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Précis of After Phrenology: Neural Reuse and the Interactive Brain

Published online by Cambridge University Press:  16 June 2015

Michael L. Anderson
Michael L. Anderson*
Affiliation:
Department of Psychology, Franklin & Marshall College, Lancaster, PA [email protected]://www.fandm.edu/michael-anderson
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Abstract

Neural reuse is a form of neuroplasticity whereby neural elements originally developed for one purpose are put to multiple uses. A diverse behavioral repertoire is achieved by means of the creation of multiple, nested, and overlapping neural coalitions, in which each neural element is a member of multiple different coalitions and cooperates with a different set of partners at different times. Neural reuse has profound implications for how we think about our continuity with other species, for how we understand the similarities and differences between psychological processes, and for how best to pursue a unified science of the mind. After Phrenology: Neural Reuse and the Interactive Brain (2014; henceforth After Phrenology in this Précis) surveys the terrain and advocates for a series of reforms in psychology and cognitive neuroscience. The book argues that, among other things, we should capture brain function in a multidimensional manner, develop a new, action-oriented vocabulary for psychology, and recognize that higher-order cognitive processes are built from complex configurations of already evolved circuitry.

Keywords

dynamic systemsembodied cognitionevolutionmodularitynatural selectionneuroplasticitypragmatism
Type
Target Article
Information
Behavioral and Brain Sciences , Volume 39 , 2016 , e120
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Copyright
Copyright © Cambridge University Press 2016 

