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

dc.contributor.authorKraikivski, Pavelen
dc.date.accessioned2024-02-23T15:17:51Zen
dc.date.available2024-02-23T15:17:51Zen
dc.date.issued2024-01-31en
dc.date.updated2024-02-23T15:03:13Zen
dc.description.abstractThe 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.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationKraikivski, P. A Mechanistic Model of Perceptual Binding Predicts That Binding Mechanism Is Robust against Noise. Entropy 2024, 26, 133.en
dc.identifier.doihttps://doi.org/10.3390/e26020133en
dc.identifier.urihttps://hdl.handle.net/10919/118125en
dc.language.isoenen
dc.publisherMDPIen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleA Mechanistic Model of Perceptual Binding Predicts That Binding Mechanism Is Robust against Noiseen
dc.title.serialEntropyen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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