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More dynamical and more symbiotic: Cortico-striatal models of resolve, suppression, and routine habit

Published online by Cambridge University Press:  26 April 2021

Linus Ta-Lun Huang Open the ORCID record for Linus Ta-Lun Huang [Opens in a new window]
Linus Ta-Lun Huang*
Affiliation:
Department of Philosophy, University of California, San Diego, La Jolla, CA 92093 linusthuang@gmail.com Philosophy Program, Institute of European and American Studies, Academia Sinica, Taipei 11529, Taiwan.
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Abstract

I extend Ainslie's core claims with three cortico-striatal models that respectively subserve the key constructs of resolve, suppression, and routine habit. I show that these models suggest a more dynamical and symbiotic relation among the constructs: there are more ways they interact to reinforce willpower, and the temporal dimension of the interactions can often determine the effectiveness of the reinforcement.

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Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 44 , 2021 , e41
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Creative Commons
The target article and response article are works of the U.S. Government and are not subject to copyright protection in the United States.
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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References

Dayan, P., & Berridge, K. C. (2014). Model-based and model-free Pavlovian reward learning: Revaluation, revision, and revelation. Cognitive, Affective, & Behavioral Neuroscience, 14(2), 473–492. https://doi.org/10.3758/s13415-014-0277-8.CrossRefGoogle ScholarPubMed
Dolan, R. J., & Dayan, P. (2013). Goals and habits in the brain. Neuron, 80(2), 312–325. https://doi.org/10.1016/j.neuron.2013.09.007.CrossRefGoogle Scholar
Gershman, S. J., Daw, N. D., Rabinovich, M. I., Friston, K. J., & Varona, P. (2012). Perception, action and utility: The tangled skein. In M. I. Rabinovich, K. J. Friston, & P. Varona, (Ed.), Principles of brain dynamics: Global state interactions (pp. 293–312). MIT Press.Google Scholar
Hélie, S., Ell, S. W., & Ashby, F. G. (2015). Learning robust cortico-cortical associations with the basal ganglia: An integrative review. Cortex, 64, 123–135. https://doi.org/10.1016/j.cortex.2014.10.011.CrossRefGoogle Scholar
Huang, L. T.-L. (2017). Neurodemocracy: Self-Organization of the Embodied Mind (Ph.D. dissertation). University of Sydney.Google Scholar
Ito, M., & Doya, K. (2011). Multiple representations and algorithms for reinforcement learning in the cortico-basal ganglia circuit. Current Opinion in Neurobiology, 21(3), 368–373. https://doi.org/10.1016/j.conb.2011.04.001.CrossRefGoogle ScholarPubMed
Minsky, M. L. (1986). The society of mind. Simon and Schuster.Google Scholar
Wiecki, T. V., & Frank, M. J. (2013). A computational model of inhibitory control in frontal cortex and basal ganglia. Psychological Review, 120(2), 329–355. https://doi.org/10.1037/a0031542.CrossRefGoogle ScholarPubMed