Publications by authors named "Randy L Buckner"

173 Publications

Sociodemographic characteristics of missing data in digital phenotyping.

Sci Rep 2021 Jul 29;11(1):15408. Epub 2021 Jul 29.

Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

The ubiquity of smartphones, with their increasingly sophisticated array of sensors, presents an unprecedented opportunity for researchers to collect longitudinal, diverse, temporally-dense data about human behavior while minimizing participant burden. Researchers increasingly make use of smartphones for "digital phenotyping," the collection and analysis of raw phone sensor and log data to study the lived experiences of subjects in their natural environments using their own devices. While digital phenotyping has shown promise in fields such as psychiatry and neuroscience, there are fundamental gaps in our knowledge about data collection and non-collection (i.e., missing data) in smartphone-based digital phenotyping. In this meta-study using individual-level data from six different studies, we examined accelerometer and GPS sensor data of 211 participants, amounting to 29,500 person-days of observation, using Bayesian hierarchical negative binomial regression with study- and user-level random intercepts. Sensitivity analyses including alternative model specification and stratified models were conducted. We found that iOS users had lower GPS non-collection than Android users. For GPS data, rates of non-collection did not differ by race/ethnicity, education, age, or gender. For accelerometer data, Black participants had higher rates of non-collection, but rates did not differ by sex, education, or age. For both sensors, non-collection increased by 0.5% to 0.9% per week. These results demonstrate the feasibility of using smartphone-based digital phenotyping across diverse populations, for extended periods of time, and within diverse cohorts. As smartphones become increasingly embedded in everyday life, the insights of this study will help guide the design, planning, and analysis of digital phenotyping studies.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41598-021-94516-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322366PMC
July 2021

Precision Estimates of Parallel Distributed Association Networks: Evidence for Domain Specialization and Implications for Evolution and Development.

Curr Opin Behav Sci 2021 Aug 3;40:120-129. Epub 2021 May 3.

Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138 USA.

Humans can reason about other minds, comprehend language and imagine. These abilities depend on association regions that exhibit evolutionary expansion and prolonged postnatal development. Precision maps within individuals reveal these expanded zones are populated by multiple specialized networks that each possess a spatially distributed motif but remain anatomically separated throughout the cortex for language, social and mnemonic / spatial functions. Rather than converge on multi-domain regions or hubs, these networks include distinct regions within rostral prefrontal and temporal association zones. To account for these observations, we propose the expansion-fractionation-specialization (EFS) hypothesis: evolutionary expansion of human association cortex may have allowed for an archetype distributed network to fractionate into multiple specialized networks. Human development may recapitulate fractionation and specialization when these abilities emerge.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cobeha.2021.03.029DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8274557PMC
August 2021

Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years.

Hum Brain Mapp 2021 Feb 17. Epub 2021 Feb 17.

Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil.

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/hbm.25364DOI Listing
February 2021

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years.

Hum Brain Mapp 2021 Feb 11. Epub 2021 Feb 11.

Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, USA.

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/hbm.25320DOI Listing
February 2021

Characterizing cerebral hemodynamics across the adult lifespan with arterial spin labeling MRI data from the Human Connectome Project-Aging.

Neuroimage 2021 04 29;230:117807. Epub 2021 Jan 29.

Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, 149 Thirteenth Street, Suite, 2301, Charlestown 02129, MA, United States; Department of Radiology, Harvard Medical School, Boston, MA, United States; Neuroimaging Research for Veterans Center, VA Boston Healthcare System, Boston, MA, United States.

Arterial spin labeling (ASL) magnetic resonance imaging (MRI) has become a popular approach for studying cerebral hemodynamics in a range of disorders and has recently been included as part of the Human Connectome Project-Aging (HCP-A). Due to the high spatial resolution and multiple post-labeling delays, ASL data from HCP-A holds promise for localization of hemodynamic signals not only in gray matter but also in white matter. However, gleaning information about white matter hemodynamics with ASL is challenging due in part to longer blood arrival times in white matter compared to gray matter. In this work, we present an analytical approach for deriving measures of cerebral blood flow (CBF) and arterial transit times (ATT) from the ASL data from HCP-A and report on gray and white matter hemodynamics in a large cohort (n = 234) of typically aging adults (age 36-90 years). Pseudo-continuous ASL data were acquired with labeling duration = 1500 ms and five post-labeling delays = 200 ms, 700 ms, 1200, 1700 ms, and 2200 ms. ATT values were first calculated on a voxel-wise basis through normalized cross-correlation analysis of the acquired signal time course in that voxel and an expected time course based on an acquisition-specific Bloch simulation. CBF values were calculated using a two-compartment model and with age-appropriate blood water longitudinal relaxation times. Using this approach, we found that white matter CBF reduces (ρ = 0.39) and white matter ATT elongates (ρ = 0.42) with increasing age (p < 0.001). In addition, CBF is lower and ATTs are longer in white matter compared to gray matter across the adult lifespan (Wilcoxon signed-rank tests; p < 0.001). We also found sex differences with females exhibiting shorter white matter ATTs than males, independently of age (Wilcoxon rank-sum test; p < 0.001). Finally, we have shown that CBF and ATT values are spatially heterogeneous, with significant differences in cortical versus subcortical gray matter and juxtacortical versus periventricular white matter. These results serve as a characterization of normative physiology across the human lifespan against which hemodynamic impairment due to cerebrovascular or neurodegenerative diseases could be compared in future studies.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neuroimage.2021.117807DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8185881PMC
April 2021

The detailed organization of the human cerebellum estimated by intrinsic functional connectivity within the individual.

