza, G. & Merchant, H. (2014). Motor system evolution and the emergence of high cognitive functions. Progress in Neurobiology 122: 73–93.Google Scholar
Merchant, J. (2001). The Syntax of Silence: Sluicing, Islands, and the Theory of Ellipsis. Oxford: Oxford University Press.Google Scholar
Mesgarani, N., Cheung, C., Johnson, K., & Chang, E. F. (2014). Phonetic features encoding in human superior temporal gyrus. Science 343: 1006–1010.Google Scholar
Mesulam, M. M, Thompson, C. K., Weintraub, S., & Rogalski, E. J. (2015). The Wernicke conundrum and the anatomy of language comprehension in primary progressive aphasia. Brain 138(8): 2423–2437.Google Scholar
Meyer, L. (2018). The neural oscillations of speech processing and language comprehension: state of the art and emerging mechanisms. European Journal of Neuroscience 48(7): 2609–2621.Google Scholar
Meyer, L. (2019). The neural oscillations of language processing: Examples from German. Talk presented at Public Lecture. University of Georgia, Athens, GA. 2019–02-20–2019–02-20.Google Scholar
Meyer, L., Grigutsch, M., Schmuck, N., Gaston, P., & Friederici, A. D. (2015). Frontal-posterior theta oscillations reflect memory retrieval during sentence comprehension. Cortex 71: 205–218.Google Scholar
Meyer, L. & Gumbert, M. (2018). Synchronization of electrophysiological responses with speech benefits syntactic information processing. Journal of Cognitive Neuroscience 11: 1–9.Google Scholar
Meyer, L., Henry, M. J., Gaston, P., Schmuck, N., & Friederici, A. (2017). Linguistic bias modulates interpretation of speech via neural delta-band oscillations. Cerebral Cortex 7(9): 4293–4302.Google Scholar
Meyer, L., Obleser, J., & Friederici, A. (2013). Left parietal alpha enhancement during working memory-intensive sentence processing. Cortex 49(3): 711–721.Google Scholar
Meyer, L., Sun, Y., & Martin, A. E. (2019). Synchronous, but not entrained: exogenous and endogenous cortical rhythms of speech and language processing. Language, Cognition, and Neuroscience. DOI:10.1080/23273798.2019.1693050Google Scholar
Michelmann, S., Bowman, H., & Hanslmayr, S. (2016). The temporal signature of memories: identification of a general mechanism for dynamic memory replay in humans. PLoS Biology 14(8): e1002528.Google Scholar
Miłkowski, M. (2012). Limits of computational explanation of cognition. In Müller, V. C. (ed.). Philosophy and Theory of Artificial Intelligence. New York: Springer. 69–84.Google Scholar
Miller, I. F., Barton, R. A., & Nunn, C. L. (2019). Quantitative uniqueness of human brain evolution revealed through phylogenetic comparative analysis. eLife 8: e41250.Google Scholar
Miller, K. J., Hermes, D., Honey, C. J., Sharma, M., Rao, R. P., den Nijs, M., Fetz, E. E., Sejnowski, T. J., Hebb, A. O., Ojemann, J. G., Makeig, S., & Leuthardt, E. C. (2010). Dynamic modulation of local population activity by rhythm phase in human occipital cortex during a visual search task. Frontiers in Human Neuroscience 4: 197.Google Scholar
Milne, A. E., Wilson, B., & Christiansen, M. H. (2018). Structured sequence learning across sensory modalities in humans and nonhuman primates. Current Opinion in Behavioral Sciences 21: 39–48.Google Scholar
Mišić, B. & Sporns, O. (2016). From regions to connections and networks: new bridges between brain and behavior. Current Opinion in Neurobiology 40: 1–7.Google Scholar
Mišić, B., Goni, J., Betzel, R. F., Sporns, O., & McIntosh, A. R. (2014). A network convergence zone in the hippocampus. PLoS Computational Biology 10: e1003982.Google Scholar
Mithun, M. (2015). Gender and culture. In Corbett, G. G. (ed.). The Expression of Gender. Berlin: Walter de Gruyter. 131–160.Google Scholar
Miyagawa, S., Berwick, R. C., & Okanoya, K. (2013). The emergence of hierarchical structure in human language. Frontiers in Psychology 4: 71.Google Scholar
Mohammad-Rezazadeh, I., Frohlich, J., Loo, S. K., & Jeste, S. S. (2016). Brain connectivity in autism spectrum disorder. Current Opinion in Neurobiology 29: 137–147.Google Scholar
Mohr, J. P., Pessin, M. S., Finkelstein, S., Funkenstein, H. H., Duncan, G. W., & Davis, K. R. (1978). Broca aphasia: pathologic and clinical. Neurology 28: 311–324.Google Scholar
Molinaro, N. & Lizarazu, M. (2018). Delta(but not theta)-band cortical entrainment involves speech-specific processing. European Journal of Neuroscience 48(7): 2642–2650.Google Scholar
Molinaro, N., Paz-Alonso, P. M., Duñabeitia, J. A., & Carreiras, M. (2015). Combinatorial semantics strengthens angular-anterior temporal coupling. Cortex 65: 113–127.Google Scholar
Mollo, G., Cornelissen, P. L., Millman, R. E., Ellis, A. W., & Jefferies, E. (2017). Oscillatory dynamics supporting semantic cognition: MEG evidence for the contribution of the anterior temporal lobe hub and modality-specific spokes. PLoS ONE 12(1): e0169269.Google Scholar
Molnár, G., Oláh, S., Komlósi, G., Füle, M., Szabadics, J., Varga, C., Barzó, P., & Tamás, G. (2008). Complex events initiated by individual spikes in the human cerebral cortex. PLoS Biology 6(9): e222.Google Scholar
Moltmann, F. (Forthcoming). Levels of ontology and natural language: the case of the ontology of parts and wholes. In Miller, J. (ed). The Language of Ontology. Oxford: Oxford University Press.Google Scholar
Momenian, M., Nilipour, R., Samar, R. G., Oghabian, M. A., & Cappa, S. (2016). Neural correlates of verb and noun processing: an fMRI study of Persian. Journal of Neurolinguistics 37: 12–21.Google Scholar
Momma, S. (2016). Parsing, generation, and grammar. PhD dissertation. University of Maryland.Google Scholar
Montalbetti, M. (1984). After Binding. PhD thesis, MIT.Google Scholar
Montgomery, S. H., Mundy, N. I., & Barton, R. A. (2016). Brain evolution and development: adaptation, allometry and constraint. Proceedings of the Royal Society B 283: 20160433.Google Scholar
Moore, R. (2017). Gricean communication and cognitive development. Philosophical Quarterly 67(267): 303–326.Google Scholar
Moore, R. (2018). Gricean communication, joint action, and the evolution of cooperation. Topoi 37: 329–341.Google Scholar
Moreno, A., Limousin, F., Dehaene, S., & Pallier, C. (2018). Brain correlates of constituent structure in sign language comprehension. NeuroImage 167: 151–161.Google Scholar
Moro, A. (2006). Copular sentences. In Everaert, M. & van Riemsdijk, H. (eds.). The Blackwell Companion to Syntax II. Oxford: Blackwell. 1–23.Google Scholar
Moro, A. (2014). On the similarity between syntax and actions. Trends in Cognitive Sciences 18(3): 109–110.Google Scholar
Moro, A. (2015). The Boundaries of Babel: The Brain and the Enigma of Impossible Languages. 2nd ed. Cambridge, MA: MIT Press.Google Scholar
Morton, N. W., Sherrill, K. R., & Preston, A. R. (2017). Memory integration constructs maps of space, time, and concepts. Current Opinion in Behavioral Sciences 17: 161–168.Google Scholar
Müller, F. M. (1866). Lectures on the Science of Language: Delivered at the Royal Institution of Great Britain in April, May, & June 1861. London: Longmans, Green.Google Scholar
Müller, G. B. (2008). EvoDevo as a discipline. In Minelli, A. & Fusco, G. (eds.). Evolving Pathways: Key Themes in Evolutionary Developmental Biology. Cambridge: Cambridge University Press. 3–29.Google Scholar
Muller, L., Chavane, F., Reynolds, J., & Sejnowski, T. J. (2018). Cortical travelling waves: mechanisms and computational principles. Nature Reviews Neuroscience 19: 255–268.Google Scholar
Murakami, S. & Okada, Y. (2006). Contributions of principal neocortical neurons to magnetoencephalography and electroencephalography signals. Journal of Physiology 575: 925–936.Google Scholar
Murphy, E. (2015a). Labels, cognomes and cyclic computation: an ethological perspective. Frontiers in Psychology 6: 715.Google Scholar
Murphy, E. (2015b). The brain dynamics of linguistic computation. Frontiers in Psychology 6: 1515.Google Scholar
Murphy, E. (2016a). A theta-gamma neural code for feature set composition with phase-entrained delta nestings. UCL Working Papers in Linguistics 28: 1–23.Google Scholar
Murphy, E. (2016b). Evolutionary monkey oscillomics: generating linking hypotheses from preserved brain rhythms. Theoretical Linguistics 42(1–2): 117–137.Google Scholar
Murphy, E. (2016c). The human oscillome and its explanatory potential. Biolinguistics 10: 6–20.Google Scholar
Murphy, E. (2016d). A pragmatic oscillome: aligning visual attentional mechanisms with language comprehension. Frontiers in Systems Neuroscience 10: 72.Google Scholar
Murphy, E. (2017a). Acquiring the impossible: developmental stages of copredication. Frontiers in Psychology 8: 1072.Google Scholar
Murphy, E. (2017b). Implications of travelling weakly coupled oscillators for the cortical language circuit. UCL Working Papers in Linguistics 29: 24–29.Google Scholar
Murphy, E. (2018a). A domesticated code: on the emergence of the oscillatory basis of phrase structure. Cuskley, C., Flaherty, M., McCrohon, L., Little, H., Ravignani, A., & Verhoef, T. (eds.). The Evolution of Language: Proceedings of the 12th International Conference (Evolang 12). Torun: Nicolaus Copernicus University. 335–338.Google Scholar
Murphy, E. (2018b). Interfaces (travelling oscillations) + recursion (delta-theta code) = language. In Luef, E. & Manuela, M. (eds.). The Talking Species: Perspectives on the Evolutionary, Neuronal and Cultural Foundations of Language. Graz: Unipress Graz Verlag. 251–269.Google Scholar
Murphy, E. (2019). No country for Oldowan men: emerging factors in language evolution. Frontiers in Psychology 10: 1448.Google Scholar
Murphy, E. & Benítez-Burraco, A. (2016). Bridging the gap between genes and language deficits in schizophrenia: an oscillopathic approach. Frontiers in Human Neuroscience 10: 422.Google Scholar
Murphy, E. & Benítez-Burraco, A. (2017). Language deficits in schizophrenia and autism as related oscillatory connectomopathies: an evolutionary account. Neuroscience and Biobehavioral Reviews 83: 742–764.Google Scholar
Murphy, E. & Benítez-Burraco, A. (2018). Paleo-oscillomics: inferring aspects of Neanderthal language abilities from gene regulation of neural oscillations. Journal of Anthropological Sciences 96: 111–124.Google Scholar
Murphy, E., & Shim, J.-Y. (2020). Copy invisibility and (non)categorial labeling. Linguistic Research 33(1): 177–198.Google Scholar
Muthukumaraswamy, S. D., Edden, R. A. E., Jones, D. K., Swettenham, J. B., & Singh, K. D. (2009). Resting GABA concentration predicts peak gamma frequency and fMRI amplitude in response to visual stimulation in humans. PNAS 106: 8356–8361.Google Scholar
Nadeau, S. E. & Crosson, B. (1997). Subcortical aphasia. Brain and Language 58: 355–402, discussion 418–423.Google Scholar
Najjar, R. & Brooker, R. J. (2017). Delta-beta coupling is associated with paternal caregiving behaviors during preschool. International Journal of Psychophysiology 112: 31–39.Google Scholar
Nandi, B., Swiatek, P., Kocsis, B., & Ding, M. (2019). Inferring the direction of rhythmic neural transmission via inter-regional phase-amplitude coupling (ir-PAC). Scientific Reports 9: 6933.Google Scholar
Narita, H. (2009). Full interpretation of optimal labeling. Biolinguistics 3(2–3): 213–254.Google Scholar
Narita, H. (2011). Phasing in full interpretation. PhD thesis, Harvard University.Google Scholar
Narita, H. (2012). Phase cycles in service of projection-free syntax. In Gallego, Á. J. (ed.). Phases: Developing the Framework. Boston: Walter de Gruyter. 125–172.Google Scholar
Narita, H. (2014a). Endocentric Structuring of Projection-free Syntax. Amsterdam: John Benjamins.Google Scholar
