Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-10T09:37:02.949Z Has data issue: false hasContentIssue false
  • English
  • Français

On the neural implausibility of the modular mind: Evidence for distributed construction dissolves boundaries between perception, cognition, and emotion

Published online by Cambridge University Press:  05 January 2017

Leor M. Hackel ,
Grace M. Larson ,
Jeffrey D. Bowen ,
Gaven A. Ehrlich ,
Thomas C. Mann ,
Brianna Middlewood ,
Ian D. Roberts ,
Julie Eyink ,
Janell C. Fetterolf  and
Fausto Gonzalez
...Show all authors
Leor M. Hackel
Affiliation:
Department of Psychology, New York University, New York, NY 10003. leor.hackel@nyu.edu
Grace M. Larson
Affiliation:
Department of Psychology, Northwestern University, Evanston, IL 60208. gracelarson2017@u.northwestern.edu
Jeffrey D. Bowen
Affiliation:
Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, CA 93106. bowen@psych.ucsb.edu
Gaven A. Ehrlich
Affiliation:
Department of Psychology, Syracuse University, Syracuse, NY 13244. gaehrlic@syr.edu
Thomas C. Mann
Affiliation:
Department of Psychology, Cornell University, Ithaca, NY 14853. tcm79@cornell.edu
Brianna Middlewood
Affiliation:
Department of Psychology, Pennsylvania State University, University Park, PA 16801. blm266@psu.educarlosgarrido@psu.edu
Ian D. Roberts
Affiliation:
Department of Psychology, The Ohio State University, Columbus, OH 43210. roberts.1134@osu.edu
Julie Eyink
Affiliation:
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405. jeyink@indiana.edu
Janell C. Fetterolf
Affiliation:
Department of Psychology, Rutgers University, Piscataway, NJ 08854. j.fetterolf@gmail.com
Fausto Gonzalez
Affiliation:
Department of Psychology, University of California, Berkeley, Berkeley, CA 94720. fjgonzal@berkeley.edu
Carlos O. Garrido
Affiliation:
Department of Psychology, Pennsylvania State University, University Park, PA 16801. blm266@psu.educarlosgarrido@psu.edu
Jinhyung Kim
Affiliation:
Department of Psychology, Texas A&M University, College Station, TX 77840. jhkim82@tamu.edu
Thomas C. O'Brien
Affiliation:
Department of Psychology, University of Massachusetts, Amherst, Amherst, MA 01003. tcobrien@psych.umass.edu
Ellen E. O'Malley
Affiliation:
Department of Psychology, State University of New York, Albany, Albany, NY 12222. ellen.e.omalley@gmail.com
Batja Mesquita
Affiliation:
Center for Social and Cultural Psychology, University of Leuven, B-3000 Leuven, Belgium.mesquita@psy.kuleuven.be
Lisa Feldman Barrett
Affiliation:
Department of Psychology, Northeastern University, Boston, MA 02115. l.barrett@neu.edu Department of Psychiatry and the Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Boston, MA 02114.
Get access Rights & Permissions [Opens in a new window]

Abstract

Firestone & Scholl (F&S) rely on three problematic assumptions about the mind (modularity, reflexiveness, and context-insensitivity) to argue cognition does not fundamentally influence perception. We highlight evidence indicating that perception, cognition, and emotion are constructed through overlapping, distributed brain networks characterized by top-down activity and context-sensitivity. This evidence undermines F&S's ability to generalize from case studies to the nature of perception.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 39 , 2016 , e246
Copyright
Copyright © Cambridge University Press 2016 

