Cortico-striatal differences in the epigenome in attention-deficit/ hyperactivity disorder

While epigenetic modifications have been implicated in ADHD through studies of peripheral tissue, to date there has been no examination of the epigenome of the brain in the disorder. To address this gap, we mapped the methylome of the caudate nucleus and anterior cingulate cortex in post-mortem tissue from fifty-eight individuals with or without ADHD. While no single probe showed adjusted significance in differential methylation, several differentially methylated regions emerged. These regions implicated genes involved in developmental processes including neurogenesis and the differentiation of oligodendrocytes and glial cells. We demonstrate a significant association between differentially methylated genes in the caudate and genes implicated by GWAS not only in ADHD but also in autistic spectrum, obsessive compulsive and bipolar affective disorders through GWAS. Using transcriptomic data available on the same subjects, we found modest correlations between the methylation and expression of genes. In conclusion, this study of the cortico-striatal methylome points to gene and gene pathways involved in neurodevelopment, consistent with studies of common and rare genetic variation, as well as the post-mortem transcriptome in ADHD.

Subcortico-Cortical Dysconnectivity in ADHD: A Voxel-Wise Mega-Analysis Across Multiple Cohorts

OBJECTIVE

A large body of functional MRI research has examined a potential role for subcortico-cortical loops in the pathogenesis of attention deficit hyperactivity disorder (ADHD), but has produced inconsistent findings. The authors performed a mega-analysis of six neuroimaging data sets to examine associations between ADHD diagnosis and traits and subcortico-cortical connectivity.

METHODS

Group differences were examined in the functional connectivity of four subcortical seeds in 1,696 youths with ADHD diagnoses (66.39% males; mean age, 10.83 years [SD=2.17]) and 6,737 unaffected control subjects (47.05% males; mean age, 10.33 years [SD=1.30]). The authors examined associations between functional connectivity and ADHD traits (total N=9,890; 50.3% males; mean age, 10.77 years [SD=1.96]). Sensitivity analyses were used to examine specificity relative to commonly comorbid internalizing and non-ADHD externalizing problems. The authors further examined results within motion-matched subsamples, and after adjusting for estimated intelligence.

RESULTS

In the group comparison, youths with ADHD showed greater connectivity between striatal seeds and temporal, fronto-insular, and supplementary motor regions, as well as between the amygdala and dorsal anterior cingulate cortex, compared with control subjects. Similar findings emerged when ADHD traits were considered and when alternative seed definitions were adopted. Dominant associations centered on the connectivity of the caudate bilaterally. Findings were not driven by in-scanner motion and were not shared with commonly comorbid internalizing and externalizing problems. Effect sizes were small (largest peak d, 0.15).

CONCLUSIONS

The findings from this large-scale mega-analysis support established links with subcortico-cortical circuits, which were robust to potential confounders. However, effect sizes were small, and it seems likely that resting-state subcortico-cortical connectivity can capture only a fraction of the complex pathophysiology of ADHD.

Association between relative age at school and persistence of ADHD in prospective studies: an individual participant data meta-analysis

BACKGROUND

The youngest children in a school class are more likely than the oldest to be diagnosed with ADHD, but this relative age effect is less frequent in older than in younger school-grade children. However, no study has explored the association between relative age and the persistence of ADHD diagnosis at older ages. We aimed to quantify the association between relative age and persistence of ADHD at older ages.

METHODS

For this meta-analysis, we searched MEDLINE, Embase, CINAHL, PsycINFO, and PubPsych up to April 1, 2022, with terms related to "cohort" and "ADHD" with no date, publication type, or language restrictions. We gathered individual participant data from prospective cohorts that included at least ten children identified with ADHD before age 10 years. ADHD was defined by either a clinical diagnosis or symptoms exceeding clinical cutoffs. Relative age was recorded as the month of birth in relation to the school-entry cutoff date. Study authors were invited to share raw data or to apply a script to analyse data locally and generate anonymised results. Our outcome was ADHD status at a diagnostic reassessment, conducted at least 4 years after the initial assessment and after age 10 years. No information on sex, gender, or ethnicity was collected. We did a two-stage random-effects individual participant data meta-analysis to assess the association of relative age with persistence of ADHD at follow-up. This study was registered with PROSPERO, CRD42020212650.

FINDINGS

Of 33 119 studies generated by our search, we identified 130 eligible unique studies and were able to gather individual participant data from 57 prospective studies following up 6504 children with ADHD. After exclusion of 16 studies in regions with a flexible school entry system that did not allow confident linkage of birthdate to relative age, the primary analysis included 41 studies in 15 countries following up 4708 children for a period of 4 to 33 years. We found that younger relative age was not statistically significantly associated with ADHD persistence at follow-up (odds ratio 1·02, 95% CI 0·99-1·06; p=0·19). We observed statistically significant heterogeneity in our model (Q=75·82, p=0·0011, I2=45%). Participant-level sensitivity analyses showed similar results in cohorts with a robust relative age effect at baseline and when restricting to cohorts involving children with a clinical diagnosis of ADHD or with a follow-up duration of more than 10 years.

INTERPRETATION

The diagnosis of ADHD in younger children in a class is no more likely to be disconfirmed over time than that of older children in the class. One interpretation is that the relative age effect decreases the likelihood of children of older relative age receiving a diagnosis of ADHD, and another is that assigning a diagnostic label of ADHD leads to unexplored carryover effects of the initial diagnosis that persist over time. Future studies should be conducted to explore these interpretations further.

FUNDING

None.

Longitudinal trajectories of childhood and adolescent attention deficit hyperactivity disorder diagnoses in three cohorts

Background

Attention deficit/hyperactivity disorder (ADHD) is usually conceptualized as a childhood-onset neurodevelopmental disorder, in which symptoms either decrease steadily into adulthood or remain stable. A recent study challenged this view, reporting that for most with ADHD, diagnostic status fluctuates with age. We ask if such a 'fluctuating' ADHD symptom trajectory subgroup is present in other population-based and clinic-based cohorts, centered on childhood and adolescence.

Methods

Cohorts were the population-based Adolescent Brain Cognitive Development (ABCD: N = 9735), Neurobehavioral Clinical Research (NCR: N = 258), and the Nathan Kline Institute-Rockland (NKI-Rockland: N = 149). All participants had three or more assessments spanning different age windows. Participants were categorized into developmental diagnostic subgroups: fluctuant ADHD (defined by two or more switches between meeting and not meeting ADHD criteria), remitting ADHD, persisting ADHD, emerging ADHD and never affected. Data were collected between 2011 and 2022. Analyses were performed between May 2022 and April 2023.

