Spatiotemporal structure of neural population dynamics in the motor system

  • Awardees
  • John P. Cunningham, Ph.D. Columbia University
  • Larry Abbott, Ph.D. Columbia University
  • Mark M. Churchland, Ph.D. Columbia University
  • Liam Paninski, Ph.D. Columbia University

Consider the simple act of reaching for a cup of coffee. The brain must decide to pick up the coffee, prepare for movement, and then execute the movement. Each stage of the process requires that neurons in the brain exhibit different activity. Experiments have revealed that a part of the brain involved in movement, the motor cortex, is active both during the planning phase of movement and during the execution of the movement itself. But how can the same brain area—the same set of neurons—be responsible for two distinct phases? To answer this question, we must understand the patterns of activity exhibited by a set of neurons across time, a phenomenon termed “internal dynamics.” When we switch from planning to executing a movement, the internal dynamics of the same set of neurons change. This allows for the same neural network to control two different types of processes. Working in the motor cortex, we will use recording technology that allows us to observe the activity of many neurons simultaneously. This way, we hope to address how the motor cortex changes its internal dynamics from the planning to the movement phase. Our recent results have allowed us to characterize mathematically such changes in internal dynamics. This mathematical characterization allows us to identify and study key transitions between brain states. Our research seeks to produce a better understanding of how the brain produces movement and how it transitions from one state to another more generally.


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