scholarly journals A Large-Scale Investigation of White Matter Microstructural Associations with Reading Ability

NeuroImage ◽  
2022 ◽  
pp. 118909
Author(s):  
Steven L. Meisler ◽  
John D.E. Gabrieli
Keyword(s):  
White Matter ◽  
Reading Ability ◽  
Large Scale

scholarly journals A Large-Scale Investigation of White Matter Microstructural Associations with Reading Ability

2021 ◽  
Author(s):  
Steven L Meisler ◽  
John D.E. Gabrieli
Keyword(s):  
White Matter ◽  
Reading Disabilities ◽  
Reading Ability ◽  
Large Scale ◽  
Reading Skills ◽  
Right Hemisphere ◽  
Small Sample ◽  
Poor Readers ◽  
Neural Basis ◽  
Data Set

Reading involves the functioning of a widely distributed brain network, and white matter tracts are responsible for sending information between constituent network nodes. Several studies have analyzed fiber bundle microstructural properties to shed insights into the neural basis of reading abilities and disabilities. Findings have been inconsistent, potentially due to small sample sizes and varying methodology. To address this, we analyzed a large data set of 690 children ages 5-18 using state-of-the-art neuroimaging acquisitions and processing techniques. We searched for associations between fractional anisotropy (FA) and single-word and nonword reading skills in both typical and poor readers across multiple tracts previously thought to contribute to reading. Consistent with prior studies, FA increased with age across all tracts. There were significant correlations between better reading skills and higher FA in several fiber bundles among poor readers, but fewer and occasionally negative associations among proficient readers. The left superior longitudinal fasciculus and arcuate fasciculus unexpectedly exhibited higher FA within those diagnosed with reading disabilities compared to those without a diagnosis, while their right-hemisphere homologs exhibited higher FA in those with higher reading scores, regardless of diagnostic status. These results suggest a different relation between white matter pathways in children with typical reading ability versus those with reading disabilities.

What Has Direct Cortical and Subcortical Electrostimulation Taught Us about Neurolinguistics?

2019 ◽  
pp. 185-211
Author(s):  
Hugues Duffau
Keyword(s):  
White Matter ◽  
Large Scale ◽  
Functional Neuroimaging ◽  
Great Accuracy ◽  
Subcortical White Matter ◽  
Cerebral Lesions ◽  
Physiological Basis ◽  
Postoperative Mri ◽  
The Brain

Investigating the neural and physiological basis of language is one of the most important challenges in neurosciences. Direct electrical stimulation (DES), usually performed in awake patients during surgery for cerebral lesions, is a reliable tool for detecting both cortical and subcortical (white matter and deep grey nuclei) regions crucial for cognitive functions, especially language. DES transiently interacts locally with a small cortical or axonal site, but also nonlocally, as the focal perturbation will disrupt the entire subnetwork sustaining a given function. Thus, in contrast to functional neuroimaging, DES represents a unique opportunity to identify with great accuracy and reproducibility, in vivo in humans, the structures that are actually indispensable to the function, by inducing a transient virtual lesion based on the inhibition of a subcircuit lasting a few seconds. Currently, this is the sole technique that is able to directly investigate the functional role of white matter tracts in humans. Thus, combining transient disturbances elicited by DES with the anatomical data provided by pre- and postoperative MRI enables to achieve reliable anatomo-functional correlations, supporting a network organization of the brain, and leading to the reappraisal of models of language representation. Finally, combining serial peri-operative functional neuroimaging and online intraoperative DES allows the study of mechanisms underlying neuroplasticity. This chapter critically reviews the basic principles of DES, its advantages and limitations, and what DES can reveal about the neural foundations of language, that is, the large-scale distribution of language areas in the brain, their connectivity, and their ability to reorganize.

scholarly journals Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Arian Ashourvan ◽  
Preya Shah ◽  
Adam Pines ◽  
Shi Gu ◽  
Christopher W. Lynn ◽  
...  
Keyword(s):  
White Matter ◽  
Maximum Entropy ◽  
Large Scale ◽  
Structural Connectivity ◽  
Quantitative Relationship ◽  
Brain Regions ◽  
Maximum Entropy Model ◽  
Entropy Model ◽  
Activation Patterns ◽  
Co Activation

AbstractA major challenge in neuroscience is determining a quantitative relationship between the brain’s white matter structural connectivity and emergent activity. We seek to uncover the intrinsic relationship among brain regions fundamental to their functional activity by constructing a pairwise maximum entropy model (MEM) of the inter-ictal activation patterns of five patients with medically refractory epilepsy over an average of ~14 hours of band-passed intracranial EEG (iEEG) recordings per patient. We find that the pairwise MEM accurately predicts iEEG electrodes’ activation patterns’ probability and their pairwise correlations. We demonstrate that the estimated pairwise MEM’s interaction weights predict structural connectivity and its strength over several frequencies significantly beyond what is expected based solely on sampled regions’ distance in most patients. Together, the pairwise MEM offers a framework for explaining iEEG functional connectivity and provides insight into how the brain’s structural connectome gives rise to large-scale activation patterns by promoting co-activation between connected structures.