J Neurophysiol 2021 02 2;125(2):358-384. Epub 2020 Dec 2.

Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.

Distinct regions of the cerebellum connect to separate regions of the cerebral cortex forming a complex topography. Although cerebellar organization has been examined in group-averaged data, study of individuals provides an opportunity to discover features that emerge at a higher spatial resolution. Here, functional connectivity MRI was used to examine the cerebellum of two intensively sampled individuals (each scanned 31 times). Connectivity to somatomotor cortex showed the expected crossed laterality and topography of the body maps. A surprising discovery was connectivity to the primary visual cortex along the vermis with evidence for representation of the central field. Within the hemispheres, each individual displayed a hierarchical progression from the inverted anterior lobe somatomotor map through to higher-order association zones. The hierarchy ended at Crus I/II and then progressed in reverse order through to the upright somatomotor map in the posterior lobe. Evidence for a third set of networks was found in the most posterior extent of the cerebellum. Detailed analysis of the higher-order association networks revealed robust representations of two distinct networks linked to the default network, multiple networks linked to cognitive control, as well as a separate representation of a language network. Although idiosyncratic spatial details emerged between subjects, each network could be detected in both individuals, and seed regions placed within the cerebellum recapitulated the full extent of the spatially specific cerebral networks. The observation of multiple networks in juxtaposed regions at the Crus I/II apex confirms the importance of this zone to higher-order cognitive function and reveals new organizational details. Stable, within-individual maps of cerebellar organization reveal orderly macroscale representations of the cerebral cortex with local juxtaposed zones representing distinct networks. In addition, individuals reveal idiosyncratic organizational features.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1152/jn.00561.2020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7948146PMC
February 2021

Heterogeneity of Cerebral White Matter Lesions and Clinical Correlates in Older Adults.

Stroke 2021 Jan 7;52(2):620-630. Epub 2021 Jan 7.

Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston (K.-H.J., K.A.S., K.M.Y., J.M.R., C.M.K., D.H.S.).

Background And Purpose: Cerebral white matter signal abnormalities (WMSAs) are a significant radiological marker associated with brain and vascular aging. However, understanding their clinical impact is limited because of their pathobiological heterogeneity. We determined whether use of robust reliable automated procedures can distinguish WMSA classes with different clinical consequences.

Methods: Data from generally healthy participants aged >50 years with moderate or greater WMSA were selected from the Human Connectome Project-Aging (n=130). WMSAs were segmented on T1 imaging. Features extracted from WMSA included total and regional volume, number of discontinuous clusters, size of noncontiguous lesion, contrast of lesion intensity relative to surrounding normal appearing tissue using a fully automated procedure. Hierarchical clustering was used to classify individuals into distinct classes of WMSA. Radiological and clinical variability was evaluated across the individual WMSA classes.

Results: Class I was characterized by multiple, small, lower-contrast lesions predominantly in the deep WM; class II by large, confluent lesions in the periventricular WM; and class III by higher-contrast lesions restricted to the juxtaventricular WM. Class II was associated with lower myelin content than the other 2 classes. Class II was more prevalent in older subjects and was associated with a higher prevalence of hypertension and lower physical activity levels. Poor sleep quality was associated with a greater risk of class I.

Conclusions: We classified heterogeneous subsets of cerebral white matter lesions into distinct classes that have different clinical risk factors. This new method for identifying classes of WMSA will be important in understanding the underlying pathophysiology and in determining the impact on clinical outcomes.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1161/STROKEAHA.120.031641DOI Listing
January 2021

Situating the left-lateralized language network in the broader organization of multiple specialized large-scale distributed networks.

J Neurophysiol 2020 11 23;124(5):1415-1448. Epub 2020 Sep 23.

Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts.

Using procedures optimized to explore network organization within the individual, the topography of a candidate language network was characterized and situated within the broader context of adjacent networks. The candidate network was first identified using functional connectivity and replicated across individuals, acquisition tasks, and analytical methods. In addition to classical language regions near the perisylvian cortex and temporal pole, regions were also observed in dorsal posterior cingulate, midcingulate, and anterior superior frontal and inferior temporal cortex. The candidate network was selectively activated when processing meaningful (as contrasted with nonword) sentences, whereas spatially adjacent networks showed minimal or even decreased activity. Results were replicated and triplicated across two prospectively acquired cohorts. Examined in relation to adjacent networks, the topography of the language network was found to parallel the motif of other association networks, including the transmodal association networks linked to theory of mind and episodic remembering (often collectively called the default network). The several networks contained juxtaposed regions in multiple association zones. Outside of these juxtaposed higher-order networks, we further noted a distinct frontotemporal network situated between language regions and a frontal orofacial motor region and a temporal auditory region. A possibility is that these functionally related sensorimotor regions might anchor specialization of neighboring association regions that develop into a language network. What is most striking is that the canonical language network appears to be just one of multiple similarly organized, differentially specialized distributed networks that populate the evolutionarily expanded zones of human association cortex. This research shows that a language network can be identified within individuals using functional connectivity. Organizational details reveal that the language network shares a common spatial motif with other association networks, including default and frontoparietal control networks. The language network is activated by language task demands, whereas closely juxtaposed networks are not, suggesting that similarly organized but differentially specialized distributed networks populate association cortex.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1152/jn.00753.2019DOI Listing
November 2020

The genetic architecture of the human cerebral cortex.

Science 2020 03;367(6484)

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1126/science.aay6690DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295264PMC
March 2020

Parallel distributed networks dissociate episodic and social functions within the individual.

