title: The critical role of locomotion mechanics in decoding sensory systems.
abstract: How do neural systems process sensory information to control locomotion? The weakly electric knifefish Eigenmannia, an ideal model for studying sensorimotor control, swims to stabilize the sensory image of a sinusoidally moving refuge. Tracking performance is best at stimulus frequencies less than approximately 1 Hz. Kinematic analysis, which is widely used in the study of neural control of movement, predicts commensurately low-pass sensory processing for control. The inclusion of Newtonian mechanics in the analysis of the behavior, however, categorically shifts the prediction: this analysis predicts that sensory processing is high pass. The counterintuitive prediction that a low-pass behavior is controlled by a high-pass neural filter nevertheless matches previously reported but poorly understood high-pass filtering seen in electrosensory afferents and downstream neurons. Furthermore, a model incorporating the high-pass controller matches animal behavior, whereas the model with the low-pass controller does not and is unstable. Because locomotor mechanics are similar in a wide array of animals, these data suggest that such high-pass sensory filters may be a general mechanism used for task-level locomotion control. Furthermore, these data highlight the critical role of mechanical analyses in addition to widely used kinematic analyses in the study of neural control systems.
authors.affiliation: Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA. ncowan@jhu.edu
authors.forename: Noah J
authors.initials: NJ
authors.lastname: Cowan
authors.forename: Eric S
authors.initials: ES
authors.lastname: Fortune
mesh_terms: D000818:Animals; D001696:Biomechanical Phenomena; D004555:Electric Fish; D023702:Gymnotiformes; D008124:Locomotion / Q000502:physiology*; D008959:Models, Neurological; D009475:Neurons, Afferent / Q000502:physiology*; D011984:Sensory Receptor Cells / Q000502:physiology*