White matter microstructure throughout the brain correlates with visual imagery in grapheme–color synesthesia

NeuroImage ◽  
2014 ◽  
Vol 90 ◽  
pp. 52-59 ◽  
Author(s):  
Kirstie J. Whitaker ◽  
Xiaojian Kang ◽  
Timothy J. Herron ◽  
David L. Woods ◽  
Lynn C. Robertson ◽  
...  
Keyword(s):  
White Matter ◽  
Visual Imagery ◽  
White Matter Microstructure ◽  
Brain Correlates ◽  
The Brain

scholarly journals Development of white matter microstructure and executive functions during childhood and adolescence: a review of diffusion MRI studies

2020 ◽  
Author(s):  
Anne-Lise Goddings ◽  
David Roalf ◽  
Catherine Lebel ◽  
Christian K. Tamnes
Keyword(s):  
White Matter ◽  
Executive Functions ◽  
Structural Connectivity ◽  
Child And Adolescent ◽  
Childhood And Adolescence ◽  
Cross Sectional ◽  
Indirect Measures ◽  
White Matter Microstructure ◽  
P Diffusion ◽  
The Brain

Diffusion magnetic resonance imaging (dMRI) provides indirect measures of white matter microstructure that can be used to make inferences about structural connectivity within the brain. Over the last decade, a growing literature of cross-sectional and longitudinal studies have documented relationships between dMRI indices and cognitive development. In this review, we provide a brief overview of dMRI methods and how they can be used to study white matter and connectivity, briefly discuss challenges with using dMRI in child and adolescent populations, and review the extant literature examining the links between dMRI indices and executive functions during development. We explore the links between white matter microstructure and specific executive functions: inhibition, working memory and cognitive shifting, as well as performance on complex executive function tasks. Where there is concordance in findings across studies, this is highlighted, and potential explanations for discrepancies between results are discussed. Finally, we explore future directions that are necessary to better understand the links between child and adolescent development of executive functions and structural connectivity of the brain.

scholarly journals White matter alterations in glaucoma and monocular blindness differ outside the visual system

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sandra Hanekamp ◽  
Branislava Ćurčić-Blake ◽  
Bradley Caron ◽  
Brent McPherson ◽  
Anneleen Timmer ◽  
...  
Keyword(s):  
Motor Control ◽  
White Matter ◽  
Visual System ◽  
Visual Loss ◽  
Indirect Evidence ◽  
Sensory Inputs ◽  
White Matter Microstructure ◽  
Early Visual System ◽  
Patient Groups ◽  
The Brain

AbstractThe degree to which glaucoma has effects in the brain beyond the eye and the visual pathways is unclear. To clarify this, we investigated white matter microstructure (WMM) in 37 tracts of patients with glaucoma, monocular blindness, and controls. We used brainlife.io for reproducibility. White matter tracts were subdivided into seven categories ranging from those primarily involved in vision (the visual white matter) to those primarily involved in cognition and motor control. In the vision tracts, WMM was decreased as measured by fractional anisotropy in both glaucoma and monocular blind subjects compared to controls, suggesting neurodegeneration due to reduced sensory inputs. A test–retest approach was used to validate these results. The pattern of results was different in monocular blind subjects, where WMM properties increased outside the visual white matter as compared to controls. This pattern of results suggests that whereas in the monocular blind loss of visual input might promote white matter reorganization outside of the early visual system, such reorganization might be reduced or absent in glaucoma. The results provide indirect evidence that in glaucoma unknown factors might limit the reorganization as seen in other patient groups following visual loss.

scholarly journals Brain structural correlates of autistic traits across the diagnostic divide: A grey matter and white matter microstructure study

2021 ◽  
Author(s):  
Varun Arunachalam Chandran ◽  
Christos Pliatsikas ◽  
Janina Neufeld ◽  
Garret O'Connell ◽  
Anthony Haffey ◽  
...  
Keyword(s):  
White Matter ◽  
Grey Matter ◽  
Diffusion Tensor ◽  
Autistic Traits ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Brain Volumes ◽  
White Matter Microstructure ◽  
The Social ◽  
Brain Correlates

Autism Spectrum Disorders (ASD) are a set of neurodevelopmental conditions characterised by difficulties in social interaction and communication as well as stereotyped and restricted patterns of interest. Autistic traits exist in a continuum across the general population, whilst the extreme end of this distribution is diagnosed as clinical ASD. While many studies have investigated brain structure in autism using a case-control design, few have used a dimensional approach. To add to this growing body of literature, we investigated the structural brain correlates of autistic traits in a mixed sample of adults (N=91) with and without a clinical diagnosis of autism. We examined regional brain volumes (using voxel-based morphometry and surface-based morphometry) and white matter microstructure properties (using Diffusion Tensor Imaging). Our findings show widespread grey matter differences, including in the social brain regions, and some evidence for white matter microstructure differences related to higher autistic traits. These grey matter and white matter microstructure findings from our study are consistent with previous reports and support the brain structural differences in ASD. These findings provide further support for shared aetiology for autistic traits across the diagnostic divide.

