Brain White Matter Connectivity Research Articles

Brain structure and connectivity mediate the association of lifestyle and cognition: the Maastricht study

Abstract Life-course exposure to risk and protective factors impacts brain macro- and micro-structure, which in turn affects cognition. The concept of Brain Age Gap (BAG) assesses brain health by comparing an individual’s neuroimaging-based predicted age with their calendar age. Higher BAG implies accelerated brain aging and is expected to be associated with worse cognition. In this study, we comprehensively modelled mutual associations between brain-health and lifestyle factors, brain age, and cognition in a large, middle-aged population. For this study, cognitive test scores, lifestyle, and 3T MRI data for n=4881 participants (mean age (±SD) = 59.2 (±8.6), 50.1% male) were available from The Maastricht Study, a population-based cohort study with extensive phenotyping. Whole brain volumes (grey matter (GM), cerebrospinal fluid (CSF), white matter hyperintensity (WMH)), cerebral microbleeds (CMB), and structural white matter connectivity were calculated. Lifestyle factors were combined into an adapted LIfestyle for BRAin health (LIBRA) weighted sum score, with higher score indicating greater dementia risk. Cognition was calculated by averaging z-scores across three cognitive domains (memory, information processing speed, executive function and attention). BAG was calculated by comparing calendar age to predictions from a neuroimaging-based multivariable regression model. Paths between LIBRA tertiles, BAG and cognitive function were tested using linear regression and structural equation modelling, adjusting for sociodemographic and clinical confounders. Results show that CSF, GM, WMH and CMB best predicted BAG (R2 = 0.455, RMSE = 6.44). In regression analysis, higher LIBRA scores (greater dementia risk) were associated with higher BAG (standardized regression coefficient ß = 0.126, p < 0.001) and worse cognition (ß = -0.046, p = 0.013), while higher BAG was associated with worse cognition (ß=-0.163, p<0.001). In mediation analysis, 24.7% of the total difference in cognition between the highest and lowest LIBRA tertile was mediated by BAG (ßindirect = -0.049, p < 0.001; ßtotal = -0.198, p < 0.001), and an additional 3.8% was mediated via connectivity (ßindirect = -0.006, p < 0.001; ßtotal = -0.150, p < 0.001). Findings suggest that associations between health- and lifestyle-based risk/protective factors (LIBRA) and cognition can be partially explained by structural brain health markers (BAG) and white matter connectivity markers. Lifestyle interventions targeted at high-risk individuals in mid to late life may be effective in promoting and preserving cognitive function in the general public.

Resting-state functional connectivity in children cooled for neonatal encephalopathy.

Therapeutic hypothermia improves outcomes following neonatal hypoxic-ischaemic encephalopathy, reducing cases of death and severe disability such as cerebral palsy compared with normothermia management. However, when cooled children reach early school-age, they have cognitive and motor impairments which are associated with underlying alterations to brain structure and white matter connectivity. It is unknown whether these differences in structural connectivity are associated with differences in functional connectivity between cooled children and healthy controls. Resting-state functional MRI has been used to characterize static and dynamic functional connectivity in children, both with typical development and those with neurodevelopmental disorders. Previous studies of resting-state brain networks in children with hypoxic-ischaemic encephalopathy have focussed on the neonatal period. In this study, we used resting-state fMRI to investigate static and dynamic functional connectivity in children aged 6-8 years who were cooled for neonatal hypoxic-ischaemic without cerebral palsy [n = 22, median age (interquartile range) 7.08 (6.85-7.52) years] and healthy controls matched for age, sex and socioeconomic status [n = 20, median age (interquartile range) 6.75 (6.48-7.25) years]. Using group independent component analysis, we identified 31 intrinsic functional connectivity networks consistent with those previously reported in children and adults. We found no case-control differences in the spatial maps of these intrinsic connectivity networks. We constructed subject-specific static functional connectivity networks by measuring pairwise Pearson correlations between component time courses and found no case-control differences in functional connectivity after false discovery rate correction. To study the time-varying organization of resting-state networks, we used sliding window correlations and deep clustering to investigate dynamic functional connectivity characteristics. We found k = 4 repetitively occurring functional connectivity states, which exhibited no case-control differences in dwell time, fractional occupancy or state functional connectivity matrices. In this small cohort, the spatiotemporal characteristics of resting-state brain networks in cooled children without severe disability were too subtle to be differentiated from healthy controls at early school-age, despite underlying differences in brain structure and white matter connectivity, possibly reflecting a level of recovery of healthy resting-state brain function. To our knowledge, this is the first study to investigate resting-state functional connectivity in children with hypoxic-ischaemic encephalopathy beyond the neonatal period and the first to investigate dynamic functional connectivity in any children with hypoxic-ischaemic encephalopathy.