Findings

A subgroup with fluctuant child and adolescent ADHD diagnoses was found in all cohorts (29.3% of participants with ADHD in ABCD, 26.6% in NCR and 17% in NKI-Rockland). While the proportion of those with fluctuant ADHD increased with the number of assessments, it never constituted the dominant subgroup.

Interpretation

We provide further evidence in three cohorts for the existence of a fluctuant ADHD diagnostic subgroup during childhood and adolescence, albeit in a minority of cases. Such fluctuant child and adolescent ADHD diagnoses may suggest a natural history more akin to relapsing-remitting mood disorders and/or a marked sensitivity to environmental shifts that occur across development.

Funding

Intramural programs of the NHGRI and NIMH.

An Emerging Screening Method for Interrogating Human Brain Function: Tutorial

Cognitive decline can be observed due to a myriad of causes. Clinicians would benefit from a noninvasive quantitative tool to screen and monitor brain function based on direct measures of neural features. In this study, we used neuroimaging data from magnetoencephalography (with a whole-head Elekta Neuromag 306 sensor system) to derive a set of features that strongly correlate with brain function. We propose that simple signal characteristics related to peak variability, timing, and abundance can be used by clinicians as a screening tool to investigate cognitive function in at-risk individuals. Using a minimalistic set of features, we were able to perfectly distinguish between participants with normative and nonnormative brain function, and we were also able to successfully predict participants' Mini-Mental Test score (r=0.99; P<.001; mean absolute error=0.413). This set of features can be easily visualized in an analog fashion, providing clinicians with several graded measurements (in comparison to a single binary diagnostic tool) that can be used for screening and monitoring cognitive decline.

Rare copy number variants in males and females with childhood attention-deficit/hyperactivity disorder

While childhood attention-deficit/hyperactivity disorder (ADHD) is more prevalent in males than females, genetic contributors to this effect have not been established. Here, we explore sex differences in the contribution of common and/or rare genetic variants to ADHD. Participants were from the Adolescent Brain and Cognitive Development study (N = 1253 youth meeting DSM-5 criteria for ADHD [mean age = 11.46 years [SD = 0.87]; 31% female] and 5577 unaffected individuals [mean age = 11.42 years [SD = 0.89]; 50% female], overall 66% White, non-Hispanic (WNH), 19% Black/African American, and 15% other races. Logistic regression tested for interactions between sex (defined genotypically) and both rare copy number variants (CNV) and polygenic (common variant) risk in association with ADHD. There was a significant interaction between sex and the presence of a CNV deletion larger than 200 kb, both in the entire cohort (β = -0.74, CI = [-1.27 to -0.20], FDR-corrected p = 0.048) and, at nominal significance levels in the WNH ancestry subcohort (β = -0.86, CI = [-1.51 to -0.20], p = 0.010). Additionally, the number of deleted genes interacted with sex in association with ADHD (whole cohort. β = -0.13, CI = [-0.23 to -0.029], FDR-corrected p = 0.048; WNH. β = -0.17, CI = [-0.29 to -0.050], FDR-corrected p = 0.044) as did the total length of CNV deletions (whole cohort. β = -0.12, CI = [-0.19 to -0.044], FDR-corrected p = 0.028; WNH. β = -0.17, CI = [-0.28 to -0.061], FDR-corrected p = 0.034). This sex effect was driven by increased odds of childhood ADHD for females but not males in the presence of CNV deletions. No similar sex effect was found for CNV duplications or polygenic risk scores. The association between CNV deletions and ADHD was partially mediated by measures of cognitive flexibility. In summary, CNV deletions were associated with increased odds for childhood ADHD in females, but not males.

Evidence from "big data" for the default-mode hypothesis of ADHD: a mega-analysis of multiple large samples

We sought to identify resting-state characteristics related to attention deficit/hyperactivity disorder, both as a categorical diagnosis and as a trait feature, using large-scale samples which were processed according to a standardized pipeline. In categorical analyses, we considered 1301 subjects with diagnosed ADHD, contrasted against 1301 unaffected controls (total N = 2602; 1710 males (65.72%); mean age = 10.86 years, sd = 2.05). Cases and controls were 1:1 nearest neighbor matched on in-scanner motion and key demographic variables and drawn from multiple large cohorts. Associations between ADHD-traits and resting-state connectivity were also assessed in a large multi-cohort sample (N = 10,113). ADHD diagnosis was associated with less anticorrelation between the default mode and salience/ventral attention (B = 0.009, t = 3.45, p-FDR = 0.004, d = 0.14, 95% CI = 0.004, 0.014), somatomotor (B = 0.008, t = 3.49, p-FDR = 0.004, d = 0.14, 95% CI = 0.004, 0.013), and dorsal attention networks (B = 0.01, t = 4.28, p-FDR < 0.001, d = 0.17, 95% CI = 0.006, 0.015). These results were robust to sensitivity analyses considering comorbid internalizing problems, externalizing problems and psychostimulant medication. Similar findings were observed when examining ADHD traits, with the largest effect size observed for connectivity between the default mode network and the dorsal attention network (B = 0.0006, t = 5.57, p-FDR < 0.001, partial-r = 0.06, 95% CI = 0.0004, 0.0008). We report significant ADHD-related differences in interactions between the default mode network and task-positive networks, in line with default mode interference models of ADHD. Effect sizes (Cohen's d and partial-r, estimated from the mega-analytic models) were small, indicating subtle group differences. The overlap between the affected brain networks in the clinical and general population samples supports the notion of brain phenotypes operating along an ADHD continuum.

A Mega-analytic Study of White Matter Microstructural Differences Across 5 Cohorts of Youths With Attention-Deficit/Hyperactivity Disorder

BACKGROUND

While attention-deficit/hyperactivity disorder (ADHD) has been associated with differences in the structural connections formed by the brain's white matter tracts, studies of such differences have yielded inconsistent findings, likely reflecting small sample sizes. Thus, we conducted a mega-analysis on in vivo measures of white matter microstructure obtained through diffusion tensor imaging of more than 6000 participants from 5 cohorts.

METHODS

In a mega-analysis, linear mixed models were used to test for associations between the fractional anisotropy of 42 white matter tracts and ADHD traits and diagnosis. Contrasts were made against measures of mood, anxiety, and other externalizing problems.