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References

Aboitiz, F. (1996) Does bigger mean better? Evolutionary determinants of brain size and structure. Brain, Behavior and Evolution 47:225–45.CrossRefGoogle ScholarPubMed
Agnati, L. F., Guidolin, D., Guescini, M., Genedani, S. & Fuxe, K. (2010) Understanding wiring and volume transmission. Brain Research Review 64:137–59.Google Scholar
Anderson, M. L. (2008a) Circuit sharing and the implementation of intelligent systems. Connection Science 20(4):239–51.Google Scholar
Anderson, M. L. (2010) Neural reuse: A fundamental organizational principle of the brain. Behavioral and Brain Sciences 33(4):245–66. doi: 10.1017/S0140525X10000853.CrossRefGoogle ScholarPubMed
Anderson, M. L. (2014) After phrenology: Neural reuse and the interactive brain. MIT Press.Google Scholar
Anderson, M. L. (2015) Beyond componential constitution in the brain: Starburst amacrine cells and enabling constraints. In: Open MIND, ed. Metzinger, T. K. & Windt, J. M.. MIND Group. doi: 10.15502/9783958570429.Google Scholar
Anderson, M. L. & Finlay, B. (2014) Allocating structure to function: The strong links between neuroplasticity and natural selection. Frontiers in Human Neuroscience 7:918.Google Scholar
Anderson, M. L., Kinnison, J. & Pessoa, L. (2013) Describing functional diversity of brain regions and brain networks. NeuroImage 73:50–58.CrossRefGoogle ScholarPubMed
Anderson, M. L. & Penner-Wilger, M. (2013) Neural reuse in the evolution and development of the brain: Evidence for developmental homology? Developmental Psychobiology 55(1):42–51.Google Scholar
Atkinson, J. (1984) Human visual development over the first 6 months of life. A review and a hypothesis. Human Neurobiology 3(2):61–74.Google Scholar
Bargh, J. A. & Shalev, I. (2012) The substitutability of physical and social warmth in daily life. Emotion 12(1):154–62.Google Scholar
Bargmann, C. I. (2012) Beyond the connectome: How neuromodulators shape neural circuits. Bioessays 34(6):458–65.Google Scholar
Barrett, H. C. & Kurzban, R. (2006) Modularity in cognition: Framing the debate. Psychological Review 113(3):628.Google Scholar
Barrett, L. F. & Satpute, A. (2013) Large-scale brain networks in affective and social neuroscience: Towards an integrative architecture of the human brain. Current Opinion in Neurobiology 23:1–12.Google Scholar
Bauer, M., Heinz, A. & Whybrow, P. C. (2001) Thyroid hormones, serotonin and mood: Of synergy and significance in the adult brain. Molecular Psychiatry 7(2):140–56.Google Scholar
Buss, D. M., ed. (2005) The handbook of evolutionary psychology. John Wiley.Google Scholar
Carruthers, P. (2006) The architecture of the mind: Massive modularity and the flexibility of thought. Oxford University Press.Google Scholar
Chomsky, N. (1957) Syntactic structures. Mouton.Google Scholar
Cisek, P. (1999) Beyond the computer metaphor: Behaviour as interaction. Journal of Consciousness Studies 6 (11–12):125–42.Google Scholar
Cisek, P. (2007) Cortical mechanisms of action selection: The affordance competition hypothesis. Philosophical Transactions of the Royal Society B: Biological Sciences 362(1485):1585–99.Google Scholar
Cisek, P. & Kalaska, J. F. (2005) Neural correlates of reaching decisions in dorsal premotor cortex: Specification of multiple direction choices and final selection of action. Neuron 45(5):801–14.Google Scholar
Cisek, P. & Kalaska, J. F. (2010) Neural mechanisms for interacting with a world full of action choices. Annual Review of Neuroscience 33:269–98.Google Scholar
Clark, A. (1997) Being there: Putting brain, body, and world together again. MIT Press.Google Scholar
Clark, H. H. (1996) Using language. Cambridge University Press.CrossRefGoogle Scholar
Cole, M. W., Reynolds, J. R., Power, J. D., Repovs, G., Anticevic, A. & Braver, T. S. (2013) Multi-task connectivity reveals flexible hubs for adaptive task control. Nature Neuroscience 16(9):1348–55.Google Scholar
Confer, J. C., Easton, J. A., Fleischman, D. S., Goetz, C. D., Lewis, D. M., Perilloux, C. & Buss, D. M. (2010) Evolutionary psychology: Controversies, questions, prospects, and limitations. American Psychologist 65(2):110–26.Google Scholar
Craver, C. (2007) Explaining the brain: Mechanisms and the mosaic unity of neuroscience. Oxford University Press.CrossRefGoogle Scholar
Desimone, R. & Duncan, J. (1995) Neural mechanisms of selective visual attention. Annual Review of Neuroscience 18(1):193–222.Google Scholar
Edelman, S. (2008) Computing the mind: How the mind really works. Oxford University Press.Google Scholar
Finlay, B. L. & Darlington, R. B. (1995) Linked regularities in the development and evolution of mammalian brains. Science 268:1578–84.Google Scholar
Finlay, B. L., Darlington, R. B. & Nicastro, N. (2001) Developmental structure in brain evolution. Behavioral and Brain Sciences 24:263–307.CrossRefGoogle ScholarPubMed
Gibson, J. J. (1966) The senses considered as perceptual systems. Houghton-Mifflin.Google Scholar
Gibson, J. J. (1979) The ecological approach to visual perception. Erlbaum.Google Scholar
Glenberg, A. M. & Kaschak, M. P. (2002) Grounding language in action. Psychonomic Bulletin and Review 9(3):558–65.Google Scholar
Glenberg, A. M., Sato, M. & Cattaneo, L. (2008) Use-induced motor plasticity affects the processing of abstract and concrete language. Current Biology 18(7):R290–91.CrossRefGoogle ScholarPubMed
Gold, K., Havasi, C., Anderson, M. & Arnold, K. (2011) Comparing matrix decomposition methods for meta-analysis and reconstruction of cognitive neuroscience results. Proceedings of the Twenty-Fourth Annual Conference of the Florida Artificial Intelligence Research Society 24:21–26.Google Scholar
