scholarly journals White matter network connectivity deficits in developmental dyslexia

2018 ◽  
Vol 40 (2) ◽  
pp. 505-516 ◽  
Author(s):  
Chenglin Lou ◽  
Xiting Duan ◽  
Irene Altarelli ◽  
John A. Sweeney ◽  
Franck Ramus ◽  
...  
2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 918-918
Author(s):  
Blake Neyland ◽  
Christina Hugenschmidt ◽  
Samuel Lockhart ◽  
Laura Baker ◽  
Suzanne Craft ◽  
...  

Abstract Brain pathologies are increasingly understood to confer mobility risk, but the malleability of functional brain networks may be a mechanism for mobility reserve. In particular, white matter hyperintensities (WMH) are strongly associated with mobility and alter functional network connectivity. To assess the potential role of brain networks as a mechanism of mobility reserve, 116 participants with MRI from the Brain Networks and Mobility Function (B-NET) were categorized into 4 groups based on median splits of SPPB scores and WMH burden: Expected Healthy (EH: low WMH, SPPB>10, N=45), Expected Impaired (EI: high WMH, SPPB10, N=24), Unexpected Impaired (EI: low WMH, SPPB<10, N=10) and Unexpected Unhealthy (UH: low WMH, SPPB<10, N=37). Functional brain networks were calculated using graph theory methods and white matter hyperintensities were quantified with the Lesion Segmentation Toolbox (LST) in SPM12. Somatomotor cortex community structure (SMC-CS) was similar between UH and EH with both having higher consistency than EI and UI. However, UH displayed a unique increase in second-order connections between the motor cortex and the anterior cingulate. It is possible that this increase in connections is a signal of higher reserve or resilience in UH participants and may indicate a mechanism of compensation in regards to mobility function and advanced WMH burden. These data suggest functional brain networks may be a mechanism for mobility resilience in older adults at mobility risk due to WMH burden.


2019 ◽  
Vol 23 ◽  
pp. 101931
Author(s):  
Stijn Michielse ◽  
Kimberley Rakijo ◽  
Sanne Peeters ◽  
Wolfgang Viechtbauer ◽  
Jim van Os ◽  
...  

2019 ◽  
Vol 29 ◽  
pp. S149-S150
Author(s):  
J. Lionarons ◽  
J. Hendriksen ◽  
A. Berns ◽  
C. Marini-Bettolo ◽  
K. Hollingsworth ◽  
...  

Cortex ◽  
2016 ◽  
Vol 76 ◽  
pp. 51-62 ◽  
Author(s):  
Jingjing Zhao ◽  
Michel Thiebaut de Schotten ◽  
Irene Altarelli ◽  
Jessica Dubois ◽  
Franck Ramus

2015 ◽  
pp. bhv281 ◽  
Author(s):  
Nicolas Langer ◽  
Barbara Peysakhovich ◽  
Jennifer Zuk ◽  
Marie Drottar ◽  
Danielle D. Sliva ◽  
...  

2021 ◽  
Vol 13 ◽  
Author(s):  
Martina Vettore ◽  
Matteo De Marco ◽  
Claudia Pallucca ◽  
Matteo Bendini ◽  
Maurizio Gallucci ◽  
...  

“Mild cognitive impairment” (MCI) is a diagnosis characterised by deficits in episodic memory (aMCI) or in other non-memory domains (naMCI). Although the definition of subtypes is helpful in clinical classification, it provides little insight on the variability of neurofunctional mechanisms (i.e., resting-state brain networks) at the basis of symptoms. In particular, it is unknown whether the presence of a high load of white-matter hyperintensities (WMHs) has a comparable effect on these functional networks in aMCI and naMCI patients. This question was addressed in a cohort of 123 MCI patients who had completed an MRI protocol inclusive of T1-weighted, fluid-attenuated inversion recovery (FLAIR) and resting-state fMRI sequences. T1-weighted and FLAIR images were processed with the Lesion Segmentation Toolbox to quantify whole-brain WMH volumes. The CONN toolbox was used to preprocess all fMRI images and to run an independent component analysis for the identification of four large-scale haemodynamic networks of cognitive relevance (i.e., default-mode, salience, left frontoparietal, and right frontoparietal networks) and one control network (i.e., visual network). Patients were classified based on MCI subtype (i.e., aMCI vs. naMCI) and WMH burden (i.e., low vs. high). Maps of large-scale networks were then modelled as a function of the MCI subtype-by-WMH burden interaction. Beyond the main effects of MCI subtype and WMH burden, a significant interaction was found in the salience and left frontoparietal networks. Having a low WMH burden was significantly more associated with stronger salience-network connectivity in aMCI (than in naMCI) in the right insula, and with stronger left frontoparietal-network connectivity in the right frontoinsular cortex. Vice versa, having a low WMH burden was significantly more associated with left-frontoparietal network connectivity in naMCI (than in aMCI) in the left mediotemporal lobe. The association between WMH burden and strength of connectivity of resting-state functional networks differs between aMCI and naMCI patients. Although exploratory in nature, these findings indicate that clinical profiles reflect mechanistic interactions that may play a central role in the definition of diagnostic and prognostic statuses.


2016 ◽  
Vol 37 (4) ◽  
pp. 1443-1458 ◽  
Author(s):  
Zaixu Cui ◽  
Zhichao Xia ◽  
Mengmeng Su ◽  
Hua Shu ◽  
Gaolang Gong

Radiology ◽  
2009 ◽  
Vol 251 (3) ◽  
pp. 882-891 ◽  
Author(s):  
Nancy K. Rollins ◽  
Behroze Vachha ◽  
Priya Srinivasan ◽  
Jonathon Chia ◽  
Joyce Pickering ◽  
...  

2021 ◽  
Author(s):  
Dirk Jan Ardesch ◽  
Lianne H. Scholtens ◽  
Siemon C. de Lange ◽  
Lea Roumazeilles ◽  
Alexandre A. Khrapitchev ◽  
...  

Brains come in many shapes and sizes. Nature has endowed big-brained primate species like humans with a proportionally large cerebral cortex. White matter connectivity - the brain's infrastructure for long-range communication - might not always scale at the same pace as the cortex. We investigated the consequences of this allometric scaling for white matter brain network connectivity. Structural T1 and diffusion MRI data were collated across fourteen primate species, describing a comprehensive 350-fold range in brain volume. We report volumetric scaling relationships that point towards a restriction in macroscale connectivity in larger brains. Building on previous findings, we show cortical surface to outpace white matter volume and the corpus callosum, suggesting the emergence of a white matter 'bottleneck' of lower levels of connectedness through the corpus callosum in larger brains. At the network level, we find a potential consequence of this bottleneck in shaping connectivity patterns, with homologous regions in the left and right hemisphere showing more divergent connectivity in larger brains. Our findings show conserved scaling relationships of major brain components and their consequence for macroscale brain circuitry, providing a comparative framework for expected connectivity architecture in larger brains such as the human brain.


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