Narita, H. (2014b). *{t, t}. Poster presented at the 32nd West-Coast Conference on Formal Linguistics (WCCFL 32), University of Southern California.Google Scholar
Narita, H. & Fujita, K. (2010). A naturalist reconstruction of minimalist and evolutionary biolinguistics. Biolinguistics 4(4): 356–376.Google Scholar
Narita, H. & Fujita, K. (2016). Feature-equilibria in syntax. In Fujita, K. & Boeckx, C. (eds.). Advances in Biolinguistics: The Human Language Faculty and its Biological Basis. London: Routledge. 20–50.Google Scholar
Narita, H., Kasai, H., Kato, T., Zushi, M., & Fukui, N. (2017). 0-Search and 0-Merge. In Fukui, N. (ed.). Merge in the Mind-Brain. New York: Routledge. 127–154.Google Scholar
Neeleman, A. (2013). Comments on Pullum. Mind & Language 28(4): 522–531.Google Scholar
Nelson, M. J., Karoui, I. E., Giber, K., Yang, X., Cohen, L., Koopman, H., Cash, S. S., Naccache, L., Hale, J. T., Pallier, C., & Dehaene, S. (2017). Neurophysiological dynamics of phrase-structure building during sentence processing. PNAS 114(18): E3669–E3678.Google Scholar
Neubauer, A. C. & Fink, A. (2009). Intelligence and neural efficiency. Neuroscience and Biobehavioral Reviews 33: 1004–1023.Google Scholar
Neubauer, S., Hublin, J-J., & Gunz, P. (2018). The evolution of modern human brain shape. Science Advances 4: eaao5961.Google Scholar
Neubert, F. X., Mars, R. B., Sallet, J., & Rushworth, M. F. (2015). Connectivity reveals relationship of brain areas for reward-guided learning and decision making in human and monkey frontal cortex. PNAS 112: E2695–E2704.Google Scholar
Neuper, C., Wortz, M., & Pfurtscheller, G. (2006). ERD/ERS patterns reflecting sensorimotor activation and deactivation. Progress in Brain Research 159: 211–222.Google Scholar
Nevins, A. (2010). Two case studies in phonological universals: a view from artificial grammars. Biolinguistics 4: 218–233.Google Scholar
Nevins, A. (2016). Lectures on postsyntactic morphology. Ms. University College London.Google Scholar
Newman, S. A., Forgacs, G., & Müller, G. D. (2006). Before programs: the physical origination of multicellular forms. International Journal of Developmental Biology 50: 289–299.Google Scholar
Newton, I. (1687). Philosophiae Naturalis Principia Mathematica. London.Google Scholar
Neymotin, S. A., Lazarewicz, M. T., Sherif, M., Contreras, D., Finkel, L. H., & Lytton, W. W. (2011). Ketamine disrupts theta modulation of gamma in a computer model of hippocampus. Journal of Neuroscience 31(32): 11733–11743.Google Scholar
Neymotin, S. A., Lee, H., Park, E., Fenton, A. A., & Lytton, W. W. (2011). Emergence of physiological oscillation frequencies in a computer model of neocortex. Frontiers in Computational Neuroscience 5: 19.Google Scholar
Nieuwland, M. S. & Martin, A. E. (2017). Neural oscillations and a nascent corticohippocampal theory of reference. Journal of Cognitive Neuroscience 29(5): 896–910.Google Scholar
Ninomiya, T., Dougherty, K., Godlove, D. C., Schall, J. D., & Maier, A. (2015). Microcircuitry of a granular frontal cortex: contrasting laminar connectivity between occipital and frontal areas. Journal of Neurophysiology 113: 3242–3255.Google Scholar
Noguchi, Y. & Kakigi, R. (2020). Temporal codes of visual working memory in the human cerebral cortex. bioRxiv doi.org/10.1101/2020.04.26.062752Google Scholar
Nosarti, C., Rushe, T. M., Woodruff, P. W. R., Stewart, A. L., Rifkin, L., & Murray, R. M. (2004). Corpus callosum size and very preterm birth: relationship to neuropsychological outcome. Brain 127: 2080–2089.Google Scholar
Noser, R. & Byrne, R. W. (2015). Wild chacma baboons (Papio ursinus) remember single foraging episodes. Animal Cognition 18(4): 921–929.Google Scholar
Novick, J. M., Trueswell, J. C., & Thompson-Schill, S. L. (2010). Broca’s area and language processing: evidence for the cognitive control connection. Language and Linguistics Compass 4: 906–924.Google Scholar
Nusbaum, M. P. & Beenhakker, M. P. (2002). A small-systems approach to motor pattern generation. Nature 417(6886): 343–350.Google Scholar
O’Keefe, J. & Nadal, L. (1978). The Hippocampus as a Cognitive Map. Oxford: Oxford University Press.Google Scholar
O’Meara, D. J. (ed.). (1981). Neoplatonism and Christian Thought. Albany, NY: State University of New York Press.Google Scholar
O’Neill, J., Boccara, C. N., Stella, F., Schoenenberger, P., & Csicsvari, J. (2017). Superficial layers of the medial entorhinal cortex replay independently of the hippocampus. Science 355: 184–188.Google Scholar
Odden, D. (1986). On the role of the Obligatory Contour Principle in phonological theory. Language 62: 353–383.Google Scholar
Oettler, J., Schmid, V. S., Zankl, N., Rey, O., Dress, A., & Heinze, J. (2013). Fermat’s principle of least time predicts refraction of ant trails at substrate borders. PLoS ONE 8(3): e59739.Google Scholar
Ohira, T. & Uzawa, T. (eds.) (2015). Mathematical Approaches to Biological Systems: Networks, Oscillations, and Collective Motions. New York: Springer.Google Scholar
Ohki, T., Gunji, A., Takei, Y., Takahashi, H., Kaneko, Y., Kita, Y., Hironaga, N., Tobimatsu, S., Kamio, Y., Hanakawa, T., Inagaki, M., & Hiraki, K. (2016). Neural oscillations in the temporal pole for a temporally congruent audio-visual speech detection task. Scientific Reports 6: 37973.Google Scholar
Ohki, T. & Takei, Y. (2018). Neural mechanisms of mental schema: a triplet of delta, low beta/spindle, and ripple. European Journal of Neuroscience 48(7): 2416–2430.Google Scholar
Ohta, S., Fukui, N., & Sakai, K. (2013). Syntactic computation in the human brain: the degree of merger as a key factor. PLoS ONE 8(2): e56230.Google Scholar
Ojemann, G. A. (1990). Organization of language cortex derived from investigations during neurosurgery. Seminars in Neuroscience 2: 297–306.Google Scholar
Ojima, S. & Okanoya, K. (2014). The non-hierarchical nature of the Chomsky hierarchy-driven artificial-grammar learning. Biolinguistics 8: 163–180.Google Scholar
Okanoya, K. (2012). Behavioural factors governing song complexity in Bengalese finches. International Journal of Comparative Psychology 25(1): 44–59.Google Scholar
Okanoya, K. (2013). Finite-state song syntax in Bengalese finches: sensorimotor evidence, developmental processes, and formal procedures for syntax extraction. In Bolhuis, J. J. & Everaert, M. (eds.). Birdsong, Speech, and Language: Exploring the Evolution of Mind and Brain. Cambridge, MA: MIT Press. 229–242.Google Scholar
Okanoya, K. & Merker, B. (2007). Neural substrates for string-context mutual segmentation: a path to human language. In Lyon, C., Nehaniv, C. L., & Cangelosi, A. (eds.). Emergence of Communication and Language. London: Springer. 421–434.Google Scholar
Onton, J., Delorme, A., & Makeig, S. (2005). Frontal midline EEG dynamics during working memory. NeuroImage 27: 341–356.Google Scholar
Oseki, Y. (2015). Eliminating pair-Merge. Proceedings of WCCFL 32: 303–312.Google Scholar
Oseki, Y. & Marantz, A. (2017). Hierarchical vs. linear syntactic models of morphological processing. Poster presented at the 30th CUNY Conference on Human Sentence Processing, Massachussets Institute of Technology.Google Scholar
Ossandón, T., Jerbi, K., Vidal, J. R., Bayle, D. J., Henaff, M. A., Jung, J., Minotti, L., Bertrand, O., Kahane, P., & Lachaux, J. P. (2011). Transient suppression of broadband gamma power in the default-mode network is correlated with task complexity and subject performance. Journal of Neuroscience 31: 14521–14530.Google Scholar
Ota, M. & Skarabela, B. (2016). Reduplicated words are easier to learn. Language Learning and Development 12: 380–397.Google Scholar
Ota, M. & Skarabela, B. (2018). Reduplication facilitates early word segmentation. Journal of Child Language 45(1): 204–218.Google Scholar
Ott, D. (2017). Strong generative capacity and the empirical base of linguistic theory. Frontiers in Psychology 8: 1617.Google Scholar
Ouattara, K., Lemasson, A., & Zuberbühler, K. (2009). Campbell’s monkeys concatenate vocalizations into context-specific call sequences. PNAS 106: 22026–31.Google Scholar
Overath, T., McDermott, J. H., Zarate, J. M., & Poeppel, D. (2015). The cortical analysis of speech-specific temporal structure revealed by responses to sound quilts. Nature Neuroscience 18(6): 903–911.Google Scholar
Pääbo, S. (2014). The human condition – a molecular approach. Cell 157: 216–226.Google Scholar
Pajevic, S., Basser, P. J., & Fields, R. D. (2014). Role of myelin plasticity in oscillations and synchrony of neuronal activity. Neuroscience 276: 135–147.Google Scholar
Palmer, C., Zapparoli, L., & Kilner, J. M. (2016). A new framework to explain sensorimotor beta oscillations. Trends in Cognitive Sciences 20(5): 321–323.Google Scholar
Palomero-Gallagher, N. & Zilles, K. (2019). Differences in cytoarchitecture of Broca’s region between human, ape and macaque brains. Cortex 118: 132–153.Google Scholar
Palva, J. M. & Palva, S. (2018). Functional integration across oscillation frequencies by cross-frequency phase synchronization. European Journal of Neuroscience 48(7): 2399–2406.Google Scholar
Panagiotidis, P. (2014). A minimalist approach to roots. In Kosta, P., Schürcks, L., Franks, S., & Radeva-Bork, T. (eds.). Minimalism and Beyond: Radicalizing the Interfaces. Amsterdam: John Benjamins. 287–303.Google Scholar
Panagiotidis, P. (2015). Categorial Features: A Generative Theory of Word Class Categories. Cambridge: Cambridge University Press.Google Scholar
Panoz-Brown, D., Corbin, H. E., Dalecki, S. J., Gentry, M., Brotheridge, S., Sluka, C. M., Wu, J-E., & Crystal, J. D. (2016). Rats remember items in context using episodic memory. Current Biology 26: 2821–2826.Google Scholar
Panzeri, S., Harvey, C. D., Piasini, E., Latham, P. E., & Fellin, T. (2017). Cracking the neural code for sensory perception by combining statistics, intervention, and behavior. Neuron 93: 491–507.Google Scholar
Papadimitriou, C. H., & Vempala, S. S. (2019). Random projection in the brain and computation with assemblies of neurons. Blum, A. (Ed). Leibniz International Proceedings in Informatics 57: 1–19.Google Scholar
Papathanasiou, I., & Coppens, P.(2017). Aphasia and Related Neurogenic Communication Disorders. 2nd ed. Burlington, MA: Jones & Bartlett Publishers.Google Scholar
Park, H., Ince, R. A. A., Schyns, P. G., Thut, G., & Gross, J. (2018). Representational interactions during audiovisual speech entrainment: redundancy in left posterior superior temporal gyrus and synergy in left motor cortex. PLoS Biology 16(8): e2006558.Google Scholar
Park, H., Lee, D. S., Kang, E., Kang, H., Hahm, J., Kim, J. S., Chung, C. K., Jiang, H., Gross, J., & Jensen, O. (2016). Formation of visual memories controlled by gamma power phrase-locked to alpha oscillations. Scientific Reports 6: 28092.Google Scholar
Parker, S. T. & McKinney, M. L. (1999). Origins of Intelligence: The Evolution of Cognitive Development in Monkeys, Apes, and Humans. Baltimore, MD: Johns Hopkins University Press.Google Scholar
Parnaudeau, S., O’Neill, P. K., Bolkan, S. S., Ward, R. D., Abbas, A. I., Roth, B. L., Balsam, P. D., Gordon, J. A. & Kellendonk, C. (2013). Inhibition of mediodorsal thalamus disrupts thalamofrontal connectivity and cognition. Neuron 77: 1151–1162.Google Scholar
Pascanu, R. & Jaeger, H. (2011). A neurodynamical model for working memory. Neural Networks 24(2): 199–207.Google Scholar
Pattamadilok, C., Dehaene, S., & Pallier, C. (2016). A role for left inferior frontal and posterior superior temporal cortex in extracting a syntactic tree from a sentence. Cortex 75: 44–55.Google Scholar
