Changes in White Matter Connectivity Following Therapy for Anomia Post stroke

2013 ◽  
Vol 28 (4) ◽  
pp. 325-334 ◽  
Author(s):  
Sophia van Hees ◽  
Katie McMahon ◽  
Anthony Angwin ◽  
Greig de Zubicaray ◽  
Stephen Read ◽  
...  
Keyword(s):  
White Matter ◽  
Post Stroke ◽  
White Matter Connectivity

Abstract WP163: Post-stroke Aphasia Severity is Determined by the Disorganization of Residual White Matter Networks

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Barbara K Marebwa ◽  
Julius Fridriksson ◽  
Grigori Yourganov ◽  
Lynda Feenaughty ◽  
Chris Rorden ◽  
...  
Keyword(s):  
White Matter ◽  
Left Hemisphere ◽  
Right Hemisphere ◽  
Brain Regions ◽  
Clinical Staging ◽  
Post Stroke ◽  
Brain Connectome ◽  
Fragmentation Index ◽  
Chronic Aphasia ◽  
White Matter Connectivity

Introduction: Many stroke survivors who suffer from aphasia in the acute period experience spontaneous recovery within the first six months post-stroke. About 20% sustain permanent and disabling language problems and the factors that drive incomplete recovery are not clear. Cortical dysfunction may occur in areas seemingly spared by the stroke due to changes to metabolism as well as loss of white matter connectivity and disruption of cortical and subcortical network integrity. We hypothesized that residual white matter connectivity could provide a personalized predictor of the severity of chronic aphasia. Methods: We reconstructed the individual structural whole-brain connectome from 90 right handed participants with a single left hemisphere ischemic or hemorrhagic stroke. All participants underwent language assessment using the Western Aphasia Battery (WAB-AQ). Data analysis was performed on each subject’s individual connectome, a weighted adjacency matrix M of size 189 x 189. We measured comprehensive white matter topological network organization using Newman’s modularity algorithm and calculated the probability of brain regions clustering together though a community affiliation index, which was used to determine the structural fragmentation of white matter networks in the left hemisphere relative to right hemisphere, expressed by a fragmentation index. Results: Patients with greater post-stroke left hemisphere network fragmentation and higher modularity index had more severe chronic aphasia, controlling for the size of the stroke lesion. Modularity and fragmentation index significantly increased with aphasia severity (r = -0.42), and (r = -0.43) respectively. Even when the left hemisphere was relatively spared, patients with disorganized community structure had significantly worse aphasia. Conclusion: Our findings confirm that residual white matter integrity and disorganization of neuronal networks are important determinants of chronic aphasia severity. Furthermore, the assessment of residual connectome white matter organization through modularity provides a comprehensive and personalized measurement that may be used as a marker for clinical staging and aphasia treatment planning.

scholarly journals Tractography Alterations in the Arcuate and Uncinate Fasciculi in Post-Stroke Aphasia

2021 ◽  
Vol 11 (1) ◽  
pp. 53
Author(s):  
Sara Kierońska ◽  
Milena Świtońska ◽  
Grzegorz Meder ◽  
Magdalena Piotrowska ◽  
Paweł Sokal
Keyword(s):  
White Matter ◽  
Brain Connectivity ◽  
Three Dimensional ◽  
Cerebral White Matter ◽  
Neural Pathways ◽  
Uncinate Fasciculus ◽  
Arcuate Fasciculus ◽  
Fiber Tractography ◽  
Post Stroke

Fiber tractography based on diffuse tensor imaging (DTI) can reveal three-dimensional white matter connectivity of the human brain. Tractography is a non-invasive method of visualizing cerebral white matter structures in vivo, including neural pathways surrounding the ischemic area. DTI may be useful for elucidating alterations in brain connectivity resulting from neuroplasticity after stroke. We present a case of a male patient who developed significant mixed aphasia following ischemic stroke. The patient had been treated by mechanical thrombectomy followed by an early rehabilitation, in conjunction with transcranial direct current stimulation (tDCS). DTI was used to examine the arcuate fasciculus and uncinate fasciculus upon admission and again at three months post-stroke. Results showed an improvement in the patient’s symptoms of aphasia, which was associated with changes in the volume and numbers of tracts in the uncinate fasciculus and the arcuate fasciculus.

scholarly journals White matter network damage mediates association between cerebrovascular disease and cognition

2021 ◽  
pp. 0271678X2199098
Author(s):  
Saima Hilal ◽  
Siwei Liu ◽  
Tien Yin Wong ◽  
Henri Vrooman ◽  
Ching-Yu Cheng ◽  
...  
Keyword(s):  
White Matter ◽  
Cerebrovascular Disease ◽  
Verbal Memory ◽  
Visual Memory ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Domain Specific ◽  
Epidemiology Of Dementia ◽  
Z Scores ◽  
White Matter Connectivity