RESULTS

Overall, 6993 participants (ages 6-18 years, mean age 10.62 years [SD 1.99]; 3368 girls, 3625 boys; 764 African American, 4146 non-Hispanic White, and 2083 other race/ethnicities) had measures of ADHD and other emotional/behavioral symptoms (N = 6933) and/or enough clinical data to allow a diagnosis of ADHD (n = 951) or its absence (n = 4884). Both the diagnosis and symptoms of ADHD were associated with lower fractional anisotropy of the inferior longitudinal and left uncinate fasciculi (at a false discovery rate-adjusted p < .05). Associated effect sizes were small (the strongest association with ADHD traits had an effect size of partial r = -0.14, while the largest case-control difference was associated with an effect size of d = -0.3). Similar microstructural anomalies were not present for anxiety, mood, or externalizing problems. Findings held when ADHD cases and control subjects were matched on in-scanner motion.

CONCLUSIONS

While present across cohorts, ADHD-associated microstructural differences had small effects, underscoring the limited clinical utility of this imaging modality used in isolation.

The Anatomy of Friendship: Neuroanatomic Homophily of the Social Brain among Classroom Friends

Homophily refers to the tendency to like similar others. Here, we ask if homophily extends to brain structure. Specifically: do children who like one another have more similar brain structures? We hypothesized that neuroanatomic similarity tied to friendship is most likely to pertain to brain regions that support social cognition. To test this hypothesis, we analyzed friendship network data from 1186 children in 49 classrooms. Within each classroom, we identified "friendship distance"-mutual friends, friends-of-friends, and more distantly connected or unconnected children. In total, 125 children (mean age = 7.57 years, 65 females) also had good quality neuroanatomic magnetic resonance imaging scans from which we extracted properties of the "social brain." We found that similarity of the social brain varied by friendship distance: mutual friends showed greater similarity in social brain networks compared with friends-of-friends (β = 0.65, t = 2.03, P = 0.045) and even more remotely connected peers (β = 0.77, t = 2.83, P = 0.006); friends-of-friends did not differ from more distantly connected peers (β = -0.13, t = -0.53, P = 0.6). We report that mutual friends have similar "social brain" networks, adding a neuroanatomic dimension to the adage that "birds of a feather flock together."

Genetic variants associated with longitudinal changes in brain structure across the lifespan

Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging.

Analysis of structural brain asymmetries in attention-deficit/hyperactivity disorder in 39 datasets

OBJECTIVE

Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium.

METHODS

We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries.

RESULTS

There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen's d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing.

CONCLUSION

Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait.

A Longitudinal Study of Resting-State Connectivity and Response to Psychostimulant Treatment in ADHD

OBJECTIVE

Psychostimulants are first-line pharmacological treatments for attention deficit hyperactivity disorder (ADHD), although symptom reduction varies widely between patients and these individual differences in treatment response are poorly understood. The authors sought to examine whether the resting-state functional connectivity within and between cingulo-opercular, striato-thalamic, and default mode networks was associated with treatment response to psychostimulant medication, and whether this relationship changed with development.

METHODS

Patients with ADHD (N=110; 196 observations; mean age at first observation, 10.83 years, SD=2.2) and typically developing control subjects (N=142; 330 observations; mean age at first observation, 10.49 years, SD=2.81) underwent functional neuroimaging on up to five occasions during development (age range, 6-17 years). For patients, symptoms were assessed on and off psychostimulant medication (methylphenidate-based treatments: N=132 observations, 67%; amphetamine-based treatments: N=64 observations, 33%) using the Diagnostic Interview for Children and Adolescents for parents. Linear mixed-effects models examined whether resting-state connectivity was associated with treatment response and its interaction with age. Comparisons with typically developing control subjects were performed to contextualize any significant associations.

RESULTS

Resting-state connectivity within the cingulo-opercular network was associated with a significant interaction between treatment response and age. Specifically, worse responses to treatment compared with better responses to treatment among patients and compared with typically developing control subjects were associated with an atypical increase in cingulo-opercular connectivity with increasing age from childhood to adolescence.

CONCLUSIONS

This work delineates how resting-state connectivity may be associated over development with response to psychostimulants in ADHD. Functioning and development within the cingulo-opercular network may warrant further investigation as a contributor to differential response to psychostimulants.

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

BACKGROUND

Twin studies show that age-related change in symptoms of attention-deficit/hyperactivity disorder (ADHD) is heritable. However, we do not know the heritability of the development of the neural substrates underlying the disorder. Here, we estimated the heritability of developmental change in white matter tracts and the brain's intrinsic functional connectivity using longitudinal data. We further determined associations with change in ADHD symptoms.

METHODS

The study reports on 288 children, which included 127 siblings, 19 cousins, and 142 singletons; 150 (52%) had a diagnosis of ADHD (determined by clinician interview with parent); 188 were male. All had two clinical assessments (overall baseline mean age: 9.4 ± 2.4 years; follow-up: 12.5 ± 2.6 years). Diffusion tensor imaging estimated microstructural properties of white matter tracts on 252 participants. Resting-state functional magnetic resonance imaging estimated intrinsic connectivity within and between major brain networks on 226 participants. Total additive genetic heritability (h²) of the annual rate of change in these neural phenotypes was calculated using SOLAR (Sequential Oligogenic Linkage Analysis Routines).

RESULTS

Significant heritability was found for the rates of change of 6 white matter tract microstructural properties and for change in the connectivity between the ventral attention network and both the cognitive control and dorsal attention networks. Change in hyperactivity-impulsivity was associated with heritable change in white matter tracts metrics and change in the connectivity between the ventral attention and cognitive networks.

CONCLUSIONS

The relatively small number of heritable, ADHD-associated developmental neural phenotypes can serve as phenotypes for future gene discovery and understanding.

Adolescent Attention-Deficit/Hyperactivity Disorder: Understanding Teenage Symptom Trajectories

Symptoms of attention-deficit/hyperactivity disorder (ADHD) run a variable course through adolescence. While most affected individuals show some improvement, particularly of hyperactivity-impulsivity, symptoms of inattention are more persistent, and some individuals may meet diagnostic criteria for the first time during adolescence. Genetic factors affect adolescent symptom trajectories; those showing persistence likely carry a greater burden of common risk alleles. Rare structural genomic variants, such as copy number variants and point mutations, might also play a role. Although psychostimulant medication is associated with better functional outcomes, an impact on underlying adolescent symptom trajectories has been hard to demonstrate. At a neural level, several studies report that adolescents whose childhood ADHD symptoms have remitted are indistinguishable from neurotypical individuals. This finding could reflect the "carrying forward" of relatively typical childhood neural features among those destined for adolescent remission or the correction of early childhood anomalies with a convergence toward typical dimensions. Other studies have noted unique, possibly compensatory patterns of neural activity among adolescents whose ADHD has improved. Finally, different neural processes might occur in different brain regions. Thus, some functional imaging studies find that subcortical anomalies reflect the onset of ADHD and remain throughout life regardless of symptom change, whereas the variable clinical course of adolescent ADHD is determined by plasticity of the cerebral cortex. Integrating an understanding of the neural processes with genomic risk could elucidate the mechanisms underlying the complex course of adolescent ADHD.

Mapping associations between polygenic risks for childhood neuropsychiatric disorders, symptoms of attention deficit hyperactivity disorder, cognition, and the brain

There are now large-scale data on which common genetic variants confer risk for attention deficit hyperactivity disorder (ADHD). Here, we use mediation analyses to explore how cognitive and neural features might explain the association between common variant (polygenic) risk for ADHD and its core symptoms. In total, 544 participants participated (mean 21 years, 212 (39%) with ADHD), most with cognitive assessments, neuroanatomic imaging, and imaging of white matter tract microstructure. We found that polygenic risk for ADHD was associated with symptoms of hyperactivity-impulsivity but not inattention. This association was mediated across multiple PRS thresholds by white matter microstructure, specifically by axial diffusivity of the right corona radiata, (maximum indirect effect β = -0.034 (CI: -0.065 to -0.01), by thickness of the left dorsomedial prefrontal (β = -0.029; CI: -0.061 to -0.0047) and area of the right lateral temporal cortex (β = 0.024; CI: 0.0034-0.054). In addition, modest serial mediation was found, mapping a pathway from polygenic risk, to white matter microstructure of the anterior corona radiata, then cognition (working memory, focused attention), and finally to hyperactivity-impulsivity (working memory β = -0.014 (CI: -0.038 to -0.0026); focused attention β = -0.011 (CI: -0.033 to -0.0017). These mediation pathways were diagnostically specific and were not found for polygenic risk for ASD or schizophrenia. In conclusion, using a deeply phenotyped cohort, we delineate a pathway from polygenic risk for ADHD to hyperactive-impulsive symptoms through white matter microstructure, cortical anatomy, and cognition.

Subcortical Brain Volume, Regional Cortical Thickness, and Cortical Surface Area Across Disorders: Findings From the ENIGMA ADHD, ASD, and OCD Working Groups

OBJECTIVE

Attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data.

METHODS

Structural T1-weighted whole-brain MRI data from healthy control subjects (N=5,827) and from patients with ADHD (N=2,271), ASD (N=1,777), and OCD (N=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. The authors examined subcortical volume, cortical thickness, and cortical surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults, using linear mixed-effects models adjusting for age, sex, and site (and intracranial volume for subcortical and surface area measures).

RESULTS

No shared differences were found among all three disorders, and shared differences between any two disorders did not survive correction for multiple comparisons. Children with ADHD compared with those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller intracranial volume than control subjects and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared with adult control subjects and other clinical groups. No OCD-specific differences were observed across different age groups and surface area differences among all disorders in childhood and adulthood.

CONCLUSIONS

The study findings suggest robust but subtle differences across different age groups among ADHD, ASD, and OCD. ADHD-specific intracranial volume and hippocampal differences in children and adolescents, and ASD-specific cortical thickness differences in the frontal cortex in adults, support previous work emphasizing structural brain differences in these disorders.

The lexical semantics of adjective-noun phrases in the human brain

As a person reads, the brain performs complex operations to create higher order semantic representations from individual words. While these steps are effortless for competent readers, we are only beginning to understand how the brain performs these actions. Here, we explore lexical semantics using magnetoencephalography (MEG) recordings of people reading adjective-noun phrases presented one word at a time. We track the neural representation of single word representations over time, through different brain regions. Our results reveal two novel findings: (a) a neural representation of the adjective is present during noun presentation, but this representation is different from that observed during adjective presentation and (b) the neural representation of adjective semantics observed during adjective reading is reactivated after phrase reading, with remarkable consistency. We also note that while the semantic representation of the adjective during the reading of the adjective is very distributed, the later representations are concentrated largely to temporal and frontal areas previously associated with composition. Taken together, these results paint a picture of information flow in the brain as phrases are read and understood.

Brain Imaging of the Cortex in ADHD: A Coordinated Analysis of Large-Scale Clinical and Population-Based Samples

OBJECTIVE

Neuroimaging studies show structural alterations of various brain regions in children and adults with attention deficit hyperactivity disorder (ADHD), although nonreplications are frequent. The authors sought to identify cortical characteristics related to ADHD using large-scale studies.

METHODS

Cortical thickness and surface area (based on the Desikan-Killiany atlas) were compared between case subjects with ADHD (N=2,246) and control subjects (N=1,934) for children, adolescents, and adults separately in ENIGMA-ADHD, a consortium of 36 centers. To assess familial effects on cortical measures, case subjects, unaffected siblings, and control subjects in the NeuroIMAGE study (N=506) were compared. Associations of the attention scale from the Child Behavior Checklist with cortical measures were determined in a pediatric population sample (Generation-R, N=2,707).

RESULTS

In the ENIGMA-ADHD sample, lower surface area values were found in children with ADHD, mainly in frontal, cingulate, and temporal regions; the largest significant effect was for total surface area (Cohen's d=-0.21). Fusiform gyrus and temporal pole cortical thickness was also lower in children with ADHD. Neither surface area nor thickness differences were found in the adolescent or adult groups. Familial effects were seen for surface area in several regions. In an overlapping set of regions, surface area, but not thickness, was associated with attention problems in the Generation-R sample.

CONCLUSIONS

Subtle differences in cortical surface area are widespread in children but not adolescents and adults with ADHD, confirming involvement of the frontal cortex and highlighting regions deserving further attention. Notably, the alterations behave like endophenotypes in families and are linked to ADHD symptoms in the population, extending evidence that ADHD behaves as a continuous trait in the population. Future longitudinal studies should clarify individual lifespan trajectories that lead to nonsignificant findings in adolescent and adult groups despite the presence of an ADHD diagnosis.

Mapping the neuroanatomic substrates of cognition in familial attention deficit hyperactivity disorder

BACKGROUND

While the neuroanatomic substrates of symptoms of attention deficit hyperactivity disorder (ADHD) have been investigated, less is known about the neuroanatomic correlates of cognitive abilities pertinent to the disorder, particularly in adults. Here we define the neuroanatomic correlates of key cognitive abilities and determine if there are associations with histories of psychostimulant medication.

METHODS

We acquired neuroanatomic magnetic resonance imaging data from 264 members of 60 families (mean age 29.5; s.d. 18.4, 116 with ADHD). Using linear mixed model regression, we tested for associations between cognitive abilities (working memory, information processing, intelligence, and attention), symptoms and both cortical and subcortical volumes.

RESULTS

Symptom severity was associated with spatial working memory (t = -3.77, p = 0.0002), processing speed (t = -2.95, p = 0.004) and a measure of impulsive responding (t = 2.19, p = 0.03); these associations did not vary with age (all p &gt; 0.1). Neuroanatomic associations of cognition varied by task but centered on prefrontal, lateral parietal and temporal cortical regions, the thalamus and putamen. The neuroanatomic correlates of ADHD symptoms overlapped significantly with those of working memory (Dice's overlap coefficient: spatial, p = 0.003; verbal, p = 0.001) and information processing (p = 0.02). Psychostimulant medication history was associated with neither cognitive skills nor with a brain-cognition relationships.

CONCLUSIONS

Diagnostic differences in the cognitive profile of ADHD does not vary significantly with age; nor were cognitive differences associated with psychostimulant medication history. The neuroanatomic substrates of working memory and information overlapped with those for symptoms within these extended families, consistent with a pathophysiological role for these cognitive skills in familial ADHD.

Self-crosslinked fibrous collagen/chitosan blends: Processing, properties evaluation and monitoring of degradation by bi-fluorescence imaging

Porous collagen/chitosan scaffolds with different Collagen:Chitosan (Coll:Ch) ratios were prepared by freeze-drying followed by self-crosslinking via dehydrothermal treatment (DHT) and characterized as biomaterials for tissue engineering. Cy7 and Cy5.5 fluorochromes were covalently grafted to collagen and chitosan, respectively. Thus, it was possible, using optical fluorescence imaging of the two fluorochromes, to simultaneously track their in vivo biodegradation, in a blend scaffold form. The fluorescence signal evolution, due to the bioresorption, corroborated with histological analysis. In vitro cytocompatibility of Coll:Ch blend scaffolds were evaluated with standardized tests. In addition, the scaffolds showed a highly interconnected porous structure. Extent of crosslinking was analyzed by convergent analysis using thermogravimetry, Fourier Transform Infrared Spectroscopy and PBS uptake. The variations observed with these techniques indicate strong interactions between collagen and chitosan (covalent and hydrogen bonds) promoted by the DHT. The mechanical properties were characterized to elucidate the impact of the different processing steps in the sample preparation (DHT, neutralization and sterilization by β-irradiation) and showed a robust processing scheme with low impact of Coll:Ch composition ratio.

A multicohort, longitudinal study of cerebellar development in attention deficit hyperactivity disorder

BACKGROUND

The cerebellum supports many cognitive functions disrupted in attention deficit hyperactivity disorder (ADHD). Prior neuroanatomic studies have been often limited by small sample sizes, inconsistent findings, and a reliance on cross-sectional data, limiting inferences about cerebellar development. Here, we conduct a multicohort study using longitudinal data, to characterize cerebellar development.

METHODS

Growth trajectories of the cerebellar vermis, hemispheres and white matter were estimated using piecewise linear regression from 1,656 youth; of whom 63% had longitudinal data, totaling 2,914 scans. Four cohorts participated, all contained childhood data (age 4-12 years); two had adolescent data (12-25 years). Growth parameters were combined using random-effects meta-analysis.

RESULTS

Diagnostic differences in growth were confined to the corpus medullare (cerebellar white matter). Here, the ADHD group showed slower growth in early childhood compared to the typically developing group (left corpus medullare z = 2.49, p = .01; right z = 2.03, p = .04). This reversed in late childhood, with faster growth in ADHD in the left corpus medullare (z = 2.06, p = .04). Findings held when gender, intelligence, comorbidity, and psychostimulant medication were considered.

DISCUSSION

Across four independent cohorts, containing predominately longitudinal data, we found diagnostic differences in the growth of cerebellar white matter. In ADHD, slower white matter growth in early childhood was followed by faster growth in late childhood. The findings are consistent with the concept of ADHD as a disorder of the brain's structural connections, formed partly by developing cortico-cerebellar white matter tracts.

Growing out of attention deficit hyperactivity disorder: Insights from the 'remitted' brain

We consider developmental and cognitive models to explain why some children 'grow out' of attention deficit hyperactivity disorder (ADHD) by adulthood. The first model views remission as a convergence towards more typical brain function and structure. In support, some studies find that adult remitters are indistinguishable from those who were never affected in the neural substrates of 'top-down' mechanisms of cognitive control, some 'bottom-up' processes of vigilance/response preparation, prefrontal cortical morphology and intrinsic functional connectivity. A second model postulates that remission is driven by the recruitment of new brain systems that compensate for ADHD symptoms. It draws support from demonstrations of atypical, but possibly beneficial, patterns of connectivity within the cognitive control network in adult remitters. The final model holds that some childhood ADHD anomalies show lifelong persistence, regardless of adult outcome, supported by shared reports of anomalies in remitters and persisters in posterior cerebral and striato-thalamic regions. The models are compatible: different processes driving remission might occur in different brain regions. These models provide a framework for future studies which might inform novel treatments to 'accelerate' remission.

Neuroanatomic, epigenetic and genetic differences in monozygotic twins discordant for attention deficit hyperactivity disorder

The study of monozygotic twins discordant for attention deficit hyperactivity disorder can elucidate mechanisms that contribute to the disorder, which affects ~7% of children. First, using in vivo neuroanatomic imaging on 14 pairs of monozygotic twins (mean age 9.7, s.d. 1.9 years), we found that discordance for the disorder is mirrored by differing dimensions of deep brain structures (the striatum and cerebellum), but not the cerebral cortex. Next, using whole-blood DNA from the same twins, we found a significant enrichment of epigenetic differences in genes expressed in these 'discordant' brain structures. Specifically, there is differential methylation of probes lying in the shore and shelf and enhancer regions of striatal and cerebellar genes. Notably, gene sets pertaining to the cerebral cortex (which did not differ in volume between affected and unaffected twins) were not enriched by differentially methylated probes. Genotypic differences between the twin pairs-such as copy number and rare, single-nucleotide variants-did not contribute to phenotypic discordance. Pathway analyses of the genes implicated by the most differentially methylated probes implicated γ-aminobutyric acid (GABA), dopamine and serotonin neurotransmitter systems. The study illustrates how neuroimaging can help guide the search for epigenomic mechanisms in neurodevelopmental disorders.

