Abstract:Animals can quickly learn the timing of events with fixed intervals and their rate of acquisition does not depend on the length of the interval. In contrast, recurrent neural networks that use gradient based learning have difficulty predicting the timing of events that depend on stimulus that occurred long ago. We present the latent time-adaptive drift-diffusion model (LTDDM), an extension to the time-adaptive driftdiffusion model (TDDM), a model for animal learning of timing that exhibits behavioural properti… Show more
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