To determine whether white matter network disruption mediates the association between MRI markers of cerebrovascular disease (CeVD) and cognitive impairment. Participants (n = 253, aged ≥60 years) from the Epidemiology of Dementia in Singapore study underwent neuropsychological assessments and MRI. CeVD markers were defined as lacunes, white matter hyperintensities (WMH), microbleeds, cortical microinfarcts, cortical infarcts and intracranial stenosis (ICS). White matter microstructure damage was measured as fractional anisotropy and mean diffusivity by tract based spatial statistics from diffusion tensor imaging. Cognitive function was summarized as domain-specific Z-scores. Lacunar counts, WMH volume and ICS were associated with worse performance in executive function, attention, language, verbal and visual memory. These three CeVD markers were also associated with white matter microstructural damage in the projection, commissural, association, and limbic fibers. Path analyses showed that lacunar counts, higher WMH volume and ICS were associated with executive and verbal memory impairment via white matter disruption in commissural fibers whereas impairment in the attention, visual memory and language were mediated through projection fibers. Our study shows that the abnormalities in white matter connectivity may underlie the relationship between CeVD and cognition. Further longitudinal studies are needed to understand the cause-effect relationship between CeVD, white matter damage and cognition.

White matter connectivity networks predict levodopa-induced dyskinesia in Parkinson’s disease

2021 ◽  
Author(s):  
Jin Ho Jung ◽  
Yae Ji Kim ◽  
Seok Jong Chung ◽  
Han Soo Yoo ◽  
Yang Hyun Lee ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
White Matter ◽  
White Matter Connectivity

scholarly journals Differences in white matter connectivity between treatment-resistant and treatment-responsive subtypes of schizophrenia

2018 ◽  
Vol 282 ◽  
pp. 47-54 ◽  
Author(s):  
Carolyn Beth McNabb ◽  
Rob Kydd ◽  
Frederick Sundram ◽  
Ian Soosay ◽  
Bruce Roy Russell
Keyword(s):  
White Matter ◽  
Treatment Resistant ◽  
White Matter Connectivity

scholarly journals The convergence and divergence of episodic and semantic functions across lateral parietal cortex

2020 ◽  
Author(s):  
Gina F. Humphreys ◽  
JeYoung Jung ◽  
Matthew A. Lambon Ralph
Keyword(s):  
White Matter ◽  
Semantic Memory ◽  
Parietal Cortex ◽  
Memory Retrieval ◽  
Task Difficulty ◽  
Structural Connectivity ◽  
Angular Gyrus ◽  
Episodic Retrieval ◽  
Semantic Retrieval ◽  
White Matter Connectivity

AbstractSeveral decades of neuropsychological and neuroimaging research have highlighted the importance of lateral parietal cortex (LPC) across a myriad of cognitive domains. Yet, despite the prominence of this region the underlying function of LPC remains unclear. Two domains that have placed particular emphasis on LPC involvement are semantic memory and episodic memory retrieval. From each domain, sophisticated models have been proposed as to the underlying function, as well as the more domain-general that LPC is engaged by any form of internally-directed cognition (episodic and semantic retrieval both being examples if this process). Here we directly address these alternatives using a combination of fMRI and DTI white-matter connectivity data. The results show that ventral LPC (angular gyrus) was positively engaged during episodic retrieval but disengaged during semantic memory retrieval. In addition, the level of activity negatively varied with task difficulty in the semantic task whereas episodic activation was independent of difficulty. In contrast, dorsal LPC (intraparietal sulcus) showed domain general activation that was positively correlated with task difficulty. In terms of structural connectivity, a dorsal-ventral and anterior-posterior gradient of connectivity was found to different processing networks (e.g., mid-angular gyrus (AG) connected with episodic retrieval). We propose a unifying model in which LPC as a whole might share a common underlying function (e.g., multimodal buffering) and variations across subregions arise due to differences in the underlying white matter connectivity.

scholarly journals Exploring the laminar connectome

2021 ◽  
Author(s):  
Ittai Shamir ◽  
Omri Tomer ◽  
Ronnie Krupnik ◽  
Yaniv Assaf
Keyword(s):  
White Matter ◽  
Grey Matter ◽  
Structural Description ◽  
Mri Imaging ◽  
Healthy Human ◽  
Cortical Grey Matter ◽  
Cortical Laminar ◽  
White Matter Connectivity ◽  
Human Brains

The human connectome is the complete structural description of the network of connections and elements that form the wiring diagram of the brain. Because of the current scarcity of information regarding laminar end points of white matter tracts inside cortical grey matter, tractography remains focused on cortical partitioning into regions, while ignoring radial partitioning into laminar components. To overcome this biased representation of the cortex as a single homogenous unit, we use a recent data-derived model of cortical laminar connectivity, which has been further explored and corroborated in the macaque brain by comparison to published studies. The model integrates multimodal MRI imaging datasets regarding both white matter connectivity and grey matter laminar composition into a laminar-level connectome. In this study we model the laminar connectome of healthy human brains (N=20) and explore them via a set of neurobiologically meaningful complex network measures. Our analysis demonstrates a subdivision of network hubs that appear in the standard connectome into each individual component of the laminar connectome, giving a fresh look into the role of laminar components in cortical connectivity and offering new prospects in the fields of both structural and functional connectivity.

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