A Mechanistic Model of Perceptual Binding Predicts That Binding Mechanism Is Robust against Noise.

The brain creates its own internal representations of time and space, which may differ from external time and space. This work presents a mechanistic model of interconnected processes that encode phenomenal representations of space and time, elaborating how these processes bind together. A stochastic version of the model explores how binding strength interacts with noise, using spectral entropy to characterize noise effects. Results show that spectral entropy values for strongly bound systems are similar to those for weakly bound or decoupled systems, indicating that the binding mechanism is resilient to noise.

Study at a glance

Abstract

The concept of the brain's own time and space is central to many models and theories that aim to explain how the brain generates consciousness. For example, the temporo-spatial theory of consciousness postulates that the brain implements its own inner time and space for conscious processing of the outside world. Furthermore, our perception and cognition of time and space can be different from actual time and space. This study presents a mechanistic model of mutually connected processes that encode phenomenal representations of space and time. The model is used to elaborate the binding mechanism between two sets of processes representing internal space and time, respectively. Further, a stochastic version of the model is developed to investigate the interplay between binding strength and noise. Spectral entropy is used to characterize noise effects on the systems of interacting processes when the binding strength between them is varied. The stochastic modeling results reveal that the spectral entropy values for strongly bound systems are similar to those for weakly bound or even decoupled systems. Thus, the analysis performed in this study allows us to conclude that the binding mechanism is noise-resilient.