THE SOCIAL DETERMINANTS OF BRAIN HEALTH: FROM THE SEARCH FOR MECHANISMS TO RECOMMENDATIONS TO INCREASE EQUITY

Abstract Dementia risk has been established to be partly attributable to modifiable social and behavioral risk factors. However, the biological pathways behind these associations and the effects of intervening on present risk factors to reduce dementia risk have not been fully elucidated. The symposium will present latest research on the social determinants of brain health and dementia. We will explore proposed mechanisms between modifiable risk factors and risk of dementia, and present findings on the modifiability of dementia risk through addressing risk factors. Specifically, the first presentation reports analyses testing possible pathways from socioeconomic status, notably childhood and adulthood indicators such as (parental) education and occupation, to cognitive functioning in later mid-adulthood via indicators of brain damage and white matter connectivity with the Maastricht Study. The second presentation reports empirical analyses testing the possible mediating role of the gut microbiome in the relationships between social and modifiable risk factors and Mild Cognitive Impairment with data of the controls of the Luxembourg Parkinson’s Study. The third presentation reports on the associations between hearing loss as a modifiable risk factor and incident dementia in the UK Biobank and investigates the potential to modify hearing loss-associated dementia risk through the use of hearing aids. Lastly, the fourth presentation moves to recommendations for policy and government action. It gives an overview of various fields in which policy and legislation could implement cognitive impact assessments to protect individuals’ cognition, with the aim of improving population brain health and health equity. This is a Brain Interest Group Sponsored Symposium.

Brains of endurance athletes differ in the association areas but not in the primary areas.

Regular participation in sports results in a series of physiological adaptations. However, little is known about the brain adaptations to physical activity. Here we aimed to investigate whether young endurance athletes and non-athletes differ in the gray and white matter of the brain and whether cardiorespiratory fitness (CRF) is associated with these differences. We assessed the CRF, volumes of the gray and white matter of the brain using structural magnetic resonance imaging (sMRI), and brain white matter connections using diffusion magnetic resonance imaging (dMRI) in 20 young male endurance athletes and 21 healthy non-athletes. While total brain volume was similar in both groups, the white matter volume was larger and the gray matter volume was smaller in the athletes compared to non-athletes. The reduction of gray matter was located in the association areas of the brain that are specialized in processing of sensory stimuli. In the microstructure analysis, significant group differences were found only in the association tracts, for example, the inferior occipito-frontal fascicle (IOFF) showing higher fractional anisotropy and lower radial diffusivity, indicating stronger myelination in this tract. Additionally, gray and white matter brain volumes, as well as association tracts correlated with CRF. No changes were observed in other brain areas or tracts. In summary, the brain signature of the endurance athlete is characterized by changes in the integration of sensory and motor information in the association areas.

Maternal childhood maltreatment: associations to offspring brain volume and white matter connectivity.

The deleterious effects of adversity are likely intergenerational, such that one generation's adverse experiences can affect the next. Epidemiological studies link maternal adversity to offspring depression and anxiety, possibly via transmission mechanisms that influence offspring fronto-limbic connectivity. However, studies have not thoroughly disassociated postnatal exposure effects nor considered the role of offspring sex. We utilized infant neuroimaging to test the hypothesis that maternal childhood maltreatment (CM) would be associated with increased fronto-limbic connectivity in infancy and tested brain-behavior associations in childhood. Ninety-two dyads participated (32 mothers with CM, 60 without; 52 infant females, 40 infant males). Women reported on their experiences of CM and non-sedated sleeping infants underwent MRIs at 2.44 ± 2.74 weeks. Brain volumes were estimated via structural MRI and white matter structural connectivity (fiber counts) via diffusion MRI with probabilistic tractography. A subset of parents (n = 36) reported on children's behaviors at age 5.17 ± 1.73 years. Males in the maltreatment group demonstrated greater intra-hemispheric fronto-limbic connectivity (b = 0.96, p= 0.008, [95%CI 0.25, 1.66]), no differences emerged for females. Fronto-limbic connectivity was related to somatic complaints in childhood only for males (r = 0.673, p = 0.006). Our findings suggest that CM could have intergenerational associations to offspring brain development, yet mechanistic studies are needed.

