Literature DB >> 25079472

The computational and neural basis of cognitive control: charted territory and new frontiers.

Matthew M Botvinick1, Jonathan D Cohen.   

Abstract

Cognitive control has long been one of the most active areas of computational modeling work in cognitive science. The focus on computational models as a medium for specifying and developing theory predates the PDP books, and cognitive control was not one of the areas on which they focused. However, the framework they provided has injected work on cognitive control with new energy and new ideas. On the occasion of the books' anniversary, we review computational modeling in the study of cognitive control, with a focus on the influence that the PDP approach has brought to bear in this area. Rather than providing a comprehensive review, we offer a framework for thinking about past and future modeling efforts in this domain. We define control in terms of the optimal parameterization of task processing. From this vantage point, the development of control systems in the brain can be seen as responding to the structure of naturalistic tasks, through the filter of the brain systems with which control directly interfaces. This perspective lays open a set of fascinating but difficult research questions, which together define an important frontier for future computational research.
Copyright © 2014 Cognitive Science Society, Inc.

Entities:  

Keywords:  Cognitive control; Computational modeling

Mesh:

Year:  2014        PMID: 25079472     DOI: 10.1111/cogs.12126

Source DB:  PubMed          Journal:  Cogn Sci        ISSN: 0364-0213


  63 in total

1.  A diffusion model analysis of sustained attention in children with attention deficit hyperactivity disorder.

Authors:  Cynthia Huang-Pollock; Roger Ratcliff; Gail McKoon; Alexandra Roule; Tyler Warner; Jason Feldman; Shane Wise
Journal:  Neuropsychology       Date:  2020-04-23       Impact factor: 3.295

Review 2.  The expected value of control: an integrative theory of anterior cingulate cortex function.

Authors:  Amitai Shenhav; Matthew M Botvinick; Jonathan D Cohen
Journal:  Neuron       Date:  2013-07-24       Impact factor: 17.173

3.  Assessing the role of reward in task selection using a reward-based voluntary task switching paradigm.

Authors:  David A Braun; Catherine M Arrington
Journal:  Psychol Res       Date:  2017-09-26

4.  Individual Neurons in the Cingulate Cortex Encode Action Monitoring, Not Selection, during Adaptive Decision-Making.

Authors:  Yin S Li; Matthew R Nassar; Joseph W Kable; Joshua I Gold
Journal:  J Neurosci       Date:  2019-06-19       Impact factor: 6.167

5.  Why has evolution not selected for perfect self-control?

Authors:  Benjamin Y Hayden
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-02-18       Impact factor: 6.237

Review 6.  Mental labour.

Authors:  Wouter Kool; Matthew Botvinick
Journal:  Nat Hum Behav       Date:  2018-09-03

7.  The test of both worlds: identifying feature binding and control processes in congruency sequence tasks by means of action dynamics.

Authors:  Stefan Scherbaum; Simon Frisch; Maja Dshemuchadse; Matthias Rudolf; Rico Fischer
Journal:  Psychol Res       Date:  2016-11-07

Review 8.  Comparative psychometrics: establishing what differs is central to understanding what evolves.

Authors:  Christoph J Völter; Brandon Tinklenberg; Josep Call; Amanda M Seed
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2018-09-26       Impact factor: 6.237

Review 9.  The algorithmic anatomy of model-based evaluation.

Authors:  Nathaniel D Daw; Peter Dayan
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2014-11-05       Impact factor: 6.237

Review 10.  Control without Controllers: Toward a Distributed Neuroscience of Executive Control.

Authors:  Benjamin R Eisenreich; Rei Akaishi; Benjamin Y Hayden
Journal:  J Cogn Neurosci       Date:  2017-04-21       Impact factor: 3.225

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