A neurobiologically constrained cortex model of semantic grounding with spiking neurons and brain-like connectivity

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Tomasello, R.; Garagnani, M.; Wennekers, T. and Pulvermüller, F.. 2018. A neurobiologically constrained cortex model of semantic grounding with spiking neurons and brain-like connectivity. Frontiers in Computational Neuroscience, 12(88), [Article]

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Official URL: https://www.frontiersin.org/articles/10.3389/fncom...

Abstract or 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 that become differentially active during meaning processing, ranging from semantic hubs (which bind different types of meaning together) to modality-specific sensorimotor areas, involved in specific conceptual categories. Why and how the brain uses such complex organization for conceptualization can be investigated using biologically constrained neurocomputational models. Here, we apply a spiking neuron model mimicking structure and connectivity of frontal, temporal and occipital areas to simulate semantic learning and symbol grounding in action and perception. 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.

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Article

Identification Number (DOI):

https://doi.org/10.3389/fncom.2018.00088