Patten, T. M., Rennie, C. J., Robinson, P. A., & Gong, P. (2012). Human cortical traveling waves: dynamical properties and correlations with responses. PLoS ONE 7: e38392.Google Scholar
Pearce, E., Stringer, C., & Dunbar, R. I. M. (2013). New insights into differences in brain organization between Neanderthals and anatomically modern humans. Proceedings of the Royal Society B 280: 20130168.Google Scholar
Pearson, J. (1790). A Plain and Rational Account of the Nature and Effects of Animal Magnetism: in a Series of Letters. With Notes and an Appendix. By the editor. Eighteenth Century Collections Online, London.Google Scholar
Peelle, J. E. & Davis, M. H. (2012). Neural oscillations carry speech rhythm through to comprehension. Frontiers in Psychology 3: 320.Google Scholar
Peelle, J. E., Gross, J., & Davis, M. H. (2013). Phase-locking responses to speech in human auditory cortex are enhanced during comprehension. Cerebral Cortex 23: 1378–1387.Google Scholar
Pefkou, M., Arnal, L. H., Fontolan, L., & Giraud, A.-L. (2017). Theta- and beta-band neural activity reflect independent syllable tracking and comprehension of time-compressed speech. Journal of Neuroscience 37(33): 7930–7938.Google Scholar
Penn, D. C., Holyoak, K. J., & Povinelli, D. J. (2008). Darwin’s mistake: Explaining the discontinuity between human and nonhuman minds. Behavioral and Brain Sciences 31(2): 109–178.Google Scholar
Pepperberg, I. M. (2007). Emergence of linguistic communication: studies on grey parrots. In Lyon, C., Nehaniv, C. L., & Cangelosi, A. (eds.). Emergence of Communication and Language. London: Springer. 355–386.Google Scholar
Perani, D., Saccuman, M. C., Scifo, P., Anwander, A., Spada, D., Baldoli, C., Poloniato, A., Lohmann, G., & Friederici, A. D. (2011). Neural language networks at birth. PNAS 108: 16056–16061.Google Scholar
Perdomo-Sabotal, A., Kanton, S., Walter, M. B., & Nowick, K. (2014). The role of gene regulatory factors in the evolutionary history of humans. Current Opinion in Genetics & Development 29 C: 60–67.Google Scholar
Perrodin, C., Kayser, C., Logothetis, N. K., & Petkov, C. I. (2015). Natural asynchronies in audiovisual communication signals regulate neuronal multisensory interactions in voice-sensitive cortex. PNAS 112: 273–278.Google Scholar
Pesaran, B., Nelson, M. J., & Andersen, R. A. (2008). Free choice activates a decision circuit between frontal and parietal cortex. Nature 453: 406–409.Google Scholar
Pessoa, L. (2016). Beyond disjoint brain networks: overlapping networks for cognition and emotion. Behavioral and Brain Sciences 39: e120.Google Scholar
Petersen, S. E. & Sporns, O. (2015). Brain networks and cognitive architectures. Neuron 88: 207–219.Google Scholar
Petersson, K. M. & Hagoort, P. (2012). The neurobiology of syntax: beyond string sets. Philosophical Transactions of the Royal Society B 367: 1971–1983.Google Scholar
Petersson, K. M., Folia, V., & Hagoort, P. (2012). What artificial grammar learning reveals about the neurobiology of syntax. Brain & Language 120(2): 83–95.Google Scholar
Petkov, C. I., Kayser, C., Steudel, T., Whittingstall, K., Augath, M., & Logothetis, N. K. (2008). A voice region in the monkey brain. Nature Neuroscience 11: 367–374.Google Scholar
Petrides, M. & Pandya, D. N. (2009). Distinct parietal and temporal pathways to the homologues of Broca’s area in the monkey. PLoS Biology 7: e1000170.Google Scholar
Pérez, A., Molinaro, N., Mancini, S., Barraza, P., & Carreiras, M. (2012). Oscillatory dynamics related to the Unagreement pattern in Spanish. Neuropsychologia 50(11): 2584–2597.Google Scholar
Pezzulo, G. & Levin, M. (2017). Embodying Markov blankets. Comment on ‘Answering Schrödinger’s question: Afree-energy formulation’ by Maxwell James Désormeau Ramstead et al. Physics of Life Reviews.https://doi.org/10.1016/j.plrev.2017.09.001Google Scholar
Pfenning, A. R., Hara, E., Whitney, O., Rivas, M. V., Wang, R., Roulhac, P. L., Howard, J. T., Wirthlin, M., Lovell, P. V., Ganapathy, G. et al. (2014). Convergent transcriptional specializations in the brains of humans and song-learning birds. Science 346(6215): 1256846.Google Scholar
Phillips, C. (2003). Linear order and constituency. Linguistic Inquiry 34: 37–90.Google Scholar
Piai, V., Meyer, L., Dronkers, N. F., & Knights, R. T. (2016). Neuroplasticity of language in left-hemisphere stroke: evidence linking subsecond electrophysiology and structural connectivity. Poster presented at the Society for the Neurobiology of Language Annual Meeting 2016. 17–20 August.Google Scholar
Piattelli-Palmarini, M. (1974). A Debate on Bio-linguistics, Endicott House, Dedham, MA (May 20–21, 1974). Paris: Centre Royaumont pour une Science de l’Homme.Google Scholar
Piattelli-Palmarini, M. (1989). Evolution, selection, and cognition: from ‘learning’ to parameter setting in biology and in the study of language. Cognition 31: 1–44.Google Scholar
Piattelli-Palmarini, M. (2017). From zero to fifty: considerations on Eric Lenneberg’s Biological Foundations of Language and updates. Biolinguistics 11.SI.Google Scholar
Piattelli-Palmarini, M., & Uriagereka, J.(2008). Still a bridge too far? Biolinguistic questions for grounding language on brains. Physics of Life Reviews 5: 207–224.Google Scholar
Piattelli-Palmarini, M. & Vitiello, G.(2015). Linguistics and some aspects of its underlying dynamics. Biolinguistics 9: 96–115Google Scholar
Piattelli-Palmarini, M. & Vitiello, G. (2017). Quantum field theory and the linguistic minimalist program: a remarkable isomorphism. Journal of Physics: Conference Series 880(1): 012016.Google Scholar
Pietroski, P. (2002). Function and concatenation. In Preyer, G. & Peter, G. (eds.). Logical Form and Language. Oxford: Oxford University Press. 91–117.Google Scholar
Pietroski, P. (2005). Events and Semantic Architecture. Oxford: Oxford University Press.Google Scholar
Pietroski, P. (2008). Minimalist meaning, internalist interpretation. Biolinguistics 2(4): 317–341.Google Scholar
Pietroski, P. (2018). Conjoining Meanings: Semantics without Truth Values. Oxford: Oxford University Press.Google Scholar
Pigliucci, M. & Müller, G. B. (2010). Elements of an extended evolutionary synthesis. In Pigliucci, M. & Müller, G. B. (eds.). Evolution – The Extended Synthesis. Cambridge, MA: MIT Press. 3–17.Google Scholar
Pignatelli, M., Beyeler, A., & Leinekugel, X. (2012). Neural circuits underlying the generation of theta oscillations. Journal of Physiology-Paris 106: 81–92.Google Scholar
Pika, S. & Bugnyar, T. (2011). The use of referential gestures in ravens (Corvus corax) in the wild. Nature Communications 2: 560.Google Scholar
Pillay, S. B., Binder, J. R., Humphries, C., Gross, W. L., & Book, D. S. (2017). Lesion localization of speech comprehension deficits in chronic aphasia. Neurology 88: 970–975.Google Scholar
Pina, J. E., Bodner, M., & Ermentrout, B. (2018). Oscillations in working memory and neural binding: a mechanism for multiple memories and their interactions. PLoS Computational Biology 14(11): e1006517.Google Scholar
Pinker, S. (1999). How the Mind Works. New York: W. W. Norton & Company.Google Scholar
Pinker, S. (2015). Language, Cognition, and Human Nature: Selected Articles. Oxford: Oxford University Press.Google Scholar
Pinker, S. & Bloom, P. (1990). Natural language and natural selection. Behavioral and Brain Sciences 13: 707–784.Google Scholar
Pinotsis, D. A., Buschman, T. J., & Miller, E. K. (2019). Working memory load modulates neuronal coupling. Cerebral Cortex 29(4): 1670–1681.Google Scholar
Plato. (1945). The Republic of Plato. Trans. F. M. Cornford. Oxford: Oxford University Press.Google Scholar
Poeppel, D. (1996). Neurobiology and linguistics are not yet unifiable. Behavioral and Brain Sciences 19: 642–643.Google Scholar
Poeppel, D. (2008). The cartographic imperative: confusing localization and explanation in human brain mapping. In Bildwelten des Wissens: Vol. 6.1. Bildwelten des wissens. Akademie Verlag, Berlin, Germany. 13.Google Scholar
Poeppel, D. (2011). Genetics and language: a neurobiological perspective on the missing link(-ing hypothesis). Journal of Neurodevelopmental Disorders 3(4): 381–387.Google Scholar
Poeppel, D. (2012). The maps problem and the mapping problem: two challenges for a cognitive neuroscience of speech and language. Cognitive Neuropsychology 29: 34–55.Google Scholar
Poeppel, D. (2014). The neuroanatomic and neurophysiological infrastructure for speech and language. Current Opinion in Neurobiology. 28 C, 142–149.Google Scholar
Poeppel, D. (2017). The influence of Chomsky on the neuroscience of language. In McGilvray, J. (ed.). The Cambridge Companion to Chomsky. 2nd ed. Cambridge: Cambridge University Press. 155–174.Google Scholar
Poeppel, D. & Assaneo, M. F. (2020). Speech rhythms and their neural foundations. Nature Neuroscience. https://doi.org/10.1038/s41583-020-0304-4Google Scholar
Poeppel, D. & Embick, D. (2005). Defining the relation between linguistics and neuroscience. In Cutler, A. (ed.). Twenty-First Century Psycholinguistics: Four Cornerstones. New Jersey: Lawrence Erlbaum. 103–118.Google Scholar
Postle, B. R. (2006). Working memory as an emergent property of the mind and brain. Neuroscience 139: 23–38.Google Scholar
Poulisse, C., Wheeldon, L., & Segaert, K. (2019). Evidence against preserved syntactic comprehension in healthy aging. Journal of Experimental Psychology: Learning, Memory and Cognition 45(12): 2290–2308.Google Scholar
Powys, J. C. ([1951]2007). Porius: A Romance of the Dark Ages. Bond, J. & Krisdóttir, M. (eds.). London: Overlook Duckworth.Google Scholar
Pratt, J., Dawson, N., Morris, B. J., Grent-‘t-Jong, T., Roux, F., & Uhlhaas, P. J. (2017). Thalamo-cortical communication, glutamatergic neurotransmission and neural oscillations: a unique window into the origins of ScZ? Schizophrenia Research 180: 4–12.Google Scholar
Price, C. J. (2010). The anatomy of language: a review of 100 fMRI studies published in 2009. Annals of the New Yorks Academy of Sciences 119: 62–88.Google Scholar
Prindle, A., Liu, J., Asally, M., Ly, S., Garcia-Ojalvo, J., & Süel, G. M. (2015). Ion channels enable electrical communication in bacterial communities. Nature 527: 59–63.Google Scholar
Proskovec, A. L., Heinrichs-Graham, E., & Wilson, T. W. (2019). Load modulates the alpha and beta oscillatory dynamics serving verbal working memory. NeuroImage 184: 256–265.Google Scholar
Prystauka, Y. & Lewis, A. G. (2019). The power of neural oscillations to inform sentence comprehension: a linguistic perspective. Language and Linguistics Compass 13: e12347.Google Scholar
Pu, Y., Cheyne, D., Sun, Y., & Johnson, B. W. (2020). Theta oscillations support the interface between language and memory. NeuroImage 215: 116782.Google Scholar
Pulvermüller, F. (2014). The syntax of action. Trends in Cognitive Sciences 18(5): 219–220.Google Scholar
Pulvermüller, F., Preissl, H., Eulitz, C., Pantev, C., Lutzenberger, W., Elbert, T., & Birbaumer, N. (1994). Brain rhythms, cell assemblies and cognition: evidence from the processing of words and pseudowords. Psycoloquy 5(48): 1–30.Google Scholar
Pylkkänen, L. (2019). The neural basis of combinatory syntax and semantics. Science 366: 62–66.Google Scholar
Pylyshyn, Z. W. (1984). Computation and Cognition. Cambridge, MA: MIT Press.Google Scholar
Quax, S., Jensen, O., & Tiesinga, P. (2017). Top-down control of cortical gamma-band communication via pulvinar induced phase shifts in the alpha rhythm. PLoS Computational Biology 13(5): e1005519.Google Scholar
Quian Quiroga, R. (2012). Concept cells: the building blocks of declarative memory functions. Nature Reviews Neuroscience 13: 587–597.Google Scholar
