Abstract

Progress in understanding multisensory integration in human have suggested researchers that the integration may result into the enhancement or depression of incoming signals. It is evident based on different psychological and behavioral experiments that stimuli coming from different perceptual modalities at the same time or from the same place, the signal having more strength under the influence of emotions effects the response accordingly. Current research in multisensory integration has not studied the effect of emotions despite its significance and natural influence in multisensory enhancement or depression. Therefore, there is a need to integrate the emotional state of the agent with incoming stimuli for signal enhancement or depression. In this study, two different neural network-based learning algorithms have been employed to learn the impact of emotions on signal enhancement or depression. It was observed that the performance of a proposed system for multisensory integration increases when emotion features were present during enhancement or depression of multisensory signals.

Highlights

  • The brain is the most complex part of the human body

  • The focus of this research paper is limited to sensory enhancement or depression, other parts of Superior colliculus (SC) such as the sensory integration module, event history module, and Working memory (WM) have been described in this paper very briefly to outline the scope of the generic system proposed for multisensory integration but they have no significance in this paper

  • This paper proposes ANN-based system for signal enhancement and depression during the integration process of senses i.e., audio and visual

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Summary

Introduction

The brain is the most complex part of the human body. The nervous system inside the human brain is composed of different types of cells. The primary functional unit of the nervous system is called the neuron. Every neuron passes signals which cause thoughts, actions, feelings, and memories [1]. The brain has a specific area to deal with sensory input and the most significant capabilities of the brain include an appropriate response to sensory input and information processing [2].

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