Faculty Bibliography
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412
Subcortical Brain Volume, Regional Cortical Thickness, and Cortical Surface Area Across Disorders: Findings From the ENIGMA ADHD, ASD, and OCD Working Groups
OBJECTIVE:Attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data. METHODS:-weighted whole-brain MRI data from healthy control subjects (N=5,827) and from patients with ADHD (N=2,271), ASD (N=1,777), and OCD (N=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. The authors examined subcortical volume, cortical thickness, and cortical surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults, using linear mixed-effects models adjusting for age, sex, and site (and intracranial volume for subcortical and surface area measures). RESULTS:No shared differences were found among all three disorders, and shared differences between any two disorders did not survive correction for multiple comparisons. Children with ADHD compared with those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller intracranial volume than control subjects and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared with adult control subjects and other clinical groups. No OCD-specific differences were observed across different age groups and surface area differences among all disorders in childhood and adulthood. CONCLUSIONS:The study findings suggest robust but subtle differences across different age groups among ADHD, ASD, and OCD. ADHD-specific intracranial volume and hippocampal differences in children and adolescents, and ASD-specific cortical thickness differences in the frontal cortex in adults, support previous work emphasizing structural brain differences in these disorders.
PMID: 32539527
ISSN: 1535-7228
CID: 4484542
Journal of the American Academy of Child and Adolescent Psychiatry. 2020:59(3):422-433.DOI: 10.1016/j.jaac.2019.05.033
Sensory-to-Cognitive Systems Integration Is Associated With Clinical Severity in Autism Spectrum Disorder
OBJECTIVE:Impaired multisensory integration in autism spectrum disorder (ASD) may arise from functional dysconnectivity among brain systems. Our study examines the functional connectivity integration between primary modal sensory regions and heteromodal processing cortex in ASD, and whether abnormalities in network integration relate to clinical severity. METHOD/METHODS:We studied a sample of 55 high-functioning ASD and 64 healthy controls (HC) male children and adolescents (total n = 119, age range 7-18). Stepwise functional connectivity analysis (SFC) was applied to resting state functional magnetic resonance images (rsfMRI) to characterize the connectivity paths that link primary sensory cortices to higher-order brain cognitive functional circuits and relate alterations in functional connectivity integration with three clinical scales: Social Communication Questionnaire, Social Responsiveness Scale, and Vineland Adaptive Behavior Scales. RESULTS:HC displayed typical functional connectivity transitions from primary sensory systems to association areas, but the ASD group showed altered patterns of multimodal sensory integration to heteromodal systems. Specifically, compared to the HC group, the ASD group showed (1) hyper-connectivity in visual cortex at initial link step distances; (2) hyper-connectivity between sensory unimodal regions and regions of the default mode network; and (3) hypo-connectivity between sensory unimodal regions and areas of the fronto-parietal and attentional networks. These patterns of hyper- and hypo-connectivity were associated with increased clinical severity in ASD. CONCLUSION/CONCLUSIONS:Network-wise reorganization in high-functioning ASD individuals affects strategic regions of unimodal-to-heteromodal cortical integration predicting clinical severity. Additionally, SFC analysis appears to be a promising approach for studying the neural pathophysiology of multisensory integration deficits in ASD.
PMID: 31260788
ISSN: 1527-5418
CID: 3971612
Altered resting-state dynamic functional brain networks in major depressive disorder: Findings from the REST-meta-MDD consortium
BACKGROUND:Major depressive disorder (MDD) is known to be characterized by altered brain functional connectivity (FC) patterns. However, whether and how the features of dynamic FC would change in patients with MDD are unclear. In this study, we aimed to characterize dynamic FC in MDD using a large multi-site sample and a novel dynamic network-based approach. METHODS:Resting-state functional magnetic resonance imaging (fMRI) data were acquired from a total of 460 MDD patients and 473 healthy controls, as a part of the REST-meta-MDD consortium. Resting-state dynamic functional brain networks were constructed for each subject by a sliding-window approach. Multiple spatio-temporal features of dynamic brain networks, including temporal variability, temporal clustering and temporal efficiency, were then compared between patients and healthy subjects at both global and local levels. RESULTS:). Corresponding local changes in MDD were mainly found in the default-mode, sensorimotor and subcortical areas. Measures of temporal variability and characteristic temporal path length were significantly correlated with depression severity in patients (corrected p < 0.05). Moreover, the observed between-group differences were robustly present in both first-episode, drug-naïve (FEDN) and non-FEDN patients. CONCLUSIONS:Our findings suggest that excessive temporal variations of brain FC, reflecting abnormal communications between large-scale bran networks over time, may underlie the neuropathology of MDD.
