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Jacobsson P, Hopwood CJ, Krueger RF, Söderpalm B, Nilsson T. Conceptualizing adult ADHD with the DSM alternative model of personality disorder. Personal Ment Health 2024; 18:369-386. [PMID: 39239863 DOI: 10.1002/pmh.1632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 07/11/2024] [Accepted: 07/22/2024] [Indexed: 09/07/2024]
Abstract
Personality traits and personality disorders are related to ADHD and indicate dysfunction in clinical populations. The goals of this study were to examine how the DSM-5 Alternative Model of Personality Disorder (AMPD) a) indicates the presence of ADHD and b) communicates information about dysfunction over and above ADHD diagnosis. A sample of 330 adult psychiatric patients with and without ADHD (60% female; mean age 33 years) were assessed for ADHD symptoms, personality impairment, maladaptive personality traits, and functional life impairment domains. The maladaptive personality domain Disinhibition and particularly the lower order facet of Distractibility distinguished between individuals with psychiatric difficulties with and without ADHD. Distractibility is strongly related to the ADHD symptom dimension Inattentiveness, and Antagonism to Hyperactivity/impulsivity. General personality impairment augmented ADHD diagnosis in predicting life impairments. The AMPD has utility in ADHD assessments for diagnosis and prognosis.
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Affiliation(s)
- Peter Jacobsson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sektionskansliet: Blå Stråket 15, vån 3, SU/Sahlgrenska University Hospital, Gothenburg, Sweden
- Region Halland, Varberg, Sweden
| | | | - Robert F Krueger
- Department of Psychology, N414 Elliott Hall, 75 East River, Parkway, University of Minnesota, Minneapolis, MN, USA
| | - Bo Söderpalm
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sektionskansliet: Blå Stråket 15, vån 3, SU/Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Thomas Nilsson
- Centre for Ethics, Law and Mental Health (CELAM), Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
- Forensic Psychiatry, Sahlgrenska University Hospital, Gothenburg, Sweden
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Koirala S, Grimsrud G, Mooney MA, Larsen B, Feczko E, Elison JT, Nelson SM, Nigg JT, Tervo-Clemmens B, Fair DA. Neurobiology of attention-deficit hyperactivity disorder: historical challenges and emerging frontiers. Nat Rev Neurosci 2024:10.1038/s41583-024-00869-z. [PMID: 39448818 DOI: 10.1038/s41583-024-00869-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/19/2024] [Indexed: 10/26/2024]
Abstract
Extensive investigations spanning multiple levels of inquiry, from genetic to behavioural studies, have sought to unravel the mechanistic foundations of attention-deficit hyperactivity disorder (ADHD), with the aspiration of developing efficacious treatments for this condition. Despite these efforts, the pathogenesis of ADHD remains elusive. In this Review, we reflect on what has been learned about ADHD while also providing a framework that may serve as a roadmap for future investigations. We emphasize that ADHD is a highly heterogeneous disorder with multiple aetiologies that necessitates a multifactorial dimensional phenotype, rather than a fixed dichotomous conceptualization. We highlight new findings that suggest a more brain-wide, 'global' view of the disorder, rather than the traditional localizationist framework, which asserts that a limited set of brain regions or networks underlie ADHD. Last, we underscore how underpowered studies that have aimed to associate neurobiology with ADHD phenotypes have long precluded the field from making progress. However, a new age of ADHD research with refined phenotypes, advanced methods, creative study designs and adequately powered investigations is beginning to put the field on a good footing. Indeed, the field is at a promising juncture to advance the neurobiological understanding of ADHD and fulfil the promise of clinical utility.
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Affiliation(s)
- Sanju Koirala
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Gracie Grimsrud
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Michael A Mooney
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
- Departments of Psychiatry, Oregon Health & Science University, Portland, OR, USA
- Center for Mental Health Innovation, Oregon Health & Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Bart Larsen
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Eric Feczko
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Jed T Elison
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Steven M Nelson
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Joel T Nigg
- Departments of Psychiatry, Oregon Health & Science University, Portland, OR, USA
- Center for Mental Health Innovation, Oregon Health & Science University, Portland, OR, USA
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, USA
| | - Brenden Tervo-Clemmens
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Damien A Fair
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA.
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA.
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA.
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Andersson Konke L, Falck-Ytter T, Jones EJH, Goodwin A, Brocki K. Using the Infant Sibling-Design to Explore Associations Between Autism and ADHD Traits in Probands and Temperament in the Younger Siblings. J Autism Dev Disord 2024; 54:3262-3273. [PMID: 37355531 PMCID: PMC11362528 DOI: 10.1007/s10803-023-06047-x] [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] [Accepted: 06/09/2023] [Indexed: 06/26/2023]
Abstract
The purpose of the current study was to use the infant sibling design to explore whether proband traits of autism and ADHD could provide information about their infant sibling's temperament. This could help us to gain information about the extent to which infant temperament traits are differentially associated with autism and ADHD traits. We used parent-ratings of autistic traits and ADHD traits (CRS-3) in older siblings diagnosed with autism (age range 4 to 19 years), and their infant siblings' temperament traits (IBQ) at 9 months of age in 216 sibling pairs from two sites (BASIS, UK, and EASE, Sweden) to examine associations across siblings. We found specific, but modest, associations across siblings after controlling for sex, age, developmental level and site. Proband autistic traits were specifically related to low levels of approach in the infant siblings, with infant developmental level explaining part of the variance in infant approach. Proband ADHD traits were specifically related to high levels of infant activity even after controlling for covariates. Our findings suggest that proband traits of autism and ADHD carry information for infant sibling's temperament, indicating that inherited liability may influence early emerging behaviours in infant siblings. The impact of sex, age, developmental level and site are discussed.
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Affiliation(s)
- Linn Andersson Konke
- Department of Psychology, Uppsala University, Box 1225, 751 42, Uppsala, Sweden.
| | - Terje Falck-Ytter
- Department of Women's and Children's Health, Karolinska Institutet Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden
- Stockholm Health Care Services, Stockholm County Council, CAP Research Centre, Stockholm, Sweden
- Development and Neurodiversity Lab (DIVE), Department of Psychology, Uppsala University, Uppsala, Sweden
- The Swedish Collegium for Advanced Study (SCAS), Uppsala, Sweden
| | - Emily J H Jones
- Center for Brain and Cognitive Development, Birkbeck, University of London, London, UK
| | - Amy Goodwin
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Karin Brocki
- Department of Psychology, Uppsala University, Box 1225, 751 42, Uppsala, Sweden
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Radhoe TA, Agelink van Rentergem JA, Torenvliet C, Groenman AP, van der Putten WJ, Geurts HM. Finding Similarities in Differences Between Autistic Adults: Two Replicated Subgroups. J Autism Dev Disord 2024; 54:3449-3466. [PMID: 37438586 PMCID: PMC11362251 DOI: 10.1007/s10803-023-06042-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/05/2023] [Indexed: 07/14/2023]
Abstract
Autism is heterogeneous, which complicates providing tailored support and future prospects. We aim to identify subgroups in autistic adults with average to high intelligence, to clarify if certain subgroups might need support. We included 14 questionnaire variables related to aging and/or autism (e.g., demographic, psychological, and lifestyle). Community detection analysis was used for subgroup identification in an original sample of 114 autistic adults with an adulthood diagnosis (autism) and 58 non-autistic adults as comparison group (COMP), and a replication sample (NAutism = 261; NCOMP = 287), both aged 30-89 years. Next, we identified subgroups and assessed external validity (for cognitive and psychological difficulties, and quality of life [QoL]) in the autism samples. To test specificity, we repeated the analysis after adding 123 adults with ADHD, aged 30-80 years. As expected, the autism and COMP groups formed distinct subgroups. Among autistic adults, we identified three subgroups of which two were replicated. One of these subgroups seemed most vulnerable on the cluster variables; this subgroup also reported the most cognitive and psychological difficulties, and lowest QoL. Adding the ADHD group did not alter results. Within autistic adults, one subgroup could especially benefit from support and specialized care, although this must be tested in future studies.
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Affiliation(s)
- Tulsi A Radhoe
- Brain & Cognition, Department of Psychology, Dutch Autism & ADHD Research Center (d'Arc), University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 WS, Amsterdam, The Netherlands.
| | - Joost A Agelink van Rentergem
- Brain & Cognition, Department of Psychology, Dutch Autism & ADHD Research Center (d'Arc), University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 WS, Amsterdam, The Netherlands
| | - Carolien Torenvliet
- Brain & Cognition, Department of Psychology, Dutch Autism & ADHD Research Center (d'Arc), University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 WS, Amsterdam, The Netherlands
| | - Annabeth P Groenman
- Brain & Cognition, Department of Psychology, Dutch Autism & ADHD Research Center (d'Arc), University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 WS, Amsterdam, The Netherlands
- Research Institute for Child Development and Education, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 WS, Amsterdam, The Netherlands
| | - Wikke J van der Putten
- Brain & Cognition, Department of Psychology, Dutch Autism & ADHD Research Center (d'Arc), University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 WS, Amsterdam, The Netherlands
- Leo Kannerhuis (Youz/Parnassiagroep), Overschiestraat 57, 1062 HN, Amsterdam, The Netherlands
| | - Hilde M Geurts
- Brain & Cognition, Department of Psychology, Dutch Autism & ADHD Research Center (d'Arc), University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 WS, Amsterdam, The Netherlands
- Leo Kannerhuis (Youz/Parnassiagroep), Overschiestraat 57, 1062 HN, Amsterdam, The Netherlands
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Norman LJ, Sudre G, Price J, Shaw P. Subcortico-Cortical Dysconnectivity in ADHD: A Voxel-Wise Mega-Analysis Across Multiple Cohorts. Am J Psychiatry 2024; 181:553-562. [PMID: 38476041 PMCID: PMC11486346 DOI: 10.1176/appi.ajp.20230026] [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] [Indexed: 03/14/2024]
Abstract
OBJECTIVE A large body of functional MRI research has examined a potential role for subcortico-cortical loops in the pathogenesis of attention deficit hyperactivity disorder (ADHD), but has produced inconsistent findings. The authors performed a mega-analysis of six neuroimaging data sets to examine associations between ADHD diagnosis and traits and subcortico-cortical connectivity. METHODS Group differences were examined in the functional connectivity of four subcortical seeds in 1,696 youths with ADHD diagnoses (66.39% males; mean age, 10.83 years [SD=2.17]) and 6,737 unaffected control subjects (47.05% males; mean age, 10.33 years [SD=1.30]). The authors examined associations between functional connectivity and ADHD traits (total N=9,890; 50.3% males; mean age, 10.77 years [SD=1.96]). Sensitivity analyses were used to examine specificity relative to commonly comorbid internalizing and non-ADHD externalizing problems. The authors further examined results within motion-matched subsamples, and after adjusting for estimated intelligence. RESULTS In the group comparison, youths with ADHD showed greater connectivity between striatal seeds and temporal, fronto-insular, and supplementary motor regions, as well as between the amygdala and dorsal anterior cingulate cortex, compared with control subjects. Similar findings emerged when ADHD traits were considered and when alternative seed definitions were adopted. Dominant associations centered on the connectivity of the caudate bilaterally. Findings were not driven by in-scanner motion and were not shared with commonly comorbid internalizing and externalizing problems. Effect sizes were small (largest peak d, 0.15). CONCLUSIONS The findings from this large-scale mega-analysis support established links with subcortico-cortical circuits, which were robust to potential confounders. However, effect sizes were small, and it seems likely that resting-state subcortico-cortical connectivity can capture only a fraction of the complex pathophysiology of ADHD.
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Affiliation(s)
- Luke J. Norman
- Office of the Clinical Director, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892
| | - Gustavo Sudre
- Section on Neurobehavioral and Clinical Research, Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892
| | - Jolie Price
- Section on Neurobehavioral and Clinical Research, Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892
| | - Philip Shaw
- Office of the Clinical Director, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892
- Section on Neurobehavioral and Clinical Research, Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892
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Ojha A, Jones NP, Henry T, Versace A, Gnagy EM, Joseph HM, Molina BSG, Ladouceur CD. Altered Lateral Prefrontal Cortex Functioning During Emotional Interference Resistance Is Associated With Affect Lability in Adults With Persisting Symptoms of Attention-Deficit/Hyperactivity Disorder From Childhood. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024; 9:588-596. [PMID: 38378127 PMCID: PMC11369975 DOI: 10.1016/j.bpsc.2024.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 01/09/2024] [Accepted: 02/12/2024] [Indexed: 02/22/2024]
Abstract
BACKGROUND Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder characterized by inattention and/or impulsivity/hyperactivity. ADHD, especially when persisting into adulthood, often includes emotional dysregulation, such as affect lability; however, the neural correlates of emotionality in adults with heterogeneous ADHD symptom persistence remain unclear. METHODS The present study sought to determine shared and distinct functional neuroanatomical profiles of neural circuitry during emotional interference resistance using the emotional face n-back task in adult participants with persisting (n = 47), desisting (n = 93), or no (n = 42) childhood ADHD symptoms while undergoing functional magnetic resonance imaging. RESULTS Participants without any lifetime ADHD diagnosis performed significantly better (faster and more accurately) than participants with ADHD diagnoses on trials with high cognitive loads (2-back) that included task-irrelevant emotional distractors, tapping into executive functioning and emotion regulatory processes. In participants with persisting ADHD symptoms, more severe emotional symptoms were related to worse task performance. Heightened dorsolateral and ventrolateral prefrontal cortex activation was associated with more accurate and faster performance on 2-back emotional faces trials, respectively. Reduced activation was associated with greater affect lability in adults with persisting ADHD, and dorsolateral prefrontal cortex activation mediated the relationship between affect lability and task accuracy. CONCLUSIONS These findings suggest that alterations in dorsolateral prefrontal cortex function associated with greater interference in cognitive processes from emotion could represent a marker of risk for problems with emotional dysregulation in individuals with persisting ADHD and thus represent a potential therapeutic target for those with greater emotional symptoms of ADHD.
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Affiliation(s)
- Amar Ojha
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, Pennsylvania; Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, Pennsylvania; Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Neil P Jones
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Teague Henry
- Department of Psychology, University of Virginia, Charlottesville, Virginia; School of Data Science, University of Virginia, Charlottesville, Virginia
| | - Amelia Versace
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Elizabeth M Gnagy
- Department of Psychology, Florida International University, Miami, Florida
| | - Heather M Joseph
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Brooke S G Molina
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Cecile D Ladouceur
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, Pennsylvania; Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, Pennsylvania; Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania.
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7
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Figuracion MT, Kozlowski MB, Macknyk KS, Heise MB, Pieper SM, Alperin BR, Morton HE, Nigg JT, Karalunas SL. The Relationship Between Emotion Dysregulation and Error Monitoring in Adolescents with ADHD. Res Child Adolesc Psychopathol 2024; 52:605-620. [PMID: 37843650 DOI: 10.1007/s10802-023-01127-z] [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] [Accepted: 09/12/2023] [Indexed: 10/17/2023]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is emblematic of the limitations of existing diagnostic categories. One potential solution, consistent with the Research Domain Criteria (RDoC) initiative, is to interrogate psychological mechanisms at the behavioral and physiological level together to try and identify meaningful subgroups within existing categories. Such approaches provide a way to revise diagnostic boundaries and clarify individual variation in mechanisms. Here, we illustrate this approach to help resolve heterogeneity in ADHD using a combination of behaviorally-rated temperament measures from the Early Adolescent Temperament Questionnaire; cognitive performance on three difference conditions of an emotional go/no-go task; and electroencephalogram (EEG)-measured variation in multiple stages of error processing, including the error-related negativity (ERN) and positivity (Pe). In a large (N = 342), well-characterized sample of adolescents with ADHD, latent profile analysis identified two ADHD temperament subgroups: 1) emotionally regulated and 2) emotionally dysregulated (with high negative affect). Cognitive and EEG assessment in a subset of 272 adolescents (nADHD = 151) found that the emotionally dysregulated group showed distinct patterns of change in early neural response to errors (ERN) across emotional task conditions as compared to emotionally-regulated ADHD adolescents and typically-developing controls. Both ADHD groups showed blunted later response to errors (Pe) that was stable across emotional task conditions. Overall, neural response patterns identified important differences in how trait and state emotion interact to affect cognitive processing. Results highlight important temperament variation within ADHD that helps clarify its relationship to the ERN, one of the most prominent putative neural biomarkers for psychopathology.
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Affiliation(s)
| | - Michael B Kozlowski
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Katelyn S Macknyk
- Department of Psychological Sciences, Purdue University, West Lafayette, IN, USA
| | - Madelyn B Heise
- Department of Psychological Sciences, Purdue University, West Lafayette, IN, USA
| | - Sarah M Pieper
- Department of Psychological Sciences, Purdue University, West Lafayette, IN, USA
| | - Brittany R Alperin
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Hannah E Morton
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Joel T Nigg
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Sarah L Karalunas
- Department of Psychological Sciences, Purdue University, West Lafayette, IN, USA
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Carlson GA, Althoff RR, Singh MK. Future Directions: The Phenomenology of Irritable Mood and Outbursts: Hang Together or Hang Separately 1. JOURNAL OF CLINICAL CHILD AND ADOLESCENT PSYCHOLOGY : THE OFFICIAL JOURNAL FOR THE SOCIETY OF CLINICAL CHILD AND ADOLESCENT PSYCHOLOGY, AMERICAN PSYCHOLOGICAL ASSOCIATION, DIVISION 53 2024; 53:309-327. [PMID: 38588602 DOI: 10.1080/15374416.2024.2332999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/10/2024]
Abstract
Recognition of the importance of irritable mood and outbursts has been increasing over the past several decades. This "Future Directions" aims to develop a set of recommendations for future research emphasizing that irritable mood and outbursts "hang together," but have important distinctions and thus also need to "hang separately." Outbursts that are the outcome of irritable mood may be quite different from outbursts that are the trigger or driving force that make youth and his/her environment miserable. What, then, is the relation between irritable mood and outbursts? As the field currently stands, we not only cannot answer this question, but we may also lack the tools to effectively do so. Here, we will propose recommendations for understanding the phenomenology of irritable mood and outbursts so that more directed and clinically useful assessment tools can be designed. We discuss the transdiagnostic and treatment implications that relate to improvements in measurement. We describe the need to do more than repurpose our current assessment tools, specifically interviews and rating scales, which were designed for different purposes. The future directions of the study and treatment of irritable mood and outbursts will require, among others, using universally accepted nomenclature, supporting the development of tools to measure the characteristics of each irritable mood and outbursts, understanding the effects of question order, informant, development and longitudinal course, and studying the ways in which outbursts and irritable mood respond to treatment.
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Affiliation(s)
- Gabrielle A Carlson
- Psychiatry and Pediatrics, Renaissance School of Medicine at Stony Brook University
| | - Robert R Althoff
- Psychiatry, Pediatrics, & Psychological Science, University of Vermont
| | - Manpreet Kaur Singh
- Professor of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine
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9
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Arnett AB, Guiney H, Bakir-Demir T, Trudgen A, Schierding W, Reid V, O'Sullivan J, Gluckman P, Reese E, Poulton R. Resting EEG correlates of neurodevelopment in a socioeconomically and linguistically diverse sample of toddlers: Wave 1 of the Kia Tīmata Pai best start New Zealand study. Dev Cogn Neurosci 2024; 65:101336. [PMID: 38157733 PMCID: PMC10790011 DOI: 10.1016/j.dcn.2023.101336] [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: 07/19/2023] [Revised: 12/20/2023] [Accepted: 12/22/2023] [Indexed: 01/03/2024] Open
Abstract
Development of communication and self-regulation skills is fundamental to psychosocial maturation in childhood. The Kia Tīmata Pai Best Start (KTP) longitudinal study aims to promote these skills through interventions delivered at early childcare centers across New Zealand. In addition to evaluating effects of the interventions on behavioral and cognitive outcomes, the study utilizes electroencephalography (EEG) to characterize cortical development in a subsample of participating children. Here, we present results of the baseline resting EEG assessment with 193 children aged 15 to 33 months. We identified EEG correlates of individual differences in demographics, communication abilities, and temperament. We obtained communication and behavior ratings from multiple informants, and we applied contemporary analytic methods to the EEG data. Periodic spectral power adjusted for aperiodic activity was most closely associated with demographic, language, and behavioral measures. As in previous studies, gamma power was positively associated with verbal language. Alpha power was positively associated with effortful control. Nonverbal and verbal language measures showed distinct associations with EEG indices, as did the three temperament domains. Our results identified a number of candidate EEG measurements for use as longitudinal markers of optimal cortical development and response to interventions in the KTP cohort.
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Affiliation(s)
- Anne B Arnett
- Developmental Medicine, Boston Children's Hospital, Boston, MA, USA; Pediatrics, Harvard Medical School, Cambridge, MA, USA.
| | - Hayley Guiney
- Department of Psychology, University of Otago, Dunedin, New Zealand
| | | | - Anita Trudgen
- Liggins Institute, University of Auckland, Auckland, New Zealand
| | - William Schierding
- Liggins Institute, University of Auckland, Auckland, New Zealand; Department of Ophthalmology, University of Auckland, Auckland, New Zealand
| | - Vincent Reid
- School of Psychology, University of Waikato, Hamilton, New Zealand
| | | | - Peter Gluckman
- Liggins Institute, University of Auckland, Auckland, New Zealand.
| | - Elaine Reese
- Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Richie Poulton
- Department of Psychology, University of Otago, Dunedin, New Zealand
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10
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Morris SSJ, Timmons A, Musser ED. An Individualized, Data-Driven Biological Approach to Attention-Deficit/Hyperactivity Disorder (ADHD) Heterogeneity. Res Child Adolesc Psychopathol 2023; 51:1565-1579. [PMID: 37542616 DOI: 10.1007/s10802-023-01104-6] [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] [Accepted: 07/18/2023] [Indexed: 08/07/2023]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is the most commonly diagnosed mental health disorder in childhood, however, there is well-established heterogeneity in both the presentation of ADHD symptoms and secondary characteristics across the literature. Existing Diagnostic and Statistical Manual of Mental Disorders (DSM-5) nosology has been ineffective in explaining such heterogeneity in terms of both pathophysiology and clinical trajectories. The current study investigated ADHD heterogeneity via a biologically-based, data-driven approach (k-Means algorithm). Specifically, unique biological profiles (derived from patterns of parasympathetic and sympathetic functioning) were identified and utilized as predictors of clinical presentations. Two hundred eighty-nine participants (167 youth with ADHD), ages 5 to 13 years, completed an emotion-based task while indexes of parasympathetic (i.e., respiratory sinus arrhythmia [RSA]) and sympathetic (i.e., electrodermal activity [EDA]) activity were obtained. Overall, results suggest that three distinct biological profiles among youth with ADHD are evident, with biological profiles differing in regulation and arousal levels during emotionally evocative contexts: (Profile 1) underregulated, hyperaroused (negative contexts only), (Profile 2) typically regulated, underaroused, and (Profile 3) overregulated (positive contexts only), hyperaroused. Results are supported by several dopaminergic- and reward-based theories, integrating differing concepts across the literature, and adds biological support for existing models. Behaviorally, results may translate into differing clinical presentations, however, further work is needed. In general, youth with ADHD are heterogenous in autonomic functioning, which could have implications for synthesizing across differing theories within the literature, predicting clinical presentations, and developing targeted treatments.
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Affiliation(s)
| | - Adela Timmons
- Department of Psychology, University of Texas at Austin, Austin, USA
| | - Erica D Musser
- Department of Psychology, Florida International University, Miami, USA
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11
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Suk JW, Blair RJR, Vaughan B, Lerdahl A, Garvey WF, Edwards R, Leibenluft E, Hwang S. Mediating effect of amygdala activity on response to fear vs. happiness in youth with significant levels of irritability and disruptive mood and behavior disorders. Front Behav Neurosci 2023; 17:1204574. [PMID: 37901308 PMCID: PMC10602729 DOI: 10.3389/fnbeh.2023.1204574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 09/12/2023] [Indexed: 10/31/2023] Open
Abstract
Introduction Irritability, characterized by a tendency to exhibit increased anger, is a common clinical problem in youth. Irritability is a significant clinical issue in youth with various psychiatric diagnoses, especially disruptive behavior, and mood disorders (Attention-Deficit/Hyperactivity Disorder, Oppositional Defiant Disorder, Conduct Disorder, and Disruptive Mood Dysregulation Disorder). Although there have been previous studies focusing on functional alteration in the amygdala related to irritability, there is no comprehensive model between emotional, neuronal, and behavioral characteristics. Methods Using an functional magnetic resonance imaging (fMRI) procedure, we investigated the relationships between behavioral irritability, selective impairments in processing facial emotions and the amygdala neural response in youth with increased irritability. Fifty-nine youth with disruptive mood and behavior disorder completed a facial expression processing task with an event-related fMRI paradigm. The severity of irritability was evaluated using the Affective Reactivity Index. Results In the result of behavioral data, irritability, and reaction time (RT) differences between interpreting negative (fear) and positive (happiness) facial expressions were positively correlated. In the fMRI result, youth showed higher activation in the right cingulate gyrus, bilateral cerebellum, right amygdala, right precuneus, right superior frontal gyrus, right middle occipital gyrus, and middle temporal gyrus, during the happiness condition vs. fear condition. No brain region exhibited greater activation in the fear than in the happiness conditions. In the result of the mediator analysis, increased irritability was associated with a longer RT toward positive vs. negative facial expressions. Irritability was also positively associated with the difference in amygdala blood oxygen level-dependent responses between the two emotional conditions (happiness > fear). This difference in amygdala activity mediated the interaction between irritability and the RT difference between negative and positive facial expressions. Discussion We suggest that impairment in the implicit processing of facial emotional expressions with different valences causes distinct patterns of amygdala response, which correlate with the level of irritability. These results broaden our understanding of the biological mechanism of irritability at the neural level and provide information for the future direction of the study.
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Affiliation(s)
- Ji-Woo Suk
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, NE, United States
- Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon, Republic of Korea
| | - Robert J. R. Blair
- Child and Adolescent Mental Health Centre, Mental Health Services, Capital Region of Denmark, Emotion and Development Branch, Copenhagen, Denmark
| | - Brigette Vaughan
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, NE, United States
| | - Arica Lerdahl
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, NE, United States
| | - William F. Garvey
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, NE, United States
| | - Ryan Edwards
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, NE, United States
| | - Ellen Leibenluft
- National Institute of Mental Health, Bethesda, MD, United States
| | - Soonjo Hwang
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, NE, United States
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12
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Wang Q, Zhao C, Qiu J, Lu W. Two neurosubtypes of ADHD different from the clinical phenotypes. Psychiatry Res 2023; 328:115453. [PMID: 37660582 DOI: 10.1016/j.psychres.2023.115453] [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: 07/11/2023] [Revised: 08/24/2023] [Accepted: 08/27/2023] [Indexed: 09/05/2023]
Abstract
Clinical and etiological variability of attention deficit hyperactivity disorder (ADHD) presents an obstacle to understand the disorder. The aim of this study was to disentangle the heterogeneity of ADHD using neuroimaging and a semi-supervised machine learning algorithm. We collected brain structural and functional magnetic resonance imaging (MRI) data and clinical profiles of 183 children with ADHD and 396 neurotypical controls from 7 independent sites. We also used an external validation set with 750 subjects. We adopted a semi-supervised clustering method to subtype ADHD by regional volumetric measures of gray matter, white matter, and fractional amplitude of low frequency fluctuation (fALFF). In addition, split sample test, leave-one-site-out test and external validation were applied to evaluate the reproducibility and stability of ADHD subtypes. Two stable and reproducible neurosubtypes of ADHD were disclosed, which were proved by the split-sample test and leave-one-site-out validation. The structural and functional patterns of ADHD subtypes were also stable in the external validation set. The current two neurosubtypes differed in clinical manifestations and volumetric gray matter, white matter volume and fALFF patterns. The current neurosubtypes of ADHD which were different from clinical phenotypes could facilitate understanding the underlying neuropathological and neurobiological mechanism of the disorder.
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Affiliation(s)
- Qi Wang
- Department of Radiology, the Second Affiliated Hospital of Shandong First Medical University, Taian, 271000, China
| | - Chuanhua Zhao
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271000, China
| | - Jianfeng Qiu
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271000, China
| | - Weizhao Lu
- Department of Radiology, the Second Affiliated Hospital of Shandong First Medical University, Taian, 271000, China.
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13
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Feng A, Feng Y, Zhi D, Jiang R, Fu Z, Xu M, Zhao M, Yu S, Stevens M, Sun L, Calhoun V, Sui J. Functional Imaging Derived ADHD Biotypes Based on Deep Clustering May Guide Personalized Medication Therapy. RESEARCH SQUARE 2023:rs.3.rs-3272441. [PMID: 37790426 PMCID: PMC10543279 DOI: 10.21203/rs.3.rs-3272441/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Attention deficit hyperactivity disorder (ADHD) is one prevalent neurodevelopmental disorder with childhood onset, however, there is no clear correspondence established between clinical ADHD subtypes and primary medications. Identifying objective and reliable neuroimaging markers for categorizing ADHD biotypes may lead to more individualized, biotype-guided treatment. Here we proposed graph convolutional network plus deep clustering for ADHD biotype detection using functional network connectivity (FNC), resulting in two biotypes based on 1069 ADHD patients selected from Adolescent Brain and Cognitive Development (ABCD) study, which were well replicated on independent ADHD adolescents undergoing longitudinal medication treatment (n=130). Interestingly, in addition to differences in cognitive performance and hyperactivity/impulsivity symptoms, biotype 1 treated with methylphenidate demonstrated significantly better recovery than biotype 2 treated with atomoxetine (p<0.05, FDR corrected). This imaging-driven, biotype-guided approach holds promise for facilitating personalized treatment of ADHD, exploring possible boundaries through innovative deep learning algorithms aimed at improving medication treatment effectiveness.
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Affiliation(s)
- Aichen Feng
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China, 100190
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China, 100049
| | - Yuan Feng
- Peking University Sixth Hospital/Institute of Mental Health, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China, 100191
| | - Dongmei Zhi
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China, 100875
| | - Rongtao Jiang
- Department of Radiology and Biomedical imaging, Yale University, New Haven, Connecticut, USA
| | - Zening Fu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Emory University and Georgia State University, Atlanta, Georgia, United States, 30303
| | - Ming Xu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China, 100190
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China, 100049
| | - Min Zhao
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China, 100190
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China, 100049
| | - Shan Yu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China, 100190
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China, 100049
| | - Michael Stevens
- Department of Psychiatry, Olin Neuropsychiatry Research Center, Institute of Living, Hartford Healthcare Corporation, Hartford, CT, United States
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Li Sun
- Peking University Sixth Hospital/Institute of Mental Health, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China, 100191
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Emory University and Georgia State University, Atlanta, Georgia, United States, 30303
| | - Jing Sui
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China, 100875
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Emory University and Georgia State University, Atlanta, Georgia, United States, 30303
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14
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Yu G, Liu Z, Wu X, Becker B, Zhang K, Fan H, Peng S, Kuang N, Kang J, Dong G, Zhao XM, Schumann G, Feng J, Sahakian BJ, Robbins TW, Palaniyappan L, Zhang J. Common and disorder-specific cortical thickness alterations in internalizing, externalizing and thought disorders during early adolescence: an Adolescent Brain and Cognitive Development study. J Psychiatry Neurosci 2023; 48:E345-E356. [PMID: 37673436 PMCID: PMC10495167 DOI: 10.1503/jpn.220202] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 02/13/2023] [Accepted: 05/17/2023] [Indexed: 09/08/2023] Open
Abstract
BACKGROUND A growing body of neuroimaging studies has reported common neural abnormalities among mental disorders in adults. However, it is unclear whether the distinct disorder-specific mechanisms operate during adolescence despite the overlap among disorders. METHODS We studied a large cohort of more than 11 000 preadolescent (age 9-10 yr) children from the Adolescent Brain and Cognitive Development cohort. We adopted a regrouping approach to compare cortical thickness (CT) alterations and longitudinal changes between healthy controls (n = 4041) and externalizing (n = 1182), internalizing (n = 1959) and thought disorder (n = 347) groups. Genome-wide association study (GWAS) was performed on regional CT across 4468 unrelated European youth. RESULTS Youth with externalizing or internalizing disorders exhibited increased regional CT compared with controls. Externalizing (p = 8 × 10-4, Cohen d = 0.10) and internalizing disorders (p = 2 × 10-3, Cohen d = 0.08) shared thicker CT in the left pars opercularis. The somatosensory and the primary auditory cortex were uniquely affected in externalizing disorders, whereas the primary motor cortex and higher-order visual association areas were uniquely affected in internalizing disorders. Only youth with externalizing disorders showed decelerated cortical thinning from age 10-12 years. The GWAS found 59 genome-wide significant associated genetic variants across these regions. Cortical thickness in common regions was associated with glutamatergic neurons, while internalizing-specific regional CT was associated with astrocytes, oligodendrocyte progenitor cells and GABAergic neurons. LIMITATIONS The sample size of the GWAS was relatively small. CONCLUSION Our study provides strong evidence for the presence of specificity in CT, developmental trajectories and underlying genetic underpinnings among externalizing and internalizing disorders during early adolescence. Our results support the neurobiological validity of the regrouping approach that could supplement the use of a dimensional approach in future clinical practice.
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Affiliation(s)
- Gechang Yu
- From the Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China (Yu, Wu, Fan, Peng, Kuang, Kang, Dong, Zhao, Feng, Sahakian, Robbins, Zhang); the Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, China (Yu, Wu, Fan, Peng, Kuang, Feng, Zhang); the Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Mass., USA (Liu); the Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Mass., USA (Liu); the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass., USA (Liu); the Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China (Becker); the School of Computer Science and Technology, East China Normal University, Shanghai, China (Zhang); the Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China (Kang); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China (Dong, Zhao); the Zhangjiang Fudan International Innovation Center, Shanghai, China (Zhao); the PONS Centre Shanghai, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Schumann); the PONS Centre Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany (Feng); the Shanghai Center for Mathematical Sciences, Shanghai, China (Feng); the Department of Computer Science, University of Warwick, Coventry, UK (Feng); the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China (Feng); the Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China (Feng); the Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK (Sahakian); the Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK (Robbins); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Que., Canada (Palaniyappan); the Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan); the Robarts Research Institute, Western University, London, Ont., Canada (Palaniyappan); the Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan)
| | - Zhaowen Liu
- From the Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China (Yu, Wu, Fan, Peng, Kuang, Kang, Dong, Zhao, Feng, Sahakian, Robbins, Zhang); the Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, China (Yu, Wu, Fan, Peng, Kuang, Feng, Zhang); the Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Mass., USA (Liu); the Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Mass., USA (Liu); the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass., USA (Liu); the Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China (Becker); the School of Computer Science and Technology, East China Normal University, Shanghai, China (Zhang); the Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China (Kang); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China (Dong, Zhao); the Zhangjiang Fudan International Innovation Center, Shanghai, China (Zhao); the PONS Centre Shanghai, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Schumann); the PONS Centre Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany (Feng); the Shanghai Center for Mathematical Sciences, Shanghai, China (Feng); the Department of Computer Science, University of Warwick, Coventry, UK (Feng); the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China (Feng); the Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China (Feng); the Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK (Sahakian); the Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK (Robbins); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Que., Canada (Palaniyappan); the Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan); the Robarts Research Institute, Western University, London, Ont., Canada (Palaniyappan); the Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan)
| | - Xinran Wu
- From the Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China (Yu, Wu, Fan, Peng, Kuang, Kang, Dong, Zhao, Feng, Sahakian, Robbins, Zhang); the Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, China (Yu, Wu, Fan, Peng, Kuang, Feng, Zhang); the Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Mass., USA (Liu); the Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Mass., USA (Liu); the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass., USA (Liu); the Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China (Becker); the School of Computer Science and Technology, East China Normal University, Shanghai, China (Zhang); the Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China (Kang); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China (Dong, Zhao); the Zhangjiang Fudan International Innovation Center, Shanghai, China (Zhao); the PONS Centre Shanghai, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Schumann); the PONS Centre Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany (Feng); the Shanghai Center for Mathematical Sciences, Shanghai, China (Feng); the Department of Computer Science, University of Warwick, Coventry, UK (Feng); the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China (Feng); the Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China (Feng); the Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK (Sahakian); the Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK (Robbins); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Que., Canada (Palaniyappan); the Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan); the Robarts Research Institute, Western University, London, Ont., Canada (Palaniyappan); the Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan)
| | - Benjamin Becker
- From the Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China (Yu, Wu, Fan, Peng, Kuang, Kang, Dong, Zhao, Feng, Sahakian, Robbins, Zhang); the Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, China (Yu, Wu, Fan, Peng, Kuang, Feng, Zhang); the Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Mass., USA (Liu); the Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Mass., USA (Liu); the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass., USA (Liu); the Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China (Becker); the School of Computer Science and Technology, East China Normal University, Shanghai, China (Zhang); the Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China (Kang); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China (Dong, Zhao); the Zhangjiang Fudan International Innovation Center, Shanghai, China (Zhao); the PONS Centre Shanghai, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Schumann); the PONS Centre Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany (Feng); the Shanghai Center for Mathematical Sciences, Shanghai, China (Feng); the Department of Computer Science, University of Warwick, Coventry, UK (Feng); the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China (Feng); the Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China (Feng); the Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK (Sahakian); the Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK (Robbins); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Que., Canada (Palaniyappan); the Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan); the Robarts Research Institute, Western University, London, Ont., Canada (Palaniyappan); the Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan)
| | - Kai Zhang
- From the Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China (Yu, Wu, Fan, Peng, Kuang, Kang, Dong, Zhao, Feng, Sahakian, Robbins, Zhang); the Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, China (Yu, Wu, Fan, Peng, Kuang, Feng, Zhang); the Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Mass., USA (Liu); the Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Mass., USA (Liu); the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass., USA (Liu); the Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China (Becker); the School of Computer Science and Technology, East China Normal University, Shanghai, China (Zhang); the Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China (Kang); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China (Dong, Zhao); the Zhangjiang Fudan International Innovation Center, Shanghai, China (Zhao); the PONS Centre Shanghai, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Schumann); the PONS Centre Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany (Feng); the Shanghai Center for Mathematical Sciences, Shanghai, China (Feng); the Department of Computer Science, University of Warwick, Coventry, UK (Feng); the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China (Feng); the Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China (Feng); the Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK (Sahakian); the Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK (Robbins); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Que., Canada (Palaniyappan); the Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan); the Robarts Research Institute, Western University, London, Ont., Canada (Palaniyappan); the Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan)
| | - Huaxin Fan
- From the Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China (Yu, Wu, Fan, Peng, Kuang, Kang, Dong, Zhao, Feng, Sahakian, Robbins, Zhang); the Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, China (Yu, Wu, Fan, Peng, Kuang, Feng, Zhang); the Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Mass., USA (Liu); the Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Mass., USA (Liu); the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass., USA (Liu); the Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China (Becker); the School of Computer Science and Technology, East China Normal University, Shanghai, China (Zhang); the Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China (Kang); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China (Dong, Zhao); the Zhangjiang Fudan International Innovation Center, Shanghai, China (Zhao); the PONS Centre Shanghai, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Schumann); the PONS Centre Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany (Feng); the Shanghai Center for Mathematical Sciences, Shanghai, China (Feng); the Department of Computer Science, University of Warwick, Coventry, UK (Feng); the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China (Feng); the Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China (Feng); the Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK (Sahakian); the Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK (Robbins); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Que., Canada (Palaniyappan); the Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan); the Robarts Research Institute, Western University, London, Ont., Canada (Palaniyappan); the Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan)
| | - Songjun Peng
- From the Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China (Yu, Wu, Fan, Peng, Kuang, Kang, Dong, Zhao, Feng, Sahakian, Robbins, Zhang); the Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, China (Yu, Wu, Fan, Peng, Kuang, Feng, Zhang); the Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Mass., USA (Liu); the Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Mass., USA (Liu); the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass., USA (Liu); the Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China (Becker); the School of Computer Science and Technology, East China Normal University, Shanghai, China (Zhang); the Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China (Kang); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China (Dong, Zhao); the Zhangjiang Fudan International Innovation Center, Shanghai, China (Zhao); the PONS Centre Shanghai, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Schumann); the PONS Centre Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany (Feng); the Shanghai Center for Mathematical Sciences, Shanghai, China (Feng); the Department of Computer Science, University of Warwick, Coventry, UK (Feng); the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China (Feng); the Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China (Feng); the Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK (Sahakian); the Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK (Robbins); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Que., Canada (Palaniyappan); the Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan); the Robarts Research Institute, Western University, London, Ont., Canada (Palaniyappan); the Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan)
| | - Nanyu Kuang
- From the Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China (Yu, Wu, Fan, Peng, Kuang, Kang, Dong, Zhao, Feng, Sahakian, Robbins, Zhang); the Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, China (Yu, Wu, Fan, Peng, Kuang, Feng, Zhang); the Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Mass., USA (Liu); the Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Mass., USA (Liu); the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass., USA (Liu); the Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China (Becker); the School of Computer Science and Technology, East China Normal University, Shanghai, China (Zhang); the Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China (Kang); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China (Dong, Zhao); the Zhangjiang Fudan International Innovation Center, Shanghai, China (Zhao); the PONS Centre Shanghai, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Schumann); the PONS Centre Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany (Feng); the Shanghai Center for Mathematical Sciences, Shanghai, China (Feng); the Department of Computer Science, University of Warwick, Coventry, UK (Feng); the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China (Feng); the Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China (Feng); the Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK (Sahakian); the Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK (Robbins); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Que., Canada (Palaniyappan); the Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan); the Robarts Research Institute, Western University, London, Ont., Canada (Palaniyappan); the Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan)
| | - Jujiao Kang
- From the Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China (Yu, Wu, Fan, Peng, Kuang, Kang, Dong, Zhao, Feng, Sahakian, Robbins, Zhang); the Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, China (Yu, Wu, Fan, Peng, Kuang, Feng, Zhang); the Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Mass., USA (Liu); the Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Mass., USA (Liu); the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass., USA (Liu); the Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China (Becker); the School of Computer Science and Technology, East China Normal University, Shanghai, China (Zhang); the Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China (Kang); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China (Dong, Zhao); the Zhangjiang Fudan International Innovation Center, Shanghai, China (Zhao); the PONS Centre Shanghai, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Schumann); the PONS Centre Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany (Feng); the Shanghai Center for Mathematical Sciences, Shanghai, China (Feng); the Department of Computer Science, University of Warwick, Coventry, UK (Feng); the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China (Feng); the Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China (Feng); the Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK (Sahakian); the Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK (Robbins); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Que., Canada (Palaniyappan); the Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan); the Robarts Research Institute, Western University, London, Ont., Canada (Palaniyappan); the Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan)
| | - Guiying Dong
- From the Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China (Yu, Wu, Fan, Peng, Kuang, Kang, Dong, Zhao, Feng, Sahakian, Robbins, Zhang); the Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, China (Yu, Wu, Fan, Peng, Kuang, Feng, Zhang); the Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Mass., USA (Liu); the Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Mass., USA (Liu); the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass., USA (Liu); the Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China (Becker); the School of Computer Science and Technology, East China Normal University, Shanghai, China (Zhang); the Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China (Kang); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China (Dong, Zhao); the Zhangjiang Fudan International Innovation Center, Shanghai, China (Zhao); the PONS Centre Shanghai, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Schumann); the PONS Centre Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany (Feng); the Shanghai Center for Mathematical Sciences, Shanghai, China (Feng); the Department of Computer Science, University of Warwick, Coventry, UK (Feng); the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China (Feng); the Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China (Feng); the Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK (Sahakian); the Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK (Robbins); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Que., Canada (Palaniyappan); the Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan); the Robarts Research Institute, Western University, London, Ont., Canada (Palaniyappan); the Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan)
| | - Xing-Ming Zhao
- From the Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China (Yu, Wu, Fan, Peng, Kuang, Kang, Dong, Zhao, Feng, Sahakian, Robbins, Zhang); the Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, China (Yu, Wu, Fan, Peng, Kuang, Feng, Zhang); the Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Mass., USA (Liu); the Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Mass., USA (Liu); the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass., USA (Liu); the Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China (Becker); the School of Computer Science and Technology, East China Normal University, Shanghai, China (Zhang); the Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China (Kang); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China (Dong, Zhao); the Zhangjiang Fudan International Innovation Center, Shanghai, China (Zhao); the PONS Centre Shanghai, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Schumann); the PONS Centre Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany (Feng); the Shanghai Center for Mathematical Sciences, Shanghai, China (Feng); the Department of Computer Science, University of Warwick, Coventry, UK (Feng); the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China (Feng); the Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China (Feng); the Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK (Sahakian); the Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK (Robbins); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Que., Canada (Palaniyappan); the Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan); the Robarts Research Institute, Western University, London, Ont., Canada (Palaniyappan); the Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan)
| | - Gunter Schumann
- From the Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China (Yu, Wu, Fan, Peng, Kuang, Kang, Dong, Zhao, Feng, Sahakian, Robbins, Zhang); the Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, China (Yu, Wu, Fan, Peng, Kuang, Feng, Zhang); the Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Mass., USA (Liu); the Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Mass., USA (Liu); the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass., USA (Liu); the Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China (Becker); the School of Computer Science and Technology, East China Normal University, Shanghai, China (Zhang); the Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China (Kang); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China (Dong, Zhao); the Zhangjiang Fudan International Innovation Center, Shanghai, China (Zhao); the PONS Centre Shanghai, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Schumann); the PONS Centre Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany (Feng); the Shanghai Center for Mathematical Sciences, Shanghai, China (Feng); the Department of Computer Science, University of Warwick, Coventry, UK (Feng); the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China (Feng); the Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China (Feng); the Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK (Sahakian); the Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK (Robbins); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Que., Canada (Palaniyappan); the Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan); the Robarts Research Institute, Western University, London, Ont., Canada (Palaniyappan); the Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan)
| | - Jianfeng Feng
- From the Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China (Yu, Wu, Fan, Peng, Kuang, Kang, Dong, Zhao, Feng, Sahakian, Robbins, Zhang); the Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, China (Yu, Wu, Fan, Peng, Kuang, Feng, Zhang); the Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Mass., USA (Liu); the Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Mass., USA (Liu); the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass., USA (Liu); the Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China (Becker); the School of Computer Science and Technology, East China Normal University, Shanghai, China (Zhang); the Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China (Kang); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China (Dong, Zhao); the Zhangjiang Fudan International Innovation Center, Shanghai, China (Zhao); the PONS Centre Shanghai, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Schumann); the PONS Centre Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany (Feng); the Shanghai Center for Mathematical Sciences, Shanghai, China (Feng); the Department of Computer Science, University of Warwick, Coventry, UK (Feng); the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China (Feng); the Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China (Feng); the Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK (Sahakian); the Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK (Robbins); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Que., Canada (Palaniyappan); the Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan); the Robarts Research Institute, Western University, London, Ont., Canada (Palaniyappan); the Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan)
| | - Barbara J Sahakian
- From the Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China (Yu, Wu, Fan, Peng, Kuang, Kang, Dong, Zhao, Feng, Sahakian, Robbins, Zhang); the Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, China (Yu, Wu, Fan, Peng, Kuang, Feng, Zhang); the Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Mass., USA (Liu); the Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Mass., USA (Liu); the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass., USA (Liu); the Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China (Becker); the School of Computer Science and Technology, East China Normal University, Shanghai, China (Zhang); the Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China (Kang); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China (Dong, Zhao); the Zhangjiang Fudan International Innovation Center, Shanghai, China (Zhao); the PONS Centre Shanghai, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Schumann); the PONS Centre Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany (Feng); the Shanghai Center for Mathematical Sciences, Shanghai, China (Feng); the Department of Computer Science, University of Warwick, Coventry, UK (Feng); the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China (Feng); the Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China (Feng); the Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK (Sahakian); the Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK (Robbins); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Que., Canada (Palaniyappan); the Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan); the Robarts Research Institute, Western University, London, Ont., Canada (Palaniyappan); the Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan)
| | - Trevor W Robbins
- From the Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China (Yu, Wu, Fan, Peng, Kuang, Kang, Dong, Zhao, Feng, Sahakian, Robbins, Zhang); the Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, China (Yu, Wu, Fan, Peng, Kuang, Feng, Zhang); the Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Mass., USA (Liu); the Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Mass., USA (Liu); the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass., USA (Liu); the Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China (Becker); the School of Computer Science and Technology, East China Normal University, Shanghai, China (Zhang); the Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China (Kang); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China (Dong, Zhao); the Zhangjiang Fudan International Innovation Center, Shanghai, China (Zhao); the PONS Centre Shanghai, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Schumann); the PONS Centre Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany (Feng); the Shanghai Center for Mathematical Sciences, Shanghai, China (Feng); the Department of Computer Science, University of Warwick, Coventry, UK (Feng); the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China (Feng); the Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China (Feng); the Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK (Sahakian); the Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK (Robbins); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Que., Canada (Palaniyappan); the Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan); the Robarts Research Institute, Western University, London, Ont., Canada (Palaniyappan); the Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan)
| | - Lena Palaniyappan
- From the Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China (Yu, Wu, Fan, Peng, Kuang, Kang, Dong, Zhao, Feng, Sahakian, Robbins, Zhang); the Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, China (Yu, Wu, Fan, Peng, Kuang, Feng, Zhang); the Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Mass., USA (Liu); the Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Mass., USA (Liu); the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass., USA (Liu); the Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China (Becker); the School of Computer Science and Technology, East China Normal University, Shanghai, China (Zhang); the Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China (Kang); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China (Dong, Zhao); the Zhangjiang Fudan International Innovation Center, Shanghai, China (Zhao); the PONS Centre Shanghai, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Schumann); the PONS Centre Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany (Feng); the Shanghai Center for Mathematical Sciences, Shanghai, China (Feng); the Department of Computer Science, University of Warwick, Coventry, UK (Feng); the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China (Feng); the Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China (Feng); the Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK (Sahakian); the Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK (Robbins); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Que., Canada (Palaniyappan); the Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan); the Robarts Research Institute, Western University, London, Ont., Canada (Palaniyappan); the Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan)
| | - Jie Zhang
- From the Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China (Yu, Wu, Fan, Peng, Kuang, Kang, Dong, Zhao, Feng, Sahakian, Robbins, Zhang); the Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, China (Yu, Wu, Fan, Peng, Kuang, Feng, Zhang); the Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Mass., USA (Liu); the Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Mass., USA (Liu); the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass., USA (Liu); the Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China (Becker); the School of Computer Science and Technology, East China Normal University, Shanghai, China (Zhang); the Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China (Kang); the MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China (Dong, Zhao); the Zhangjiang Fudan International Innovation Center, Shanghai, China (Zhao); the PONS Centre Shanghai, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Schumann); the PONS Centre Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany (Feng); the Shanghai Center for Mathematical Sciences, Shanghai, China (Feng); the Department of Computer Science, University of Warwick, Coventry, UK (Feng); the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China (Feng); the Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China (Feng); the Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK (Sahakian); the Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK (Robbins); the Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Que., Canada (Palaniyappan); the Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan); the Robarts Research Institute, Western University, London, Ont., Canada (Palaniyappan); the Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ont., Canada (Palaniyappan)
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Wexler BE, Kish R. Using micro-cognition biomarkers of neurosystem dysfunction to redefine ADHD subtypes: A scalable digital path to diagnosis based on brain function. Psychiatry Res 2023; 326:115348. [PMID: 37494880 PMCID: PMC10517859 DOI: 10.1016/j.psychres.2023.115348] [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: 03/14/2023] [Revised: 07/14/2023] [Accepted: 07/16/2023] [Indexed: 07/28/2023]
Abstract
Symptom-based diagnosis does not align with underlying neruropathology, confounding new treatment development and treatment selection for individual patients. Using high precision micro-cognition biomarkers of neurosystem dysfunction acquired during digital neurotherapy (DNT), we characterized subgroups of ADHD children with different neuropathology. K-means clustering applied to 69 children 6-9 years old with ADHD using performance variables from a Go/NoGo test normalized against 58 typically developing (TD) children identified four subgroups that were validated and further characterized by micro-cognition biomarkers extracted from thousands of responses during the DNT. The clusters differed on emblematic features of ADHD. Cluster 4 showed poor response inhibition and inconsistent attention. Cluster 3 showed only poor response inhibition and the other two showed neither. Cluster 2 showed faster and more consistent responses, higher detection of simple targets and better working memory than TD children but marked performance decrements when required to track multiple targets or ignore distractors. Cluster 1 showed much greater ability recognizing members of abstract categories rather than natural categories that children learn through physical interaction with the environment while Cluster 4 was the opposite. Fine-grained, low-cost, noninvasive, and scalable digital micro-cognition biomarkers can identify patients with the same symptom-based diagnosis but differing neuropathology.
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Affiliation(s)
- Bruce E Wexler
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States; C8 Sciences, New Haven, CT, United States.
| | - Ryan Kish
- C8 Sciences, New Haven, CT, United States
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Brancati GE, Acierno D, Barbuti M, Elefante C, Gemignani S, Raia A, Perugi G. Revisiting stimulant use for emotional dysregulation in attention-deficit/hyperactivity disorder (ADHD). Expert Rev Neurother 2023; 23:981-994. [PMID: 37747111 DOI: 10.1080/14737175.2023.2263645] [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: 05/29/2023] [Accepted: 09/22/2023] [Indexed: 09/26/2023]
Abstract
INTRODUCTION Emotional dysregulation (ED) symptoms are present in a considerable portion of patients with attention-deficit/hyperactivity disorder (ADHD). In recent years, an increasing number of studies investigated the effects of stimulant medications on ED in patients with ADHD. AREAS COVERED A narrative review of the literature on stimulant treatment for ED is provided, including controlled and observational clinical studies conducted on pediatric and adult samples and neurobiological investigations. Positive effects of stimulants on irritability have been demonstrated in children. Comorbidity with disruptive behavior disorders (DBD) and disruptive mood dysregulation disorder does not prevent stimulant effectiveness. Methylphenidate has also been found to reduce temper problems, affective instability, and emotional over-reactivity in adults with ADHD, although with variable effect sizes. A variety of adverse emotional effects have been reported, especially at high doses and in special populations. However, several possible confounders of treatment-emergent ED have been highlighted. Finally, according to neuroimaging studies, stimulants may mitigate emotional processing anomalies associated with ADHD. EXPERT OPINION The findings are consistent with models including ED within the core features of ADHD. Stimulant treatment should be prioritized over antipsychotics in ADHD-DBD. It remains to be elucidated whether other medications may be more effective in specific populations with ADHD and/or ED.
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Affiliation(s)
- Giulio Emilio Brancati
- Psychiatry Unit 2, Department of Clinical and Experimental Medicine, University Hospital of Pisa, Pisa, Italy
| | - Donatella Acierno
- Psychiatry Unit 2, Department of Clinical and Experimental Medicine, University Hospital of Pisa, Pisa, Italy
| | - Margherita Barbuti
- Psychiatry Unit 2, Department of Clinical and Experimental Medicine, University Hospital of Pisa, Pisa, Italy
| | - Camilla Elefante
- Psychiatry Unit 2, Department of Clinical and Experimental Medicine, University Hospital of Pisa, Pisa, Italy
| | - Samuele Gemignani
- Psychiatry Unit 2, Department of Clinical and Experimental Medicine, University Hospital of Pisa, Pisa, Italy
| | - Accursio Raia
- Psychiatry Unit 2, Department of Clinical and Experimental Medicine, University Hospital of Pisa, Pisa, Italy
| | - Giulio Perugi
- Psychiatry Unit 2, Department of Clinical and Experimental Medicine, University Hospital of Pisa, Pisa, Italy
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Bunford N, Hámori G, Nemoda Z, Angyal N, Fiáth R, Sebők-Welker TÉ, Pászthy B, Ulbert I, Réthelyi JM. The domain-variant indirect association between electrophysiological response to reward and ADHD presentations is moderated by dopaminergic polymorphisms. Compr Psychiatry 2023; 124:152389. [PMID: 37104986 DOI: 10.1016/j.comppsych.2023.152389] [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: 11/09/2022] [Revised: 03/24/2023] [Accepted: 04/13/2023] [Indexed: 04/29/2023] Open
Abstract
BACKGROUND Understanding the etiopathogenesis of attention-deficit/hyperactivity disorder (ADHD) may necessitate decomposition of the heterogeneous clinical phenotype into more homogeneous intermediate phenotypes. Reinforcement sensitivity is a promising candidate, but the exact nature of the ADHD-reward relation - including how, for whom, and to which ADHD dimensions atypicalities in reward processing are relevant - is equivocal. METHODS Aims were to examine, in a carefully phenotyped sample of adolescents (N = 305; Mage = 15.30 years, SD = 1.07; 39.7% girls), whether functional dopaminergic polymorphisms implicated in both reward processing and ADHD (1) are differentially associated with event-related potentials (ERPs) of reward anticipation at distinct levels of ADHD risk (nno risk = 174, nat-risk = 131, ndiagnosed = 83); and (2) moderate the indirect effect of dispositional affectivity on the association between ERPs and ADHD domains. RESULTS In adolescents at-risk for or with ADHD, carrying a hypodopaminergic allele was associated with enhanced ERPs of attention allocation to cue and attenuated ERPs of anticipatory attention to feedback. No associations were observed in adolescents not at-risk for or without ADHD. Controlling for age and sex, both the negative indirect effect of positive affectivity (PA) on the association between ERPs and inattention and the positive indirect effect of PA on the association between ERPs and hyperactivity/impulsivity were supported only for those with high activity dopamine transporter (DAT) alleles. CONCLUSIONS Reward and affective processing are promising intermediate phenotypes relevant to disentangling ADHD developmental pathways. Consistent with developmental multifinality, through the successive effects of reward anticipation and positive affectivity, functional dopaminergic variants may confer protection against inattention or risk for hyperactivity/impulsivity.
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Affiliation(s)
- N Bunford
- Research Centre for Natural Sciences Institute of Cognitive Neuroscience and Psychology, Clinical and Developmental Neuropsychology Research Group, Magyar Tudósok körútja 2., H-1117 Budapest, Hungary.
| | - Gy Hámori
- Research Centre for Natural Sciences Institute of Cognitive Neuroscience and Psychology, Clinical and Developmental Neuropsychology Research Group, Magyar Tudósok körútja 2., H-1117 Budapest, Hungary; Department of Cognitive Science, Faculty of Natural Sciences, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary
| | - Z Nemoda
- Department of Molecular Biology, Institute of Biochemistry and Molecular Biology, Semmelweis University, Tűzoltó utca 37-47., H-1094 Budapest, Hungary
| | - N Angyal
- Department of Molecular Biology, Institute of Biochemistry and Molecular Biology, Semmelweis University, Tűzoltó utca 37-47., H-1094 Budapest, Hungary
| | - R Fiáth
- Integrative Neuroscience Research Group, Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Magyar Tudósok körútja 2., H-1117 Budapest, Hungary; Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 50/A., H-1083 Budapest, Hungary
| | - T É Sebők-Welker
- Research Centre for Natural Sciences Institute of Cognitive Neuroscience and Psychology, Clinical and Developmental Neuropsychology Research Group, Magyar Tudósok körútja 2., H-1117 Budapest, Hungary; Doctoral School of Mental Health Sciences, Semmelweis University, Balassa u. 6., 1083 Budapest, Hungary
| | - B Pászthy
- Pediatric Center, MTA Center of Excellence, Semmelweis University, Bókay János u. 53-43., H-1083 Budapest, Hungary
| | - I Ulbert
- Integrative Neuroscience Research Group, Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Magyar Tudósok körútja 2., H-1117 Budapest, Hungary; Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 50/A., H-1083 Budapest, Hungary
| | - J M Réthelyi
- Department of Psychiatry and Psychotherapy, Faculty of Medicine, Semmelweis University, Balassa u. 6., H-1083 Budapest, Hungary
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Agelink van Rentergem JA, Bathelt J, Geurts HM. Clinical subtyping using community detection: Limited utility? Int J Methods Psychiatr Res 2023; 32:e1951. [PMID: 36415153 PMCID: PMC10242199 DOI: 10.1002/mpr.1951] [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: 07/25/2022] [Revised: 09/13/2022] [Accepted: 09/25/2022] [Indexed: 11/24/2022] Open
Abstract
OBJECTIVES To discover psychiatric subtypes, researchers are adopting a method called community detection. This method was not subjected to the same scrutiny in the psychiatric literature as traditional clustering methods. Furthermore, many community detection algorithms have been developed without psychiatric sample sizes and variable numbers in mind. We aim to provide clarity to researchers on the utility of this method. METHODS We provide an introduction to community detection algorithms, specifically describing the crucial differences between correlation-based and distance-based community detection. We compare community detection results to results of traditional methods in a simulation study representing typical psychiatry settings, using three conceptualizations of how subtypes might differ. RESULTS We discovered that the number of recovered subgroups was often incorrect with several community detection algorithms. Correlation-based community detection fared better than distance-based community detection, and performed relatively well with smaller sample sizes. Latent profile analysis was more consistent in recovering subtypes. Whether methods were successful depended on how differences were introduced. CONCLUSIONS Traditional methods like latent profile analysis remain reasonable choices. Furthermore, results depend on assumptions and theoretical choices underlying subtyping analyses, which researchers need to consider before drawing conclusions on subtypes. Employing multiple subtyping methods to establish method dependency is recommended.
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Affiliation(s)
| | - Joe Bathelt
- Department of PsychologyDutch Autism & ADHD Research Centre (d’Arc)University of AmsterdamAmsterdamThe Netherlands
- Department of PsychologyRoyal HollowayUniversity of LondonEghamUK
| | - Hilde M. Geurts
- Department of PsychologyDutch Autism & ADHD Research Centre (d’Arc)University of AmsterdamAmsterdamThe Netherlands
- Leo Kannerhuis (Youz/Parnassia Groep)AmsterdamThe Netherlands
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Nigg JT, Karalunas SL, Mooney MA, Wilmot B, Nikolas MA, Martel MM, Tipsord J, Nousen EK, Schmitt C, Ryabinin P, Musser ED, Nagel BJ, Fair DA. The Oregon ADHD-1000: A new longitudinal data resource enriched for clinical cases and multiple levels of analysis. Dev Cogn Neurosci 2023; 60:101222. [PMID: 36848718 PMCID: PMC9984785 DOI: 10.1016/j.dcn.2023.101222] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 01/31/2023] [Accepted: 02/20/2023] [Indexed: 02/27/2023] Open
Abstract
The fields of developmental psychopathology, developmental neuroscience, and behavioral genetics are increasingly moving toward a data sharing model to improve reproducibility, robustness, and generalizability of findings. This approach is particularly critical for understanding attention-deficit/hyperactivity disorder (ADHD), which has unique public health importance given its early onset, high prevalence, individual variability, and causal association with co-occurring and later developing problems. A further priority concerns multi-disciplinary/multi-method datasets that can span different units of analysis. Here, we describe a public dataset using a case-control design for ADHD that includes: multi-method, multi-measure, multi-informant, multi-trait data, and multi-clinician evaluation and phenotyping. It spans > 12 years of annual follow-up with a lag longitudinal design allowing age-based analyses spanning age 7-19 + years with a full age range from 7 to 21. Measures span genetic and epigenetic (DNA methylation) array data; EEG, functional and structural MRI neuroimaging; and psychophysiological, psychosocial, clinical and functional outcomes data. The resource also benefits from an autism spectrum disorder add-on cohort and a cross sectional case-control ADHD cohort from a different geographical region for replication and generalizability. Datasets allowing for integration from genes to nervous system to behavior represent the "next generation" of researchable cohorts for ADHD and developmental psychopathology.
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Affiliation(s)
- Joel T Nigg
- Department of Psychiatry & Behavioral Neuroscience, Oregon Health & Science University, USA.
| | | | - Michael A Mooney
- Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, USA
| | - Beth Wilmot
- Oregon Clinical and Translational Research Institute, Oregon Health & Science University, USA
| | - Molly A Nikolas
- Department of Psychological and Brain Sciences, University of Iowa, USA
| | | | - Jessica Tipsord
- Department of Psychiatry & Behavioral Neuroscience, Oregon Health & Science University, USA
| | - Elizabeth K Nousen
- Department of Psychiatry & Behavioral Neuroscience, Oregon Health & Science University, USA
| | - Colleen Schmitt
- Department of Psychiatry & Behavioral Neuroscience, Oregon Health & Science University, USA
| | - Peter Ryabinin
- Knight Cancer Institute, Oregon Health & Science University, USA
| | - Erica D Musser
- Department of Psychology, Florida International University, USA
| | - Bonnie J Nagel
- Department of Psychiatry & Behavioral Neuroscience, Oregon Health & Science University, USA
| | - Damien A Fair
- Department of Pediatrics, Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, University of Minnesota, USA.
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20
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Vogel AC, Brotman MA, Roy AK, Perlman SB. Review: Defining Positive Emotion Dysregulation: Integrating Temperamental and Clinical Perspectives. J Am Acad Child Adolesc Psychiatry 2023; 62:297-305. [PMID: 36007814 PMCID: PMC11323061 DOI: 10.1016/j.jaac.2022.06.019] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 05/19/2022] [Accepted: 08/15/2022] [Indexed: 11/16/2022]
Abstract
OBJECTIVE Although emotion dysregulation has been defined as a maladaptive process of emotional experiences, there is no specific reference to the emotional valence of the dysregulation. To date, child psychiatry has focused primarily on dysregulation of negative affect. Here, we suggest that positive emotion dysregulation requires additional clinical and research attention. METHOD First, we present a developmental approach to the study of positive emotion regulation within a temperament framework. Second, we describe emerging research findings regarding dysregulation of positive emotion in early childhood. Third, we integrate neuroscientific approaches to positive emotion regulation and introduce a framework for future investigations and clinical applications. RESULTS Dysregulation in positive affect can be examined from temperamental, developmental, clinical, and neuroscientific perspectives. Both temperamental surgency, which includes positive affect, and the proposed clinical extension, excitability, are associated with increased risk of externalizing symptoms and clinical impairment in youth. CONCLUSION Studying the role of both temperamental surgency and clinically impairing positive affect, or excitability, in developmental psychopathology will help to elucidate the full spectrum of emotion dysregulation and to clarify the neural basis of dysregulation. A more comprehensive conceptualization of positively valanced emotion dysregulation will provide a more nuanced understanding of developmental risk and potential targets for intervention. DIVERSITY & INCLUSION STATEMENT One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science.
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Affiliation(s)
- Alecia C Vogel
- Drs. Vogel and Perlman are with Washington University School of Medicine, St. Louis, Missouri. Dr. Brotman is with the National Institute of Mental Health, Bethesda, Maryland. Dr. Roy is with Fordham University, Bronx, New York.
| | - Melissa A Brotman
- Drs. Vogel and Perlman are with Washington University School of Medicine, St. Louis, Missouri. Dr. Brotman is with the National Institute of Mental Health, Bethesda, Maryland. Dr. Roy is with Fordham University, Bronx, New York
| | - Amy Krain Roy
- Drs. Vogel and Perlman are with Washington University School of Medicine, St. Louis, Missouri. Dr. Brotman is with the National Institute of Mental Health, Bethesda, Maryland. Dr. Roy is with Fordham University, Bronx, New York
| | - Susan B Perlman
- Drs. Vogel and Perlman are with Washington University School of Medicine, St. Louis, Missouri. Dr. Brotman is with the National Institute of Mental Health, Bethesda, Maryland. Dr. Roy is with Fordham University, Bronx, New York
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Mareva S, Akarca D, Holmes J. Transdiagnostic profiles of behaviour and communication relate to academic and socioemotional functioning and neural white matter organisation. J Child Psychol Psychiatry 2023; 64:217-233. [PMID: 36127748 PMCID: PMC10087495 DOI: 10.1111/jcpp.13685] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/07/2022] [Indexed: 01/17/2023]
Abstract
BACKGROUND Behavioural and language difficulties co-occur in multiple neurodevelopmental conditions. Our understanding of these problems has arguably been slowed by an overreliance on study designs that compare diagnostic groups and fail to capture the overlap across different neurodevelopmental disorders and the heterogeneity within them. METHODS We recruited a large transdiagnostic cohort of children with complex needs (N = 805) to identify distinct subgroups of children with common profiles of behavioural and language strengths and difficulties. We then investigated whether and how these data-driven groupings could be distinguished from a comparison sample (N = 158) on measures of academic and socioemotional functioning and patterns of global and local white matter connectome organisation. Academic skills were assessed via standardised measures of reading and maths. Socioemotional functioning was captured by the parent-rated version of the Strengths and Difficulties Questionnaire. RESULTS We identified three distinct subgroups of children, each with different levels of difficulties in structural language, pragmatic communication, and hot and cool executive functions. All three subgroups struggled with academic and socioemotional skills relative to the comparison sample, potentially representing three alternative but related developmental pathways to difficulties in these areas. The children with the weakest language skills had the most widespread difficulties with learning, whereas those with more pronounced difficulties with hot executive skills experienced the most severe difficulties in the socioemotional domain. Each data-driven subgroup could be distinguished from the comparison sample based on both shared and subgroup-unique patterns of neural white matter organisation. Children with the most pronounced deficits in language, cool executive, or hot executive function were differentiated from the comparison sample by altered connectivity in predominantly thalamocortical, temporal-parietal-occipital, and frontostriatal circuits, respectively. CONCLUSIONS These findings advance our understanding of commonly co-morbid behavioural and language problems and their relationship to behavioural outcomes and neurobiological substrates.
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Affiliation(s)
- Silvana Mareva
- Medical Research Council Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
| | - Danyal Akarca
- Medical Research Council Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
| | - Joni Holmes
- Medical Research Council Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
- School of Psychology, Faculty of Social SciencesUniversity of East AngliaNorwichUK
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22
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Widmer A, Havewala M, Bowker JC, Rubin KH. Secure Attachment Relationships With Mothers, But Not Fathers, Moderate the Relation Between Attention-Deficit Hyperactivity Symptoms and Delinquency in Adolescents. J Atten Disord 2023; 27:46-56. [PMID: 36039532 DOI: 10.1177/10870547221120694] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
OBJECTIVE The primary aim of this study was to investigate whether secure parent-adolescent attachment relationships moderate the longitudinal relation between 9th grade (G9) ADHD symptoms and 12th grade (G12) delinquency within a community sample of adolescents. METHOD Participants included 335 9th graders, of whom 203 students completed measures again in 12th grade. Mothers reported on their adolescents' ADHD symptoms and aggressive behaviors, and adolescents completed measures of their own delinquency and their perceptions of their parent-child attachment relationships. RESULTS G9 ADHD symptoms predicted increases in G12 delinquent behaviors. Moderation effects were also found such that G9 ADHD symptoms predicted G12 delinquency for only those youth who had moderate or low levels of secure maternal attachment. Paternal secure attachment did not moderate the effects of G9 ADHD symptoms on G12 delinquency. CONCLUSION Findings underscore the importance of secure maternal attachment relationships in the development of delinquency among adolescents with ADHD symptoms.
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23
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Shapiro ZR, Bray B, Huang-Pollock C. Mechanism-based groups of children with ADHD are associated with distinct domains of impairment. Psychiatry Res 2023; 319:115018. [PMID: 36549097 PMCID: PMC9835004 DOI: 10.1016/j.psychres.2022.115018] [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: 04/12/2022] [Revised: 12/15/2022] [Accepted: 12/18/2022] [Indexed: 12/23/2022]
Abstract
Person-oriented analyses are commonly used to identify subgroups of children with mental health conditions in the hopes that they will meaningfully inform the taxonomy, assessment, and treatment of psychological disorder. However, whether these data-driven groups are demonstrably better at predicting important aspects of adaptive functioning than standard DSM taxonomy has not been established. Using Attention-Deficit-Hyperactivity-Disorder (ADHD) as a model condition, we utilized dimensions of personality and cognitive ability to identify person-centered profiles of school-aged children (N=246) and evaluated the association of these profiles with critical areas of adaptive functioning. A single profile ("Conscientious") represented non-ADHD controls and was characterized by faster drift rate and higher executive functioning scores. Three profiles ("Disagreeable," "Negative Emotionality," and "Extraverted") were identified for children with ADHD. Drift rate, but not executive functioning, distinguished among ADHD profiles, which were also distinctly associated with comorbid externalizing and internalizing psychopathology, social skills, and academic achievement. In contrast, the Diagnostic and Statistical Manual (DSM) presentations were not informative and showed similar patterns of impairment across domains. Person-centered profiles of children with ADHD are associated with distinct adaptive functioning deficits and may be useful in informing clinical practice.
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Affiliation(s)
- Zvi R Shapiro
- Department of Psychiatry, Emory University, Atlanta, GA, USA.
| | - Bethany Bray
- Center for Dissemination and Implementation Science, The University of Illinois at Chicago, Chicago, IL, USA
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Karalunas SL, Antovich D, Miller N, Nigg JT. Prospective prediction of developing internalizing disorders in ADHD. J Child Psychol Psychiatry 2022; 64:768-778. [PMID: 36464786 DOI: 10.1111/jcpp.13731] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/14/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND Clinical course in attention-deficit/hyperactivity disorder (ADHD) is highly heterogeneous with respect to both core symptoms and associated features and impairment. Onset of comorbid anxiety and mood disorders during later childhood and adolescence is one critical aspect of divergent outcomes in ADHD. Characterizing heterogeneity in onset of anxiety and depression and identifying prospective predictors of these divergent courses may facilitate early identification of the children most at risk. METHODS A total of 849 children recruited for a case-control study of ADHD development, aged 7-12 years at baseline, completed up to six annual waves of comprehensive clinical and cognitive assessment, including multi-informant behavior ratings, parent semi-structured clinical diagnostic interviews, and measures of executive function (EF). Latent class growth curve analyses (LCGAs) characterized patterns of anxiety and depression over time. Trajectories were predicted from baseline parent-rated child temperament, lab-measured child EF, coded parental criticism, and child-reported self-blame for inter-parental conflict. RESULTS Latent class growth curve analyses separately identified three trajectories for anxiety and three for depression: persistently high, persistently low, and increasing. Temperamental fear/sadness and irritability were independent predictors that interacted with family characteristics. Baseline parental criticism and self-blame for inter-parental conflict exerted influence but only in the context of low temperamental risk. Better baseline child working memory was associated with delayed onset of depression. CONCLUSIONS The interaction of baseline child emotional features with EF or family environment predicted divergent courses of both anxiety and depression from middle-childhood to mid-adolescence. Results suggest modifiable risk factors associated with prospective differences in long-term outcomes.
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Affiliation(s)
| | - Dylan Antovich
- Psychiatry and Behavioral Neuroscience, Oregon Health and Science University, Portland, OR, USA
| | - Natalie Miller
- Psychiatry and Behavioral Neuroscience, Oregon Health and Science University, Portland, OR, USA
| | - Joel T Nigg
- Psychiatry and Behavioral Neuroscience, Oregon Health and Science University, Portland, OR, USA
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Öztekin I, Garic D, Bayat M, Hernandez ML, Finlayson MA, Graziano PA, Dick AS. Structural and diffusion-weighted brain imaging predictors of attention-deficit/hyperactivity disorder and its symptomology in very young (4- to 7-year-old) children. Eur J Neurosci 2022; 56:6239-6257. [PMID: 36215144 PMCID: PMC10165616 DOI: 10.1111/ejn.15842] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 09/15/2022] [Accepted: 09/21/2022] [Indexed: 12/29/2022]
Abstract
The current study aimed to identify the key neurobiology of attention-deficit/hyperactivity disorder (ADHD), as it relates to ADHD diagnostic category and symptoms of hyperactive/impulsive behaviour and inattention. To do so, we adapted a predictive modelling approach to identify the key structural and diffusion-weighted brain imaging measures and their relative standing with respect to teacher ratings of executive function (EF) (measured by the Metacognition Index of the Behavior Rating Inventory of Executive Function [BRIEF]) and negativity and emotion regulation (ER) (measured by the Emotion Regulation Checklist [ERC]), in a critical young age range (ages 4 to 7, mean age 5.52 years, 82.2% Hispanic/Latino), where initial contact with educators and clinicians typically take place. Teacher ratings of EF and ER were predictive of both ADHD diagnostic category and symptoms of hyperactive/impulsive behaviour and inattention. Among the neural measures evaluated, the current study identified the critical importance of the largely understudied diffusion-weighted imaging measures for the underlying neurobiology of ADHD and its associated symptomology. Specifically, our analyses implicated the inferior frontal gyrus as a critical predictor of ADHD diagnostic category and its associated symptomology, above and beyond teacher ratings of EF and ER. Collectively, the current set of findings have implications for theories of ADHD, the relative utility of neurobiological measures with respect to teacher ratings of EF and ER, and the developmental trajectory of its underlying neurobiology.
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Affiliation(s)
- Ilke Öztekin
- Center for Children and Families and Department of Psychology, Florida International University, Miami, Florida, USA.,Exponent, Inc., Philadelphia, Pennsylvania, USA
| | - Dea Garic
- Carolina Institute for Developmental Disabilities, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Mohammadreza Bayat
- Center for Children and Families and Department of Psychology, Florida International University, Miami, Florida, USA
| | - Melissa L Hernandez
- Center for Children and Families and Department of Psychology, Florida International University, Miami, Florida, USA
| | - Mark A Finlayson
- School of Computing and Information Sciences, Florida International University, Miami, Florida, USA
| | - Paulo A Graziano
- Center for Children and Families and Department of Psychology, Florida International University, Miami, Florida, USA
| | - Anthony Steven Dick
- Center for Children and Families and Department of Psychology, Florida International University, Miami, Florida, USA
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Naim R, Shaughnessy S, Smith A, Karalunas SL, Kircanski K, Brotman MA. Real-time assessment of positive and negative affective fluctuations and mood lability in a transdiagnostic sample of youth. Depress Anxiety 2022; 39:870-880. [PMID: 36325887 PMCID: PMC9729410 DOI: 10.1002/da.23293] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 09/30/2022] [Accepted: 10/22/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Emotional lability, defined as rapid and/or intense affect fluctuations, is associated with pediatric psychopathology. Although numerous studies have examined labile mood in clinical groups, few studies have used real-time assessments in a well-characterized transdiagnostic sample, and no prior study has included participants with disruptive mood dysregulation disorder (DMDD). The present study leverages ecological momentary assessment (EMA) to assess emotional lability in a transdiagnostic pediatric sample. METHODS One hundred thirty participants ages 8-18 with primary diagnoses of DMDD, attention-deficit/hyperactivity disorder (ADHD), an anxiety disorder (ANX), or healthy volunteers completed a previously validated 1-week EMA protocol. Clinicians determined diagnoses based on semi-structured interviews and assessed levels of functional impairment. Participants reported momentary affective states and mood change. Composite scores of fluctuations in positive and negative affect were generated. Affect fluctuations were compared between diagnostic groups and tested for their association with functional impairment. RESULTS Diagnostic groups differed in levels of negative and positive emotional lability. DMDD patients demonstrated the highest level of labile mood compared with other groups. Emotional lability was associated with global impairment in the whole sample. CONCLUSIONS Both positive and negative emotional lability is salient in pediatric psychopathology and is associated with functional impairment, particularly in DMDD youth.
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Affiliation(s)
- Reut Naim
- Emotion and Development Branch, National Institute of
Mental Health, Bethesda, MD,Corresponding author- Reut Naim, National
Institute of Mental Health, Bldg. 15K, MSC 2670, Bethesda, MD 20892-2670, Phone:
301-827-6138,
| | - Shannon Shaughnessy
- Emotion and Development Branch, National Institute of
Mental Health, Bethesda, MD
| | - Ashley Smith
- Emotion and Development Branch, National Institute of
Mental Health, Bethesda, MD
| | - Sarah L. Karalunas
- Department of Psychological Sciences, Purdue University,
West Lafayette, IN
| | - Katharina Kircanski
- Emotion and Development Branch, National Institute of
Mental Health, Bethesda, MD
| | - Melissa A. Brotman
- Emotion and Development Branch, National Institute of
Mental Health, Bethesda, MD
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Kozlowski MB, Antovich D, Karalunas SL, Nigg JT. Temperament in middle childhood questionnaire: New data on factor structure and applicability in a child clinical sample. Psychol Assess 2022; 34:1081-1092. [PMID: 36174168 PMCID: PMC9772251 DOI: 10.1037/pas0001180] [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] [Indexed: 12/24/2022]
Abstract
The Temperament in Middle Childhood Questionnaire (TMCQ) is one of a family of instruments representing one of the major conceptual models of child temperament. The present study reports new psychometric information on the TMCQ using a larger sample than in prior factor-analytic studies of this instrument. Data from parent ratings of 1,418 children were utilized. The sample of community volunteers included 697 typically developing youth and 721 defined by research diagnostic procedures as having attention-deficit/hyperactivity disorder. Results failed to support the original proposed structure of the TMCQ, but found support for a structure with 12 subscales that confirmed a substantial portion of the lower order factor structure. However, the intended three-factor higher order structure was not able to be fully recovered. Two-group invariance was supported in the final model, supporting use in studies of typical and atypical development. In conclusion, with some modifications the TMCQ remains a useful research measure at the lower order factor level. The validity of the higher order structure is less clear, likely due to measure-specific limitations, and suggests a need for some refinement to the measure. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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28
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Nili AN, Krogh-Jespersen S, Perlman SB, Estabrook R, Petitclerc A, Briggs-Gowan MJ, Sherlock PR, Norton ES, Wakschlag LS. Joint Consideration of Inhibitory Control and Irritability in Young Children: Contributions to Emergent Psychopathology. Res Child Adolesc Psychopathol 2022; 50:1415-1427. [PMID: 35838931 PMCID: PMC9753138 DOI: 10.1007/s10802-022-00945-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/01/2022] [Indexed: 10/17/2022]
Abstract
Deficits in self-regulation capacity have been linked to subsequent impairment and clinical symptomology across the lifespan. Prior work has identified difficulty regulating angry emotions (i.e., irritability) as a powerful transdiagnostic indicator of current and future clinical concerns. Less is known regarding how irritability intersects with cognitive features of self-regulation, in particular inhibitory control, despite its mental health relevance. A promising avenue for improving specificity of clinical predictions in early childhood is multi-method, joint consideration of irritability and inhibitory control capacities. To advance early identification of impairment and psychopathology risk, we contrast group- and variable-based models of neurodevelopmental vulnerability at the interface of irritability and inhibitory control in contexts of varied motivational and emotional salience. This work was conducted in a longitudinal study of children recruited at well-child visits in Midwestern pediatric clinics at preschool age (N = 223, age range = 3-7 years). Group-based models (clustering and regression of clusters on clinical outcomes) indicated significant heterogeneity of self-regulation capacity in this sample. Meanwhile, variable-based models (continuous multiple regression) evidenced associations with concurrent clinical presentation, future symptoms, and impairment across the broad spectrum of psychopathology. Irritability transdiagnostically indicated internalizing and externalizing problems, concurrently and longitudinally. In contrast, inhibitory control was uniquely associated with attention-deficit/hyperactivity symptoms. We present these findings to advance a joint consideration approach to two promising indicators of neurodevelopmental vulnerability and mental health risk. Models suggest that both emotional and cognitive self-regulation capacities can address challenges in characterizing the developmental unfolding of psychopathology from preschool to early childhood age.
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Affiliation(s)
- Amanda N Nili
- Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, 633 N. St. Clair, Suite 1900, Chicago, IL, 60611, USA.
- Institute for Innovations in Developmental Sciences, Northwestern University, Evanston, IL, USA.
| | - Sheila Krogh-Jespersen
- Institute for Innovations in Developmental Sciences, Northwestern University, Evanston, IL, USA
| | - Susan B Perlman
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Ryne Estabrook
- Department of Psychology, University of Illinois at Chicago, Chicago, IL, USA
| | | | | | - Phil R Sherlock
- Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, 633 N. St. Clair, Suite 1900, Chicago, IL, 60611, USA
| | - Elizabeth S Norton
- Institute for Innovations in Developmental Sciences, Northwestern University, Evanston, IL, USA
- School of Communications, Northwestern University, Evanston, IL, USA
| | - Laurie S Wakschlag
- Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, 633 N. St. Clair, Suite 1900, Chicago, IL, 60611, USA
- Institute for Innovations in Developmental Sciences, Northwestern University, Evanston, IL, USA
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29
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Cordova MM, Antovich DM, Ryabinin P, Neighbor C, Mooney MA, Dieckmann NF, Miranda-Dominguez O, Nagel BJ, Fair DA, Nigg JT. Attention-Deficit/Hyperactivity Disorder: Restricted Phenotypes Prevalence, Comorbidity, and Polygenic Risk Sensitivity in the ABCD Baseline Cohort. J Am Acad Child Adolesc Psychiatry 2022; 61:1273-1284. [PMID: 35427730 PMCID: PMC9677584 DOI: 10.1016/j.jaac.2022.03.030] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 02/15/2022] [Accepted: 03/25/2022] [Indexed: 11/25/2022]
Abstract
OBJECTIVE To evaluate the prevalence and major comorbidities of ADHD using different operational definitions in a newly available national dataset and to test the utility of operational definitions against genetic and cognitive correlates. METHOD The US Adolescent Brain Cognitive Development (ABCD) Study enrolled 11,878 children aged 9-10 years at baseline. ADHD prevalence, comorbidity, and association with polygenic risk score and laboratory-assessed executive functions were calculated at 4 thresholds of ADHD phenotype restrictiveness. Bias from missingness, sampling, and nesting were addressed statistically. RESULTS Prevalence of current ADHD for 9- to 10-year old children was 3.53% (95% CI 3.14%-3.92%) when Computerized Schedule for Affective Disorders and Schizophrenia for School-Age Children (K-SADS-COMP) score and parent and teacher ratings were required to converge. Of ADHD cases so defined, 70% had a comorbid psychiatric disorder. After control for overlapping comorbidity and ruling out for psychosis or low IQ, 30.9% (95% CI 25.7%-36.7%) had a comorbid disruptive behavior disorder, 27.4% (95% CI 22.3%-33.1%) had an anxiety or fear disorder, and 2.1% (95% CI 1.2%-3.8%) had a mood disorder. Children in the top decile of polygenic load incurred a 63% increased chance of having ADHD vs the bottom half of polygenic load (p < .01)-an effect detected only with a stringent phenotype definition. Dimensional latent variables for irritability, externalizing, and ADHD yielded convergent results for cognitive correlates. CONCLUSION This fresh estimate of national prevalence of ADHD in the United States suggests that the DSM-5 definition requiring multiple informants yields a prevalence of about 3.5%. Results may inform further ADHD studies in the ABCD sample.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Joel T Nigg
- Oregon Health & Science University, Portland.
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30
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Arnett AB, McGrath LM, Flaherty BP, Pennington BF, Willcutt E. Heritability and Clinical Characteristics of Neuropsychological Profiles in Youth With and Without Elevated ADHD Symptoms. J Atten Disord 2022; 26:1422-1436. [PMID: 35102766 PMCID: PMC9283222 DOI: 10.1177/10870547221075842] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
OBJECTIVE In the last decade, there has been an increase in research that aims to parse heterogeneity in attention deficit hyperactivity disorder (ADHD). The current study tests heritability of latent class neuropsychological subtypes. METHOD Latent class analysis was used to derive subtypes in a sample of school-age twins (N = 2,564) enriched for elevated ADHD symptoms. RESULTS Five neuropsychological profiles replicated across twin 1 and twin 2 datasets. Latent class membership was heritable overall, but heritability varied by profile and was lower than heritability of ADHD status. Variability in neuropsychological performance across domains was the strongest predictor of elevated ADHD symptoms. Neuropsychological profiles showed distinct associations with age, psychiatric symptoms and reading ability. CONCLUSION Neuropsychological profiles are associated with unique neurocognitive presentations, but are not strong candidate endophenotypes for ADHD diagnosis.
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Affiliation(s)
- Anne B. Arnett
- Division of Developmental Medicine, Boston Children’s Hospital, Brookline, MA
| | | | | | | | - Erik Willcutt
- Department of Psychology and Neuroscience, University of Colorado at Boulder, Boulder, CO
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO
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31
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Arnett AB, Flaherty BP. A framework for characterizing heterogeneity in neurodevelopmental data using latent profile analysis in a sample of children with ADHD. J Neurodev Disord 2022; 14:45. [PMID: 35922762 PMCID: PMC9351075 DOI: 10.1186/s11689-022-09454-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 07/24/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Heterogeneity in neurodevelopmental disorders, and attention deficit hyperactivity disorder (ADHD) in particular, is increasingly identified as a barrier to identifying biomarkers and developing standards for clinical care. Clustering analytic methods have previously been used across a variety of data types with the goal of identifying meaningful subgroups of individuals with ADHD. However, these analyses have often relied on algorithmic approaches which assume no error in group membership and have not made associations between patterns of behavioral, neurocognitive, and genetic indicators. More sophisticated latent classification models are often not utilized in neurodevelopmental research due to the difficulty of working with these models in small sample sizes. METHODS In the current study, we propose a framework for evaluating mixture models in sample sizes typical of neurodevelopmental research. We describe a combination of qualitative and quantitative model fit evaluation procedures. We test our framework using latent profile analysis (LPA) in a case study of 120 children with and without ADHD, starting with well-understood neuropsychological indicators, and building toward integration of electroencephalogram (EEG) measures. RESULTS We identified a stable five-class LPA model using seven neuropsychological indicators. Although we were not able to identify a stable multimethod indicator model, we did successfully extrapolate results of the neuropsychological model to identify distinct patterns of resting EEG power across five frequency bands. CONCLUSIONS Our approach, which emphasizes theoretical as well as empirical evaluation of mixture models, could make these models more accessible to clinical researchers and may be a useful approach to parsing heterogeneity in neurodevelopmental disorders.
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Affiliation(s)
- Anne B Arnett
- Division of Developmental Medicine, Boston Children's Hospital, Boston, MA, 02115, USA. .,Department of Pediatrics, Harvard Medical School, Boston, MA, USA.
| | - Brian P Flaherty
- Department of Psychology, University of Washington, Seattle, WA, USA
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32
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Lahey BB, Tong L, Pierce B, Hedeker D, Berman MG, Cardenas-Iniguez C, Moore TM, Applegate B, Tiemeier H, Kaczkurkin AN. Associations of polygenic risk for attention-deficit/hyperactivity disorder with general and specific dimensions of childhood psychological problems and facets of impulsivity. J Psychiatr Res 2022; 152:187-193. [PMID: 35752070 PMCID: PMC10001434 DOI: 10.1016/j.jpsychires.2022.06.019] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 06/07/2022] [Accepted: 06/10/2022] [Indexed: 11/24/2022]
Abstract
A polygenic risk score (PRS) for attention-deficit/hyperactivity disorder (ADHD) has been found to be associated with ADHD in multiple studies, but also with many other dimensions of problems. Little is known, however, about the processes underlying these transdiagnostic associations. Using data from the baseline and 1-year follow-up assessments of 9- to 10-year-old children in the Adolescent Brain Cognitive Development™ (ABCD©) Study, associations were assessed between an ADHD PRS and both general and specific factors of psychological problems defined in bifactor modeling. Additionally, prospective mediated paths were tested from the ADHD PRS to dimensions of problems in the follow-up assessment through baseline measures of executive functioning (EF) and two facets of impulsivity: lower perseverance and greater impulsiveness in the presence of surgent positive emotions. Previous findings of modest but significant direct associations of the ADHD PRS with the general factor of psychological problems were replicated in both assessments in 4,483 children of European ancestry. In addition, significant statistical mediation was found from the ADHD PRS to the general factor, specific ADHD, and conduct problems in the follow-up assessment through each of the two facets of impulsivity. In contrast, EF did not statistically mediate associations between the ADHD PRS and psychological problems. These results suggest that polygenic risk transdiagnostically influences both psychological problems and facets of impulsivity, perhaps partly through indirect pathways via facets of impulsivity.
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Affiliation(s)
- Benjamin B Lahey
- Department of Public Health Sciences, University of Chicago, 5841 S. Maryland Avenue, Chicago, IL, 60637, USA.
| | - Lin Tong
- Department of Public Health Sciences, University of Chicago, 5841 S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Brandon Pierce
- Department of Public Health Sciences, University of Chicago, 5841 S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Donald Hedeker
- Department of Public Health Sciences, University of Chicago, 5841 S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Marc G Berman
- Department of Psychology, University of Chicago, 5848 S University Ave, Chicago, IL, 60637, USA.
| | - Carlos Cardenas-Iniguez
- Keck School of Medicine, University of Southern California, 1975 Zonal Avenue, Los Angeles, CA, 90033, USA
| | - Tyler M Moore
- Department of Psychiatry, University of Pennsylvania School of Medicine, 3700 Hamilton Walk, Philadelphia, PA, 19104, USA.
| | - Brooks Applegate
- Department of Educational Leadership, Research & Technology, Western Michigan University, 1903 West Michigan Avenue, Kalamazoo, MI, 49008, USA.
| | - Henning Tiemeier
- Chan School of Public Health, Harvard University, 677 Huntington Avenue, Boston, MA, 02215, USA.
| | - Antonia N Kaczkurkin
- Department of Psychology, Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN, 37240-7817, USA.
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33
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Abstract
It is widely agreed that the DSM-5, the handbook of psychiatric diagnosis, suffers from both high overlap among its putative disorders and high heterogeneity (variability) within each disorder. While these may appear to be opposite problems, in fact both may stem from failure to recognize transdiagnostic dimensions of emotion, cognition, and personality, among others, that inform psychopathology. These fundamental nosological challenges are exemplified in the case of attention-deficit/hyperactivity disorder (ADHD). In ADHD, broad clinical heterogeneity has defied easy clinical prediction of outcomes or clean statistical differentiation of meaningful, biologically informative sub-groups. Progress for ADHD heterogeneity looks promising, however, when we consider dimensions of trait affectivity such as surgency and negative affectivity, their constituent lower order traits such as irritability, and the integrative function of self-regulation. Focusing on developments in the study of temperament traits and ADHD as they relate to emotional dysregulation, several lines of investigation are proving useful. Utilization of selective computational models, biological validators, and longitudinal analyses points toward potential improvements in nosology and clinical assessment in the future by taking temperament traits into account.
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34
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Buitelaar J, Bölte S, Brandeis D, Caye A, Christmann N, Cortese S, Coghill D, Faraone SV, Franke B, Gleitz M, Greven CU, Kooij S, Leffa DT, Rommelse N, Newcorn JH, Polanczyk GV, Rohde LA, Simonoff E, Stein M, Vitiello B, Yazgan Y, Roesler M, Doepfner M, Banaschewski T. Toward Precision Medicine in ADHD. Front Behav Neurosci 2022; 16:900981. [PMID: 35874653 PMCID: PMC9299434 DOI: 10.3389/fnbeh.2022.900981] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 05/16/2022] [Indexed: 11/17/2022] Open
Abstract
Attention-Deficit Hyperactivity Disorder (ADHD) is a complex and heterogeneous neurodevelopmental condition for which curative treatments are lacking. Whilst pharmacological treatments are generally effective and safe, there is considerable inter-individual variability among patients regarding treatment response, required dose, and tolerability. Many of the non-pharmacological treatments, which are preferred to drug-treatment by some patients, either lack efficacy for core symptoms or are associated with small effect sizes. No evidence-based decision tools are currently available to allocate pharmacological or psychosocial treatments based on the patient's clinical, environmental, cognitive, genetic, or biological characteristics. We systematically reviewed potential biomarkers that may help in diagnosing ADHD and/or stratifying ADHD into more homogeneous subgroups and/or predict clinical course, treatment response, and long-term outcome across the lifespan. Most work involved exploratory studies with cognitive, actigraphic and EEG diagnostic markers to predict ADHD, along with relatively few studies exploring markers to subtype ADHD and predict response to treatment. There is a critical need for multisite prospective carefully designed experimentally controlled or observational studies to identify biomarkers that index inter-individual variability and/or predict treatment response.
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Affiliation(s)
- Jan Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, Netherlands.,Karakter Child and Adolescent Psychiatry University Center, Nijmegen, Netherlands
| | - Sven Bölte
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institutet, Solna, Sweden.,Child and Adolescent Psychiatry, Stockholm Health Care Services, Stockholm, Sweden.,Curtin Autism Research Group, School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, WA, Australia
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany.,Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Arthur Caye
- Department of Psychiatry, Hospital de Clinicas de Porto Alegre, Federal University of Rio Grande do Sul, Porto Alegre, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents, São Paulo, Brazil
| | - Nina Christmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Samuele Cortese
- Centre for Innovation in Mental Health, Academic Unit of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, United Kingdom.,Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of Medicine, University of Southampton, Southampton, United Kingdom.,Solent National Health System Trust, Southampton, United Kingdom.,Hassenfeld Children's Hospital at NYU Langone, New York University Child Study Center, New York, NY, United States.,Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - David Coghill
- Departments of Paediatrics and Psychiatry, Royal Children's Hospital, University of Melbourne, Melbourne, VIC, Australia
| | - Stephen V Faraone
- Departments of Psychiatry, Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, New York, NY, United States
| | - Barbara Franke
- Departments of Human Genetics and Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
| | - Markus Gleitz
- Medice Arzneimittel Pütter GmbH & Co. KG, Iserlohn, Germany
| | - Corina U Greven
- Karakter Child and Adolescent Psychiatry University Center, Nijmegen, Netherlands.,Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands.,King's College London, Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, London, United Kingdom
| | - Sandra Kooij
- Amsterdam University Medical Center, Location VUMc, Amsterdam, Netherlands.,PsyQ, Expertise Center Adult ADHD, The Hague, Netherlands
| | - Douglas Teixeira Leffa
- Department of Psychiatry, Hospital de Clinicas de Porto Alegre, Federal University of Rio Grande do Sul, Porto Alegre, Brazil.,National Institute of Developmental Psychiatry for Children and Adolescents, São Paulo, Brazil
| | - Nanda Rommelse
- Karakter Child and Adolescent Psychiatry University Center, Nijmegen, Netherlands.,Department of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
| | - Jeffrey H Newcorn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Guilherme V Polanczyk
- Department of Psychiatry, Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil
| | - Luis Augusto Rohde
- National Institute of Developmental Psychiatry for Children and Adolescents, São Paulo, Brazil.,ADHD Outpatient Program and Developmental Psychiatry Program, Hospital de Clinica de Porto Alegre, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Emily Simonoff
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Mark Stein
- Department of Psychiatry and Behavioral Sciences, Seattle, WA, United States
| | - Benedetto Vitiello
- Department of Public Health and Pediatric Sciences, Section of Child and Adolescent Neuropsychiatry, University of Turin, Turin, Italy.,Department of Public Health, Johns Hopkins University, Baltimore, MA, United States
| | - Yanki Yazgan
- GuzelGunler Clinic, Istanbul, Turkey.,Yale Child Study Center, New Haven, CT, United States
| | - Michael Roesler
- Institute for Forensic Psychology and Psychiatry, Neurocenter, Saarland, Germany
| | - Manfred Doepfner
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Medical Faculty of the University of Cologne, Cologne, Germany.,School for Child and Adolescent Cognitive Behavioural Therapy, University Hospital of Cologne, Cologne, Germany
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
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35
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Xie W, Bathelt J, Fasman A, Nelson CA, Enlow MB. Temperament and psychopathology: The "community" to which you belong matters. Child Dev 2022; 93:995-1011. [PMID: 35226361 PMCID: PMC9970029 DOI: 10.1111/cdev.13742] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We utilized a community detection approach to longitudinally (a) identify distinct groups of children with common temperament profiles in infancy and at 2 and 3 years of age and (b) determine whether co-occurrence of certain temperament traits may be early predictors of internalizing problems at 5 years of age. Seven hundred and seventy-four infants (360 girls; 88.6% White, 9.8% Hispanic, and 1.6% other races) were recruited from the Boston area. Data collection spanned from 2012 to 2021. The analysis yielded three distinct groups of children with different temperament traits and was associated with significant variation in levels of internalizing symptoms and anxiety diagnosis rate. Our findings suggest that stable temperament "communities" can be detected in early childhood and may predict risk for psychopathology later in life.
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Affiliation(s)
- Wanze Xie
- School of Psychological and Cognitive Sciences, Peking University, China,PKU-IDG/McGovern Institute for Brain Research, Peking University, China,Beijing Key Laboratory of Behavior and Mental Health, Peking University, China,Boston Children’s Hospital, Boston, Massachusetts, USA
| | - Joe Bathelt
- Department of Psychology, Royal Holloway, University of London, UK
| | - Anna Fasman
- Boston Children’s Hospital, Boston, Massachusetts, USA
| | - Charles A. Nelson
- Boston Children’s Hospital, Boston, Massachusetts, USA,Harvard Medical School, Boston, Massachusetts, USA,Harvard Graduate School of Education, Cambridge, Massachusetts, USA
| | - Michelle Bosquet Enlow
- Boston Children’s Hospital, Boston, Massachusetts, USA,Harvard Medical School, Boston, Massachusetts, USA
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36
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Methylphenidate Use for Emotional Dysregulation in Children and Adolescents with ADHD and ADHD and ASD: A Naturalistic Study. J Clin Med 2022; 11:jcm11102922. [PMID: 35629047 PMCID: PMC9142913 DOI: 10.3390/jcm11102922] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 05/10/2022] [Accepted: 05/20/2022] [Indexed: 02/05/2023] Open
Abstract
Emotional dysregulation (ED) is common in attention-deficit/hyperactivity disorder (ADHD). Nonetheless, research on ADHD in children with autism spectrum disorder (ASD) and ADHD is still ongoing. Several studies suggest that methylphenidate (MPH) may be effective for ED in ADHD, while there is not enough evidence about its use in ASD with comorbid ADHD. This naturalistic study aims to investigate the effectiveness of immediate- and extended-release MPH in the treatment of ED in 70 children and adolescents (6–18 years), with a diagnosis of ADHD (n = 41) and of ASD with comorbid ADHD (n = 29), using the Child Behavior Checklist—Attention/Aggressive/Anxious (CBCL-AAA). Their parents completed the CBCL twice—first during the summer medication-free period, that is, at least one month after drug interruption; and again after three months of treatment restart. Results demonstrate that MPH is associated with a statistically significant reduction in ED in ADHD and ASD, without substantial adverse events, supporting the use of psychostimulants for the treatment of ED in these neurodevelopmental disorders.
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37
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Jones JS, Astle DE. Segregation and integration of the functional connectome in neurodevelopmentally 'at risk' children. Dev Sci 2022; 25:e13209. [PMID: 34873798 PMCID: PMC7613070 DOI: 10.1111/desc.13209] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 10/08/2021] [Accepted: 11/22/2021] [Indexed: 01/22/2023]
Abstract
Functional connectivity within and between Intrinsic Connectivity Networks (ICNs) transforms over development and is thought to support high order cognitive functions. But how variable is this process, and does it diverge with altered cognitive development? We investigated age-related changes in integration and segregation within and between ICNs in neurodevelopmentally 'at-risk' children, identified by practitioners as experiencing cognitive difficulties in attention, learning, language, or memory. In our analysis we used performance on a battery of 10 cognitive tasks alongside resting-state functional magnetic resonance imaging in 175 at-risk children and 62 comparison children aged 5-16. We observed significant age-by-group interactions in functional connectivity between two network pairs. Integration between the ventral attention and visual networks and segregation of the limbic and fronto-parietal networks increased with age in our comparison sample, relative to at-risk children. Furthermore, functional connectivity between the ventral attention and visual networks in comparison children significantly mediated age-related improvements in executive function, compared to at-risk children. We conclude that integration between ICNs show divergent neurodevelopmental trends in the broad population of children experiencing cognitive difficulties, and that these differences in functional brain organisation may partly explain the pervasive cognitive difficulties within this group over childhood and adolescence.
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Affiliation(s)
- Jonathan S Jones
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Duncan E Astle
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
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38
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Mukherjee P, Vilgis V, Rhoads S, Chahal R, Fassbender C, Leibenluft E, Dixon JF, Pakyurek M, van den Bos W, Hinshaw SP, Guyer AE, Schweitzer JB. Associations of Irritability With Functional Connectivity of Amygdala and Nucleus Accumbens in Adolescents and Young Adults With ADHD. J Atten Disord 2022; 26:1040-1050. [PMID: 34724835 PMCID: PMC8957582 DOI: 10.1177/10870547211057074] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
OBJECTIVE Irritability is a common characteristic in ADHD. We examined whether dysfunction in neural connections supporting threat and reward processing was related to irritability in adolescents and young adults with ADHD. METHOD We used resting-state fMRI to assess connectivity of amygdala and nucleus accumbens seeds in those with ADHD (n = 34) and an age- and gender-matched typically-developing comparison group (n = 34). RESULTS In those with ADHD, irritability was associated with atypical functional connectivity of both seed regions. Amygdala seeds showed greater connectivity with right inferior frontal gyrus and caudate/putamen, and less connectivity with precuneus. Nucleus accumbens seeds showed altered connectivity with middle temporal gyrus and precuneus. CONCLUSION The irritability-ADHD presentation is associated with atypical functional connectivity of reward and threat processing regions with cognitive control and emotion processing regions. These patterns provide novel evidence for irritability-associated neural underpinnings in adolescents and young adults with ADHD. The findings suggest cognitive and behavioral treatments that address response to reward, including omission of an expected reward and irritability, may be beneficial for ADHD.
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Affiliation(s)
| | | | - Shawn Rhoads
- University of California, Davis, CA, USA,Georgetown University, Washington, DC, USA
| | - Rajpreet Chahal
- University of California, Davis, CA, USA,Stanford University, Palo Alto, CA, USA
| | | | - Ellen Leibenluft
- The National Institutes of Mental Health, United States Department of Health and Human Services, Bethesda, MD, USA
| | | | | | | | - Stephen P. Hinshaw
- University of California, Berkeley, CA, USA,University of California, San Francisco, USA
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Heterogeneity in caregiving-related early adversity: Creating stable dimensions and subtypes. Dev Psychopathol 2022; 34:621-634. [PMID: 35314012 PMCID: PMC9492894 DOI: 10.1017/s0954579421001668] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Early psychosocial adversities exist at many levels, including caregiving-related, extrafamilial, and sociodemographic, which despite their high interrelatedness may have unique impacts on development. In this paper, we focus on caregiving-related early adversities (crEAs) and parse the heterogeneity of crEAs via data reduction techniques that identify experiential cooccurrences. Using network science, we characterized crEA cooccurrences to represent the comorbidity of crEA experiences across a sample of school-age children (n = 258; 6-12 years old) with a history of crEAs. crEA dimensions (variable level) and crEA subtypes (subject level) were identified using parallel factor analysis/principal component analysis and graph-based Louvain community detection. Bagging enhancement with cross-validation provided estimates of robustness. These data-driven dimensions/subtypes showed evidence of stability, transcended traditional sociolegally defined groups, were more homogenous than sociolegally defined groups, and reduced statistical correlations with sociodemographic factors. Finally, random forests showed both unique and common predictive importance of the crEA dimensions/subtypes for childhood mental health symptoms and academic skills. These data-driven outcomes provide additional tools and recommendations for crEA data reduction to inform precision medicine efforts in this area.
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Colonna S, Eyre O, Agha SS, Thapar A, van Goozen S, Langley K. Investigating the associations between irritability and hot and cool executive functioning in those with ADHD. BMC Psychiatry 2022; 22:166. [PMID: 35247998 PMCID: PMC8898423 DOI: 10.1186/s12888-022-03818-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 02/24/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Irritability is especially pertinent to those with Attention Deficit Hyperactivity Disorder (ADHD) as it is highly prevalent and associated with a more severe clinical presentation and poorer longitudinal outcomes. Preliminary evidence suggests that top-down cognitive processes taking place in emotional contexts (i.e., hot executive functions) as opposed to those evoked in abstract scenarios (i.e., cool executive functions) may be relevant to the presentation of irritability in ADHD. This study explored the cognitive mechanisms underlying irritability in young people with ADHD, hypothesising that irritability would be associated with hot, but not cool, executive function impairments. METHODS Our sample included 219 individuals with ADHD. A composite irritability score was derived extracting items from a parent interview, with scores ranging from 0 to 5. Associations were investigated using linear regression analyses, between irritability and four hot tasks measuring sensitivity to risk, risk-taking behaviour following reward or punishment, acceptance of reward delay and reaction to unfair behaviour from others, and two cool tasks measuring set-shifting and motor inhibition. RESULTS As hypothesised, there were no significant associations between irritability and cool executive functions in those with ADHD; however, contrary to expectations, there was also no significant evidence that hot executive functions were associated with irritability. CONCLUSIONS These results, in a large well characterised sample and using a comprehensive task battery, suggest that the variation in irritability in those with ADHD may not be associated with differences in hot or cool executive function performance.
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Affiliation(s)
- Silvia Colonna
- grid.5600.30000 0001 0807 5670School of Psychology, Cardiff University, Tower Building, 70 Park Place, Cardiff, CF10 3AT UK
| | - Olga Eyre
- grid.5600.30000 0001 0807 5670MRC Centre for Psychiatric Genetics & Genomics, Division of Psychological Medicine, School of Medicine, Cardiff University, Maindy Road, Cardiff, UK
| | - Sharifah Shameem Agha
- grid.5600.30000 0001 0807 5670MRC Centre for Psychiatric Genetics & Genomics, Division of Psychological Medicine, School of Medicine, Cardiff University, Maindy Road, Cardiff, UK ,Cwm Taf Morgannwg University Health Board, Pontypridd, Wales, UK
| | - Anita Thapar
- grid.5600.30000 0001 0807 5670School of Psychology, Cardiff University, Tower Building, 70 Park Place, Cardiff, CF10 3AT UK ,grid.5600.30000 0001 0807 5670MRC Centre for Psychiatric Genetics & Genomics, Division of Psychological Medicine, School of Medicine, Cardiff University, Maindy Road, Cardiff, UK
| | - Stephanie van Goozen
- grid.5600.30000 0001 0807 5670School of Psychology, Cardiff University, Tower Building, 70 Park Place, Cardiff, CF10 3AT UK
| | - Kate Langley
- School of Psychology, Cardiff University, Tower Building, 70 Park Place, Cardiff, CF10 3AT, UK. .,MRC Centre for Psychiatric Genetics & Genomics, Division of Psychological Medicine, School of Medicine, Cardiff University, Maindy Road, Cardiff, UK.
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Emotional regulation and psychomotor development after threatening preterm labor: a prospective study. Eur Child Adolesc Psychiatry 2022; 31:473-481. [PMID: 33585967 DOI: 10.1007/s00787-021-01733-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Accepted: 01/28/2021] [Indexed: 01/09/2023]
Abstract
A threatened preterm labor (TPL) represents an adverse prenatal event that may affect fetal neurodevelopment, even in absence of prematurity. Indeed, late-preterm infants, without neurological complications, also exhibit neurodevelopment impairment with psychomotor delay as well as emotional regulation disturbances, considered early manifestations of neuropsychiatric disorders. The aim of this study is to examine the impact of TPL on infant's psychomotor development and temperament. This prospective cohort study recruited mothers who suffered from a TPL and a control group of mothers without TPL and full-term gestation (n = 61). TPL infants were classified into three groups depending on delivery time: Full-Term (n = 37), Late-Preterm (n = 66), and Very-Preterm (n = 38). Neurodevelopmental assessment was performed at 6 months using the Ages & Stages Questionnaires for psychomotor development and the Infant Behaviour Questionnaire-Revised for temperament. After controlling for potential cofounders (multiple pregnancy and in vitro fertilization), Full-Term TPL infants, relative to the control group, exhibited development delay in Communication (p = 0.044) and Personal-social domains (p = 0.005) as well as temperament disturbances with higher Negative Affect (p = 0.013), lower Positive Affect (p = 0.010), and worse Emotional Regulation (p < 0.001) compared to Control. No differences were found between Full-Term and Late-Preterm TPL infants. TPL may represent a risk factor for neurodevelopmental disturbances in the offspring, affecting both psychomotor and emotional infant competences, even when infants were born at term.
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Biele G, Overgaard KR, Friis S, Zeiner P, Aase H. Cognitive, emotional, and social functioning of preschoolers with attention deficit hyperactivity problems. BMC Psychiatry 2022; 22:78. [PMID: 35105343 PMCID: PMC8808769 DOI: 10.1186/s12888-021-03638-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 11/30/2021] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Attention Deficit Hyperactivity Disorder (ADHD) is associated with deficits in different functional domains. It remains unclear if deficits in different domains are equally strong in early childhood, and which deficits are specific to ADHD. Here, we describe functional domains in preschoolers and assess deficits in children with ADHD problems, by comparing them to preschoolers with other mental health problems or who develop typically. METHODS The ADHD Study assessed 1195 ca. 3.5 years old preschoolers through a semi-structured parent interview, parent questionnaires, and with neuropsychological tests. We determined functional domains by applying factor analytic methods to a broad set of questionnaire- and test-scales. Using resulting factor scores, we employed a Bayesian hierarchical regression to estimate functional deficits in children with ADHD. RESULTS We found that preschoolers' functioning could be described along the seven relatively independent dimensions activity level and regulation, executive function, cognition, language, emotion regulation, introversion, and sociability. Compared to typically developing preschoolers, those with ADHD had deficits in all domains except introversion and sociability. Only deficits in activity level regulation and executive functions were larger than 0.5 standardised mean deviations and larger than deficits of children with other mental health problems. CONCLUSIONS Preschoolers with ADHD have deficits in multiple functional domains, but only impairments in activity level and regulation and executive functions are specific for ADHD and large enough to be clinically significant. Research on functioning in these domains will be important for understanding the development of ADHD, and for improving treatment and prevention approaches.
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Affiliation(s)
- Guido Biele
- Norwegian Institute of Public Health, Oslo, Norway.
| | | | - Svein Friis
- grid.55325.340000 0004 0389 8485Oslo University Hospital, Oslo, Norway
| | - Pal Zeiner
- grid.55325.340000 0004 0389 8485Oslo University Hospital, Oslo, Norway
| | - Heidi Aase
- grid.418193.60000 0001 1541 4204Norwegian Institute of Public Health, Oslo, Norway
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Introduction to the Special Section: What Do We Know About the Psychophysiology of Child Psychopathy and Conduct Problems? JOURNAL OF PSYCHOPATHOLOGY AND BEHAVIORAL ASSESSMENT 2022. [DOI: 10.1007/s10862-021-09950-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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Carta A, Vainieri I, Rommel AS, Zuddas A, Kuntsi J, Sotgiu S, Adamo N. Temperament Dimensions and Awakening Cortisol Levels in Attention-Deficit/Hyperactivity Disorder. Front Psychiatry 2022; 13:803001. [PMID: 35546956 PMCID: PMC9081759 DOI: 10.3389/fpsyt.2022.803001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 03/28/2022] [Indexed: 11/25/2022] Open
Abstract
OBJECTIVE To investigate whether temperament dimensions, Effortful Control (EC), Surgency-Extraversion (SE), and Negative Affectivity (NA), are associated with attention-deficit/hyperactivity disorder (ADHD) and how they relate to awakening cortisol levels, as a proxy measure of peripheral arousal. METHODS Parent-rated temperament and saliva samples were collected from 55 children with ADHD and 65 age-matched controls. RESULTS Compared to controls, youths with ADHD showed lower EC, higher NA, and lower awakening cortisol levels but did not differ in SE. Similar findings emerged in dimensional analyses linking temperament traits to inattention and hyperactivity-impulsivity symptoms. The results remained unchanged when controlling for the presence of co-occurring opposition-defiance and anxiety traits, as well as medication status. Temperament dimensions were not associated with cortisol levels. CONCLUSIONS Poor temperamental emotional and cognitive self-regulation showed significant associations with ADHD but did not appear to be linked to the under-arousal typically seen in ADHD.
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Affiliation(s)
- Alessandra Carta
- Child Neuropsychiatry Unit, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy.,Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Isabella Vainieri
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.,South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
| | - Anna-Sophie Rommel
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Alessandro Zuddas
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy.,Child and Adolescent Neuropsychiatry Unit, 'A.Cao', Paediatric Hospital, 'G. Brotzu' Hospital Trust, Cagliari, Italy
| | - Jonna Kuntsi
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Stefano Sotgiu
- Child Neuropsychiatry Unit, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy
| | - Nicoletta Adamo
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.,South London and Maudsley National Health Service Foundation Trust, London, United Kingdom
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Suk JW, Poppert Cordts KM, Garvey W, Lerdahl A, Soltis-Vaughan B, Bohn A, Edwards R, Blair RJ, Hwang S, Hwang S. Research Audit on Clinical Utility of Dimensional Disruptive Mood and Behavior Psychopathologies in Child and Adolescent Psychiatry Practice. Front Psychiatry 2022; 13:742148. [PMID: 35463527 PMCID: PMC9020472 DOI: 10.3389/fpsyt.2022.742148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 02/15/2022] [Indexed: 11/13/2022] Open
Abstract
To investigate the utility of dimensional psychopathologies of disruptive mood and behavior disorders (DBDs) by applying latent profile analysis (LPA) for characterization of youth referred to the tertiary outpatient clinic of child and adolescent psychiatry clinic and pharmacological treatment choices. One hundred fifty-eight children and adolescents with significant DBDs symptoms participated. Core dimensional psychopathologies of DBDs (irritability, callous-unemotional trait, and reactive-proactive aggressive behavior), DSM diagnoses, prescribed medications, and behavioral and emotional problems (Child Behavior Checklist, CBCL) were measured at baseline (clinic intake) and at 3-month follow-up. Latent Profile Analysis (LPA) was applied to characterize the study population based on the levels and interrelations among the core dimensional DBDs psychopathologies. Following LPA, the differences in clinical and treatment features between the latent classes were analyzed. LPA revealed two latent classes based on severity of DBDs symptoms. Class 1 (the moderate group) was characterized by relatively low scores on all trans-diagnostic indicators, whereas class 2 (the severe/critical group) showed higher levels of the dimensional psychopathologies and the majority of CBCL subscales. In addition, the severe/critical group was more often prescribed antipsychotic medications, and also experienced more frequent medication changes (addition, increasing the dose, and trial of different medications). Our findings suggested that application of LPA to a cluster of dimensional DBDs psychopathologies may provide valuable characterization of the youths referred to a tertiary outpatient child and adolescent psychiatric clinic, and offer insight into the providers' decision making on psychotropic medications, by overall severity of these psychopathologies rather than by single categorical diagnosis or single externalizing psychopathology.
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Affiliation(s)
- Ji-Woo Suk
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, NE, United States
| | | | - William Garvey
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, NE, United States
| | - Arica Lerdahl
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, NE, United States
| | | | - Alexandra Bohn
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, NE, United States
| | - Ryan Edwards
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, NE, United States
| | - Robert James Blair
- Child and Adolescent Mental Health Centre, Mental Health Services, Capital Region of Denmark, Copenhagen, Denmark
| | - Soonjo Hwang
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, NE, United States
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Radhoe TA, Agelink van Rentergem JA, Kok AAL, Huisman M, Geurts HM. Subgroups in Late Adulthood Are Associated With Cognition and Wellbeing Later in Life. Front Psychol 2021; 12:780575. [PMID: 34925184 PMCID: PMC8671814 DOI: 10.3389/fpsyg.2021.780575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 11/08/2021] [Indexed: 12/05/2022] Open
Abstract
Objectives: In this study, we aim to discover whether there are valid subgroups in aging that are defined by modifiable factors and are determinant of clinically relevant outcomes regarding healthy aging. Method: Data from interviews were collected in the Longitudinal Aging Study Amsterdam at two measurement occasions with a 3-year interval. Input for the analyses were seven well-known vulnerability and protective factors of healthy aging. By means of community detection, we tested whether we could distinguish subgroups in a sample of 1478 participants (T1-sample, aged 61–101 years). We tested both the external validity (T1) and predictive validity (T2) for wellbeing and subjective cognitive decline. Moreover, replicability and long-term stability were determined in 1186 participants (T2-sample, aged 61–101 years). Results: Three similar subgroups were identified at T1 and T2. Subgroup A was characterized by high levels of education with personal vulnerabilities, subgroup B by being physically active with low support and low levels of education, and subgroup C by high levels of support with low levels of education. Subgroup C showed the lowest wellbeing and memory profile, both at T1 and T2. On most measures of wellbeing and memory, subgroups A and B did not differ from each other. At T2, the same number of subgroups was identified and subgroup profiles at T1 and T2 were practically identical. Per T1 subgroup 47–62% retained their membership at T2. Discussion: We identified valid subgroups that replicate over time and differ on external variables at current and later measurement occasions. Individual change in subgroup membership over time shows that transitions to subgroups with better outcomes are possible.
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Affiliation(s)
- Tulsi A Radhoe
- Dutch Autism and ADHD Research Center (d'Arc), Department of Psychology, Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Joost A Agelink van Rentergem
- Dutch Autism and ADHD Research Center (d'Arc), Department of Psychology, Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Almar A L Kok
- Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam UMC - Location VU University Medical Center, Amsterdam, Netherlands.,Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Public Health, Amsterdam, Netherlands
| | - Martijn Huisman
- Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam UMC - Location VU University Medical Center, Amsterdam, Netherlands.,Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Sociology, Amsterdam Public Health, Amsterdam, Netherlands
| | - Hilde M Geurts
- Dutch Autism and ADHD Research Center (d'Arc), Department of Psychology, Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands.,Leo Kannerhuis (Youz/Parnassia Groep), Amsterdam, Netherlands
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Longitudinal network model of the co-development of temperament, executive functioning, and psychopathology symptoms in youth with and without ADHD. Dev Psychopathol 2021; 33:1803-1820. [DOI: 10.1017/s0954579421000900] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
AbstractAttention-deficit hyperactivity disorder (ADHD) is a common, chronic, and impairing disorder, yet presentations of ADHD and clinical course are highly heterogeneous. Despite substantial research efforts, both (a) the secondary co-occurrence of ADHD and complicating additional clinical problems and (b) the developmental pathways leading toward or away from recovery through adolescence remain poorly understood. Resolving these requires accounting for transactional influences of a large number of features across development. Here, we applied a longitudinal cross-lagged panel network model to a multimodal, multilevel dataset in a well-characterized sample of 488 children (nADHD = 296) to test Research Domain Criteria initiative-inspired hypotheses about transdiagnostic risk. Network features included Diagnostic and Statistical Manual of Mental Disorders symptoms, trait-based ratings of emotional functioning (temperament), and performance-based measures of cognition. Results confirmed that ADHD symptom domains, temperamental irritability, and working memory are independent transdiagnostic risk factors for psychopathology based on their direct associations with other features across time. ADHD symptoms and working memory each had direct, independent associations with depression. Results also demonstrated tightly linked co-development of ADHD symptoms and temperamental irritability, consistent with the possibility that this type of anger dysregulation is a core feature that is co-expressed as part of the ADHD phenotype for some children.
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Naim R, Goodwin MS, Dombek K, Revzina O, Agorsor C, Lee K, Zapp C, Freitag GF, Haller SP, Cardinale E, Jangraw D, Brotman MA. Cardiovascular reactivity as a measure of irritability in a transdiagnostic sample of youth: Preliminary associations. Int J Methods Psychiatr Res 2021; 30:e1890. [PMID: 34390050 PMCID: PMC8633925 DOI: 10.1002/mpr.1890] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 06/22/2021] [Accepted: 07/23/2021] [Indexed: 12/17/2022] Open
Abstract
OBJECTIVES Irritability is a transdiagnostic symptom in developmental psychopathology, conceptualized as a low threshold for frustration and increased proneness to anger. While central to emotion regulation, there is a vital need for empirical studies to explore the relationship between irritability and underlying physiological mechanisms of cardiovascular arousal. METHODS We examined the relationship between irritability and cardiovascular arousal (i.e., heart rate [HR] and heart rate variability [HRV]) in a transdiagnostic sample of 51 youth (M = 12.63 years, SD = 2.25; 62.7% male). Data was collected using the Empatica E4 during a laboratory stop-signal task. In addition, the impact of motion activity, age, medication, and sleep on cardiovascular responses was explored. RESULTS Main findings showed that irritability was associated with increased HR and decreased HRV during task performance. CONCLUSIONS Findings support the role of peripheral physiological dysregulation in youth with emotion regulation problems and suggest the potential use of available wearable consumer electronics as an objective measure of irritability and physiological arousal in a transdiagnostic sample of youth.
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Affiliation(s)
- Reut Naim
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, USA
| | - Matthew S Goodwin
- Department of Health Sciences, Khoury College of Computer Sciences, Northeastern University, Boston, Massachusetts, USA
| | - Kelly Dombek
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, USA
| | - Olga Revzina
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, USA
| | - Courtney Agorsor
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, USA
| | - Kyunghun Lee
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, USA
| | - Christian Zapp
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, USA
| | - Gabrielle F Freitag
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, USA
| | - Simone P Haller
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, USA
| | - Elise Cardinale
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, USA
| | - David Jangraw
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, USA
| | - Melissa A Brotman
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, USA
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Crum KI, Hwang S, Blair KS, Aloi JM, Meffert H, White SF, Tyler PM, Leibenluft E, Pope K, Blair RJR. Interaction of irritability and anxiety on emotional responding and emotion regulation: a functional MRI study. Psychol Med 2021; 51:2778-2788. [PMID: 32584213 PMCID: PMC7759590 DOI: 10.1017/s0033291720001397] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 04/17/2020] [Accepted: 04/29/2020] [Indexed: 01/14/2023]
Abstract
BACKGROUND Irritability and anxiety frequently co-occur in pediatric populations. Studies separately looking at the neural correlates of these symptoms have identified engagement of similar neural systems - particularly those implicated in emotional processing. Both irritability and anxiety can be considered negative valence emotional states that might relate to emotion dysregulation. However, previous work has not examined the neural responding during the performance of an emotion regulation task as a function of interaction between irritability and anxiety simultaneously. METHODS This fMRI study involved 155 participants (90 with significant psychopathologies and 92 male) who performed the Affective Stroop Task, designed to engage emotion regulation as a function of task demands. The Affective Reactivity Index (ARI) was used to index irritability and the Screen for Child Anxiety Related Emotional Disorders (SCARED) was used to index anxiety. RESULTS Levels of irritability, but not anxiety, was positively correlated with responses to visual images within the right rostro-medial prefrontal cortex and left anterior cingulate cortex during view trials. The second region of ventral anterior cingulate cortex showed a condition-by-emotion-by-ARI score-by-SCARED score interaction. Specifically, anxiety level was significantly correlated with a decreased differential BOLD response to negative relative to neutral view trials but only in the presence of relatively high irritability. CONCLUSIONS Atypical maintenance of emotional stimuli within the rostro-medial prefrontal cortex may exacerbate the difficulties faced by adolescents with irritability. Moreover, increased anxiety combined with significant irritability may disrupt an automatic emotional conflict-based form of emotion regulation that is particularly associated with the ventral anterior cingulate cortex.
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Affiliation(s)
- Kathleen I. Crum
- Medical University of South Carolina, Charleston, South Carolina, USA
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, Nebraska, USA
| | - Soonjo Hwang
- University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Karina S. Blair
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, Nebraska, USA
| | | | | | - Stuart F. White
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, Nebraska, USA
| | - Patrick M. Tyler
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, Nebraska, USA
| | - Ellen Leibenluft
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, Maryland, USA
| | - Kayla Pope
- Medical College of Wisconsin, Northeastern Wisconsin Psychiatry Training Program, Winnebago, Wisconsin, USA
| | - R. J. R. Blair
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, Nebraska, USA
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Jones JS, The Calm Team, Astle DE. A transdiagnostic data-driven study of children's behaviour and the functional connectome. Dev Cogn Neurosci 2021; 52:101027. [PMID: 34700195 PMCID: PMC8551598 DOI: 10.1016/j.dcn.2021.101027] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 10/06/2021] [Accepted: 10/19/2021] [Indexed: 10/24/2022] Open
Abstract
Behavioural difficulties are seen as hallmarks of many neurodevelopmental conditions. Differences in functional brain organisation have been observed in these conditions, but little is known about how they are related to a child's profile of behavioural difficulties. We investigated whether behavioural difficulties are associated with how the brain is functionally organised in an intentionally heterogeneous and transdiagnostic sample of 957 children aged 5-15. We used consensus community detection to derive data-driven profiles of behavioural difficulties and constructed functional connectomes from a subset of 238 children with resting-state functional Magnetic Resonance Imaging (fMRI) data. We identified three distinct profiles of behaviour that were characterised by principal difficulties with hot executive function, cool executive function, and learning. Global organisation of the functional connectome did not differ between the groups, but multivariate patterns of connectivity at the level of Intrinsic Connectivity Networks (ICNs), nodes, and hubs significantly predicted group membership in held-out data. Fronto-parietal connector hubs were under-connected in all groups relative to a comparison sample and children with hot vs cool executive function difficulties were distinguished by connectivity in ICNs associated with cognitive control, emotion processing, and social cognition. This demonstrates both general and specific neurodevelopmental risk factors in the functional connectome.
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Affiliation(s)
- Jonathan S Jones
- MRC Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge CB2 7EF, UK.
| | - The Calm Team
- MRC Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge CB2 7EF, UK
| | - Duncan E Astle
- MRC Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge CB2 7EF, UK
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