TY - JOUR
T1 - Neural correlates of verbal fluency revealed by longitudinal T1, T2 and FLAIR imaging in stroke
AU - Xiong, Yanyu
AU - Khlif, Mohamed Salah
AU - Egorova-Brumley, Natalia
AU - Brodtmann, Amy
AU - Stark, Brielle C.
N1 - Funding Information:
Our study utilized anatomical, non-diffusion images to identify that semantic fluency was supported by the left SLF and the posterior segment of the left AF for chronic stroke patients. Greater disconnection probabilities of the two tracts were correlated to reduced semantic fluency. In contrast, phonemic fluency pointed to the right subcortical GM volume as the crucial neural substrate. The results lend further support to the claim that semantic and phonemic fluency may engage different neural correlates.
Publisher Copyright:
© 2023 The Author(s)
PY - 2023/1
Y1 - 2023/1
N2 - Diffusion-weighted imaging has been widely used in the research on post-stroke verbal fluency but acquiring diffusion data is not always clinically feasible. Achieving comparable reliability for detecting brain variables associated with verbal fluency impairments, based on more readily available anatomical, non-diffusion images (T1, T2 and FLAIR), enables clinical practitioners to have complementary neurophysiological information at hand to facilitate diagnosis and treatment of language impairment. Meanwhile, although the predominant focus in the stroke recovery literature has been on cortical contributions to verbal fluency, it remains unclear how subcortical regions and white matter disconnection are related to verbal fluency. Our study thus utilized anatomical scans of ischaemic stroke survivors (n = 121) to identify longitudinal relationships between subcortical volume, white matter tract disconnection, and verbal fluency performance at 3- and 12-months post-stroke. Subcortical grey matter volume was derived from FreeSurfer. We used an indirect probabilistic approach to quantify white matter disconnection in terms of disconnection severity, the proportion of lesioned voxel volume to the total volume of a tract, and disconnection probability, the probability of the overlap between the stroke lesion and a tract. These disconnection variables of each subject were identified based on the disconnectome map of the BCBToolkit. Using a linear mixed multiple regression method with 5-fold cross-validations, we correlated the semantic and phonemic fluency scores with longitudinal measurements of subcortical grey matter volume and 22 bilateral white matter tracts, while controlling for demographic variables (age, sex, handedness and education), total brain volume, lesion volume, and cortical thickness. The results showed that the right subcortical grey matter volume was positively correlated with phonemic fluency averaged over 3 months and 12 months. The finding generalized well on the test data. The disconnection probability of left superior longitudinal fasciculus II and left posterior arcuate fasciculus was negatively associated with semantic fluency only on the training data, but the result aligned with our previous study using diffusion scans in the same clinical population. In sum, our results presented evidence that routinely acquired anatomical scans can serve as a reliable source for deriving neural variables of post-stroke verbal fluency performance. The use of this method might provide an ecologically valid and more readily implementable analysis tool.
AB - Diffusion-weighted imaging has been widely used in the research on post-stroke verbal fluency but acquiring diffusion data is not always clinically feasible. Achieving comparable reliability for detecting brain variables associated with verbal fluency impairments, based on more readily available anatomical, non-diffusion images (T1, T2 and FLAIR), enables clinical practitioners to have complementary neurophysiological information at hand to facilitate diagnosis and treatment of language impairment. Meanwhile, although the predominant focus in the stroke recovery literature has been on cortical contributions to verbal fluency, it remains unclear how subcortical regions and white matter disconnection are related to verbal fluency. Our study thus utilized anatomical scans of ischaemic stroke survivors (n = 121) to identify longitudinal relationships between subcortical volume, white matter tract disconnection, and verbal fluency performance at 3- and 12-months post-stroke. Subcortical grey matter volume was derived from FreeSurfer. We used an indirect probabilistic approach to quantify white matter disconnection in terms of disconnection severity, the proportion of lesioned voxel volume to the total volume of a tract, and disconnection probability, the probability of the overlap between the stroke lesion and a tract. These disconnection variables of each subject were identified based on the disconnectome map of the BCBToolkit. Using a linear mixed multiple regression method with 5-fold cross-validations, we correlated the semantic and phonemic fluency scores with longitudinal measurements of subcortical grey matter volume and 22 bilateral white matter tracts, while controlling for demographic variables (age, sex, handedness and education), total brain volume, lesion volume, and cortical thickness. The results showed that the right subcortical grey matter volume was positively correlated with phonemic fluency averaged over 3 months and 12 months. The finding generalized well on the test data. The disconnection probability of left superior longitudinal fasciculus II and left posterior arcuate fasciculus was negatively associated with semantic fluency only on the training data, but the result aligned with our previous study using diffusion scans in the same clinical population. In sum, our results presented evidence that routinely acquired anatomical scans can serve as a reliable source for deriving neural variables of post-stroke verbal fluency performance. The use of this method might provide an ecologically valid and more readily implementable analysis tool.
KW - Anatomical scans
KW - Phonemic fluency
KW - Semantic fluency
KW - Stroke
KW - Subcortical grey matter volume
KW - White matter tract disconnection
UR - https://www.scopus.com/pages/publications/85153237428
U2 - 10.1016/j.nicl.2023.103406
DO - 10.1016/j.nicl.2023.103406
M3 - Article
C2 - 37104929
AN - SCOPUS:85153237428
SN - 2213-1582
VL - 38
JO - NeuroImage: Clinical
JF - NeuroImage: Clinical
M1 - 103406
ER -