Computational mechanism underlying switching of motor actions.

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS PLoS Computational Biology Pub Date : 2025-02-10 DOI:10.1371/journal.pcbi.1012811
Shan Zhong, Nader Pouratian, Vassilios Christopoulos
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Abstract

Survival of species in an ever-changing environment requires a flexibility that extends beyond merely selecting the most appropriate actions. It also involves readiness to stop or switch actions in response to environmental changes. Although considerable research has been devoted to understanding how the brain switches actions, the computations underlying the switching process and how it relates to the selecting and stopping processes remain elusive. A normative theory suggests that switching is simply an extension of the stopping process, during which a current action is first inhibited by an independent pause mechanism before a new action is generated. This theory was challenged by the affordance competition hypothesis, according to which the switching process is implemented through a competition between the current and new actions, without engaging an independent pause mechanism. To delineate the computations underlying these action regulation functions, we utilized a neurocomputational theory that models the process of selecting, stopping and switching reaching movements. We tested the model predictions in healthy individuals who performed reaches in dynamic and uncertain environments that often required stopping and switching actions. Our findings suggest that unlike the stopping process, switching does not necessitate a proactive pause mechanism to delay movement initiation. Hence, the switching and stopping processes seem to be implemented by different mechanisms at the planning phase of the reaching movement. However, once the reaching movement has been initiated, the switching process seems to involve an independent pause mechanism if the new target location is unknown prior to movement initiation. These findings offer a new understanding of the computations underlying action switching, contribute valuable insights into the fundamental neuroscientific mechanisms of action regulation, and open new avenues for future neurophysiological investigations.

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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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