Development of a Bayesian Estimator for Audio-Visual Integration: A Neurocomputational Study.

ABSTRACT: The brain integrates information from different sensory modalities to generate a coherent and accurate percept of external events. Several experimental studies suggest that this integration follows the principle of Bayesian estimate. However, the neural mechanisms responsible for this behavior, and its development in a multisensory environment, are still insufficiently understood. We recently presented a neural network model of audio-visual integration (Neural Computation, 2017) to investigate how a Bayesian estimator can spontaneously develop from the statistics of external stimuli. Model assumes the presence of two unimodal areas (auditory and visual) topologically organized. Neurons in each area receive an input from the external environment, computed as the inner product of the sensory

SUBMITTER: Ursino M 

PROVIDER: S-EPMC5633019 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature