Properties Of White Matter Tracts Research Articles

Intrahemispheric White Matter Asymmetries and Interhemispheric Connections Underlying the Lateralization of Language Production and Spatial Attention in Left-Handers

ABSTRACT Leftward language production and rightward spatial attention are salient features of functional organization in most humans, but their anatomical basis remains unclear. Interhemispheric connections and intrahemispheric white matter asymmetries have been proposed as important factors underlying functional lateralization. To investigate the role of white matter connectivity in functional lateralization, we first identified 96 left-handers using visual half field naming tasks. They were then divided into atypical and typical functional dominance based on the lateralization of brain activation in a word generation task (for language production) and a landmark task (for spatial attention). Using a novel fixel-based framework, we obtained fiber-specific properties of white matter pathways. Results showed, first, that differences between two language dominance groups occurred in the asymmetry of the superior longitudinal fasciculus-III (SLF-III), whereas differences between two spatial attention dominance groups occurred in the rostrum and rostral body of the corpus callosum. However, the directions of functional lateralization were not associated with the directions of white matter asymmetries. Second, the degree of language lateralization was predicted by SLF-III asymmetry and the rostral body of the corpus callosum, whereas the degree of spatial attention lateralization was predicted by the rostrum of the corpus callosum. Notably, the degree of each functional lateralization was positively correlated with the anterior and middle callosal connections, supporting the excitatory model of the corpus callosum. The results suggest that language lateralization is shaped by a combined effect of intra- and interhemispheric connections, whereas spatial attention lateralization relies more on interhemispheric connections.

Amyloid, Tau, and APOE in Alzheimer's Disease: Impact on White Matter Tracts.

Alzheimer's disease (AD) is characterized by cognitive decline and memory loss due to the abnormal accumulation of amyloid-beta (Aβ) plaques and tau tangles in the brain; its onset and progression also depend on genetic factors such as the apolipoprotein E (APOE) genotype. Understanding how these factors affect the brain's neural pathways is important for early diagnostics and interventions. Tractometry is an advanced technique for 3D quantitative assessment of white matter tracts, localizing microstructural abnormalities in diseased populations in vivo. In this work, we applied BUAN (Bundle Analytics) tractometry to 3D diffusion MRI data from 730 participants in ADNI3 (phase 3 of the Alzheimer's Disease Neuroimaging Initiative; age range: 55-95 years, 349M/381F, 214 with mild cognitive impairment, 69 with AD, and 447 cognitively healthy controls). Using along-tract statistical analysis, we assessed the localized impact of amyloid, tau, and APOE genetic variants on the brain's neural pathways. BUAN quantifies microstructural properties of white matter tracts, supporting along-tract statistical analyses that identify factors associated with brain microstructure. We visualize the 3D profile of white matter tract associations with tau and amyloid burden in Alzheimer's disease; strong associations near the cortex may support models of disease propagation along neural pathways. Relative to the neutral genotype, APOE ϵ3/ϵ3, carriers of the AD-risk conferring APOE ϵ4 genotype show microstructural abnormalities, while carriers of the protective ϵ2 genotype also show subtle differences. Of all the microstructural metrics, mean diffusivity (MD) generally shows the strongest associations with AD pathology, followed by axial diffusivity (AxD) and radial diffusivity (RD), while fractional anisotropy (FA) is typically the least sensitive metric. Along-tract microstructural metrics are sensitive to tau and amyloid accumulation, showing the potential of diffusion MRI to track AD pathology and map its impact on neural pathways.

