Abstract

Animals in their natural environments display a remarkably diverse variety of walking patterns. Although some of this diversity is generated by alterations in feedback from the moving limbs, animals can modify their walking in many ways that cannot be directly attributed to this sensory feedback. For example, animals and humans can learn to associate a particular environment with disturbances that were experienced there earlier, and alter their stepping accordingly even after the disturbance has ceased. Another relevant example is that walking animals are aware of the locations of obstacles around them, and use this awareness to alter their stepping patterns even when there is no visual information available about the location of the obstacles relative to the body. In this article, we discuss recent work from our laboratory that addresses these two topics. First, we report that perturbing walking cats in a consistent manner evokes long-lasting changes to the walking pattern that are expressed only in the context in which walking was disturbed. Secondly, we show that cats that have stepped over an obstacle remember the location of that obstacle relative to the body during long delays, and can use that memory to guide stepping. The general theme of this research is that sensory inputs that signal context-the visual and auditory environment that surrounds an animal-play an important role in shaping the basic pattern of locomotion.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.