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Computation on Demand: Action-Specific Representations of Visual Task Features Arise during Distinct Movement Phases.

Authors :
Lee, Nina
Guo, Lin Lawrence
Nestor, Adrian
Niemeier, Matthias
Source :
Journal of Neuroscience. 7/17/2024, Vol. 44 Issue 29, p1-12. 12p.
Publication Year :
2024

Abstract

The intention to act influences the computations of various task-relevant features. However, little is known about the time course of these computations. Furthermore, it is commonly held that these computations are governed by conjunctive neural representations of the features. But, support for this view comes from paradigms arbitrarily combining task features and affordances, thus requiring representations in working memory. Therefore, the present study used electroencephalography and a well-rehearsed task with features that afford minimal working memory representations to investigate the temporal evolution of feature representations and their potential integration in the brain. Female and male human participants grasped objects or touched them with a knuckle. Objects had different shapes and were made of heavy or light materials with shape and weight being relevant for grasping, not for “knuckling.” Using multivariate analysis showed that representations of object shape were similar for grasping and knuckling. However, only for grasping did early shape representations reactivate at later phases of grasp planning, suggesting that sensorimotor control signals feed back to the early visual cortex. Grasp-specific representations of material/weight only arose during grasp execution after object contact during the load phase. A trend for integrated representations of shape and material also became graspspecific but only briefly during the movement onset. These results suggest that the brain generates action-specific representations of relevant features as required for the different subcomponents of its action computations. Our results argue against the view that goaldirected actions inevitably join all features of a task into a sustained and unified neural representation. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02706474
Volume :
44
Issue :
29
Database :
Academic Search Index
Journal :
Journal of Neuroscience
Publication Type :
Academic Journal
Accession number :
178521357
Full Text :
https://doi.org/10.1523/JNEUROSCI.2100-23.2024