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<p>Walking is fundamental to humans and animals, yet the neural principles underlying movement generation remain unclear. In particular, the relationship between neuronal cell types, networks, and functions has been difficult to establish. Here, we propose that the spatial organization of the spinal cord governs network-driven locomotor rhythms and patterns. An asymmetric “Mexican hat" connectivity - local excitation with longer-range inhibition and a longitudinal skew - accounts for proper motor dynamics, while segregation of cell types in the transversal plane allows descending fibers to find appropriate targets and control network dynamics. We extract these principles via a model of the mouse spinal cord, where synaptic connections are sampled probabilistically from cell-specific projection patterns derived from single-cell RNA sequencing and spatial transcriptomics. Essential aspects of locomotion are induced and controlled without extensive parameter optimization. We additionally predict propagating activity bumps during rhythmic movement. This work reveals universal spatial principles linking cell types, connectivity, and behavior across species.</p>

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Spatial and network principles behind neural generation of locomotion

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月15日

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  • Salif Komi,
  • August Winther,
  • Grace A. Houser,
  • Thomas Topilko,
  • R.J.F. Sørensen,
  • Silas Dalum Larsen,
  • Madelaine C. Adamsson Bonfils,
  • Guanghui Li,
  • Rune W. Berg

摘要

Walking is fundamental to humans and animals, yet the neural principles underlying movement generation remain unclear. In particular, the relationship between neuronal cell types, networks, and functions has been difficult to establish. Here, we propose that the spatial organization of the spinal cord governs network-driven locomotor rhythms and patterns. An asymmetric “Mexican hat" connectivity - local excitation with longer-range inhibition and a longitudinal skew - accounts for proper motor dynamics, while segregation of cell types in the transversal plane allows descending fibers to find appropriate targets and control network dynamics. We extract these principles via a model of the mouse spinal cord, where synaptic connections are sampled probabilistically from cell-specific projection patterns derived from single-cell RNA sequencing and spatial transcriptomics. Essential aspects of locomotion are induced and controlled without extensive parameter optimization. We additionally predict propagating activity bumps during rhythmic movement. This work reveals universal spatial principles linking cell types, connectivity, and behavior across species.