scholarly journals The spatial correspondence and genetic influence of inter-hemispheric connectivity with white matter microstructure

2018 ◽  
Author(s):  
Jeroen Mollink ◽  
Stephen M. Smith ◽  
Lloyd T. Elliott ◽  
Michiel Kleinnijenhuis ◽  
Marlies Hiemstra ◽  
...  
Keyword(s):  
White Matter ◽  
Functional Connectivity ◽  
Neural Development ◽  
Neural Circuit ◽  
Brain Regions ◽  
Nucleotide Polymorphisms ◽  
Imaging Data ◽  
Single Nucleotide ◽  
White Matter Microstructure ◽  
Microscopic Features

AbstractMicroscopic features (i.e., microstructure) of axons affect neural circuit activity through characteristics such as conduction speed. Deeper understanding of structure-function relationships and translating this into human neuroscience has been limited by the paucity of studies relating axonal microstructure in white matter pathways to functional connectivity (synchrony) between macroscopic brain regions. Using magnetic resonance imaging data in 11354 subjects, we constructed multi-variate models that predict the functional connectivity of pairs of brain regions from the microstructural signature of white matter pathways that connect them. Microstructure-derived models provide predictions of functional connectivity that were significant in up to 86% of the brain region pairs considered. These relationships are specific to the relevant white matter pathway and have high reproducibility. The microstructure-function relationships are associated to genetic variants (single-nucleotide polymorphisms), co-located with genes DAAM1 and LPAR1, that have previously been reported to play a role in neural development. Our results demonstrate that variation in white matter microstructure across individuals consistently and specifically predicts functional connectivity, and that this relationship is underpinned by genetic variability.

scholarly journals Topological Segmentation of Time-Varying Functional Connectivity Highlights the Role of Preferred Cortical Circuits

2020 ◽  
Author(s):  
Jacob Billings ◽  
Manish Saggar ◽  
Shella Keilholz ◽  
Giovanni Petri
Keyword(s):  
Functional Connectivity ◽  
Brain Function ◽  
Persistent Homology ◽  
Brain Regions ◽  
Topological Data Analysis ◽  
Time Varying ◽  
Imaging Data ◽  
Experimental Conditions ◽  
Common Time ◽  
Brain Imaging Data

Functional connectivity (FC) and its time-varying analogue (TVFC) leverage brain imaging data to interpret brain function as patterns of coordinating activity among brain regions. While many questions remain regarding the organizing principles through which brain function emerges from multi-regional interactions, advances in the mathematics of Topological Data Analysis (TDA) may provide new insights into the brain’s spontaneous self-organization. One tool from TDA, “persistent homology”, observes the occurrence and the persistence of n-dimensional holes presented in the metric space over a dataset. The occurrence of n-dimensional holes within the TVFC point cloud may denote conserved and preferred routes of information flow among brain regions. In the present study, we compare the use of persistence homology versus more traditional TVFC metrics at the task of segmenting brain states that differ across a common time-series of experimental conditions. We find that the structures identified by persistence homology more accurately segment the stimuli, more accurately segment volunteer performance during experimentally defined tasks, and generalize better across volunteers. Finally, we present empirical and theoretical observations that interpret brain function as a topological space defined by cyclic and interlinked motifs among distributed brain regions, especially, the attention networks.

scholarly journals White Matter Development from Birth to 6 Years of Age: A Longitudinal Study

2020 ◽  
Vol 30 (12) ◽  
pp. 6152-6168
Author(s):  
Rebecca L Stephens ◽  
Benjamin W Langworthy ◽  
Sarah J Short ◽  
Jessica B Girault ◽  
Martin A Styner ◽  
...  
Keyword(s):  
Individual Differences ◽  
White Matter ◽  
Diffusion Tensor ◽  
First Year ◽  
Imaging Data ◽  
White Matter Microstructure ◽  
White Matter Development ◽  
Psychiatric Outcomes ◽  
First Year Of Life ◽  
Diffusion Tensor Imaging Data

Abstract Human white matter development in the first years of life is rapid, setting the foundation for later development. Microstructural properties of white matter are linked to many behavioral and psychiatric outcomes; however, little is known about when in development individual differences in white matter microstructure are established. The aim of the current study is to characterize longitudinal development of white matter microstructure from birth through 6 years to determine when in development individual differences are established. Two hundred and twenty-four children underwent diffusion-weighted imaging after birth and at 1, 2, 4, and 6 years. Diffusion tensor imaging data were computed for 20 white matter tracts (9 left–right corresponding tracts and 2 commissural tracts), with tract-based measures of fractional anisotropy and axial and radial diffusivity. Microstructural maturation between birth and 1 year are much greater than subsequent changes. Further, by 1 year, individual differences in tract average values are consistently predictive of the respective 6-year values, explaining, on average, 40% of the variance in 6-year microstructure. Results provide further evidence of the importance of the first year of life with regard to white matter development, with potential implications for informing early intervention efforts that target specific sensitive periods.