PMID: 31953148
ISSN: 2213-1582
CID: 4264672
Charting brain growth in tandem with brain templates for schoolchildren
Brain growth charts and age-normed brain templates are essential resources for researchers to eventually contribute to the care of individuals with atypical developmental trajectories. The present work generates age-normed brain templates for children and adolescents at one-year intervals and the corresponding growth charts to investigate the influences of age and ethnicity using a common pediatric neuroimaging protocol. Two accelerated longitudinal cohorts with the identical experimental design were implemented in the United States and China. Anatomical magnetic resonance imaging (MRI) of typically developing school-age children (TDC) was obtained up to three times at nominal intervals of 1.25 years. The protocol generated and compared population- and age-specific brain templates and growth charts, respectively. A total of 674 Chinese pediatric MRI scans were obtained from 457 Chinese TDC and 190 American pediatric MRI scans were obtained from 133 American TDC. Population- and age-specific brain templates were used to quantify warp cost, the differences between individual brains and brain templates. Volumetric growth charts for labeled brain network areas were generated. Shape analyses of cost functions supported the necessity of age-specific and ethnicity-matched brain templates, which was confirmed by growth chart analyses. These analyses revealed volumetric growth differences between the two ethnicities primarily in lateral frontal and parietal areas, regions which are most variable across individuals in regard to their structure and function. Age- and ethnicity-specific brain templates facilitate establishing unbiased pediatric brain growth charts, indicating the necessity of the brain charts and brain templates generated in tandem. These templates and growth charts as well as related codes have been made freely available to the public for open neuroscience (https://github.com/zuoxinian/CCS/tree/master/H3/GrowthCharts).
SCOPUS:85089066722
ISSN: 2095-9273
CID: 4579022
Meditation effect in changing functional integrations across large-scale brain networks: Preliminary evidence from a meta-analysis of seed-based functional connectivity
Meditation is a type of mental training commonly applied in clinical settings and also practiced for general well-being. Brain functional connectivity (FC) patterns associated with meditation have revealed its brain mechanisms. However, the variety of FC methods applied has made it difficult to identify brain communication patterns associated with meditation. Here we carried out a coordinate-based meta-analysis to get preliminary evidence of meditation effects on changing brain network interactions. Fourteen seed-based, voxel-wise FC studies reported in 13 publications were reviewed; 10 studies with seeds in the default mode network (DMN) were meta-analyzed. Seed coordinates and the effect sizes in statistically significant regions were extracted, based on 170 subjects in meditation groups and 163 subjects in control groups. Seed-based d-mapping was used to analyze meditation versus control FC differences with DMN seeds. Meditation was associated with increased connectivity within DMN and between DMN and somatomotor network and with decreased connectivity between DMN and frontoparietal network (FPN) as well as ventral attention network (VAN). The pattern of decreased within-DMN FC and increased between-network FC (FPN and DAN with DMN) was more robust in highly experienced meditators compared to less experienced individuals. The identified neural network interactions may also promote meditation's effectiveness in clinical interventions for treating physical and mental disorders.
SCOPUS:85081387888
ISSN: 1834-4909
CID: 4393712
Erratum: Meditation effect in changing functional integrations across large-scale brain networks: Preliminary evidence from a meta-analysis of seed-based functional connectivity (Journal of Pacific Rim Psychology (2020) 14 (E10) DOI: 10.1017/prp.2020.1)
In the above published article there was an error in the abstract, the sentence should read as follows: "Meditation was associated with decreased connectivity within DMN and between DMN and somatomotor network and with increased connectivity between DMN and frontoparietal network (FPN) as well as ventral attention network (VAN)." The authors apologise for this error.
SCOPUS:85096525516
ISSN: 1834-4909
CID: 4732192
Diffusion Kurtosis Imaging of the Cerebellum in Autism Spectrum Disorder [Meeting Abstract]
ISI:000535308200664
ISSN: 0006-3223
CID: 4560872
Resting-State fMRI Correlates of Clinical Response to Stimulant Treatments in Children and Adolescents With ADHD [Meeting Abstract]
ISI:000535308200046
ISSN: 0006-3223
CID: 4560722
RESTING-STATE FMRI CORRELATES OF CLINICAL RESPONSE TO STIMULANTS IN CHILDREN AND ADOLESCENTS WITH ADHD [Meeting Abstract]
ISI:000579844101264
ISSN: 0890-8567
CID: 4685552
Emerging Insights Into the Association Between Nature Exposure and Healthy Neuronal Development
PMID: 31851342
ISSN: 2574-3805
CID: 4242732
