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 (ß = -0.74, CI = [-1.27 to -0.20], FDR-corrected p = 0.048) and, at nominal significance levels in the WNH ancestry subcohort (ß = -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. ß = -0.13, CI = [-0.23 to -0.029], FDR-corrected p = 0.048; WNH. ß = -0.17, CI = [-0.29 to -0.050], FDR-corrected p = 0.044) as did the total length of CNV deletions (whole cohort. ß = -0.12, CI = [-0.19 to -0.044], FDR-corrected p = 0.028; WNH. ß = -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.

Mapping the cortico-striatal transcriptome in attention deficit hyperactivity disorder.

Despite advances in identifying rare and common genetic variants conferring risk for ADHD, the lack of a transcriptomic understanding of cortico-striatal brain circuitry has stymied a molecular mechanistic understanding of this disorder. To address this gap, we mapped the transcriptome of the caudate nucleus and anterior cingulate cortex in post-mortem tissue from 60 individuals with and without ADHD. Significant differential expression of genes was found in the anterior cingulate cortex and, to a lesser extent, the caudate. Significant downregulation emerged of neurotransmitter gene pathways, particularly glutamatergic, in keeping with models that implicate these neurotransmitters in ADHD. Consistent with the genetic overlap between mental disorders, correlations were found between the cortico-striatal transcriptomic changes seen in ADHD and those seen in other neurodevelopmental and mood disorders. This transcriptomic evidence points to cortico-striatal neurotransmitter anomalies in the pathogenesis of ADHD, consistent with current models of the disorder.

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 (ß = 0.65, t = 2.03, P = 0.045) and even more remotely connected peers (ß = 0.77, t = 2.83, P = 0.006); friends-of-friends did not differ from more distantly connected peers (ß = -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."

Predicting the course of ADHD symptoms through the integration of childhood genomic, neural, and cognitive features.

Childhood attention deficit hyperactivity disorder (ADHD) shows a highly variable course with age: some individuals show improving, others stable or worsening symptoms. The ability to predict symptom course could help individualize treatment and guide interventions. By studying a cohort of 362 youth, we ask if polygenic risk for ADHD, combined with baseline neural and cognitive features could aid in the prediction of the course of symptoms over an average period of 4.8 years. Compared to a never-affected comparison group, we find that participants with worsening symptoms carried the highest polygenic risk for ADHD, followed by those with stable symptoms, then those whose symptoms improved. Participants with worsening symptoms also showed atypical baseline cognition. Atypical microstructure of the cingulum bundle and anterior thalamic radiation was associated with improving symptoms while reduction of thalamic volume was found in those with stable symptoms. Machine-learning algorithms, trained and tested on independent groups, performed well in classifying those never affected against groups with worsening, stable, and improving symptoms (area under the curve >0.79). We conclude that some measures of polygenic risk, cognition, and neuroimaging show significant associations with the future course of ADHD symptoms and may have modest predictive power. These features warrant further exploration as prognostic tools.

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 ß = -0.034 (CI: -0.065 to -0.01), by thickness of the left dorsomedial prefrontal (ß = -0.029; CI: -0.061 to -0.0047) and area of the right lateral temporal cortex (ß = 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 ß = -0.014 (CI: -0.038 to -0.0026); focused attention ß = -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.

Multimodal mapping of the brain's functional connectivity and the adult outcome of attention deficit hyperactivity disorder.

We have a limited understanding of why many children with attention deficit hyperactivity disorder do not outgrow the disorder by adulthood. Around 20-30% retain the full syndrome as young adults, and about 50% show partial, rather than complete, remission. Here, to delineate the neurobiology of this variable outcome, we ask if the persistence of childhood symptoms into adulthood impacts on the brain's functional connectivity. We studied 205 participants followed clinically since childhood. In early adulthood, participants underwent magnetoencephalography (MEG) to measure neuronal activity directly and functional MRI (fMRI) to measure hemodynamic activity during a task-free period (the "resting state"). We found that symptoms of inattention persisting into adulthood were associated with disrupted patterns of typical functional connectivity in both MEG and fMRI. Specifically, those with persistent inattention lost the typical balance of connections within the default mode network (DMN; prominent during introspective thought) and connections between this network and those supporting attention and cognitive control. By contrast, adults whose childhood inattentive symptoms had resolved did not differ significantly from their never-affected peers, both hemodynamically and electrophysiologically. The anomalies in functional connectivity tied to clinically significant inattention centered on midline regions of the DMN in both MEG and fMRI, boosting confidence in a possible pathophysiological role. The findings suggest that the clinical course of this common childhood onset disorder impacts the functional connectivity of the adult brain.

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.

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 > 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.

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.

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.

Multivariate analysis of correlation between electrophysiological and hemodynamic responses during cognitive processing.

Animal and human studies have frequently shown that in primary sensory and motor regions the BOLD signal correlates positively with high-frequency and negatively with low-frequency neuronal activity. However, recent evidence suggests that this relationship may also vary across cortical areas. Detailed knowledge of the possible spectral diversity between electrophysiological and hemodynamic responses across the human cortex would be essential for neural-level interpretation of fMRI data and for informative multimodal combination of electromagnetic and hemodynamic imaging data, especially in cognitive tasks. We applied multivariate partial least squares correlation analysis to MEG-fMRI data recorded in a reading paradigm to determine the correlation patterns between the data types, at once, across the cortex. Our results revealed heterogeneous patterns of high-frequency correlation between MEG and fMRI responses, with marked dissociation between lower and higher order cortical regions. The low-frequency range showed substantial variance, with negative and positive correlations manifesting at different frequencies across cortical regions. These findings demonstrate the complexity of the neurophysiological counterparts of hemodynamic fluctuations in cognitive processing.

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.

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.

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.

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.

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.

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.

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.

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.

An examination of the relationships between attention/deficit hyperactivity disorder symptoms and functional connectivity over time.

Previous cross-sectional work has demonstrated resting-state connectivity abnormalities in children and adolescents with attention/deficit hyperactivity disorder (ADHD) relative to typically developing controls. However, it is unclear to what extent these neural abnormalities confer risk for later symptoms of the disorder, or represent the downstream effects of symptoms on functional connectivity. Here, we studied 167 children and adolescents (mean age at baseline = 10.74 years (SD = 2.54); mean age at follow-up = 13.3 years (SD = 2.48); 56 females) with varying levels of ADHD symptoms, all of whom underwent resting-state functional magnetic resonance imaging and ADHD symptom assessments on two occasions during development. Resting-state functional connectivity was quantified using eigenvector centrality mapping. Using voxelwise cross-lag modeling, we found that less connectivity at baseline within right inferior frontal gyrus was associated with more follow-up symptoms of inattention (significant at an uncorrected cluster-forming threshold of p ≤ 0.001 and a cluster-level familywise error corrected threshold of p < 0.05). Findings suggest that previously reported cross-sectional abnormalities in functional connectivity within inferior frontal gyrus in patients with ADHD may represent a longitudinal risk factor for the disorder, in line with efforts to target this region with novel therapeutic methods.