Cerebellar growth, volume and diffusivity in children cooled for neonatal encephalopathy without cerebral palsy

Children cooled for HIE and who did not develop cerebral palsy (CP) still underperform at early school age in motor and cognitive domains and have altered supra-tentorial brain volumes and white matter connectivity. We obtained T1-weighted and diffusion-weighted MRI, motor (MABC-2) and cognitive (WISC-IV) scores from children aged 6–8 years who were cooled for HIE secondary to perinatal asphyxia without CP (cases), and controls matched for age, sex, and socioeconomic status. In 35 case children, we measured cerebellar growth from infancy (age 4–15 days after birth) to childhood. In childhood, cerebellar volumes were measured in 26 cases and 23 controls. Diffusion properties (mean diffusivity, MD and fractional anisotropy, FA) were calculated in 24 cases and 19 controls, in 9 cerebellar regions. Cases with FSIQ ≤ 85 had reduced growth of cerebellar width compared to those with FSIQ > 85 (p = 0.0005). Regional cerebellar volumes were smaller in cases compared to controls (p < 0.05); these differences were not significant when normalised to total brain volume. There were no case–control differences in MD or FA. Interposed nucleus volume was more strongly associated with IQ in cases than in controls (p = 0.0196). Other associations with developmental outcome did not differ between cases and controls.

Superficial white matter analysis: An efficient point-cloud-based deep learning framework with supervised contrastive learning for consistent tractography parcellation across populations and dMRI acquisitions.

Diffusion MRI tractography is an advanced imaging technique that enables in vivo mapping of the brain's white matter connections. White matter parcellation classifies tractography streamlines into clusters or anatomically meaningful tracts. It enables quantification and visualization of whole-brain tractography. Currently, most parcellation methods focus on the deep white matter (DWM), whereas fewer methods address the superficial white matter (SWM) due to its complexity. We propose a novel two-stage deep-learning-based framework, Superficial White Matter Analysis (SupWMA), that performs an efficient and consistent parcellation of 198 SWM clusters from whole-brain tractography. A point-cloud-based network is adapted to our SWM parcellation task, and supervised contrastive learning enables more discriminative representations between plausible streamlines and outliers for SWM. We train our model on a large-scale tractography dataset including streamline samples from labeled long- and medium-range (over 40mm) SWM clusters and anatomically implausible streamline samples, and we perform testing on six independently acquired datasets of different ages and health conditions (including neonates and patients with space-occupying brain tumors). Compared to several state-of-the-art methods, SupWMA obtains highly consistent and accurate SWM parcellation results on all datasets, showing good generalization across the lifespan in health and disease. In addition, the computational speed of SupWMA is much faster than other methods.

Immuno-epigenetic signature derived in saliva associates with the encephalopathy of prematurity and perinatal inflammatory disorders

BackgroundPreterm birth is closely associated with a phenotype that includes brain dysmaturation and neurocognitive impairment, commonly termed Encephalopathy of Prematurity (EoP), of which systemic inflammation is considered a key driver. DNA methylation (DNAm) signatures of inflammation from peripheral blood associate with poor brain imaging outcomes in adult cohorts. However, the robustness of DNAm inflammatory scores in infancy, their relation to comorbidities of preterm birth characterised by inflammation, neonatal neuroimaging metrics of EoP, and saliva cross-tissue applicability are unknown. MethodsUsing salivary DNAm from 258 neonates (n = 155 preterm, gestational age at birth 23.28 – 34.84 weeks, n = 103 term, gestational age at birth 37.00 – 42.14 weeks), we investigated the impact of a DNAm surrogate for C-reactive protein (DNAm CRP) on brain structure and other clinically defined inflammatory exposures. We assessed i) if DNAm CRP estimates varied between preterm infants at term equivalent age and term infants, ii) how DNAm CRP related to different types of inflammatory exposure (maternal, fetal and postnatal) and iii) whether elevated DNAm CRP associated with poorer measures of neonatal brain volume and white matter connectivity. ResultsHigher DNAm CRP was linked to preterm status (-0.0107 ± 0.0008, compared with −0.0118 ± 0.0006 among term infants; p < 0.001), as well as perinatal inflammatory diseases, including histologic chorioamnionitis, sepsis, bronchopulmonary dysplasia, and necrotising enterocolitis (OR range |2.00 | to |4.71|, p < 0.01). Preterm infants with higher DNAm CRP scores had lower brain volume in deep grey matter, white matter, and hippocampi and amygdalae (β range |0.185| to |0.218|). No such associations were observed for term infants. Association magnitudes were largest for measures of white matter microstructure among preterms, where elevated epigenetic inflammation associated with poorer global measures of white matter integrity (β range |0.206| to |0.371|), independent of other confounding exposures. ConclusionsInflammatory-related DNAm captures the allostatic load of inflammatory burden in preterm infants. Such DNAm measures complement biological and clinical metrics when investigating the determinants of neurodevelopmental differences.