Abstract WP205: Pipeline for Automated White Matter Hyperintensity Segmentation in Patients With Acute Ischemic Stroke: The MRI-GENIE Study

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Markus D Schirmer ◽  
Adrian V Dalca ◽  
Ramesh Sridharan ◽  
Anne-Katrin Giese ◽  
Joseph P Broderick ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
White Matter ◽  
Acute Ischemic Stroke ◽  
Large Scale ◽  
Current Knowledge ◽  
Principal Component ◽  
White Matter Hyperintensity ◽  
Brain Extraction ◽  
Fluid Attenuated Inversion Recovery ◽  
Good Agreement

Introduction: White matter hyperintensity volume (WMHv) is an important and highly heritable cerebrovascular phenotype; however, manual or semi-automated approaches to clinically acquired MRI analysis hinder large-scale studies in acute ischemic stroke (AIS). In this work, we develop a high-throughput, fully automated WMHv analysis pipeline for clinical fluid-attenuated inversion recovery (FLAIR) images to facilitate rapid genetic discovery in AIS. Methods: Automated WMHv extraction from multiple subjects relies on significant pre-processing of medical scans, including co-registration of the images. To reduce the effects of anisotropic voxel sizes, each FLAIR image is upsampled using bi-cubic interpolation. Brain extraction is performed using RObust Brain EXtraction (ROBEX). Images are then registered to an in-house FLAIR template using Advanced Normalization Tools (ANTs). The spatial covariation of WMH is learned through principal component analysis (PCA) of manual outlines from 100 subjects. Areas of leukoaraiosis are identified and separated from other lesions using the PCA modes. Volumes are then computed using non-interpolated slices for each subject. Standard deviation (SD) in WMHv (9 subjects; 6 raters each) is calculated as a measure of variability. Good agreement between automated and manual outlines is assessed in 358 subjects (automated WMHv within 3SD of manual WMHv). Results: As part of the MRI - Gen etics I nterface E xploration (MRI-GENIE) study, WMHv were calculated on a set of 2703 FLAIR images of patients from 12 independent AIS cohorts (sites). Results are shown in Figure 1. Comparing manual and automated WMHv shows that 88% of the automated WMHv fall within 3 SD from the manual WMHv, suggesting good agreement. Conclusion: WMHv segmentation using a fully-automated pipeline for analysis of clinical MRIs is both feasible and accurate. Ongoing analysis of the extracted WMHv is expected to advance current knowledge of risks and outcomes in AIS.

scholarly journals Activity-dependent myelination: A glial mechanism of oscillatory self-organization in large-scale brain networks

2020 ◽  
Vol 117 (24) ◽  
pp. 13227-13237 ◽  
Author(s):  
Rabiya Noori ◽  
Daniel Park ◽  
John D. Griffiths ◽  
Sonya Bells ◽  
Paul W. Frankland ◽  
...  
Keyword(s):  
White Matter ◽  
Large Scale ◽  
Phase Synchronization ◽  
Brain Networks ◽  
Self Organization ◽  
Conduction Delay ◽  
Neural Communication ◽  
Wide Range ◽  
The Impact ◽  
Activity Dependent

Communication and oscillatory synchrony between distributed neural populations are believed to play a key role in multiple cognitive and neural functions. These interactions are mediated by long-range myelinated axonal fiber bundles, collectively termed as white matter. While traditionally considered to be static after development, white matter properties have been shown to change in an activity-dependent way through learning and behavior—a phenomenon known as white matter plasticity. In the central nervous system, this plasticity stems from oligodendroglia, which form myelin sheaths to regulate the conduction of nerve impulses across the brain, hence critically impacting neural communication. We here shift the focus from neural to glial contribution to brain synchronization and examine the impact of adaptive, activity-dependent changes in conduction velocity on the large-scale phase synchronization of neural oscillators. Using a network model based on primate large-scale white matter neuroanatomy, our computational and mathematical results show that such plasticity endows white matter with self-organizing properties, where conduction delay statistics are autonomously adjusted to ensure efficient neural communication. Our analysis shows that this mechanism stabilizes oscillatory neural activity across a wide range of connectivity gain and frequency bands, making phase-locked states more resilient to damage as reflected by diffuse decreases in connectivity. Critically, our work suggests that adaptive myelination may be a mechanism that enables brain networks with a means of temporal self-organization, resilience, and homeostasis.

