The vestibulo-ocular reflex (VOR), which stabilizes the eyes in space during head movements, can undergo adaptive modification to maintain retinal stability in response to natural or experimental challenges. A number of models and neural sites have been proposed to account for this adaptation but these do not fully explain how the nervous system can detect and correct errors in both gain and phase of the VOR. This paper presents a general error correction algorithm based on the multiplicative combination of three signals (retinal slip velocity, head position, head velocity) directly relevant to processing of the VOR. The algorithm is highly specific, requiring the combination of particular sets of signals to achieve compensation. It is robust, with essentially perfect compensation observed for all gain (0.25 X-4.0 X) and phase (-180°-+180°) errors tested. Output of the model closely resembles behavioral data from both gain and phase adaptation experiments in a variety of species. Imposing physiological constraints (no negative activation levels or changes in the sign of unit weights) does not alter the effectiveness of the algorithm. These results suggest that the mechanisms implemented in our model correspond to those implemented in the brain of the behaving organism. Predictions concerning the nature of the adaptive process are specific enough to permit experimental verification using electrophysiological techniques. In addition, the model provides a strategy for adaptive control of any first order mechanical system.
ASJC Scopus subject areas
- Computer Science(all)