@article{6ee7f330ceab4201a85e1e5f40051c15,
title = "Motor Cortex Embeds Muscle-like Commands in an Untangled Population Response",
abstract = "Primate motor cortex projects to spinal interneurons and motoneurons, suggesting that motor cortex activity may be dominated by muscle-like commands. 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 facilitates 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 by leveraging the hypothesis that muscle-like commands are embedded in additional structure that yields low tangling. Using a novel extended movement task, Russo et al. show that neural activity in motor cortex is dominated by non-muscle-like signals. A computational approach reveals that these dominant features are expected and can be predicted given the constraint that neural activity produces muscle commands while obeying a smooth flow-field.",
keywords = "motor control, motor cortex, movement generation, neural dynamics, neural network, pattern generation, rhythmic movement",
author = "Russo, {Abigail A.} and Bittner, {Sean R.} and Perkins, {Sean M.} and Seely, {Jeffrey S.} and London, {Brian M.} and Lara, {Antonio H.} and Andrew Miri and Marshall, {Najja J.} and Adam Kohn and Jessell, {Thomas M.} and Abbott, {Laurence F.} and Cunningham, {John P.} and Churchland, {Mark M.}",
note = "Funding Information: We thank C. Hussar for task development and Y. Pavlova for animal care. Support was provided by the Grossman Center for the Statistics of Mind , Burroughs Wellcome Fund (M.M.C.), Searle Scholars Program (M.M.C.), Sloan Foundation (M.M.C. and J.P.C.), Simons Foundation (M.M.C., J.P.C., L.F.A., T.M.J., and A.K.), McKnight Foundation (M.M.C. and J.P.C.), Helen Hay Whitney Foundation (A.M.), NIH Director{\textquoteright}s New Innovator Award DP2 NS083037 (M.M.C.), NIH NS033245 (T.M.J.), NIH EY016774 (A.K.), NIH CRCNS R01NS100066 (M.M.C. and J.P.C.), NIH 1U19NS104649 (M.M.C., L.F.A., and T.M.J.), NIH R01MH93338 (L.F.A.), NIH F32NS092350 (A.H.L.), NIH 5T32NS064929 (A.A.R.), National Science Foundation (N.J.M., J.S.S., and S.R.B.), Kavli Foundation (M.M.C. and T.M.J.), Klingenstein Foundation (M.M.C.), Project ALS (T.M.J.), Mathers Foundation (T.M.J.), and the Howard Hughes Medical Institute (T.M.J.). Funding Information: We thank C. Hussar for task development and Y. Pavlova for animal care. Support was provided by the Grossman Center for the Statistics of Mind, Burroughs Wellcome Fund (M.M.C.), Searle Scholars Program (M.M.C.), Sloan Foundation (M.M.C. and J.P.C.), Simons Foundation (M.M.C., J.P.C., L.F.A., T.M.J., and A.K.), McKnight Foundation (M.M.C. and J.P.C.), Helen Hay Whitney Foundation (A.M.), NIH Director's New Innovator Award DP2 NS083037 (M.M.C.), NIH NS033245 (T.M.J.), NIH EY016774 (A.K.), NIH CRCNS R01NS100066 (M.M.C. and J.P.C.), NIH 1U19NS104649 (M.M.C., L.F.A., and T.M.J.), NIH R01MH93338 (L.F.A.), NIH F32NS092350 (A.H.L.), NIH 5T32NS064929 (A.A.R.), National Science Foundation (N.J.M., J.S.S., and S.R.B.), Kavli Foundation (M.M.C. and T.M.J.), Klingenstein Foundation (M.M.C.), Project ALS (T.M.J.), Mathers Foundation (T.M.J.), and the Howard Hughes Medical Institute (T.M.J.). Publisher Copyright: {\textcopyright} 2018 Elsevier Inc.",
year = "2018",
month = feb,
day = "21",
doi = "10.1016/j.neuron.2018.01.004",
language = "English (US)",
volume = "97",
pages = "953--966.e8",
journal = "Neuron",
issn = "0896-6273",
publisher = "Cell Press",
number = "4",
}