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Cognitive Neurodynamics

, Volume 12, Issue 5, pp 481–499 | Cite as

An oscillatory neural network model that demonstrates the benefits of multisensory learning

  • A. Ravishankar Rao
Research Article

Abstract

Since the world consists of objects that stimulate multiple senses, it is advantageous for a vertebrate to integrate all the sensory information available. However, the precise mechanisms governing the temporal dynamics of multisensory processing are not well understood. We develop a computational modeling approach to investigate these mechanisms. We present an oscillatory neural network model for multisensory learning based on sparse spatio-temporal encoding. Recently published results in cognitive science show that multisensory integration produces greater and more efficient learning. We apply our computational model to qualitatively replicate these results. We vary learning protocols and system dynamics, and measure the rate at which our model learns to distinguish superposed presentations of multisensory objects. We show that the use of multiple channels accelerates learning and recall by up to 80%. When a sensory channel becomes disabled, the performance degradation is less than that experienced during the presentation of non-congruent stimuli. This research furthers our understanding of fundamental brain processes, paving the way for multiple advances including the building of machines with more human-like capabilities.

Keywords

Oscillatory neural networks Synchronization Binding Multisensory processing Learning Audio–visual processing 

Notes

Acknowledgements

The author greatly appreciates helpful comments from the reviewers, which improved this manuscript.

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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Gildart Haase School of Computer Sciences and EngineeringFairleigh Dickinson UniversityTeaneckUSA

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