Brain Correlates of Numerical Disabilities

2014 ◽  
Author(s):  
Karin Kucian ◽  
Liane Kaufmann ◽  
Michael von Aster
Keyword(s):  
Learning Disabilities ◽  
White Matter ◽  
Brain Imaging ◽  
Imaging Findings ◽  
Parietal Lobes ◽  
Critical Issues ◽  
First Results ◽  
Brain Correlates ◽  
Typically Achieving ◽  
The Brain

What are the brain correlates of numerical disabilities? To date only few studies have examined the neuronal underpinnings of specific numerical learning disabilities like developmental dyscalculia (DD). However, first results provide important insights if and where brains of children diagnosed with DD differ from those of typically achieving peers. Main deficits are apparent in core regions for number processing, which mainly comprise gray, as well as white matter in parietal lobes. Moreover, it already can be demonstrated that brain activation in DD is changing according to learning and intervention. The present chapter will bring together existing puzzle pieces of brain imaging findings in DD, as well as highlight some critical issues that have to be considered when comparing studies including children with DD.

scholarly journals White matter alterations in glaucoma and vision-deprived brains differ outside the visual system

2020 ◽  
Author(s):  
Sandra Hanekamp ◽  
Branislava Ćurčić-Blake ◽  
Bradley Caron ◽  
Brent McPherson ◽  
Anneleen Timmer ◽  
...  
Keyword(s):  
White Matter ◽  
Visual System ◽  
Brain Plasticity ◽  
Indirect Evidence ◽  
Sensory Inputs ◽  
Computing Platform ◽  
White Matter Microstructure ◽  
Patient Groups ◽  
Cloud Computing Platform ◽  
The Brain

AbstractThe degree to which glaucoma has effects beyond the eye –in the brain– is unclear. We investigated white matter microstructure (WMM) alterations in 37 tracts of patients with glaucoma, monocular blindness and controls. We used reproducible methods and the advanced cloud computing platform brainlife.io. White matter tracts were subdivided into seven categories ranging from primarily involved in vision (the visual white matter) to primarily involved in cognition and motor control. WMM in both glaucoma and monocular blind subjects was lower than controls in the visual white matter, suggesting neurodegenerative mechanisms due to reduced sensory inputs. In glaucoma participants WMM differences from controls decreased outside the visual white matter. A test-retest validation approach was used to validate these results. The pattern of results was different in monocular blind participants, where WMM properties increased outside the visual white matter as compared to controls. The pattern of results suggests that whereas in the blind loss of visual input might promote white matter reorganization outside of the early visual system, such reorganization might be reduced or absent in glaucoma. The results provide indirect evidence that in glaucoma unknown factors might limit the brain plasticity effects that in other patient groups follow visual loss.

Development of Reading Remediation for Dyslexic Individuals

2016 ◽  
Vol 224 (4) ◽  
pp. 240-246 ◽  
Author(s):  
Mélanie Bédard ◽  
Line Laplante ◽  
Julien Mercier
Keyword(s):  
20Th Century ◽  
Scientific Literature ◽  
Behavioral Data ◽  
Educational Neuroscience ◽  
Reading Remediation ◽  
Functional Brain ◽  
Neurophysiological Data ◽  
Brain Correlates ◽  
Research Questions ◽  
The Brain

Abstract. Dyslexia is a phenomenon for which the brain correlates have been studied since the beginning of the 20th century. Simultaneously, the field of education has also been studying dyslexia and its remediation, mainly through behavioral data. The last two decades have seen a growing interest in integrating neuroscience and education. This article provides a quick overview of pertinent scientific literature involving neurophysiological data on functional brain differences in dyslexia and discusses their very limited influence on the development of reading remediation for dyslexic individuals. Nevertheless, it appears that if certain conditions are met – related to the key elements of educational neuroscience and to the nature of the research questions – conceivable benefits can be expected from the integration of neurophysiological data with educational research. When neurophysiological data can be employed to overcome the limits of using behavioral data alone, researchers can both unravel phenomenon otherwise impossible to document and raise new questions.

Characterization of Ischemic Stroke in CT Images using Image Processing

2017 ◽  
Vol 7 (9) ◽  
pp. 18
Author(s):  
Amal Alzain ◽  
Suhaib Alameen ◽  
Rani Elmaki ◽  
Mohamed E. M. Gar-Elnabi
Keyword(s):  
Ischemic Stroke ◽  
White Matter ◽  
Classification Accuracy ◽  
Ct Images ◽  
Gray Level ◽  
Level Variation ◽  
Interactive Data ◽  
The Brain ◽  
Brain Tissues

This study concern to characterize the brain tissues to ischemic stroke, gray matter, white matter and CSF using texture analysisto extract classification features from CT images. The First Order Statistic techniques included sevenfeatures. To find the gray level variation in CT images it complements the FOS features extracted from CT images withgray level in pixels and estimate the variation of thesubpatterns. analyzing the image with Interactive Data Language IDL software to measure the grey level of images. The results show that the Gray Level variation and   features give classification accuracy of ischemic stroke 97.6%, gray matter95.2%, white matter 97.3% and the CSF classification accuracy 98.0%. The overall classification accuracy of brain tissues 97.0%.These relationships are stored in a Texture Dictionary that can be later used to automatically annotate new CT images with the appropriate brain tissues names.

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