Geometrically accurate topology-correction of cortical surfaces using nonseparating loops

Light intensity physical activity is beneficially associated with brain volume in older adults with high cardiovascular risk

Background

Older people with high cardiovascular risk, including those without cardiovascular diseases, are an at-risk population for dementia. Regular physical activity is generally recommended to maintain brain health; however, the optimal intensity of physical activity for maintaining brain volume in older adults with cardiovascular risk remains unclear. We examined the associations between intensity-specific physical activity and brain volume stratified by absolute cardiovascular risk level in older adults without cardiovascular diseases.

Methods and results

This cross-sectional study involved 725 community-dwelling older Japanese adults without cardiovascular diseases. We estimated absolute cardiovascular risk using the World Health Organization risk estimation charts, which include variables such as age, sex, diabetes mellitus, smoking, systolic blood pressure, and total cholesterol, and stratified cardiovascular risk level into three risk categories: low (≤ 9%), moderate (10–14%), and high (≥15%). We measured daily physical activity using a triaxial accelerometer, and calculated the average time spent in moderate-to-vigorous intensity physical activity (MVPA) and light intensity physical activity (LPA). We performed brain T1-weighted magnetic resonance imaging and calculated the volume of the cortical gray matter, subcortical gray matter, and cerebral white matter, using the FreeSurfer software. In the overall sample, multivariable linear regression analysis showed that greater MVPA was significantly associated with greater volume of the cortical gray matter and cerebral white matter, and greater LPA was significantly associated with greater volume of the cerebral white matter. Additionally, in the analysis of the sample stratified by absolute cardiovascular risk level, cerebral white matter volume was significantly associated with both MVPA and LPA in the high cardiovascular risk group.

Conclusions

The association between physical activity and brain volume differed according to cardiovascular risk level in community-dwelling older adults. In a population at high cardiovascular risk, maintaining or increasing LPA might be a practical and achievable strategy for healthy brain aging.

Story Memory Impairment Rates and Association with Hippocampal Volumes in a Memory Clinic Population

OBJECTIVE

Story memory tasks are among the most commonly used memory tests; however, research suggests they may be less sensitive to memory decline and have a weaker association with hippocampal volumes than list learning tasks. To examine its utility, we compared story memory to other memory tests on impairment rates and association with hippocampal volumes.

METHOD

Archival records from 1617 older adults (M_age = 74.41, range = 65-93) who completed the Wechsler Memory Scale - 4^th edition (WMS-IV) Logical Memory (LM), Hopkins Verbal Learning Test - Revised (HVLT-R), and Brief Visuospatial Memory Test - Revised (BVMT-R) as part of a clinical neuropsychological evaluation were reviewed. Scores >1.5 SD below age-adjusted means were considered impaired, and frequency distributions were used to examine impairment rates. A subset of participants (n = 179) had magnetic resonance imaging (MRI) data that underwent image quality assessment. Partial correlations and linear regression analyses, accounting for age, education, and total intracranial volume (TIV), examined associations between memory raw scores and hippocampal volumes.

RESULTS

For delayed recall, nearly half of the sample was impaired on HVLT-R (48.8%) and BVMT-R (46.1%), whereas a little more than a third was impaired on LM (35.7%). Better performance on all three measures was related to larger hippocampal volumes (r's =. 26-.43, p's < .001). Individually adding memory scores to regression models predicting hippocampal volumes improved the model fit for all measures.

CONCLUSIONS

Despite findings suggesting that story memory is less sensitive to memory dysfunction, it was not differentially associated with hippocampal volumes compared to other memory measures. Results support assessing memory using different formats and modalities in older adults.

Fibromyalgia impact in the prefrontal cortex subfields: An assessment with MRI

INTRODUCTION

Previous studies have associated brain abnormalities in people with fibromyalgia with accelerated brain ageing. The prefrontal cortex is located in the anterior pole of the mammalian brain. It is defined as the part of the cerebral cortex that receives projections from the mediodorsal nucleus of the thalamus.

AIM

This study aimed to evaluate the volumetric differences in the prefrontal cortex subfields between healthy women and women with fibromyalgia using magnetic resonance imaging (MRI) and controlling for age, estimated intracranial volume, depression, and cognitive impairment.

MATERIAL AND METHODS

A total of 47 women with fibromyalgia (recruited from a fibromyalgia local association) and 43 healthy women (retrieved from the Open Access Series of Imaging Studies database) participated in this cross-sectional study. Multiple linear regressions were used to predict the value of the prefrontal cortex subfields as well as to determine if there were volumetric differences between the groups.

RESULTS

Volume of all prefrontal cortex regions decreased with each year of age. Healthy women showed higher volume in all the prefrontal cortex subfields than women with fibromyalgia. Regarding partial correlations performed, no significant relation were found between the fibromyalgia impact and the brain volumes analyzed, controlling for depression.

CONCLUSIONS

Women with fibromyalgia showed reduced volume in the right caudal middle frontal gyrus, rostral middle frontal gyrus, left inferior frontal gyrus pars opercularis, inferior frontal gyrus pars triangularis, inferior frontal gyrus pars orbitalis, lateral orbitofrontal cortex, right medial orbitofrontal cortex, right rostral anterior cingulate gyrus subfields of the prefrontal cortex and total gray matter compared to healthy women. Furthermore, through an analysis of multiple linear regressions, the left rostral middle frontal gyrus and left lateral orbitofrontal cortex showed significantly volumetric decreases related to depression levels. The total gray matter also shows a significant decrease related to age observed through the analysis of multiple linear regressions. No significant relation were found between the impact of the disease and the brain volumes analyzed, controlling for depression in women with fibromyalgia.

Neuroimaging and cognitive correlates of retinal Optical Coherence Tomography (OCT) measures at late middle age in a twin sample

Sharing in embryology and function between the eye and brain has led to interest in whether assessments of the eye reflect brain changes seen in neurodegeneration. We aimed to examine the associations between measures of retinal layer thickness using optical coherence tomography (OCT) and multimodal measures of brain structure and function. Using a convenient sample of twins discordant for type 2 diabetes, we performed cognitive testing, structural brain MRI (tissue volumetry), diffusion tensor imaging (white matter microstructure), and arterial spin labelling (cerebral blood flow). OCT images were recorded and retinal thickness maps generated. We used mixed level modelling to examine the relationship between retinal layer thicknesses and brain measures. We enrolled 35 people (18 pairs, mean age 63.8 years, 63% female). Ganglion cell layer thickness was positively associated with memory, speed, gray matter volume, and altered mean diffusivity. Ganglion cell layer thickness was strongly positively associated with regional cerebral blood flow. We found only a limited number of associations between other retinal layer thickness and measures of brain structure or function. Ganglion cell layer thickness showed consistent associations with a range of brain measures suggesting it may have utility as a marker for future dementia risk.

Structural connectivity and intelligence in brain-injured children

In children, higher general intelligence corresponds with better processing speed ability. However, the relationship between structural brain connectivity and processing speed in the context of intelligence is unclear. Furthermore, the impact of brain injury on this relationship is also unknown. Structural networks were constructed for 36 brain tumor patients (mean age: 13.45 ± 2.73, 58% males) and 35 typically developing children (13.30 ± 2.86, 51% males). Processing speed and general intelligence scores were acquired using standard batteries. The relationship between network properties, processing speed, and intelligence was assessed using a partial least squares analysis. Results indicated that structural networks in brain-injured children were less integrated (β = -.38, p = 0.001) and more segregated (β = 0.4, p = 0.0005) compared to typically developing children. There was an indirect effect of network segregation on general intelligence via processing speed, where greater network segregation predicted slower processing speed which in turn predicted worse general intelligence (GoF = 0.37). These findings provide the first evidence of relations between structural connectivity, processing speed, and intelligence in children. Injury-related disruption to the structural network may result in worse intelligence through impacts on information processing. Our findings are discussed in the context of a network approach to understanding brain-behavior relationships.

Individual Differences in Hemispheric Emotional Valence by Computerized Test Correlate with Lateralized Differences in Nucleus Accumbens, Hippocampal and Amygdala Volumes

Purpose

Conventional theories of hemispheric emotional valence (HEV) postulate fixed hemispheric differences in emotional processing. Schiffer’s dual brain psychology proposes that there are prominent individual differences with a substantial subset showing a reversed laterality pattern. He further proposed that hemispheric differences were more akin to differences in personality than in emotional processing. This theory is supported by findings that unilateral treatments, such as transcranial magnetic stimulation, are effective if they accurately target individual differences in laterality. The aim of this paper was to assess if a computer test of hemispheric emotional valence (CTHEV) could effectively identify individual differences in HEV and to ascertain if these individual differences were associated with underlying differences in brain structure and connectivity.

Patients and Methods

The CTHEV was administered to 50 (18 male/32 female) right-handed participants, aged 18–19 years, enrolled in a study assessing the neurobiological effects of childhood maltreatment. Based on a literature review, we determined whether CTHEV correlated with lateralized volumes of the nucleus accumbens, amygdala, hippocampus, and subgenual anterior cingulate as well as volume of the corpus callosum.

