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Thieux M, Lioret J, Bouet R, Guyon A, Lachaux JP, Herbillon V, Franco P. Behavioral and Electrophysiological Markers of Attention Fluctuations in Children with Hypersomnolence. J Clin Med 2024; 13:5077. [PMID: 39274290 PMCID: PMC11395852 DOI: 10.3390/jcm13175077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2024] [Revised: 08/23/2024] [Accepted: 08/24/2024] [Indexed: 09/16/2024] Open
Abstract
Background. No device is yet available to effectively capture the attentional repercussions of hypersomnolence (HYP). The present study aimed to compare attentional performance of children with HYP, attention deficit hyperactivity disorder (ADHD), and controls using behavioral and electrophysiological (EEG) markers, and to assess their relationship with conventional sleepiness measurements. Methods. Children with HYP underwent a multiple sleep latency test (MSLT) and completed the adapted Epworth sleepiness scale (AESS). Along with age-matched children with ADHD, they were submitted to a resting EEG followed by the Bron-Lyon Attention Stability Test (BLAST). The control group only performed the BLAST. Multivariate models compared reaction time (RT), error percentage, BLAST-Intensity, BLAST-Stability, theta activity, and theta/beta ratio between groups. Correlations between these measures and conventional sleepiness measurements were conducted in children with HYP. Results. Children with HYP had lower RT and BLAST-Stability than controls but showed no significant difference in BLAST/EEG markers compared to children with ADHD. The AESS was positively correlated with the percentage of errors and negatively with BLAST-Intensity. Conclusions. Children with HYP showed impulsivity and attention fluctuations, without difference from children with ADHD for BLAST/EEG markers. The BLAST-EEG protocol could be relevant for the objective assessment of attentional fluctuations related to hypersomnolence.
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Affiliation(s)
- Marine Thieux
- Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Université Claude Bernard Lyon 1, 69500 Lyon, France
- Unité de Sommeil Pédiatrique, Service d'épileptologie Clinique, des Troubles du Sommeil et de Neurologie Fonctionnelle de l'enfant, Hôpital Femme-Mère-Enfant, Hospices Civils de Lyon, 69500 Lyon, France
| | - Julien Lioret
- Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Université Claude Bernard Lyon 1, 69500 Lyon, France
- Unité de Sommeil Pédiatrique, Service d'épileptologie Clinique, des Troubles du Sommeil et de Neurologie Fonctionnelle de l'enfant, Hôpital Femme-Mère-Enfant, Hospices Civils de Lyon, 69500 Lyon, France
| | - Romain Bouet
- Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Université Claude Bernard Lyon 1, 69500 Lyon, France
| | - Aurore Guyon
- Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Université Claude Bernard Lyon 1, 69500 Lyon, France
- Unité de Sommeil Pédiatrique, Service d'épileptologie Clinique, des Troubles du Sommeil et de Neurologie Fonctionnelle de l'enfant, Hôpital Femme-Mère-Enfant, Hospices Civils de Lyon, 69500 Lyon, France
| | - Jean-Philippe Lachaux
- Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Université Claude Bernard Lyon 1, 69500 Lyon, France
| | - Vania Herbillon
- Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Université Claude Bernard Lyon 1, 69500 Lyon, France
- Unité de Sommeil Pédiatrique, Service d'épileptologie Clinique, des Troubles du Sommeil et de Neurologie Fonctionnelle de l'enfant, Hôpital Femme-Mère-Enfant, Hospices Civils de Lyon, 69500 Lyon, France
| | - Patricia Franco
- Centre de Recherche en Neurosciences de Lyon, INSERM U1028, CNRS UMR5292, Université Claude Bernard Lyon 1, 69500 Lyon, France
- Unité de Sommeil Pédiatrique, Service d'épileptologie Clinique, des Troubles du Sommeil et de Neurologie Fonctionnelle de l'enfant, Hôpital Femme-Mère-Enfant, Hospices Civils de Lyon, 69500 Lyon, France
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Bogdańska-Chomczyk E, Wojtacha P, Tsai ML, Huang ACW, Kozłowska A. Age-related changes in the architecture and biochemical markers levels in motor-related cortical areas of SHR rats-an ADHD animal model. Front Mol Neurosci 2024; 17:1414457. [PMID: 39246601 PMCID: PMC11378348 DOI: 10.3389/fnmol.2024.1414457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Accepted: 06/25/2024] [Indexed: 09/10/2024] Open
Abstract
Introduction Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder whose exact pathophysiology has not been fully understood yet. Numerous studies have suggested disruptions in the cellular architecture and neuronal activity within brain structures of individuals with ADHD, accompanied by imbalances in the immune system, oxidative stress, and metabolism. Methods This study aims to assess two functionally and histologically distinct brain areas involved in motor control and coordination: the motor cortex (MC) and prefrontal cortex (PFC). Namely, the morphometric analysis of the MC throughout the developmental stages of Spontaneously Hypertensive Rats (SHRs) and Wistar Kyoto Rats (WKYs). Additionally, the study aimed to investigate the levels and activities of specific immune, oxidative stress, and metabolic markers in the PFC of juvenile and maturing SHRs in comparison to WKYs. Results The most significant MC volume reductions occurred in juvenile SHRs, accompanied by alterations in neuronal density in these brain areas compared to WKYs. Furthermore, juvenile SHRs exhibit heightened levels and activity of various markers, including interleukin-1α (IL-1α), IL-6, serine/threonine-protein mammalian target of rapamycin, RAC-alpha serine/threonine-protein kinase, glucocorticoid receptor β, malondialdehyde, sulfhydryl groups, superoxide dismutase, peroxidase, glutathione reductase, glutathione S-transferase, glucose, fructosamine, iron, lactic acid, alanine, aspartate transaminase, and lactate dehydrogenase. Discussion Significant changes in the MC morphometry and elevated levels of inflammatory, oxidative, and metabolic markers in PFC might be associated with disrupted brain development and maturation in ADHD.
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Affiliation(s)
- E Bogdańska-Chomczyk
- Department of Human Physiology and Pathophysiology, School of Medicine, Collegium Medicum, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland
| | - P Wojtacha
- Department of Psychology and Sociology of Health and Public Health, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland
| | - M L Tsai
- Department of Biomechatronic Engineering, National Ilan University, Yilan, Taiwan
| | - A C W Huang
- Department of Psychology, Fo Guang University, Yilan, Taiwan
| | - A Kozłowska
- Department of Human Physiology and Pathophysiology, School of Medicine, Collegium Medicum, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland
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Göttlich M, Chatterjee K, Moran C, Heldmann M, Rogge B, Cirkel A, Brabant G, Münte TF. Altered brain functional connectivity in patients with resistance to thyroid hormone ß. PLoS One 2024; 19:e0306538. [PMID: 39172991 PMCID: PMC11341041 DOI: 10.1371/journal.pone.0306538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 06/19/2024] [Indexed: 08/24/2024] Open
Abstract
To investigate changes in brain network organization and possible neurobehavioral similarities to attention-deficit hyperactivity disorder (ADHD), we measured changes in brain resting-state functional connectivity (rs-fMRI) and cognitive domains in patients with resistance to thyroid hormone β (RTHβ) and compared them with those in healthy control subjects. In this prospective case-control study, twenty-one participants with genetically confirmed RTHβ were matched with 21 healthy controls. The Adult ADHD Self-Report Scale (ASRS-v1.1) and ADHD Rating Scale-IV were used to assess self-reported symptoms of ADHD. A voxel-wise and atlas-based approach was used to identify changes in the brain networks. The RTHβ group reported behavioral symptoms similar to those of ADHD. We found evidence of weaker network integration of the lingual and fusiform gyri in the RTHβ group, which was mainly driven by weaker connectivity to the bilateral insula and supplementary motor cortex. Functional connectivity between regions of the default mode network (angular gyrus/middle temporal gyrus) and regions of the cognitive control network (bilateral middle frontal gyrus) was increased in RTHβ patients compared to healthy controls. Increased connectivity between regions of the default mode network and the dorsolateral prefrontal cortex is frequently reported in ADHD and is interpreted to be associated with deficits in attention. Our finding of weaker connectivity of the lingual gyrus to the bilateral insula (salience network) in RTHβ patients has also been reported previously in ADHD and may reflect decreased habituation to visual stimuli and increased distractibility. Overall, our observations support the notion of neuropsychological similarities between RTHβ and ADHD.
