Sensory-evoked perturbations of locomotor activity by sparse sensory input: a computational study

Author:

Bui Tuan V.12,Brownstone Robert M.34

Affiliation:

1. Department of Biology, University of Ottawa, Ottawa, Ontario, Canada;

2. Centre for Neural Dynamics, University of Ottawa, Ottawa, Ontario, Canada;

3. Department of Surgery (Neurosurgery), Dalhousie University, Halifax, Nova Scotia, Canada; and

4. Department of Medical Neuroscience, Dalhousie University, Halifax, Nova Scotia, Canada

Abstract

Sensory inputs from muscle, cutaneous, and joint afferents project to the spinal cord, where they are able to affect ongoing locomotor activity. Activation of sensory input can initiate or prolong bouts of locomotor activity depending on the identity of the sensory afferent activated and the timing of the activation within the locomotor cycle. However, the mechanisms by which afferent activity modifies locomotor rhythm and the distribution of sensory afferents to the spinal locomotor networks have not been determined. Considering the many sources of sensory inputs to the spinal cord, determining this distribution would provide insights into how sensory inputs are integrated to adjust ongoing locomotor activity. We asked whether a sparsely distributed set of sensory inputs could modify ongoing locomotor activity. To address this question, several computational models of locomotor central pattern generators (CPGs) that were mechanistically diverse and generated locomotor-like rhythmic activity were developed. We show that sensory inputs restricted to a small subset of the network neurons can perturb locomotor activity in the same manner as seen experimentally. Furthermore, we show that an architecture with sparse sensory input improves the capacity to gate sensory information by selectively modulating sensory channels. These data demonstrate that sensory input to rhythm-generating networks need not be extensively distributed.

Funder

Canadian Institute of Health Research

Publisher

American Physiological Society

Subject

Physiology,General Neuroscience

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