Program in Neural Computation, Carnegie Mellon University, Pittsburgh, United States; Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States; Machine Learning Department, Carnegie Mellon University, Pittsburgh, United States
Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States; Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, United States
Peter J Lund
Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States; Machine Learning Department, Carnegie Mellon University, Pittsburgh, United States; Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, United States
Patrick T Sadtler
Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States; Department of Bioengineering, University of Pittsburgh, Pittsburgh, United States
Emily R Oby
Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States; Department of Bioengineering, University of Pittsburgh, Pittsburgh, United States
Kristin M Quick
Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States; Department of Bioengineering, University of Pittsburgh, Pittsburgh, United States
Stephen I Ryu
Department of Neurosurgery, Palo Alto Medical Foundation, California, United States; Department of Electrical Engineering, Stanford University, California, United States
Elizabeth C Tyler-Kabara
Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States; Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, United States; Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, United States
Aaron P Batista
Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States; Department of Bioengineering, University of Pittsburgh, Pittsburgh, United States
Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States; Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, United States; Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, United States
Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, United States; Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, United States
Millions of neurons drive the activity of hundreds of muscles, meaning many different neural population activity patterns could generate the same movement. Studies have suggested that these redundant (i.e. behaviorally equivalent) activity patterns may be beneficial for neural computation. However, it is unknown what constraints may limit the selection of different redundant activity patterns. We leveraged a brain-computer interface, allowing us to define precisely which neural activity patterns were redundant. Rhesus monkeys made cursor movements by modulating neural activity in primary motor cortex. We attempted to predict the observed distribution of redundant neural activity. Principles inspired by work on muscular redundancy did not accurately predict these distributions. Surprisingly, the distributions of redundant neural activity and task-relevant activity were coupled, which enabled accurate predictions of the distributions of redundant activity. This suggests limits on the extent to which redundancy may be exploited by the brain for computation.
