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Multivariate Analysis of Electrophysiological Signals Reveals the Time Course of Precision Grasps Programs: Evidence for Nonhierarchical Evolution of Grasp Control
Authors:Lin Lawrence Guo  Yazan Shamli Oghli  Adam Frost  Matthias Niemeier
Affiliation:1.Department of Psychology, University of Toronto Scarborough, Toronto, Ontario M1C 1A4, Canada;2.Centre for Vision Research, York University, Toronto, Ontario M4N 3M6, Canada;3.Vision: Science to Applications, York University, Toronto, Ontario M3J 1P3, Canada
Abstract:Current understanding of the neural processes underlying human grasping suggests that grasp computations involve gradients of higher to lower level representations and, relatedly, visual to motor processes. However, it is unclear whether these processes evolve in a strictly canonical manner from higher to intermediate and to lower levels given that this knowledge importantly relies on functional imaging, which lacks temporal resolution. To examine grasping in fine temporal detail here we used multivariate EEG analysis. We asked participants to grasp objects while controlling the time at which crucial elements of grasp programs were specified. We first specified the orientation with which participants should grasp objects, and only after a delay we instructed participants about which effector to use to grasp, either the right or the left hand. We also asked participants to grasp with both hands because bimanual and left-hand grasping share intermediate-level grasp representations. We observed that grasp programs evolved in a canonical manner from visual representations, which were independent of effectors to motor representations that distinguished between effectors. However, we found that intermediate representations of effectors that partially distinguished between effectors arose after representations that distinguished among all effector types. Our results show that grasp computations do not proceed in a strictly hierarchically canonical fashion, highlighting the importance of the fine temporal resolution of EEG for a comprehensive understanding of human grasp control.SIGNIFICANCE STATEMENT A long-standing assumption of the grasp computations is that grasp representations progress from higher to lower level control in a regular, or canonical, fashion. Here, we combined EEG and multivariate pattern analysis to characterize the temporal dynamics of grasp representations while participants viewed objects and were subsequently cued to execute an unimanual or bimanual grasp. Interrogation of the temporal dynamics revealed that lower level effector representations emerged before intermediate levels of grasp representations, thereby suggesting a partially noncanonical progression from higher to lower and then to intermediate level grasp control.
Keywords:EEG   grasp program   motor   MVPA   precision grasp   visual
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