Quian Quiroga, R., Kraskov, A., Koch, C. & Fried, I. (2009). Explicit encoding of multimodal percepts by single neurons in the human brain. Current Biology 19: 1308–1313.Google Scholar
Quian Quiroga, R., Reddy, L., Kreiman, G., Koch, C., & Fried, I. (2005). Invariant visual representation by single neurons in the human brain. Nature 435: 1102–1107.Google Scholar
Raghavachari, S., Kahana, M. J., Rizzuto, D. S., Caplan, J. B., Kirschen, M. P, Bourgeois, B., Madsen, J. R., & Lisman, J. E. (2001). Gating of human theta oscillations by a working memory task. Journal of Neuroscience 21(9): 3175–3183.Google Scholar
Raichle, M. E, MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001). A default mode of brain function. PNAS 98: 676–682.Google Scholar
Rakic, P. & Kornack, D. R. (2001). Neocortical expansion and elaboration during primate evolution. In Falk, D. & Gibson, K. R. (eds.). Evolutionary Anatomy of the Primate Cerebral Cortex. Cambridge: Cambridge University Press. 30–56.Google Scholar
Ramirez-Villegas, J. F., Logothetis, N. K., & Besserve, M. (2015). Sharp wave-ripple complexes in a reduced model of the hippocampal CA3-CA1 network of the macaque monkey. BMC Neuroscience 16(Suppl 1): P15.Google Scholar
Ramkumar, P., Acuna, D. E., Berniker, M., Grafton, S. T., Turner, R. S., & Kording, K. P. (2016). Chunking as the result of an efficiency computation trade-off. Nature Communications 7: 12176.Google Scholar
Räsänen, O., Doyle, G., & Frank, M. C. (2017). Pre-linguistic segmentation of speech into syllable-like units. Cognition 171: 130–150.Google Scholar
Rauschecker, J. P. (1998). Cortical processing of complex sounds. Current Opinion in Neurobiology 8: 516–521.Google Scholar
Rauschecker, J. P. (2018). Where did language come from? Precursor mechanisms in nonhuman primates. Current Opinion in Behavioral Sciences 21: 195–204.Google Scholar
Ravignani, A., Bowling, D. L., & Fitch, W. T. (2014). Chorusing, synchrony, and the evolutionary functions of rhythm. Frontiers in Ecology and Evolution 5: 1118.Google Scholar
Ravignani, A. & Norton, P. (2017). Measuring rhythmic complexity: a primer to quantify and compare temporal structure in speech, movement, and animal vocalizations. Journal of Language Evolution 2(1): 4–19.Google Scholar
Ravignani, A., Thompson, B., & Filippi, P. (2018). The evolution of musicality: what can be learned from language evolution research? Frontiers in Neuroscience 12: 20.Google Scholar
Ray, S. & Maunsell, J. H. R. (2015). Do gamma oscillations play a role in cerebral cortex? Trends in Cognitive Sciences 19(2): 78–85.Google Scholar
Rayner, K., Pollatsek, A., Ashby, J., & Clifton, C. Jr. (2012). Psychology of Reading. 2nd ed. New York: Psychology Press.Google Scholar
Reale, M. E., Webb, I. C., Wang, X., Baltazar, R. M., Coolen, L. M., & Lehman, M. N. (2013). The transcription factor Runx2 is under circadian control in the suprachiasmatic nucleus and functions in the control of rhythmic behavior. PLoS ONE 8: e54317.Google Scholar
Reboul, A. C. (2015). Why language really is not a communication system: a cognitive view of language evolution. Frontiers in Psychology 6: 1434.Google Scholar
Reboul, A. (2017). Cognition and Communication in the Evolution of Language. Oxford: Oxford University Press.Google Scholar
Regel, S., Meyer, L., & Gunter, T. C. (2014). Distinguishing neurocognitive processes reflected by P600 effects: evidence from ERPs and neural oscillations. PLoS ONE 9(5): e96840.Google Scholar
Reimann, M. W., Muller, E. B., Ramaswamy, S., & Markram, H. (2015). An algorithm to predict the connectome of neural microcircuits. Frontiers in Neural Circuits 9: 28.Google Scholar
Reinhart, T. (2002). The theta system: an overview. Theoretical Linguistics 28: 229–290.Google Scholar
Reiss, C. (2003). Quantification in structural descriptions: attested and unattested patterns. Linguistic Review 20: 305–338.Google Scholar
Revonsuo, A. (2001). On the nature of explanation in the neurosciences. In Machamer, P. K., Grush, R., & McLaughlin, P. (eds.). Theory and Method in the Neurosciences. Pittsburgh, PA: University of Pittsburgh Press. 45–69.Google Scholar
Richards, M. (2011). Deriving the edge: what’s in a phase? Syntax 14: 74–95.Google Scholar
Richards, N. (2010). Uttering Trees. Cambridge, MA: MIT Press.Google Scholar
Richter, C., Thompson, W. H., Bosman, C. A., & Fries, P. (2017). Top-down beta enhances bottom-up gamma. The Journal of Neuroscience 37(28): 6698–6711.Google Scholar
Riddle, J., McFerren, A., & Frohlich, F. (2019). Causal evidence for delta-beta and theta-gamma cross-frequency coupling in different dimensions of cognitive control. Poster presented at the 49th Meeting of the Society for Neuroscience, Chicago, 19–23 October.Google Scholar
Riddle, J., Scimeca, J. M., Cellier, D., Dhanani, S., & D’Esposito, M. (2020). Causal evidence for a role of theta and alpha oscillations in the control of working memory. Current Biology 30: 1–7.Google Scholar
Riebel, K. & Slater, P. J. B. (2003). Temporal variation in male chaffinch song depends on the singer and the song type. Behaviour 140: 269–288.Google Scholar
Riecke, L., Formisano, E., Sorger, B., Baskent, D., & Gaudrain, E.(2018). Neural entrainment to speech modulates speech intelligibility. Current Biology. 28: 161–169.Google Scholar
Rieke, F., Warland, D., van Steveninck, R. D. R., & Bialek, W. (1997). Spikes: Exploring the Neural Code. Cambridge, MA: MIT Press.Google Scholar
Rimmele, J. M., Sun, Y., Michalareas, G., Ghitza, O., & Poeppel, D. (2019). Dynamics of functional networks for syllable and word-level processing. bioRxiv 584375. https://doi.org/10.1101/584375Google Scholar
Rizzi, L. (2012). Core linguistic computations: how are they expressed in the mind/brain? Journal of Neurolinguistics 25: 489–499.Google Scholar
Rizzi, L. (2016). Monkey morpho-syntax and merge-based systems. Theoretical Linguistics 42(1–2): 139–145.Google Scholar
Rizzuto, D. S., Madsen, J. R., Bromfield, E. B., Schulze-Bonhage, A., & Kahana, M. J. (2006). Human neocortical oscillations exhibit theta phase differences between encoding and retrieval. NeuroImage 31: 1352–1358.Google Scholar
Rodrigues, F. A., Peron, T. K. DM., Ji, P., & Kurths, J. (2016). The Kuramoto model in complex networks. Physics Reports 610: 1–98.Google Scholar
Rodríguez-Martínez, E. I., Barriga-Paulino, C. I., Rojas-Benjumea, M. A., & Gómez, C. M. (2015). Co-maturation of theta and low-beta rhythms during child development. Brain Topography 28: 250–260.Google Scholar
Roehm, D., Bornkessel-Schlesewsky, I., & Schlesewsky, M. (2007). The internal structure of the N400: frequency charactersitics of a language related ERP component. Chaos and Complexity Letters 2: 365–395.Google Scholar
Rogalsky, C., Rong, F., Saberi, K., & Hickok, G. (2011). Functional anatomy of language and music perception: Temporal and structural factors investigated using fMRI. Journal of Neuroscience 31(10): 3843–3852.Google Scholar
Rogers, J. & Hauser, M. (2010). The use of formal language theory in studies of artificial language learning: a proposal for distinguishing the differences between human and nonhuman animal learners. In Hulst, H. (ed.). Recursion and Human Language. New York: de Gruyter. 213–232.Google Scholar
Rogers, J., Heinz, J., Bailey, G., Edlefsen, M., Visscher, M., Wellcome, D., & Wibel, S. (2010). On languages piecewise testable in the strict sense. In Ebert, C., Jager, G., & Michaelis, J. (eds.). Proceedings of the 11th Meeting of the Mathematics of Language Association. New York: Springer-Verlag. 255–265.Google Scholar
Roll, M., Lindgren, M., Alter, K., & Horne, M. (2012). Time-driven effects on parsing during reading. Brain & Language 121: 267–272.Google Scholar
Rommers, J., Dickson, D. S., Norton, J. J. S., Wlotko, E. W., & Federmeier, K. D. (2017). Alpha and theta band dynamics related to sentential constraint and word expectancy. Language, Cognition and Neuroscience 32(5): 576–589.Google Scholar
Roux, F. & Uhlhaas, P. J. (2014). Working memory and neural oscillations: alpha-gamma versus theta-gamma codes for distinct WM information? Trends in Cognitive Sciences 18: 16–25.Google Scholar
Royer, S., Zemelman, B. V., Losonczy, A., Kim, J., Chance, F., Magee, J. C., & Buzsáki, G. (2012). Control of timing, rate and bursts of hippocampal place cells by dendritic and somatic inhibition. Nature Neuroscience 15: 769–775.Google Scholar
Rubio-Garrido, P., Pérez-De-Manzo, F., Porrero, C., Galazo, M. J. & Clascá, F. (2009). Thalamic input to distal apical dendrites in neocortical layer 1 is massive and highly convergent. Cerebral Cortex 19: 2380–2395.Google Scholar
Rugani, R., Vallortigara, G., Vallini, B., & Regolin, L. (2011). Asymmetrical number-space mapping in the avian brain. Neurobiology of Learning and Memory 95: 231–238.Google Scholar
Russell, B. (1919). Introduction to Mathematical Philosophy. London: George Allen & Unwin.Google Scholar
Russell, B. (1948). Human Knowledge: Its Scope and Limits. London: George Allen & Unwin.Google Scholar
Russell, E. S. (1916). Form and Function. London: John Murray.Google Scholar
Ryan, T. J., Roy, D. S., Pignatelli, M., Arons, A., & Tonegawa, S. (2015). Engram cells retain memory under retrograde amnesia. Science 348: 1007–1013.Google Scholar
Saalmann, Y. B., Pinsk, M. A., Wang, L., Li, X., & Kastner, S. (2012). The pulvinar regulates information transmission between cortical areas based on attention demands. Science 337: 753–756.Google Scholar
Saalmann, Y. B. (2014). Intralaminar and medial thalamic influence on cortical synchrony, information transmission and cognition. Frontiers in Systems Neuroscience 8: 83.Google Scholar
Sabeti, P. C., Schaffner, S. F., Fry, B., Lohmueller, J., Varilly, P., Shamovsky, O., Palma, A., Mikkelsen, T. S. et al. (2006). Positive natural selection in the human lineage. Science 312: 1614–1620.Google Scholar
Sadagopan, S., Temiz-Karayol, N. Z., & Voss, H. U. (2015). High-field functional magnetic resonance imaging of vocalization processing in marmosets. Scientific Reports 5: 10950.Google Scholar
Salami, M., Itami, C., Tsumoto, T., & Kimura, F. (2003). Change of conduction velocity by regional myelination yields constant latency irrespective of distance between thalamus and cortex. PNAS 100: 6174–6179.Google Scholar
Saleem, A. B., Lien, A. D., Krumin, M., Haider, B., Roman Roson, M., Ayaz, A., Reinhold, K., Busse, L., Carandini, M., & Harris, K. D. (2017). Subcortical source and modulation of the narrowband gamma oscillation in mouse visual cortex. Neuron 93: 315–322.Google Scholar
Salimpour, Y. & Anderson, W. S. (2019). Cross-frequency coupling based neuromodulation for treating neurological disorders. Frontiers in Neuroscience 13: 125.Google Scholar
Samuels, B. (2015). Biolinguistics in phonology: a prospectus. Phonological Studies 18: 161–171.Google Scholar
Samuels, B. D. (2011). Phonological Architecture: A Biolinguistic Perspective. Oxford: Oxford University Press.Google Scholar
Sanchez-Vives, M. V., Massimini, M., & Mattia, M. (2017). Shaping the default activity pattern of the cortical network. Neuron 94: 993–1001.Google Scholar
Sanchez-Vives, M. V. & McCormick, D. A. (2000). Cellular and network mechanisms of rhythmic recurrent activity in neocortex. Nature Neuroscience 3: 1027–1034.Google Scholar
Sanides, F. (1962). Die Architektonik des Menschlichen Stirnhirns: Zugleich eine Darstellung der Prinzipien Seiner Gestaltung als Spiegel der Stammesgeschichtlichen Differenzierung der Grosshirnrinde. Berlin/Heidelberg: Springer-Verlag.Google Scholar
Santi, A. & Grodzinsky, Y. (2010). fMRI adaptation dissociates syntactic complexity dimensions. NeuroImage 51(4): 1285–1293.Google Scholar
