Committee on Computational Neuroscience, University of Chicago, Chicago, United States
Matthew Kaufman
Committee on Computational Neuroscience, University of Chicago, Chicago, United States; Department of Organismal Biology and Anatomy, University of Chicago, Chicago, United States; Grossman Institute for Neuroscience, Quantitative Biology and Human Behavior, University of Chicago, Chicago, United States
Nicholas G Hatsopoulos
Committee on Computational Neuroscience, University of Chicago, Chicago, United States; Department of Organismal Biology and Anatomy, University of Chicago, Chicago, United States; Grossman Institute for Neuroscience, Quantitative Biology and Human Behavior, University of Chicago, Chicago, United States
Committee on Computational Neuroscience, University of Chicago, Chicago, United States; Department of Organismal Biology and Anatomy, University of Chicago, Chicago, United States; Grossman Institute for Neuroscience, Quantitative Biology and Human Behavior, University of Chicago, Chicago, United States
Low-dimensional linear dynamics are observed in neuronal population activity in primary motor cortex (M1) when monkeys make reaching movements. This population-level behavior is consistent with a role for M1 as an autonomous pattern generator that drives muscles to give rise to movement. In the present study, we examine whether similar dynamics are also observed during grasping movements, which involve fundamentally different patterns of kinematics and muscle activations. Using a variety of analytical approaches, we show that M1 does not exhibit such dynamics during grasping movements. Rather, the grasp-related neuronal dynamics in M1 are similar to their counterparts in somatosensory cortex, whose activity is driven primarily by afferent inputs rather than by intrinsic dynamics. The basic structure of the neuronal activity underlying hand control is thus fundamentally different from that underlying arm control.