Tracking Brain Development and Dimensional Psychiatric Symptoms in Children: A Longitudinal Population-Based Neuroimaging Study

OBJECTIVE

Psychiatric symptomatology during childhood predicts persistent mental illness later in life. While neuroimaging methodologies are routinely applied cross-sectionally to the study of child and adolescent psychopathology, the nature of the relationship between childhood symptoms and the underlying neurodevelopmental processes remains unclear. The authors used a prospective population-based cohort to delineate the longitudinal relationship between childhood psychiatric problems and brain development.

METHOD

A total of 845 children participated in the study. Psychiatric symptoms were measured with the parent-rated Child Behavior Checklist at ages 6 and 10. MRI data were collected at ages 8 and 10. Cross-lagged panel models and linear mixed-effects models were used to determine the associations between psychiatric symptom ratings and quantitative anatomic and white matter microstructural measures over time.

RESULTS

Higher ratings for externalizing and internalizing symptoms at baseline predicted smaller increases in both subcortical gray matter volume and global fractional anisotropy over time. The reverse relationship did not hold; thus, baseline measures of gray matter and white matter were not significantly related to changes in symptom ratings over time.

CONCLUSIONS

Children presenting with behavioral problems at an early age show differential subcortical and white matter development. Most neuroimaging models tend to explain brain differences observed in psychopathology as an underlying (causal) neurobiological substrate. However, the present work suggests that future neuroimaging studies showing effects that are pathogenic in nature should additionally explore the possibility of the downstream effects of psychopathology on the brain.

Automated quality assessment of structural magnetic resonance images in children: Comparison with visual inspection and surface-based reconstruction

Motion-related artifacts are one of the major challenges associated with pediatric neuroimaging. Recent studies have shown a relationship between visual quality ratings of T₁ images and cortical reconstruction measures. Automated algorithms offer more precision in quantifying movement-related artifacts compared to visual inspection. Thus, the goal of this study was to test three different automated quality assessment algorithms for structural MRI scans. The three algorithms included a Fourier-, integral-, and a gradient-based approach which were run on raw T₁ -weighted imaging data collected from four different scanners. The four cohorts included a total of 6,662 MRI scans from two waves of the Generation R Study, the NIH NHGRI Study, and the GUSTO Study. Using receiver operating characteristics with visually inspected quality ratings of the T₁ images, the area under the curve (AUC) for the gradient algorithm, which performed better than either the integral or Fourier approaches, was 0.95, 0.88, and 0.82 for the Generation R, NHGRI, and GUSTO studies, respectively. For scans of poor initial quality, repeating the scan often resulted in a better quality second image. Finally, we found that even minor differences in automated quality measurements were associated with FreeSurfer derived measures of cortical thickness and surface area, even in scans that were rated as good quality. Our findings suggest that the inclusion of automated quality assessment measures can augment visual inspection and may find use as a covariate in analyses or to identify thresholds to exclude poor quality data.

Subcortical brain volume differences in participants with attention deficit hyperactivity disorder in children and adults: a cross-sectional mega-analysis

BACKGROUND

Neuroimaging studies have shown structural alterations in several brain regions in children and adults with attention deficit hyperactivity disorder (ADHD). Through the formation of the international ENIGMA ADHD Working Group, we aimed to address weaknesses of previous imaging studies and meta-analyses, namely inadequate sample size and methodological heterogeneity. We aimed to investigate whether there are structural differences in children and adults with ADHD compared with those without this diagnosis.

METHODS

In this cross-sectional mega-analysis, we used the data from the international ENIGMA Working Group collaboration, which in the present analysis was frozen at Feb 8, 2015. Individual sites analysed structural T1-weighted MRI brain scans with harmonised protocols of individuals with ADHD compared with those who do not have this diagnosis. Our primary outcome was to assess case-control differences in subcortical structures and intracranial volume through pooling of all individual data from all cohorts in this collaboration. For this analysis, p values were significant at the false discovery rate corrected threshold of p=0·0156.

FINDINGS

Our sample comprised 1713 participants with ADHD and 1529 controls from 23 sites with a median age of 14 years (range 4-63 years). The volumes of the accumbens (Cohen's d=-0·15), amygdala (d=-0·19), caudate (d=-0·11), hippocampus (d=-0·11), putamen (d=-0·14), and intracranial volume (d=-0·10) were smaller in individuals with ADHD compared with controls in the mega-analysis. There was no difference in volume size in the pallidum (p=0·95) and thalamus (p=0·39) between people with ADHD and controls. Exploratory lifespan modelling suggested a delay of maturation and a delay of degeneration, as effect sizes were highest in most subgroups of children (<15 years) versus adults (>21 years): in the accumbens (Cohen's d=-0·19 vs -0·10), amygdala (d=-0·18 vs -0·14), caudate (d=-0·13 vs -0·07), hippocampus (d=-0·12 vs -0·06), putamen (d=-0·18 vs -0·08), and intracranial volume (d=-0·14 vs 0·01). There was no difference between children and adults for the pallidum (p=0·79) or thalamus (p=0·89). Case-control differences in adults were non-significant (all p>0·03). Psychostimulant medication use (all p>0·15) or symptom scores (all p>0·02) did not influence results, nor did the presence of comorbid psychiatric disorders (all p>0·5).

INTERPRETATION

With the largest dataset to date, we add new knowledge about bilateral amygdala, accumbens, and hippocampus reductions in ADHD. We extend the brain maturation delay theory for ADHD to include subcortical structures and refute medication effects on brain volume suggested by earlier meta-analyses. Lifespan analyses suggest that, in the absence of well powered longitudinal studies, the ENIGMA cross-sectional sample across six decades of ages provides a means to generate hypotheses about lifespan trajectories in brain phenotypes.

FUNDING

National Institutes of Health.

