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A Versatile Murine Model of Subcortical White Matter Stroke for the Study of Axonal Degeneration and White Matter Neurobiology
Published on: March 17, 2016
Behavioral Effects of Chronic Gray and White Matter Stroke Lesions in a Functionally Defined Connectome for Naming
Shihui Xing1,2, Ayan Mandal2, Elizabeth H Lacey2,3
11 First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Background:
In functional magnetic resonance imaging studies, picture naming engages widely distributed brain regions in the parietal, frontal, and temporal cortices. However, it remains unknown whether those activated areas, along with white matter pathways between them, are actually crucial for naming.
Objective:
We aimed to identify nodes and pathways implicated in naming in healthy older adults and test the impact of lesions to the connectome on naming ability.
Methods:
We first identified 24 cortical nodes activated by a naming task and reconstructed anatomical connections between these nodes using probabilistic tractography in healthy adults. We then used structural scans and fractional anisotropy (FA) maps in 45 patients with left hemisphere stroke to assess the relationships of node and pathway integrity to naming, phonology, and nonverbal semantic ability.
Results:
We found that mean FA values in 13 left hemisphere white matter tracts within the dorsal and ventral streams and 1 interhemispheric tract significantly related to naming scores after controlling for lesion size and demographic factors. In contrast, lesion loads in the cortical nodes were not related to naming performance after controlling for the same variables. Among the identified tracts, the integrity of 4 left hemisphere ventral stream tracts related to nonverbal semantic processing and 1 left hemisphere dorsal stream tract related to phonological processing.
Conclusions:
Our findings reveal white matter structures vital for naming and its subprocesses. These findings demonstrate the value of multimodal methods that integrate functional imaging, structural connectivity, and lesion data to understand relationships between brain networks and behavior.
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