Motor cortex embeds muscle-like commands in an untangled population response
By Abigail A. Russo, Sean R. Bittner, Sean M. Perkins, Jeffrey S. Seely, B. London, Antonio H. Lara, A. Miri, Najja J. Marshall, Adam Kohn, T. Jessell and 3 more. Neuron, 2018
300 citations recorded by the source corpus.
Summary Primate motor cortex projects to spinal interneurons and motor neurons, suggesting that motor cortex activity may be dominated by muscle-like commands. Extensive observations during reaching lend support to this view, but evidence remains ambiguous and much-debated. To provide a different perspective, we employed a novel behavioral paradigm that affords extensive comparison between time-evolving neural and muscle activity. We found that single motor cortex neurons displayed many muscle-like properties, but the structure of population activity was not muscle-like. Unlike muscle activity, neural activity was structured to avoid ‘tangling’: moments where similar activity patterns led to dissimilar future patterns. Avoidance of tangling was present across tasks and species. Network models revealed a potential reason for this consistent feature: low tangling confers noise robustness. Finally, we were able to predict motor cortex activity from muscle activity alone, by leveraging the hypothesis that muscle-like commands are embedded in additional structure that yields low tangling.
Subfields: Cognitive Neuroscience
View Paper: https://www.semanticscholar.org/paper/bb55661948b42141f011fd52bf602be7553a58a2
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cognitive Neuroscience
- John P. Cunningham
- Mehrdad Jazayeri
- Srdjan Ostojic
- Saurabh Saxena
- Krishna V. Shenoy
- Saurabh Vyas
- Matthew D. Golub
- David Sussillo
Citations in the corpus
- Towards the neural population doctrine. (2019, background): “Gao et al. [30] introduced ANNs as the nonlinear map from latent dynamics to observable neural population activity, a theme which has been elaborated both by including ANNs in the dynamics model, and otherwise [63–66].”
- Interpreting neural computations by examining intrinsic and embedding dimensionality of neural activity (2021, background): “For example, in the primary motor cortex (M1), millions of neurons interact to control just a few muscles involved in a movement [2].”
- Computation Through Neural Population Dynamics (2020, background): “A recent study by Russo et al. (2018) found evidence for the latter.”