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Quantifying the Connectivity of the Language‐Specific Cerebrocebellar Network (LSCN)
Author(s) -
George Ian,
Beversdorf David,
Aldridge Kristina
Publication year - 2015
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.29.1_supplement.216.3
Subject(s) - cerebrum , diffusion mri , neuroscience , white matter , tractography , cerebellum , human brain , neuroimaging , functional magnetic resonance imaging , brain mapping , computer science , psychology , magnetic resonance imaging , medicine , central nervous system , radiology
Language was arguably a key influence in the evolution of the human brain and the evolution of this behavior in humans was likely associated with gross morphological changes and novel neural networks. Our previous research examined one such network and verified anatomical connectivity between regions of the cerebellum, thalamus, and frontal lobe active during language using a combination of magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). The results of the DTI analysis and fiber tracking support the hypothesis that there is discrete anatomical connectivity in a language‐specific network. Our current study is designed to characterize and quantify this anatomical connectivity in the language‐specific functional network between the cerebrum and cerebellum. We analyzed the language‐specific cerebrocerebellar network (LSCN) in 30 right‐handed neurotypical males through DTI images. Our results show the white matter tracts in the LSCN have greater connectivity than that of the white matter in the whole brain, indicating that there is a discrete network between the cerebrum and cerebellum exclusively for language. Information about the anatomical connectivity in this neural network can now be used in conjunction with behavioral measures to shed light on the evolution of the human brain, evolution of language, and pathologies that affect language production. This research was funded by the Wenner‐Gren Foundation, the MU Life Sciences Fellowship, Pearson, and the MU Brain Imaging Center.