Estimating the Heritability of Structural and Functional Brain Connectivity in Families Affected by Attention-Deficit/Hyperactivity Disorder

IMPORTANCE

Despite its high heritability, few risk genes have been identified for attention-deficit/hyperactivity disorder (ADHD). Brain-based phenotypes could aid gene discovery. There is a myriad of structural and functional connections that support cognition. Disruption of such connectivity is a key pathophysiologic mechanism for ADHD, and identifying heritable phenotypes within these connections could provide candidates for genomic studies.

OBJECTIVE

To identify the structural and functional connections that are heritable and pertinent to ADHD.

DESIGN, SETTING, AND PARTICIPANTS

Members of extended multigenerational families enriched for ADHD were evaluated. Structural connectivity was defined by diffusion tensor imaging (DTI) of white matter tract microstructure and functional connectivity through resting-state functional magnetic resonance imaging (rsfMRI). Heritability and association with ADHD symptoms were estimated in 24 extended multigenerational families enriched for ADHD (305 members with clinical phenotyping, 213 with DTI, and 193 with rsfMRI data). Findings were confirmed in 52 nuclear families (132 members with clinical phenotypes, 119 with DTI, and 84 with rsfMRI). The study and data analysis were conducted from April 1, 2010, to September 1, 2016.

RESULTS

In the 52 nuclear families, 86 individuals (65.2%) were male and the mean (SD) age at imaging was 20.9 (15.0) years; in the 24 multigenerational extended families, 145 individuals (47.5%) were male and mean age at imaging was 30.4 (19.7) years. Microstructural properties of white matter tracts connecting ipsilateral cortical regions and the corpus callosum were significantly heritable, ranging from total additive genetic heritability (h2) = 0.69 (SE, 0.13; P = .0000002) for radial diffusivity of the right superior longitudinal fasciculus to h2 = 0.46 (SE, 0.15; P = .0009) for fractional anisotropy of the right inferior fronto-occipital fasciculus. Association with ADHD symptoms was found in several tracts, most strongly for the right superior longitudinal fasciculus (t = -3.05; P = .003). Heritable patterns of functional connectivity were detected within the default mode (h2 = 0.36; SE, 0.16; cluster level significance, P < .002), cognitive control (h2 = 0.32; SE, 0.15; P < .002), and ventral attention networks (h2 = 0.36; SE, 0.16; P < .002). In all cases, subregions within each network showed heritable functional connectivity with the rest of that network. More symptoms of hyperactivity/impulsivity (t = -2.63; P = .008) and inattention (t = -2.34; P = .02) were associated with decreased functional connectivity within the default mode network. Some cross-modal correlations were purely phenotypic, such as that between axial diffusivity of the right superior longitudinal fasciculus and heritable aspects of the default mode network (phenotypic correlation, ρp = -0.12; P = .03). A genetic cross-modal correlation was seen between the ventral attention network and radial diffusivity of the right inferior fronto-occipital fasciculus (genetic correlation, ρg = -0.45, P = .02).

CONCLUSIONS

Analysis of data on multigenerational extended and nuclear families identified the features of structural and functional connectivity that are both significantly heritable and associated with ADHD. In addition, shared genetic factors account for some phenotypic correlations between functional and structural connections. Such work helps to prioritize the facets of the brain's connectivity for future genomic studies.

A multicenter study of the early detection of synaptic dysfunction in Mild Cognitive Impairment using Magnetoencephalography-derived functional connectivity

Synaptic disruption is an early pathological sign of the neurodegeneration of Dementia of the Alzheimer's type (DAT). The changes in network synchronization are evident in patients with Mild Cognitive Impairment (MCI) at the group level, but there are very few Magnetoencephalography (MEG) studies regarding discrimination at the individual level. In an international multicenter study, we used MEG and functional connectivity metrics to discriminate MCI from normal aging at the individual person level. A labeled sample of features (links) that distinguished MCI patients from controls in a training dataset was used to classify MCI subjects in two testing datasets from four other MEG centers. We identified a pattern of neuronal hypersynchronization in MCI, in which the features that best discriminated MCI were fronto-parietal and interhemispheric links. The hypersynchronization pattern found in the MCI patients was stable across the five different centers, and may be considered an early sign of synaptic disruption and a possible preclinical biomarker for MCI/DAT.

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Across centers reliable abnormalities in the neuronal network organization of MCI patients

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These findings are consistent with the view that AD may, in its earliest stages, represent a disconnection syndrome.

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A high rate of classification accuracy in a blind study, especially for individuals who were cognitively normal

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All these suggest that MEG may be a useful marker of preclinical synaptic disruption.

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The hypersynchronization found in MCI patients may represent a compensatory response.

Subcortical and cortical morphological anomalies as an endophenotype in obsessive-compulsive disorder

Endophentoypes, quantifiable traits lying on the causal chain between a clinical phenotype and etiology, can be used to accelerate genomic discovery in obsessive-compulsive disorder (OCD). Here we identify the neuroanatomic changes that are shared by 22 OCD adult and adolescent patients and 25 of their unaffected siblings who are at genetic risk for the disorder. Comparisons were made against 47 age and sex matched healthy controls. We defined the surface morphology of the striatum, globus pallidus and thalamus, and thickness of the cerebral cortex. Patients with OCD show significant surface expansion compared with healthy controls, following adjustment for multiple comparisons, in interconnected regions of the caudate, thalamus and right orbitofrontal cortex. Their unaffected siblings show similar, significant expansion, most marked in the ventromedial caudate bilaterally, the right pulvinar thalamic nucleus and the right orbitofrontal cortex. These regions define a network that has been consistently implicated in OCD. In addition, both patients with OCD and unaffected siblings showed similar increased thickness of the right precuneus, which receives rich input from the thalamic pulvinar nuclei and the left medial temporal cortex. Anatomic change within the orbitofrontostriatal and posterior brain circuitry thus emerges as a promising endophenotype for OCD.

Brain structural and functional recovery following initiation of combination antiretroviral therapy

NeuroAIDS persists in the era of combination antiretroviral therapies. We describe here the recovery of brain structure and function following 6 months of therapy in a treatment-naive patient presenting with HIV-associated dementia. The patient's neuropsychological test performance improved and his total brain volume increased by more than 5 %. Neuronal functional connectivity measured by magnetoencephalography changed from a pattern identical to that observed in other HIV-infected individuals to one that was indistinguishable from that of uninfected control subjects. These data suggest that at least some of the effects of HIV on the brain can be fully reversed with treatment.