Evaluation of simultaneous multi-slice readout-segmented diffusion-weighted MRI acquisition in human optic nerve measurements

Diffusion-weighted magnetic resonance imaging (dMRI) is the only available method to measure the tissue properties of white matter tracts in living human brains and has opened avenues for neuroscientific and clinical studies on human white matter. However, dMRI using conventional simultaneous multi-slice (SMS) single-shot echo planar imaging (ssEPI) still presents challenges in the analyses of some specific white matter tracts, such as the optic nerve, which are heavily affected by susceptibility-induced artifacts. In this study, we evaluated dMRI data acquired by using SMS readout-segmented EPI (rsEPI), which aims to reduce susceptibility-induced artifacts by dividing the acquisition space into multiple segments along the readout direction to reduce echo spacing. To this end, we acquired dMRI data from 11 healthy volunteers by using SMS ssEPI and SMS rsEPI, and then compared the dMRI data of the human optic nerve between the SMS ssEPI and SMS rsEPI datasets by visual inspection of the datasets and statistical comparisons of fractional anisotropy (FA) values. In comparison with the SMS ssEPI data, the SMS rsEPI data showed smaller susceptibility-induced distortion and exhibited a significantly higher FA along the optic nerve. In summary, this study demonstrates that despite its prolonged acquisition time, SMS rsEPI is a promising approach for measuring the tissue properties of the optic nerve in living humans and will be useful for future neuroscientific and clinical investigations of this pathway.

Topography of associations between cardiovascular risk factors and myelin loss in the ageing human brain

Our knowledge of the mechanisms underlying the vulnerability of the brain’s white matter microstructure to cardiovascular risk factors (CVRFs) is still limited. We used a quantitative magnetic resonance imaging (MRI) protocol in a single centre setting to investigate the cross-sectional association between CVRFs and brain tissue properties of white matter tracts in a large community-dwelling cohort (n = 1104, age range 46–87 years). Arterial hypertension was associated with lower myelin and axonal density MRI indices, paralleled by higher extracellular water content. Obesity showed similar associations, though with myelin difference only in male participants. Associations between CVRFs and white matter microstructure were observed predominantly in limbic and prefrontal tracts. Additional genetic, lifestyle and psychiatric factors did not modulate these results, but moderate-to-vigorous physical activity was linked to higher myelin content independently of CVRFs. Our findings complement previously described CVRF-related changes in brain water diffusion properties pointing towards myelin loss and neuroinflammation rather than neurodegeneration.

Neural Correlates of Sensory Eye Dominance in Human Visual White Matter Tracts.

A significant proportion of the human neurotypical population exhibits some degree of sensory eye dominance (SED), referring to the brain's preferential processing of one eye's input versus another. The neural substrates underlying this functional imbalance are not well known. Here, we investigated the relationship between visual white matter tract properties and SED in the human neurotypical population. Observers' performance on two commonly used dichoptic tasks were used to index SED, along with performance on a third task to address a functional implication of binocular imbalance: stereovision. We show that diffusivity metrics of the optic radiations (ORs) well predict behavioral SED metrics. We found no relationship between SED and stereosensitivity. Our data suggest that SED is not simply reflected by gray matter structural and functional alterations, as often suggested, but relates, at least in part to the microstructural properties of thalamocortical white matter.

Quantitative MRI Evidence for Cognitive Reserve in Healthy Elders and Prodromal Alzheimer's Disease.

Cognitive reserve (CR) has been postulated to contribute to the variation observed between neuropathology and clinical outcomes in Alzheimer's disease (AD). We investigated the effect of an education-occupation derived CR proxy on biological properties of white matter tracts in patients with amnestic mild cognitive impairment (aMCI) and healthy elders (HC). Educational attainment and occupational complexity ratings (complexity with data, people, and things) from thirty-five patients with aMCI and twenty-eight HC were used to generate composite CR scores. Quantitative magnetic resonance imaging (qMRI) and multi-shell diffusion MRI were used to extract macromolecular tissue volume (MTV) across major white matter tracts. We observed significant differences in the association between CR and white matter tract MTV in aMCI versus HC when age, gender, intracranial volume, and memory ability were held constant. Particularly, in aMCI, higher CR was associated with worse tract pathology (lower MTV) in the left and right dorsal cingulum, callosum forceps major, right inferior fronto-occipital fasciculus, and right superior longitudinal fasciculus (SLF) tracts. Conversely higher CR was associated with higher MTV in the right parahippocampal cingulum and left SLF in HC. Our results support compensatory CR mechanisms in aMCI and neuroprotective mechanisms in HC and suggest differential roles for CR on white matter macromolecular properties in healthy elders versus prodromal AD patients.

Modeling the Properties of White Matter Tracts Using Diffusion Tensor Imaging to Characterize Patterns of Injury in Aging and Neurodegenerative Disease.

Diffusion tensor imaging (DTI) is a relatively novel magnetic resonance-based imaging methodology that can provide valuable insight into the microstructure of white matter tracts of the brain. In this paper, we evaluated the reliability and reproducibility of deriving a semi-automated pseudo-atlas DTI tractography method vs. standard atlas-based analysis alternatives, for use in clinical cohorts with neurodegeneration and ventriculomegaly. We showed that the semi-automated pseudo-atlas DTI tractography method was reliable and reproducible across different cohorts, generating 97.7% of all tracts. However, DTI metrics obtained from both methods were significantly different across the majority of cohorts and white matter tracts (p < 0.001). Despite this, we showed that both methods produced patterns of white matter injury that are consistent with findings reported in the literature and with DTI profiles generated from these methodologies. Scatter plots comparing DTI metrics obtained from each methodology showed that the pseudo-atlas method produced metrics that implied a more preserved neural structure compared to its counterpart. When comparing DTI metrics against a measure of ventriculomegaly (i.e., Evans’ Index), we showed that the standard atlas-based method was able to detect decreasing white matter integrity with increasing ventriculomegaly, while in contrast, metrics obtained using the pseudo-atlas method were sensitive for stretch or compression in the posterior limb of the internal capsule. Additionally, both methods were able to show an increase in white matter disruption with increasing ventriculomegaly, with the pseudo-atlas method showing less variability and more specificity to changes in white matter tracts near to the ventricles. In this study, we found that there was no true gold-standard for DTI methodologies or atlases. Whilst there was no congruence between absolute values from DTI metrics, differing DTI methodologies were still valid but must be appreciated to be variably sensitive to different changes within white matter injury occurring concurrently. By combining both atlas and pseudo-atlas based methodologies with DTI profiles, it was possible to navigate past such challenges to describe white matter injury changes in the context of confounders, such as neurodegenerative disease and ventricular enlargement, with transparency and consistency.

An investigation of white matter properties as they relate to spelling behaviour in skilled and impaired readers

ABSTRACT We examined the extent to which white matter is related to spelling behaviour in adults with skilled vs. impaired literacy skills. Adults (N = 30; 17 skilled) completed a battery of spelling tasks and underwent a brain scan to measure diffusion properties of white matter tracts, namely the arcuate fasciculus, inferior longitudinal fasciculus, inferior frontal occipital fasciculus and uncinate fasciculus. Regression analyses and between groups tests of correlation strength were run. Results While the inferior longitudinal fasciculus was more strongly related to spelling behaviour in skilled adults, the uncinate fasciculus was more strongly related to spelling behaviour in impaired adults. We found strong left lateralization of the arcuate fasciculus and inferior longitudinal fasciculus in both groups. However, lateralization of the inferior frontal occipital fasciculus was more strongly related to spelling response time behaviour in skilled adults, whereas lateralization of the uncinate fasciculus was more strongly related to spelling accuracy behaviour in the impaired adults. Conclusion This study provides some useful information for understanding the underlying white matter pathways that support spelling in skilled and impaired adults and underscore the advantage of adopting multiple spelling tasks and outcomes (i.e., response time and accuracy) to better characterize brain-behaviour relationships in skilled and impaired adults.

Reproduced correlations between integrity of white matter tracts and self-reported anxiety

Diffusion tensor imaging (DTI) allows us to evaluate the structural properties of white matter tracts which are associated with trait anxiety. However, in recent DTI studies of anxiety, research was focused mainly on selected white matter tracts, e.g. the uncinate fasciculus. At the same time, whole-brain structural connectivity has been rarely investigated in non-clinical populations. The present study aimed to explore correlations between white matter tract characteristics evaluated with the generalized fractional anisotropy (GFA) measure and state and trait anxiety inventory (STAI) scores at the whole-brain scale using the connectometry approach. In addition, we conducted psychological testing twice and examined the within-study reproducibility of these correlations. The results indicate reproduced correlations between both trait and state anxiety scores and GFA in the corpus callosum and association fibers predominantly in the right hemisphere, including the inferior, superior, and inferior fronto-occipital fasciculus, and cingulum bundle. The associations with state anxiety are the same as with trait anxiety except for the negative one with GFA in the left cingulum. The findings point to the role of the integrity of these white matter tracts in susceptibility to high trait and state anxiety. The defined local connectome correlations with anxiety ratings could serve as targets for anxiety disorders preventive diagnostics.

