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  • 1
    Online Resource
    Online Resource
    Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium
    Proceedings of the National Academy of Sciences ; 2018
    In:  Proceedings of the National Academy of Sciences Vol. 115, No. 22 ( 2018-05-29)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 115, No. 22 ( 2018-05-29)
    Abstract: Hemispheric asymmetry is a cardinal feature of human brain organization. Altered brain asymmetry has also been linked to some cognitive and neuropsychiatric disorders. Here, the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium presents the largest-ever analysis of cerebral cortical asymmetry and its variability across individuals. Cortical thickness and surface area were assessed in MRI scans of 17,141 healthy individuals from 99 datasets worldwide. Results revealed widespread asymmetries at both hemispheric and regional levels, with a generally thicker cortex but smaller surface area in the left hemisphere relative to the right. Regionally, asymmetries of cortical thickness and/or surface area were found in the inferior frontal gyrus, transverse temporal gyrus, parahippocampal gyrus, and entorhinal cortex. These regions are involved in lateralized functions, including language and visuospatial processing. In addition to population-level asymmetries, variability in brain asymmetry was related to sex, age, and intracranial volume. Interestingly, we did not find significant associations between asymmetries and handedness. Finally, with two independent pedigree datasets ( n = 1,443 and 1,113, respectively), we found several asymmetries showing significant, replicable heritability. The structural asymmetries identified and their variabilities and heritability provide a reference resource for future studies on the genetic basis of brain asymmetry and altered laterality in cognitive, neurological, and psychiatric disorders.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1718418115
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2018
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  • 2
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    Online Resource
    Premotor functional connectivity predicts impulsivity in juvenile offenders
    Proceedings of the National Academy of Sciences ; 2011
    In:  Proceedings of the National Academy of Sciences Vol. 108, No. 27 ( 2011-07-05), p. 11241-11245
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 108, No. 27 ( 2011-07-05), p. 11241-11245
    Abstract: Teenagers are often impulsive. In some cases this is a phase of normal development; in other cases impulsivity contributes to criminal behavior. Using functional magnetic resonance imaging, we examined resting-state functional connectivity among brain systems and behavioral measures of impulsivity in 107 juveniles incarcerated in a high-security facility. In less-impulsive juveniles and normal controls, motor planning regions were correlated with brain networks associated with spatial attention and executive control. In more-impulsive juveniles, these same regions correlated with the default-mode network, a constellation of brain areas associated with spontaneous, unconstrained, self-referential cognition. The strength of these brain–behavior relationships was sufficient to predict impulsivity scores at the individual level. Our data suggest that increased functional connectivity of motor-planning regions with networks subserving unconstrained, self-referential cognition, rather than those subserving executive control, heightens the predisposition to impulsive behavior in juvenile offenders. To further explore the relationship between impulsivity and neural development, we studied functional connectivity in the same motor-planning regions in 95 typically developing individuals across a wide age span. The change in functional connectivity with age mirrored that of impulsivity: younger subjects tended to exhibit functional connectivity similar to the more-impulsive incarcerated juveniles, whereas older subjects exhibited a less-impulsive pattern. This observation suggests that impulsivity in the offender population is a consequence of a delay in typical development, rather than a distinct abnormality.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1108241108
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2011
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  • 3
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    Online Resource
    Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD
    Proceedings of the National Academy of Sciences ; 2012
    In:  Proceedings of the National Academy of Sciences Vol. 109, No. 17 ( 2012-04-24), p. 6769-6774
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 109, No. 17 ( 2012-04-24), p. 6769-6774
    Abstract: Research and clinical investigations in psychiatry largely rely on the de facto assumption that the diagnostic categories identified in the Diagnostic and Statistical Manual (DSM) represent homogeneous syndromes. However, the mechanistic heterogeneity that potentially underlies the existing classification scheme might limit discovery of etiology for most developmental psychiatric disorders. Another, perhaps less palpable, reality may also be interfering with progress—heterogeneity in typically developing populations. In this report we attempt to clarify neuropsychological heterogeneity in a large dataset of typically developing youth and youth with attention deficit/hyperactivity disorder (ADHD), using graph theory and community detection. We sought to determine whether data-driven neuropsychological subtypes could be discerned in children with and without the disorder. Because individual classification is the sine qua non for eventual clinical translation, we also apply support vector machine-based multivariate pattern analysis to identify how well ADHD status in individual children can be identified as defined by the community detection delineated subtypes. The analysis yielded several unique, but similar subtypes across both populations. Just as importantly, comparing typically developing children with ADHD children within each of these distinct subgroups increased diagnostic accuracy. Two important principles were identified that have the potential to advance our understanding of typical development and developmental neuropsychiatric disorders. The first tenet suggests that typically developing children can be classified into distinct neuropsychological subgroups with high precision. The second tenet proposes that some of the heterogeneity in individuals with ADHD might be “nested” in this normal variation.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1115365109
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2012
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  • 4
    Online Resource
    Online Resource
    Distinct brain networks for adaptive and stable task control in humans
    Proceedings of the National Academy of Sciences ; 2007
    In:  Proceedings of the National Academy of Sciences Vol. 104, No. 26 ( 2007-06-26), p. 11073-11078
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 104, No. 26 ( 2007-06-26), p. 11073-11078
    Abstract: Control regions in the brain are thought to provide signals that configure the brain's moment-to-moment information processing. Previously, we identified regions that carried signals related to task-control initiation, maintenance, and adjustment. Here we characterize the interactions of these regions by applying graph theory to resting state functional connectivity MRI data. In contrast to previous, more unitary models of control, this approach suggests the presence of two distinct task-control networks. A frontoparietal network included the dorsolateral prefrontal cortex and intraparietal sulcus. This network emphasized start-cue and error-related activity and may initiate and adapt control on a trial-by-trial basis. The second network included dorsal anterior cingulate/medial superior frontal cortex, anterior insula/frontal operculum, and anterior prefrontal cortex. Among other signals, these regions showed activity sustained across the entire task epoch, suggesting that this network may control goal-directed behavior through the stable maintenance of task sets. These two independent networks appear to operate on different time scales and affect downstream processing via dissociable mechanisms.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.0704320104
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2007
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  • 5
    Online Resource
    Online Resource
    Development of distinct control networks through segregation and integration
    Proceedings of the National Academy of Sciences ; 2007
    In:  Proceedings of the National Academy of Sciences Vol. 104, No. 33 ( 2007-08-14), p. 13507-13512
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 104, No. 33 ( 2007-08-14), p. 13507-13512
    Abstract: Human attentional control is unrivaled. We recently proposed that adults depend on distinct frontoparietal and cinguloopercular networks for adaptive online task control versus more stable set control, respectively. During development, both experience-dependent evoked activity and spontaneous waves of synchronized cortical activity are thought to support the formation and maintenance of neural networks. Such mechanisms may encourage tighter “integration” of some regions into networks over time while “segregating” other sets of regions into separate networks. Here we use resting state functional connectivity MRI, which measures correlations in spontaneous blood oxygenation level-dependent signal fluctuations between brain regions to compare previously identified control networks between children and adults. We find that development of the proposed adult control networks involves both segregation (i.e., decreased short-range connections) and integration (i.e., increased long-range connections) of the brain regions that comprise them. Delay/disruption in the developmental processes of segregation and integration may play a role in disorders of control, such as autism, attention deficit hyperactivity disorder, and Tourette's syndrome.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.0705843104
    RVK:
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2007
    detail.hit.zdb_id: 209104-5
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  • 6
    Online Resource
    Online Resource
    The maturing architecture of the brain's default network
    Proceedings of the National Academy of Sciences ; 2008
    In:  Proceedings of the National Academy of Sciences Vol. 105, No. 10 ( 2008-03-11), p. 4028-4032
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 105, No. 10 ( 2008-03-11), p. 4028-4032
    Abstract: In recent years, the brain's “default network,” a set of regions characterized by decreased neural activity during goal-oriented tasks, has generated a significant amount of interest, as well as controversy. Much of the discussion has focused on the relationship of these regions to a “default mode” of brain function. In early studies, investigators suggested that, the brain's default mode supports “self-referential” or “introspective” mental activity. Subsequently, regions of the default network have been more specifically related to the “internal narrative,” the “autobiographical self,” “stimulus independent thought,” “mentalizing,” and most recently “self-projection.” However, the extant literature on the function of the default network is limited to adults, i.e., after the system has reached maturity. We hypothesized that further insight into the network's functioning could be achieved by characterizing its development. In the current study, we used resting-state functional connectivity MRI (rs-fcMRI) to characterize the development of the brain's default network. We found that the default regions are only sparsely functionally connected at early school age (7–9 years old); over development, these regions integrate into a cohesive, interconnected network.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.0800376105
    RVK:
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2008
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  • 7
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    Online Resource
    Sex differences in the functional topography of association networks in youth
    Proceedings of the National Academy of Sciences ; 2022
    In:  Proceedings of the National Academy of Sciences Vol. 119, No. 33 ( 2022-08-16)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 119, No. 33 ( 2022-08-16)
    Abstract: Prior work has shown that there is substantial interindividual variation in the spatial distribution of functional networks across the cerebral cortex, or functional topography. However, it remains unknown whether there are sex differences in the topography of individualized networks in youth. Here, we leveraged an advanced machine learning method (sparsity-regularized non-negative matrix factorization) to define individualized functional networks in 693 youth (ages 8 to 23 y) who underwent functional MRI as part of the Philadelphia Neurodevelopmental Cohort. Multivariate pattern analysis using support vector machines classified participant sex based on functional topography with 82.9% accuracy ( P 〈 0.0001). Brain regions most effective in classifying participant sex belonged to association networks, including the ventral attention, default mode, and frontoparietal networks. Mass univariate analyses using generalized additive models with penalized splines provided convergent results. Furthermore, transcriptomic data from the Allen Human Brain Atlas revealed that sex differences in multivariate patterns of functional topography were spatially correlated with the expression of genes on the X chromosome. These results highlight the role of sex as a biological variable in shaping functional topography.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2110416119
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2022
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  • 8
    Online Resource
    Online Resource
    Large-scale topology and the default mode network in the mouse connectome
    Proceedings of the National Academy of Sciences ; 2014
    In:  Proceedings of the National Academy of Sciences Vol. 111, No. 52 ( 2014-12-30), p. 18745-18750
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 111, No. 52 ( 2014-12-30), p. 18745-18750
    Abstract: Noninvasive functional imaging holds great promise for serving as a translational bridge between human and animal models of various neurological and psychiatric disorders. However, despite a depth of knowledge of the cellular and molecular underpinnings of atypical processes in mouse models, little is known about the large-scale functional architecture measured by functional brain imaging, limiting translation to human conditions. Here, we provide a robust processing pipeline to generate high-resolution, whole-brain resting-state functional connectivity MRI (rs-fcMRI) images in the mouse. Using a mesoscale structural connectome (i.e., an anterograde tracer mapping of axonal projections across the mouse CNS), we show that rs-fcMRI in the mouse has strong structural underpinnings, validating our procedures. We next directly show that large-scale network properties previously identified in primates are present in rodents, although they differ in several ways. Last, we examine the existence of the so-called default mode network (DMN)—a distributed functional brain system identified in primates as being highly important for social cognition and overall brain function and atypically functionally connected across a multitude of disorders. We show the presence of a potential DMN in the mouse brain both structurally and functionally. Together, these studies confirm the presence of basic network properties and functional networks of high translational importance in structural and functional systems in the mouse brain. This work clears the way for an important bridge measurement between human and rodent models, enabling us to make stronger conclusions about how regionally specific cellular and molecular manipulations in mice relate back to humans.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1404346111
    RVK:
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2014
    detail.hit.zdb_id: 209104-5
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  • 9
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    Toward discovery science of human brain function
    Proceedings of the National Academy of Sciences ; 2010
    In:  Proceedings of the National Academy of Sciences Vol. 107, No. 10 ( 2010-03-09), p. 4734-4739
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 107, No. 10 ( 2010-03-09), p. 4734-4739
    Abstract: Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency ( 〈 0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's “functional connectome.” Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain–behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/ .
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.0911855107
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2010
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