Parallel specification of competing sensorimotor control policies for alternative action options
Open accessAbstract
Recent theory proposes that the brain, when confronted with several action possibilities, prepares multiple competing movements before deciding among them. Psychophysical supporting evidence for this idea comes from the observation that when reaching towards multiple potential targets, the initial movement is directed towards the average location of the targets, consistent with multiple prepared reaches being executed simultaneously. However, reach planning involves far more than specifying movement direction; it requires the specification of a sensorimotor control policy that sets feedback gains shaping how the motor system responds to errors induced by noise or external perturbations. Here we found that, when a subject is reaching towards multiple potential targets, the feedback gain corresponds to an average of the gains specified when reaching to each target presented alone. Our findings provide evidence that the brain, when presented with multiple action options, computes multiple competing sensorimotor control policies in parallel before implementing one of them.
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Using Bayesian logic, a brain uses pattern completion to decide among simulations and implement one based on predicted maintenance of physiological efficiency across multiple body systems.
“Using Bayesian logic (Deneve, 2008; Bastos et al., 2012), a brain uses pattern completion to decide among simulations and implement one of them (Gallivan et al., 2016), based on predicted maintenance of physiological efficiency across multiple body systems”
From The theory of constructed emotion: an active inference account of interoception and categorization (2016) · cites this paper as Gallivan et al., 2016
The Introduction (page unavailable) says the brain prepares multiple potential movements in parallel before deciding between and implementing one. That supports the selection-and-implementation part attributed to Gallivan et al., but the paper does not describe this as pattern completion among simulations. The Bayesian-logic and physiological-efficiency clauses are not attached to this citation. (LLM, conf=0.88)
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- Authors
- Gallivan, J. P., Logan, L., Wolpert, D. M., & Flanagan, J. R.
- Affiliations
- Queen's University (CA)
- University of Cambridge (GB)
- Corresponding author
- Gallivan, Jason P
- Flanagan, J Randall
- Venue
- Nature Neuroscience
- Published
- 2016-01-11
- Volume
- 19
- Issue
- 2
- Pages
- 320-326
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- PMC
- PMC6103436
- OpenAlex
- W2239228331
- Cited by
- 124
- References
- 57
- Citations by year
- 2026: 9 · 2025: 6 · 2024: 6 · 2023: 10 · 2022: 17 · 2021: 12 · 2020: 10 · 2019: 12 · 2018: 14 · 2017: 15 · 2016: 13
- FWCI
- 11.45
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Cambridge University Engineering Department Publications Database (submittedVersion)
- Apollo (University of Cambridge) (submittedVersion)
- Apollo
- Funders
- Wellcome Trust (097803, 097803/Z/11/Z)
- Canadian Institutes of Health Research
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Free Will and Agency
- Keywords
- sensorimotor control, feedback gain, reach planning, movement selection, motor noise, perturbation response
- MeSH terms
- Adolescent, Brain, Female, Humans, Male, Movement, Noise, Photic Stimulation, Psychomotor Performance, Sensation, Feedback, Psychological, Young Adult
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