Coordinated spinal locomotor network dynamics emerge from cell-type-specific connectivity patterns

Even without detailed instruction from the brain, spinal locomotor circuitry generates coordinated behavior characterized by left–right alternation, segment-to-segment propagation, and variable-speed control. While existing models have emphasized the contributions of cellular- and network-level properties, the core mechanisms underlying rhythmogenesis remain incompletely understood. Further, neither family of models has fully accounted for recent experimental results in zebrafish and other organisms pointing to the importance of cell-type-specific intersegmental connectivity patterns and recruitment of speed-selective subpopulations of interneurons. Informed by these experimental findings and others, we developed a hierarchy of increasingly detailed models of the locomotor network. We find that coordinated locomotion emerges in an inhibition-dominated network in which connectivity is determined by intersegmental phase relationships among interneurons and variable-speed control is implemented by recruitment of speed-selective subpopulations. Further, while structured excitatory connections are not necessary for rhythmogenesis, they are useful for increasing peak locomotion frequency, albeit at the cost of smooth transitions at intermediate frequencies, suggesting a basic computational trade-off between speed and control. Together, this family of models shows that network-level interactions are sufficient to generate coordinated, variable-speed locomotion, providing new interpretations of intersegmental excitatory and inhibitory connectivity, as well as the basic, recruitment-based mechanism of speed control.

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Publication Details

Journal
eLife
Published
2025-12-31
DOI
https://doi.org/10.7554/elife.106658.3
Primary Topic
Zebrafish Biomedical Research Applications
Type
article
Field-Weighted Citation Impact
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article

Coordinated spinal locomotor network dynamics emerge from cell-type-specific connectivity patterns

James Murray, David L. McLean, Benjamin K Lemberger, F David Wandler
eLife
Zebrafish Biomedical Research Applications
article

Coordinated spinal locomotor network dynamics emerge from cell-type-specific connectivity patterns

James Murray, David L. McLean, Benjamin K Lemberger, F David Wandler
article en

Abstract

Even without detailed instruction from the brain, spinal locomotor circuitry generates coordinated behavior characterized by left–right alternation, segment-to-segment propagation, and variable-speed control. While existing models have emphasized the contributions of cellular- and network-level properties, the core mechanisms underlying rhythmogenesis remain incompletely understood. Further, neither family of models has fully accounted for recent experimental results in zebrafish and other organisms pointing to the importance of cell-type-specific intersegmental connectivity patterns and recruitment of speed-selective subpopulations of interneurons. Informed by these experimental findings and others, we developed a hierarchy of increasingly detailed models of the locomotor network. We find that coordinated locomotion emerges in an inhibition-dominated network in which connectivity is determined by intersegmental phase relationships among interneurons and variable-speed control is implemented by recruitment of speed-selective subpopulations. Further, while structured excitatory connections are not necessary for rhythmogenesis, they are useful for increasing peak locomotion frequency, albeit at the cost of smooth transitions at intermediate frequencies, suggesting a basic computational trade-off between speed and control. Together, this family of models shows that network-level interactions are sufficient to generate coordinated, variable-speed locomotion, providing new interpretations of intersegmental excitatory and inhibitory connectivity, as well as the basic, recruitment-based mechanism of speed control.

eLifeVol. 14
University of Oregon (US), Discovery Centre (CA)
Openalex Percentile: Top 32%
Zebrafish Biomedical Research Applications
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