Evaluating the Reliability of Human Brain White Matter Tractometry.

The validity of research results depends on the reliability of analysis methods. In recent years, there have been concerns about the validity of research that uses diffusion-weighted MRI (dMRI) to understand human brain white matter connections in vivo, in part based on the reliability of analysis methods used in this field. We defined and assessed three dimensions of reliability in dMRI-based tractometry, an analysis technique that assesses the physical properties of white matter pathways: (1) reproducibility, (2) test-retest reliability, and (3) robustness. To facilitate reproducibility, we provide software that automates tractometry (https://yeatmanlab.github.io/pyAFQ). In measurements from the Human Connectome Project, as well as clinical-grade measurements, we find that tractometry has high test-retest reliability that is comparable to most standardized clinical assessment tools. We find that tractometry is also robust: showing high reliability with different choices of analysis algorithms. Taken together, our results suggest that tractometry is a reliable approach to analysis of white matter connections. The overall approach taken here both demonstrates the specific trustworthiness of tractometry analysis and outlines what researchers can do to establish the reliability of computational analysis pipelines in neuroimaging.

Effect of rTMS on fractional anisotropy, radial diffusivity, and axonal volume in select fiber tracts in patients with traumatic brain injury

Abstract Traumatic brain injury (TBI) frequently involves damage to the white matter tracts in the brain. Repetitive transcranial magnetic stimulation (rTMS) can improve many of the sequelae of TBI, including depression and executive order dysfunction. This raises the question of whether rTMS treatment may result in measurable changes in the diffusion properties of white matter tracts, especially in those proximal to the rTMS treatment target location. In this study, 33 Veterans diagnosed with mild or moderate TBI (age 20-69 years; mild (n = 27) and moderate (n = 6) underwent the rTMS protocol that is FDA approved for major depression, receiving one treatment per day, five days per week, for four weeks (either treatment (n=17) or sham (n=16) version). Each participant underwent cognitive testing, as well as T1-weighted (T1W) and diffusion weighted (DWI) MR imaging scans, at the baseline, immediate post-treatment, and one month follow up timepoints. DWIs were processed using the Automated Fiber Quantification (AFQ) pipeline (Yeatman et al. 2012). This procedure identifies 20 white matter fiber tracts in the brain and obtain the diffusion parameters, e.g. fractional anisotropy (FA) and radial diffusivity (RD), at the100 discrete segments along the central portions of the fiber tracts. AFQ outcomes from each timepoint will be subjected to a linear mixed effects analysis to determine what effect rTMS treatment has on the diffusion properties in fibers proximal to the target, especially the superior longitudinal fasciculus. We will control for age, years of education, and baseline diffusivity values. Diffusion parameters of interest include fractional anisotropy, radial diffusivity, and one non-diffusivity variable, tract volume. We also plan to correlate these outcomes with performance on an executive function task. Keywords: DTI, AFQ, LME, rTMS

The neural correlates of sensory eye dominance as revealed by visual white matter tract properties

The neural correlates of sensory eye dominance as revealed by visual white matter tract properties

Fiber ball white matter modeling in focal epilepsy.

