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Buimer EEL, Pas P, van den Boomen C, Raemaekers M, Brouwer RM, Hulshoff Pol HE. Age- and sex-related differences in social competence and emotion labeling in pre-adolescence. Dev Cogn Neurosci 2025; 71:101503. [PMID: 39733501 PMCID: PMC11743816 DOI: 10.1016/j.dcn.2024.101503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2024] [Revised: 12/22/2024] [Accepted: 12/23/2024] [Indexed: 12/31/2024] Open
Abstract
Identification of facial expressions is important to navigate social interactions and associates with developmental outcomes. It is presumed that social competence, behavioral emotion labeling and neural emotional face processing are related, but this has rarely been studied. Here, we investigated these interrelations and their associations with age and sex, in the YOUth cohort (1055 children, 8-11 years old). Using a multistep linear modelling approach, we associated parent-reported social competence, basic emotion labeling skills based on pictures of facial expressions, and neural facial emotion processing during a passive-watching fMRI task with pictures of houses and emotional faces. Results showed better emotion labeling and higher social competence for girls compared to boys. Age was positively associated with emotion labeling skills and specific social competence subscales. These age- and sex-differences were not reflected in brain function. During fMRI, happy faces elicited more activity than neutral or fearful faces. However, we did not find evidence for the hypothesized links between social competence and behavioral emotion labeling, and with neural activity. To conclude, in pre-adolescents, social competence and emotion labeling varied with age and sex, while social competence, emotion labeling and neural processing of emotional faces were not associated with each other.
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Affiliation(s)
- Elizabeth E L Buimer
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands; Institute of Education and Child Studies, Leiden University, Leiden, the Netherlands.
| | - Pascal Pas
- Department of Experimental Psychology, Utrecht University, Utrecht, the Netherlands
| | - Carlijn van den Boomen
- Department of Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, the Netherlands
| | - Mathijs Raemaekers
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Rachel M Brouwer
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands; Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, VU University, Amsterdam, the Netherlands
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands; Department of Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, the Netherlands
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2
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Peverill M, Russell JD, Keding TJ, Rich HM, Halvorson MA, King KM, Birn RM, Herringa RJ. Balancing Data Quality and Bias: Investigating Functional Connectivity Exclusions in the Adolescent Brain Cognitive Development℠ (ABCD Study) Across Quality Control Pathways. Hum Brain Mapp 2025; 46:e70094. [PMID: 39788921 PMCID: PMC11717557 DOI: 10.1002/hbm.70094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2024] [Revised: 11/07/2024] [Accepted: 11/24/2024] [Indexed: 01/12/2025] Open
Abstract
Analysis of resting state fMRI (rs-fMRI) typically excludes images substantially degraded by subject motion. However, data quality, including degree of motion, relates to a broad set of participant characteristics, particularly in pediatric neuroimaging. Consequently, when planning quality control (QC) procedures researchers must balance data quality concerns against the possibility of biasing results by eliminating data. In order to explore how researcher QC decisions might bias rs-fMRI findings and inform future research design, we investigated how a broad spectrum of participant characteristics in the Adolescent Brain and Cognitive Development (ABCD) study were related to participant inclusion/exclusion across versions of the dataset (the ABCD Community Collection and ABCD Release 4) and QC choices (specifically, motion scrubbing thresholds). Across all these conditions, we found that the odds of a participant's exclusion related to a broad spectrum of behavioral, demographic, and health-related variables, with the consequence that rs-fMRI analyses using these variables are likely to produce biased results. Consequently, we recommend that missing data be formally accounted for when analyzing rs-fMRI data and interpreting results. Our findings demonstrate the urgent need for better data acquisition and analysis techniques which minimize the impact of motion on data quality. Additionally, we strongly recommend including detailed information about quality control in open datasets such as ABCD.
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Affiliation(s)
- Matthew Peverill
- Department of
PsychiatryUniversity of Wisconsin–MadisonMadison, WIUSA
| | - Justin D. Russell
- Department of
PsychiatryUniversity of Wisconsin–MadisonMadison, WIUSA
| | - Taylor J. Keding
- Department of
PsychiatryUniversity of Wisconsin–MadisonMadison, WIUSA
- Department of
PsychologyYale UniversityNew Haven, CTUSA
| | - Hailey M. Rich
- Department of
PsychiatryUniversity of Wisconsin–MadisonMadison, WIUSA
| | | | - Kevin M. King
- Department of
PsychologyUniversity of WashingtonSeattle, WAUSA
| | - Rasmus M. Birn
- Department of
PsychiatryUniversity of Wisconsin–MadisonMadison, WIUSA
| | - Ryan J. Herringa
- Department of
PsychiatryUniversity of Wisconsin–MadisonMadison, WIUSA
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3
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Martin E, Cao M, Schulz KP, Hildebrandt T, Sysko R, Berner LA, Li X. Distinct Topological Properties of the Reward Anticipation Network in Preadolescent Children With Binge Eating Disorder Symptoms. J Am Acad Child Adolesc Psychiatry 2024; 63:1158-1168. [PMID: 38461893 PMCID: PMC11380707 DOI: 10.1016/j.jaac.2024.02.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 02/01/2024] [Accepted: 03/01/2024] [Indexed: 03/12/2024]
Abstract
OBJECTIVE Few studies have considered the neural underpinnings of binge eating disorder (BED) in children, despite clinical and subclinical symptom presentation occurring in this age group. Symptom presentation at this age is of clinical relevance, as early onset of binge eating is linked to negative health outcomes. Studies in adults have highlighted dysfunction in the frontostriatal reward system as a potential candidate for binge eating pathophysiology, although the exact nature of such dysfunction is currently unclear. METHOD Data from 83 children (mean age 9.9 years, SD = 0.60) with symptoms of BED (57% girls) and 123 control participants (mean age 10.0 years, SD = 0.60) (52% girls) were acquired from the 4.0 baseline release of the Adolescent Brain Cognitive Development Study. Task-based graph theoretic techniques were used to analyze data from anticipation trials of the monetary incentive delay task. Network and nodal properties were compared between groups. RESULTS The BED-S group showed alterations in topological properties associated with the frontostriatal subnetwork, such as reduced nodal efficiency in the superior frontal gyrus, nucleus accumbens, putamen, and in normal sex-difference patterns of these properties, such as diminished girls-greater-than-boys pattern of betweenness-centrality in nucleus accumbens observed in controls. CONCLUSION Distinct network properties and sex-difference patterns in preadolescent children with BED-S suggest dysregulation in the reward system compared to those of matched controls. For the first time, these results quantify this dysregulation in terms of systems-level properties during anticipation of monetary reward and significantly inform the early and sex-related brain markers of BED symptoms. PLAIN LANGUAGE SUMMARY Binge eating disorder is the most common eating disorder. One factor that may contribute to binge eating is dysregulation of the reward system in the brain. This study analyzed brain activity during anticipation of monetary rewards in 83 youth with and 123 children without binge eating disorder symptoms from the Adolescent Brain Cognitive Development Study. The authors found specific alterations in the frontostriatal system, responsible for reward processing, in children with binge eating disorder symptoms, compared to the control group, suggesting dysregulation of the reward system.
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Affiliation(s)
- Elizabeth Martin
- Icahn School of Medicine at Mount Sinai, New York, New Jersey; New Jersey Institute of Technology, Newark, New Jersey
| | - Meng Cao
- New Jersey Institute of Technology, Newark, New Jersey
| | - Kurt P Schulz
- Icahn School of Medicine at Mount Sinai, New York, New Jersey
| | - Tom Hildebrandt
- Icahn School of Medicine at Mount Sinai, New York, New Jersey
| | - Robyn Sysko
- Icahn School of Medicine at Mount Sinai, New York, New Jersey
| | - Laura A Berner
- Icahn School of Medicine at Mount Sinai, New York, New Jersey
| | - Xiaobo Li
- New Jersey Institute of Technology, Newark, New Jersey.
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4
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Cattarinussi G, Di Giorgio A, Sambataro F. Cerebellar dysconnectivity in schizophrenia and bipolar disorder is associated with cognitive and clinical variables. Schizophr Res 2024; 267:497-506. [PMID: 38582653 DOI: 10.1016/j.schres.2024.03.039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 03/11/2024] [Accepted: 03/27/2024] [Indexed: 04/08/2024]
Abstract
BACKGROUND Abnormal cerebellar functional connectivity (FC) has been implicated in the pathophysiology of schizophrenia (SCZ) and bipolar disorder (BD). However, the patterns of cerebellar dysconnectivity in these two disorders and their association with cognitive functioning and clinical symptoms have not been fully clarified. In this study, we examined cerebellar FC alterations in SCZ and BD-I and their association with cognition and psychotic symptoms. METHODS Resting-state functional magnetic resonance imaging (rs-fMRI) data of 39 SCZ, 43 BD-I, and 61 healthy controls from the Consortium for Neuropsychiatric Phenomics dataset were examined. The cerebellum was parcellated into ten functional networks, and seed-based FC was calculated for each cerebellar system. Principal component analyses were used to reduce the dimensionality of the diagnosis-related FC and cognitive variables. Multiple regression analyses were used to assess the relationship between FC and cognitive and clinical data. RESULTS We observed decreased cerebellar FC with the frontal, temporal, occipital, and thalamic areas in individuals with SCZ, and a more widespread decrease in cerebellar FC in individuals with BD-I, involving the frontal, cingulate, parietal, temporal, occipital, and thalamic regions. SCZ had increased within-cerebellum and cerebellar frontal FC compared to BD-I. In BD-I, memory and verbal learning performances, which were higher compared to SCZ, showed a greater interaction with cerebellar FC patterns. Additionally, patterns of increased cortico-cerebellar FC were marginally associated with positive symptoms in patients. CONCLUSIONS Our findings suggest that shared and distinct patterns of cortico-cerebellar dysconnectivity in SCZ and BD-I could underlie cognitive impairments and psychotic symptoms in these disorders.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Padova, Italy; Padova Neuroscience Center, University of Padova, Padova, Italy; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Annabella Di Giorgio
- Department of Mental Health and Addictions, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Padova, Italy; Padova Neuroscience Center, University of Padova, Padova, Italy.
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5
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Bloom PA, Pagliaccio D, Zhang J, Bauer CCC, Kyler M, Greene KD, Treves I, Morfini F, Durham K, Cherner R, Bajwa Z, Wool E, Olafsson V, Lee RF, Bidmead F, Cardona J, Kirshenbaum JS, Ghosh S, Hinds O, Wighton P, Galfalvy H, Simpson HB, Whitfield-Gabrieli S, Auerbach RP. Mindfulness-based real-time fMRI neurofeedback: a randomized controlled trial to optimize dosing for depressed adolescents. BMC Psychiatry 2023; 23:757. [PMID: 37848857 PMCID: PMC10580563 DOI: 10.1186/s12888-023-05223-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Accepted: 09/26/2023] [Indexed: 10/19/2023] Open
Abstract
BACKGROUND Adolescence is characterized by a heightened vulnerability for Major Depressive Disorder (MDD) onset, and currently, treatments are only effective for roughly half of adolescents with MDD. Accordingly, novel interventions are urgently needed. This study aims to establish mindfulness-based real-time fMRI neurofeedback (mbNF) as a non-invasive approach to downregulate the default mode network (DMN) in order to decrease ruminatory processes and depressive symptoms. METHODS Adolescents (N = 90) with a current diagnosis of MDD ages 13-18-years-old will be randomized in a parallel group, two-arm, superiority trial to receive either 15 or 30 min of mbNF with a 1:1 allocation ratio. Real-time neurofeedback based on activation of the frontoparietal network (FPN) relative to the DMN will be displayed to participants via the movement of a ball on a computer screen while participants practice mindfulness in the scanner. We hypothesize that within-DMN (medial prefrontal cortex [mPFC] with posterior cingulate cortex [PCC]) functional connectivity will be reduced following mbNF (Aim 1: Target Engagement). Additionally, we hypothesize that participants in the 30-min mbNF condition will show greater reductions in within-DMN functional connectivity (Aim 2: Dosing Impact on Target Engagement). Aim 1 will analyze data from all participants as a single-group, and Aim 2 will leverage the randomized assignment to analyze data as a parallel-group trial. Secondary analyses will probe changes in depressive symptoms and rumination. DISCUSSION Results of this study will determine whether mbNF reduces functional connectivity within the DMN among adolescents with MDD, and critically, will identify the optimal dosing with respect to DMN modulation as well as reduction in depressive symptoms and rumination. TRIAL REGISTRATION This study has been registered with clinicaltrials.gov, most recently updated on July 6, 2023 (trial identifier: NCT05617495).
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Affiliation(s)
- Paul A Bloom
- Department of Psychiatry, Columbia University, New York, NY, USA.
| | - David Pagliaccio
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Jiahe Zhang
- Department of Psychology, Northeastern University, Boston, MA, USA
| | - Clemens C C Bauer
- Department of Psychology, Northeastern University, Boston, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Mia Kyler
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Keara D Greene
- Department of Psychology, Northeastern University, Boston, MA, USA
| | - Isaac Treves
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - Katherine Durham
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Rachel Cherner
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Zia Bajwa
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Emma Wool
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Valur Olafsson
- Northeastern University Biomedical Imaging Center, Boston, MA, USA
| | - Ray F Lee
- Zuckerman Mind Brain and Behavior Institute, Columbia University, New York, NY, USA
| | - Fred Bidmead
- Northeastern University Biomedical Imaging Center, Boston, MA, USA
| | - Jonathan Cardona
- Zuckerman Mind Brain and Behavior Institute, Columbia University, New York, NY, USA
| | | | | | | | - Paul Wighton
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Hanga Galfalvy
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - H Blair Simpson
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Susan Whitfield-Gabrieli
- Department of Psychology, Northeastern University, Boston, MA, USA
- Northeastern University Biomedical Imaging Center, Boston, MA, USA
| | - Randy P Auerbach
- Department of Psychiatry, Columbia University, New York, NY, USA
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6
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Ruiz M, Groessing A, Guran A, Koçan AU, Mikus N, Nater UM, Kouwer K, Posserud MB, Salomon-Gimmon M, Todorova B, Wagner IC, Gold C, Silani G, Specht K. Music for autism: a protocol for an international randomized crossover trial on music therapy for children with autism. Front Psychiatry 2023; 14:1256771. [PMID: 37886114 PMCID: PMC10598663 DOI: 10.3389/fpsyt.2023.1256771] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 09/18/2023] [Indexed: 10/28/2023] Open
Abstract
The notion of a connection between autism and music is as old as the first reported cases of autism, and music has been used as a therapeutic tool for many decades. Music therapy holds promise as an intervention for individuals with autism, harnessing their strengths in music processing to enhance communication and expression. While previous randomized controlled trials have demonstrated positive outcomes in terms of global improvement and quality of life, their reliance on psychological outcomes restricts our understanding of underlying mechanisms. This paper introduces the protocol for the Music for Autism study, a randomized crossover trial designed to investigate the effects of a 12-week music therapy intervention on a range of psychometric, neuroimaging, and biological outcomes in school-aged children with autism. The protocol builds upon previous research and aims to both replicate and expand upon findings that demonstrated improvements in social communication and functional brain connectivity following a music intervention. The primary objective of this trial is to determine whether music therapy leads to improvements in social communication and functional brain connectivity as compared to play-based therapy. In addition, secondary aims include exploring various relevant psychometric, neuroimaging, and biological outcomes. To achieve these objectives, we will enroll 80 participants aged 6-12 years in this international, assessor-blinded, crossover randomized controlled trial. Each participant will be randomly assigned to receive either music therapy or play-based therapy for a period of 12 weeks, followed by a 12-week washout period, after which they will receive the alternate intervention. Assessments will be conducted four times, before and after each intervention period. The protocol of the Music for Autism trial provides a comprehensive framework for studying the effects of music therapy on a range of multidimensional outcomes in children with autism. The findings from this trial have the potential to contribute to the development of evidence-based interventions that leverage strengths in music processing to address the complex challenges faced by individuals with autism. Clinical Trial Registration: Clinicaltrials.gov identifier NCT04936048.