Santi, A. & Grodzinsky, Y. (2012). Broca’s area and sentence comprehension: a relationship parasitic on dependency displacement or predictability? Neuropsychologia 50: 821–832.Google Scholar
Santi, A., Friederici, A. D., Makuuchi, M., & Grodzinsky, Y. (2015). An fMRI study dissociating distance measures computed by Broca’s area in movement processing: clause boundary vs. identity. Frontiers in Psychology 6: 654.Google Scholar
Sato, J. R., Biazoli, C. E., Salum, G. A., Gadelha, A., Crossley, N., Vieira, G., & Anés, M. (2016). Connectome hubs at resting state in children and adolescents: reproducibility and psychopathological correlation. Developmental Cognitive Neuroscience 20: 2–11.Google Scholar
Sauseng, P., Klimesch, W., Doppelmayr, M., Pecherstorfer, T., Freunberger, R., & Hanslmayr, S. (2005). EEG alpha synchronization and functional coupling during top-down processing in a working memory task. Human Brain Mapping 26(2): 148–155.Google Scholar
Sauseng, P., Klimesch, W., Gruber, W. R., Hanslmayr, S., Freunberger, R., & Doppelmayr, M. (2007). Are event-related potential components generated by phase resetting of brain oscillations? A critical discussion. Neuroscience 146: 1435–1444.Google Scholar
Sauseng, P., Peylo, C., Lena Biel, A., Friedrich, E. V. C., & Romberg-Taylor, C. (2019). Does cross-frequency phase coupling of oscillatory brain activity contribute to a better understanding of visual working memory? British Journal of Psychology 110(2): 245–255.Google Scholar
Saygin, Z. M., Osher, D. E., Norton, E. S., Youssoufian, D. A., Beach, S. A., Feather, S., Gaab, N., Gabrieli, J. D. E., & Kanwisher, N. (2016). Connectivity precedes function in the development of the visual word form area. Nature Neuroscience 19: 1250–1255.Google Scholar
Schapiro, A. C., Turk-Browne, N. B., Botvinick, M. M., & Norman, K. A. (2017). Complementary learning systems within the hippocampus: a neural network modeling approach to recomciling episodic memory with statistical learning. Philosophical Transactions of the Royal Society B 372(1711): 20160049.Google Scholar
Scharinger, C., Soutschek, A., Schubert, T., & Gerjets, P. (2017). Comparison of the working memory load in N-back and working memory span tasks by means of EEG frequency band power and P300 amplitude. Frontiers in Human Neuroscience 11: 6.CrossRefGoogle ScholarPubMed
Scharinger, M., Bendixen, A., Herrmann, B., Henry, M. J., Mildner, T., & Obleser, J. (2015). Predictions interact with missing sensory evidence in semantic processing areas. Human Brain Mapping 37(2): 704–716.Google Scholar
Scheeringa, R. & Fries, P. (2019). Cortical layers, rhythms and BOLD signals. NeuroImage 197: 689–698.Google Scholar
Schenker, N. M., Buxhoeveden, D. P., Blackmon, W. L., Amunts, K., Zilles, K., & Semendeferi, K. (2008). A comparative quantitative analysis of cytoarchitecture and minicolumnar organization in Broca’s area in humans and great apes. Journal of Comparative Neurology 510: 117–128.Google Scholar
Schlenker, P., Chemla, E., Arnold, K., Lemasson, A., Ouattara, K., Keenan, S., Stephan, C., Ryder, R., & Zuberbühler, K. (2014). Monkey semantics: two ‘dialects’ of Campbell’s monkey alarm calls. Linguistics and Philosophy 37(6): 439–501.Google Scholar
Schlenker, P., Chemla, E., Schel, A. M., Fuller, J., Gautier, J.-P., Kuhn, J., Veselinović, D., Arnold, K., Cäsar, C., Keenan, S., Lemasson, A., Ouattara, K., Ryder, R., & Zuberbühler, K. (2016). Formal monkey linguistics. Theoretical Linguistics 42(1–2): 1–90.Google Scholar
Schmitt, L. I., Wimmer, R. D., Nakajima, M., Happ, M., Mofakham, S., & Halassa, M. M. (2017). Thalamic amplification of cortical connectivity sustains attentional control. Nature 545: 219–223.Google Scholar
Schneider, J. M., Abel, A. D., Ogiela, D. A., Middleton, A. E., & Maguire, M. J. (2016). Developmental differences in beta and theta power during sentence processing. Developmental Cognitive Neuroscience 19: 19–30.Google Scholar
Schneider, J. M. & Maguire, M. J. (2019). Developmental differences in the neural correlates supporting semantics and syntax during sentence processing. Developmental Science 22(4): e12782.Google Scholar
Schoch, S., Riedner, B., Dean, D., O’Muircheartaigh, J., Deoni, S., Huber, R., Jenni, O., LeBourgeois, M., & Kurth, S. (2017). EEG signatures of brain maturation in children: age-related and across-night dynamics in spatial propagation of slow oscillations. Sleep Medicine 40: e174.Google Scholar
Schoenemann, P. T. (2012). Evolution of brain and language. Progress in Brain Research 195: 443–459.Google Scholar
Schomburg, E. W., Fernandez-Ruiz, A., Mizuseki, K., Berenyi, A., Anastassiou, C. A., Koch, C., & Buzsáki, G. (2014). Theta phase segregation of input-specific gamma patterns in entorhinal-hippocampal networks. Neuron 84: 470–485.CrossRefGoogle ScholarPubMed
Schroeder, C. E. & Lakatos, P. (2008). Low-frequency neuronal oscillations as instruments of sensory selection. Trends in Neurosciences 32(1): 9–18.CrossRefGoogle ScholarPubMed
Schroeter, M. S., Charlesworth, P., Kitzbichler, M. G., Paulsen, O., & Bullmore, E. T. (2015). Emergence of rich-club topology and coordinated dynamics in development of hippocampal functional networks in vitro. The Journal of Neuroscience 35: 5459–5470.Google Scholar
Scott-Phillips, T. C. (2015). Speaking Our Minds: Why Human Communication is Different, and How Language Evolved to Make It Special. New York: Palgrave Macmillan.Google Scholar
Scott-Phillips, T. C. & Blythe, R. A. (2013). Why is combinatorial combination rare in the natural world, and why is language an exception to this trend? Journal of the Royal Society Interface 10: 2015020.CrossRefGoogle ScholarPubMed
Sedivy, J. (2019). Language in Mind: An Introduction to Psycholinguistics. 2nd ed. Oxford: Oxford University Press.Google Scholar
Segaert, K., Mazaheri, A., & Hagoort, P. (2018). Binding language: structuring sentences through precisely timed oscillatory mechanisms. European Journal of Neuroscience 48(7): 2651–2662.Google Scholar
Sengupta, B., Stemmler, M. B., & Friston, K. J. (2013). Information and efficiency in the nervous system – a synthesis. PLoS Computational Biology 9(7): e1003157.Google Scholar
Sennert, D. (1650). Tractatus de consensus et dissensu Galenicorum et Peripateticorum cum Chymicis, Opera omnia. Vol. 3. Lyons.Google Scholar
Seung, S. (2012). Connectome: How the brain’s wiring makes us who we are. Boston: Houghton, Mifflin, Harcourt.Google Scholar
Seyfarth, R. M. & Cheney, D. L. (2017). Precursors to language: social cognition and pragmatic inference in primates. Psychonomic Bulletin & Review 24: 79–84.Google Scholar
Shain, C., Blank, I. A., Schijndel, M. V., Schuler, W., & Fedorenko, E. (2020). fMRI reveals language-specific predictive coding during naturalistic sentence comprehension. Neuropsychologia 138: 107307.Google Scholar
Sheng, J., Zheng, L., Lyu, B., Cen, Z., Qin, L., Tan, L. H., Huang, M-X., Ding, N., & Gao, J-H. (2019). The cortical maps of hierarchical linguistic structures during speech perception. Cerebral Cortex 29(8): 3232–3240.Google Scholar
Shieber, S. (1985). Evidence against the context-freeness of natural language. Linguistics and Philosophy 8: 333–343.Google Scholar
Shim, J.-Y. (2013). External merge by phase: its implications for feature-inheritance, transfer and internal merge. In Lee, I.-J. & Uujinbai, D. (eds.). Proceedings of the 15th Seoul International Conference on Generative Grammar (SICOGG): Universals and Parameters. Seoul: Hankuk Publishing Co. 359–387.Google Scholar
Shim, J.-Y. (2018). <φ, φ>-less labeling. Language Research 54(1): 23–39.Google Scholar
Shine, J. M., Eisenberg, I., & Poldrack, R. A. (2016). Computational specificity in the human brain. Behavioral and Brain Sciences 39: e131.Google Scholar
Siebenhühner, F., Wang, S. H., Arnulfo, G., Nobili, L., Palva, J. M., & Palva, S. (2020). Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings. PLoS Biology 18(5): e3000685.Google Scholar
Siegel, M., Buschman, T. J., & Miller, E. K. (2015). Cortical information flow during flexible sensorimotor decisions. Science 348(6241): 1352–1355.Google Scholar
Siegelman, M., Mineroff, Z., Blank, I., & Fedorenko, E. (2017). An attempt to replicate a dissociation between syntax and semantics during sentence comprehension reported by Dapretto & Bookheimer (1999, Neuron). bioRxiv. https://doi.org/10.1101/110791Google Scholar
Siegelmann, H. T. (1999). Neural Networks and Analog Computation: Beyond the Turing Limit. Basel, Switzerland: Springer.Google Scholar
Sikela, J. M. & Searles Quick, V. B. (2018). Genomic trade‑offs: are autism and schizophrenia the steep price of the human brain? Human Genetics 137: 1–13.Google Scholar
Singer, W. (2013). Cortical dynamics revisited. Trends in Cognitive Sciences 17: 616–626.CrossRefGoogle ScholarPubMed
Singer, W. (2018). Neural oscillations: unavoidable and useful? European Journal of Neuroscience 48(7): 2389–2398.Google Scholar
Skeide, M. A. & Friederici, A. D. (2016). The ontogeny of the cortical language network. Nature Reviews Neuroscience 17: 323–332.Google Scholar
Skeide, M. A., Brauer, J., & Friederici, A. D. (2016). Brain functional and structural predictors of language performance. Cerebral Cortex 26: 2127–2139.Google Scholar
Skelton, A. E., Catchpole, G., Abbott, J. T., Bosten, J. M., & Franklin, A. (2017). Biological origins of color categorization. PNAS 114(21): 5545–5550.Google Scholar
Sklar, R. (1968). Chomsky’s revolution in linguistics. The Nation. 9 September.Google Scholar
Snyder, J. S. (2015). Sound perception: Rhythmic brain activity really is important for auditory segregation. Current Biology 25: R1166–R1185.Google Scholar
Solomon, E. A., Kragel, J. E., Sperling, M. R., Sharan, A., Worrell, G., Kucewicz, M. et al. (2017). Widespread theta synchrony and high-frequency desynchronization underlies enhanced cognition. Nature Communications 8: 1704.Google Scholar
Soma, M. & Mori, C. (2015). The songbird as a percussionist: syntactic rules for non-vocal sound and song production in java sparrows. PLoS One 10(5): e0124876.Google Scholar
Somel, M., Liu, X., & Khaitovich, P. (2013). Human brain evolution: transcripts, metabolites and their regulators. Nature Reviews Neuroscience 14: 112–127.Google Scholar
Somogyi, P. & Klausberger, T. (2005). Defined types of cortical interneurone structure space and spike timing in the hippocampus. The Journal of Physiology 562(1): 9–26.Google Scholar
Sotero, R. C. (2015). Modeling the generation of phase-amplitude coupling in cortical circuits: from detailed networks to neural mass models. BioMed Research International 2015: 915606.Google Scholar
Sotero, R. C., Sanchez-Rodriguez, L. M., Dousty, M., Iturria-Medina, Y., & Sanchez-Bornot, J. M. (2019). Cross-frequency interactions during information flow in complex brain networks are facilitated by scale-free properties. Frontiers in Physics 7: 107.Google Scholar
Sousa, A. M. M., Zhu, Y., Raghanti, M. A., Kitchen, R. R., Onorati, M., Tebbenkamp, A. T. N., Stutz, B., Meyer, K. A. et al. (2017). Molecular and cellular reorganization of neural circuits in the human lineage. Science 358: 1027–1032.Google Scholar
Spaak, E., Bonnefond, M., Maier, A., Leopold, D. A., & Jensen, O. (2012). Layer-specific entrainment of gamma-band neural activity by the alpha rhythm in monkey visual cortex. Current Biology 22: 2313–2318.Google Scholar
Spaak, E., Zeitler, M., & Gielen, S. (2012). Hippocampal theta modulation of neocortical spike times and gamma rhythm: a biophysical model study. PLoS ONE 7(10): e45688.Google Scholar
