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Structured sequence processing and combinatorial binding: neurobiologically and computationally informed hypotheses

Lookup NU author(s): Dr Ryan Calmus, Dr Ben Wilson, Dr Yuki Kikuchi, Professor Christopher Petkov

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

Understanding how the brain forms representations of structured information distributed in time is a challenging endeavour for the neuroscientific community, requiring computationally and neurobiologically informed approaches. The neural mechanisms for segmenting continuous streams of sensory input and establishing representations of dependencies remain largely unknown, as do the transformations and computations occurring between the brain regions involved in these aspects of sequence processing. We propose a blueprint for a neurobiologically informed and informing computational model of sequence processing (entitled: Vector-symbolic Sequencing of Binding INstantiating Dependencies, or VS-BIND). This model is designed to support the transformation of serially ordered elements in sensory sequences into structured representations of bound dependencies, readily operates on multiple timescales, and encodes or decodes sequences with respect to chunked items wherever dependencies occur in time. The model integrates established vector symbolic additive and conjunctive binding operators with neurobiologically plausible oscillatory dynamics, and is compatible with modern spiking neural network simulation methods. We show that the model is capable of simulating previous findings from structured sequence processing tasks that engage fronto-temporal regions, specifying mechanistic roles for regions such as prefrontal areas 44/45 and the frontal operculum during interactions with sensory representations in temporal cortex. Finally, we are able to make predictions based on the configuration of the model alone that underscore the importance of serial position information, which requires input from time-sensitive cells, known to reside in the hippocampus and dorsolateral prefrontal cortex. This article is part of the theme issue 'Towards mechanistic models of meaning composition'.


Publication metadata

Author(s): Calmus R, Wilson B, Kikuchi Y, Petkov CI

Publication type: Article

Publication status: Published

Journal: Philosophical Transactions of the Royal Society B

Year: 2019

Volume: 375

Issue: 1791

Pages: 20190304

Print publication date: 16/12/2019

Acceptance date: 04/11/2019

Date deposited: 02/01/2020

ISSN (print): 0962-8436

ISSN (electronic): 1471-2970

Publisher: The Royal Society Publishing

URL: https://doi.org/10.1098/rstb.2019.0304

DOI: 10.1098/rstb.2019.0304

PubMed id: 31840585


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Funding

Funder referenceFunder name
BB/J009849/1Biotechnology and Biological Sciences Research Council (BBSRC)
MECHIDENT
R01-DC04290
WT092606AIA
WT110198

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