Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

A Dynamic Mechanistic Model of Perceptual Binding

Version 1 : Received: 24 February 2022 / Approved: 25 February 2022 / Online: 25 February 2022 (08:46:39 CET)

How to cite: Kraikivski, P. A Dynamic Mechanistic Model of Perceptual Binding. Preprints 2022, 2022020326 (doi: 10.20944/preprints202202.0326.v1). Kraikivski, P. A Dynamic Mechanistic Model of Perceptual Binding. Preprints 2022, 2022020326 (doi: 10.20944/preprints202202.0326.v1).

Abstract

The brain’s ability to create a unified conscious representation of an object by integrating information from multiple perception pathways is called perceptual binding. Binding is crucial for normal cognitive function. Some perceptual binding errors and disorders have been linked to certain neurological conditions, brain lesions, and conditions that give rise to illusory conjunctions. However, the mechanism of perceptual binding remains elusive. Here, we present a computational model of binding using two sets of coupled oscillatory processes that are assumed to occur in response to two different percepts. We use the model to study the dynamic behavior of coupled processes to characterize how these processes can modulate each other and reach a temporal synchrony. We identify different oscillatory dynamic regimes that depend on coupling mechanisms and parameter values. The model can also discriminate different combinations of initial inputs that are set by initial states of coupled processes. Decoding brain signals that are formed through perceptual binding is a challenging task, but our modeling results demonstrate how crosstalk between two systems of processes can possibly modulate their outputs. Therefore, our mechanistic model can help one gain a better understanding of how crosstalk between perception pathways can affect the dynamic behavior of the systems that involve perceptual binding.

Keywords

Binding Problem; Perceptual Binding; Consciousness; Perception

Subject

MATHEMATICS & COMPUTER SCIENCE, Other

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.