Native language differences in the structural connectome of the human brain

Is the neuroanatomy of the language structural connectome modulated by the life-long experience of speaking a specific language? The current study compared the brain white matter connections of the language and speech production network in a large cohort of 94 native speakers of two very different languages: an Indo-European morphosyntactically complex language (German) and a Semitic root-based language (Arabic). Using high-resolution diffusion-weighted MRI and tractography-based network statistics of the language connectome, we demonstrated that German native speakers exhibited stronger connectivity in an intra-hemispheric frontal to parietal/temporal dorsal language network, known to be associated with complex syntax processing. In comparison, Arabic native speakers showed stronger connectivity in the connections between semantic language regions, including the left temporo-parietal network, and stronger inter-hemispheric connections via the posterior corpus callosum connecting bilateral superior temporal and inferior parietal regions. The current study suggests that the structural language connectome develops and is modulated by environmental factors such as the characteristic processing demands of the native language.

Diffusion tensor imaging pipeline measures of cerebral white matter integrity: An overview of recent advances and prospects.

Cerebral small vessel disease (CSVD) is a leading cause of age-related microvascular cognitive decline, resulting in significant morbidity and decreased quality of life. Despite a progress on its key pathophysiological bases and general acceptance of key terms from neuroimaging findings as observed on the magnetic resonance imaging (MRI), key questions on CSVD remain elusive. Enhanced relationships and reliable lesion studies, such as white matter tractography using diffusion-based MRI (dMRI) are necessary in order to improve the assessment of white matter architecture and connectivity in CSVD. Diffusion tensor imaging (DTI) and tractography is an application of dMRI that provides data that can be used to non-invasively appraise the brain white matter connections via fiber tracking and enable visualization of individual patient-specific white matter fiber tracts to reflect the extent of CSVD-associated white matter damage. However, due to a lack of standardization on various sets of software or image pipeline processing utilized in this technique that driven mostly from research setting, interpreting the findings remain contentious, especially to inform an improved diagnosis and/or prognosis of CSVD for routine clinical use. In this minireview, we highlight the advances in DTI pipeline processing and the prospect of this DTI metrics as potential imaging biomarker for CSVD, even for subclinical CSVD in at-risk individuals.

Increased persuadability and credulity in people with corpus callosum dysgenesis

Corpus callosum dysgenesis is one of the most common congenital neurological malformations. Despite being a clear and identifiable structural alteration of the brain's white matter connectivity, the impact of corpus callosum dysgenesis on cognition and behaviour has remained unclear. Here we build upon past clinical observations in the literature to define the clinical phenotype of corpus callosum dysgenesis better using unadjusted and adjusted group differences compared with a neurotypical sample on a range of social and cognitive measures that have been previously reported to be impacted by a corpus callosum dysgenesis diagnosis. Those with a diagnosis of corpus callosum dysgenesis (n = 22) demonstrated significantly higher persuadability, credulity, and insensitivity to social trickery than neurotypical (n = 86) participants, after controlling for age, sex, education, autistic-like traits, social intelligence, and general cognition. To explore this further, we examined the covariance structure of our psychometric variables using a machine learning algorithm trained on a neurotypical dataset. The algorithm was then used to test whether these dimensions possessed the capability to discriminate between a test-set of neurotypical and corpus callosum dysgenesis participants. After controlling for age and sex, and with Leave-One-Out-Cross-Validation across 250 training-set bootstrapped iterations, we found that participants with a diagnosis of corpus callosum dysgenesis were best classed within dimension space along the same axis as persuadability, credulity, and insensitivity to social trickery, with a mean accuracy of 71.7%. These results have implications for a) the characterisation of corpus callosum dysgenesis, and b) the role of the corpus callosum in social inference.