Task-related MEG source localization via discriminant analysis

To investigate the neural activity corresponding to different cognitive states, it is of great importance to localize the cortical areas that are associated with task-related modulation. In this paper, we propose a novel discriminant pattern source localization (DPSL) method to analyze MEG data. Unlike most traditional source localization methods that aim to find "dominant" sources, DPSL is developed to capture the "differential" sources that distinguish different cognitive states. As will be demonstrated by the experimental results in this paper, the proposed DPSL method offers superior accuracy to identify the spatial locations of task-related sources.

Tracking neural coding of perceptual and semantic features of concrete nouns

We present a methodological approach employing magnetoencephalography (MEG) and machine learning techniques to investigate the flow of perceptual and semantic information decodable from neural activity in the half second during which the brain comprehends the meaning of a concrete noun. Important information about the cortical location of neural activity related to the representation of nouns in the human brain has been revealed by past studies using fMRI. However, the temporal sequence of processing from sensory input to concept comprehension remains unclear, in part because of the poor time resolution provided by fMRI. In this study, subjects answered 20 questions (e.g. is it alive?) about the properties of 60 different nouns prompted by simultaneous presentation of a pictured item and its written name. Our results show that the neural activity observed with MEG encodes a variety of perceptual and semantic features of stimuli at different times relative to stimulus onset, and in different cortical locations. By decoding these features, our MEG-based classifier was able to reliably distinguish between two different concrete nouns that it had never seen before. The results demonstrate that there are clear differences between the time course of the magnitude of MEG activity and that of decodable semantic information. Perceptual features were decoded from MEG activity earlier in time than semantic features, and features related to animacy, size, and manipulability were decoded consistently across subjects. We also observed that regions commonly associated with semantic processing in the fMRI literature may not show high decoding results in MEG. We believe that this type of approach and the accompanying machine learning methods can form the basis for further modeling of the flow of neural information during language processing and a variety of other cognitive processes.

Potential utility of resting-state magnetoencephalography as a biomarker of CNS abnormality in HIV disease

There is a lack of a neuroimaging biomarker for HIV-Associated Neurocognitive Disorder. We report magnetoencephalography (MEG) data from patients with HIV disease and risk-group appropriate controls that were collected to determine the MEG frequency profile during the resting state, and the stability of the profile over 24 weeks. 17 individuals (10 HIV+, 7 HIV-) completed detailed neurobehavioral evaluations and 10min of resting-state MEG acquisition with a 306-channel whole-head system. The entire evaluation and MEG measurement were repeated 24 weeks later. Relative MEG power in the delta (0-4Hz), theta (4-7Hz), alpha (8-12Hz), beta (12-30Hz) and low gamma (30-50Hz) bands was computed for 8 predefined sensor groups. The median stability of resting-state relative power over 24 weeks of follow-up was .80 with eyes closed, and .72 with eyes open. The relative gamma power in the right occipital (t(15)=1.99, p<.06, r=-.46) and right frontal (t(15)=2.15, p<.05, r=-.48) regions was associated with serostatus. The effect of age on delta power was greater in the seropositive subjects (r(2)=.51) than in the seronegative subjects (r(2)=.11). Individuals with high theta-to-gamma ratios tended to have lower cognitive test performance, regardless of serostatus. The stability of the wide-band MEG frequency profiles over 24 weeks supports the utility of MEG as a biomarker. The links between the MEG profile, serostatus, and cognition suggest further research on its potential in HAND is needed.

Magnetoencephalography as a putative biomarker for Alzheimer's disease

Alzheimer's Disease (AD) is the most common dementia in the elderly and is estimated to affect tens of millions of people worldwide. AD is believed to have a prodromal stage lasting ten or more years. While amyloid deposits, tau filaments, and loss of brain cells are characteristics of the disease, the loss of dendritic spines and of synapses predate such changes. Popular preclinical detection strategies mainly involve cerebrospinal fluid biomarkers, magnetic resonance imaging, metabolic PET scans, and amyloid imaging. One strategy missing from this list involves neurophysiological measures, which might be more sensitive to detect alterations in brain function. The Magnetoencephalography International Consortium of Alzheimer's Disease arose out of the need to advance the use of Magnetoencephalography (MEG), as a tool in AD and pre-AD research. This paper presents a framework for using MEG in dementia research, and for short-term research priorities.

Clustering linear discriminant analysis for MEG-based brain computer interfaces

In this paper, we propose a clustering linear discriminant analysis algorithm (CLDA) to accurately decode hand movement directions from a small number of training trials for magnetoencephalography-based brain computer interfaces (BCIs). CLDA first applies a spectral clustering algorithm to automatically partition the BCI features into several groups where the within-group correlation is maximized and the between-group correlation is minimized. As such, the covariance matrix of all features can be approximated as a block diagonal matrix, thereby facilitating us to accurately extract the correlation information required by movement decoding from a small set of training data. The efficiency of the proposed CLDA algorithm is theoretically studied and an error bound is derived. Our experiment on movement decoding of five human subjects demonstrates that CLDA achieves superior decoding accuracy over other traditional approaches. The average accuracy of CLDA is 87% for single-trial movement decoding of four directions (i.e., up, down, left, and right).

Wetting transition on hydrophobic surfaces covered by polyelectrolyte brushes

We study the wetting by water of complex "hydrophobic-hydrophilic" surfaces made of a hydrophobic substrate covered by a hydrophilic polymer brush. Polystyrene (PS) substrates covered with polystyrene- block-poly(acrylic acid) PS- b-PAA diblock copolymer layers were fabricated by Langmuir-Schaefer depositions and analyzed by atomic force microscopy (AFM) and ellipsometry. On bare PS substrate, we measured advancing angles theta A = 93 +/- 1 degrees and receding angles theta R = 81 +/- 1 degrees . On PS covered with poorly anchored PS- b-PAA layers, we observed large contact angle hysteresis, theta A approximately 90 degrees and theta R approximately 0 degrees , that we attributed to nanometric scale dewetting of the PS- b-PAA layers. On well-anchored PS- b-PAA layers that form homogeneous PAA brushes, a wetting transition from partial to total wetting occurs versus the amount deposited: both theta A and theta R decrease close to zero. A model is proposed, based on the Young-Dupre equation, that takes into account the interfacial pressure of the brush Pi, which was determined experimentally, and the free energy of hydration of the polyelectrolyte monomers Delta G PAA (hyd), which is the only fitting parameter. With Delta G PAA (hyd) approximately -1300 J/mol, the model renders the wetting transition for all samples and explains why the wetting transition depends mainly on the average thickness of the brush and weakly on the length of PAA chains.