Multicompartment diffusion magnetic resonance imaging (MRI) approaches are increasingly being applied to estimate intra‐axonal and extra‐axonal diffusion characteristics in the human brain. Fiber ball imaging (FBI) and its extension fiber ball white matter modeling (FBWM) are such recently described multicompartment approaches. However, these particular approaches have yet to be applied in clinical cohorts. The modeling of several diffusion parameters with interpretable biological meaning may offer the development of new, noninvasive biomarkers of pharmacoresistance in epilepsy. In the present study, we used FBI and FBWM to evaluate intra‐axonal and extra‐axonal diffusion properties of white matter tracts in patients with longstanding focal epilepsy. FBI/FBWM diffusion parameters were calculated along the length of 50 white matter tract bundles and statistically compared between patients with refractory epilepsy, nonrefractory epilepsy and controls. We report that patients with chronic epilepsy had a widespread distribution of extra‐axonal diffusivity relative to controls, particularly in circumscribed regions along white matter tracts projecting to cerebral cortex from thalamic, striatal, brainstem, and peduncular regions. Patients with refractory epilepsy had significantly greater markers of extra‐axonal diffusivity compared to those with nonrefractory epilepsy. The extra‐axonal diffusivity alterations in patients with epilepsy observed in the present study could be markers of neuroinflammatory processes or a reflection of reduced axonal density, both of which have been histologically demonstrated in focal epilepsy. FBI is a clinically feasible MRI approach that provides the basis for more interpretive conclusions about the microstructural environment of the brain and may represent a unique biomarker of pharmacoresistance in epilepsy.

Focal white matter disruptions along the cingulum tract explain cognitive decline in amnestic mild cognitive impairment (aMCI)

White matter abnormalities of the human brain are implicated in typical aging and neurodegenerative diseases. However, our understanding of how fine-grained changes in microstructural properties along white matter tracts are associated with memory and cognitive decline in normal aging and mild cognitive impairment remains elusive. We quantified tract profiles with a newer method that can reliably measure fine-grained changes in white matter properties along the tracts using advanced multi-shell diffusion magnetic resonance imaging in 25 patients with amnestic mild cognitive impairment (aMCI) and 23 matched healthy controls (HC). While the changes in tract profiles were parallel across aMCI and HC, we found a significant focal shift in the profile at specific locations along major tracts sub-serving memory in aMCI. Particularly, our findings depict white matter alterations at specific locations on the right cingulum cingulate, the right cingulum hippocampus and anterior corpus callosum (CC) in aMCI compared to HC. Notably, focal changes in white matter tract properties along the cingulum tract predicted memory and cognitive functioning in aMCI. The results suggest that white matter disruptions at specific locations of the cingulum bundle may be a hallmark for the early prediction of Alzheimer’s disease and a predictor of cognitive decline in aMCI.

Cognitive Networks Disarrangement in Patients With Migraine Predicts Cutaneous Allodynia.

Two-thirds of patients with migraine without aura (MwoA) complain ictal cutaneous allodynia (CA), clinical sign of central nociceptive pathway sensitization, and independent predictor for migraine chronification. We aimed to investigate whether functional abnormalities, structural, or microstructural changes of the main cognitive networks (default mode network [DMN], salience network [SN], and central executive network [CEN]) could predict the development of CA in patients with MwoA. Baseline 3-Tesla MRI images of 50 patients with MwoA were analyzed between 2009 and 2015. Over a three-year period, patients were then stratified into 2 groups based on CA development and compared with matched healthy controls (HC). Group-level independent components analysis was used to investigate intrinsic functional connectivity (FC) differences within the cognitive resting-state networks. Voxel-based morphometry (VBM) was used to assess whether group differences in cognitive network FC were related to structural differences. Tract-based spatial statistical analyses (TBSS) were conducted to assess the microstructural properties of white matter tracts. We also compared internetwork connectivity between patients. Finally, a logistic regression analysis was used to investigate baseline imaging predictors of CA development. We observed a significantly reduced FC of both DMN and CEN in patients with MwoA developing CA (MwoA d CA) when compared with both patients with MwoA not developing CA (MwoA nd CA) and HC. Within the DMN, the PCC/precuneus is a key hub aimed to anti-nociception and multisensory integration. The reduced intrinsic PCC/precuneus FC observed in patients with MwoA d CA could subtend abnormal inputs integration, from different sensory modalities, allowing the development of CA. On the other hand, within the CEN, a central role in pain modulation as well as in executive functions is played by ACC and MFG. Our finding of reduced ACC and MFG FC in MwoA d CA may represent the neuronal substrate of both subclinical impairment of complex executive functions and dysfunctional anti-nociceptive pathway, making these patients more prone to migraine chronification. TBSS analyses showed a statistically significant reduced corpus callosum (CC) FA in patients with MwoA d CA as previously demonstrated in migraine patients with other chronification factors such as medication overuse or affective disorders. No VBM differences in both global and local volumes were revealed between groups. No significant correlations have been found between the observed functional and microstructural changes and clinical parameters of disease severity. Logistic regression analysis indicated that the full model containing all predictors was statistically significant while the decreased ACC-FC was significantly associated with CA development. We suggest that DMN and CEN FC abnormalities as well as CC microstructural changes could represent a prognostic imaging biomarker able to identify migraine patients more prone to experiencing CA and therefore, more inclined to chronic migraine. In the new pharmacological scenario, it would be useful to address therapeutic resources to specific migraine populations with a high risk of more severe clinical phenotype.