Spelke, E. (2010). Innateness, choice, and language. In Bricmont, J. & Franck, J. (eds.). Chomsky Notebook. New York: Columbia University Press. 203–210.Google Scholar
Sporns, E. (2013). The human connectome: origins and challenges. NeuroImage 80: 53–61.Google Scholar
Sporns, O., Tononi, G., & Kötter, R. (2005). The human connectome: A structural description of the human brain. PLoS Computational Biology 1: e42.CrossRefGoogle ScholarPubMed
Sprouse, J. & Almeida, D. (2013). The empirical status of data in syntax: a reply to Gibson and Fedorenko. Language and Cognitive Processes 28(3): 222–228.CrossRefGoogle Scholar
Stabler, E. P. (1997). Derivational minimalism. Retoré, C. (ed.). Logical Aspects of Computational Linguistics. LNCS 1328. New York: Springer-Verlag. 68–95.Google Scholar
Stankovski, T., Ticcinelli, V., McClintock, P. V. E., & Stefanovska, A. (2017). Neural cross-frequency coupling functions. Frontiers in Systems Neuroscience 11: 33.Google Scholar
Stanley, G. B. (2013). Reading and writing the neural code. Nature Neuroscience 16(3): 259–263.Google Scholar
Staudigl, T., Hartl, E., Noachtar, S., Doeller, C. F., & Jensen, O. (2017). Saccades are phase-locked to alpha oscillations in the occipital and medial temporal lobe during successful memory encoding. PLoS ONE 15(12): e2003404.Google Scholar
Steinhauer, K., Alter, K., & Friederici, A. D. (1999). Brain potentials indicate immediate use of prosodic cues in natural speech processing. Nature Neuroscience 2: 191–196.Google Scholar
Steinmetzger, K. & Rosen, S. (2017). Effects of acoustic periodicity and intelligibility on the neural oscillations in response to speech. Neuropsychologia 95: 173–181.Google Scholar
Steriade, M. (1993). Cellular substrates of brain rhythms. In Niedermeyer, E. & Lopez Da Silva, F. (eds.). Electroencephalography: Basic Principles, Clinical Application, and Related Fields. Baltimore: Williams & Wilkins. 27–62.Google Scholar
Steriade, M., Curro Dossi, R., & Contreras, D. (1993). Electrophysiological properties of intralaminar thalamocortical cells discharging rhythmic (~40 Hz) spike-bursts at ~1000 Hz during waking and rapid eye movement sleep. Neuroscience 56: 1–9.Google Scholar
Sterling, P. & Laughlin, S. (2015). Principles of Neural Design. Cambridge, MA: MIT Press.Google Scholar
Sternberg, S. (1966). High-speed scanning in human memory. Science 153(736): 652–654.Google Scholar
Sternberg, S. (1969). Memory-scanning: mental processes revealed by reaction-time experiments. American Scientist 57: 421–457.Google ScholarPubMed
Sternberg, S. (2011). Modular processes in mind and brain. Cognitive Neuropsychology 28: 156–208.Google Scholar
Storchi, R., Bedford, R. A., Martial, F. P., Allen, A. E., Wynne, J., Montemurro, M. A., Petersen, R. S., & Lucas, R. J. (2017). Modulation of fast narrowband oscillations in the mouse retina and dLGN according to background light intensity. Neuron 93: 299–307.Google Scholar
Storm, J. F. (1990). Potassium currents in hippocampal pyramidal cells. Progress in Brain Research 83: 161–187.Google Scholar
Stowe, L. A., Kaan, E., Sabourin, L., & Taylor, R. C. (2018). The sentence wrap-up dogma. Cognition 176: 232–247.Google Scholar
Strauss, A., Henry, M. J., Scharinger, M., & Obleser, J. (2015). Alpha phase determines successful lexical decision in noise. Journal of Neuroscience 35(7): 3256–3262.Google Scholar
Strawson, G. (2008). Real Materialism and Other Essays. Oxford: Oxford University Press.Google Scholar
Strawson, G. (2010). Mental Reality. 2nd ed. Cambridge, MA: MIT Press.Google Scholar
Strawson, P. F. (1966). The Bounds of Sense: An Essay on Kant’s Critique of Pure Reason. London: Methuen.Google Scholar
Strub, R. L. (1989). Frontal lobe syndrome in a patient with bilateral globus pallidus lesions. Archives of Neurology 46: 1024–1027.Google Scholar
Sugisaki, K. (2016). Structure dependence in child English. In Fujita, K. & Boeckx, C. (eds.). Advances in Biolinguistics: The Human Language Faculty and its Biological Basis. London: Routledge. 111–132.Google Scholar
Sukhinin, D. I., Engel, A. K., Manger, P., & Hilgetag, C. C. (2016). Building the ferretome. Frontiers in Neuroinformatics 10: 16.Google Scholar
Sun, C., Yang, W., Martin, J., & Tonegawa, S. (2020). Hippocampal neurons represent events as transferable units of experience. Nature Neuroscience 23(5): 651–663.Google Scholar
Suzuki, T. N., Wheatcroft, D., & Griesser, M. (2016). Experimental evidence for compositional syntax in bird calls. Nature Communications 7: 10986.Google Scholar
Svensson, E. I. (2018). On reciprocal causation in the evolutionary process. Evolutionary Biology 45: 1–14.Google Scholar
Swanson, L. W. & Lichtman, J. W. (2016). From Cajal to connectome and beyond. Annual Review of Neuroscience 39: 197–216.Google Scholar
Sweeney-Reed, C. M., Zaehle, T., Voges, J., Schmitt, F. C., Buentjen, L., Kopitzki, K., Hinrichs, H., Heinze, H-J., Rugg, M. D., Knight, R. T., & Richardson-Klavehn, A. (2015). Thalamic theta phase alignment predicts human memory formation and anterior thalamic cross-frequency coupling. eLife 4: e07578.CrossRefGoogle ScholarPubMed
Symons, A. E., El-Deredy, W., Schwartze, M., & Kotz, S. A. (2016). The functional role of neural oscillations in non-verbal emotional communication. Frontiers in Human Neuroscience 10: 239.Google Scholar
Szalisznyó, K., Silverstein, D., Teichmann, M., Duffau, H., & Smits, A.(2017). Cortico-striatal language pathways dynamically adjust for syntactic complexity: a computational study. Brain & Language. 164: 53–62.Google Scholar
Szathmáry, E. (1996). From RNA to language. Current Biology 6(7): 764.Google Scholar
Szatloczki, G., Hoffmann, I., Vincze, V., Kalman, J., & Pakaski, M. (2015) Speaking in Alzheimer’s disease, is that an early sign? Importance of changes in language abilities in Alzheimer’s disease. Frontiers in Aging Neuroscience 7: 195.Google Scholar
Taglialatela, J. P., Russell, J. L., Schaeffer, J. A., & Hopkins, W. D. (2011). Chimpanzee vocal signaling points to a multimodal origin of human language. PLoS ONE 6(4): e18852.Google Scholar
Takahasi, M., Yamada, H., & Okanoya, K. (2010). Statistical and prosodic sues for song segmentation learning by Bengalese Finches (Lonchura striata var. domestica). Ethology 116: 481–489.Google Scholar
Takashima, A., Bakker, I., van Hell, J. T., Janzen, G., & McQueen, J. M. (2017). Interaction between episodic and semantic memory networks in the acquisition and consolidation of novel spoken words. Brain & Language 167: 44–60.Google Scholar
Tallerman, M. (2016). Against the emergent view of language evolution. In Roberts, S. G., Cuskley, C., McCrohon, L., Barceló-Coblijn, L., Feher, O., & Verhoef, T. (eds.). The Evolution of Language: Proceedings of the 11th International Conference (EVOLANGXI). New Orleans, United States of America.Google Scholar
Tallon-Baudry, C. & Bertrand, O. (1999). Oscillatory gamma activity in humans and its role in object representation. Trends in Cognitive Sciences 3(4): 151–162.Google Scholar
Tamura, M., Spellman, T. J., Rosen, A. M., Gogos, J. A., & Gordon, J. A. (2017). Hippocampal-prefrontal theta-gamma coupling during performance of a spatial working memory task. Nature Communications 8: 2182.Google Scholar
Tass, P. A. (1999). Phase Resetting in Medicine and Biology. New York: Springer.Google Scholar
Tass, P. A. (2000). Stochastic phase resetting: a theory for deep brain stimulation. Progress of Theoretical Physics Supplement 139, 301–313.Google Scholar
Tattersall, I. (2017). How can we detect when language emerged? Psychonomic Bulletin & Review 24: 64–67.Google Scholar
Tavano, A., Blohm, S., Knoop, C., Muralikrishnan, R., Scharinger, M., Wagner, V., Thiele, D., Ghitza, O., Ding, N., Menninghaus, W., & Poeppel, D. (2020). Neural harmonics reflect grammaticality. bioRxiv. doi.org/10.1101/2020.04.08.031575Google Scholar
Ten Cate, C. & Okanoya, K. (2012). Revisiting the syntactic abilities of non-human animals: natural vocalizations and artificial grammar learning. Philosophical Transactions of the Royal Society B 367(1598): 1984–1994.Google Scholar
Teng, X., Ma, M., Yang, J., Blohm, S., Cai, Q., & Tian, X. (2020). Constrained structure of ancient Chinese poetry facilitates speech content grouping. Current Biology 30: 1299–1305.Google Scholar
Teng, X., Tian, X., Doelling, K., & Poeppel, D. (2018). Theta band oscillations reflect more than entrainment: behavioral and neural evidence demonstrates an active chunking process. European Journal of Neuroscience 48(8): 2770–2782.Google Scholar
Terporten, R., Schoffelen, J-M., Dai, B., Hagoort, P., & Kösem, A. (2019). The relation between alpha/beta oscillations and the encoding of sentence induced contextual information. Scientific Reports 9: 20255.Google Scholar
Terzi, A., Marinis, T., Zafeiri, A., & Francis, K. (2019). Subject and object pronouns in high-functioning children with ASD of a null-subject language. Frontiers in Psychology 10: 1301.Google Scholar
Tesche, C. D. & Karhu, J. (2000). Theta oscillations index human hippocampal activation during a working memory task. PNAS 97: 919–924.Google Scholar
Tettamanti, M. & Weniger, D. (2006). Broca’s area: A supramodel hierarchical processor? Cortex 42(4): 491–494.Google Scholar
Teyler, T. J. & DiScenna, P. (1986). The hippocampal memory indexing theory. Behavioural Neuroscience 100(2): 147–154.Google Scholar
Theofanopoulou, C. (2015). Brain asymmetry in the white matter making and globularity. Frontiers in Psychology 6: 1355.Google Scholar
Theofanopoulou, C. & Boeckx, C. (2016). The central role of the thalamus in language and cognition. In Boeckx, C. & Fujita, K. (eds.). Advances in Biolinguistics: The Human Language Faculty and its Biological Basis. London: Routledge.Google Scholar
Theofanopoulou, C. & Boeckx, C. (2018). (Neural) syntax. In Martin, R, R. & Gallego, Á. (eds.). Language, Syntax, and the Natural Sciences. Cambridge: Cambridge University Press.Google Scholar
Theyel, B. B., Llano, D. A., & Sherman, S. M. (2010). The corticothalamocortical circuit drives higher-order cortex in the mouse. Nature Neuroscience 13(1): 84–88.Google Scholar
Theves, S., Fernandez, G., & Doeller, C. F. (2019). The hippocampus encodes distances in multidimensional feature space. Current Biology 29: 1226–1231.Google Scholar
Thompson, P., Kuttab-Boulos, H., Witonsky, D., Yang, L., Roe, B. A., & Di Rienzo, A. (2001). Genetic influences on brain structure. Nature Neuroscience 4: 1253–1258.Google Scholar
Tian, B., Reser, D., Durham, A., Kustov, A., & Rauschecker, J. P. (2001). Functional specialization in rhesus monkey auditory cortex. Science 292: 290–293.Google Scholar
Tian, L. Y. & Brainard, M. S. (2017). Discrete circuits support generalized versus context-specific vocal learning in the songbird. Neuron 96(5): 1168–1177.Google Scholar
Tinbergen, N. (1963). On the aims and methods of ethology. Zeitschrift für Tierpsychologie 20: 410–463.Google Scholar
Todt, D. & Hultsch, H. (1998). How songbirds deal with large amounts of serial information: retrieval rules suggest a hierarchical song memory. Biological Cybernetics 79: 487–500.Google Scholar
Tomalin, M. (2006). Linguistics and the Formal Sciences: The Origins of Generative Grammar. Cambridge: Cambridge University Press.Google Scholar
Tomalin, M. (2007). Reconsidering recursion in syntactic theory. Lingua 117: 1784–1800.Google Scholar
Tooby, J. & Cosmides, L. (1992). The psychological foundations of culture. In Barkow, J. H., Cosmides, L. & Tooby, J. (eds.). The Adapted Mind: Evolutionary Psychology and the Generation of Culture. Oxford: Oxford University Press. 19–136.Google Scholar
