IC8 – Computational principles of gaze-stabilization during locomotion

Lecturer: Hans Straka
Fields: Experimental Neurobiology

Content

Continuous accurate perception of the visual world is a behavioral requirement during self-generated motion. All animals are confronted with the disruptive effects of locomotor activity on the ability to maintain stable images on the retina. This is due to the fact that self-motion is accompanied by head movements that cause retinal image displacement with a resultant degradation of visual information processing. To stabilize gaze and to retain visual acuity during locomotion, retinal image drift is offset by counteractive eye and/or head-adjustments. These offsetting motor reactions are classically attributed to the concerted action of visuo-vestibular and proprioceptive reflexes. However, stereotyped, rhythmic locomotion has predictable consequences for image perturbations. This, in principle, allows employing efference copies of propulsive motor commands to directly initiate spatio-temporally adequate eye movements. Such eye-adjusting motor commands have been demonstrated in the amphibian Xenopus laevis. These signals are feed-forward replica of the spinal central pattern generator output that produces the actual propulsive body movements. Spinal locomotor efference copies directly target horizontal extraocular motoneurons, consistent with the plane and direction of swimming-related head rotations. The signals actively attenuate vestibulo-ocular reflexes, emphasizing the predominant role for intrinsic efference copies for gaze-stabilization during self-motion. The suppressive influence of motor efference copies on vestibular signals occurs at the mechanosensory periphery. The resultant gain reduction in sensory signal encoding likely prevents overstimulation by adjusting the system to increased stimulus magnitudes during locomotion. This leaves efference copy-evoked gaze-stabilizing eye movements as dominant computational mechanism. Further suggestive evidence for a ubiquitous role of such signals in this context has been provided for quadrupedal and bipedal locomotion in terrestrial vertebrates including humans.

Literature

  • Lambert F.M., Combes D., Simmers J. and Straka H. (2012) Gaze stabilization by efference copy signaling without sensory feedback during vertebrate locomotion. Curr. Biol. 22: 1649-1658.
  • Chagnaud B.P., Simmers J. and Straka H. (2012) Predictability of visual perturbation during locomotion: implications for corrective efference copy signaling. Biol. Cybern. 106: 669-679.
  • von Uckermann G., Le Ray D., Combes D., Straka H. and Simmers J. (2013) Spinal efference copy signaling and gaze stabilization during locomotion in juvenile Xenopus frogs. J. Neurosci. 33: 4253-4264.
  • Chagnaud B.P., Banchi R., Simmers J. and Straka H. (2015) Spinal corollary discharge modulates motion sensing during vertebrate locomotion. Nat. Comm. 6: 7982 doi: 10.1038/ncomms8982.
  • von Uckermann G., Lambert F.M., Combes D., Straka H. and Simmers J. (2016) Adaptive plasticity of retinal image stabilization during locomotion in developing Xenopus. J. Exp. Biol. 219: 1110-1121.
  • Straka H., Simmers J. and Chagnaud B.P. (2018) A new perspective on predictive motor signaling. Curr. Biol. 28: R232-R243.

Lecturer

Hans Straka

Hans Straka is Professor for Systemic Neurosciences at the Faculty of Biology at the LMU Munich. He studied Biology at the LMU Munich and received his PhD from the same University. Starting with his postdoc, he got interested in the functional organization of the vestibular system including its variable morphology as well as the ontogeny and phylogeny of this sensory system. Using a variety of animal models, he has studied over the past years in the US, in France and currently in Munich the respective contributions of cellular and neural networks to the sensory transformation of head/body motion-related signals into appropriate extraocular motor commands. Interactions with computational neuroscientists have resulted in a number of conceptual novelties on gaze control and computational models that bridge the gap between empiric experiments and theoretical background.

Affiliation: Depatment Biology II, Ludwig-Maximilians-Universiy Munich
Homepage: https://neuro.bio.lmu.de/members/systems_neuro_straka/straka_h/index.html