Auto-encoded Latent Representations of White Matter Streamlines for Quantitative Distance Analysis

Parcellation of whole brain tractograms is a critical step to study brain white matter structures and connectivity patterns. The existing methods based on supervised classification of streamlines into predefined streamline bundle types are not designed to explore sub-bundle structures, and methods with manually designed features are expensive to compute streamline-wise similarities. To resolve these issues, we propose a novel atlas-free method that learns a latent space using a deep recurrent auto-encoder trained in an unsupervised manner. The method efficiently embeds any length of streamlines to fixed-size feature vectors, named streamline embedding, for tractogram parcellation using non-parametric clustering in the latent space. The method was evaluated on the ISMRM 2015 tractography challenge dataset with discrimination of major bundles using clustering algorithms and streamline querying based on similarity, as well as real tractograms of 102 subjects Human Connectome Project. The learnt latent streamline and bundle representations open the possibility of quantitative studies of arbitrary granularity of sub-bundle structures using generic data mining techniques.

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.

Four decades of chemotherapy-induced cognitive dysfunction: comprehensive review of clinical, animal and in vitro studies, and insights of key initiating events.

Cognitive dysfunction has been one of the most reported and studied adverse effects of cancer treatment, but, for many years, it was overlooked by the medical community. Nevertheless, the medical and scientific communities have now recognized that the cognitive deficits caused by chemotherapy have a strong impact on the morbidity of cancer treated patients. In fact, chemotherapy-induced cognitive dysfunction or 'chemobrain' (also namedalsochemofog) is at present a well-recognized effect of chemotherapy that could affect up to 78% of treated patients. Nonetheless, its underlying neurotoxic mechanism is still not fully elucidated. Therefore, this work aimed to provide a comprehensive review using PubMed as a database to assess the studies published on the field and, therefore, highlight the clinical manifestations of chemobrain and the putative neurotoxicity mechanisms.In the last two decades, a great number of papers was published on the topic, mainly with clinical observations. Chemotherapy-treated patients showed that the cognitive domains most often impaired were verbal memory, psychomotor function, visual memory, visuospatial and verbal learning, memory function and attention. Chemotherapy alters the brain's metabolism, white and grey matter and functional connectivity of brain areas. Several mechanisms have been proposed to cause chemobrain but increase of proinflammatory cytokines with oxidative stress seem more relevant, not excluding the action on neurotransmission and cellular death or impaired hippocampal neurogenesis. The interplay between these mechanisms and susceptible factors makes the clinical management of chemobrain even more difficult. New studies, mainly referring to the underlying mechanisms of chemobrain and protective measures, are important in the future, as it is expected that chemobrain will have more clinical impact in the coming years, since the number of cancer survivors is steadily increasing.

Grip training improves handgrip strength, cognition, and brain white matter in minor acute ischemic stroke patients

ObjectiveA large proportion of stroke patients experience cognitive impairment. Previous studies found that handgrip training can improve cognitive dysfunction after stroke through an unknown mechanism. In this study, we aimed to examine the influence of handgrip training on the cognition of patients with acute mild ischemic stroke and explore the mechanism using an advanced post-processing method for magnetic resonance imaging. MethodsSeventy-six patients with acute mild ischemic stroke were recruited for this study and randomly divided into a grip training group (n = 37) and a control group (n = 39). Both groups of patients also received standardized treatment for stroke in the acute phase and for secondary prevention, as well as conventional physical therapy after stroke. Grip strength, global cognitive function, and the local and global efficiencies of white matter networks derived from diffusion tensor images were measured before and after the 12-week training period. ResultsIn the within-group comparisons, grip training significantly improved the grip strength (3.52 [3.09–3.96], p = 0.02), Montreal Cognitive Assessment (MoCA) (2.27 [1.68–2.86], p = 0.05), and local, but not global, efficiency of the brain white matter network (0.03 [0.02–0.03], p = 0.02) in the experimental group. In contrast, these parameters were not statistically different over the same period in the control group. In the between-groups comparisons, the improvement of grip strength (2.71 [2.20–3.21], p = 0.01), MoCA (1.17 [0.39–1.95], p = 0.05), and local efficiency (0.02 [0.01–0.03], p = 0.01) showed statistically significant differences after the intervention, but not the absolute value of them, neither at the base line nor after the intervention. ConclusionsOur results indicate that grip training can improve cognitive function by increasing the local efficiency of brain white matter connectivity. This suggests that white matter remodeling is a potential physiological mechanism connecting grip training and cognition improvement.