J Neurophysiol 2020 03 12;123(3):1144-1179. Epub 2020 Feb 12.

Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts.

Association cortex is organized into large-scale distributed networks. One such network, the default network (DN), is linked to diverse forms of internal mentation, opening debate about whether shared or distinct anatomy supports multiple forms of cognition. Using within-individual analysis procedures that preserve idiosyncratic anatomical details, we probed whether multiple tasks from two domains, episodic projection and theory of mind (ToM), rely on the same or distinct networks. In an initial experiment (6 subjects, each scanned 4 times), we found evidence that episodic projection and ToM tasks activate separate regions distributed throughout the cortex, with adjacent regions in parietal, temporal, prefrontal, and midline zones. These distinctions were predicted by the hypothesis that the DN comprises two parallel, interdigitated networks. One network, linked to parahippocampal cortex (PHC), is preferentially recruited during episodic projection, including both remembering and imagining the future. A second juxtaposed network, which includes the temporoparietal junction (TPJ), is differentially engaged during multiple forms of ToM. In two prospectively acquired independent experiments, we replicated and triplicated the dissociation (each with 6 subjects scanned 4 times). Furthermore, the dissociation was found in all zones when analyzed independently, including robustly in midline regions previously described as hubs. The TPJ-linked network is interwoven with the PHC-linked network across the cortex, making clear why it is difficult to fully resolve the two networks in group-averaged or lower-resolution data. These results refine our understanding of the functional-anatomical organization of association cortex and raise fundamental questions about how specialization might arise in parallel, juxtaposed association networks. Two distributed, interdigitated networks exist within the bounds of the canonical default network. Here we used repeated scanning of individuals, across three independent samples, to provide evidence that tasks requiring episodic projection or theory of mind differentially recruit the two networks across multiple cortical zones. The two distributed networks thus appear to preferentially subserve distinct functions.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1152/jn.00529.2019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7099479PMC
March 2020

Abnormal Auditory Mismatch Fields in Children and Adolescents With 16p11.2 Deletion and 16p11.2 Duplication.

Biol Psychiatry Cogn Neurosci Neuroimaging 2020 10 26;5(10):942-950. Epub 2019 Nov 26.

Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Department of Linguistics, University of Pennsylvania, Philadelphia, Pennsylvania. Electronic address:

Background: Individuals with either deletion or duplication of the BP4-BP5 segment of chromosome 16p11.2 have varied behavioral phenotypes that may include autistic features, mild to moderate intellectual disability, and/or language impairment. However, the neurophysiological correlates of auditory language discrimination processing in individuals with 16p11.2 deletion and 16p11.2 duplication have not been investigated.

Methods: Magnetoencephalography was used to measure magnetic mismatch fields (MMFs) arising from the left and right superior temporal gyrus during an auditory oddball paradigm with vowel stimuli (/a/ and /u/) in children and adolescents with 16p11.2 deletion or 16p11.2 duplication and in typically developing peers. One hundred twenty-eight participants ranging from 7 to 17 years of age were included in the final analysis (typically developing: n = 61, 12.08 ± 2.50 years of age; 16p11.2 deletion: n = 45, 11.28 ± 2.51 years of age; and 16p11.2 duplication: n = 22, 10.73 ± 2.49 years of age).

Results: Delayed MMF latencies were found in both 16p11.2 deletion and 16p11.2 duplication groups compared with typically developing subjects. In addition, these delayed MMF latencies were associated with language and cognitive ability, with prolonged latency predicting greater impairment.

Conclusions: Our findings suggest that auditory MMF response delays are associated with clinical severity of language and cognitive impairment in individuals with either 16p11.2 deletion or 16p11.2 duplication, indicating a correlate of their shared/overlapping behavioral phenotype (and not a correlate of gene dosage).
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.bpsc.2019.11.005DOI Listing
October 2020

Genetic architecture of subcortical brain structures in 38,851 individuals.

Nat Genet 2019 11 21;51(11):1624-1636. Epub 2019 Oct 21.

Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-019-0511-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7055269PMC
November 2019

The brain's default network: updated anatomy, physiology and evolving insights.

Nat Rev Neurosci 2019 10 6;20(10):593-608. Epub 2019 Sep 6.

Department of Psychology, Harvard University, Cambridge, MA, USA.

Discoveries over the past two decades demonstrate that regions distributed throughout the association cortex, often called the default network, are suppressed during tasks that demand external attention and are active during remembering, envisioning the future and making social inferences. This Review describes progress in understanding the organization and function of networks embedded within these association regions. Detailed high-resolution analyses of single individuals suggest that the default network is not a single network, as historically described, but instead comprises multiple interwoven networks. The multiple networks share a common organizational motif (also evident in marmoset and macaque anatomical circuits) that might support a general class of processing function dependent on internally constructed rather than externally constrained representations, with each separate interwoven network specialized for a distinct processing domain. Direct neuronal recordings in humans and monkeys reveal evidence for competitive relationships between the internally and externally oriented networks. Findings from rodent studies suggest that the thalamus might be essential to controlling which networks are engaged through specialized thalamic reticular neurons, including antagonistic subpopulations. These association networks (and presumably thalamocortical circuits) are expanded in humans and might be particularly vulnerable to dysregulation implicated in mental illness.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41583-019-0212-7DOI Listing
October 2019

Macroscale cortical organization and a default-like apex transmodal network in the marmoset monkey.

Nat Commun 2019 04 29;10(1):1976. Epub 2019 Apr 29.

Centre National de la Recherche Scientifique, CNRS UMR 7225, Institut du Cerveau et de la Moelle épinière, Paris, 75013, France.

