Faculty Bibliography

OBJECTIVE: A substantial proportion of children with attention-deficit/hyperactivity disorder (ADHD) also display emotion regulation deficits manifesting as chronic irritability, severe temper outbursts, and aggression. The amygdala is implicated in emotion regulation, but its connectivity and relation to emotion regulation in ADHD has yet to be explored. The purpose of this study was to examine the relationship between intrinsic functional connectivity (iFC) of amygdala circuits and emotion regulation deficits in youth with ADHD. METHOD: Bilateral amygdala iFC was examined using functional magnetic resonance imaging in 63 children with ADHD, aged 6 to 13 years. First, we examined the relationship between amygdala IFC and parent ratings of emotional lability (EL) in children with ADHD. Second, we compared amygdala iFC across subgroups of children with ADHD and high EL (n = 18), ADHD and low EL (n = 20), and typically developing children (TDC), all with low EL (n = 19). RESULTS: Higher EL ratings were associated with greater positive iFC between the amygdala and rostral anterior cingulate cortex in youth with ADHD. EL scores were also negatively associated with iFC between bilateral amygdala and posterior insula/superior temporal gyrus. Patterns of amygdala-cortical iFC in ADHD participants with low EL were not different from the comparison group, and the effect sizes for these comparisons were smaller than those for the trend-level differences observed between the high-EL and TDC groups. CONCLUSIONS: In children with ADHD and a range of EL, deficits in emotion regulation were associated with altered amygdala-cortical iFC. When comparing groups that differed on ADHD status but not EL, differences in amygdala iFC were small and nonsignificant, highlighting the specificity of this finding to emotional deficits, independent of other ADHD symptoms.

The default network of the human brain has drawn much attention due to its relevance to various brain disorders, cognition, and behavior. However, its functional components and boundaries have not been precisely defined. There is no consensus as to whether the precuneus, a hub in the functional connectome, acts as part of the default network. This discrepancy is more critical for brain development and aging studies: it is not clear whether age has a stronger impact on the default network or precuneus, or both. We used Generalized Ranking and Averaging Independent Component Analysis by Reproducibility (gRAICAR) to investigate the lifespan trajectories of intrinsic functional networks. By estimating individual-specific spatial components and aligning them across subjects, gRAICAR measures the spatial variation of component maps across a population without constraining the same components to appear in every subject. In a cross-lifespan fMRI dataset (N=126, 7-85years old), we observed stronger age dependence in the spatial pattern of a precuneus-dorsal posterior cingulate cortex network compared to the default network, despite the fact that the two networks exhibit considerable spatial overlap and temporal correlation. These results remained even when analyses were restricted to a subpopulation with very similar head motion across age. Our analyses further showed that the two networks tend to merge with increasing age. Post-hoc analyses of functional connectivity confirmed the distinguishable cross-lifespan trajectories between the two networks. Based on these observations, we proposed a dynamic model of cross-lifespan functional segregation and integration between the two networks, suggesting that the precuneus network may have a different functional role than the default network, which declines with age. These findings have implications for understanding the functional roles of the default network, gaining insight into its dynamics throughout life, and guiding interpretation of alterations in brain disorders.

BACKGROUND: Alzheimer's disease (AD) is the most common cause of dementia; the main risk factors are age and several recently identified genes. A major challenge for AD research is the early detection of subjects at risk. The aim of this study is to develop a predictive model using proton magnetic resonance spectroscopy (1H-MRS), a noninvasive technique that evaluates brain chemistry in vivo, for monitoring the clinical outcome of carriers of a fully penetrant mutation that causes AD. METHODS: We studied 75 subjects from the largest multigenerational pedigree in the world ( approximately 5000 people) that segregates a unique form of early-onset Alzheimer's disease (EOAD) caused by a fully penetrant mutation in the Presenilin-1 gene (PSEN1 p.Glu280Ala [E280 A]). Forty-four subjects were carriers of the mutation, and 31 were noncarriers. Seventeen carriers had either mild cognitive impairment (MCI) or early-stage AD (collectively MCI-AD). In right and left parietal white mater and parasagittal parietal gray matter (RPPGM and LPPGM) of the posterior cingulate gyrus and precuneus, we measured levels of the brain metabolites N-acetylaspartate (NAA), inositol (Ins), choline (Cho), and glutamate-glutamine complex (Glx) relative to creatine (Cr) levels (NAA/Cr, Ins/Cr, Cho/Cr, and Glx/Cr, respectively) with two-dimensional 1H-MRS. Using advanced recursive partition analysis and random forest analysis, we built classificatory decision trees for both mutation carrier status and the presence of MCI-AD symptoms, fitting them to 1H-MRS data while controlling for age, educational level, and sex. RESULTS: We found that (1) the combination of LPPGM Cho/Cr <0.165 and RPPGM Glx/Cr >1.54 fully excluded carriers; (2) LPPGM Cho/Cr >0.165, RPPGM Glx/Cr <1.54, and left parietal white mater NAA/Cr >1.16 identified asymptomatic carriers with sensitivity of 97.7% and specificity of 77.4%; and (3) RPPGM NAA/Cr >1.05 defined asymptomatic subjects (independent of carrier status) with sensitivity of 100% and a specificity of 96.6%. CONCLUSIONS: Brain metabolites measured by 1H-MRS in the posterior cingulate gyrus and precuneus are optimally sensitive and specific potential noninvasive biomarkers of subclinical emergence of AD caused by the PSEN1 p.Glu280Ala (E280 A) mutation.

Human brain function undergoes complex transformations across the lifespan. We employed resting-state functional MRI and graph-theory approaches to systematically chart the lifespan trajectory of the topological organization of human whole-brain functional networks in 126 healthy individuals ranging in age from 7 to 85 years. Brain networks were constructed by computing Pearson's correlations in blood-oxygenation-level-dependent temporal fluctuations among 1024 parcellation units followed by graph-based network analyses. We observed that the human brain functional connectome exhibited highly preserved non-random modular and rich club organization over the entire age range studied. Further quantitative analyses revealed linear decreases in modularity and inverted-U shaped trajectories of local efficiency and rich club architecture. Regionally heterogeneous age effects were mainly located in several hubs (e.g., default network, dorsal attention regions). Finally, we observed inverse trajectories of long- and short-distance functional connections, indicating that the reorganization of connectivity concentrates and distributes the brain's functional networks. Our results demonstrate topological changes in the whole-brain functional connectome across nearly the entire human lifespan, providing insights into the neural substrates underlying individual variations in behavior and cognition. These results have important implications for disease connectomics because they provide a baseline for evaluating network impairments in age-related neuropsychiatric disorders.

Differential core symptoms and treatment responses are associated with the pure versus comorbid forms of attention-deficit/hyperactivity disorder (ADHD). However, comorbidity has largely been unaccounted for in neuroimaging studies of ADHD. We used diffusional kurtosis imaging to investigate gray matter (GM) and white matter (WM) microstructure of children and adolescents with ADHD (n = 22) compared to typically developing controls (TDC, n = 27) and examined whether differing developmental patterns are related to comorbidity. The ADHD group (ADHD-mixed) consisted of subgroups with and without comorbidity (ADHD-comorbid, n = 11; ADHD-pure, n = 11, respectively). Age-related changes and group differences in cerebral microstructure of the ADHD-mixed group and each ADHD subgroup were compared to TDC. Whole-brain voxel-based analyses with mean kurtosis (MK) and mean diffusivity (MD) metrics were conducted to probe GM and WM. Tract-based spatial statistics analyses of WM were performed with MK, MD, fractional anisotropy, and directional (axial, radial) kurtosis and diffusivity metrics. ADHD-pure patients lacked significant age-related changes in GM and WM microstructure that were observed globally in TDC and had significantly greater WM microstructural complexity than TDC in bilateral frontal and parietal lobes, insula, corpus callosum, and right external and internal capsules. Including ADHD patients with diverse comorbidities in analyses masked these findings. A distinct atypical age-related trajectory and aberrant regional differences in brain microstructure were detected in ADHD without comorbidity. Our results suggest that different phenotypic manifestations of ADHD, defined by the presence or absence of comorbidity, differ in cerebral microstructural markers. Hum Brain Mapp, 2013. (c) 2013 Wiley Periodicals, Inc.

The connectivity of neuronal systems is their most fundamental characteristic. Here, we focus on recent developments in understanding structural and functional connectivity at the macroscale, which is accessible with current imaging technology. Structural connectivity is examined via diffusion weighted imaging methods, of which diffusion tensor imaging is the most frequently used. Many cross-sectional and an increasing number of longitudinal studies using diffusion tensor imaging have been recently conducted over the period of development starting with newborns. Functional connectivity has been studied through task-based functional magnetic resonance imaging, and increasingly through studies on task-free functional imaging, also known as resting state functional imaging. The study of intrinsic functional connectivity beginning during fetal life reveals the developmental organization of intrinsic connectivity networks such as the default mode network, the dorsal attention network, the frontal-parietal executive control network, as well as primary cortical networks. As methods of examining both structural and functional connectivity mature, they increasingly inform our understanding of the development of connectivity in service of the long-term goal of delineating the substrates of much of developmental psychopathology.

