ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2019
Multivariate Analysis of Electrophysiological Signals Reveals the Temporal Properties of Visuomotor Computations for Precision Grips.
Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Article
- Phase-Dependent Visual and Sensorimotor Integration of Features for Grasp Computations before and after Effector Specification.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Computation on Demand: Action-Specific Representations of Visual Task Features Arise during Distinct Movement Phases.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Grasping with a Twist: Dissociating Action Goals from Motor Actions in Human Frontoparietal Circuits.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Decoding reach-to-grasp from EEG using classifiers trained with data from the contralateral limb.Frontiers in human neuroscience · 2023Article
- Multivariate Analysis of Electrophysiological Signals Reveals the Time Course of Precision Grasps Programs: Evidence for Nonhierarchical Evolution of Grasp Control.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
- Disentangling human grasping type from the object's intrinsic properties using low-frequency EEG signals.Neuroimage. Reports · 2021Article
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Authors and funding
5 authors.
Funding
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Abstract
The frontoparietal networks underlying grasping movements have been extensively studied, especially using fMRI. Accordingly, whereas much is known about their cortical locus much less is known about the temporal dynamics of visuomotor transformations. Here, we show that multivariate EEG analysis allows for detailed insights into the time course of visual and visuomotor computations of precision grasps. Male and female human participants first previewed one of several objects and, upon its reappearance, reached to grasp it with the thumb and index finger along one of its two symmetry axes. Object shape classifiers reached transient accuracies of 70% at ∼105 ms, especially based on scalp sites over visual cortex, dropping to lower levels thereafter. Grasp orientation classifiers relied on a system of occipital-to-frontal electrodes. Their accuracy rose concurrently with shape classification but ramped up more gradually, and the slope of the classification curve predicted individual reaction times. Further, cross-temporal generalization revealed that dynamic shape representation involved early and late neural generators that reactivated one another. In contrast, grasp computations involved a chain of generators attaining a sustained state about 100 ms before movement onset. Our results reveal the progression of visual and visuomotor representations over the course of planning and executing grasp movements.
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