Mark M. Churchland

Affiliations: 
Stanford University, Palo Alto, CA 
Area:
Motor Cortex
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"Mark Churchland"
Mean distance: 13.6 (cluster 17)
 
SNBCP

Parents

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Stephen G. Lisberger grad student 2001 UCSF
 (Reconstructing visual speed: Behavior, perception, models, and the neural basis of an illusion of increased speed.)
Krishna V. Shenoy post-doc 2001-2011 Stanford

Collaborators

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Brian D. DePasquale collaborator
Matthew T. Kaufman collaborator 2006- Stanford
David Ferster collaborator 2010- Northwestern
BETA: Related publications

Publications

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Zimnik AJ, Lara AH, Churchland MM. (2019) Perturbation of macaque supplementary motor area produces context-independent changes in the probability of movement initiation. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience
Lara AH, Elsayed GF, Zimnik AJ, et al. (2018) Conservation of preparatory neural events in monkey motor cortex regardless of how movement is initiated. Elife. 7
Russo AA, Bittner SR, Perkins SM, et al. (2018) Motor Cortex Embeds Muscle-like Commands in an Untangled Population Response. Neuron
Miri A, Warriner CL, Seely JS, et al. (2017) Behaviorally Selective Engagement of Short-Latency Effector Pathways by Motor Cortex. Neuron
Seely JS, Kaufman MT, Ryu SI, et al. (2016) Tensor Analysis Reveals Distinct Population Structure that Parallels the Different Computational Roles of Areas M1 and V1. Plos Computational Biology. 12: e1005164
Elsayed GF, Lara AH, Kaufman MT, et al. (2016) Reorganization between preparatory and movement population responses in motor cortex. Nature Communications. 7: 13239
Kaufman MT, Seely JS, Sussillo D, et al. (2016) The Largest Response Component in the Motor Cortex Reflects Movement Timing but Not Movement Type. Eneuro. 3
Kao JC, Nuyujukian P, Ryu SI, et al. (2015) Single-trial dynamics of motor cortex and their applications to brain-machine interfaces. Nature Communications. 6: 7759
Kiehn O, Churchland MM. (2015) Editorial overview: Motor circuits and action. Current Opinion in Neurobiology
Sussillo D, Churchland MM, Kaufman MT, et al. (2015) A neural network that finds a naturalistic solution for the production of muscle activity. Nature Neuroscience. 18: 1025-33
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