Neural Trajectories in the Supplementary Motor Area and Motor Cortex Exhibit Distinct Geometries, Compatible with Different Classes of Computation

被引:86
作者
Russo, Abigail A. [1 ,2 ]
Khajeh, Ramin [1 ,2 ,5 ]
Bittner, Sean R. [1 ,2 ,5 ]
Perkins, Sean M. [2 ,3 ]
Cunningham, John P. [2 ,4 ,5 ,6 ]
Abbott, L. F. [1 ,2 ,4 ,5 ,7 ,8 ]
Churchland, Mark M. [1 ,2 ,4 ,8 ]
机构
[1] Columbia Univ, Dept Neurosci, New York, NY 10027 USA
[2] Columbia Univ, Zuckerman Mind Brain Behav Inst, New York, NY 10027 USA
[3] Columbia Univ, Dept Biomed Engn, New York, NY 10027 USA
[4] Columbia Univ, Grossman Ctr Stat Mind, New York, NY 10027 USA
[5] Columbia Univ, Ctr Theoret Neurosci, New York, NY 10027 USA
[6] Columbia Univ, Dept Stat, New York, NY 10027 USA
[7] Columbia Univ, Dept Physiol & Cellular Biophys, Med Ctr, New York, NY 10032 USA
[8] Columbia Univ, Kavli Inst Brain Sci, New York, NY 10027 USA
关键词
NEURONAL-ACTIVITY; TEMPORAL ORGANIZATION; VOLUNTARY MOVEMENTS; CEREBRAL-CORTEX; FRONTAL-CORTEX; SHORT-TERM; DYNAMICS; REPRESENTATIONS; GENERATION; PREMOTOR;
D O I
10.1016/j.neuron.2020.05.020
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
The supplementary motor area (SMA) is believed to contribute to higher order aspects of motor control. We considered a key higher order role: tracking progress throughout an action. We propose that doing so requires population activity to display low "trajectory divergence": situations with different future motor outputs should be distinct, even when present motor output is identical. We examined neural activity in SMA and primary motor cortex (M1) as monkeys cycled various distances through a virtual environment. SMA exhibited multiple response features that were absent in M1. At the single-neuron level, these included ramping firing rates and cycle-specific responses. At the population level, they included a helical population-trajectory geometry with shifts in the occupied subspace as movement unfolded. These diverse features all served to reduce trajectory divergence, which was much lower in SMA versus M1. Analogous population-trajectory geometry, also with low divergence, naturally arose in networks trained to internally guide multi-cycle movement.
引用
收藏
页码:745 / +
页数:20
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