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Brain connectivity during the processing of nouns and verbs: a dynamic Bayesian network analysis

Abstract

Dynamic Bayesian network was used to study the connections among the brain regions activated during processing of nouns and verbs. Under simplifying assumptions, we arrived at a dynamic Bayesian network learning algorithm with reduced time complexity, which allowed us to test all possible connectivity models exhaustively and choose the best model based on the Bayesian information criterion (BIC) score. We found a posterior to anterior flow of processing of both nouns and verbs. The left medial frontal gyrus was found to play an important role in the network. For verb processing, strong involvements of motor cortex and cerebellum were found.published_or_final_versio

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