Torday, J. S. & Miller, W. B. Jr. (2016). On the evolution of the mammalian brain. Frontiers in Systems Neuroscience 10: 31.Google Scholar
Tort, A. B., Komorowski, R. W., Manns, J. R., Kopell, N. J., & Eichenbaum, H. (2009). Theta-gamma coupling increases during the learning of item-context associations. PNAS 106: 20942–20947.Google Scholar
Tort, A. B. L., Rotstein, H. G., Dugladze, T., Gloveli, T., & Kopell, N. J. (2007). On the formation of gamma-coherent cell assemblies by oriens lacunosum-moleculare interneurons in the hippocampus. Proceedings of the National Academy of Sciences of the United States of America 104(33): 13490–13495.Google Scholar
Tremblay, P. & Dick, A. S. (2016). Broca and Wernicke are dead, or moving past the classic model of neurobiology. Brain & Language 162: 60–71.Google Scholar
Trettenbrein, P. C. (2016). The demise of the synapse as the locus of memory: a looming paradigm shift? Frontiers Systems Neuroscience 10: 88.Google Scholar
Trevisan, M. A., Mindlin, G. B., & Goller, F. (2006). Nonlinear model predicts diverse respiratory patterns of birdsongs. Physical Review Letters 96(5): 058103.Google Scholar
Trotzke, A. (2015). Rethinking Syntacticentrism: Architectural Issues and Case Studies at the Syntax-Pragmatics Interface. Amsterdam: John Benjamins.Google Scholar
Tsien, J. Z. (2016). Principles of intelligence: on evolutionary logic of the brain. Frontiers in Systems Neuroscience 9: 186.Google Scholar
Tsuda, I. (2013). Chaotic itinerancy. Scholarpedia 8: 4459.Google Scholar
Tsuda, I. (2015). Chaotic itinerancy and its roles in cognitive neurodynamics. Current Opinion in Neurobiology 31: 67–71.Google Scholar
Turken, A. U. & Dronkers, N. F. (2011). The neural architecture of the language comprehension network: converging evidence from lesion and connectivity analyses. Frontiers in Systems Neuroscience 5: 1.Google Scholar
Tutunjian, D. & Boland, J. E. (2008). Do we need a distinction between arguments and adjuncts? Evidence from psycholinguistic studies of comprehension. Language and Linguistics Compass 2: 631–646.Google Scholar
Tzourio-Mazoyer, N. & Mazoyer, B. (2017). Variations of planum temporale asymmetries with Heschl’s Gyri duplications and association with cognitive abilities: MRI investigation of 428 healthy volunteers. Brain Structure and Function 222(6): 2711–2726.Google Scholar
Uddén, J., Hultén, A., Schoffelen, J.-M., Lam, N., Harbusch, K., van den Bosch, A., Kempen, G., Petersson, K. M., & Hagoort, P. (2019). Supramodal sentence processing in the human brain: fMRI evidence for the influence of syntactic complexity in more than 200 participants. bioRxiv. https://doi.org/10.1101/576769Google Scholar
Uddén, J., Ingvar, M., Hagoort, P., & Magnus Petersson, K. (2017). Broca’s region: a causal role in implicit processing of grammars with crossed non-adjacent dependencies. Cognition 164: 188–198.Google Scholar
Ueda, M. (2016). On the current status of biolinguistics as a biological science. In Fujita, K. & Boeckx, C. (eds.). Advances in Biolinguistics: The Human Language Faculty and its Biological Basis. London: Routledge. 264–289.Google Scholar
Uhlhaas, P. J., Haenschel, C., Nikolić, D., & Singer, W. (2008). The role of oscillations and synchrony in cortical networks and their putative relevance for the pathophysiology of schizophrenia. Schizophrenia Bulletin 34(5): 927–943.Google Scholar
Underhill, J. W. (2009). Humboldt, Worldview and Language. Edinburgh: Edinburgh University Press.Google Scholar
Uriagereka, J. (2012). Spell-Out and the Minimalist Program. Oxford: Oxford University Press.Google Scholar
Ursini, F-A. (2011). Space and the vision-language interface: a model-theoretic approach. Biolinguistics 5(3): 170–225.Google Scholar
Vaas, R. (2001). It binds, therefore I am! Review of Rodolfo Llinás’s I of the Vortex. Journal of Consciousness Studies 8(4): 85–88.Google Scholar
van de Cavey, J. & Hartsuiker, R. J. (2016). Is there a domain-general cognitive structuring system? Evidence from structural priming across music, math, action descriptions, and language. Cognition 146: 172–184.Google Scholar
van de Velde, F. (2011). Left-peripheral expansion of the English NP. English Language and Linguistics 15: 387–415.Google Scholar
van der Lely, H. K. & Pinker, S. (2014). The biological basis of language: insight from developmental grammatical impairments. Trends in Cognitive Sciences 18(11): 586–595.Google Scholar
van Driel, J., Gunseli, E., Meeter, M., & Olivers, C. N. L. (2017). Local and interregional alpha EEG dynamics dissociate between memory for search and memory for recognition. NeuroImage 149: 114–128.Google Scholar
van Gelderen, E. (2018). Problems of projection: the role of language change in labeling paradoxes. Studia Linguistica 72(1): 113–127.Google Scholar
van Le, Q., Isbell, L. A., Matsumoto, J., Nishimaru, H., Hori, E., Maior, R. S., Tomaz, C., Ono, T., & Nishijo, H. (2016). Snakes elicit earlier, and monkey faces, later, gamma oscillations in macaque pulvinar neurons. Scientific Reports 6: 20595.Google Scholar
van Petten, C. & Luka, B. J. (2006). Neural localization of semantic context effects in electromagnetic and hemodynamic studies. Brain and Language 97: 279–293.Google Scholar
van Riemsdijk, H. (2008). Identity avoidance: OCP effects in Swiss relatives. In Freidin, R., Otero, C. P., & Luisa Zubizarreta, M. (eds.). Foundational Issues in Linguistic Theory: Essays in Honor of Jean-Roger Vergnaud. Cambridge, MA: MIT Press. 227–250.Google Scholar
van Rooij, I. (2008). The tractable cognition thesis. Cognitive Science 32(6): 939–984.Google Scholar
Vanier, D., Sherwood, C., & Smaers, J. (2019). The evolution of hippocampal formation subregions in primates. Poster presented at the 49th Meeting of the Society for Neuroscience, Chicago, 19–23 October.Google Scholar
VanRullen, R. (2016). Perceptual cycles. Trends in Cognitive Sciences 20(10): 723–735.Google Scholar
VanRullen, R., Guyonneau, R., & Thorpe, S. J. (2005). Spike times make sense. Trends in Neuroscience 28(1): 1–4.Google Scholar
Varga, C., Golshani, P., & Soltesz, I. (2012). Frequency-invariant temporal ordering of interneuronal discharges during hippocampal oscillations in awake mice. PNAS 109: E2726–E2734.Google Scholar
Vaz, A. P., Yaffe, R. B., Wittig, J. H., Inati, S. K., & Zaghloul, K. A. (2017). Dual origins of measured phase-amplitude coupling reveal distinct neural mechanisms underlying human episodic memory in the human cortex. NeuroImage 148: 148–159.Google Scholar
Verguts, T. (2017). Binding by random bursts: a computational model of cognitive control. Journal of Cognitive Neuroscience 29(6): 1103–1118.Google Scholar
Vertes, R. P. & Kocsis, B. (1997). Brainstem-diencephalo-septohippocampal systems controlling the theta rhythm of the hippocampus. Neuroscience 81: 893–926.Google Scholar
Veselinovic, D., Candiotti, A., & Lemasson, A. (2014). Female Diana monkeys (Cercopithecus Diana) have complex calls. Ms. New York University.Google Scholar
Vetter, P., Edwards, G., & Muckli, L. (2013). Transfer of predictive signals across saccades. Frontiers in Psychology 3: 176.Google Scholar
Vicario, D. S. & Simpson, H. B. (1995). Electrical stimulation in forebrain nuclei elicits learned vocal patterns in songbirds. Journal of Neurophysiology 73: 2602–2607.Google Scholar
Vidaurre, D., Hunt, L. T., Quinn, A. J., Hunt, B. A. E., Brookes, M. J., Nobre, A. C., & Woolrich, M. W. (2018). Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks. Nature Communications 9: 2987.Google Scholar
Vignali, L., Himmelstoss, N. A., Hawelka, S., Richlan, F., & Hutzler, F. (2016). Oscillatory brain dynamics during sentence reading: a fixation-related spectral perturbation analysis. Frontiers in Human Neuroscience 10: 191.Google Scholar
Vijayan, S. & Kopell, N. J. (2012). Thalamic model of awake alpha oscillations and implications for stimulus processing. PNAS U.S.A. 109(45): 18553–18558.Google Scholar
Vinogradov, S. & Herman, A. (2016). Psychiatric illnesses as oscillatory connectomopathies. Neuropsychopharmacology 41: 387–388.Google Scholar
Vitiello, G. (2015). The use of many-body physics and thermodynamics to describe the dynamics of rhythmic generators in sensory cortices engaged in memory and learning. Current Opinion in Neurobiology 31: 7–12.Google Scholar
Vollrath, M., Kazenwadel, J., & Krüger, H-P. (1992). A universal constant in temporal segmentation of human speech. Naturwissenschaften 79: 479–480.Google Scholar
Voloh, B. & Womelsdorf, T. (2016). A role of phase-resetting in coordinating large scale neural networks during attention and goal-directed behavior. Frontiers in Systems Neuroscience 10: 18.Google Scholar
von Lautz, A. H., Herding, J., Ludwig, S., Nierhaus, T., Maess, B., Villringer, A., & Blankenburg, F. (2017). Gamma and beta oscillations in human MEG encode the contents of vibrotactile working memory. Frontiers in Human Neuroscience 11: 576.Google Scholar
Vosskuhl, J., Huster, R. J., & Herrmann, C. S. (2015). Increase in short-term memory capacity induced by down-regulating individual theta frequency via transcranial alternating current stimulation. Frontiers Human Neuroscience 9: 257.Google Scholar
Vukovic, N. & Shtyrov, Y. (2017). Cortical networks for reference-frame processing are shared by language and spatial navigation systems. NeuroImage 161: 120–133.Google Scholar
Wahl, M., Marzinzik, F., Friederici, A. D., Hahne, A., Kupsch, A., Schneider, G. H., Saddy, D., Curio, G., & Klostermann, F. (2008). The human thalamus processes syntactic and semantic language violations. Neuron 59: 695–707.Google Scholar
Walsh, D. M. (2015). Organisms, Agency, and Evolution. Cambridge: Cambridge University Press.Google Scholar
Wang, L., Hagoort, P., & Jensen, O. (2018). Language prediction is reflected by coupling between frontal gamma and posterior alpha oscillations. Journal of Cognitive Neuroscience 30(3): 432–447.Google Scholar
Wang, L., Hua, L., Wu, E. X., & Chen, F. (2019). Cortical auditory responses index the contributions of different RMS-level-dependent segments to speech intelligibility. Hearing Research 383: 107808.CrossRefGoogle ScholarPubMed
Wang, L., Jensen, O., van den Brink, D., Weder, N., Schoffelen, J., Magyari, L. et al. (2012). Beta oscillations relate to the N400m during language comprehension. Human Brain Mapping 33: 2898–2912.Google Scholar
Wang, L., Zhu, Z., & Bastiaansen, M. (2012). Integration or predictability? A further specification of the functional role of gamma oscillations in language comprehension. Frontiers in Psychology 3: 187.Google Scholar
Wang, Z., Wang, J., Zhang, H., Mchugh, R., Sun, X., Li, K., & Yang, Q. X. (2015). Interhemispheric functional and structural disconnection in Alzheimer’s disease: a combined resting-state fMRI and DTI study. PLoS ONE 10: e0126310.Google Scholar
Ward, L. M. (2003). Synchronous neural oscillations and cognitive processes. Trends in Cognitive Sciences 7(12): 553–559.Google Scholar
Watanabe, H., Takahashi, K., & Isa, T. (2015). Phase locking of β oscillation in electrocorticography (ECoG) in the monkey motor cortex at the onset of EMGs and 3D reaching movements. Engineering in Medicine and Biology Society (EMBC), 37th Annual International Conference of the IEEE. 55–58.Google Scholar
Watrous, A. J., Deuker, L., Fell, J., & Axmacher, N. (2015). Phase-amplitude coupling supports phase coding in human ECoG. eLife 4: e07886.Google Scholar
Watumull, J., Hauser, M. D., & Berwick, R. B. (2014). Conceptual and methodological problems with comparative work on artificial language learning. Biolinguistics 8: 120–129.Google Scholar
