Neural Networks for Real-Time Sensory Data Processing and Sensorimotor Control.

Abstract

In our experimental work we have completed several studies and have begun at least one more long term project. These include observations in both motion analysis and electrophysiological techniques. Perhaps the most significant accomplishment of this period is the completion of motion analysis measurements on the basic movements that make up the escape turns. This work has now been accepted for publication in a paper (Nye and Ritzmann, 1992) that will serve as a very useful baseline for all future experimentation on the escape system. In this paper we report that the escape system utilizes at least three different types of turning movements, depending upon the front-back location of the wind source. The paper also documents observations that suggest that several of the joint movements incorporate proprioceptive information into their movements. Beyond this basic study, we also completed the study on leg lesion. Unfortunately, this study resulted in ambiguous findings. Although animals tend to regain some facility in turning when observed under free ranging conditions, we were not able to reproduce these findings with any confidence in the tethered preparation.

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Document Details

Document Type
Technical Report
Publication Date
Jun 09, 1992
Accession Number
ADA251567

Entities

People

  • Randall D. Beer

Organizations

  • Case Western Reserve University

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computations
  • Data Processing
  • Escape Systems
  • Genetic Algorithms
  • Locomotion
  • Models
  • Neural Networks
  • Neurons
  • Observation
  • Recurrent Neural Networks
  • Robotics
  • Robots
  • Simulations
  • Simulators
  • Wind
  • Wind Direction

Readers

  • Clinical Trial Research.
  • Robotics and Automation.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference