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Background: The combination of structural and functional analyses is a biologically valid approach that offers methodological advantages in autism spectrum disorder (ASD) neuroimaging science. The paucity of studies combining these methods constitutes an important knowledge gap. In this study, we investigate structural abnormalities and their associated functional differences in a developmentally homogeneous ASD cohort. Methods: Whole-brain voxel-based morphometry (VBM) analyses were performed on 28 ASD participants and 38 age-matched typically developing healthy controls (HC) to derive gray matter (GM) volume differences. The anatomically relevant clusters identified by VBM served as seed regions of interest (ROI) for resting-state functional-connectivity (RsFc) analysis. Results: Whole-brain VBM analyses revealed significant right lateralized GM volume abnormality in the ASD group, with lower GM volumes in cerebellar lobules VIIb/VIIIa (cluster 1) and significantly higher GM volumes in posterior middle/superior temporal gyri (Brodmann area [BA] 21/22, cluster 2) compared with HC. Whole-brain RsFc analysis in high-functioning ASD (HF-ASD) revealed significant hypoconnectivity of the cerebellar VBM cluster with the right cerebral cortical regions of superior parietal lobule (BA 7) and occipital pole (BA 19) (overlapping with dorsal attention and visual networks, respectively). Cerebral cortical VBM cluster (cluster 2) revealed significant hypoconnectivity in HF-ASD with other task-positive cerebral cortical including the left lateral prefrontal cortex (frontoparietal network) and some aspects of the insula (ventral attention network) and ectopic positive connectivity (lack of anticorrelations) with posterior cingulate cortex and medial prefrontal cortex (default mode network). Conclusions: The cerebro-cerebellar intrinsic functional dysconnectivity based on the whole-brain VBM-derived ROIs may advance our understanding of the compensatory mechanisms associated with ASD and offer cerebellum as a potential target for diagnostic, predictive, prognostic, and therapeutic interventions in ASD. Our findings also provide additional support indicating that functional abnormalities as indexed by RsFc exist in ASD, and highlight that there is likely a relationship between structural and functional abnormalities in this disorder. Impact statement Our findings indicate that functional differences as indexed by resting-state functional connectivity exist in autism spectrum disorder (ASD), and highlight that there is likely a relationship between structural and functional abnormalities in this disorder. Future developments in neuroimaging research should continue investigating structural and associated functional differences in ASD, and in this way complement the behavioral characterization of this disorder, potentially improving diagnosis, prognosis, and prediction.

Diffusion MRI tractography produces massive sets of streamlines that need to be clustered into anatomically meaningful white-matter bundles. Conventional clustering techniques group streamlines based on their proximity in Euclidean space. We have developed AnatomiCuts, an unsupervised method for clustering tractography streamlines based on their neighboring anatomical structures, rather than their coordinates in Euclidean space. In this work, we show that the anatomical similarity metric used in AnatomiCuts can be extended to find corresponding clusters across subjects and across hemispheres, without inter-subject or inter-hemispheric registration. Our proposed approach enables group-wise tract cluster analysis, as well as studies of hemispheric asymmetry. We evaluate our approach on data from the pilot MGH-Harvard-USC Lifespan Human Connectome project, showing improved correspondence in tract clusters across 184 subjects aged 8-90. Our method shows up to 38% improvement in the overlap of corresponding clusters when comparing subjects with large age differences. The techniques presented here do not require registration to a template and can thus be applied to populations with large inter-subject variability, e.g., due to brain development, aging, or neurological disorders.

During adolescence, rapid development and reorganization of the dopaminergic system supports increasingly sophisticated reward learning and the ability to exert behavioral control. Disruptions in the ability to exert control over previously rewarded behavior may underlie some forms of adolescent psychopathology. Specifically, symptoms of externalizing psychopathology may be associated with difficulties in flexibly adapting behavior in the context of reward. However, the direct interaction of cognitive control and reward learning in adolescent psychopathology symptoms has not yet been investigated. The present study used a Research Domain Criteria framework to investigate whether behavioral and neuronal indices of inhibition to previously rewarded stimuli underlie individual differences in externalizing symptoms in N = 61 typically developing adolescents. Using a task that integrates the Monetary Incentive Delay and Go-No-Go paradigms, we observed a positive association between externalizing symptoms and activation of the left middle frontal gyrus during response inhibition to cues with a history of reward. These associations were robust to controls for internalizing symptoms and neural recruitment during inhibition of cues with no reward history. Our findings suggest that inhibitory control over stimuli with a history of reward may be a useful marker for future inquiry into the development of externalizing psychopathology in adolescence.

Individuals vary widely in their tendency to seek stimulation and act impulsively, early developing traits with genetic origins. Failures to regulate these behaviors increase risk for maladaptive outcomes including substance abuse. Here, we explored the neuroanatomical correlates of sensation seeking and impulsivity in healthy young adults. Our analyses revealed links between sensation seeking and reduced cortical thickness that were preferentially localized to regions implicated in cognitive control, including anterior cingulate and middle frontal gyrus (n= 1015). These associations generalized to self-reported motor impulsivity, replicated in an independent group (n= 219), and correlated with heightened alcohol, tobacco, and caffeine use. Critically, the relations between sensation seeking and brain structure were evident in participants without a history of alcohol or tobacco use, suggesting that observed associations with anatomy are not solely a consequence of substance use. These results demonstrate that individual differences in the tendency to seek stimulation, act on impulse, and engage in substance use are correlated with the anatomical structure of cognitive control circuitry. Our findings suggest that, in healthy populations, covariation across these complex multidimensional behaviors may in part originate from a common underlying biology.SIGNIFICANCE STATEMENTImpaired cognitive control may result in a tendency to seek stimulation impulsively and an increased risk for maladaptive outcomes, including substance abuse. Here, we examined the structural correlates of sensation seeking and impulsivity in a large cohort of healthy young adults. Our analyses revealed links between sensation seeking and reduced cortical thickness that were preferentially localized to regions implicated in cognitive control, including anterior cingulate and middle frontal gyrus. The observed associations generalized to motor impulsivity, replicated in an independent group, and predicted heightened alcohol, tobacco, and caffeine use. These data indicate that normal variability in cognitive control system anatomy predicts sensation seeking and motor impulsivity in the healthy populations, potentially increasing risk for substance use disorders.

The goal of the Brain Genomics Superstruct Project (GSP) is to enable large-scale exploration of the links between brain function, behavior, and ultimately genetic variation. To provide the broader scientific community data to probe these associations, a repository of structural and functional magnetic resonance imaging (MRI) scans linked to genetic information was constructed from a sample of healthy individuals. The initial release, detailed in the present manuscript, encompasses quality screened cross-sectional data from 1,570 participants ages 18 to 35 years who were scanned with MRI and completed demographic and health questionnaires. Personality and cognitive measures were obtained on a subset of participants. Each dataset contains a T1-weighted structural MRI scan and either one (n=1,570) or two (n=1,139) resting state functional MRI scans. Test-retest reliability datasets are included from 69 participants scanned within six months of their initial visit. For the majority of participants self-report behavioral and cognitive measures are included (n=926 and n=892 respectively). Analyses of data quality, structure, function, personality, and cognition are presented to demonstrate the dataset’s utility.

The MGH-USC CONNECTOM MRI scanner housed at the Massachusetts General Hospital (MGH) is a major hardware innovation of the Human Connectome Project (HCP). The 3T CONNECTOM scanner is capable of producing a magnetic field gradient of up to 300 mT/m strength for in vivo human brain imaging, which greatly shortens the time spent on diffusion encoding, and decreases the signal loss due to T2 decay. To demonstrate the capability of the novel gradient system, data of healthy adult participants were acquired for this MGH-USC Adult Diffusion Dataset (N=35), minimally preprocessed, and shared through the Laboratory of Neuro Imaging Image Data Archive (LONI IDA) and the WU-Minn Connectome Database (ConnectomeDB). Another purpose of sharing the data is to facilitate methodological studies of diffusion MRI (dMRI) analyses utilizing high diffusion contrast, which perhaps is not easily feasible with standard MR gradient system. In addition, acquisition of the MGH-Harvard-USC Lifespan Dataset is currently underway to include 120 healthy participants ranging from 8 to 90 years old, which will also be shared through LONI IDA and ConnectomeDB. Here we describe the efforts of the MGH-USC HCP consortium in acquiring and sharing the ultra-high b-value diffusion MRI data and provide a report on data preprocessing and access. We conclude with a demonstration of the example data, along with results of standard diffusion analyses, including q-ball Orientation Distribution Function (ODF) reconstruction and tractography.

Background Depression is a common source of human disability for which etiologic insights remain limited. Although abnormalities of monoamine neurotransmission, including dopamine, are theorized to contribute to the pathophysiology of depression, evidence linking dopamine-related genes to depression has been mixed. The current study sought to address this knowledge-gap by examining whether the combined effect of dopamine polymorphisms was associated with depressive symptomatology in both healthy individuals and individuals with depression. Methods Data were drawn from three independent samples: (1) a discovery sample of healthy adult participants (n = 273); (2) a replication sample of adults with depression (n = 1,267); and (3) a replication sample of healthy adult participants (n = 382). A genetic risk score was created by combining functional polymorphisms from five genes involved in synaptic dopamine availability (COMT and DAT) and dopamine receptor binding (DRD1, DRD2, DRD3). Results In the discovery sample, the genetic risk score was associated with depressive symptomatology (β = −0.80, p = 0.003), with lower dopamine genetic risk scores (indicating lower dopaminergic neurotransmission) predicting higher levels of depression. This result was replicated with a similar genetic risk score based on imputed genetic data from adults with depression (β = −0.51, p = 0.04). Results were of similar magnitude and in the expected direction in a cohort of healthy adult participants (β = −0.86, p = 0.15). Conclusions Sequence variation in multiple genes regulating dopamine neurotransmission may influence depressive symptoms, in a manner that appears to be additive. Further studies are required to confirm the role of genetic variation in dopamine metabolism and depression.

Individual differences in affective and social processes may arise from variability in amygdala-medial prefrontal (mPFC) circuitry and related genetic heterogeneity. To explore this possibility in humans, we examined the structural correlates of trait negative affect in a sample of 1050 healthy young adults with no history of psychiatric illness. Analyses revealed that heightened negative affect was associated with increased amygdala volume and reduced thickness in a left mPFC region encompassing the subgenual and rostral anterior cingulate cortex. The most extreme individuals displayed an inverse correlation between amygdala volume and mPFC thickness, suggesting that imbalance between these structures is linked to negative affect in the general population. Subgroups of participants were further evaluated on social (n= 206) and emotional (n= 533) functions. Individuals with decreased mPFC thickness exhibited the poorest social cognition and were least able to correctly identify facial emotion. Given prior links between disrupted amygdala–mPFC circuitry and the presence of major depressive disorder (MDD), we explored whether the individual differences in anatomy observed here in healthy young adults were associated with polygenic risk for MDD (n= 438) using risk scores derived from a large genome-wide association analysis (n= 18,759). Analyses revealed associations between increasing polygenic burden for MDD and reduced cortical thickness in the left mPFC. These collective findings suggest that, within the healthy population, there is significant variability in amygdala–mPFC circuitry that is associated with poor functioning across affective and social domains. Individual differences in this circuitry may arise, in part, from common genetic variability that contributes to risk for MDD.

Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.