scholarly journals Individual Differences in White-Matter Microstructure Reflect Variation in Functional Connectivity during Choice

2007 ◽  
Vol 17 (16) ◽  
pp. 1426-1431 ◽  
Author(s):  
Erie Dell Boorman ◽  
Jacinta O'Shea ◽  
Catherine Sebastian ◽  
Matthew F.S. Rushworth ◽  
Heidi Johansen-Berg
Keyword(s):  
Individual Differences ◽  
White Matter ◽  
Functional Connectivity ◽  
White Matter Microstructure

scholarly journals Cerebral White Matter Sex Dimorphism in Alcoholism: A Diffusion Tensor Imaging Study

2017 ◽  
Author(s):  
Kayle S. Sawyer ◽  
Nasim Maleki ◽  
George Papadimitriou ◽  
Nikos Makris ◽  
Marlene Oscar-Berman ◽  
...  
Keyword(s):  
Sex Differences ◽  
White Matter ◽  
Corpus Callosum ◽  
Diffusion Tensor ◽  
Imaging Study ◽  
Brain Regions ◽  
Cerebral White Matter ◽  
Excessive Alcohol Consumption ◽  
White Matter Microstructure ◽  
White Matter Connectivity

AbstractBackgroundExcessive alcohol consumption is associated with widespread brain damage, including abnormalities in frontal and limbic brain regions. In a prior study of neuronal circuitry connecting the frontal lobes and limbic system structures in abstinent alcoholic men, we demonstrated decreases in white matter fractional anisotropy (FA) on diffusion tensor magnetic resonance imaging (dMRI). In the present study, we examined sex differences in alcoholism-related abnormalities of white matter connectivity.MethodsdMRI scans were acquired from 49 abstinent alcoholic individuals (26 women) and 41 nonalcoholic controls (22 women). Tract-based spatial statistical tools were used to estimate regional FA of white matter tracts and to determine sex differences and their relation to measures of alcoholism history.ResultsSex-related differences in white matter connectivity were observed in association with alcoholism: Compared to nonalcoholic men, alcoholic men had diminished FA in portions of the corpus callosum, the superior longitudinal fasciculi II and III, and the arcuate fasciculus and extreme capsule. In contrast, alcoholic women had higher FA in these regions. Sex differences also were observed for correlations between corpus callosum FA and length of sobriety.ConclusionsSexual dimorphism in white matter microstructure in abstinent alcoholics may implicate underlying differences in the neurobehavioral liabilities for developing alcohol abuse disorders, or for sequelae following abuse.

scholarly journals Sex-dependent and sex-independent brain resting-state functional connectivity in children with autism spectrum disorder

2016 ◽  
Author(s):  
Xin Di ◽  
Bharat B Biswal
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Resting State ◽  
Data Exchange ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Imaging Data ◽  
Resting State Functional Connectivity ◽  
Main Effects

Background: Males are more likely to suffer from autism spectrum disorder (ASD) than females. As to whether females with ASD have similar brain alterations remain an open question. The current study aimed to examine sex-dependent as well as sex-independent alterations in resting-state functional connectivity in individuals with ASD compared with typically developing (TD) individuals. Method: Resting-state functional MRI data were acquired from the Autism Brain Imaging Data Exchange (ABIDE). Subjects between 6 to 20 years of age were included for analysis. After matching the intelligence quotient between groups for each dataset, and removing subjects due to excessive head motion, the resulting effective sample contained 28 females with ASD, 49 TD females, 129 males with ASD, and 141 TD males, with a two (diagnosis) by two (sex) design. Functional connectivity among 153 regions of interest (ROIs) comprising the whole brain was computed. Two by two analysis of variance was used to identify connectivity that showed diagnosis by sex interaction or main effects of diagnosis. Results: The main effects of diagnosis were found mainly between visual cortex and other brain regions, indicating sex-independent connectivity alterations. We also observed two connections whose connectivity showed diagnosis by sex interaction between the precuneus and medial cerebellum as well as the precunes and dorsal frontal cortex. While males with ASD showed higher connectivity in these connections compared with TD males, females with ASD had lower connectivity than their counterparts. Conclusions: Both sex-dependent and sex-independent functional connectivity alterations are present in ASD.

scholarly journals An Autism Spectrum Disorder Adaptive Identification Based on the Elimination of Brain Connections: A Proof of Long-Range Underconnectivity

2021 ◽  
Author(s):  
Fatima zahra Benabdallah ◽  
Ahmed Drissi El Maliani ◽  
Dounia Lotfi ◽  
Rachid Jennane ◽  
Mohammed El hassouni
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Long Range ◽  
Data Exchange ◽  
Brain Connectivity ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Imaging Data ◽  
Brain Imaging Data

