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The power of many brains: Catalyzing neuropsychiatric discovery through open neuroimaging data and large-scale collaboration

Lu, Bin; Chen, Xiao; Xavier Castellanos, Francisco; Thompson, Paul M; Zuo, Xi-Nian; Zang, Yu-Feng; Yan, Chao-Gan
Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders. By pooling images from various cohorts, statistical power has increased, enabling the detection of subtle abnormalities and robust associations, and fostering new research methods. Global collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted treatment. Large-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric studies. We also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric disorders. However, challenges such as data harmonization across different sites, privacy protection, and effective data sharing must be addressed. With proper governance and open science practices, we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis, treatment selection, and outcome prediction, contributing to optimal brain health.
PMID: 38519398
ISSN: 2095-9281
CID: 5640992

Transcranial photobiomodulation increases intrinsic brain activity within irradiated areas in early Alzheimer's disease: Potential link with cerebral metabolism [Letter]

Gaggi, Naomi L; Collins, Katherine A; Gonzalez-Castillo, Javier; Hurtado, Aura M; Castellanos, Francisco Xavier; Osorio, Ricardo; Cassano, Paolo; Iosifescu, Dan V
PMID: 38387555
ISSN: 1876-4754
CID: 5634492

Chronic Mild Sleep Restriction Does Not Lead to Marked Neuronal Alterations Compared to Maintained Adequate Sleep in Adults

Li, Xue-Ying; Yoncheva, Yuliya; Yan, Chao-Gan; Castellanos, Francisco Xavier; St-Onge, Marie-Pierre
BACKGROUND:Sleep restriction (SR) has been shown to upregulate neuronal reward networks in response to food stimuli but prior studies were short-term and employed severe SR paradigms. OBJECTIVE:Our goal was to determine whether mild SR, achieved by delaying bedtimes by 1.5h, influences neuronal networks responsive to food stimuli compared to maintained adequate sleep (AS) >7h/night. METHODS:A randomized controlled crossover study with two 6-wk phases, AS (≥7h sleep/night) and SR (-1.5h/night relative to screening), was conducted. Adults with adequate sleep duration, measured using wrist-actigraphy over a 2-wk screening period, and self-reported good sleep quality were enrolled. Resting-state and food-stimulated functional neuroimaging (fMRI) was performed at endpoint of each phase. Resting-state fMRI data analyses included a priori region-of-interest seed-based functional connectivity, whole-brain voxel-wise analyses, and network analyses. Food-task fMRI analyses compared brain activity patterns in response to food cues between conditions. Paired-sample t-tests tested differences between conditions. RESULTS:Twenty-six participants (16 males; age 29.6±5.3y, body mass index 26.9±4.0kg/m2) contributed complete data. Total sleep time was 7h30±28min/night during AS vs. 6h12±26min/night during SR. We employed different statistical approaches to replicate prior studies in the field and to apply more robust approaches that are currently advocated in the field. Using uncorrected P<0.01, cluster ≥10 voxels thresholds, we replicate prior findings of increased activation in response to foods in reward networks after SR vs. AS (right insula, right inferior frontal gyrus, and right supramarginal gyrus). These findings did not survive more rigorous analytical approaches (Gaussian Random Field theory correction at two-tailed voxel P<0.001, cluster P<0.05). CONCLUSIONS:Results suggest that mild SR leads to increased reward responsivity to foods but with low confidence given failure to meet significance from rigorous statistical analyses. Further research is necessary to inform the mechanisms underlying the role of sleep on food intake regulation. CLINICAL TRIAL REGISTRATION/BACKGROUND:NCT02960776; https://clinicaltrials.gov/ct2/show/NCT02960776.
PMID: 38104943
ISSN: 1541-6100
CID: 5612572

Internet use 101 in college: Do undergraduates want to learn healthier internet use?

Baroni, A; Feder, M A; Castellanos, F X; Li, J; Shatkin, J
BACKGROUND/UNASSIGNED:Internet overuse is an emerging public health emergency, especially for college students in the United States. The purpose of this study was to assess college students' internet usage and interest in learning healthy internet usage skills as part of a college curriculum. STUDY DESIGN/UNASSIGNED:Participants completed an online anonymous questionnaire which included the short version of the Internet Addiction Test, a modified Youth Health Movement survey, and questions regarding their interest in healthy internet use coursework. METHODS/UNASSIGNED:A total of 402 participants were recruited via an email LISTSERV of current undergraduates and recent graduates who had taken at least one class within a child and adolescent mental health studies minor while enrolled in a large university. RESULTS/UNASSIGNED:Overall, 70% of participants reported that they use the internet excessively, and a majority of participants reported that internet use has negatively affected their sleep and increased their anxiety. Seventy percent of participants reported that they would benefit from instruction on healthy internet usage via formal courses for credit or online modules. CONCLUSIONS/UNASSIGNED:Students are aware of the difficulty in managing their internet use in college and are motivated to engage in novel courses on healthy internet usage. Academic institutions should consider developing courses or modules on healthy internet use.
PMCID:10413188
PMID: 37576526
ISSN: 2666-5352
CID: 5591892

Aberrant resting-state functional connectivity of the globus pallidus interna in first-episode schizophrenia

Qi, Wei; Wen, Zhenfu; Chen, Jingyun; Capichioni, Gillian; Ando, Fumika; Chen, Zhe Sage; Wang, Jijun; Yoncheva, Yuliya; Castellanos, Francisco X; Milad, Mohammed; Goff, Donald C
BACKGROUND:The striatal-pallidal pathway plays an important role in cognitive control and modulation of behaviors. Globus pallidus interna (GPi), as a primary output structure, is crucial in modulating excitation and inhibition. Studies of GPi in psychiatric illnesses are lacking given the technical challenges of examining this small and functionally diverse subcortical structure. METHODS:71 medication-naïve first episode schizophrenia (FES) participants and 73 healthy controls (HC) were recruited at the Shanghai Mental Health Center. Clinical symptoms and imaging data were collected at baseline and, in a subset of patients, 8 weeks after initiating treatment. Resting-state functional connectivity of sub-regions of the GP were assessed using a novel mask that combines two atlases to create 8 ROIs in the GP. RESULTS: = 0.486, p < 0.001). CONCLUSIONS:Our results implicate striatal-pallidal-thalamic pathways in antipsychotic efficacy. If replicated, these findings may reflect failure of neurodevelopmental processes in adolescence and early adulthood that decrease functional connectivity as an index of failure of the limbic/associative GPi to appropriately inhibit irrelevant signals in psychosis.
PMID: 37716202
ISSN: 1573-2509
CID: 5593342

A systematic review of digital interventions for smoking cessation in patients with serious mental illness

Martinez Agulleiro, Luis; Patil, Bhagyashree; Firth, Joseph; Sawyer, Chelsea; Amann, Benedikt L; Fonseca, Francina; Torrens, Marta; Perez, Victor; Castellanos, Francisco Xavier; Kane, John M; Guinart, Daniel
Tobacco smoking is highly prevalent among patients with serious mental illness (SMI), with known deleterious consequences. Smoking cessation is therefore a prioritary public health challenge in SMI. In recent years, several smoking cessation digital interventions have been developed for non-clinical populations. However, their impact in patients with SMI remains uncertain. We conducted a systematic review to describe and evaluate effectiveness, acceptability, adherence, usability and safety of digital interventions for smoking cessation in patients with SMI. PubMed/MEDLINE, EMBASE, CINAHL, Web of Science, PsychINFO and the Cochrane Tobacco Addiction Group Specialized Register were searched. Studies matching inclusion criteria were included and their information systematically extracted by independent investigators. Thirteen articles were included, which reported data on nine different digital interventions. Intervention theoretical approaches ranged from mobile contingency management to mindfulness. Outcome measures varied widely between studies. The highest abstinence rates were found for mSMART MIND (7-day point-prevalent abstinence: 16-40%). Let's Talk About Quitting Smoking reported greater acceptability ratings, although this was not evaluated with standardized measures. Regarding usability, Learn to Quit showed the highest System Usability Scale scores [mean (s.d.) 85.2 (15.5)]. Adverse events were rare and not systematically reported. Overall, the quality of the studies was fair to good. Digitally delivered health interventions for smoking cessation show promise for improving outcomes for patients with SMI, but lack of availability remains a concern. Larger trials with harmonized assessment measures are needed to generate more definitive evidence and specific recommendations.
PMID: 37161690
ISSN: 1469-8978
CID: 5544552

