Pseudo-linear summation explains neural geometry of multi-finger movements in human premotor cortex

Nishal P. Shah (), Donald Avansino, Foram Kamdar, Claire Nicolas, Anastasia Kapitonava, Carlos Vargas-Irwin, Leigh R. Hochberg, Chethan Pandarinath, Krishna V. Shenoy, Francis R. Willett and Jaimie M. Henderson
Additional contact information
Nishal P. Shah: Stanford University
Donald Avansino: Stanford University
Foram Kamdar: Stanford University
Claire Nicolas: Harvard Medical School
Anastasia Kapitonava: Harvard Medical School
Carlos Vargas-Irwin: Providence VA Medical Center
Leigh R. Hochberg: Harvard Medical School
Chethan Pandarinath: Emory University and Georgia Institute of Technology
Krishna V. Shenoy: Howard Hughes Medical Institute at Stanford University
Francis R. Willett: Stanford University
Jaimie M. Henderson: Stanford University

Nature Communications, 2025, vol. 16, issue 1, 1-15

Abstract: Abstract How does the motor cortex combine simple movements (such as single finger flexion/extension) into complex movements (such as hand gestures, or playing the piano)? To address this question, motor cortical activity was recorded using intracortical multi-electrode arrays in two male people with tetraplegia as they attempted single, pairwise and higher-order finger movements. Neural activity for simultaneous movements was largely aligned with linear summation of corresponding single finger movement activities, with two violations. First, the neural activity exhibited normalization, preventing a large magnitude with an increasing number of moving fingers. Second, the neural tuning direction of weakly represented fingers changed significantly as a result of the movement of more strongly represented fingers. These deviations from linearity resulted in non-linear methods outperforming linear methods for neural decoding. Simultaneous finger movements are thus represented by the combination of individual finger movements by pseudo-linear summation.

Date: 2025
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DOI: 10.1038/s41467-025-59039-z

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