Neural control of behavior in a neuromechanical salamander simulation

Abstract

With arguably the simplest vertebrate nervous system, the salamander is a model organism used to study basic issues in vertebrate neuroscience. We are using a neuromechanical simulation program to investigate behavioral consequences of the amphibian's neural organization. The system's Central Pattern Generators (CPGs)produce biologically plausible spinal waveforms, thus producing characteristic walking and swimming movement. The system has been used to investigate prey approach behavior with the realistic mechanical simulation and a simplified visual system model. We are using this model to investigate the relative contributions of sensory feedback and direct CPG control on head stabilization during locomotion. We will use computer vision techniques to determine, from video obtained under controlled conditions, precise kinematic parameters of the locomotion gaits, particularly head movement parameters. These kinematic parameters will constrain the simulation. From a current study, it appears likely that the pattern generators play the predominant role in head stabilization. We will describe an approach to meeting the kinematic constraints using the CPG model. A somewhat related effort studies a model of the amphibian medial pallium (MP) -- a likely homology to the hippocampal formation. Recent work on the salamander has produced neuroanatomical results that will constrain an older model of the toad MP that explained intricate patterns of habituation and ishabituation to prey-like stimuli. Investigators have hypothesized that hippocampus homologies are involved in evolutionarily conserved patterns of vertebrate behavior – e.g., spatial memory involved in navigation and perhaps other forms of territorial behavior. This computational investigation analyzes such a hypothesis in the context of a model which has demonstrated biological plausibility at other levels of analysis. The fusion of these disparate investigations will be a unified, modular, biologically plausible model of an autonomous agent successfully interacting with a complex environment in order to satisfy biological drives – a computational neuroethological model. Questions about the interfaces of these systems will be discussed.