Work

Improved stability and interpretability of motor modules computed with an autoencoder

Year: 2026

Type: article

Abstract: This work presents an approach for computing motor modules using an autoencoder and comprehensively compares the stability of motor module structure, functional significance at low module counts, and interpretation of VAF 1 to the current state of the art. The AE-computed module structures were more stable at different module counts. The AE has the potential to improve confidence in module structure and make analysis less dependent on the specific number of modules selected.

Source: Journal of Neurophysiology

DOI: 10.1152/jn.00565.2025

Authors: Siddharth R. Nathella, Bryant A. Seamon, Aaron Young, Lena H. Ting

Institutions: Georgia Institute of Technology, Medical University of South Carolina, Emory University

Language: English

Topic: Motor Control and Adaptation

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: hybrid

Funder: National Science Foundation Graduate Research Fellowship Program

OpenAlex ID: W7212083781

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Cites: 43

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