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Meda S.A.,Institute of Living at Hartford Hospital | Wang Z.,Central South University | Ivleva E.I.,University of Texas at Dallas | Poudyal G.,University of Texas at Dallas | And 13 more authors.
Schizophrenia Bulletin | Year: 2015

Background: We quantified frequency-specific, absolute, and fractional amplitude of low-frequency fluctuations (ALFF/fALFF) across the schizophrenia (SZ)-psychotic bipolar disorder (PBP) psychosis spectrum using resting functional magnetic resonance imaging data from the large BSNIP family study. Methods: We assessed 242 healthy controls (HC), 547 probands (180 PBP, 220 SZ, and 147 schizoaffective disorder - SAD), and 410 of their first-degree relatives (134 PBPR, 150SZR, and 126 SADR). Following standard preprocessing in statistical parametric mapping (SPM8), we computed absolute and fractional power (ALFF/fALFF) in 2 low-frequency bands: slow-5 (0.01-0.027 Hz) and slow-4 (0.027-0.073 Hz). We evaluated voxelwise post hoc differences across traditional Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition diagnostic categories. Results: Across ALFF/fALFF, in contrast to HC, BP/SAD showed hypoactivation in frontal/anterior brain regions in the slow-5 band and hypoactivation in posterior brain regions in the slow-4 band. SZ showed consistent hypoactivation in precuneus/cuneus and posterior cingulate across both bands and indices. Increased ALFF/fALFF was noted predominantly in deep subcortical and temporal structures across probands in both bands and indices. Across probands, spatial ALFF/fALFF differences in SAD resembled PBP more than SZ. None of these ALFF/fALFF differences were detected in relatives. Conclusions: Results suggest ALFF/fALFF is a putative biomarker rather than a familial endophenotype. Overall sensitivity to discriminate proband brain alteration was stronger for fALFF than ALFF. Patterns of differences noted in SAD were more similar to those observed in PBP. Differential effects were noted across the 2 frequency bands, more prominently for BP/SAD compared with SZ, suggesting frequency-sensitive physiologic mechanisms for the former. © 2015 The Author. Source

Stevens M.C.,Institute of Living at Hartford Hospital | Stevens M.C.,Yale University | Haney-Caron E.,Institute of Living at Hartford Hospital
Journal of Psychiatry and Neuroscience | Year: 2012

Background: Previous studies of brain structure abnormalities in conduct disorder and attention-deficit/hyperactivity disorder (ADHD) samples have been limited owing to cross-comorbidity, preventing clear understanding of which structural brain abnormalities might be specific to or shared by each disorder. To our knowledge, this study was the first direct comparison of grey and white matter volumes in diagnostically "pure" (i.e., no comorbidities) conduct disorder and ADHD samples. Methods: Groups of adolescents with noncormobid conduct disorder and with noncomorbid, combined-subtype ADHD were compared with age- and sex-matched controls using DARTEL voxel-based analysis of T1,-weighted brain structure images. Analysis of variance with post hoc analyses compared whole brain grey and white matter volumes among the groups. Results: We included 24 adolescents in each study group. There was an overall 13% reduction in grey matter volume in adolescents with conduct disorder, reflecting numerous frontal, temporal, parietal and subcortical deficits. The same grey matter regions typically were not abnormal in those with ADHD. Deficits in frontal lobe regions previously identified in studies of patients with ADHD either were not detected, or group differences from controls were not as strong as those between the conduct disorder and control groups. White matter volume measurements did not differentiate conduct disorder and ADHD. Limitations: Our modest sample sizes prevented meaningful examination of individual features of ADHD or conduct disorder, such as aggression, callousness, or hyperactive versus inattentive symptom subtypes. Conclusion: The evidence supports theories of frontotemporal abnormalities in adolescents with conduct disorder, but raises questions about the prominence of frontal lobe and striatal structural abnormalities in those with noncomorbid, combined-subtype ADHD. The latter point is clinically important, given the widely held belief that ADHD is associated with numerous frontal lobe structural deficits, a conclusion that is not strongly supported following direct comparison of diagnostically pure groups. The results are important for future etiological studies, particularly those seeking to identify how early expression of specific brain structure abnormalities could potentiate the risk for antisocial behaviour. © 2012 Canadian Medical Association. Source