Estimating the Heritability of Developmental Change in Neural Connectivity, and Its Association With Changing Symptoms of Attention-Deficit/Hyperactivity Disorder

BackgroundTwin studies show that age-related change in symptoms of attention-deficit/hyperactivity disorder (ADHD) is heritable. However, we do not know the heritability of the development of the neural substrates underlying the disorder. Here, we estimated the heritability of developmental change in white matter tracts and the brain’s intrinsic functional connectivity using longitudinal data. We further determined associations with change in ADHD symptoms. MethodsThe study reports on 288 children, which included 127 siblings, 19 cousins, and 142 singletons; 150 (52%) had a diagnosis of ADHD (determined by clinician interview with parent); 188 were male. All had two clinical assessments (overall baseline mean age: 9.4 ± 2.4 years; follow-up: 12.5 ± 2.6 years). Diffusion tensor imaging estimated microstructural properties of white matter tracts on 252 participants. Resting-state functional magnetic resonance imaging estimated intrinsic connectivity within and between major brain networks on 226 participants. Total additive genetic heritability (h2) of the annual rate of change in these neural phenotypes was calculated using SOLAR (Sequential Oligogenic Linkage Analysis Routines). ResultsSignificant heritability was found for the rates of change of 6 white matter tract microstructural properties and for change in the connectivity between the ventral attention network and both the cognitive control and dorsal attention networks. Change in hyperactivity-impulsivity was associated with heritable change in white matter tracts metrics and change in the connectivity between the ventral attention and cognitive networks. ConclusionsThe relatively small number of heritable, ADHD-associated developmental neural phenotypes can serve as phenotypes for future gene discovery and understanding.

Patterns of sociocognitive stratification and perinatal risk in the child brain

The expanding behavioral repertoire of the developing brain during childhood and adolescence is shaped by complex brain-environment interactions and flavored by unique life experiences. The transition into young adulthood offers opportunities for adaptation and growth but also increased susceptibility to environmental perturbations, such as the characteristics of social relationships, family environment, quality of schools and activities, financial security, urbanization and pollution, drugs, cultural practices, and values, that all act in concert with our genetic architecture and biology. Our multivariate brain-behavior mapping in 7,577 children aged 9 to 11 y across 585 brain imaging phenotypes and 617 cognitive, behavioral, psychosocial, and socioeconomic measures revealed three population modes of brain covariation, which were robust as assessed by cross-validation and permutation testing, taking into account siblings and twins, identified using genetic data. The first mode revealed traces of perinatal complications, including preterm and twin birth, eclampsia and toxemia, shorter period of breastfeeding, and lower cognitive scores, with higher cortical thickness and lower cortical areas and volumes. The second mode reflected a pattern of sociocognitive stratification, linking lower cognitive ability and socioeconomic status to lower cortical thickness, area, and volumes. The third mode captured a pattern related to urbanicity, with particulate matter pollution (PM25) inversely related to home value, walkability, and population density, associated with diffusion properties of white matter tracts. These results underscore the importance of a multidimensional and interdisciplinary understanding, integrating social, psychological, and biological sciences, to map the constituents of healthy development and to identify factors that may precede maladjustment and mental illness.

