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Neural Network Connection Characteristics Between Motor Cortex and Spinal Cord During Rat Bipedal Walking.

Created on 18 Sep 2026

Authors

Pengcheng Xi, Xiaodan Lyu, Jiping He, Rongyu Tang, Yiran Lang

Published in

CNS neuroscience & therapeutics. Volume 32. Issue 9. Pages e71160.

Abstract

Bipedal locomotion requires coordinated corticospinal interactions, yet how these networks dynamically reorganize across gait phases remains poorly understood. This study aimed to characterize the phase-dependent restructuring of corticospinal functional networks during rest, stance, and swing in healthy rats.
Single-unit spiking activity was simultaneously recorded from the hindlimb motor cortex and lumbar spinal cord of healthy rats across three behavioral states: Rest, stance, and swing. Granger causality analysis was applied to local field potentials (LFPs) to assess directed functional connectivity. Total Spiking Probability Edges (TSPE) algorithm was used to estimate spike-train functional connectivity. Network topology was characterized by global efficiency and rich-club coefficient.
Granger causality revealed that corticospinal connectivity was most prominent in the beta band (13-35 Hz) during active locomotion. Global efficiency rose from rest (0.33) to stance (0.53) and swing (0.51). TSPE confirmed rich-club topology in all conditions. Spinal hub neurons predominated during locomotion, comprising 81.13% ± 15.5% of rich-club hubs at stance and 60.48% ± 10.21% at swing, while cortical and spinal hubs were balanced at rest. Mean latency decreased from 29.60 ± 20.66 ms at rest to 9.67 ± 1.65 ms during stance.
The central nervous system dynamically restructures corticospinal functional networks across gait phases, with spinal hub neurons assuming a dominant role during active locomotion. This framework provides a mechanistic reference for studying corticospinal disruptions in spinal cord injury, Parkinson's disease, and stroke, and identifies phase-specific beta-band coupling and rich-club hub dynamics as candidate targets for closed-loop neural interfaces in gait rehabilitation.

PMID:
42758103
Bibliographic data and abstract were imported from PubMed on 18 Sep 2026.

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