This letter shows by digital simulation that a simple rule applied to one-dimensional self-organized maps for integrating sensory perceptions from two identical sources yielding position information as integers, corrupted by independent noise sources, yields almost statistically optimal results for position estimation as determined by maximum likelihood estimation. There is no learning of the corrupting noise sources nor is any information about the statistics of the noise sources available to the integrating process. The simple rule employed yields a measure of the quality of the estimated position of the source. The letter also shows that if the Bayesian estimates, which are rational numbers, are rounded in order to comply with the stipulation that integers be identified, the Bayesian estimation will have a larger variance than the proposed integration.

The multimodal self-organizing network (MMSON), an artificial neural network architecture carrying out sensory integration, is presented here. The architecture is designed using neurophysiological findings and imaging studies that pertain to sensory integration and consists of interconnected lattices of artificial neurons. In this artificial neural architecture, the degree of recognition of stimuli, that is, the perceived reliability of stimuli in the various subnetworks, is included in the computation. The MMSON's behavior is compared to aspects of brain function that deal with sensory integration. According to human behavioral studies, integration of signals from sensory receptors of different modalities enhances perception of objects and events and also reduces time to detection. In neocortex, integration takes place in bimodal and multimodal association areas and result, not only in feedback-mediated enhanced unimodal perception and shortened reaction time, but also in robust bimodal or multimodal percepts. Simulation data from the presented artificial neural network architecture show that it replicates these important psychological and neuroscientific characteristics of sensory integration.