DocumentCode :
2696667
Title :
A neural network that learns to integrate oculomotor signals
Author :
Arnold, Donald B. ; Robinson, David A.
fYear :
1990
fDate :
17-21 June 1990
Firstpage :
693
Abstract :
Neurophysiological studies reveal a neural network in the brain stem that converts a velocity to a position signal to mediate the vestibulo reflex. This integrator is calibrated at birth and then maintained through disease and trauma. Therefore, it is a network that learns. It was modeled by a group of interconnected neurons that received a continuous time function at its input and generated a continuous output. The output was monitored to create an error. The network learned on a trial-and-error, synapse-by-synapse algorithm. The resulting network integrated by forming multiple positive feedback loops. Cell behaviour was distributed and resembled that seen with microelectrodes in the real integrator
Keywords :
eye; muscle; neural nets; neurophysiology; physiological models; brain stem; cell behaviour; continuous time function; disease; interconnected neurons; microelectrodes; multiple positive feedback loops; neural network; neurophysiological studies; position signal; synapse-by-synapse algorithm; trauma; vestibulo reflex;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1990., 1990 IJCNN International Joint Conference on
Conference_Location :
San Diego, CA, USA
Type :
conf
DOI :
10.1109/IJCNN.1990.137781
Filename :
5726739
Link To Document :
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