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Above and beyond “Above and beyond the concrete”

Published online by Cambridge University Press:  19 June 2020

Michael Gilead Open the ORCID record for Michael Gilead [Opens in a new window] ,
Yaacov Trope  and
Nira Liberman
Michael Gilead
Affiliation:
Department of Psychology, Ben-Gurion University, Beersheba84105, Israelmgilead@bgu.ac.il http://www.gileadlab.net/
Yaacov Trope
Affiliation:
Department of Psychology, New York University, New York, NY10003yaacov.trope@nyu.edu http://www.psych.nyu.edu/tropelab/
Nira Liberman
Affiliation:
Department of Psychology, Tel-Aviv University, Tel-Aviv69978, Israel.niralib@tauex.ac.il https://en-social-sciences.tau.ac.il/profile/niralib
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Abstract

The commentaries address our view of abstraction, our ontology of abstract entities, and our account of predictive cognition as relying on relatively concrete simulation or relatively abstract theory-based inference. These responses revisit classic questions concerning mental representation and abstraction in the context of current models of predictive cognition. The counter arguments to our article echo: constructivist theories of knowledge, “neat” approaches in artificial intelligence and decision theory, neo-empiricist models of concepts, and externalist views of cognition. We offer several empirical predictions that address points of contention and that highlight the generative potential of our model.

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Authors' Response
Information
Behavioral and Brain Sciences , Volume 43 , 2020 , e153
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Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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References

Aravena, P., Courson, M., Frak, V., Cheylus, A., Paulignan, Y., Deprez, V. & Nazir, T. (2014) Action relevance in linguistic context drives word-induced motor activity. Frontiers in Human Neuroscience 8:163.CrossRefGoogle ScholarPubMed
Aravena, P., Delevoye-Turrell, Y., Deprez, V., Cheylus, A., Paulignan, Y., Frak, V. & Nazir, T. (2012) Grip force reveals the context sensitivity of language-induced motor activity during “action words” processing: Evidence from sentential negation. PLOS ONE 7(12):e50287.CrossRefGoogle ScholarPubMed
Brainerd, C. J., Yang, Y., Reyna, V. F., Howe, M. L. & Mills, B. A. (2008) Semantic processing in “associative” false memory. Psychonomic Bulletin & Review 15(6):1035–1053. doi: 10.3758/PBR.15.6.1035.CrossRefGoogle ScholarPubMed
Clark, A. (2013) Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral and Brain Sciences 36(3):181–204.CrossRefGoogle ScholarPubMed
Doya, K. (2007) Bayesian brain: Probabilistic approaches to neural coding. MIT press.Google Scholar
Friston, K. J., Parr, T. & de Vries, B. (2017c) The graphical brain: Belief propagation and active inference. Network Neuroscience 1(4):381–414. doi: 10.1162/NETN_a_00018.CrossRefGoogle Scholar
Gilead, M., Liberman, N. & Maril, A. (2013) The language of future-thought: An fMRI study of embodiment and tense processing. Neuroimage 65:267–79. Available at: http://doi.org/10.1016/j.neuroimage.2012.09.073.CrossRefGoogle Scholar
Goldman, A. I. (2005) Imitation, mind reading, and simulation. In: Perspectives on imitation: Imitation, human development, and culture, Vol. 79.Google Scholar
Helmholtz, H. von (1856/1961) Treatise of physiological optics: Concerning the perceptions in general. In: Classics in psychology, ed. Shipley, T., pp. 79–127. Philosophy Library. (Original work published in 1856)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(7600):453–58. doi: 10.1038/nature17637.CrossRefGoogle ScholarPubMed
Kemmerer, D. (2015) Are the motor features of verb meanings represented in the precentral motor cortices? Yes, but within the context of a flexible, multilevel architecture for conceptual knowledge. Psychonomic Bulletin & Review 22(4):1068–75.CrossRefGoogle ScholarPubMed
Kemmerer, D., Rudrauf, D., Manzel, K. & Tranel, D. (2012) Behavioral patterns and lesion sites associated with impaired processing of lexical and conceptual knowledge of actions. Cortex 48(7):826–48. doi: 10.1016/j.cortex.2010.11.001.CrossRefGoogle ScholarPubMed
Knill, D. C. & Pouget, A. (2004) The Bayesian brain: The role of uncertainty in neural coding and computation. Trends in Neurosciences 27(12):712–19.CrossRefGoogle ScholarPubMed
Knutson, K. M., Wood, J. N. & Grafman, J. (2004) Brain activation in processing temporal sequence: An fMRI study. NeuroImage 23(4):1299–307.CrossRefGoogle Scholar
Marcus, G. (2009) Kluge: The haphazard evolution of the human mind. Houghton Mifflin Harcourt.Google Scholar
Meyer, M. L., Hershfield, H. E., Waytz, A. G., Mildner, J. N. & Tamir, D. I. (2019) Creative expertise is associated with transcending the here and now. Journal of Personality and Social Psychology 116(4):483–94. https://doi.org/10.1037/pspa0000148.CrossRefGoogle ScholarPubMed
Mikolov, T., Chen, K., Corrado, G. & Dean, J. (2013) Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781.Google Scholar
Murphy, G. L. & Medin, D. L. (1985) The role of theories in conceptual coherence. Psychological Review 92(3):289.CrossRefGoogle ScholarPubMed
Ng, A. Y. & Jordan, M. I. (2002) On discriminative vs. generative classifiers: A comparison of logistic regression and naive Bayes. In: Advances in neural information processing systems, ed. Dietterich, T. G., Becker, S. & Ghahramani, Z., pp. 841–48.Google Scholar
Peters, J. & Büchel, C. (2010) Episodic future thinking reduces reward delay discounting through an enhancement of prefrontal-mediotemporal interactions. Neuron 66(1):138–48.CrossRefGoogle ScholarPubMed
Postle, N., McMahon, K. L., Ashton, R., Meredith, M. & de Zubicaray, G. I. (2008) Action word meaning representations in cytoarchitectonically defined primary and premotor cortices. NeuroImage 43(3):634–44.CrossRefGoogle ScholarPubMed
Rogers, T. T. & McClelland, J. L. (2004) Semantic cognition: A parallel distributed processing approach. MIT Press.CrossRefGoogle Scholar
Tarhan, L. Y., Watson, C. E. & Buxbaum, L. J. (2015) Shared and distinct neuroanatomic regions critical for tool-related action production and recognition: Evidence from 131 left-hemisphere stroke patients. Journal of Cognitive Neuroscience 27(12):2491–511.CrossRefGoogle ScholarPubMed
Tomasino, B., Fabbro, F. & Brambilla, P. (2014) How do conceptual representations interact with processing demands: An fMRI study on action- and abstract-related words. Brain Research 1591:38–52.CrossRefGoogle Scholar
Tomasino, B. & Rumiati, R. (2013) At the mercy of strategies: The role of motor representations in language understanding. Frontiers in Psychology 4:27. doi: 10.3389/fpsyg.2013.00027.CrossRefGoogle ScholarPubMed
Wang, J., Conder, J. A., Blitzer, D. N. & Shinkareva, S. V. (2010) Neural representation of abstract and concrete concepts: A meta-analysis of neuroimaging studies. Human Brain Mapping 31(10):1459–68.CrossRefGoogle ScholarPubMed
Watson, C. E., Cardillo, E. R., Ianni, G. R. & Chatterjee, A. (2013) Action concepts in the brain: An activation likelihood estimation meta-analysis. Journal of Cognitive Neuroscience 25(8):1191–205. doi: 10.1162/jocn_a_00401.CrossRefGoogle ScholarPubMed