Structural connectivity predicts sequential processing differences in music perception ability.

To relate individual differences in music perception ability with whole brain white matter connectivity, we scanned a group of 27 individuals with varying degrees of musical training and assessed musical ability in sensory and sequential music perception domains using the Profile of Music Perception Skills-Short version (PROMS-S). Sequential processing ability was estimated by combining performance on tasks for Melody, Standard Rhythm, Embedded Rhythm, and Accent subscores while sensory processing ability was ascertained via tasks of Tempo, Pitch, Timbre, and Tuning. Controlling for musical training, gender, and years of training, network-based statistics revealed positive linear associations between total PROMS-S scores and increased interhemispheric fronto-temporal and parieto-frontal white matter connectivity, suggesting a distinct segregated structural network for music perception. Secondary analysis revealed two subnetworks for sequential processing ability, one comprising ventral fronto-temporal and subcortical regions and the other comprising dorsal fronto-temporo-parietal regions. A graph-theoretic analysis to characterize the structural network revealed a positive association of modularity of the whole brain structural connectome with the d' total score. In addition, the nodal degree of the right posterior cingulate cortex also showed a significant positive correlation with the total d' score. Our results suggest that a distinct structural network of connectivity across fronto-temporal, cerebellar, and cerebro-subcortical regions is associated with music processing abilities and the right posterior cingulate cortex mediates the connectivity of this network.

Relating quantitative 7T MRI across cortical depths to cytoarchitectonics, gene expression and connectomics.

Ultra‐high field MRI across the depth of the cortex has the potential to provide anatomically precise biomarkers and mechanistic insights into neurodegenerative disease like Huntington's disease that show layer‐selective vulnerability. Here we compare multi‐parametric mapping (MPM) measures across cortical depths for a 7T 500 μm whole brain acquisition to (a) layer‐specific cell measures from the von Economo histology atlas, (b) layer‐specific gene expression, using the Allen Human Brain atlas and (c) white matter connections using high‐fidelity diffusion tractography, at a 1.3 mm isotropic voxel resolution, from a 300mT/m Connectom MRI system. We show that R2*, but not R1, across cortical depths is highly correlated with layer‐specific cell number and layer‐specific gene expression. R1‐ and R2*‐weighted connectivity strength of cortico‐striatal and intra‐hemispheric cortical white matter connections was highly correlated with grey matter R1 and R2* across cortical depths. Limitations of the layer‐specific relationships demonstrated are at least in part related to the high cross‐correlations of von Economo atlas cell counts and layer‐specific gene expression across cortical layers. These findings demonstrate the potential and limitations of combining 7T MPMs, gene expression and white matter connections to provide an anatomically precise framework for tracking neurodegenerative disease.

Alteration of brain structural connectivity in progression of Parkinson's disease: A connectome-wide network analysis

Pinpointing the brain dysconnectivity in idiopathic rapid eye movement sleep behaviour disorder (iRBD) can facilitate preventing the conversion of Parkinson's disease (PD) from prodromal phase. Recent neuroimage investigations reported disruptive brain white matter connectivity in both iRBD and PD, respectively. However, the intrinsic process of the human brain structural network evolving from iRBD to PD still remains largely unknown. To address this issue, 151 participants including iRBD, PD and age-matched normal controls were recruited to receive diffusion MRI scans and neuropsychological examinations. The connectome-wide association analysis was performed to detect reorganization of brain structural network along with PD progression. Eight brain seed regions in both cortical and subcortical areas demonstrated significant structural pattern changes along with the progression of PD. Applying machine learning on the key connectivity related to these seed regions demonstrated better classification accuracy compared to conventional network-based statistic. Our study shows that connectome-wide association analysis reveals the underlying structural connectivity patterns related to the progression of PD, and provide a promising distinct capability to predict prodromal PD patients.