Gender Diversity and Brain Morphology Among Adolescents

Xerxa, Yllza; White, Tonya; Busa, Samantha; Trasande, Leonardo; Hillegers, Manon H J; Jaddoe, Vincent W; Castellanos, Francisco Xavier; Ghassabian, Akhgar
IMPORTANCE:Gender-diverse youths have higher rates of mental health problems compared with the general population, as shown in both clinical and nonclinical populations. Brain correlates of gender diversity, however, have been reported only among youths with gender dysphoria or in transgender individuals. OBJECTIVE:To examine brain morphologic correlates of gender diversity among adolescents from a general pediatric population who were assigned male or female at birth, separately. DESIGN, SETTING, AND PARTICIPANTS:This cross-sectional study was embedded in Generation R, a multiethnic population-based study conducted in Rotterdam, the Netherlands. Adolescents who were born between April 1, 2002, and January 31, 2006, and had information on self-reported or parent-reported gender diversity and structural neuroimaging at ages 13 to 15 years were included. Data analysis was performed from April 1 to July 31, 2022. EXPOSURES:Gender-diverse experiences among adolescents were measured with selected items from the Achenbach System of Empirically Based Assessment forms and the Gender Identity/Gender Dysphoria Questionnaire for Adolescents and Adults, as reported by adolescents and/or their parents. MAIN OUTCOMES AND MEASURES:High-resolution structural neuroimaging data were collected using a 3-T magnetic resonance imaging scanner (at a single site). We used linear regression models to examine differences in global brain volumetric measures between adolescents who reported gender diversity and those who did not. RESULTS:This study included 2165 participants, with a mean (SD) age of 13.8 (0.6) years at scanning. A total of 1159 participants (53.5%) were assigned female at birth and 1006 (46.5%) were assigned male at birth. With regard to maternal country of origin, 1217 mothers (57.6%) were from the Netherlands and 896 (42.4%) were from outside the Netherlands. Adolescents who reported gender diversity did not differ in global brain volumetric measures from adolescents who did not report gender diversity. In whole-brain, vertexwise analyses among adolescents assigned male at birth, thicker cortices in the left inferior temporal gyrus were observed among youths who reported gender diversity compared with those who did not. No associations were observed between gender diversity and surface area in vertexwise analyses. CONCLUSIONS AND RELEVANCE:The findings of this cross-sectional study suggest that global brain volumetric measures did not differ between adolescents who reported gender diversity and those who did not. However, these findings further suggest that gender diversity in the general population correlates with specific brain morphologic features in the inferior temporal gyrus among youths who are assigned male at birth. Replication of these findings is necessary to elucidate the potential neurobiological basis of gender diversity in the general population. Future longitudinal studies should also investigate the directionality of these associations.
PMCID:10182431
PMID: 37171820
ISSN: 2574-3805
CID: 5496632

Annual Research Review: Perspectives on progress in ADHD science - from characterization to cause

Sonuga-Barke, Edmund J S; Becker, Stephen P; Bölte, Sven; Castellanos, Francisco Xavier; Franke, Barbara; Newcorn, Jeffrey H; Nigg, Joel T; Rohde, Luis Augusto; Simonoff, Emily
The science of attention-deficit/hyperactivity disorder (ADHD) is motivated by a translational goal - the discovery and exploitation of knowledge about the nature of ADHD to the benefit of those individuals whose lives it affects. Over the past fifty years, scientific research has made enormous strides in characterizing the ADHD condition and in understanding its correlates and causes. However, the translation of these scientific insights into clinical benefits has been limited. In this review, we provide a selective and focused survey of the scientific field of ADHD, providing our personal perspectives on what constitutes the scientific consensus, important new leads to be highlighted, and the key outstanding questions to be addressed going forward. We cover two broad domains - clinical characterization and, risk factors, causal processes and neuro-biological pathways. Part one focuses on the developmental course of ADHD, co-occurring characteristics and conditions, and the functional impact of living with ADHD - including impairment, quality of life, and stigma. In part two, we explore genetic and environmental influences and putative mediating brain processes. In the final section, we reflect on the future of the ADHD construct in the light of cross-cutting scientific themes and recent conceptual reformulations that cast ADHD traits as part of a broader spectrum of neurodivergence.
PMID: 36220605
ISSN: 1469-7610
CID: 5360952

