Cargando…

A Neurobiologically Constrained Cortex Model of Semantic Grounding With Spiking Neurons and Brain-Like Connectivity

One of the most controversial debates in cognitive neuroscience concerns the cortical locus of semantic knowledge and processing in the human brain. Experimental data revealed the existence of various cortical regions relevant for meaning processing, ranging from semantic hubs generally involved in...

Descripción completa

Detalles Bibliográficos
Autores principales: Tomasello, Rosario, Garagnani, Max, Wennekers, Thomas, Pulvermüller, Friedemann
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6232424/
https://www.ncbi.nlm.nih.gov/pubmed/30459584
http://dx.doi.org/10.3389/fncom.2018.00088
_version_ 1783370397562961920
author Tomasello, Rosario
Garagnani, Max
Wennekers, Thomas
Pulvermüller, Friedemann
author_facet Tomasello, Rosario
Garagnani, Max
Wennekers, Thomas
Pulvermüller, Friedemann
author_sort Tomasello, Rosario
collection PubMed
description One of the most controversial debates in cognitive neuroscience concerns the cortical locus of semantic knowledge and processing in the human brain. Experimental data revealed the existence of various cortical regions relevant for meaning processing, ranging from semantic hubs generally involved in semantic processing to modality-preferential sensorimotor areas involved in the processing of specific conceptual categories. Why and how the brain uses such complex organization for conceptualization can be investigated using biologically constrained neurocomputational models. Here, we improve pre-existing neurocomputational models of semantics by incorporating spiking neurons and a rich connectivity structure between the model ‘areas’ to mimic important features of the underlying neural substrate. Semantic learning and symbol grounding in action and perception were simulated by associative learning between co-activated neuron populations in frontal, temporal and occipital areas. As a result of Hebbian learning of the correlation structure of symbol, perception and action information, distributed cell assembly circuits emerged across various cortices of the network. These semantic circuits showed category-specific topographical distributions, reaching into motor and visual areas for action- and visually-related words, respectively. All types of semantic circuits included large numbers of neurons in multimodal connector hub areas, which is explained by cortical connectivity structure and the resultant convergence of phonological and semantic information on these zones. Importantly, these semantic hub areas exhibited some category-specificity, which was less pronounced than that observed in primary and secondary modality-preferential cortices. The present neurocomputational model integrates seemingly divergent experimental results about conceptualization and explains both semantic hubs and category-specific areas as an emergent process causally determined by two major factors: neuroanatomical connectivity structure and correlated neuronal activation during language learning.
format Online
Article
Text
id pubmed-6232424
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-62324242018-11-20 A Neurobiologically Constrained Cortex Model of Semantic Grounding With Spiking Neurons and Brain-Like Connectivity Tomasello, Rosario Garagnani, Max Wennekers, Thomas Pulvermüller, Friedemann Front Comput Neurosci Neuroscience One of the most controversial debates in cognitive neuroscience concerns the cortical locus of semantic knowledge and processing in the human brain. Experimental data revealed the existence of various cortical regions relevant for meaning processing, ranging from semantic hubs generally involved in semantic processing to modality-preferential sensorimotor areas involved in the processing of specific conceptual categories. Why and how the brain uses such complex organization for conceptualization can be investigated using biologically constrained neurocomputational models. Here, we improve pre-existing neurocomputational models of semantics by incorporating spiking neurons and a rich connectivity structure between the model ‘areas’ to mimic important features of the underlying neural substrate. Semantic learning and symbol grounding in action and perception were simulated by associative learning between co-activated neuron populations in frontal, temporal and occipital areas. As a result of Hebbian learning of the correlation structure of symbol, perception and action information, distributed cell assembly circuits emerged across various cortices of the network. These semantic circuits showed category-specific topographical distributions, reaching into motor and visual areas for action- and visually-related words, respectively. All types of semantic circuits included large numbers of neurons in multimodal connector hub areas, which is explained by cortical connectivity structure and the resultant convergence of phonological and semantic information on these zones. Importantly, these semantic hub areas exhibited some category-specificity, which was less pronounced than that observed in primary and secondary modality-preferential cortices. The present neurocomputational model integrates seemingly divergent experimental results about conceptualization and explains both semantic hubs and category-specific areas as an emergent process causally determined by two major factors: neuroanatomical connectivity structure and correlated neuronal activation during language learning. Frontiers Media S.A. 2018-11-06 /pmc/articles/PMC6232424/ /pubmed/30459584 http://dx.doi.org/10.3389/fncom.2018.00088 Text en Copyright © 2018 Tomasello, Garagnani, Wennekers and Pulvermüller. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Tomasello, Rosario
Garagnani, Max
Wennekers, Thomas
Pulvermüller, Friedemann
A Neurobiologically Constrained Cortex Model of Semantic Grounding With Spiking Neurons and Brain-Like Connectivity
title A Neurobiologically Constrained Cortex Model of Semantic Grounding With Spiking Neurons and Brain-Like Connectivity
title_full A Neurobiologically Constrained Cortex Model of Semantic Grounding With Spiking Neurons and Brain-Like Connectivity
title_fullStr A Neurobiologically Constrained Cortex Model of Semantic Grounding With Spiking Neurons and Brain-Like Connectivity
title_full_unstemmed A Neurobiologically Constrained Cortex Model of Semantic Grounding With Spiking Neurons and Brain-Like Connectivity
title_short A Neurobiologically Constrained Cortex Model of Semantic Grounding With Spiking Neurons and Brain-Like Connectivity
title_sort neurobiologically constrained cortex model of semantic grounding with spiking neurons and brain-like connectivity
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6232424/
https://www.ncbi.nlm.nih.gov/pubmed/30459584
http://dx.doi.org/10.3389/fncom.2018.00088
work_keys_str_mv AT tomasellorosario aneurobiologicallyconstrainedcortexmodelofsemanticgroundingwithspikingneuronsandbrainlikeconnectivity
AT garagnanimax aneurobiologicallyconstrainedcortexmodelofsemanticgroundingwithspikingneuronsandbrainlikeconnectivity
AT wennekersthomas aneurobiologicallyconstrainedcortexmodelofsemanticgroundingwithspikingneuronsandbrainlikeconnectivity
AT pulvermullerfriedemann aneurobiologicallyconstrainedcortexmodelofsemanticgroundingwithspikingneuronsandbrainlikeconnectivity
AT tomasellorosario neurobiologicallyconstrainedcortexmodelofsemanticgroundingwithspikingneuronsandbrainlikeconnectivity
AT garagnanimax neurobiologicallyconstrainedcortexmodelofsemanticgroundingwithspikingneuronsandbrainlikeconnectivity
AT wennekersthomas neurobiologicallyconstrainedcortexmodelofsemanticgroundingwithspikingneuronsandbrainlikeconnectivity
AT pulvermullerfriedemann neurobiologicallyconstrainedcortexmodelofsemanticgroundingwithspikingneuronsandbrainlikeconnectivity