An overview of adaptive model theory: solving the problems of redundancy, resources, and nonlinear interactions in human movement control.

Abstract:

:Adaptive model theory (AMT) is a computational theory that addresses the difficult control problem posed by the musculoskeletal system in interaction with the environment. It proposes that the nervous system creates motor maps and task-dependent synergies to solve the problems of redundancy and limited central resources. These lead to the adaptive formation of task-dependent feedback/feedforward controllers able to generate stable, noninteractive control and render nonlinear interactions unobservable in sensory-motor relationships. AMT offers a unified account of how the nervous system might achieve these solutions by forming internal models. This is presented as the design of a simulator consisting of neural adaptive filters based on cerebellar circuitry. It incorporates a new network module that adaptively models (in real time) nonlinear relationships between inputs with changing and uncertain spectral and amplitude probability density functions as is the case for sensory and motor signals.

journal_name

J Neural Eng

authors

Neilson PD,Neilson MD

doi

10.1088/1741-2560/2/3/S10

subject

Has Abstract

pub_date

2005-09-01 00:00:00

pages

S279-312

issue

3

eissn

1741-2560

issn

1741-2552

pii

S1741-2560(05)94059-7

journal_volume

2

pub_type

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