scholarly journals White matter connectivity between structures of the basal ganglia using 3T and 7T

Author(s):  
Jae-Hyuk Shim ◽  
Hyeon-Man Baek
2020 ◽  
Vol 87 (9) ◽  
pp. S264
Author(s):  
Eyal Abraham ◽  
Myrna Weissman ◽  
Priya Wickramaratne ◽  
Milenna van Dijk ◽  
Lifang Pan ◽  
...  

2016 ◽  
Vol 24 (4) ◽  
pp. 266-271
Author(s):  
이훈상 ◽  
이윤진 ◽  
김영미 ◽  
Yeon Gyu Min ◽  
김경민 ◽  
...  

2021 ◽  
pp. 0271678X2199098
Author(s):  
Saima Hilal ◽  
Siwei Liu ◽  
Tien Yin Wong ◽  
Henri Vrooman ◽  
Ching-Yu Cheng ◽  
...  

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.


Author(s):  
Jin Ho Jung ◽  
Yae Ji Kim ◽  
Seok Jong Chung ◽  
Han Soo Yoo ◽  
Yang Hyun Lee ◽  
...  

Stroke ◽  
2005 ◽  
Vol 36 (6) ◽  
pp. 1184-1188 ◽  
Author(s):  
Gabriel Gold ◽  
Enikö Kövari ◽  
François R. Herrmann ◽  
Alessandra Canuto ◽  
Patrick R. Hof ◽  
...  

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

2020 ◽  
Author(s):  
Gina F. Humphreys ◽  
JeYoung Jung ◽  
Matthew A. Lambon Ralph

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.


2021 ◽  
Author(s):  
Ittai Shamir ◽  
Omri Tomer ◽  
Ronnie Krupnik ◽  
Yaniv Assaf

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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