Abstract Autism spectrum disorder (ASD) is theoretically characterized by alterations in functional connectivity between brain regions. Many works presented approaches to determine informative patterns that help to predict autism from typical development. However, most of the proposed pipelines are not specifically designed for the autism problem, i.e they do not corroborate with autism theories about functional connectivity. In this paper, we propose a framework that takes into account the properties of local connectivity and long range under-connectivity in the autistic brain. The originality of the proposed approach is to adopt elimination as a technique in order to well emerge the autistic brain connectivity alterations, and show how they contribute to differentiate ASD from controls. Experimental results conducted on the large multi-site Autism Brain Imaging Data Exchange (ABIDE) show that our approach provides accurate prediction up to 70% and succeeds to prove the existence of deficits in the long-range connectivity in the ASD subjects brains.

scholarly journals The relationship between spatial configuration and functional connectivity of brain regions

2017 ◽  
Author(s):  
Janine D. Bijsterbosch ◽  
Mark W. Woolrich ◽  
Matthew F. Glasser ◽  
Emma C. Robinson ◽  
Christian F. Beckmann ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Spatial Configuration ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Spatial Arrangement ◽  
Brain Regions ◽  
Imaging Data ◽  
Functional Regions ◽  
Cortical Regions ◽  
The Relationship

AbstractBrain connectivity is often considered in terms of the communication between functionally distinct brain regions. Many studies have investigated the extent to which patterns of coupling strength between multiple neural populations relates to behavior. For example, studies have used "functional connectivity fingerprints" to characterise individuals' brain activity. Here, we investigate the extent to which the exact spatial arrangement of cortical regions interacts with measures of brain connectivity. We find that the shape and exact location of brain regions interact strongly with the modelling of brain connectivity, and present evidence that the spatial arrangement of functional regions is strongly predictive of non-imaging measures of behaviour and lifestyle. We believe that, in many cases, cross-subject variations in the spatial configuration of functional brain regions are being interpreted as changes in functional connectivity. Therefore, a better understanding of these effects is important when interpreting the relationship between functional imaging data and cognitive traits.

scholarly journals Using structural connectivity to augment community structure in EEG functional connectivity

2020 ◽  
Vol 4 (3) ◽  
pp. 761-787 ◽  
Author(s):  
Katharina Glomb ◽  
Emeline Mullier ◽  
Margherita Carboni ◽  
Maria Rubega ◽  
Giannarita Iannotti ◽  
...  
Keyword(s):  
Community Structure ◽  
White Matter ◽  
Functional Connectivity ◽  
Large Scale ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Source Analysis ◽  
Volume Conduction ◽  
Functional Relationships ◽  
The Impact

Recently, EEG recording techniques and source analysis have improved, making it feasible to tap into fast network dynamics. Yet, analyzing whole-cortex EEG signals in source space is not standard, partly because EEG suffers from volume conduction: Functional connectivity (FC) reflecting genuine functional relationships is impossible to disentangle from spurious FC introduced by volume conduction. Here, we investigate the relationship between white matter structural connectivity (SC) and large-scale network structure encoded in EEG-FC. We start by confirming that FC (power envelope correlations) is predicted by SC beyond the impact of Euclidean distance, in line with the assumption that SC mediates genuine FC. We then use information from white matter structural connectivity in order to smooth the EEG signal in the space spanned by graphs derived from SC. Thereby, FC between nearby, structurally connected brain regions increases while FC between nonconnected regions remains unchanged, resulting in an increase in genuine, SC-mediated FC. We analyze the induced changes in FC, assessing the resemblance between EEG-FC and volume-conduction- free fMRI-FC, and find that smoothing increases resemblance in terms of overall correlation and community structure. This result suggests that our method boosts genuine FC, an outcome that is of interest for many EEG network neuroscience questions.

Common genetic variation influencing human white matter microstructure

Science ◽  
2021 ◽  
Vol 372 (6548) ◽  
pp. eabf3736
Author(s):  
Bingxin Zhao ◽  
Tengfei Li ◽  
Yue Yang ◽  
Xifeng Wang ◽  
Tianyou Luo ◽  
...  
Keyword(s):  
White Matter ◽  
Complex Traits ◽  
Large Scale ◽  
Wide Spectrum ◽  
Genetic Correlations ◽  
Regulatory Elements ◽  
Brain Regions ◽  
Brain Diseases ◽  
White Matter Microstructure ◽  
Common Genetic Variants

Brain regions communicate with each other through tracts of myelinated axons, commonly referred to as white matter. We identified common genetic variants influencing white matter microstructure using diffusion magnetic resonance imaging of 43,802 individuals. Genome-wide association analysis identified 109 associated loci, 30 of which were detected by tract-specific functional principal components analysis. A number of loci colocalized with brain diseases, such as glioma and stroke. Genetic correlations were observed between white matter microstructure and 57 complex traits and diseases. Common variants associated with white matter microstructure altered the function of regulatory elements in glial cells, particularly oligodendrocytes. This large-scale tract-specific study advances the understanding of the genetic architecture of white matter and its genetic links to a wide spectrum of clinical outcomes.

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