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Affiliation(s)
- Marianna Ruiz
- Department of Health and Social Sciences, Norwegian Research Centre (NORCE), Bergen, Norway
- Department of Biological and Medical Psychology, Faculty of Psychology, University of Bergen, Bergen, Norway
| | - Alexander Groessing
- Department of Clinical and Health Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Alexandrina Guran
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
- Vienna Cognitive Science Hub, University of Vienna, Vienna, Austria
| | - Asena U. Koçan
- Department of Clinical and Health Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Nace Mikus
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
- School of Culture and Society, Interacting Minds Centre, Aarhus University, Aarhus, Denmark
| | - Urs M. Nater
- Department of Clinical and Health Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Karlijn Kouwer
- Department of Biological and Medical Psychology, Faculty of Psychology, University of Bergen, Bergen, Norway
| | - Maj-Britt Posserud
- Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Medicine, Faculty of Medicine, University of Bergen, Bergen, Norway
| | - Maayan Salomon-Gimmon
- Department of Clinical and Health Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
- The School of Creative Arts Therapies, Faculty of Social Welfare and Health Sciences, University of Haifa, Haifa, Israel
| | - Boryana Todorova
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Isabella C. Wagner
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
- Vienna Cognitive Science Hub, University of Vienna, Vienna, Austria
- Centre for Microbiology and Environmental Systems Science, University of Vienna, Vienna, Austria
| | - Christian Gold
- Department of Health and Social Sciences, Norwegian Research Centre (NORCE), Bergen, Norway
- Department of Clinical and Health Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Giorgia Silani
- Department of Clinical and Health Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Karsten Specht
- Department of Biological and Medical Psychology, Faculty of Psychology, University of Bergen, Bergen, Norway
- Department of Radiology, Mohn Medical Imaging and Visualization Centre, Haukeland University Hospital, Bergen, Norway
- Department of Education, Faculty of Humanities, Social Sciences and Education, UiT-The Arctic University of Norway, Tromsø, Norway
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Elyounssi S, Kunitoki K, Clauss JA, Laurent E, Kane K, Hughes DE, Hopkinson CE, Bazer O, Sussman RF, Doyle AE, Lee H, Tervo-Clemmens B, Eryilmaz H, Gollub RL, Barch DM, Satterthwaite TD, Dowling KF, Roffman JL. Uncovering and mitigating bias in large, automated MRI analyses of brain development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.28.530498. [PMID: 36909456 PMCID: PMC10002762 DOI: 10.1101/2023.02.28.530498] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
Large, population-based MRI studies of adolescents promise transformational insights into neurodevelopment and mental illness risk 1,2. However, MRI studies of youth are especially susceptible to motion and other artifacts 3,4. These artifacts may go undetected by automated quality control (QC) methods that are preferred in high-throughput imaging studies, 5 and can potentially introduce non-random noise into clinical association analyses. Here we demonstrate bias in structural MRI analyses of children due to inclusion of lower quality images, as identified through rigorous visual quality control of 11,263 T1 MRI scans obtained at age 9-10 through the Adolescent Brain Cognitive Development (ABCD) Study6. Compared to the best-rated images (44.9% of the sample), lower-quality images generally associated with decreased cortical thickness and increased cortical surface area measures (Cohen's d 0.14-2.84). Variable image quality led to counterintuitive patterns in analyses that associated structural MRI and clinical measures, as inclusion of lower-quality scans altered apparent effect sizes in ways that increased risk for both false positives and negatives. Quality-related biases were partially mitigated by controlling for surface hole number, an automated index of topological complexity that differentiated lower-quality scans with good specificity at Baseline (0.81-0.93) and in 1,000 Year 2 scans (0.88-1.00). However, even among the highest-rated images, subtle topological errors occurred during image preprocessing, and their correction through manual edits significantly and reproducibly changed thickness measurements across much of the cortex (d 0.15-0.92). These findings demonstrate that inadequate QC of youth structural MRI scans can undermine advantages of large sample size to detect meaningful associations.
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Affiliation(s)
- Safia Elyounssi
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Keiko Kunitoki
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Jacqueline A. Clauss
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Eline Laurent
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Kristina Kane
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Dylan E. Hughes
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
- Departments of Psychiatry & Biobehavioral Sciences, University of California, Los Angeles
| | - Casey E. Hopkinson
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Oren Bazer
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Rachel Freed Sussman
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Alysa E. Doyle
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Center for Genomic Medicine, Massachusetts General Hospital
| | - Hang Lee
- Biostatistics Center, Massachusetts General Hospital and Harvard Medical School
| | | | - Hamdi Eryilmaz
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Randy L. Gollub
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Deanna M. Barch
- Department of Psychological and Brain Sciences, Washington University in St. Louis
| | - Theodore D. Satterthwaite
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine
- Penn Lifespan and Neuroimaging Center, University of Pennsylvania Perelman School of Medicine
- Penn-CHOP Lifespan Brain Institute
| | - Kevin F. Dowling
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Department of Psychiatry, University of Pittsburgh
| | - Joshua L. Roffman
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
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