Semantic grounding in a neurobiologically-constrained cortex-model with realistic connectivity and spiking neurons
Tomasello, Rosario; Garagnani, M.; Wennekers, Thomas and Pulvermüller, Friedemann. 2017. 'Semantic grounding in a neurobiologically-constrained cortex-model with realistic connectivity and spiking neurons'. In: 24th Annual Meeting of the Cognitive Neuroscience Society (CNS 2017). San Francisco, United States 25-28 March 2017. [Conference or Workshop Item]
No full text availableAbstract or Description
Previous neurocomputational work has addressed the question why and how many cortical areas contribute to semantic processing and, specifically, why semantic hubs involved in all types of semantics contrast with category-specific areas preferentially processing certain meaning subtypes. However, much of the pre-existing work used either basic neuron models or much-simplified connectivity so that a more sophisticated and biologically-realistic model would be desirable. Here, we applied a neural-network model replicating anatomical and physiological features of a range of cortical areas in the temporal-occipital and frontal lobes to simulate the learning of semantic relationships between word-forms and specific object perceptions and motor movements of the own body. The two neuronal architecture differed in the level of detail with which cortico-cortical connectivity was implemented. Furthermore, one model adopted a mean-field approach by using graded-response neurons, whereas the other implemented leaky integrate-and-fire neurons. Equipped with correlation-based learning rules and under the impact of repeated sensorimotor pattern presentations, both models showed spontaneous emergence of specific tightly interlinked cell assemblies within the larger networks, interlinking the processing of word-form information to that of sensorimotor semantic information. Both models also showed category-specificity in the cortical distribution of word-related circuits, with high-degree connection hub areas central to the network architecture exhibiting involvement in all types of semantic processing and only moderate categoryspecificity. The present simulations account for the emergence of both category-specific and general-semantic hub areas in the human brain and show that realistic neurocomputational models at different levels of detail consistently provide such explanation.
Item Type: |
Conference or Workshop Item (Poster) |
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Event Location: |
San Francisco, United States |
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Date range: |
25-28 March 2017 |
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Item ID: |
27759 |
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Date Deposited: |
13 Dec 2019 14:53 |
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Last Modified: |
13 Dec 2019 14:53 |
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