Multivariate analysis of electrophysiological signals reveals the temporal properties of visuomotor computations for precision grips

Abstract

Thefrontoparietal networks underlying grasping movements have been extensively studied, especially usingfMRI. Accordingly, whereas much is known abouttheir cortical locus much less is known aboutthetemporal dynamics of visuomotortransformations. Here, we show that multivariate EEG analysis allows for detailed insights into the time course of visual and visuomotor computations of precision grasps. Male andfemale human participantsfirst previewed one of several objects and, upon its reappearance, reachedto grasp it withthe 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, andthe 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.