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A dynamical framework to relate perceptual variability with multisensory information processing.

Bhumika Thakur1, Abhishek Mukherjee2, Abhijit Sen1

  • 1Institute for Plasma Research (IPR), Bhat, Gandhinagar 382428, Gujarat, India.

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|August 10, 2016
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Summary
This summary is machine-generated.

This study introduces a dynamic systems model for multisensory processing, revealing that synchronized sensory inputs (zero audiovisual lag) enhance perception. Deviations from this synchronization decrease stability, offering a quantitative framework for understanding how the brain integrates sensory information.

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Area of Science:

  • Cognitive Neuroscience
  • Computational Neuroscience
  • Psychophysics

Background:

  • Multisensory processing integrates information from various sensory streams (e.g., vision, audition) for perception.
  • The McGurk effect demonstrates illusory speech sound perception from incongruent audiovisual stimuli.
  • Auditory-visual lag and unisensory perturbations significantly modulate multisensory perception, yet quantitative models are scarce.

Purpose of the Study:

  • To propose a dynamic systems model for multisensory processing.
  • To investigate the role of coupling parameters and time delays in multisensory integration.
  • To provide a quantitative framework for understanding perceptual variability in multisensory environments.

Main Methods:

  • Developed a dynamic systems model with two unisensory and one multisensory subsystem (nodes).
  • Incorporated biophysically inspired coupling parameters and time delays between nodes.
  • Analyzed network synchronization patterns based on audiovisual (AV) lag.

Main Results:

  • Zero AV lag maximized the synchronization of network nodes.
  • Non-zero AV lags led to decreased synchronization.
  • Attractor states of the model correlate with stable perceptual experiences.

Conclusions:

  • The proposed dynamic model offers a quantitative framework for understanding multisensory information processing.
  • Network synchronization, driven by AV lag, is crucial for stabilizing perception.
  • The model elucidates the interplay between psychophysical variables and neural interactions in multisensory perception.