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The interaction of positive and negative sensory feedback loops in dynamic regulation of a motor pattern
Journal article   Peer reviewed

The interaction of positive and negative sensory feedback loops in dynamic regulation of a motor pattern

Jessica Ausborn, Harald Wolf and Wolfgang Stein
Journal of computational neuroscience, v 27(2), pp 245-257
01 Oct 2009
PMID: 19291377

Abstract

Afferent Pathways - physiology Algorithms Animals Central Nervous System - physiology Computer Simulation Efferent Pathways - physiology Feedback - physiology Flight, Animal - physiology Ganglia, Invertebrate - physiology Grasshoppers - cytology Grasshoppers - physiology Interneurons - physiology Mechanoreceptors - physiology Motor Neurons - physiology Movement - physiology Muscle, Striated - innervation Muscle, Striated - physiology Nerve Net - physiology Proprioception - physiology Sensory Receptor Cells - physiology Wings, Animal - innervation Wings, Animal - physiology
In many rhythmic behaviors, phasic sensory feedback modifies the motor pattern. This modification is assumed to depend on feedback sign (positive vs. negative). While on a phenomenological level feedback sign is well defined, many sensory pathways also process antagonistic, and possibly contradictory, sensory information. We here model the locust flight pattern generator and proprioceptive feedback provided by the tegula wing receptor to test the functional significance of sensory pathways processing antagonistic information. We demonstrate that the tegula provides delayed positive feedback via interneuron 301, while all other pathways provide negative feedback. Contradictory to previous assumptions, the increase of wing beat frequency when the tegula is activated during flight is due to the positive feedback. By use of an abstract model we reveal that the regulation of motor pattern frequency by sensory feedback critically depends on the interaction of positive and negative feedback, and thus on the weighting of antagonistic pathways.

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Web of Science research areas
Mathematical & Computational Biology
Neurosciences
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