Results

CTHEV scores correlated with laterality indices of the nucleus accumbens (p = 0.00016), amygdala (p = 0.0138) and hippocampus (p = 0.031). A positive left hemispheric valence was associated with a larger left-sided nucleus accumbens and hippocampus and a smaller left amygdala. We identified four eigenvector network centrality DTI measures that predict CTHEV, most notably the left amygdala, and found that CTHEV results correlated with total and segment-specific corpus callosal volumes.

Conclusion

Individual differences in HEV can be readily assessed by computer test and correlate with differences in brain structure and connectivity that could provide a mechanistic understanding. These findings provide further support for a revised understanding of HEV and provide a tool that could be used to guide lateralized brain treatments.

Combining MRI and cognitive evaluation to classify concussion in university athletes

Current methods of concussion assessment lack the objectivity and reliability to detect neurological injury. This multi-site study uses combinations of neuroimaging (diffusion tensor imaging and resting state functional MRI) and cognitive measures to train algorithms to detect the presence of concussion in university athletes. Athletes (29 concussed, 48 controls) completed symptom reports, brief cognitive evaluation, and MRI within 72 h of injury. Hierarchical linear regression compared groups on cognitive and neuroimaging measures while controlling for sex and data collection site. Logistic regression and support vector machine models were trained using cognitive and neuroimaging measures and evaluated for overall accuracy, sensitivity, and specificity. Concussed athletes reported greater symptoms than controls (∆R² = 0.32, p < .001), and performed worse on tests of concentration (∆R² = 0.07, p < .05) and delayed memory (∆R² = 0.17, p < .001). Concussed athletes showed lower functional connectivity within the frontoparietal and primary visual networks (p < .05), but did not differ on mean diffusivity and fractional anisotropy. Of the cognitive measures, classifiers trained using delayed memory yielded the best performance with overall accuracy of 71%, though sensitivity was poor at 46%. Of the neuroimaging measures, classifiers trained using mean diffusivity yielded similar accuracy. Combining cognitive measures with mean diffusivity increased overall accuracy to 74% and sensitivity to 64%, comparable to the sensitivity of symptom report. Trained algorithms incorporating both MRI and cognitive performance variables can reliably detect common neurobiological sequelae of acute concussion. The integration of multi-modal data can serve as an objective, reliable tool in the assessment and diagnosis of concussion.

Microstructural alterations predict impaired bimanual control in Parkinson’s disease

Bimanual coordination is impaired in Parkinson’s disease affecting patients’ ability to perform activities of daily living and to maintain independence. Conveyance of information between cortical and subcortical areas is essential for bimanual coordination and relies on the integrity of cerebral microstructure. As pathological deposition of alpha-synuclein compromises microstructure in Parkinson’s disease, we investigated the relationship between microstructural integrity and bimanual coordination using diffusion-weighted MRI in 23 patients with Parkinson’s disease (mean age ± standard deviation: 56.0 ± 6.45 years; 8 female) and 26 older adults (mean age ± standard deviation: 58.5 ± 5.52 years). Whole-brain analysis revealed specific microstructural alterations between patients and healthy controls matched for age, sex, handedness, and cognitive status congruent with the literature and known Parkinson’s disease pathology. A general linear model revealed distinct microstructural alterations associated with poor bimanual coordination in Parkinson’s disease, corrected for multiple comparisons using a permutation-based approach. Integrating known functional topography, we conclude that distinct changes in microstructure cause an impediment of structures involved in attention, working memory, executive function, motor planning, motor control, and visual processing contributing to impaired bimanual coordination in Parkinson’s disease.

Association of DNA Methylation of the NLRP3 Gene with Changes in Cortical Thickness in Major Depressive Disorder

The Nod-like receptor pyrin containing 3 (NLRP3) inflammasome has been reported to be a convergent point linking the peripheral immune response induced by psychological stress and neuroinflammatory processes in the brain. We aimed to identify differences in the methylation profiles of the NLRP3 gene between major depressive disorder (MDD) patients and healthy controls (HCs). We also investigated the correlation of the methylation score of loci in NLRP3 with cortical thickness in the MDD group using magnetic resonance imaging (MRI) data. A total of 220 patients with MDD and 82 HCs were included in the study, and genome-wide DNA methylation profiling of the NLRP3 gene was performed. Among the total sample, 88 patients with MDD and 74 HCs underwent T1-weighted structural MRI and were included in the neuroimaging–methylation analysis. We identified five significant differentially methylated positions (DMPs) in NLRP3. In the MDD group, the methylation scores of cg18793688 and cg09418290 showed significant positive or negative correlations with cortical thickness in the occipital, parietal, temporal, and frontal regions, which showed significant differences in cortical thickness between the MDD and HC groups. Our findings suggest that NLRP3 DNA methylation may predispose to depression-related brain structural changes by increasing NLRP3 inflammasome-related neuroinflammatory processes in MDD.

Brain network connectivity feature extraction using deep Learning for Alzheimer's disease classification

Early diagnosis and therapeutic intervention for Alzheimer's disease (AD) is currently the only viable option for improving clinical outcomes. Combining structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imaging (rs-fMRI) to diagnose AD has yielded promising results. Most studies assume fixed time lags when constructing functional networks. Since the propagation delays between brain signals are constantly changing, these methods cannot reflect more detailed relationships between brain regions. In this work, we use a deep learning-based Granger causality estimator for brain connectivity construction. It exploits the strength of long short-term memory in ever-changing time series processing. This research involves data analysis from sMRI and rs-fMRI. We use sMRI to analyze the cerebral cortex properties and use rs-fMRI to analyze the graph metrics of functional networks. We extract a small subset of optimal features from both types of data. A support vector machine (SVM) is trained and tested to classify AD (n=27) from healthy controls (n=20) using rs-fMRI and sMRI features. Using a subset of optimal features in SVM, we achieve a classification accuracy of 87.23% for sMRI, 78.72% for rs-fMRI, and 91.49% for combined sMRI with rs-fMRI. The results show the potential to identify AD from healthy controls by integrating rs-fMRI and sMRI. The integration of sMRI and rs-fMRI modalities can provide supplemental information to improve the diagnosis of AD relative to either the sMRI or fMRI modalities alone.

The sexual brain, genes, and cognition: A machine-predicted brain sex score explains individual differences in cognitive intelligence and genetic influence in young children

Sex impacts the development of the brain and cognition differently across individuals. However, the literature on brain sex dimorphism in humans is mixed. We aim to investigate the biological underpinnings of the individual variability of sexual dimorphism in the brain and its impact on cognitive performance. To this end, we tested whether the individual difference in brain sex would be linked to that in cognitive performance that is influenced by genetic factors in prepubertal children (N = 9,658, ages 9-10 years old; the Adolescent Brain Cognitive Development study). To capture the interindividual variability of the brain, we estimated the probability of being male or female based on the brain morphometry and connectivity features using machine learning (herein called a brain sex score). The models accurately classified the biological sex with a test ROC-AUC of 93.32%. As a result, a greater brain sex score correlated significantly with greater intelligence (p_fdr  < .001, η p 2 $$ {\eta}_p^2 $$  = .011-.034; adjusted for covariates) and higher cognitive genome-wide polygenic scores (GPSs) (p_fdr  < .001, η p 2 $$ {\eta}_p^2 $$  < .005). Structural equation models revealed that the GPS-intelligence association was significantly modulated by the brain sex score, such that a brain with a higher maleness score (or a lower femaleness score) mediated a positive GPS effect on intelligence (indirect effects = .006-.009; p = .002-.022; sex-stratified analysis). The finding of the sex modulatory effect on the gene-brain-cognition relationship presents a likely biological pathway to the individual and sex differences in the brain and cognitive performance in preadolescence.

Shared and unique brain network features predict cognitive, personality, and mental health scores in the ABCD study

How individual differences in brain network organization track behavioral variability is a fundamental question in systems neuroscience. Recent work suggests that resting-state and task-state functional connectivity can predict specific traits at the individual level. However, most studies focus on single behavioral traits, thus not capturing broader relationships across behaviors. In a large sample of 1858 typically developing children from the Adolescent Brain Cognitive Development (ABCD) study, we show that predictive network features are distinct across the domains of cognitive performance, personality scores and mental health assessments. On the other hand, traits within each behavioral domain are predicted by similar network features. Predictive network features and models generalize to other behavioral measures within the same behavioral domain. Although tasks are known to modulate the functional connectome, predictive network features are similar between resting and task states. Overall, our findings reveal shared brain network features that account for individual variation within broad domains of behavior in childhood.

Advanced Brain-Age in Psychotic Psychopathology: Evidence for Transdiagnostic Neurodevelopmental Origins

Schizophrenia is characterized by abnormal brain structure such as global reductions in gray matter volume. Machine learning models trained to estimate the age of brains from structural neuroimaging data consistently show advanced brain-age to be associated with schizophrenia. Yet, it is unclear whether advanced brain-age is specific to schizophrenia compared to other psychotic disorders, and whether evidence that brain structure is "older" than chronological age actually reflects neurodevelopmental rather than atrophic processes. It is also unknown whether advanced brain-age is associated with genetic liability for psychosis carried by biological relatives of people with schizophrenia. We used the Brain-Age Regression Analysis and Computation Utility Software (BARACUS) prediction model and calculated the residualized brain-age gap of 332 adults (163 individuals with psychotic disorders: 105 schizophrenia, 17 schizoaffective disorder, 41 bipolar I disorder with psychotic features; 103 first-degree biological relatives; 66 controls). The model estimated advanced brain-ages for people with psychosis in comparison to controls and relatives, with no differences among psychotic disorders or between relatives and controls. Specifically, the model revealed an enlarged brain-age gap for schizophrenia and bipolar disorder with psychotic features. Advanced brain-age was associated with lower cognitive and general functioning in the full sample. Among relatives, cognitive performance and schizotypal symptoms were related to brain-age gap, suggesting that advanced brain-age is associated with the subtle expressions associated with psychosis. Exploratory longitudinal analyses suggested that brain aging was not accelerated in individuals with a psychotic disorder. In sum, we found that people with psychotic disorders, irrespective of specific diagnosis or illness severity, show indications of non-progressive, advanced brain-age. These findings support a transdiagnostic, neurodevelopmental formulation of structural brain abnormalities in psychotic psychopathology.

Neuropathological fingerprints of survival, atrophy and language in primary progressive aphasia

Primary progressive aphasia is a neurodegenerative disease that selectively impairs language without equivalent impairment of speech, memory or comportment. In 118 consecutive autopsies on patients with primary progressive aphasia, primary diagnosis was Alzheimer's disease neuropathological changes (ADNC) in 42%, corticobasal degeneration or progressive supranuclear palsy neuropathology in 24%, Pick's disease neuropathology in 10%, transactive response DNA binding proteinopathy type A [TDP(A)] in 10%, TDP(C) in 11% and infrequent entities in 3%. Survival was longest in TDP(C) (13.2 ± 2.6 years) and shortest in TDP(A) (7.1 ± 2.4 years). A subset of 68 right-handed participants entered longitudinal investigations. They were classified as logopenic, agrammatic/non-fluent or semantic by quantitative algorithms. Each variant had a preferred but not invariant neuropathological correlate. Seventy-seven per cent of logopenics had ADNC, 56% of agrammatics had corticobasal degeneration/progressive supranuclear palsy or Pick's disease and 89% of semantics had TDP(C). Word comprehension impairments had strong predictive power for determining underlying neuropathology positively for TDP(C) and negatively for ADNC. Cortical atrophy was smallest in corticobasal degeneration/progressive supranuclear palsy and largest in TDP(A). Atrophy encompassed posterior frontal but not temporoparietal cortex in corticobasal degeneration/progressive supranuclear palsy, anterior temporal but not frontoparietal cortex in TDP(C), temporofrontal but not parietal cortex in Pick's disease and all three lobes with ADNC or TDP(A). There were individual deviations from these group patterns, accounting for less frequent clinicopathologic associations. The one common denominator was progressive asymmetric atrophy overwhelmingly favouring the left hemisphere language network. Comparisons of ADNC in typical amnestic versus atypical aphasic dementia and of TDP in type A versus type C revealed fundamental biological and clinical differences, suggesting that members of each pair may constitute distinct clinicopathologic entities despite identical downstream proteinopathies. Individual TDP(C) participants with unilateral left temporal atrophy displayed word comprehension impairments without additional object recognition deficits, helping to dissociate semantic primary progressive aphasia from semantic dementia. When common and uncommon associations were considered in the set of 68 participants, one neuropathology was found to cause multiple clinical subtypes, and one subtype of primary progressive aphasia to be caused by multiple neuropathologies, but with different probabilities. Occasionally, expected clinical manifestations of atrophy sites were absent, probably reflecting individual peculiarities of language organization. The hemispheric asymmetry of neurodegeneration and resultant language impairment in primary progressive aphasia reflect complex interactions among the cellular affinities of the degenerative disease, the constitutive biology of language cortex, familial or developmental vulnerabilities of this network and potential idiosyncrasies of functional anatomy in the affected individual.

Accelerated longitudinal cortical atrophy in OEF / OIF / OND veterans with severe PTSD and the impact of comorbid TBI

Veterans who deployed in support of Operation Enduring Freedom (OEF), Iraqi Freedom (OIF), and New Dawn (OND) commonly experience severe psychological trauma, often accompanied by physical brain trauma resulting in mild traumatic brain injury (mTBI). Prior studies of individuals with posttraumatic stress disorder (PTSD) have revealed alterations in brain structure, accelerated cellular aging, and impacts on cognition following exposure to severe psychological trauma and potential interactive effects of military‐related mTBI. To date, however, little is known how such deployment‐related trauma changes with time and age of injury of the affected veteran. In this study, we explored changes in cortical thickness, volume, and surface area after an average interval of approximately 2 years in a cohort of 254 OEF/OIF/OND Veterans ranging in age from 19 to 67 years. Whole‐brain vertex‐wise analyses revealed that veterans who met criteria for severe PTSD (Clinician‐Administered PTSD Scale ≥60) at baseline showed greater negative longitudinal changes in cortical thickness, volume, and area over time. Analyses also revealed a significant severe‐PTSD by age interaction on cortical measures with severe‐PTSD individuals exhibiting accelerated cortical degeneration with increasing age. Interaction effects of comorbid military‐related mTBI within the severe‐PTSD group were also observed in several cortical regions. These results suggest that those exhibiting severe PTSD symptomatology have accelerated atrophy that is exacerbated with increasing age and history of mTBI.

Do aggregate, multimodal structural neuroimaging measures replicate regional developmental differences observed in highly cited cellular histological studies?

Influential investigations of postmortem human brain tissue showed regional differences in tissue properties at early phases of development, such as between prefrontal and primary sensory cortical regions. Large-scale neuroimaging studies enable characterization of age-related trajectories with much denser sampling of cortical regions, assessment ages, and demographic variables than postmortem tissue analyses, but no single imaging measure perfectly captures what is measured with histology. Using publicly available data from the Pediatric Imaging, Neurocognition, and Genetics (PING) study, including 951 participants with ages ranging from 3 to 21 years, we characterized cortical regional variability in developmental trajectories of multimodal brain imaging measures. Multivariate analyses integrated morphometric and microstructural cortical surface measures. To replicate foundational histological work showing delayed synapse elimination in middle frontal gyrus relative to primary sensory areas, we tested whether developmental trajectories differ between prefrontal and visual or auditory cortex. We extended this to a whole-cortex analysis of interregional differences, producing cortical parcellations with maximally different developmental trajectories. Consistent with the general conclusions of postmortem analyses, our imaging results suggest that prefrontal regions show a protracted period of greater developmental change; however, they also illustrate the challenges of drawing conclusions about the relative maturational phases of different brain regions.

•

Multimodal, multivariate, nonlinear modeling, integrating morphometric and microstructural measures.

•

Tested regional developmental differences previously found in highly influential cellular histological studies.

•

Produced cortical parcellations with maximally different, multimodal, developmental trajectories.

•

Findings converge with evidence from histological studies showing delayed prefrontal cortical development.

•

Interregional differences vary by measure and illustrate complexities of defining which regions mature first.

Beta-amyloid moderates the relationship between cortical thickness and attentional control in middle- and older-aged adults

Although often unmeasured in studies of cognition, many older adults possess Alzheimer disease (AD) pathologies such as beta-amyloid (Aβ) deposition, despite being asymptomatic. We were interested in examining whether the behavior-structure relationship observed in later life was altered by the presence of preclinical AD pathology. A total of 511 cognitively unimpaired adults completed magnetic resonance imaging and three attentional control tasks; a subset (n = 396) also underwent Aβ-positron emissions tomography. A vertex-wise model was conducted to spatially represent the relationship between cortical thickness and average attentional control accuracy, while moderation analysis examined whether Aβ deposition impacted this relationship. First, we found that reduced cortical thickness in temporal, medial- and lateral-parietal, and dorsolateral prefrontal cortex, predicted worse performance on the attention task composite. Subsequent moderation analyses observed that levels of Aβ significantly influence the relationship between cortical thickness and attentional control. Our results support the hypothesis that preclinical AD, as measured by Aβ deposition, is partially driving what would otherwise be considered general aging in a cognitively normal adult population.

Caltech Conte Center, a multimodal data resource for exploring social cognition and decision-making

This data release of 117 healthy community-dwelling adults provides multimodal high-quality neuroimaging and behavioral data for the investigation of brain-behavior relationships. We provide structural MRI, resting-state functional MRI, movie functional MRI, together with questionnaire-based and task-based psychological variables; many of the participants have multiple datasets from retesting over the course of several years. Our dataset is distinguished by utilizing open-source data formats and processing tools (BIDS, FreeSurfer, fMRIPrep, MRIQC), providing data that is thoroughly quality checked, preprocessed to various extents and available in multiple anatomical spaces. A customizable denoising pipeline is provided as open-source code that includes tools for the generation of functional connectivity matrices and initialization of individual difference analyses. Behavioral data include a comprehensive set of psychological assessments on gold-standard instruments encompassing cognitive function, mood and personality, together with exploratory factor analyses. The dataset provides an in-depth, multimodal resource for investigating associations between individual differences, brain structure and function, with a focus on the domains of social cognition and decision-making.

Brain Atrophy and Clinical Characterization of Adults With Mild Cognitive Impairment and Different Cerebrospinal Fluid Biomarker Profiles According to the AT(N) Research Framework of Alzheimer’s Disease

Introduction

This study aimed to evaluate, in adults with mild cognitive impairment (MCI), the brain atrophy that may distinguish between three AT(N) biomarker-based profiles, and to determine its clinical value.

Methods

Structural MRI (sMRI) was employed to evaluate the volume and cortical thickness differences in MCI patients with different AT(N) profiles, namely, A−T−(N)−: normal AD biomarkers; A+T−(N)−: AD pathologic change; and A+T+(N)+: prodromal AD. Sensitivity and specificity of these changes were also estimated.

Results

An initial atrophy in medial temporal lobe (MTL) areas was found in the A+T−(N)− and A+T+(N)+ groups, spreading toward the parietal and frontal regions in A+T+(N)+ patients. These structural changes allowed distinguishing AT(N) profiles within the AD continuum; however, the profiles and their pattern of neurodegeneration were unsuccessful to determine the current clinical status.

Conclusion

sMRI is useful in the determination of the specific brain structural changes of AT(N) profiles along the AD continuum, allowing differentiation between MCI adults with or without pathological AD biomarkers.

Machine learning classification of schizophrenia patients and healthy controls using diverse neuroanatomical markers and Ensemble methods

Schizophrenia is a major psychiatric disorder that imposes enormous clinical burden on patients and their caregivers. Determining classification biomarkers can complement clinical measures and improve understanding of the neural basis underlying schizophrenia. Using neuroanatomical features, several machine learning based investigations have attempted to classify schizophrenia from healthy controls but the range of neuroanatomical measures employed have been limited in range to date. In this study, we sought to classify schizophrenia and healthy control cohorts using a diverse set of neuroanatomical measures (cortical and subcortical volumes, cortical areas and thickness, cortical mean curvature) and adopted Ensemble methods for better performance. Additionally, we correlated such neuroanatomical features with Quality of Life (QoL) assessment scores within the schizophrenia cohort. With Ensemble methods and diverse neuroanatomical measures, we achieved classification accuracies ranging from 83 to 87%, sensitivities and specificities varying between 90-98% and 65-70% respectively. In addition to lower QoL scores within schizophrenia cohort, significant correlations were found between specific neuroanatomical measures and psychological health, social relationship subscale domains of QoL. Our results suggest the utility of inclusion of subcortical and cortical measures and Ensemble methods to achieve better classification performance and their potential impact of parsing out neurobiological correlates of quality of life in schizophrenia.

Association of blood pressure with brain structure in youth with and without bipolar disorder

BACKGROUND

We previously found that blood pressure (BP) is elevated, and associated with poorer neurocognition, in youth with bipolar disorder (BD). While higher BP is associated with smaller brain structure in adults, studies have not examined this topic in BD or youth.

METHODS

Participants were 154 youth, ages 13-20 (n = 81 BD, n = 73 HC). Structural magnetic resonance imaging and diastolic (DBP), and systolic (SBP) pressure were obtained. Region of interest (ROI; anterior cingulate cortex [ACC], insular cortex, hippocampus) and vertex-wise analyses controlling for age, sex, body-mass-index, and intracranial volume investigated BP-neurostructural associations; a group-by-BP interaction was also assessed.

RESULTS

In ROI analyses, higher DBP in the overall sample was associated with smaller insular cortex area (β=-0.18 p = 0.007) and was associated with smaller ACC area to a significantly greater extent in HC vs. BD (β=-0.14 p = 0.015). In vertex-wise analyses, higher DBP and SBP were associated with smaller area and volume in the insular cortex, frontal, parietal, and temporal regions in the overall sample. Additionally, higher SBP was associated with greater thickness in temporal and parietal regions. Finally, higher SBP was associated with smaller area and volume in frontal, parietal, and temporal regions to a significantly greater extent in BD vs. HC.

LIMITATIONS

Cross-sectional design, single assessment of BP.

CONCLUSION

BP is associated with brain structure in youth, with variability related to structural phenotype (volume vs. thickness) and psychiatric diagnosis (BD vs. HC). Future studies evaluating temporality of these findings, and the association of BP changes on brain structure in youth, are warranted.

Cortical Thickness and Clinical Findings in Prescholar Children With Autism Spectrum Disorder

The term autism spectrum disorder (ASD) includes a wide variability of clinical presentation, and this clinical heterogeneity seems to reflect a still unclear multifactorial etiopathogenesis, encompassing different genetic risk factors and susceptibility to environmental factors. Several studies and many theories recognize as mechanisms of autism a disruption of brain development and maturation time course, suggesting the existence of common neurobiological substrates, such as defective synaptic structure and aberrant brain connectivity. Magnetic resonance imaging (MRI) plays an important role in both assessment of region-specific structural changes and quantification of specific alterations in gray or white matter, which could lead to the identification of an MRI biomarker. In this study, we performed measurement of cortical thickness in a selected well-known group of preschool ASD subjects with the aim of finding correlation between cortical metrics and clinical scores to understand the underlying mechanism of symptoms and to support early clinical diagnosis. Our results confirm that recent brain MRI techniques combined with clinical data can provide some useful information in defining the cerebral regions involved in ASD although large sample studies with homogeneous analytical and multisite approaches are needed.

Diversity of daily activities is associated with greater hippocampal volume

Greater engagement in a range of daily activities is associated with better cognitive functioning (Lee et al., Lee et al., 2020). The hippocampus, a subcortical brain structure implicated in learning, memory, spatial navigation and other aspects of cognitive functioning, may be structurally sensitive to exposure to and engagement with novel experiences and environments. The present study tested whether greater activity diversity, defined as the range of common daily activities engaged in and the proportion of time spent in each, is associated with larger hippocampal volume. Greater diversity of activities, as measured using daily diaries across an 8-day period, was related to greater hippocampal volume averaged across the left and right hemispheres, even when adjusting for estimated intracranial volume, total activity time, sociodemographic factors, and self-reported physical health. These findings are broadly consistent with nonhuman animal studies, demonstrating a link between enriched environments and structural changes to the hippocampus. Future longitudinal and experimental work can elucidate causal and directional relationships between diversity of daily activities and hippocampal volume.

Heart rate and heart rate variability in patients with chronic inflammatory joint disease: the role of pain duration and the insular cortex

Background

Chronic inflammatory joint diseases (CIJD) have been linked to increased cardiovascular morbidity and mortality. A decisive reason could be a dysregulation of the autonomic nervous system, which is responsible for the control of cardiovascular function. So far, the cause of changes in autonomic nervous system functions remains elusive. In this study, we investigate the role of chronic pain and the insular cortex in autonomic control of cardiac functioning in patients with CIJD.

Methods

We studied the autonomic nervous system through the assessment of heart rate and heart rate variability (HRV) at rest and under cognitive stimulation. Furthermore, we investigated insular cortex volume by performing surface-based brain morphometry with FreeSurfer. For this study, 47 participants were recruited, 22 individual age- and sex-matched pairs for the magnetic resonance imaging analyses and 14 for the HRV analyses. All available patients’ data were used for analysis.

Results

Pain duration was negatively correlated with the resting heart rate in patients with chronic inflammatory joint diseases (n = 20). In a multiple linear regression model including only CIJD patients with heart rate at rest as a dependent variable, we found a significant positive relationship between heart rate at rest and the volume of the left insular cortex and a significant negative relationship between heart rate at rest and the volume of the right insular cortex. However, we found no significant differences in HRV parameters or insular cortex volumes between both groups.

Conclusions

In this study we provide evidence to suggest insular cortex involvement in the process of ANS changes due to chronic pain in CIJD patients.

The study was preregistered with the German Clinical Trials Register (https://www.drks.de; DRKS00012791; date of registration: 28 July 2017).

Multiplex Connectome Changes across the Alzheimer’s Disease Spectrum Using Gray Matter and Amyloid Data

The organization of the Alzheimer’s disease (AD) connectome has been studied using graph theory using single neuroimaging modalities such as positron emission tomography (PET) or structural magnetic resonance imaging (MRI). Although these modalities measure distinct pathological processes that occur in different stages in AD, there is evidence that they are not independent from each other. Therefore, to capture their interaction, in this study we integrated amyloid PET and gray matter MRI data into a multiplex connectome and assessed the changes across different AD stages. We included 135 cognitively normal (CN) individuals without amyloid-β pathology (Aβ−) in addition to 67 CN, 179 patients with mild cognitive impairment (MCI) and 132 patients with AD dementia who all had Aβ pathology (Aβ+) from the Alzheimer’s Disease Neuroimaging Initiative. We found widespread changes in the overlapping connectivity strength and the overlapping connections across Aβ-positive groups. Moreover, there was a reorganization of the multiplex communities in MCI Aβ + patients and changes in multiplex brain hubs in both MCI Aβ + and AD Aβ + groups. These findings offer a new insight into the interplay between amyloid-β pathology and brain atrophy over the course of AD that moves beyond traditional graph theory analyses based on single brain networks.

Identification of Proprioceptive Thalamocortical Tracts in Children: Comparison of fMRI, MEG, and Manual Seeding of Probabilistic Tractography

Studying white matter connections with tractography is a promising approach to understand the development of different brain processes, such as proprioception. An emerging method is to use functional brain imaging to select the cortical seed points for tractography, which is considered to improve the functional relevance and validity of the studied connections. However, it is unknown whether different functional seeding methods affect the spatial and microstructural properties of the given white matter connection. Here, we compared functional magnetic resonance imaging, magnetoencephalography, and manual seeding of thalamocortical proprioceptive tracts for finger and ankle joints separately. We showed that all three seeding approaches resulted in robust thalamocortical tracts, even though there were significant differences in localization of the respective proprioceptive seed areas in the sensorimotor cortex, and in the microstructural properties of the obtained tracts. Our study shows that the selected functional or manual seeding approach might cause systematic biases to the studied thalamocortical tracts. This result may indicate that the obtained tracts represent different portions and features of the somatosensory system. Our findings highlight the challenges of studying proprioception in the developing brain and illustrate the need for using multimodal imaging to obtain a comprehensive view of the studied brain process.

Aging-Related Changes in Cortical Sources of Sleep Oscillatory Neural Activity Following Motor Learning Reflect Contributions of Cortical Thickness and Pre-sleep Functional Activity

Oscillatory neural activity during sleep, such as that in the delta and sigma bands, is important for motor learning consolidation. This activity is reduced with typical aging, and this reduction may contribute to aging-related declines in motor learning consolidation. Evidence suggests that brain regions involved in motor learning contribute to oscillatory neural activity during subsequent sleep. However, aging-related differences in regional contributions to sleep oscillatory activity following motor learning are unclear. To characterize these differences, we estimated the cortical sources of consolidation-related oscillatory activity using individual anatomical information in young and older adults during non-rapid eye movement sleep after motor learning and analyzed them in light of cortical thickness and pre-sleep functional brain activation. High-density electroencephalogram was recorded from young and older adults during a midday nap, following completion of a functional magnetic resonance imaged serial reaction time task as part of a larger experimental protocol. Sleep delta activity was reduced with age in a left-weighted motor cortical network, including premotor cortex, primary motor cortex, supplementary motor area, and pre-supplementary motor area, as well as non-motor regions in parietal, temporal, occipital, and cingulate cortices. Sleep theta activity was reduced with age in a similar left-weighted motor network, and in non-motor prefrontal and middle cingulate regions. Sleep sigma activity was reduced with age in left primary motor cortex, in a non-motor right-weighted prefrontal-temporal network, and in cingulate regions. Cortical thinning mediated aging-related sigma reductions in lateral orbitofrontal cortex and frontal pole, and partially mediated delta reductions in parahippocampal, fusiform, and lingual gyri. Putamen, caudate, and inferior parietal cortex activation prior to sleep predicted frontal and motor cortical contributions to sleep delta and theta activity in an age-moderated fashion, reflecting negative relationships in young adults and positive or absent relationships in older adults. Overall, these results support the local sleep hypothesis that brain regions active during learning contribute to consolidation-related neural activity during subsequent sleep and demonstrate that sleep oscillatory activity in these regions is reduced with aging.

The Role of Structure MRI in Diagnosing Autism

This study proposes a Computer-Aided Diagnostic (CAD) system to diagnose subjects with autism spectrum disorder (ASD). The CAD system identifies morphological anomalies within the brain regions of ASD subjects. Cortical features are scored according to their contribution in diagnosing a subject to be ASD or typically developed (TD) based on a trained machine-learning (ML) model. This approach opens the hope for developing a new CAD system for early personalized diagnosis of ASD. We propose a framework to extract the cerebral cortex from structural MRI as well as identifying the altered areas in the cerebral cortex. This framework consists of the following five main steps: (i) extraction of cerebral cortex from structural MRI; (ii) cortical parcellation to a standard atlas; (iii) identifying ASD associated cortical markers; (iv) adjusting feature values according to sex and age; (v) building tailored neuro-atlases to identify ASD; and (vi) artificial neural networks (NN) are trained to classify ASD. The system is tested on the Autism Brain Imaging Data Exchange (ABIDE I) sites achieving an average balanced accuracy score of 97±2%. This paper demonstrates the ability to develop an objective CAD system using structure MRI and tailored neuro-atlases describing specific developmental patterns of the brain in autism.

Fiber connectivity density mapping in end-stage renal disease patients: a preliminary study

Abnormal brain structural connectivity of end-stage renal disease(ESRD) is associated with cognitive impairment. However, the characteristics of cortical structural connectivity have not been investigated in ESRD patients. Here, we study structural connectivity of the entire cerebral cortex using a fiber connectivity density(FiCD) mapping method derived from diffusion tensor imaging(DTI) data of 25 ESRD patients and 20 healthy controls, and between-group differences were compared in a vertexwise manner. We also investigated the associations between these abnormal cortical connectivities and the clinical variables using Pearson correlation analysis and multifactor linear regression analysis. Our results demonstrated that the mean global FiCD value was significantly decreased in ESRD patients. Notably, FiCD values were significantly changed(decreased or increased) in certain cortical regions, which mainly involved the bilateral dorsolateral prefrontal cortex(DLPFC), inferior parietal cortex, lateral temporal cortex and middle occipital cortex. In ESRD patients, we found a trend of negative correlation between the increased FiCD values of bilateral middle frontal gyrus and serum creatinine, urea, parathyroid hormone(PTH) levels and dialysis duration. Only the white matter hyperintensity(WMH) scores were significantly negatively correlated with the global FiCD value in multifactor regression analysis. Our results suggested that ESRD patients exhibited extensive impaired cortical structural connectivity, which was related to the severity of WMHs. A compensation mechanism of cortical structural recombination may play a role in how the brain adapts to maintain optimal network function. Additionally, the serum creatinine, urea and PTH levels may be risk factors for brain structural network decompensation in ESRD patients.

Sex Differences in Brain and Cognition in de novo Parkinson's Disease

Background and Objective: Brain atrophy and cognitive impairment in neurodegenerative diseases are influenced by sex. We aimed to investigate sex differences in brain atrophy and cognition in de novo Parkinson's disease (PD) patients. Methods: Clinical, neuropsychological and T1-weighted MRI data from 205 PD patients (127 males: 78 females) and 69 healthy controls (40 males: 29 females) were obtained from the PPMI dataset. Results: PD males had a greater motor and rapid eye movement sleep behavior disorder symptomatology than PD females. They also showed cortical thinning in postcentral and precentral regions, greater global cortical and subcortical atrophy and smaller volumes in thalamus, caudate, putamen, pallidum, hippocampus, and brainstem, compared with PD females. Healthy controls only showed reduced hippocampal volume in males compared to females. PD males performed worse than PD females in global cognition, immediate verbal recall, and mental processing speed. In both groups males performed worse than females in semantic verbal fluency and delayed verbal recall; as well as females performed worse than males in visuospatial function. Conclusions: Sex effect in brain and cognition is already evident in de novo PD not explained by age per se, being a relevant factor to consider in clinical and translational research in PD.

Neural Correlates of Traumatic Brain Injury in Women Survivors of Intimate Partner Violence: A Structural and Functional Connectivity Neuroimaging Study

OBJECTIVE

More than one-third of women in the United States experience intimate partner violence (IPV) in their lifetime, increasing their risk for traumatic brain injury (TBI). Despite the prevalence of TBI among IPV survivors, research is sparse in comparison with parallel populations (eg, military, accidents, sports). This pilot study aimed to provide a preliminary investigation of the effect of TBI on brain morphometry and resting-state functional connectivity in women who experience IPV.

PARTICIPANTS

A total of 45 community-dwelling women survivors of IPV who screened positive for posttraumatic stress disorder (PTSD).

DESIGN

Participants completed comprehensive assessments of trauma exposure, PTSD, TBI history, and brain neurological health. Twenty-three participants (51.1%) met diagnostic criteria for lifetime TBI. Of these, 15 participants experienced 1 or more TBIs resulting from IPV. The remaining participants experienced TBI from non-IPV exposures (eg, sports/motor vehicle accident). Surface-based neuroimaging analyses were performed to examine group differences in cortical thickness and in functional connectivity of amygdala and isthmus cingulate seeds to examine emotion regulation and the default mode network, respectively.

MAIN MEASURES

Boston Assessment of Traumatic Brain Injury-Lifetime for Intimate Partner Violence (BAT-L/IPV); Clinician Administered PTSD Scale (CAPS); structural and functional neuroimaging.

RESULTS

History of lifetime TBI in women IPV survivors was associated with differences in cortical thickness as well as functional connectivity between the isthmus cingulate seed and a variety of regions, including superior parietal and frontal cortices. Individuals with IPV-related TBI showed greater cortical thickness in the right paracentral gyrus than individuals with TBI from other non-IPV etiologies.

CONCLUSION

Significant differences in brain structure and connectivity were observed in individuals with IPV and TBI. A greater mean cortical thickness of the paracentral gyrus was associated with TBI due to IPV than TBI from other etiologies. Although preliminary, findings from this pilot study present a step toward identifying potential mechanisms by which IPV and TBI secondary to IPV impact brain health in women.

Pre- and Post-therapy Risk Factors for Vasculopathy in Pediatric Craniopharyngioma Patients Treated with Surgery and Proton Radiotherapy

PURPOSE

Vasculopathy (VAS) is a significant complication associated with radiotherapy in patients treated for brain tumors. We studied the type, location, severity, timing, and resolution of VAS in children with craniopharyngioma treated with proton radiotherapy (PRT) and evaluated predictors of stenosis (STN) using a novel patient and imaging-based modelling approach.

MATERIALS/METHODS

Children with craniopharyngioma (N=94) were treated with 54 GyRBE PRT on a clinical trial NCTXXXXXXXX.¹ We evaluated VAS type, location, severity, and resolution. VAS events were segmented and related to their location, operative corridor, PRT dose, and vascular territory to facilitate Mixed Effect Logistic Regression Modelling of spatial predictors of STN events.

RESULTS

Forty-five (47.9%) patients had 111 instances of confirmed VAS (pre-PRT N = 37, 33.3%). The median time to post-PRT VAS was 3.41 years (95% CI 1.86-6.11). Stenosis events were observed post-PRT in 23.4% (N=22) patients. Post-PRT VAS was detected by cerebral angiogram in 9.6% (N=9), severe in 4.3% (N=4), and compensated on perfusion in 2.1% (N=2). Revascularization was required for 5 (5.3%) patients. Post-surgical, pre-PRT VAS, and PRT dose to unperturbed vessels were predictive of STN. The impact of PRT on STN was negligible within the surgical corridor.

CONCLUSIONS

VAS often precedes PRT and was the strongest predictor of post-PRT STN. The adverse impact of PRT on STN was only apparent in unperturbed vasculature beyond the operative corridor.

Interaction of childhood abuse and depressive symptoms on cortical thickness: a general population study

Childhood abuse was inconsistently related to whole-brain cortical thickness in former studies. However, both childhood abuse and cortical thickness have been associated with depressive symptoms. We hypothesised that childhood abuse moderates the association between depressive symptoms and cortical thickness. In 1551 individuals of the general population, associations between whole-brain cortical thickness and the interaction of childhood abuse (emotional, physical, and sexual) and depressive symptoms were analysed using an ANCOVA. Linear regression analyses were used to estimate the same effect on the cortical thickness of 34 separate regions (Desikan-Killiany-atlas). A significant interaction effect of childhood abuse and depressive symptoms was observed for whole-brain cortical thickness (F(2, 1534) = 5.28, p = 0.007). A thinner cortex was associated with depressive symptoms in abused (t value = 2.78, p = 0.025) but not in non-abused participants (t value = - 1.50, p = 0.224). Focussing on non-depressed participants, a thicker whole-brain cortex was found in abused compared to non-abused participants (t value = - 2.79, p = 0.025). Similar interaction effects were observed in 12 out of 34 cortical regions. Our results suggest that childhood abuse is associated with reduced cortical thickness in subjects with depressive symptoms. In abused subjects without depressive symptoms, larger cortical thickness might act compensatory and thus reflect resilience against depressive symptoms.

Effects of OPRM1 and DRD2 on brain structure in drug-naïve adolescents: Genetic and neural vulnerabilities to substance use

Genetic variants in the opioid receptor mu 1 (OPRM1) and dopamine receptor d2 (DRD2) genes are implicated in behavioral phenotypes related to substance use disorders (SUD). Despite associations among OPRM1 (rs179971) and DRD2 (rs6277) genes and structural alterations in neural reward pathways implicated in SUDs, little is known about the contribution of risk-related gene variants to structural neurodevelopment. In a 3-year longitudinal study of initially SU-naïve adolescents (N = 129; 70 females; 11-14 years old), participants underwent an MRI structural scan at baseline and provided genetic assays for OPRM1 and DRD2 with SU behavior assessed during follow-up visits. Baseline differences in key reward-related brain regions (i.e., bilateral caudate and cingulate cortex) were detected in those with genetic liability for SU in OPRM1 who went onto engage in SU at subsequent waves of data collection. In addition, main effects of OPRM1, DRD2, and SU were related to variability in structure of the putamen, anterior cingulate, and nucleus accumbens, respectively. These data provide preliminary evidence that genetic risk factors interact with future SU to confer structural variability prior to SU in regions commonly implicated in risk for SU and the development of SUDs.

Dual feature correlation guided multi-task learning for Alzheimer's disease prediction

Alzheimer's disease (AD) is a gradually progressive neurodegenerative disease affecting cognition functions. Predicting the cognitive scores from neuroimage measures and identifying relevant imaging biomarkers are important research topics in the study of AD. Despite machine learning algorithms having many successful applications, the prediction model suffers from the so-called curse of dimensionality. Multi-task feature learning (MTFL) has helped tackle this problem incorporating the correlations among multiple clinical cognitive scores. However, MTFL neglects the inherent correlation among brain imaging measures. In order to better predict the cognitive scores and identify stable biomarkers, we first propose a generalized multi-task formulation framework that incorporates the task and feature correlation structures simultaneously. Second, we present a novel feature-aware sparsity-inducing norm (FAS-norm) penalty to incorporate a useful correlation between brain regions by exploiting correlations among features. Three multi-task learning models that incorporate the FAS-norm penalty are proposed following our framework. Finally, the algorithm based on the alternating direction method of multipliers (ADMM) is developed to optimize the non-smooth problems. We comprehensively evaluate the proposed models on the cross-sectional and longitudinal Alzheimer's disease neuroimaging initiative datasets. The inputs are the thickness measures and the volume measures of the cortical regions of interest. Compared with MTFL, our methods achieve an average decrease of 4.28% in overall error in the cross-sectional analysis and an average decrease of 7.97% in the Alzheimer's Disease Assessment Scale cognitive total score longitudinal analysis. Moreover, our methods identify sensitive and stable biomarkers to physicians, such as the hippocampus, lateral ventricle, and corpus callosum.

Data-Driven Analyses of Longitudinal Hippocampal Imaging Trajectories: Discrimination and Biomarker Prediction of Change Classes

BACKGROUND

Hippocampal atrophy is a well-known biomarker of neurodegeneration, such as that observed in Alzheimer's disease (AD). Although distributions of hippocampal volume trajectories for asymptomatic individuals often reveal substantial heterogeneity, it is unclear whether interpretable trajectory classes can be objectively detected and used for prediction analyses.

OBJECTIVE

To detect and predict hippocampal trajectory classes in a computationally competitive context using established AD-related risk factors/biomarkers.

METHODS

We used biomarker/risk factor and longitudinal MRI data in asymptomatic adults from the AD Neuroimaging Initiative (n = 351; Mean = 75 years; 48.7% female). First, we applied latent class growth analyses to left (LHC) and right (RHC) hippocampal trajectory distributions to identify distinct classes. Second, using random forest analyses, we tested 38 multi-modal biomarkers/risk factors for their relative importance in discriminating the lower (potentially elevated atrophy risk) from the higher (potentially reduced risk) class.

RESULTS

For both LHC and RHC trajectory distribution analyses, we observed three distinct trajectory classes. Three biomarkers/risk factors predicted membership in LHC and RHC lower classes: male sex, higher education, and lower plasma Aβ1-42. Four additional factors selectively predicted membership in the lower LHC class: lower plasma tau and Aβ1-40, higher depressive symptomology, and lower body mass index.

CONCLUSION

Data-driven analyses of LHC and RHC trajectories detected three classes underlying the heterogeneous distributions. Machine learning analyses determined three common and four unique biomarkers/risk factors discriminating the higher and lower LHC/RHC classes. Our sequential analytic approach produced evidence that the dynamics of preclinical hippocampal trajectories can be predicted by AD-related biomarkers/risk factors from multiple modalities.

Regional Gray Matter Volume Related to High Occupational Stress in Firefighters

BACKGROUND

Firefighters inevitably encounter emotionally and physically stressful situations at work. Even firefighters without diagnosed post-traumatic stress disorder receive clinical attention because the nature of the profession exposes them to repetitive trauma and high occupational stress. This study investigated gray matter abnormalities related to high occupational stress in firefighters using voxel-based morphometry (VBM) and surface-based morphometry (SBM).

METHODS

We assessed 115 subjects (112 males and 3 females) using magnetic resonance imaging and evaluated occupational stress by the Korean Occupational Stress Scale-26 (KOSS-26). Subjects were classified into highly or lowly stressed groups based on the median value of the KOSS-26.

RESULTS

In VBM analysis, we found that firefighters with high occupational stress had lower gray matter volume (GMV) in both sides of the insula, the left amygdala, the right medial prefrontal cortex (mPFC), and the anterior cingulate cortex than firefighters with low occupational stress. In SBM analysis based on regions of interest, the GMV of the bilateral insula and right mPFC were also lower in the highly stressed group. Within the highly stressed group, low GMV of the insula was significantly correlated with the length of service (left: r = -0.347, P = 0.009; right: r = -0.333, P = 0.012).

CONCLUSION

Our findings suggest that regional GMV abnormalities are related to occupational stress. Regional gray matter abnormalities and related emotional dysregulation may contribute to firefighter susceptibility to burnout.

Body mass index but not genetic risk is longitudinally associated with altered structural brain parameters

Evidence from previous studies suggests that elevated body mass index (BMI) and genetic risk for obesity is associated with reduced brain volume, particularly in areas of reward-related cognition, e.g. the medial prefrontal cortex (AC-MPFC), the orbitofrontal cortex (OFC), the striatum and the thalamus. However, only few studies examined the interplay between these factors in a joint approach. Moreover, previous findings are based on cross-sectional data. We investigated the longitudinal relationship between increased BMI, brain structural magnetic resonance imaging (MRI) parameters and genetic risk scores in a cohort of n = 502 community-dwelling participants from the Study of Health in Pomerania (SHIP) with a mean follow-up-time of 4.9 years. We found that (1) increased BMI values at baseline were associated with decreased brain parameters at follow-up. These effects were particularly pronounced for the OFC and AC-MPFC. (2) The genetic predisposition for BMI had no effect on brain parameters at baseline or follow-up. (3) The interaction between the genetic score for BMI and brain parameters had no effect on BMI at baseline. Finding a significant impact of overweight, but not genetic predisposition for obesity on altered brain structure suggests that metabolic mechanisms may underlie the relationship between obesity and altered brain structure.

