Integrated neural processes for defining potential actions and deciding between them: a computational model
Open accessAbstract
To successfully accomplish a behavioral goal such as reaching for an object, an animal must solve two related problems: to decide which object to reach and to plan the specific parameters of the movement. Traditionally, these two problems have been viewed as separate, and theories of decision making and motor planning have been developed primarily independently. However, neural data suggests that these processes involve the same brain regions and are performed in an integrated manner. Here, a computational model is described that addresses both the question of how different potential actions are specified and how the brain decides between them. In the model, multiple potential actions are simultaneously represented as continuous regions of activity within populations of cells in frontoparietal cortex. These representations engage in a competition for overt execution that is biased by modulatory influences from prefrontal cortex. The model neural populations exhibit activity patterns that correlate with both the spatial metrics of potential actions and their associated decision variables, in a manner similar to activities in parietal, prefrontal, and premotor cortex. The model therefore suggests an explanation for neural data that have been hard to account for in terms of serial theories that propose that decision making occurs before action planning. In addition to simulating the activity of individual neurons during decision tasks, the model also reproduces key aspects of the spatial and temporal statistics of human choices and makes a number of testable predictions.
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A decision is likely to involve parallel processing across brain regions rather than proceeding strictly in serial stages.
“Rather than proceeding strictly in serial stages, a decision is likely to involve parallel processing across brain regions.”
From Decision Making in Recurrent Neuronal Circuits (2008) · cites this paper as Cisek, 2006
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“Indeed, a recurrent circuit approach has been used to build models for action selection and movement preparation (Wilimzig et al., 2006; Cisek, 2006; Heinzle et al., 2007).”
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- Authors
- Cisek, P.
- Affiliations
- Université de Montréal (CA)
- Corresponding author
- Cisek, Paul
- ORCID
- Cisek, Paul
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2006-09-20
- Volume
- 26
- Issue
- 38
- Pages
- 9761-9770
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC6674435
- OpenAlex
- W2042907834
- Cited by
- 344
- References
- 72
- Citations by year
- 2026: 2 · 2025: 9 · 2024: 8 · 2023: 11 · 2022: 15 · 2021: 11 · 2020: 42 · 2019: 9 · 2018: 25 · 2017: 16 · 2016: 15 · 2015: 26 · 2014: 30 · 2013: 26 · 2012: 20
- FWCI
- 6.96
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Canadian Institutes of Health Research
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- action selection, decision-making, motor planning, frontoparietal cortex, prefrontal cortex, population coding, computational models of decision making
- MeSH terms
- Decision Making, Models, Neurological, Neurons, Neural Networks, Computer, Computational Biology
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