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Front Neurosci. 2016 Feb 23;10:42. doi: 10.3389/fnins.2016.00042. eCollection 2016.

Speed-Dependent Modulation of the Locomotor Behavior in Adult Mice Reveals Attractor and Transitional Gaits.

Frontiers in neuroscience

Maxime Lemieux, Nicolas Josset, Marie Roussel, Sébastien Couraud, Frédéric Bretzner

Affiliations

  1. Centre de Recherche du CHU de Québec, CHUL-Neurosciences Québec, QC, Canada.
  2. Centre de Recherche du CHU de Québec, CHUL-NeurosciencesQuébec, QC, Canada; Department of Psychiatry and Neurosciences, Faculty of Medicine, Université LavalQuébec, QC, Canada.

PMID: 26941592 PMCID: PMC4763020 DOI: 10.3389/fnins.2016.00042

Abstract

Locomotion results from an interplay between biomechanical constraints of the muscles attached to the skeleton and the neuronal circuits controlling and coordinating muscle activities. Quadrupeds exhibit a wide range of locomotor gaits. Given our advances in the genetic identification of spinal and supraspinal circuits important to locomotion in the mouse, it is now important to get a better understanding of the full repertoire of gaits in the freely walking mouse. To assess this range, young adult C57BL/6J mice were trained to walk and run on a treadmill at different locomotor speeds. Instead of using the classical paradigm defining gaits according to their footfall pattern, we combined the inter-limb coupling and the duty cycle of the stance phase, thus identifying several types of gaits: lateral walk, trot, out-of-phase walk, rotary gallop, transverse gallop, hop, half-bound, and full-bound. Out-of-phase walk, trot, and full-bound were robust and appeared to function as attractor gaits (i.e., a state to which the network flows and stabilizes) at low, intermediate, and high speeds respectively. In contrast, lateral walk, hop, transverse gallop, rotary gallop, and half-bound were more transient and therefore considered transitional gaits (i.e., a labile state of the network from which it flows to the attractor state). Surprisingly, lateral walk was less frequently observed. Using graph analysis, we demonstrated that transitions between gaits were predictable, not random. In summary, the wild-type mouse exhibits a wider repertoire of locomotor gaits than expected. Future locomotor studies should benefit from this paradigm in assessing transgenic mice or wild-type mice with neurotraumatic injury or neurodegenerative disease affecting gait.

Keywords: graph analysis; kinematic; locomotor gaits; mouse; speed; steady-state

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