The potential role of leukoaraiosis in remodeling the brain network to buffer cognitive decline: a Leukoaraiosis And Disability study from Alzheimer's Disease Neuroimaging Initiative.

Leukoaraiosis (LA) is a phenomenon of the brain that is often observed in elderly people. However, little is known about the role of LA in cognitive impairment in neurodegeneration and disease. This cross-sectional, retrospective Leukoaraiosis And Disability (LADIS) study aimed to characterize the relationship between brain white matter connectivity properties with LA ratings in patients with Alzheimer's disease (AD) as compared with age-matched cognitively normal controls. Patients with AD (n=76) and elderly individuals with normal cognitive (NC) function (n=82) were classified into 3 groups, LA1, LA2, and LA3, according to the rating of their white matter changes (WMCs). Diffusion tensor imaging (DTI) data were analyzed by quantifying and comparing the white matter connectivity properties and gray matter (GM) volume of brain regions of interest (ROIs). The rich-club network properties in the AD LA1 and LA2 groups showed significant patterns of disrupted peripheral regions and reduced connectivity compared to those in the NC LA1 and LA2 groups, respectively. However, the rich-club network properties in the AD LA3 group showed similar patterns of disrupted peripheral regions and reduced connectivity compared to those in the NC LA3 group, despite there being significant hippocampal and amygdala atrophic differences between AD patients and NC elders. Compared to the NC LA1 group, the characteristic path length of white matter fiber connectivity in the NC LA3 group was significantly increased, and the brain's global efficiency, clustering coefficient, and network connectivity strength were significantly reduced (P<0.05, respectively). However, no significant differences (P>0.05) were observed in characteristic path length, reduced global efficiency, or the clustering coefficient between the NC LA3 and AD LA1 groups, or between the NC LA3 and AD LA2 groups. Our findings offer some insights into a potential role of LA in cognitive impairment that may predict the development of disability in older adults. The occurrence of LA, an intermediate degenerative change, during neurodegeneration and disease may potentially lead to the remodeling of the brain network through brain plasticity. LA, therefore, representing a possible compensatory mechanism to buffer cognitive decline.

Obsessive-Compulsive Symptoms Among Children in the Adolescent Brain and Cognitive Development Study: Clinical, Cognitive, and Brain Connectivity Correlates

BackgroundChildhood obsessive-compulsive symptoms (OCSs) are common and can be an early risk marker for obsessive-compulsive disorder. The Adolescent Brain and Cognitive Development (ABCD) Study provides a unique opportunity to characterize OCSs in a large normative sample of school-age children and to explore corticostriatal and task-control circuits implicated in pediatric obsessive-compulsive disorder. MethodsThe ABCD Study acquired data from 9- and 10-year-olds (N = 11,876). Linear mixed-effects models probed associations between OCSs (Child Behavior Checklist) and cognition (NIH Toolbox), brain structure (subcortical volume, cortical thickness), white matter (diffusion tensor imaging), and resting-state functional connectivity. ResultsOCS scores showed good psychometric properties and high prevalence, and they were related to familial/parental factors, including family conflict. Higher OCS scores related to better cognitive performance (β = .06, t9966.60 = 6.28, p < .001, ηp2= .01), particularly verbal, when controlling for attention-deficit/hyperactivity disorder, which related to worse performance. OCSs did not significantly relate to brain structure but did relate to lower superior corticostriatal tract fractional anisotropy (β = −.03, t = −3.07, p = .002, ηp2= .02). Higher OCS scores were related to altered functional connectivity, including weaker connectivity within the dorsal attention network (β = −.04, t7262.87 = −3.71, p < .001, ηp2= .002) and weaker dorsal attention–default mode anticorrelation (β = .04, t7251.95 = 3.94, p < .001, ηp2 = .002). Dorsal attention–default mode connectivity predicted OCS scores at 1 year (β = −.04, t2407.61 = −2.23, p = .03, ηp2 = .03). ConclusionsOCSs are common and may persist throughout childhood. Corticostriatal connectivity and attention network connectivity are likely mechanisms in the subclinical-to-clinical spectrum of OCSs. Understanding correlates and mechanisms of OCSs may elucidate their role in childhood psychiatric risk and suggest potential utility of neuroimaging, e.g., dorsal attention–default mode connectivity, for identifying children at increased risk for obsessive-compulsive disorder.