A model of thalamo-cortical interaction for incremental binding in mental contour-tracing.

Object-basd visual attention marks a key process of mammalian perception. By which mechanisms this process is implemented and how it can be interacted with by means of attentional control is not completely understood yet. Incremental binding is a mechanism required in demanding scenarios of object-b...

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Main Authors: Daniel Schmid, Heiko Neumann
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-05-01
Series:PLoS Computational Biology
Online Access:https://doi.org/10.1371/journal.pcbi.1012835
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author Daniel Schmid
Heiko Neumann
author_facet Daniel Schmid
Heiko Neumann
author_sort Daniel Schmid
collection DOAJ
description Object-basd visual attention marks a key process of mammalian perception. By which mechanisms this process is implemented and how it can be interacted with by means of attentional control is not completely understood yet. Incremental binding is a mechanism required in demanding scenarios of object-based attention and is experimentally well investigated. Attention spreads across a representation of the visual object and labels bound elements by constant up-modulation of neural activity. The speed of incremental binding was found to be dependent on the spatial arrangement of distracting elements in the scene and to be scale invariant giving rise to the growth-cone hypothesis. In this work, we propose a neural dynamical model of incremental binding that provides a mechanistic account for these findings. Through simulations, we investigate the model properties and demonstrate how an attentional spreading mechanism tags neurons that participate in the object binding process. They utilize Gestalt properties and eventually show growth-cone characteristics labeling perceptual items by delayed activity enhancement of neuronal firing rates. We discuss the algorithmic process underlying incremental binding and relate it to our model computations. This theoretical investigation encompasses complexity considerations and finds the model to be not only of explanatory value in terms of neurophysiological evidence, but also to be an efficient implementation of incremental binding striving to establish a normative account. By relating the connectivity motifs of the model to neuroanatomical evidence, we suggest thalamo-cortical interactions to be a likely candidate for the flexible and efficient realization suggested by the model. There, pyramidal cells are proposed to serve as the processors of incremental grouping information. Local bottom-up evidence about stimulus features is integrated via basal dendritic sites. It is combined with an apical signal consisting of contextual grouping information which is gated by attentional task-relevance selection mediated via higher-order thalamic representations.
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spelling doaj-art-f12c939bfab940b9ba7d9adb64c9a07e2025-08-20T02:33:26ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582025-05-01215e101283510.1371/journal.pcbi.1012835A model of thalamo-cortical interaction for incremental binding in mental contour-tracing.Daniel SchmidHeiko NeumannObject-basd visual attention marks a key process of mammalian perception. By which mechanisms this process is implemented and how it can be interacted with by means of attentional control is not completely understood yet. Incremental binding is a mechanism required in demanding scenarios of object-based attention and is experimentally well investigated. Attention spreads across a representation of the visual object and labels bound elements by constant up-modulation of neural activity. The speed of incremental binding was found to be dependent on the spatial arrangement of distracting elements in the scene and to be scale invariant giving rise to the growth-cone hypothesis. In this work, we propose a neural dynamical model of incremental binding that provides a mechanistic account for these findings. Through simulations, we investigate the model properties and demonstrate how an attentional spreading mechanism tags neurons that participate in the object binding process. They utilize Gestalt properties and eventually show growth-cone characteristics labeling perceptual items by delayed activity enhancement of neuronal firing rates. We discuss the algorithmic process underlying incremental binding and relate it to our model computations. This theoretical investigation encompasses complexity considerations and finds the model to be not only of explanatory value in terms of neurophysiological evidence, but also to be an efficient implementation of incremental binding striving to establish a normative account. By relating the connectivity motifs of the model to neuroanatomical evidence, we suggest thalamo-cortical interactions to be a likely candidate for the flexible and efficient realization suggested by the model. There, pyramidal cells are proposed to serve as the processors of incremental grouping information. Local bottom-up evidence about stimulus features is integrated via basal dendritic sites. It is combined with an apical signal consisting of contextual grouping information which is gated by attentional task-relevance selection mediated via higher-order thalamic representations.https://doi.org/10.1371/journal.pcbi.1012835
spellingShingle Daniel Schmid
Heiko Neumann
A model of thalamo-cortical interaction for incremental binding in mental contour-tracing.
PLoS Computational Biology
title A model of thalamo-cortical interaction for incremental binding in mental contour-tracing.
title_full A model of thalamo-cortical interaction for incremental binding in mental contour-tracing.
title_fullStr A model of thalamo-cortical interaction for incremental binding in mental contour-tracing.
title_full_unstemmed A model of thalamo-cortical interaction for incremental binding in mental contour-tracing.
title_short A model of thalamo-cortical interaction for incremental binding in mental contour-tracing.
title_sort model of thalamo cortical interaction for incremental binding in mental contour tracing
url https://doi.org/10.1371/journal.pcbi.1012835
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