Hermans, E. J., van Marle, H. J., Ossewaarde, L., Henckens, M. J., Qin, S., van Kesteren, M. T., Schoots, V. C., Cousijn, H., Rijpkema, M., Oostenveld, R. & Fernández, G. (2011) Stress-related noradrenergic activity prompts large-scale neural network reconfiguration. Science 334(6059):1151–53.Google Scholar
Holtmaat, A. & Svoboda, K. (2009) Experience dependent structural synaptic plasticity in the mammalian brain. Nature Reviews Neuroscience 10:647–58.Google Scholar
James, W. (1890) The principles of psychology. Henry Holt.Google Scholar
Johnson, M. H. (2001) Functional brain development in humans. Nature Reviews Neuroscience 2(7):475–83.CrossRefGoogle ScholarPubMed
Johnson, M. H. (2011) Interactive specialization: A domain-general framework for human functional brain development? Developmental Cognitive Neuroscience 1(1):7–21.Google Scholar
Kanwisher, N. (2010) Functional specificity in the human brain: A window into the functional architecture of the mind. Proceedings of the National Academy of Sciences, USA 107(25):11163–70.Google Scholar
Landy, D. & Goldstone, R. L. (2009) How much of symbolic manipulation is just symbol pushing? In: Proceedings of the Thirty-First Annual Conference of the Cognitive Science Society, Amsterdam, Netherlands, July 29–August 1, 2009, ed. Taatgen, N. A. & van Rijn, H., pp. 1072–77. Cognitive Science Society.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 16:533–40.Google Scholar
Lindquist, K. A., Wager, T. D., Kober, H., Bliss-Moreau, E. & Barrett, L. F. (2012) The brain basis of emotion: A meta-analytic review. Behavioral and Brain Sciences 35(3):121–43.Google Scholar
Marr, D. (1982) Vision. W. H. Freeman.Google Scholar
Merabet, L. B., Hamilton, R., Schlaug, G., Swisher, J. D., Kiriakapoulos, E. T., Pitskel, N. B., Kauffman, T. & Pascual-Leone, A. (2008) Rapid and reversible recruitment of early visual cortex for touch. PLoS One 3(8):e3046: 1–12.Google Scholar
Miller, E. K. & Cohen, J. D. (2001) An integrative theory of prefrontal cortex function. Annual Review of Neuroscience 24:167–202.Google Scholar
Murray, D. J., Ellis, R. R., Bandomir, C. A. & Ross, H. E. (1999) Charpentier (1891) on the size-weight illusion. Perception and Psychophysics 61:1681–85.Google Scholar
Noë, A. (2004) Action in perception. MIT Press.Google Scholar
Pfaff, D. W. (2002) Hormones, brain and behavior, five-volume set. Academic Press.Google Scholar
Platt, M. L. (2002) Neural correlates of decisions. Current Opinion in Neurobiology 12:141–48.CrossRefGoogle ScholarPubMed
Poldrack, R. A. (2010) Mapping mental function to brain structure: How can cognitive neuroimaging succeed? Perspectives on Psychological Science 5(6):753–61.Google Scholar
Poldrack, R. A., Halchenko, Y. O. & Hanson, S. J. (2009) Decoding the large-scale structure of brain function by classifying mental states across individuals. Psychological Science 20:1364–72.Google Scholar
Price, C. J. & Friston, K. J. (2005) Functional ontologies for cognition: The systematic definition of structure and function. Cognitive Neuropsychology 22 (3–4):262–75.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. Proceedings of the National Academy of Sciences, USA 98:676–82.Google Scholar
Rigotti, M., Barak, O., Warden, M. R., Wang, X. J., Daw, N. D., Miller, E. K. & Fusi, S. (2013) The importance of mixed selectivity in complex cognitive tasks. Nature 497(7451):585–90.Google Scholar
Roux, F. E., Boetto, S., Sacko, O., Chollet, F. & Trémoulet, M. (2003) Writing, calculating, and finger recognition in the region of the angular gyrus: A cortical stimulation study of Gerstmann syndrome. Journal of Neurosurgery 99(4):716–27.Google Scholar
Rusconi, E., Walsh, V. & Butterworth, B. (2005) Dexterity with numbers: rTMS over left angular gyrus disrupts finger gnosis and number processing. Neuropsychologia 43(11):1609–24.Google Scholar
Sebanz, N., Bekkering, H. & Knoblich, G. (2006) Joint action: Bodies and minds moving together. Trends in Cognitive Sciences 10(2):70–76.Google Scholar
Shannon, C. E. (1948) A mathematical theory of communication. Bell System Technical Journal 27(3):379–423. doi:10.1002/j.1538-7305.1948.tb01338.x.Google Scholar
Song, S., Miller, K. D. & Abbott, L. F. (2000) Competitive Hebbian learning through spike-timing-dependent synaptic plasticity. Nature Neuroscience 3(9):919–26.Google Scholar
Stephan, H., Baron, G. & Frahm, H. D. (1988) Comparative size of brain and brain components. In: Comparative primate biology, ed. Steklis, H. D. & Erwin, J., pp. 1–38. Alan R. Liss.Google Scholar
Tomasello, M. (1999) The cultural origins of human cognition. Harvard University Press.Google Scholar
van Gelder, T. (1995) What might cognition be, if not computation? The Journal of Philosophy 92(7):345–81.Google Scholar
Xiao, Y. J. & Van Bavel, J. J. (2012) See your friends close and your enemies closer: Social identity and identity threat shape the representation of physical distance. Personality and Social Psychology Bulletin 38(7):959–72.CrossRefGoogle ScholarPubMed
Yopak, K. E., Lisney, T. J., Darlington, R. B., Collin, S. P., Montgomery, J. C. & Finlay, B. L. (2010) A conserved pattern of brain scaling from sharks to primates. Proceedings of the National Academy of Sciences USA 107:12946–51.Google Scholar
Zhu, Q. & Bingham, G. P. (2011) Human readiness to throw: The size-weight illusion is not an illusion when picking the best objects to throw. Evolution and Human Behavior 32(4):288–93. doi: 10.1016/j.evolhumbehav.2010.11.005.Google Scholar