Learning in the Vestibular System: Simulations of Vestibular Compensation Using Recurrent Back-Propagation
Abstract
Vestibular compensation is the process whereby normal functioning is regained following destruction of one member of the pair of peripheral vestibular receptors. Compensation was simulated by lesioning a dynamic neural network model of the vestibulo~ular reflex (VOR) and retraining it using recurrent back-propagation. The model reproduced the pattern of VOR neuron activity experimentally observed in compensated animals, but only if connections heretofore considered uninvolved were allowed to be plastic. Because the model incorporated nonlinear units, it was able to reconcile previously conflicting, linear analyses of experimental results on the dynamic properties of VOR neurons in normal and compensated animals.
Cite
Text
Anastasio. "Learning in the Vestibular System: Simulations of Vestibular Compensation Using Recurrent Back-Propagation." Neural Information Processing Systems, 1991.Markdown
[Anastasio. "Learning in the Vestibular System: Simulations of Vestibular Compensation Using Recurrent Back-Propagation." Neural Information Processing Systems, 1991.](https://mlanthology.org/neurips/1991/anastasio1991neurips-learning/)BibTeX
@inproceedings{anastasio1991neurips-learning,
title = {{Learning in the Vestibular System: Simulations of Vestibular Compensation Using Recurrent Back-Propagation}},
author = {Anastasio, Thomas J.},
booktitle = {Neural Information Processing Systems},
year = {1991},
pages = {603-610},
url = {https://mlanthology.org/neurips/1991/anastasio1991neurips-learning/}
}