Effects of Meditation on Structural Changes of the Brain in Patients With Mild Cognitive Impairment or Alzheimer's Disease Dementia

Previous cross-sectional studies reported positive effects of meditation on the brain areas related to attention and executive function in the healthy elderly population. Effects of long-term regular meditation in persons with mild cognitive impairment (MCI) and Alzheimer's disease dementia (AD) have rarely been studied. In this study, we explored changes in cortical thickness and gray matter volume in meditation-naïve persons with MCI or mild AD after long-term meditation intervention. MCI or mild AD patients underwent detailed clinical and neuropsychological assessment and were assigned into meditation or non-meditation groups. High resolution T1-weighted magnetic resonance images (MRI) were acquired at baseline and after 6 months. Longitudinal symmetrized percentage changes (SPC) in cortical thickness and gray matter volume were estimated. Left caudal middle frontal, left rostral middle frontal, left superior parietal, right lateral orbitofrontal, and right superior frontal cortices showed changes in both cortical thickness and gray matter volume; the left paracentral cortex showed changes in cortical thickness; the left lateral occipital, left superior frontal, left banks of the superior temporal sulcus (bankssts), and left medial orbitofrontal cortices showed changes in gray matter volume. All these areas exhibited significantly higher SPC values in meditators as compared to non-meditators. Conversely, the left lateral occipital, and right posterior cingulate cortices showed significantly lower SPC values for cortical thickness in the meditators. In hippocampal subfields analysis, we observed significantly higher SPC in gray matter volume of the left CA1, molecular layer HP, and CA3 with a trend for increased gray matter volume in most other areas. No significant changes were found for the hippocampal subfields in the right hemisphere. Analysis of the subcortical structures revealed significantly increased volume in the right thalamus in the meditation group. The results of the study point out that long-term meditation practice in persons with MCI or mild AD leads to salutary changes in cortical thickness and gray matter volumes. Most of these changes were observed in the brain areas related to executive control and memory that are prominently at risk in neurodegenerative diseases.

Eccentric rehabilitation induces white matter plasticity and sensorimotor recovery in chronic spinal cord injury

Experience-dependent white matter plasticity offers new potential for rehabilitation-induced recovery after neurotrauma. This first-in-human translational experiment combined myelin water imaging in humans and genetic fate-mapping of oligodendrocyte lineage cells in mice to investigate whether downhill locomotor rehabilitation that emphasizes eccentric muscle actions promotes white matter plasticity and recovery in chronic, incomplete spinal cord injury (SCI). In humans, of 20 individuals with SCI that enrolled, four passed the imaging screen and had myelin water imaging before and after a 12-week (3 times/week) downhill locomotor treadmill training program (SCI + DH). One individual was excluded for imaging artifacts. Uninjured control participants (n = 7) had two myelin water imaging sessions within the same day. Changes in myelin water fraction (MWF), a histopathologically-validated myelin biomarker, were analyzed in a priori motor learning and non-motor learning brain regions and the cervical spinal cord using statistical approaches appropriate for small sample sizes. PDGFRα-CreER^T2:mT/mG mice, that express green fluorescent protein on oligodendrocyte precursor cells and subsequent newly-differentiated oligodendrocytes upon tamoxifen-induced recombination, were either naive (n = 6) or received a moderate (75 kilodyne), contusive SCI at T9 and were randomized to downhill training (n = 6) or unexercised groups (n = 6). We initiated recombination 29 days post-injury, seven days prior to downhill training. Mice underwent two weeks of daily downhill training on the same 10% decline grade used in humans. Between-group comparison of functional (motor and sensory) and histological (oligodendrogenesis, oligodendroglial/axon interaction, paranodal structure) outcomes occurred post-training. In humans with SCI, downhill training increased MWF in brain motor learning regions (postcentral, precuneus) and mixed motor and sensory tracts of the ventral cervical spinal cord compared to control participants (P < 0.05). In mice with thoracic SCI, downhill training induced oligodendrogenesis in cervical dorsal and lateral white matter, increased axon-oligodendroglial interactions, and normalized paranodal structure in dorsal column sensory tracts (P < 0.05). Downhill training improved sensorimotor recovery in mice by normalizing hip and knee motor control and reducing hyperalgesia, both of which were associated with new oligodendrocytes in the cervical dorsal columns (P < 0.05). Our findings indicate that eccentric-focused, downhill rehabilitation promotes white matter plasticity and improved function in chronic SCI, likely via oligodendrogenesis in nervous system regions activated by the training paradigm. Together, these data reveal an exciting role for eccentric training in white matter plasticity and sensorimotor recovery after SCI.

Structural-covariance networks identify topology-based cortical-thickness changes in children with persistent executive function impairments after traumatic brain injury

Paediatric traumatic brain injury (pTBI) results in inconsistent changes to regional morphometry of the brain across studies. Structural-covariance networks represent the degree to which the morphology (typically cortical-thickness) of cortical-regions co-varies with other regions, driven by both biological and developmental factors. Understanding how heterogeneous regional changes may influence wider cortical network organization may more appropriately capture prognostic information in terms of long term outcome following a pTBI. The current study aimed to investigate the relationships between cortical organisation as measured by structural-covariance, and long-term cognitive impairment following pTBI. T1-weighted magnetic resonance imaging (MRI) from n = 83 pTBI patients and 33 typically developing controls underwent 3D-tissue segmentation using Freesurfer to estimate cortical-thickness across 68 cortical ROIs. Structural-covariance between regions was estimated using Pearson's correlations between cortical-thickness measures across 68 regions-of-interest (ROIs), generating a group-level 68 × 68 adjacency matrix for patients and controls. We grouped a subset of patients who underwent executive function testing at 2-years post-injury using a neuropsychological impairment (NPI) rule, defining impaired- and non-impaired subgroups. Despite finding no significant reductions in regional cortical-thickness between the control and pTBI groups, we found specific reductions in graph-level strength of the structural covariance graph only between controls and the pTBI group with executive function (EF) impairment. Node-level differences in strength for this group were primarily found in frontal regions. We also investigated whether the top n nodes in terms of effect-size of cortical-thickness reductions were nodes that had significantly greater strength in the typically developing brain than n randomly selected regions. We found that acute cortical-thickness reductions post-pTBI are loaded onto regions typically high in structural covariance. This association was found in those patients with persistent EF impairment at 2-years post-injury, but not in those for whom these abilities were spared. This study posits that the topography of post-injury cortical-thickness reductions in regions that are central to the typical structural-covariance topology of the brain, can explain which patients have poor EF at follow-up.

Morphometry and functional connectivity of auditory cortex in school-age children with profound language disabilities: Five comparative case studies

Many neurodevelopmental conditions imply absent or severely reduced language capacities at school age. Evidence from functional magnetic resonance imaging is highly limited. We selected a series of five cases scanned with the same fMRI paradigm and the aim of relating individual language profiles onto underlying patterns of functional connectivity (FC) across auditory language cortex: three with neurogenetic syndromes (Coffin-Siris, Landau-Kleffner, and Fragile-X), one with idiopathic intellectual disability, one with autism spectrum disorder (ASD). Compared to both a group with typical development (TD) and a verbal ASD group (total N = 110), they all showed interhemispheric FC below two standard deviations of the TD mean. Children with higher language scores showed higher intrahemispheric FC between Heschl's gyrus and other auditory language regions, as well as an increase of FC during language stimulation compared to rest. An increase of FC in forward vs. reversed speech in the posterior and middle temporal gyri was seen across all cases. The Coffin-Siris case, the most severe, also had the most anomalous FC patterns and showed reduced myelin content, while the Landau-Kleffner case showed reduced cortical thickness. These results suggest potential for neural markers and mechanisms of severe language processing deficits under highly heterogeneous etiological conditions.

Anatomically Standardized Detection of MRI Atrophy Patterns in Early-Stage Alzheimer's Disease

MRI studies have consistently identified atrophy patterns in Alzheimer’s disease (AD) through a whole-brain voxel-based analysis, but efforts to investigate morphometric profiles using anatomically standardized and automated whole-brain ROI analyses, performed at the individual subject space, are still lacking. In this study we aimed (i) to utilize atlas-derived measurements of cortical thickness and subcortical volumes, including of the hippocampal subfields, to identify atrophy patterns in early-stage AD, and (ii) to compare cognitive profiles at baseline and during a one-year follow-up of those previously identified morphometric AD subtypes to predict disease progression. Through a prospectively recruited multi-center study, conducted at four Austrian sites, 120 patients were included with probable AD, a disease onset beyond 60 years and a clinical dementia rating of ≤1. Morphometric measures of T1-weighted images were obtained using FreeSurfer. A principal component and subsequent cluster analysis identified four morphometric subtypes, including (i) hippocampal predominant (30.8%), (ii) hippocampal-temporo-parietal (29.2%), (iii) parieto-temporal (hippocampal sparing, 20.8%) and (iv) hippocampal-temporal (19.2%) atrophy patterns that were associated with phenotypes differing predominately in the presentation and progression of verbal memory and visuospatial impairments. These morphologically distinct subtypes are based on standardized brain regions, which are anatomically defined and freely accessible so as to validate its diagnostic accuracy and enhance the prediction of disease progression.