Comparison of brain connectomes by MRI and genomics and its implication in Alzheimer\u2019s disease

BackgroundThe human brain is complex and interconnected structurally. Brain connectome change is associated with Alzheimer’s disease (AD) and other neurodegenerative diseases. Genetics and genomics studies have identified molecular changes in AD; however, the results are often limited to isolated brain regions and are difficult to interpret its findings in respect to brain connectome. The mechanisms of how one brain region impacts the molecular pathways in other regions have not been systematically studied. And how the brain regions susceptible to AD pathology interact with each other at the transcriptome level and how these interactions relate to brain connectome change are unclear.MethodsHere, we compared structural brain connectomes defined by probabilistic tracts using diffusion magnetic resonance imaging data in Alzheimer’s Disease Neuroimaging Initiative database and a brain transcriptome dataset covering 17 brain regions.ResultsWe observed that the changes in diffusion measures associated with AD diagnosis status and the associations were replicated in an independent cohort. The result suggests that disease associated white matter changes are focal. Analysis of the brain connectome by genomic data, tissue-tissue transcriptional synchronization between 17 brain regions, indicates that the regions connected by AD-associated tracts were likely connected at the transcriptome level with high number of tissue-to-tissue correlated (TTC) gene pairs (P = 0.03). And genes involved in TTC gene pairs between white matter tract connected brain regions were enriched in signaling pathways (P = 6.08 × 10−9). Further pathway interaction analysis identified ionotropic glutamate receptor pathway and Toll receptor signaling pathways to be important for tissue-tissue synchronization at the transcriptome level. Transcript profile entailing Toll receptor signaling in the blood was significantly associated with diffusion properties of white matter tracts, notable association between fractional anisotropy and bilateral cingulum angular bundles (Ppermutation = 1.0 × 10−2 and 4.9 × 10−4 for left and right respectively).ConclusionsIn summary, our study suggests that brain connectomes defined by MRI and transcriptome data overlap with each other.

6.65 ESTIMATING THE HERITABILITY OF THE BRAIN'S STRUCTURAL CONNECTIVITY AND ITS ASSOCIATION WITH CHANGING SYMPTOMS OF ADHD

Using longitudinal data, we estimated the heritability of developmental change in the microstructural properties of white matter tracts. We further determined associations with changes in ADHD symptoms.

White Matter Plasticity in Reading-Related Pathways Differs in Children Born Preterm and at Term: A Longitudinal Analysis.

Children born preterm (PT) are at risk for white matter injuries based on complications of prematurity. They learn to read but on average perform below peers born full term (FT). Studies have yet to establish whether properties of white matter pathways at the onset of learning to read are associated with individual variation later in reading development in PT children. Here, we asked whether fractional anisotropy (FA) at age 6 years is associated with reading outcome at age 8 years in PT children in the same pathways as previously demonstrated in a sample of FT children. PT (n = 34, mean gestational age = 29.5 weeks) and FT children (n = 37) completed diffusion MRI and standardized measures of non-verbal IQ, language, and phonological awareness at age 6 years. Reading skills were assessed at age 8 years. Mean tract-FA was extracted from pathways that predicted reading outcome in children born FT: left arcuate fasciculus (Arc), bilateral superior longitudinal fasciculus (SLF), and left inferior cerebellar peduncle (ICP). We explored associations in additional pathways in the PT children: bilateral inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, and uncinate fasciculus. Linear regression models examined whether the prediction of reading outcome at age 8 years based on mean tract-FA at age 6 years was moderated by birth group. Children born PT and FT did not differ significantly in tract-FA at age 6 years or in reading at age 8 years. Sex, socioeconomic status, and non-verbal IQ at age 6 years were associated with reading outcome and were included as covariates in all models. Birth group status significantly moderated associations between reading outcome and mean tract-FA only in the left Arc, right SLF, and left ICP, before and after consideration of pre-literacy skills. Microstructural properties of these cerebral and cerebellar pathways predicted later reading outcome in FT but not in PT children. Children born PT may rely on alternative pathways to achieve fluent reading. These findings have implications for plasticity of neural organization after early white matter injury.