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Book ChapterDOI

Computational model of a central pattern generator

TLDR
The results suggest that the currently identified ensemble of cells is inadequate to produce rhythmic neural activity and that several key elements of the CPG remain to be identified.
Abstract
The buccal ganglia of Aplysia contain a central pattern generator (CPG) that mediates rhythmic movements of the foregut during feeding. This CPG is a multifunctional circuit and generates at least two types of buccal motor patterns (BMPs), one that mediates ingestion (iBMP) and another that mediates rejection (rBMP). The present study used a computational approach to examine the ways in which an ensemble of identified cells and synaptic connections function as a CPG. Hodgkin-Huxley-type models were developed that mimicked the biophysical properties of these cells and synaptic connections. The results suggest that the currently identified ensemble of cells is inadequate to produce rhythmic neural activity and that several key elements of the CPG remain to be identified.

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Citations
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Journal ArticleDOI

Adaptive Control Strategies for Interlimb Coordination in Legged Robots: A Review

TL;DR: This review introduces adaptive interlimb coordination for legged robots induced by various factors (locomotion speed, environmental situation, body properties, and task) and shows characteristic properties of adaptive inter Limb coordination, such as gait hysteresis and different time-scale adaptations.
Journal ArticleDOI

The significance of dynamical architecture for adaptive responses to mechanical loads during rhythmic behavior

TL;DR: A nominal model of swallowing in Aplysia californica is described and it is shown that the underlying stable heteroclinic channel architecture exhibits dramatic slowing of activity when sensory and endogenous input is reduced, and that similar slowing with removal of proprioception is seen in vitro.
Journal ArticleDOI

Inferring neuronal network functional connectivity with directed information.

TL;DR: The inference method developed in this study is data driven and validated by conductance-based model circuits, can distinguish excitatory and inhibitory connections, is robust against synaptic plasticity, and is capable of detecting network structures that mediate motor patterns.
Book ChapterDOI

Analyzing a Discrete Model of Aplysia Central Pattern Generator

TL;DR: Using abstract discrete models of the individual neurons helps in understanding the buccal motor programs generated by the network in terms of the network connection topology and eliminates the need for detailed knowledge of the unknown parameters in the continuous model of Baxter et.
Journal ArticleDOI

Computational model of the distributed representation of operant reward memory: combinatoric engagement of intrinsic and synaptic plasticity mechanisms.

TL;DR: Results indicate that the memory for operant reward learning emerged from the combinatoric engagement of multiple sites of plasticity, and that plasticity loci exhibited mutual dependence and synergism.
References
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Journal ArticleDOI

Principles of rhythmic motor pattern generation

TL;DR: Cellular, circuit, and computational analyses of the mechanisms underlying the generation of rhythmic movements in both invertebrate and vertebrate nervous systems are discussed.
Book

Methods in Neuronal Modeling: From Ions to Networks

Christof Koch, +1 more
TL;DR: This book serves as a handbook of computational methods and techniques for modeling the functional properties of single and groups of nerve cells.
Journal ArticleDOI

Neurons, networks, and motor behavior

TL;DR: The next revolution in the field is likely to come from a paradigm shift regarding such control of motor circuits, similar to the shift that has already occurred in the authors' understanding of the pattern-generating circuits themselves.
Journal ArticleDOI

Invertebrate central pattern generation moves along.

TL;DR: Recent work on invertebrate CPGs is summarized which has provided new insights into how rhythmic motor patterns are produced and how they are controlled by higher-order command and modulatory interneurons.
Journal ArticleDOI

Operant Reward Learning in Aplysia: Neuronal Correlates and Mechanisms

TL;DR: Biophysical changes that accompanied the memory were found in an identified neuron (cell B51) that is considered critical for the expression of behavior that was rewarded and allowed for the detailed analysis of the cellular and molecular processes underlying operant conditioning.
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