Using genetic algorithms to find the most effective stimulus for sensory neurons

Genetic algorithms (GAs) can be used to find maxima in large search spaces in a relatively short period of time. We have used GAs in electrophysiological experiments to find the most effective stimulus (MES) for sensory neurons in the cochlear nucleus and inferior colliculus of anaesthetised guinea pigs. The MES is the stimulus that elicits the greatest number of spikes from a unit. We show that GAs provide an effective means of determining the best combination of up to four parameters for sinusoids with amplitude modulation. Using GAs, we have found tuning to modulation frequencies as a function of carrier frequency, sound level and temporal asymmetry. These results demonstrate the suitability of GAs in electrophysical experiments for estimating the position of the most effective stimulus in a specified parameter space.

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