Networks of widely distributed regions populate human association cortex. One network, often called the default network, is positioned at the apex of a gradient of sequential networks that radiate outward from primary cortex. Here, extensive anatomical data made available through the Marmoset Brain Architecture Project are explored to show a homologue exists in marmoset. Results reveal that a gradient of networks extend outward from primary cortex to progressively higher-order transmodal association cortex in both frontal and temporal cortex. The apex transmodal network comprises frontopolar and rostral temporal association cortex, parahippocampal areas TH / TF, the ventral posterior midline, and lateral parietal association cortex. The positioning of this network in the gradient and its composition of areas make it a candidate homologue to the human default network. That the marmoset, a physiologically- and genetically-accessible primate, might possess a default-network-like candidate creates opportunities for study of higher cognitive and social functions.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-019-09812-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6488644PMC
April 2019

Interrogating the Genetic Determinants of Tourette's Syndrome and Other Tic Disorders Through Genome-Wide Association Studies.

Am J Psychiatry 2019 03;176(3):217-227

The Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Department of Psychiatry, Massachusetts General Hospital, Boston (Yu, Illmann, Osiecki, Smoller, Pauls, Neale, Scharf); the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass. (Yu, Neale, Scharf); the Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles (Sul, Huang, Zelaya, Ophoff, Freimer, Coppola); the Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles (Sul, Huang, Zelaya, Freimer, Coppola); the Department of Molecular Biology and Genetics, Democritus University of Thrace, Xanthi, Greece (Tsetsos); the Department of Biological Sciences, Purdue University, West Lafayette, Ind. (Tsetsos, Paschou); deCODE Genetics/Amgen, Reykjavik, Iceland (Nawaz, H. Stefansson, K. Stefansson); the Bioinformatics Interdepartmental Program, University of California, Los Angeles (Huang, Zelaya); the Department of Psychiatry, University of California, San Francisco (Darrow); the Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco (Hirschtritt, Willsey); the Department of Psychiatry, Massachusetts General Hospital, Boston (Greenberg, Roffman, Buckner); the Clinic of Psychiatry, Social Psychiatry, and Psychotherapy, Hannover Medical School, Hannover, Germany (Muller-Vahl); the Institute of Human Genetics, Hannover Medical School, Hannover, Germany (Stuhrmann); McGill University Health Center, University of Montreal, McGill University Health Centre, Montreal (Dion); the Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal (Rouleau); the Department of Psychiatry and Psychotherapy, Medical University Vienna, Vienna (Aschauer, Stamenkovic); Biopsychosocial Corporation, Vienna (Aschauer, Schlögelhofer); University Health Network, Youthdale Treatment Centres, and University of Toronto, Toronto (Sandor); the Krembil Research Institute, University Health Network, Hospital for Sick Children, and University of Toronto, Toronto (Barr); Johns Hopkins University School of Medicine, Baltimore (Grados, Singer); the Institute of Human Genetics, University Hospital Bonn, University of Bonn Medical School, Bonn, Germany (Nöthen); the Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany (Hebebrand, Hinney); the Yale Child Study Center and the Department of Psychiatry, Yale University School of Medicine, New Haven, Conn. (King, Fernandez); the Institute of Medical Chemistry, Molecular Biology, and Pathobiochemistry, Semmelweis University, Budapest, Hungary (Barta); Vadaskert Child and Adolescent Psychiatric Hospital, Budapest, Hungary (Tarnok, Nagy); the Institute of Human Genetics, University Hospital Essen, University Duisburg-Essen, Essen, Germany (Depienne); Sorbonne Universités, UPMC Université Paris 06, UMR S 1127, CNRS UMR 7225, ICM, Paris (Depienne, Worbe, Hartmann); French Reference Centre for Gilles de la Tourette Syndrome, Groupe Hospitalier Pitié-Salpêtrière, Paris (Worbe, Hartmann); Assistance Publique-Hôpitaux de Paris, Department of Neurology, Groupe Hospitalier Pitié-Salpêtrière, Paris (Worbe, Hartmann); Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York (Budman); Child Neuropsychiatry, Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy (Rizzo); the Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York (Lyon); the Department of Psychiatry, University of Utah, Salt Lake City (McMahon); Children's Mercy Hospital, Kansas City, Mo. (Batterson); the Department of Psychiatry, University Medical Center Groningen and Rijksuniversity Groningen, and Drenthe Mental Health Center, Groningen, the Netherlands (Cath); the Department of Neurology, Fixel Center for Neurological Diseases, McKnight Brain Institute, University of Florida, Gainesville (Malaty, Okun); Pennsylvania State University College of Medicine, Hershey (Berlin); Marquette University and University of Wisconsin-Milwaukee, Milwaukee (Woods); Tripler Army Medical Center and University of Hawaii John A. Burns School of Medicine, Honolulu (Lee); Parkinson's Disease Center and Movement Disorders Clinic, Department of Neurology, Baylor College of Medicine, Houston (Jankovic); the Division of Psychiatry, Department of Neuropsychiatry, University College London (Robertson); the Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati (Gilbert); Children's Hospital of Philadelphia, Philadelphia (Brown); the Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami (Coffey); the Department of Child and Adolescent Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands (Dietrich, Hoekstra); University of Iowa Carver College of Medicine, Iowa City (Kuperman); the Department of Pediatrics, University of Washington, Seattle (Zinner); the Department of Pediatrics, Landspitalinn University Hospital, Reykjavik, Iceland (Luðvigsson, Thorarensen); the Faculty of Medicine, University of Iceland, Reykjavík, Iceland (Sæmundsen, Stefansson); the State Diagnostic and Counselling Centre, Kópavogur, Iceland (Sæmundsen); the Department of Genetics and the Department of Medicine, Albert Einstein College of Medicine, Bronx, New York (Atzmon, Barzilai); the Department of Human Biology, Haifa University, Haifa, Israel (Atzmon); the Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany (Wagner); the Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany (Moessner); SUNY Downstate Medical Center Brooklyn, New York (C.M. Pato, M.T. Pato, Knowles); the Athinoula A. Martinos Center for Biomedical Research, Department of Radiology, Massachusetts General Hospital, Charlestown (Roffman, Buckner); the Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston (Smoller); the Center for Brain Science and Department of Psychology, Harvard University, Cambridge, Mass. (Buckner); the Institute for Neurodegenerative Diseases, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco (Willsey); the Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers, the State University of New Jersey, Piscataway (Tischfield, Heiman); the Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, VU University Amsterdam, Amsterdam (Posthuma); the Division of Genetic Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tenn. (Cox, Davis); the Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston (Neale); the Department of Psychiatry, Genetics Institute, University of Florida, Gainesville (Mathews); and the Department of Neurology, Brigham and Women's Hospital, and the Department of Neurology, Massachusetts General Hospital, Boston (Scharf).