Amyloid and anatomical correlates of executive functioning in middle-aged offspring of patients with late-onset Alzheimer's disease

A traditional hallmark of cognitive impairment associated with late-onset Alzheimer´s disease (LOAD) is episodic memory impairment. However, early alterations have been identified in brain regions associated with executive function in asymptomatic, middle-age offspring of patients with LOAD (O-LOAD) compared to those with no family history. We hypothesized that executive function among O-LOAD would correlate with structural and amyloid brain imaging differently from those without a family history of LOAD (control subjects, CS). Executive function, cortical thickness, and in-vivo Aβ deposits were quantified in 30 O-LOAD and 25 CS. Associations were observed among O-LOAD only. Cortical thickness in the left lateral orbitofrontal cortex was positively associated with Design Fluency. The Stroop Color and Word Test, correlated positively with right rostral mid-frontal cortex thickness. Trails Making Test-B was inversely related to left medial orbitofrontal thickness. Tower of London total time was positively associated with β-amyloid deposition in the right precuneus. These results support previous evidence that early executive dysfunction might reflect subtle, early changes in persons at risk of LOAD and suggests that executive function alterations deserve further exploration in the LOAD literature.

Diagnostic Efficacy of Voxel-Mirrored Homotopic Connectivity in Vascular Dementia as Compared to Alzheimer's Related Neurodegenerative Diseases-A Resting State fMRI Study

Previous studies have demonstrated that functional connectivity (FC) of different brain regions in resting state function MRI were abnormal in patients suffering from mild cognitive impairment (MCI) and Alzheimer’s disease (AD) when comparing to healthy controls (HC) using seed based, independent component analysis (ICA) or small world network techniques. A new technique called voxel-mirrored homotopic connectivity (VMHC) was used in the current study to evaluate the value of interhemispheric functional connectivity (IFC) as a diagnostic tool to differentiate vascular dementia (VD) from other Alzheimer’s related neurodegenerative diseases. Eighty-three participants were recruited from the university hospital memory clinic. A multidisciplinary panel formed by a neuroradiologist and two geriatricians classified the participants into VD (13), AD (16), MCI (29), and HC (25) based on clinical history, Montreal Cognitive Assessment Hong Kong version (HK-MoCA) neuropsychological score, structural MRI, MR perfusion, and 18-F Flutametamol (amyloid) PET-CT findings of individual subjects. We adopted the calculation method used by Kelly et al. (2011) and Zuo et al. (2010) in obtaining VMHC maps. Specific patterns of VMHC maps were obtained for VD, AD, and MCI to HC comparison. VD showed significant reduction in VMHC in frontal orbital gyrus and gyrus rectus. Increased VMHC was observed in default mode network (DMN), executive control network (ECN), and the remaining salient network (SN) regions. AD showed a reduction of IFC in all DMN, ECN, and SN regions; whereas MCI showed VMHC reduction in vSN, and increased VMHC in DMN and ECN. When combining VMHC values of relevant brain regions, the accuracy was improved to 87%, 92%, and 83% for VD, AD, and MCI from HC, respectively, in receiver operating characteristic (ROC) analysis. Through studying the VMHC maps and using VMHC values in relevant brain regions, VMHC can be considered as a reliable diagnostic tool for VD, AD, and MCI from HC.

Structural Differences Across Multiple Visual Cortical Regions in the Absence of Cone Function in Congenital Achromatopsia

Most individuals with congenital achromatopsia (ACHM) carry mutations that affect the retinal phototransduction pathway of cone photoreceptors, fundamental to both high acuity vision and colour perception. As the central fovea is occupied solely by cones, achromats have an absence of retinal input to the visual cortex and a small central area of blindness. Additionally, those with complete ACHM have no colour perception, and colour processing regions of the ventral cortex also lack typical chromatic signals from the cones. This study examined the cortical morphology (grey matter volume, cortical thickness, and cortical surface area) of multiple visual cortical regions in ACHM (n = 15) compared to normally sighted controls (n = 42) to determine the cortical changes that are associated with the retinal characteristics of ACHM. Surface-based morphometry was applied to T1-weighted MRI in atlas-defined early, ventral and dorsal visual regions of interest. Reduced grey matter volume in V1, V2, V3, and V4 was found in ACHM compared to controls, driven by a reduction in cortical surface area as there was no significant reduction in cortical thickness. Cortical surface area (but not thickness) was reduced in a wide range of areas (V1, V2, V3, TO1, V4, and LO1). Reduction in early visual areas with large foveal representations (V1, V2, and V3) suggests that the lack of foveal input to the visual cortex was a major driving factor in morphological changes in ACHM. However, the significant reduction in ventral area V4 coupled with the lack of difference in dorsal areas V3a and V3b suggest that deprivation of chromatic signals to visual cortex in ACHM may also contribute to changes in cortical morphology. This research shows that the congenital lack of cone input to the visual cortex can lead to widespread structural changes across multiple visual areas.

Alterations in the Occipital Cortex of Drug-Naïve Adults With Major Depressive Disorder: A Surface-Based Analysis of Surface Area and Cortical Thickness

OBJECTIVE

Advances in surface-based morphometric methods have allowed researchers to separate cortical volume into cortical thickness (CTh) and surface area (SA). Although CTh alterations in major depressive disorder (MDD) have been observed in numerous studies, few studies have described significant SA alterations. Our study aimed to measure patients' SAs and to compare it with their CTh to examine whether SA exhibits alteration patterns that differ from those of CTh in drug-naïve patients with MDD.

METHODS

A total of 71 drug-naïve MDD patients and 111 healthy controls underwent structural magnetic resonance imaging, and SA and CTh were analyzed between the groups.

RESULTS

We found a smaller SA in the left superior occipital gyrus (L-SOG) in drug-naïve patients with MDD. In the CTh analysis, the bilateral fusiform gyrus, left middle occipital gyrus, left temporal superior gyrus, and right posterior cingulate showed thinner cortices in patients with MDD, while the CTh of the bilateral SOG, right straight gyrus, right posterior cingulate, and left lingual gyrus were increased.

CONCLUSION

Compared with the bilateral occipito-temporal changes in CTh, SA alterations in patients with MDD were confined to the L-SOG. These findings may improve our understanding of the neurobiological mechanisms of SA alteration in relation to MDD.

Structural assessment of thalamus morphology in brain disorders: A review and recommendation of thalamic nucleus segmentation and shape analysis

The thalamus is a central brain structure crucially involved in cognitive, emotional, sensory, and motor functions and is often reported to be involved in the pathophysiology of neurological and psychiatric disorders. The functional subdivision of the thalamus warrants morphological investigation on the level of individual subnuclei. In addition to volumetric measures, the investigation of other morphological features may give additional insights into thalamic morphology. For instance, shape features offer a higher spatial resolution by revealing small, regional differences that are left undetected in volumetric analyses. In this review, we discuss the benefits and limitations of recent advances in neuroimaging techniques to investigate thalamic morphology in vivo, leading to our proposed methodology. This methodology consists of available pipelines for volume and shape analysis, focussing on the morphological features of volume, thickness, and surface area. We demonstrate this combined approach in a Parkinson's disease cohort to illustrate their complementarity. Considering our findings, we recommend a combined methodology as it allows for more sensitive investigation of thalamic morphology in clinical populations.

Cortical thickness is differently associated with ALDH2 rs671 polymorphism according to level of amyloid deposition

Accumulating evidence indicates that amyloid-beta (Aβ) deposition and biogenic aldehyde accumulation contribute to the pathogenesis of neurodegenerative diseases. Human aldehyde dehydrogenase 2 (ALDH2) metabolizes biogenic aldehydes produced in the brain to prevent damage. However, r671G>A, a single nucleotide polymorphism of ALDH2, causes aldehyde accumulation and decreased ALDH2 activity. We aimed to investigate whether Aβ deposition and rs671 polymorphism have an interaction effect on cortical thickness (CTh). We grouped 179 participants in the Biobank Innovations for chronic Cerebrovascular disease With ALZheimer's disease Study as follows: amyloid (–) [A(–)] and amyloid (+) [A(+)] groups based on the Aβ deposition degree; A-carrier (AC) and GG (GG) groups based on the presence/absence of the rs671 A allele; and their combinations, i.e., A(–)AC, A(–)GG, A(+)AC, and A(+)GG groups. A multiple regression analysis identified nine regions of interest. Compared with the A(–)GG group, the A(–)AC group showed thinner CTh in all regions. There were no significant differences between the A(+)AC and A(+)GG groups. We observed an interaction effect of amyloid deposition and rs671 polymorphism on CTh. The CTh in the A(–) group appeared to be strongly influenced by rs671 polymorphism, which could have contributed to cortical thinning and biogenic aldehyde accumulation in the AC group. Additionally, CTh in the A(+) group appeared to be strongly influenced by amyloid deposition.