scholarly journals Large-Scale Evidence for an Association Between Peripheral Inflammation and White Matter Free Water in Schizophrenia and Healthy Individuals

2020 ◽  
Author(s):  
Maria A Di Biase ◽  
Andrew Zalesky ◽  
Suheyla Cetin-Karayumak ◽  
Yogesh Rathi ◽  
Jinglei Lv ◽  
...  
Keyword(s):  
White Matter ◽  
Large Scale ◽  
Interleukin 2 ◽  
Free Water ◽  
Markers Of Inflammation ◽  
Brain White Matter ◽  
Inflammatory Processes ◽  
Weighted Magnetic Resonance Imaging

Abstract Introduction Clarifying the role of neuroinflammation in schizophrenia is subject to its detection in the living brain. Free-water (FW) imaging is an in vivo diffusion-weighted magnetic resonance imaging (dMRI) technique that measures water molecules freely diffusing in the brain and is hypothesized to detect inflammatory processes. Here, we aimed to establish a link between peripheral markers of inflammation and FW in brain white matter. Methods All data were obtained from the Australian Schizophrenia Research Bank (ASRB) across 5 Australian states and territories. We first tested for the presence of peripheral cytokine deregulation in schizophrenia, using a large sample (N = 1143) comprising the ASRB. We next determined the extent to which individual variation in 8 circulating pro-/anti-inflammatory cytokines related to FW in brain white matter, imaged in a subset (n = 308) of patients and controls. Results Patients with schizophrenia showed reduced interleukin-2 (IL-2) (t = −3.56, P = .0004) and IL-12(p70) (t = −2.84, P = .005) and increased IL-6 (t = 3.56, P = .0004), IL-8 (t = 3.8, P = .0002), and TNFα (t = 4.30, P < .0001). Higher proinflammatory signaling of IL-6 (t = 3.4, P = .0007) and TNFα (t = 2.7, P = .0007) was associated with higher FW levels in white matter. The reciprocal increases in serum cytokines and FW were spatially widespread in patients encompassing most major fibers; conversely, in controls, the relationship was confined to the anterior corpus callosum and thalamic radiations. No relationships were observed with alternative dMRI measures, including the fractional anisotropy and tissue-related FA. Conclusions We report widespread deregulation of cytokines in schizophrenia and identify inflammation as a putative mechanism underlying increases in brain FW levels.

scholarly journals Microstructural damage of white-matter tracts connecting large-scale networks is related to impaired executive profile in alcohol use disorder

2020 ◽  
Vol 25 ◽  
pp. 102141 ◽  
Author(s):  
Chiara Crespi ◽  
Caterina Galandra ◽  
Nicola Canessa ◽  
Marina Manera ◽  
Paolo Poggi ◽  
...  
Keyword(s):  
White Matter ◽  
Alcohol Use ◽  
Alcohol Use Disorder ◽  
Large Scale ◽  
White Matter Tracts ◽  
Microstructural Damage ◽  
Large Scale Networks

scholarly journals Cloze testing for comprehension assessment: The HyTeC-cloze

2019 ◽  
Vol 36 (4) ◽  
pp. 553-572 ◽  
Author(s):  
Suzanne Kleijn ◽  
Henk Pander Maat ◽  
Ted Sanders
Keyword(s):  
Secondary School ◽  
Standardized Tests ◽  
Reading Ability ◽  
Text Comprehension ◽  
Large Scale ◽  
Secondary School Students ◽  
Reliability And Validity ◽  
School Students ◽  
Cloze Procedure ◽  
Testing Center

Although there are many methods available for assessing text comprehension, the cloze test is not widely acknowledged as one of them. Critiques on cloze testing center on its supposedly limited ability to measure comprehension beyond the sentence. However, these critiques do not hold for all types of cloze tests; the particular configuration of a cloze determines its validity. We review various cloze configurations and discuss their strengths and weaknesses. We propose a new cloze procedure specifically designed to gauge text comprehension: the Hybrid Text Comprehension cloze (HyTeC-cloze). It employs a hybrid mechanical-rational deletion strategy and semantic scoring of answers. The procedure was tested in a large-scale study, involving 2926 Dutch secondary school students with 120 unique cloze tests. Our results show that, in terms of reliability and validity, the HyTeC-cloze matches and sometimes outperforms standardized tests of reading ability.

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