Wang Z.,Central South University | Meda S.A.,Institute of Living at Hartford Hospital | Keshavan M.S.,Harvard University | Tamminga C.A.,University of Texas Southwestern Medical Center | And 9 more authors.
Frontiers in Psychiatry | Year: 2015

To investigate whether aberrant interactions between brain structure and function present similarly or differently across probands with psychotic illnesses [schizophrenia (SZ), schizoaffective disorder (SAD), and bipolar I disorder with psychosis (BP)] and whether these deficits are shared with their first-degree non-psychotic relatives. A total of 1199 subjects were assessed, including 220 SZ, 147 SAD, 180 psychotic BP, 150 first-degree relatives of SZ, 126 SAD relatives, 134 BP relatives, and 242 healthy controls (1). All subjects underwent structural MRI (sMRI) and resting-state functional MRI (rs-fMRI) scanning. Joint-independent component analysis (jICA) was used to fuse sMRI gray matter and rs-fMRI amplitude of low-frequency fluctuations data to identify the relationship between the two modalities. jICA revealed two significantly fused components. The association between functional brain alteration in a prefrontal-striatal-thalamic-cerebellar network and structural abnormalities in the default mode network was found to be common across psychotic diagnoses and correlated with cognitive function, social function, and schizo-bipolar scale scores. The fused alteration in the temporal lobe was unique to SZ and SAD. The above effects were not seen in any relative group (including those with cluster-A personality). Using a multivariate-fused approach involving two widely used imaging markers, we demonstrate both shared and distinct biological traits across the psychosis spectrum. Furthermore, our results suggest that the above traits are psychosis biomarkers rather than endophenotypes. © 2015 Wang, Meda, Keshavan, Tamminga, Sweeney, Clementz, Schretlen, Calhoun, Lui and Pearlson. Source

Anderson B.M.,Institute of Living at Hartford Hospital | Stevens M.C.,Institute of Living at Hartford Hospital | Stevens M.C.,Yale University | Meda S.A.,Institute of Living at Hartford Hospital | And 7 more authors.
Alcoholism: Clinical and Experimental Research | Year: 2011

Background: The anterior cingulate and several other prefrontal and parietal brain regions are implicated in error processing and cognitive control. The effects of different doses of alcohol on activity within these brain regions during a functional magnetic resonance imaging (fMRI) task where errors are frequently committed have not been fully explored.Methods: This study examined the impact of a placebo [breath alcohol concentration (BrAC) = 0.00%], moderate (BrAC = 0.05%), and high (BrAC = 0.10%) doses of alcohol on brain hemodynamic activity during a functional MRI (fMRI) Go/No-Go task in 38 healthy volunteers.Results: Alcohol increased reaction time and false alarm errors in a dose-dependent manner. fMRI analyses showed alcohol decreased activity in anterior cingulate, lateral prefrontal cortex, insula, and parietal lobe regions during false alarm responses to No-Go stimuli.Conclusions: These findings indicate that brain regions implicated in error processing are affected by alcohol and might provide a neural basis for alcohol's effects on behavioral performance. Copyright © 2010 by the Research Society on Alcoholism. Source

Di Martino A.,New York University | Yan C.-G.,Nathan S Kline Institute For Psychiatric Research | Li Q.,Child Mind Institute | Denio E.,New York University | And 47 more authors.
Molecular Psychiatry | Year: 2014

Autism spectrum disorders (ASDs) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, lifelong nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. Although the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE) - a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) data sets with corresponding structural MRI and phenotypic information from 539 individuals with ASDs and 573 age-matched typical controls (TCs; 7-64 years) (http://fcon-1000.projects. nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 male subjects with ASDs and 403 male age-matched TCs. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo- and hyperconnectivity in the ASD literature; both were detected, although hypoconnectivity dominated, particularly for corticocortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASDs (mid- and posterior insula and posterior cingulate cortex), and highlighted less commonly explored regions such as the thalamus. The survey of the ABIDE R-fMRI data sets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international data sets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies. © 2014 Macmillan Publishers Limited. Source

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