Autism spectrum disorders (ASDs) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, lifelong nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. Although the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE)-a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) data sets with corresponding structural MRI and phenotypic information from 539 individuals with ASDs and 573 age-matched typical controls (TCs; 7-64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 male subjects with ASDs and 403 male age-matched TCs. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo- and hyperconnectivity in the ASD literature; both were detected, although hypoconnectivity dominated, particularly for corticocortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASDs (mid- and posterior insula and posterior cingulate cortex), and highlighted less commonly explored regions such as the thalamus. The survey of the ABIDE R-fMRI data sets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international data sets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies.Molecular Psychiatry advance online publication, 18 June 2013; doi:10.1038/mp.2013.78.

Despite the common co-occurrence of symptoms of attention deficit hyperactivity disorder (ADHD) in individuals with autism spectrum disorders (ASD), the underlying mechanisms are under-explored. A potential candidate for investigation is response time intra-subject variability (RT-ISV), a hypothesized marker of attentional lapses. Direct comparisons of RT-ISV in ASD versus ADHD are limited and contradictory. We aimed to examine whether distinct fluctuations in RT-ISV characterize children with ASD and with ADHD relative to typically developing children (TDC). We applied both a priori-based and data-driven strategies to RT performance of 46 children with ASD, 46 with ADHD, and 36 TDC (aged 7-11.9 years). Specifically, we contrasted groups relative to the amplitude of four preselected frequency bands as well as to 400 frequency bins from 0.006 to 0.345 Hz. In secondary analyses, we divided the ASD group into children with and without substantial ADHD symptoms (ASD+ and ASD-, respectively). Regardless of the strategy employed, RT-ISV fluctuations at frequencies between 0.20 and 0.345 Hz distinguished children with ADHD, but not children with ASD, from TDC. Children with ASD+ and those with ADHD shared elevated amplitudes of RT-ISV fluctuations in frequencies between 0.18 and 0.345 Hz relative to TDC. In contrast, the ASD- subgroup did not differ from TDC in RT-ISV frequency fluctuations. RT-ISV fluctuations in frequencies 0.18-0.345 Hz (i.e., periods between 3 and 5 s) are associated with ADHD symptoms regardless of categorical diagnosis and may represent a biomarker. These results suggest that children with ADHD and those with ASD+ share common underlying pathophysiological mechanisms of RT-ISV.

Objective: Increased response-time (RT) fluctuations below 0.2 Hz have been reported as characteristic of ADHD in some but not all studies, possibly due to methodological differences. Accordingly, We contrasted two tasks and two analytical approaches in the same sample of children with ADHD. Method: Fifty-two children with ADHD and 49 typically developing children completed an Eriksen Flanker Task and a fixed-sequence version of the sustained attention to response task. RT fluctuations with two different frequency analyses were examined. Results: Robust ADHD-related increases of slow RT fluctuations within all frequencies were found in both tasks. Tasks were significantly correlated in both groups for frequencies above 0.07 Hz. RT fluctuations across all frequencies were greatest in children with ADHD with abnormally elevated omissions. Conclusion: We observed significantly increased fluctuations of RT in children with ADHD across two different tasks and methods supporting the hypothesis that slow frequency RT fluctuations reflect neurophysiological processes underlying ADHD. (J. of Att. Dis. 2012; XX(X) 1-XX).

In the clinical area, some symptoms of attention deficit hyperactivity disorder (ADHD) also present in patients with autism spectrum disorders (ASD). Research has shown that there are alterations in brain circuits that have an impact upon specific cognitive and behavioural failures in each of these disorders. Yet, little research has been conducted on the brain correlates underlying both the similarities and the differences in the symptoms. In this review, the structural and functional meta-analytical studies that have been carried out to date on ADHD and ASD have been analysed. On the one hand, there are convergences in the attentional dorsal, executive functions, visual, somatomotor circuits and the default activation circuit. These similarities can account for the comorbid manifestations between the disorders, such as failure in the integration of information, fine motor control and specific attention processes. On the other hand, specifically in ADHD, there is a deficit in the reward circuit and in the attentional ventral, which are systems involved in the measurement of the effects of reinforcement and monitoring of attention. In ASD, the circuits that are most strongly affected are those involved in social cognition and language processes. In conclusion, there are neuronal correlates in both disorders that explain both the convergent and divergent clinical and behavioural manifestations.