Computer-simulated neural networks: an appropriate model for motor development?

Abstract:

:The idea of an artificial neural network is introduced in a historical context, and the essential aspect of it, viz., the modifiable synapse, is compared to the aspect of plasticity in the natural nervous system. Based on such an artificial neural network, a model is presented for the way in which (the path along which) the connectivity in the spinal cord is modified during the period that a newborn 'learns' to control the movement of his forearm. In this way an automatic calibration of the receptors and the antagonists' recruitment of motor units is represented. The learning process is described in non-mathematical terminology. The model is then shown to be able after learning to reach target angles outside the training set of angles, and to be able to relearn when an important receptor has been made inoperative. In this way it is shown that the model is able to generalize, and that it is robust against at least some damage.

journal_name

Early Hum Dev

journal_title

Early human development

authors

Vos JE,Scheepstra KA

doi

10.1016/0378-3782(93)90045-v

subject

Has Abstract

pub_date

1993-09-01 00:00:00

pages

101-12

issue

1-2

eissn

0378-3782

issn

1872-6232

pii

0378-3782(93)90045-V

journal_volume

34

pub_type

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