Work

Spinal interneuron population dynamics underlying flexible pattern generation

Year: 2025

Type: article

Abstract: The mammalian spinal locomotor network is composed of diverse populations of interneurons that collectively orchestrate and execute a range of locomotor behaviors. Despite the identification of many classes of spinal interneurons constituting the locomotor network, it remains unclear how the network's collective activity computes and modifies locomotor output on a step-by-step basis. To investigate this, we analyzed lumbar interneuron population recordings and multi-muscle electromyography from spinalized cats performing air stepping and used artificial intelligence methods to uncover state space trajectories of spinal interneuron population activity on single step cycles and at millisecond timescales. Our analyses of interneuron population trajectories revealed that traversal of specific state space regions held millisecond-timescale correspondence to the timing adjustments of extensor-flexor alternation. Similarly, we found that small variations in the path of state space trajectories were tightly linked to single-step, microvolt-scale adjustments in the magnitude of muscle output. One sentence summary: Features of spinal interneuron state space trajectories capture variations in the timing and magnitude of muscle activations across individual step cycles, with precision on the scales of milliseconds and microvolts respectively.

Source: Nature Communications

DOI: 10.1038/s41467-025-64629-y

Authors: Lahiru N. Wimalasena, Chethan Pandarinath, Nicholas AuYong

Institutions: Georgia Institute of Technology, Emory University, The Wallace H. Coulter Department of Biomedical Engineering

Language: English

Topic: Motor Control and Adaptation

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $6,990