NDLI: A cerebellar neural network model for adaptative control of saccades implemented with Matlab

Content Provider	IEEE Xplore Digital Library
Author	Campos, F.A. Enderle, J.
Copyright Year	2003
Description	Author affiliation: Biomed. Eng., Connecticut Univ., Storrs, CT, USA (Campos, F.A.; Enderle, J.)
Abstract	This paper describes the implementation of a neural network for the adaptative control of the saccadic system. The model shows the cerebellum plays an important role in the adaptive control of the saccadic gain. Using only eye position input through the granule cells, the cerebellum projects this signal to the other cerebellar structures and then to motor neurons responsible for the saccade. The generation of an adjustment signal occurs in the inferior olive as a result of the error sensory signal created by the open loop saccade system from propioceptive position inputs from the last eye movement generated by the network until the movement towards the target is completed. In addition, a memory component has been defined in the error system to achieve the adaptation. This neural network involves only the horizontal saccade component modeled with Matrix Laboratory language (MATLAB), in conjunction with the Simulink tool.
Sponsorship	Schering Plough Becton Dickinson Boston Scientific Reva
Starting Page	5
Ending Page	10
File Size	198009
Page Count	6
File Format	PDF
ISBN	0780377672
DOI	10.1109/NEBC.2003.1215966
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-03-22
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Mathematical model MATLAB Brain modeling Neurons Signal generators Biomedical engineering Control systems Adaptive control Attenuation
Content Type	Text
Resource Type	Article

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