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The Journal of Neuroscience, October 3, 2007, 27(40):10742-10750; doi:10.1523/JNEUROSCI.0959-07.2007

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Behavioral/Systems/Cognitive
Single-Neuron Stability during Repeated Reaching in Macaque Premotor Cortex

Cynthia A. Chestek,^1 * Aaron P. Batista,^1,2 * Gopal Santhanam,¹ Byron M. Yu,¹ Afsheen Afshar,^1,3 John P. Cunningham,¹ Vikash Gilja,⁴ Stephen I. Ryu,^1,5 Mark M. Churchland,^1,2 and Krishna V. Shenoy^1,2

¹Department of Electrical Engineering, ²Neurosciences Program, ³Medical Scientists Training Program, ⁴Department of Computer Science, and ⁵Department of Neurosurgery, Stanford University, Stanford, California 94305

Correspondence should be addressed to Krishna Shenoy, 319 CISX, 330 Serra Mall, Paul G. Allen Center for Integrated Systems, Department of Electrical Engineering and Neurosciences Program, Stanford University, Stanford, CA 94305-4075. Email: shenoy{at}stanford.edu

Some movements that animals and humans make are highly stereotyped, repeated with little variation. The patterns of neural activity associated with repeats of a movement may be highly similar, or the same movement may arise from different patterns of neural activity, if the brain exploits redundancies in the neural projections to muscles. We examined the stability of the relationship between neural activity and behavior. We asked whether the variability in neural activity that we observed during repeated reaching was consistent with a noisy but stable relationship, or with a changing relationship, between neural activity and behavior. Monkeys performed highly similar reaches under tight behavioral control, while many neurons in the dorsal aspect of premotor cortex and the primary motor cortex were simultaneously monitored for several hours. Neural activity was predominantly stable over time in all measured properties: firing rate, directional tuning, and contribution to a decoding model that predicted kinematics from neural activity. The small changes in neural activity that we did observe could be accounted for primarily by subtle changes in behavior. We conclude that the relationship between neural activity and practiced behavior is reasonably stable, at least on timescales of minutes up to 48 h. This finding has significant implications for the design of neural prosthetic systems because it suggests that device recalibration need not be overly frequent, It also has implications for studies of neural plasticity because a stable baseline permits identification of nonstationary shifts.

Key words: premotor; arm; macaque; multielectrode array; decoding; brain machine interface

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Received March 2, 2007; revised June 13, 2007; accepted July 5, 2007.

Correspondence should be addressed to Krishna Shenoy, 319 CISX, 330 Serra Mall, Paul G. Allen Center for Integrated Systems, Department of Electrical Engineering and Neurosciences Program, Stanford University, Stanford, CA 94305-4075. Email: shenoy{at}stanford.edu

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