Parcellation‐based anatomic model of the semantic network
Autor: | Yueh-Hsin Lin, Rannulu Dineth Fonseka, Jorge Hormovas, Andrew K. Conner, Camille K Milton, Michael Y. Bai, Chad A. Glenn, Onur Tanglay, Vukshitha Dhanaraj, Robert G. Briggs, Stéphane Doyen, Michael E. Sughrue, Isabella M. Young, Peter J. Nicholas, Hugh M. Taylor, Charles Teo |
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Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
Models
Anatomic Speech production Computer science tractography Context (language use) computer.software_genre 050105 experimental psychology Lateralization of brain function Semantic network lcsh:RC321-571 03 medical and health sciences Behavioral Neuroscience 0302 clinical medicine Connectome Semantic memory Humans Speech 0501 psychology and cognitive sciences dual stream language network lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry Semantic Web Original Research Brain Mapping Human Connectome Project business.industry 05 social sciences Magnetic Resonance Imaging Semantics Categorization parcellation Artificial intelligence business computer 030217 neurology & neurosurgery Natural language processing Tractography |
Zdroj: | Brain and Behavior, Vol 11, Iss 4, Pp n/a-n/a (2021) Brain and Behavior |
ISSN: | 2162-3279 |
Popis: | Introduction The semantic network is an important mediator of language, enabling both speech production and the comprehension of multimodal stimuli. A major challenge in the field of neurosurgery is preventing semantic deficits. Multiple cortical areas have been linked to semantic processing, though knowledge of network connectivity has lacked anatomic specificity. Using attentional task‐based fMRI studies, we built a neuroanatomical model of this network. Methods One hundred and fifty‐five task‐based fMRI studies related to categorization of visual words and objects, and auditory words and stories were used to generate an activation likelihood estimation (ALE). Cortical parcellations overlapping the ALE were used to construct a preliminary model of the semantic network based on the cortical parcellation scheme previously published under the Human Connectome Project. Deterministic fiber tractography was performed on 25 randomly chosen subjects from the Human Connectome Project, to determine the connectivity of the cortical parcellations comprising the network. Results The ALE analysis demonstrated fourteen left hemisphere cortical regions to be a part of the semantic network: 44, 45, 55b, IFJa, 8C, p32pr, SFL, SCEF, 8BM, STSdp, STSvp, TE1p, PHT, and PBelt. These regions showed consistent interconnections between parcellations. Notably, the anterior temporal pole, a region often implicated in semantic function, was absent from our model. Conclusions We describe a preliminary cortical model for the underlying structural connectivity of the semantic network. Future studies will further characterize the neurotractographic details of the semantic network in the context of medical application. Using 155 attentional task‐based fMRI studies, we built a neuroanatomical model of the semantic network described in the HCP parcellation scheme. Fourteen left hemisphere cortical regions were found to be part of the semantic network: 44, 45, 55b, IFJa, 8C, p32pr, SFL, SCEF, 8BM, STSdp, STSvp, TE1p, PHT, and PBelt. Notably, the anterior temporal pole, a region often implicated in semantic function, was absent from our model. |
Databáze: | OpenAIRE |
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