Abstract
An automated system to optimize auditory stimuli based on neuronal response feedback has been developed. The ALOPEX (algorithm of pattern extraction) algorithm uses responses recorded from auditory neurons as feedback to optimize sound stimuli. This computer based system works in real time to iteratively find the optimal combination of tones for the neurons being studied. Fuzzy logic is used to classify extracellular neuronal responses for investigation of connectivity. Normalized tones used to excite the auditory neurons are produced by a Yamaha (YMF262) FM-chip on board a Sound Blaster 16 card. The response and stimuli are captured by a Dataq (DI-300F) high speed analog and digital I/O board. Results from the frog (Rana Pipien) auditory system showed that the setup is able to converge within 100 iterations. The system dynamics and reliability were also tested with the response computed as a parabolic function of frequency. A companion demonstration that uses the parabolic equation to simulate response has been developed and is presented as a demo.
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