Family Discordance in Gender Identification Is Not Associated with Increased Depression and Anxiety Among Trans Youth

Agulleiro, Luis Martinez; Castellanos, F. Xavier; Janssen, Aron; Baroni, Argelinda
Purpose: We examined the relationship between parent- and child-reported gender identity of the youth with internalizing symptoms in transgender and gender-diverse (TGD) youth. In addition, we investigated differences in sex assigned at birth ratios and pubertal development stages in TGD and cisgender youth. Methods: We analyzed longitudinal data from the Adolescent Brain Cognitive Development study (ABCD), corresponding to baseline and 1st-to-3rd-year follow-up interviews (n = 6030 to n = 9743, age range [9"“13]). Sociodemographic variables, self- and parent-reported gender identity, and clinical measures were collected. Results: TGD youth showed higher levels of internalizing symptoms compared with cisgender youth. However, this was not worsened by discordance in gender identification between TGD youth and parents. Over the 3-year follow-up period, the number of TGD participants increased from 0.8% (95% confidence interval (CI) [0.6"“1.0]) at baseline to 1.4% (95% CI [1.1"“1.7]) at the 3rd-year follow-up (v2 = 10.476, df = 1, false discovery rate (FDR)adjusted p = 0.00256), particularly among those assigned female at birth (AFAB) in relation to people assigned male at birth (AMAB) (AMAB:AFAB at baseline: 1:1.9 vs. AMAB:AFAB at 3rd-year follow-up: 1:4.7, v2 = 40.357, df = 1, FDR-adjusted p < 0.0001). Conclusions: TGD youth in ABCD reported higher internalizing symptoms than cisgender youth, although this was not affected by parental discordance in gender identification. A substantial increase over time in TGD children AFAB was documented. More research is needed to understand the clinical implications of these preliminary results, for which the longitudinal design of ABCD will be crucial.
SCOPUS:85176474037
ISSN: 2325-8292
CID: 5615942

A practical Alzheimer"™s disease classifier via brain imaging-based deep learning on 85,721 samples

Lu, Bin; Li, Hui Xian; Chang, Zhi Kai; Li, Le; Chen, Ning Xuan; Zhu, Zhi Chen; Zhou, Hui Xia; Li, Xue Ying; Wang, Yu Wei; Cui, Shi Xian; Deng, Zhao Yu; Fan, Zhen; Yang, Hong; Chen, Xiao; Thompson, Paul M.; Castellanos, Francisco Xavier; Yan, Chao Gan
Beyond detecting brain lesions or tumors, comparatively little success has been attained in identifying brain disorders such as Alzheimer"™s disease (AD), based on magnetic resonance imaging (MRI). Many machine learning algorithms to detect AD have been trained using limited training data, meaning they often generalize poorly when applied to scans from previously unseen scanners/populations. Therefore, we built a practical brain MRI-based AD diagnostic classifier using deep learning/transfer learning on a dataset of unprecedented size and diversity. A retrospective MRI dataset pooled from more than 217 sites/scanners constituted one of the largest brain MRI samples to date (85,721 scans from 50,876 participants) between January 2017 and August 2021. Next, a state-of-the-art deep convolutional neural network, Inception-ResNet-V2, was built as a sex classifier with high generalization capability. The sex classifier achieved 94.9% accuracy and served as a base model in transfer learning for the objective diagnosis of AD. After transfer learning, the model fine-tuned for AD classification achieved 90.9% accuracy in leave-sites-out cross-validation on the Alzheimer"™s Disease Neuroimaging Initiative (ADNI, 6,857 samples) dataset and 94.5%/93.6%/91.1% accuracy for direct tests on three unseen independent datasets (AIBL, 669 samples / MIRIAD, 644 samples / OASIS, 1,123 samples). When this AD classifier was tested on brain images from unseen mild cognitive impairment (MCI) patients, MCI patients who converted to AD were 3 times more likely to be predicted as AD than MCI patients who did not convert (65.2% vs. 20.6%). Predicted scores from the AD classifier showed significant correlations with illness severity. In sum, the proposed AD classifier offers a medical-grade marker that has potential to be integrated into AD diagnostic practice.
SCOPUS:85139957866
ISSN: 2196-1115
CID: 5350292