Mark Churchland, Ph.D.

Mark Churchland, Ph.D.

Research Interest

Research Summary

Professor Churchland’s research focuses on how the brain controls voluntary movement, and focuses on questions such as: how does the brain prepare and generate voluntary movement?  What is the key event that triggers a movement, and in doing so turns thought into action?  Can we understand movement generation in terms of neural dynamics that generate muscle activity and shape responses to sensory feedback? If so, how do neural populations embody the dynamics necessary to perform a vast library of skills? How do upstream ‘cognitive’ processes determine which movement to make and when to make it? At what level of anatomical detail does the brain control movement? Groups of muscles? Subsets of motor neurons? How should we use artificial neural networks to model and understand the computations performed by biological networks? We answer these questions by applying hypothesis-guided analyses to population recordings, across a variety of motor tasks, from multiple brain areas.

The brain is not only a remarkable computational organ – capable of feats that stymie the best computers and robots – it is the seat of who we are and all we think.  Yet despite such romantic notions, modern systems neuroscience has principally asked how the brain transforms inputs into outputs.  This approach has deep historical roots – Descartes, Sherrington – and fabulous modern successes – Mountcastle, Hubel and Wiesel.  Yet the brain is clearly more than a glorified input-output device.  The neural networks within it do not just respond to external stimuli, they also generate their own activity.  A principal goal of my laboratory is to study the neural dynamics responsible for this ability.  In particular, I study how primary motor cortex generates the rich temporal patterns of neural activity that are responsible for moving the body.  My laboratory also focuses on translating basic science knowledge regarding dynamics into better ‘neural prostheses’: brain-machine interfacesthat directly translate neural activity into movement, thus bypassing an injured limb or spinal cord.

Co-director, Grossman Center for the Statistics of Mind

Member, Kavli Institute for Brain Science

Member, Behavior Research

McKnight Scholar Award

Sloan Research Fellow

NIH Director's New Innovator Award Program

Searle Scholars Program

Burroughs Wellcome Fund Career Award in the Basic Biomedical Sciences

Marshall NJ, Glaser JI, Trautmann EM, Amematsro EA, Perkins SM, Shadlen MN, Abbott LF, Cunningham JP, Churchland MM (preprint available) Flexible neural control of motor units.

Schroeder KE*, Perkins SM*, Wang Q, Churchland MM (preprint available) Real-time BMI control of virtual locomotion based on rhythmic motor cortex activity.

Zimnik AJ and Churchland MM (2021) Independent generation of sequence elements by motor cortex. Nature Neuroscience. Feb 22.

Russo AA, Khajeh R, Bittner SR, Cunningham JP, Abbott LF, Churchland MM (2020) Neural trajectories in the supplementary motor area and primary motor cortex exhibit distinct geometries, compatible with different classes of computation. Neuron. Aug 19;107(4):745-758

Ames KC and Churchland MM (2019). Motor cortex signals for each arm are mixed across hemispheres and neurons yet partitioned within the population response. eLife. Oct 9.

Zimnik AJ, Lara AH, Churchland MM (2019) Perturbation of macaque supplementary motor area produces context-independent changes in the probability of movement initiation. J. Neurosci. Apr 24;39(17):3217-3233.

Lara AH, Elsayed GF, Zimnik AJ, Cunningham JP, Churchland MM (2018) Conservation of preparatory neural events in monkey motor cortex regardless of how movement is initiated. eLife Aug 22;7. https:/

Lara AH, Cunningham JP, Churchland MM (2018) Different population dynamics in the supplementary motor area and motor cortex during reaching. Nature Communications Jul 16;9(1):2754

Russo AA, Bittner SR, Perkins SM, Seely JS, London BM, Lara AH, Miri A, Marshall NJ, Kohn A, Jessell TM, Abbott LF, Cunningham JP, Churchland MM (2018) Motor cortex embeds muscle-like commands in an untangled population response. Neuron. 97(4):953-966.

Seely JS, Kaufman MT, Ryu SI, Shenoy KV, Cunningham JP, Churchland MM (2016) Tensor Analysis Reveals Distinct Population Structure that Parallels the Different Computational Roles of Areas M1 and V1. PLoS Comput Biol 12 (11): e1005164.

Elsayed GF, Lara AH, Kaufman MT, Churchland MM, Cunningham JP (2016). Reorganization between preparatory and movement population responses in motor cortex. Nat Commun. Oct 27;7:13239.

Kaufman MT, Seely JS, Sussillo D, Ryu SI, Shenoy KV, Churchland MM (2016) The Largest Response Component in the Motor Cortex Reflects Movement Timing but Not Movement Type. eNeuro. Aug 30;3(4).

  • Motor Systems