# Continuous input drives motor cortical dynamics during reaching

**Authors:** Hongwei Mao, Brady A. Hasse, Andrew B. Schwartz

PMC · DOI: 10.21203/rs.3.rs-8585660/v1 · Research Square · 2026-02-12

## TL;DR

The study shows that external input, not internal brain activity, drives motor cortex changes during reaching movements.

## Contribution

The paper introduces hybrid neural networks to demonstrate that external input drives motor cortical dynamics during reaching.

## Key findings

- Motor cortical state transitions during reaching are driven by external input rather than internal processing.
- Hybrid neural networks accurately replicate recorded neural activity with episodically modulated external input.
- Extrinsic input modulates pre-threshold integration statistics to cause state transitions in motor cortex.

## Abstract

In a departure from current models of autonomous cortical activity, we examined the effect of continuous input on the dynamic activity of motor cortical neurons throughout a reaching task. We found a series of distinct state transitions in the firing rates of these recorded neural populations. We then asked whether these changes in state were due to internal processing in the motor cortex, as previous models would suggest, or to continuous external inputs. In other words, were signals coming from outside the motor cortex the main drivers of neural activity during reaching behavior? To answer this question, we used hybrid neural networks (HNNs)—consisting of a mixture of artificial connectivity and empirical firing rates—to construct realistic model systems. The HNNs faithfully produced the firing rates of the individual neurons and the state transitions of the populations we recorded, with extrinsic input consisting of episodically modulated neurons. Instead of the reported primacy of intrinsic action, we found that input from extrinsic sources was responsible for these results. Episodic external drive produced consistent changes in the statistics of pre-threshold input integration to cause the state transitions. By using HNNs with empirically constrained connectivity, we have shown that continuous input is a plausible agent for broad system functionality.

## Full-text entities

- **Chemicals:** RNN (-)
- **Species:** Cercopithecidae (monkey, family) [taxon 9527], Macaca mulatta (rhesus macaque, species) [taxon 9544], Mus musculus (house mouse, species) [taxon 10090]
- **Cell lines:** SNN-59C — Homo sapiens (Human), Transformed cell line (CVCL_5I44)

## Full text

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## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12919204/full.md

## References

107 references — full list in the complete paper: https://tomesphere.com/paper/PMC12919204/full.md

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Source: https://tomesphere.com/paper/PMC12919204