Objective: Tourette's syndrome is polygenic and highly heritable. Genome-wide association study (GWAS) approaches are useful for interrogating the genetic architecture and determinants of Tourette's syndrome and other tic disorders. The authors conducted a GWAS meta-analysis and probed aggregated Tourette's syndrome polygenic risk to test whether Tourette's and related tic disorders have an underlying shared genetic etiology and whether Tourette's polygenic risk scores correlate with worst-ever tic severity and may represent a potential predictor of disease severity.

Methods: GWAS meta-analysis, gene-based association, and genetic enrichment analyses were conducted in 4,819 Tourette's syndrome case subjects and 9,488 control subjects. Replication of top loci was conducted in an independent population-based sample (706 case subjects, 6,068 control subjects). Relationships between Tourette's polygenic risk scores (PRSs), other tic disorders, ascertainment, and tic severity were examined.

Results: GWAS and gene-based analyses identified one genome-wide significant locus within FLT3 on chromosome 13, rs2504235, although this association was not replicated in the population-based sample. Genetic variants spanning evolutionarily conserved regions significantly explained 92.4% of Tourette's syndrome heritability. Tourette's-associated genes were significantly preferentially expressed in dorsolateral prefrontal cortex. Tourette's PRS significantly predicted both Tourette's syndrome and tic spectrum disorders status in the population-based sample. Tourette's PRS also significantly correlated with worst-ever tic severity and was higher in case subjects with a family history of tics than in simplex case subjects.

Conclusions: Modulation of gene expression through noncoding variants, particularly within cortico-striatal circuits, is implicated as a fundamental mechanism in Tourette's syndrome pathogenesis. At a genetic level, tic disorders represent a continuous spectrum of disease, supporting the unification of Tourette's syndrome and other tic disorders in future diagnostic schemata. Tourette's PRSs derived from sufficiently large samples may be useful in the future for predicting conversion of transient tics to chronic tic disorders, as well as tic persistence and lifetime tic severity.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1176/appi.ajp.2018.18070857DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6677250PMC
March 2019

Parallel distributed networks resolved at high resolution reveal close juxtaposition of distinct regions.

J Neurophysiol 2019 04 20;121(4):1513-1534. Epub 2019 Feb 20.

Department of Psychology, Center for Brain Science, Harvard University , Cambridge, Massachusetts.

Examination of large-scale distributed networks within the individual reveals details of cortical network organization that are absent in group-averaged studies. One recent discovery is that a distributed transmodal network, often referred to as the "default network," comprises two closely interdigitated networks, only one of which is coupled to posterior parahippocampal cortex. Not all studies of individuals have identified the same networks, and questions remain about the degree to which the two networks are separate, particularly within regions hypothesized to be interconnected hubs. In this study we replicate the observation of network separation across analytical (seed-based connectivity and parcellation) and data projection (volume and surface) methods in two individuals each scanned 31 times. Additionally, three individuals were examined with high-resolution (7T; 1.35 mm) functional magnetic resonance imaging to gain further insight into the anatomical details. The two networks were identified with separate regions localized to adjacent portions of the cortical ribbon, sometimes inside the same sulcus. Midline regions previously implicated as hubs revealed near complete spatial separation of the two networks, displaying a complex spatial topography in the posterior cingulate and precuneus. The network coupled to parahippocampal cortex also revealed a separate region directly within the hippocampus, at or near the subiculum. These collective results support that the default network is composed of at least two spatially juxtaposed networks. Fine spatial details and juxtapositions of the two networks can be identified within individuals at high resolution, providing insight into the network organization of association cortex and placing further constraints on interpretation of group-averaged neuroimaging data. NEW & NOTEWORTHY Recent evidence has emerged that canonical large-scale networks such as the "default network" fractionate into parallel distributed networks when defined within individuals. This research uses high-resolution imaging to show that the networks possess juxtapositions sometimes evident inside the same sulcus and within regions that have been previously hypothesized to be network hubs. Distinct circumscribed regions of one network were also resolved in the hippocampal formation, at or near the parahippocampal cortex and subiculum.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1152/jn.00808.2018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6485740PMC
April 2019

Increased amygdala-visual cortex connectivity in youth with persecutory ideation.

Psychol Med 2020 01 12;50(2):273-283. Epub 2019 Feb 12.

Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.

Background: Subclinical delusional ideas, including persecutory beliefs, in otherwise healthy individuals are heritable symptoms associated with increased risk for psychotic illness, possibly representing an expression of one end of a continuum of psychosis severity. The identification of variation in brain function associated with these symptoms may provide insights about the neurobiology of delusions in clinical psychosis.

Methods: A resting-state functional magnetic resonance imaging scan was collected from 131 young adults with a wide range of severity of subclinical delusional beliefs, including persecutory ideas. Because of evidence for a key role of the amygdala in fear and paranoia, resting-state functional connectivity of the amygdala was measured.

Results: Connectivity between the amygdala and early visual cortical areas, including striate cortex (V1), was found to be significantly greater in participants with high (n = 43) v. low (n = 44) numbers of delusional beliefs, particularly in those who showed persistence of those beliefs. Similarly, across the full sample, the number of and distress associated with delusional beliefs were positively correlated with the strength of amygdala-visual cortex connectivity. Moreover, further analyses revealed that these effects were driven by those who endorsed persecutory beliefs.

Conclusions: These findings are consistent with the hypothesis that aberrant assignments of threat to sensory stimuli may lead to the downstream development of delusional ideas. Taken together with prior findings of disrupted sensory-limbic coupling in psychosis, these results suggest that altered amygdala-visual cortex connectivity could represent a marker of psychosis-related pathophysiology across a continuum of symptom severity.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1017/S0033291718004221DOI Listing
January 2020

The Lifespan Human Connectome Project in Aging: An overview.

Neuroimage 2019 01 15;185:335-348. Epub 2018 Oct 15.

Center for Magnetic Resonance Research Imaging, Department of Radiology, University of Minnesota, Minneapolis, MN, USA.

The original Human Connectome Project yielded a rich data set on structural and functional connectivity in a large sample of healthy young adults using improved methods of data acquisition, analysis, and sharing. More recent efforts are extending this approach to include infants, children, older adults, and brain disorders. This paper introduces and describes the Human Connectome Project in Aging (HCP-A), which is currently recruiting 1200 + healthy adults aged 36 to 100+, with a subset of 600 + participants returning for longitudinal assessment. Four acquisition sites using matched Siemens Prisma 3T MRI scanners with centralized quality control and data analysis are enrolling participants. Data are acquired across multimodal imaging and behavioral domains with a focus on factors known to be altered in advanced aging. MRI acquisitions include structural (whole brain and high resolution hippocampal) plus multiband resting state functional (rfMRI), task fMRI (tfMRI), diffusion MRI (dMRI), and arterial spin labeling (ASL). Behavioral characterization includes cognitive (such as processing speed and episodic memory), psychiatric, metabolic, and socioeconomic measures as well as assessment of systemic health (with a focus on menopause via hormonal assays). This dataset will provide a unique resource for examining how brain organization and connectivity changes across typical aging, and how these differences relate to key characteristics of aging including alterations in hormonal status and declining memory and general cognition. A primary goal of the HCP-A is to make these data freely available to the scientific community, supported by the Connectome Coordination Facility (CCF) platform for data quality assurance, preprocessing and basic analysis, and shared via the NIMH Data Archive (NDA). Here we provide the rationale for our study design and sufficient details of the resource for scientists to plan future analyses of these data. A companion paper describes the related Human Connectome Project in Development (HCP-D, Somerville et al., 2018), and the image acquisition protocol common to both studies (Harms et al., 2018).
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neuroimage.2018.10.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6649668PMC
January 2019

Extending the Human Connectome Project across ages: Imaging protocols for the Lifespan Development and Aging projects.

Neuroimage 2018 12 24;183:972-984. Epub 2018 Sep 24.

Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

The Human Connectome Projects in Development (HCP-D) and Aging (HCP-A) are two large-scale brain imaging studies that will extend the recently completed HCP Young-Adult (HCP-YA) project to nearly the full lifespan, collecting structural, resting-state fMRI, task-fMRI, diffusion, and perfusion MRI in participants from 5 to 100+ years of age. HCP-D is enrolling 1300+ healthy children, adolescents, and young adults (ages 5-21), and HCP-A is enrolling 1200+ healthy adults (ages 36-100+), with each study collecting longitudinal data in a subset of individuals at particular age ranges. The imaging protocols of the HCP-D and HCP-A studies are very similar, differing primarily in the selection of different task-fMRI paradigms. We strove to harmonize the imaging protocol to the greatest extent feasible with the completed HCP-YA (1200+ participants, aged 22-35), but some imaging-related changes were motivated or necessitated by hardware changes, the need to reduce the total amount of scanning per participant, and/or the additional challenges of working with young and elderly populations. Here, we provide an overview of the common HCP-D/A imaging protocol including data and rationales for protocol decisions and changes relative to HCP-YA. The result will be a large, rich, multi-modal, and freely available set of consistently acquired data for use by the scientific community to investigate and define normative developmental and aging related changes in the healthy human brain.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neuroimage.2018.09.060DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6484842PMC
December 2018

Dedifferentiation of caudate functional connectivity and striatal dopamine transporter density predict memory change in normal aging.

Proc Natl Acad Sci U S A 2018 10 17;115(40):10160-10165. Epub 2018 Sep 17.

Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129.

Age-related changes in striatal function are potentially important for predicting declining memory performance over the adult life span. Here, we used fMRI to measure functional connectivity of caudate subfields with large-scale association networks and positron emission tomography to measure striatal dopamine transporter (DAT) density in 51 older adults (age 65-86 years) who received annual cognitive testing for up to 7 years (mean = 5.59, range 2-7 years). Analyses showed that cortical-caudate functional connectivity was less differentiated in older compared with younger adults ( = 63, age 18-32 years). Unlike in younger adults, the central lateral caudate was less strongly coupled with the frontal parietal control network in older adults. Older adults also showed less "decoupling" of the caudate from other networks, including areas of the default network (DN) and the hippocampal complex. Contrary to expectations, less decoupling between caudate and the DN was not associated with an age-related reduction of striatal DAT, suggesting that neurobiological changes in the cortex may drive dedifferentiation of cortical-caudate connectivity. Reduction of specificity in functional coupling between caudate and regions of the DN predicted memory decline over subsequent years at older ages. The age-related reduction in striatal DAT density also predicted memory decline, suggesting that a relation between striatal functions and memory decline in aging is multifaceted. Collectively, the study provides evidence highlighting the association of age-related differences in striatal function to memory decline in normal aging.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1073/pnas.1804641115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6176586PMC
October 2018

The Lifespan Human Connectome Project in Development: A large-scale study of brain connectivity development in 5-21 year olds.

Neuroimage 2018 12 22;183:456-468. Epub 2018 Aug 22.

Department of Psychiatry, Washington University Medical School, St. Louis, MO, USA; Department of Radiology, Washington University Medical School, St. Louis, MO, USA; Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA.

Recent technological and analytical progress in brain imaging has enabled the examination of brain organization and connectivity at unprecedented levels of detail. The Human Connectome Project in Development (HCP-D) is exploiting these tools to chart developmental changes in brain connectivity. When complete, the HCP-D will comprise approximately ∼1750 open access datasets from 1300 + healthy human participants, ages 5-21 years, acquired at four sites across the USA. The participants are from diverse geographical, ethnic, and socioeconomic backgrounds. While most participants are tested once, others take part in a three-wave longitudinal component focused on the pubertal period (ages 9-17 years). Brain imaging sessions are acquired on a 3 T Siemens Prisma platform and include structural, functional (resting state and task-based), diffusion, and perfusion imaging, physiological monitoring, and a battery of cognitive tasks and self-reports. For minors, parents additionally complete a battery of instruments to characterize cognitive and emotional development, and environmental variables relevant to development. Participants provide biological samples of blood, saliva, and hair, enabling assays of pubertal hormones, health markers, and banked DNA samples. This paper outlines the overarching aims of the project, the approach taken to acquire maximally informative data while minimizing participant burden, preliminary analyses, and discussion of the intended uses and limitations of the dataset.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neuroimage.2018.08.050DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6416053PMC
December 2018

Quantifying the Effects of 16p11.2 Copy Number Variants on Brain Structure: A Multisite Genetic-First Study.

Biol Psychiatry 2018 08 27;84(4):253-264. Epub 2018 Mar 27.

Service of Medical Genetics, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland; CHU Sainte-Justine Research Center, Université de Montréal, Montréal, Quebec, Canada. Electronic address:

Background: 16p11.2 breakpoint 4 to 5 copy number variants (CNVs) increase the risk for developing autism spectrum disorder, schizophrenia, and language and cognitive impairment. In this multisite study, we aimed to quantify the effect of 16p11.2 CNVs on brain structure.

Methods: Using voxel- and surface-based brain morphometric methods, we analyzed structural magnetic resonance imaging collected at seven sites from 78 individuals with a deletion, 71 individuals with a duplication, and 212 individuals without a CNV.

Results: Beyond the 16p11.2-related mirror effect on global brain morphometry, we observe regional mirror differences in the insula (deletion > control > duplication). Other regions are preferentially affected by either the deletion or the duplication: the calcarine cortex and transverse temporal gyrus (deletion > control; Cohen's d > 1), the superior and middle temporal gyri (deletion < control; Cohen's d < -1), and the caudate and hippocampus (control > duplication; -0.5 > Cohen's d > -1). Measures of cognition, language, and social responsiveness and the presence of psychiatric diagnoses do not influence these results.

Conclusions: The global and regional effects on brain morphometry due to 16p11.2 CNVs generalize across site, computational method, age, and sex. Effect sizes on neuroimaging and cognitive traits are comparable. Findings partially overlap with results of meta-analyses performed across psychiatric disorders. However, the lack of correlation between morphometric and clinical measures suggests that CNV-associated brain changes contribute to clinical manifestations but require additional factors for the development of the disorder. These findings highlight the power of genetic risk factors as a complement to studying groups defined by behavioral criteria.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.biopsych.2018.02.1176DOI Listing
August 2018

Global White Matter Diffusion Characteristics Predict Longitudinal Cognitive Change Independently of Amyloid Status in Clinically Normal Older Adults.

Cereb Cortex 2019 03;29(3):1251-1262

Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

White matter degradation has been proposed as one possible explanation for age-related cognitive decline. In the present study, we examined 2 main questions: 1) Do diffusion characteristics predict longitudinal change in cognition independently or synergistically with amyloid status? 2) Are the effects of diffusion characteristics on longitudinal cognitive change tract-specific or global in nature? Cognitive domains of executive function, episodic memory, and processing speed were measured annually (mean follow-up = 3.93 ± 1.25 years). Diffusion tensor imaging and Pittsburgh Compound-B positron emission tomography were performed at baseline in 265 clinically normal older adults (aged 63-90). Tract-specific diffusion was measured as the mean fractional anisotropy (FA) for 9 major white matter tracts. Global diffusion was measured as the mean FA across the 9 white matter tracts. Linear mixed models demonstrated independent, rather than synergistic, effects of global FA and amyloid status on cognitive decline. After controlling for amyloid status, lower global FA was associated with worse longitudinal performance in episodic memory and processing speed, but not executive function. After accounting for global FA, none of the individual tracts predicted a significant change in cognitive performance. These findings suggest that global, rather than tract-specific, diffusion characteristics predict longitudinal cognitive decline independently of amyloid status.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/cercor/bhy031DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6499008PMC
March 2019

Reply to Risk and Zhu: Mixed-effects modeling as a principled approach to heritability analysis with repeat measurements.

Proc Natl Acad Sci U S A 2018 01 29;115(2):E123. Epub 2017 Dec 29.

Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1073/pnas.1719882115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5777085PMC
January 2018

Parallel Interdigitated Distributed Networks within the Individual Estimated by Intrinsic Functional Connectivity.

Neuron 2017 Jul;95(2):457-471.e5

Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129, USA. Electronic address:

Certain organizational features of brain networks present in the individual are lost when central tendencies are examined in the group. Here we investigated the detailed network organization of four individuals each scanned 24 times using MRI. We discovered that the distributed network known as the default network is comprised of two separate networks possessing adjacent regions in eight or more cortical zones. A distinction between the networks is that one is coupled to the hippocampal formation while the other is not. Further exploration revealed that these two networks were juxtaposed with additional networks that themselves fractionate group-defined networks. The collective networks display a repeating spatial progression in multiple cortical zones, suggesting that they are embedded within a broad macroscale gradient. Regions contributing to the newly defined networks are spatially variable across individuals and adjacent to distinct networks, raising issues for network estimation in group-averaged data and applied endeavors, including targeted neuromodulation.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neuron.2017.06.038DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5519493PMC
July 2017

Heritability analysis with repeat measurements and its application to resting-state functional connectivity.

Proc Natl Acad Sci U S A 2017 05 8;114(21):5521-5526. Epub 2017 May 8.

Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129;

Heritability, defined as the proportion of phenotypic variation attributable to genetic variation, provides important information about the genetic basis of a trait. Existing heritability analysis methods do not discriminate between stable effects (e.g., due to the subject's unique environment) and transient effects, such as measurement error. This can lead to misleading assessments, particularly when comparing the heritability of traits that exhibit different levels of reliability. Here, we present a linear mixed effects model to conduct heritability analyses that explicitly accounts for intrasubject fluctuations (e.g., due to measurement noise or biological transients) using repeat measurements. We apply the proposed strategy to the analysis of resting-state fMRI measurements-a prototypic data modality that exhibits variable levels of test-retest reliability across space. Our results reveal that the stable components of functional connectivity within and across well-established large-scale brain networks can be considerably heritable. Furthermore, we demonstrate that dissociating intra- and intersubject variation can reveal genetic influence on a phenotype that is not fully captured by conventional heritability analyses.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1073/pnas.1700765114DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5448225PMC
May 2017

Novel genetic loci associated with hippocampal volume.

Nat Commun 2017 01 18;8:13624. Epub 2017 Jan 18.

Pennington Biomedical Research Center, Baton Rouge, Louisiana 70808, USA.

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (r=-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/ncomms13624DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5253632PMC
January 2017

Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects.

Nat Genet 2017 01 21;49(1):27-35. Epub 2016 Nov 21.

Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.

Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (odds ratio (OR) = 1.11, P = 5.7 × 10), which persisted after excluding loci implicated in previous studies (OR = 1.07, P = 1.7 × 10). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 × 10) and neurobehavioral phenotypes in mouse (OR = 1.18, P = 7.3 × 10). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by nonallelic homologous recombination.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/ng.3725DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5737772PMC
January 2017

Multidimensional heritability analysis of neuroanatomical shape.

Nat Commun 2016 11 15;7:13291. Epub 2016 Nov 15.

Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Charlestown, Massachusetts 02129, USA.

In the dawning era of large-scale biomedical data, multidimensional phenotype vectors will play an increasing role in examining the genetic underpinnings of brain features, behaviour and disease. For example, shape measurements derived from brain MRI scans are multidimensional geometric descriptions of brain structure and provide an alternate class of phenotypes that remains largely unexplored in genetic studies. Here we extend the concept of heritability to multidimensional traits, and present the first comprehensive analysis of the heritability of neuroanatomical shape measurements across an ensemble of brain structures based on genome-wide SNP and MRI data from 1,320 unrelated, young and healthy individuals. We replicate our findings in an extended twin sample from the Human Connectome Project (HCP). Our results demonstrate that neuroanatomical shape can be significantly heritable, above and beyond volume, and can serve as a complementary phenotype to study the genetic determinants and clinical relevance of brain structure.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/ncomms13291DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5116071PMC
November 2016

Novel genetic loci underlying human intracranial volume identified through genome-wide association.

Nat Neurosci 2016 12 3;19(12):1569-1582. Epub 2016 Oct 3.

Brain Center Rudolf Magnus, Department of Psychiatry, UMC Utrecht, Utrecht, the Netherlands.

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five previously unknown loci for intracranial volume and confirmed two known signals. Four of the loci were also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρ = 0.748), which indicates a similar genetic background and allowed us to identify four additional loci through meta-analysis (N = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, and Parkinson's disease, and were enriched near genes involved in growth pathways, including PI3K-AKT signaling. These findings identify the biological underpinnings of intracranial volume and their link to physiological and pathological traits.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/nn.4398DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5227112PMC
December 2016
-->