title: Mechanisms of left-right coordination in mammalian locomotor pattern generation circuits: a mathematical modeling view.
abstract: The locomotor gait in limbed animals is defined by the left-right leg coordination and locomotor speed. Coordination between left and right neural activities in the spinal cord controlling left and right legs is provided by commissural interneurons (CINs). Several CIN types have been genetically identified, including the excitatory V3 and excitatory and inhibitory V0 types. Recent studies demonstrated that genetic elimination of all V0 CINs caused switching from a normal left-right alternating activity to a left-right synchronized "hopping" pattern. Furthermore, ablation of only the inhibitory V0 CINs (V0D subtype) resulted in a lack of left-right alternation at low locomotor frequencies and retaining this alternation at high frequencies, whereas selective ablation of the excitatory V0 neurons (V0V subtype) maintained the left-right alternation at low frequencies and switched to a hopping pattern at high frequencies. To analyze these findings, we developed a simplified mathematical model of neural circuits consisting of four pacemaker neurons representing left and right, flexor and extensor rhythm-generating centers interacting via commissural pathways representing V3, V0D, and V0V CINs. The locomotor frequency was controlled by a parameter defining the excitation of neurons and commissural pathways mimicking the effects of N-methyl-D-aspartate on locomotor frequency in isolated rodent spinal cord preparations. The model demonstrated a typical left-right alternating pattern under control conditions, switching to a hopping activity at any frequency after removing both V0 connections, a synchronized pattern at low frequencies with alternation at high frequencies after removing only V0D connections, and an alternating pattern at low frequencies with hopping at high frequencies after removing only V0V connections. We used bifurcation theory and fast-slow decomposition methods to analyze network behavior in the above regimes and transitions between them. The model reproduced, and suggested explanation for, a series of experimental phenomena and generated predictions available for experimental testing.
authors.affiliation: Department of Mathematical Sciences, Indiana University-Purdue University, Indianapolis, Indiana, United States of America.
authors.forename: Yaroslav I
authors.initials: YI
authors.lastname: Molkov
authors.affiliation: Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, Pennsylvania, United States of America.
authors.forename: Bartholomew J
authors.initials: BJ
authors.lastname: Bacak
authors.affiliation: Department of Neuroscience, Karolinska Institute, Stockholm, Sweden.
authors.forename: Adolfo E
authors.initials: AE
authors.lastname: Talpalar
authors.affiliation: Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, Pennsylvania, United States of America.
authors.forename: Ilya A
authors.initials: IA
authors.lastname: Rybak
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D005684:Gait; D007395:Interneurons / Q000502:physiology*; D008124:Locomotion / Q000502:physiology; D051379:Mice; D018345:Mice, Knockout; D015233:Models, Statistical; D009043:Motor Activity / Q000502:physiology; D016202:N-Methylaspartate / Q000737:chemistry; D009474:Neurons / Q000502:physiology; D010363:Pattern Recognition, Automated; D013116:Spinal Cord / Q000473:pathology
chemical_list: D016202:N-Methylaspartate