Sensory interpretation of neural activity patterns

Abstract Interaction of an animal with its environment depends on motor activity and sensory stimuli from the environment. Sensors (e.g. visual, auditory, vestibular) give a transformation of stimuli into neural activity patterns which can be used to construct or update the internal representation. This procedure requires an evaluation of the neural activity in terms of sensory processes. This paper presents a theoretical approach for the sensory interpretation of neural activity based on a Bayesian estimation. The procedure implies a maximum likelihood estimation of the sensory stimulus that could have induced the observed neural activity pattern. The theoretical procedure is tested in a model study stimulating the stochastic activity in a set of auditory nerve fibers. The results of the reconstructed stimuli are in good agreement with the stimuli that induced the neural activity in the auditory nerve fibers.

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