Watumull, J., Hauser, M. D., Roberts, I. G., & Hornstein, N. (2014). On recursion. Frontiers in Psychology 4: 1017.Google Scholar
Webman-Shafran, R. & Fodor, J. D. (2015). Phrase length and prosody in on-line ambiguity resolution. Journal of Psycholinguistic Research 45: 447–474.Google Scholar
Weismann, A. (1893). The all-sufficiency of natural selection. Contemporary Review 64: 309–338, 596–610.Google Scholar
Welch, J. J. (2017). What’s wrong with evolutionary biology? Biology & Philosophy 32(2): 263–279.Google Scholar
Welle, C. G. & Contreras, D. (2017). New light on gamma oscillations. Neuron 93: 247–249.CrossRefGoogle ScholarPubMed
West-Eberhard, M. J. (2003). Developmental Plasticity and Evolution. Oxford: Oxford University Press.Google Scholar
Westerlund, M. & Pylkkänen, L. (2014). The role of the left anterior temporal lobe in semantic composition vs. semantic memory. Neuropsychologia 57: 59–70.Google Scholar
Wexler, K. (1998). Very early parameter setting and the unique checking constraint: a new explanation of the optional infinitive stage. Lingua 106: 23–79.Google Scholar
White, J. A., Banks, M. I., Pearce, R. A., & Kopell, N. J. (2000). Networks of interneurons with fast and slow γ-aminobutyric acid type A (GABAA) kinetics provide substrate for mixed gamma-theta rhythm. Proceedings of the National Academy of Sciences of the United States of America 97(14): 8128–8133.Google Scholar
Whitford, T. J., Jack, B. N., Pearson, D., Griffiths, O., Luque, D., Harris, A. W. F., Spencer, K. M., & Le Pelley, M. E. (2017). Neurophysiological evidence of efference copies to inner speech. eLife 6: e28197.Google Scholar
Whittington, M. A. & Traub, R. D. (2003). Interneuron diversity series: inhibitory interneurons and network oscillations in vitro. Trends in Neuroscience 26: 676–682.Google Scholar
Wianda, E. & Ross, B. (2019). The roles of alpha oscillation in working memory retention. Brain and Behavior DOI:10.1002/brb3.1263Google Scholar
Wiedmann, N. & Winkler, S. (2015). The influence of prosody on children’s processing of ambiguous sentences. In Winkler, S. (ed.). Ambiguity: Language and Communication. Berlin: De Gruyter. 185–197.CrossRefGoogle Scholar
Wilkinson, C. & Murphy, E. (2016). Joint interventions in autism spectrum disorder: relating oscillopathies and syntactic deficits. UCL Working Papers in Linguistics 28: 1–7.Google Scholar
Willer Gold, J., Arsenijević, B., Batinić, M., Becker, M., Čordalija, N., Kresić, M., Leko, N., Lanko Marušič, F. et al. (2017). When linearity prevails over hierarchy in syntax. PNAS 115(3): 495–500.Google Scholar
Wilsch, A., Henry, M. J., Herrmann, B., Maess, B., & Obleser, J. (2015). Alpha oscillatory dynamics index temporal expectation benefits in working memory. Cerebral Cortex 25(7): 1938–1946.Google Scholar
Wilson, B., Marslen-Wilson, W. D., & Petkov, C. I. (2017). Conserved sequence processing in primate frontal cortex. Trends in Neurosciences 40(2): 72–82.Google Scholar
Wilson, B., Slater, H., Kikuchi, Y., Milne, A. E., Marslen-Wilson, W. D., Smith, K., & Petkov, C. I. (2013). Auditory artificial grammar learning in macaque and marmoset monkeys. Journal of Neuroscience 33(48): 18825–18835.Google Scholar
Wilson, B., Kikuchi, Y., Sun, L., Hunter, D., Dick, F., Smith, K., Thiele, A., Griffiths, T. D., Marslen-Wilson, W. D., & Petkov, C. I. (2015). Auditory sequence processing reveals evolutionarily conserved regions of frontal cortex in macaques and humans. Nature Communication 6: 8901.Google Scholar
Wilson, B., Smith, K., & Petkov, C. (2015). Mixed-complexity artificial grammar learning in humans and macaque monkeys: evaluating learning strategies. European Journal of Neuroscience 41(5): 568–578.Google Scholar
Wilson, M. A., & Bower, J. M. (1991). A computer simulation of oscillatory behavior in primary visual cortex. Neural Computation 3: 498–509.Google Scholar
Wilson, S. M., DeMarco, A. T., Henry, M. L., Gesierich, B., Babiak, M., Mandelli, M. L., Miller, B. L., & Gorno-Tempini, M. L. (2014). What role does the anterior temporal lobe play in sentence-level processing? Neural correlates of syntactic processing in semantic variant primary progressive aphasia. Journal of Cognitive Neuroscience 26: 970–985.Google Scholar
Wilson, S. M., Molnar-Szakacs, I., & Iacoboni, M. (2008). Beyond superior temporal cortex: intersubject correlations in narrative speech comprehension. Cerebral Cortex 18(1): 230–242.Google Scholar
Winkler, M., Mueller, J. L., Friederici, A. D., & Männel, C. (2018). Infant cognition includes the potentially human-unique ability to encode embedding. Science Advances 4: eaar8334.Google Scholar
Wipf, D. P., Owen, J. P., Attias, H. T., Sekihara, K., & Nagarajan, S. S. (2010). Robust Bayesian estimation of the location, orientation, and time course of multiple correlated neural sources using MEG. NeuroImage 49: 641–655.Google Scholar
Witkowski, M., Garcia-Cossio, E., Chander, B. S., Braun, C., Birbaumer, N., Robinson, S. E., & Soekadar, S. R. (2016). Mapping entrained brain oscillations during transcranial alternating current stimulation (tACS). NeuroImage 140: 89–98.Google Scholar
Wojtecki, L., Elben, S., Vesper, J., & Schnitzler, A. (2017). The rhythm of the executive gate of speech: subthalamic low-frequency oscillations increase during verbal generation. European Journal of Neuroscience 45(9): 1200–1211.Google Scholar
Wolinski, N., Cooper, N., Sauseng, P., & Romei, V. (2018). The speed of parietal theta frequency drives visuospatial working memory capacity. PLoS Biology 16: e2005348.CrossRefGoogle ScholarPubMed
Woolnough, O., Forseth, K. J., Rollo, P. S., & Tandon, N. (2020). Uncovering the functional anatomy of the human insula during speech. eLife 8: e53086.CrossRefGoogle Scholar
Wöstmann, M., Herrmann, B., Wilsch, A., & Obleser, J. (2015). Neural alpha dynamics in younger and older listeners reflect acoustic challenges and predictive benefits. Journal of Neuroscience 35(4): 1458–1467.CrossRefGoogle ScholarPubMed
Wu, C-Y., Zaccarella, E., & Friederici, A. D. (2019). Universal neural basis of structure building evidenced by network modulations emerging from Broca’s area: the case of Chinese. Human Brain Mapping 40(6): 1705–1717.Google Scholar
Wutz, A., Loonis, R., Roy, J. E., Donoghue, J. A., & Miller, E. K. (2018). Different levels of category abstraction by different dynamics in different prefrontal areas. Neuron 97: 716–726.CrossRefGoogle ScholarPubMed
Xie, K., Fox, G. E., Liu, J., Lyu, C., Lee, J. C., Kuang, H., Jacobs, S., Li, M., Liu, T., Song, S., & Tsien, J. Z. (2016). Brain computation is organized via power-of-two-based permutation logic. Frontiers in Systems Neuroscience 10: 95.Google Scholar
Yael, D., Vecht, J. J., & Bar-Gad, I. (2018). Filter-based phase shifts distort neuronal timing information. eNeuro 5(2): e0261–17.2018.Google Scholar
Yan, B. & Li, P. (2013). The emergence of abnormal hypersynchronization in the anatomical structural network of human brain. NeuroImage 65: 34–51.Google Scholar
Yang, C. (2018). The linguistic origin of the next number. Ms. University of Pennsylvania.Google Scholar
Yee, E. & Thompson-Schill, S. L. (2016). Putting concepts into context. Psychonomic Bulletin & Review 23(4): 1015–1027.Google Scholar
Yelnik, J., Percheron, G., & Francois, C. (1984). A Golgi analysis of the primate globus pallidus. II. Quantitative morphology and spatial orientation of dendritic arborizations. Journal of Comparative Neurology 227(2): 200–213.Google Scholar
Yener, G. G., Emek-Savaş, D. D., Lizio, R., Çavuşoğlu, B., Carducci, P., Ada, E., Güntekin, B., Babiloni, C., & Başar, E. (2016). Frontal delta event-related oscillations relate to frontal volume in mild cognitive impairment and healthy controls. International Journal of Psychophysiology 103: 110–117.Google Scholar
Yoshimi, J. (2012). Supervenience, dynamical systems theory, and non-reductive physicalism. The British Journal for the Philosophy of Science 63(20): 373–398.Google Scholar
Zaccarella, E. & Friederici, A. D. (2017). The neurobiological nature of syntactic hierarchies. Neuroscience and Biobehavioral Reviews 81(Pt B): 205–212.Google Scholar
Zaccarella, E. & Friederici, A. D. (2015). Merge in the human brain: a sub-region based functional investigation in the left pars opercularis. Frontiers in Psychology 6: 524.Google Scholar
Zaccarella, E., Meyer, L., Makuuchi, M., & Friederici, A. D. (2017). Building by syntax: the neural basis of minimal linguistic structures. Cerebral Cortex 27(1): 411–421.Google Scholar
Zador, A. M. (2019). A critique of pure learning and what artificial neural networks can learn from animal brains. Nature Communications 10: 3770.Google Scholar
Zalesky, A., Fornito, A., Cocchi, L., Gollo, L. L., & Breakspear, M. (2014). Time-resolved resting-state brain networks. PNAS 111: 10341–10346.Google Scholar
Zeder, M. A. (2017). Domestication as a model system for the extended evolutionary synthesis. Interface Focus 7: 20160133.Google Scholar
Zhang, H. & Jacobs, J. (2015). Traveling theta waves in the human hippocampus. Journal of Neuroscience 35: 12477–12487.Google Scholar
Zhang, H., Watrous, A. J., Patel, A., & Jacobs, J. (2018). Theta and alpha oscillations are travelling waves in the human neocortex. Neuron 98: 1269–1281.Google Scholar
Zhang, L. & Pylkkänen, L. (2018). Semantic composition of sentences word by word: MEG evidence for shared processing of conceptual and logical elements. Neuropsychologia 119: 392–404.Google Scholar
Zhang, Y. E. & Pylkkänen, L. (2015). The interplay of composition and concept specificity in the left anterior temporal lobe: an MEG study. NeuroImage 11: 228–240.Google Scholar
Zhang, Y. & Wang, Y. (2007). Neural plasticity in speech learning and acquisition. Bilingualism: Language and Cognition 10(2): 147–160.Google Scholar
Zielinski, M. C. Tang, W., & Jadhav, S. P. (2020). The role of replay and theta sequences in mediating hippocampal-prefrontal interactions for memory and cognition. Hippocampus 30(1): 60–72.Google Scholar
Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2014). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex 63: 79–89.Google Scholar
Zimmerer, V. C., Cowell, P. E., & Varley, R. A. (2014). Artificial grammar learning in individuals with severe aphasia. Neuropsychologia 53: 25–38.Google Scholar
Zipf, G. K. ([1949]1965). Human Behavior and the Principle of Least Effort: An Introduction to Human Ecology. New York: Hafner.Google Scholar
Zoefel, B., Costa-Faidella, J., Lakatos, P., Schroeder, C. E., & VanRullen, R. (2017). Characterization of neural entrainment to speech with and without slow spectral energy fluctuations in laminar recordings in monkey A1. NeuroImage 150: 344–357.Google Scholar
Zuberbühler, K. (2019). Evolutionary roads to syntax. Animal Behaviour 151: 259–265.Google Scholar
Zuidema, W. (2013). Context-freeness revisited. In Knauff, M., Pauen, M., Sebanz, N., & Wachsmuth, I. (eds.). Proceedings of the 35th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. 1664–1669.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

  • References
  • Elliot Murphy, University College London
  • Book: The Oscillatory Nature of Language
  • Online publication: 20 October 2020
Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

  • References
  • Elliot Murphy, University College London
  • Book: The Oscillatory Nature of Language
  • Online publication: 20 October 2020
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • References
  • Elliot Murphy, University College London
  • Book: The Oscillatory Nature of Language
  • Online publication: 20 October 2020
Available formats
×