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

Alink, A., Schwiedrzik, C. M., Kohler, A., Singer, W. & Muckli, L. (2010) Stimulus predictability reduces responses in primary visual cortex. The Journal of Neuroscience 30(8):2960–66.Google Scholar
Anderson, M. L. (2014) After phrenology: Neural reuse and the interactive brain. MIT Press.CrossRefGoogle Scholar
Bar, M. (2007) The proactive brain: Using analogies and associations to generate predictions. Trends in Cognitive Sciences 11(7):280–89.CrossRefGoogle ScholarPubMed
Barbas, H. (2015) General cortical and special prefrontal connections: Principles from structure to function. Annu Rev Neurosci 38:269–89.CrossRefGoogle ScholarPubMed
Barrett, L. F. (2009) The future of psychology: Connecting mind to brain. Perspectives on Psychological Science 4(4):326–39.CrossRefGoogle Scholar
Barrett, L. F. & Satpute, A. B. (2013) Large-scale brain networks in affective and social neuroscience: Towards an integrative functional architecture of the brain. Current Opinion in Neurobiology 23(3):361–72.Google Scholar
Barrett, L. F. & Simmons, W. K. (2015) Interoceptive predictions in the brain. Nature Reviews Neuroscience 16:419–29.Google Scholar
Barrett, L. F., Tugade, M. M. & Engle, R. W. (2004) Individual differences in working memory capacity and dual-process theories of the mind. Psychological Bulletin 130:553–73. PMCID: PMC1351135.Google Scholar
Behrens, T. E. J., Woolrich, M. W., Walton, M. E. & Rushworth, M. F. A. (2007) Learning the value of information in an uncertain world. Nature Neuroscience 10:1214–21.Google Scholar
Chanes, L. & Barrett, L. F. (2016) Redefining the role of limbic areas in cortical processing. Trends in Cognitive Sciences 20(2):96–106.CrossRefGoogle ScholarPubMed
Cisek, P. & Klaska, J. F. (2010) Neural mechanisms for interacting with a world full of action choices. Annual Review of Neuroscience 33:269–98.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
Clark-Polner, E., Wager, T. D., Satpute, A. B. & Barrett, L. F. (2016) “Brain-based fingerprints?” Variation, and the search for neural essences in the science of emotion. In: The handbook of emotion, fourth edition, ed. Barrett, L. F., Lewis, M. & Haviland-Jones, J. M., pp. 146–65. Guilford.Google Scholar
Den Ouden, H. E., Kok, P. & De Lange, F. P. (2012) How prediction errors shape perception, attention, and motivation. Frontiers in Psychology 3:548.Google Scholar
Descartes, R. (1989) On the passions of the soul. Hackett (Original work published 1649).Google Scholar
Egner, T., Monti, J. M. & Summerfield, C. (2010) Expectation and surprise determine neural population responses in the ventral visual stream. The Journal of Neuroscience 30(49):16601–608.CrossRefGoogle ScholarPubMed
Finger, S. (2001) Origins of neuroscience: A history of explorations into brain function. Oxford University Press.Google Scholar
Fodor, J. A. (1983) Modularity of mind: An essay on faculty psychology. MIT Press.CrossRefGoogle Scholar
Friston, K (2010) The free-energy principle: A unified brain theory? Nature Reviews Neuroscience 11:127–38.Google Scholar
Gall, F. J. (1835) On the functions of the brain and of each of its parts: With observations on the possibility of determining the instincts, propensities, and talents, or the moral and intellectual dispositions of men and animals, by the configuration of the brain and head, vol. 1. Marsh, Capen & Lyon.Google Scholar
Gilbert, C. D. & Li, W. (2013) Top-down influences on visual processing. Nature Reviews Neuroscience 14(5):350–63.Google Scholar
Gilbert, C. D. & Sigman, M. (2007) Brain states: Top-down influences in sensory processing. Neuron 54(5):677–96.Google Scholar
Gottlieb, J. (2012) Attention, learning, and the value of information. Neuron 76(2):281–95.CrossRefGoogle ScholarPubMed
Hart, W., Tullett, A. M., Shreves, W. B. & Fetterman, Z. (2015) Fueling doubt and openness: Experiencing the unconscious, constructed nature of perception induces uncertainty and openness to change. Cognition 137:1–8.Google Scholar
Lindquist, K. A. & Barrett, L. F. (2012) A functional architecture of the human brain: Emerging insights from the science of emotion. Trends in Cognitive Sciences 16(11):533–40.CrossRefGoogle ScholarPubMed
Makino, H. & Komiyama, T. (2015) Learning enhances the relative impact of top-down processing in the visual cortex. Nature Neuroscience 18(8):1116–22.Google Scholar
Marder, E. (2012) Neuromodulation of neuronal circuits: Back to the future. Neuron 76(1):1–11.Google Scholar
Pessoa, L. (2015) Précis on The Cognitive-Emotional Brain . Behavioral and Brain Sciences 38:e71.Google Scholar
Peters, A. (2002) Examining neocortical circuits: Some background and facts. Journal of Neurocytology 31 (3–5):183–93.Google Scholar
Pezzulo, G. (2012) An active inference view of cognitive control. Frontiers in Psychology 3:478.Google Scholar
Pinker, S. (1997) How the mind works. Norton.Google Scholar
Rao, R. P. & Ballard, D. H. (1999) Predictive coding in the visual cortex: A functional interpretation of some extra-classical receptive-field effects. Nature Neuroscience 2(1):79–87.CrossRefGoogle ScholarPubMed
Ross, L. & Ward, A. (1996) Naïve realism in everyday life: Implications for social conflict and misunderstanding. In: Values and knowledge, ed. Reed, E. S., Turiel, E. & Brown, T., pp. 103–35. Erlbaum.Google Scholar
Sporns, O. (2011) The human connectome: A complex network. Annals of the New York Academy of Sciences 1224(1):109–25.Google Scholar
Stefanucci, J. K. & Geuss, M. N. (2009) Big people, little world: The body influences size perception. Perception 38:1782–95.Google Scholar
Sterling, P. & Laughlin, S. (2015) Principles of neural design. MIT Press.Google Scholar
van den Heuvel, M. P. & Sporns, O. (2013) Network hubs in the human brain. Trends in Cognitive Sciences 17(12):683–96.CrossRefGoogle ScholarPubMed
Yarkoni, T., Poldrack, R. A., Nichols, T. E., Van Essen, D. C. & Wager, T. D. (2011) Large-scale automated synthesis of human functional neuroimaging data. Nature Methods 8(8):665–70.CrossRefGoogle ScholarPubMed
Yeo, B. T., Krienen, F. M., Eickhoff, S. B., Yaakub, S. N., Fox, P. T., Buckner, R. L., Asplund, C. L. & Chee, M. W. (2015) Functional specialization and flexibility in human association cortex. Cerebral Cortex 25(10):3654–72.CrossRefGoogle ScholarPubMed