Abstract
Neural populations perform computations through their collective activity. Different computations likely require different population-level dynamics. We leverage this assumption to examine neural responses recorded from the supplementary motor area (SMA) and motor cortex. During visually guided reaching, the respective roles of these areas remain unclear; neurons in both areas exhibit preparation-related activity and complex patterns of movement-related activity. To explore population dynamics, we employ a novel “hypothesis-guided” dimensionality reduction approach. This approach reveals commonalities but also stark differences: linear population dynamics, dominated by rotations, are prominent in motor cortex but largely absent in SMA. In motor cortex, the observed dynamics produce patterns resembling muscle activity. Conversely, the non-rotational patterns in SMA co-vary with cues regarding when movement should be initiated. Thus, while SMA and motor cortex display superficially similar single-neuron responses during visually guided reaching, their different population dynamics indicate they are likely performing quite different computations.
Highlights
Neural populations perform computations through their collective activity
We found that supplementary motor area (SMA) and motor cortex differed in nearly every aspect of their dynamics
SMA was less-well described by linear dynamics
Summary
Different computations likely require different population-level dynamics We leverage this assumption to examine neural responses recorded from the supplementary motor area (SMA) and motor cortex. While SMA and motor cortex display superficially similar single-neuron responses during visually guided reaching, their different population dynamics indicate they are likely performing quite different computations. We addressed the relative contributions of SMA and motor cortex by examining the population-level dynamics that presumably subserve network computations This comparison is aided by recent characterizations of motor cortex dynamics. The motor cortex population displays a “central motif” composed of two aspects: a condition-invariant shift in state[5] immediately followed by state trajectories following rotational dynamics[6,12,41] This same motif is naturally displayed by network models trained to generate muscle activity patterns[42]. Given the proposed connections between dynamics and function, the central motif represents a natural point of comparison
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