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Affiliation(s)
- Martin Göttlich
- Institute of Medical Psychology, University of Lübeck, Lübeck, Germany
- Center of Brain, Behavior and Metabolism, University of Lübeck, Lübeck, Germany
| | - Krishna Chatterjee
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Carla Moran
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Marcus Heldmann
- Department of Neurology, University of Lübeck, Lübeck, Germany
- Department of Psychology II, University of Lübeck, Lübeck, Germany
| | - Berenike Rogge
- Department of Neurology, University of Lübeck, Lübeck, Germany
| | - Anna Cirkel
- Department of Neurology, University of Lübeck, Lübeck, Germany
| | - Georg Brabant
- Department of Internal Medicine I, University of Lübeck, Lübeck, Germany
| | - Thomas F. Münte
- Center of Brain, Behavior and Metabolism, University of Lübeck, Lübeck, Germany
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Wang Y, Chen H, Wang C, Liu J, Miao P, Wei Y, Wu L, Wang X, Wang P, Zhang Y, Cheng J, Fan S, Sun G. Static and dynamic interactions within the triple-network model in stroke patients with multidomain cognitive impairments. Neuroimage Clin 2024; 43:103655. [PMID: 39146837 PMCID: PMC11367478 DOI: 10.1016/j.nicl.2024.103655] [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: 04/26/2024] [Revised: 07/23/2024] [Accepted: 08/07/2024] [Indexed: 08/17/2024]
Abstract
BACKGROUND Internal capsule strokes often result in multidomain cognitive impairments across memory, attention, and executive function, typically due to disruptions in brain network connectivity. Our study examines these impairments by analyzing interactions within the triple-network model, focusing on both static and dynamic aspects. METHODS We collected resting-state fMRI data from 62 left (CI_L) and 56 right (CI_R) internal capsule stroke patients, along with 57 healthy controls (HC). Using independent component analysis to extract the default mode (DMN), executive control (ECN), and salience networks (SAN), we conducted static and dynamic functional network connectivity analyses (DFNC) to identify differences between stroke patients and controls. For DFNC, we used k-means clustering to focus on temporal properties and multilayer network analysis to examine integration and modularity Q, where integration represents dynamic interactions between networks, and modularity Q measures how well the network is divided into distinct modules. We then calculated the correlations between SFNC/DFNC properties with significant inter-group differences and cognitive scales. RESULTS Compared to HC, both CI_L and CI_R patients showed increased static FCs between SAN and DMN and decreased dynamic interactions between ECN and other networks. CI_R patients also had heightened static FCs between SAN and ECN and maintained a state with strongly positive FNCs across all networks in the triple-network model. Additionally, CI_R patients displayed decreased modularity Q. CONCLUSION These findings highlight that stroke can result in the disruption of static and dynamic interactions in the triple network model, aiding our understanding of the neuropathological basis for multidomain cognitive deficits after internal capsule stroke.
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Affiliation(s)
- Yingying Wang
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Hongxu Chen
- Cardiff University Brain Research Imaging Centre, United Kingdom
| | - Caihong Wang
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingchun Liu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Peifang Miao
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Ying Wei
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Luobing Wu
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xin Wang
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Peipei Wang
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Zhang
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingliang Cheng
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| | - Siyuan Fan
- Cardiovascular Center, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Guifang Sun
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Henan Province 450052, China.
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Chen B, Sun W, Yan C. Controllability in attention deficit hyperactivity disorder brains. Cogn Neurodyn 2024; 18:2003-2013. [PMID: 39104674 PMCID: PMC11297865 DOI: 10.1007/s11571-023-10063-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 11/23/2023] [Accepted: 12/19/2023] [Indexed: 08/07/2024] Open
Abstract
The role of network metrics in exploring brain networks of mental illness is crucial. This study focuses on quantifying a node controllability index (CA-scores) and developing a novel framework for studying the dysfunction of attention deficit hyperactivity disorder (ADHD) brains. By analyzing fMRI data from 143 healthy controls and 102 ADHD patients, the controllability metric reveals distinct differences in nodes (brain regions) and subsystems (functional modules). There are significantly atypical CA-scores in the Rolandic operculum, superior medial orbitofrontal cortex, insula, posterior cingulate gyrus, supramarginal gyrus, angular gyrus, precuneus, heschl gyrus, and superior temporal gyrus of ADHD patients. A comparison with measures of connection strength, eigenvector centrality, and topology entropy suggests that the controllability index may be more effective in identifying abnormal regions in ADHD brains. Furthermore, our controllability index could be extended to investigate functional networks associated with other psychiatric disorders. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-023-10063-z.
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Affiliation(s)
- Bo Chen
- Department of Mathematics, School of Science, Hangzhou Dianzi University, Hangzhou, 310018 People’s Republic of China
| | - Weigang Sun
- Department of Mathematics, School of Science, Hangzhou Dianzi University, Hangzhou, 310018 People’s Republic of China
| | - Chuankui Yan
- College of Mathematics and Physics, Wenzhou University, Wenzhou, 325024 People’s Republic of China
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Laatsch J, Stein F, Maier S, Matthies S, Sobanski E, Alm B, Tebartz van Elst L, Krug A, Philipsen A. Neural correlates of inattention in adults with ADHD. Eur Arch Psychiatry Clin Neurosci 2024:10.1007/s00406-024-01872-2. [PMID: 39073447 DOI: 10.1007/s00406-024-01872-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 07/15/2024] [Indexed: 07/30/2024]
Abstract
In the last two decades, numerous magnetic resonance imaging (MRI) studies have examined differences in cortical structure between individuals with Attention-Deficit/Hyperactivity Disorder (ADHD) and healthy controls. These studies primarily emphasized alterations in gray matter volume (GMV) and cortical thickness (CT). Still, the scientific literature is notably scarce in regard to investigating associations of cortical structure with ADHD psychopathology, specifically inattention within adults with ADHD. The present study aimed to elucidate neurobiological underpinnings of inattention beyond GMV and CT by including cortical gyrification, sulcal depth, and fractal dimension. Building upon the Comparison of Methylphenidate and Psychotherapy in Adult ADHD Study (COMPAS), cortical structure parameters were investigated using 141 T1-weighted anatomical scans of adult patients with ADHD. All brain structural analyses were performed using the threshold-free cluster enhancement (TFCE) approach and the Computational Anatomy Toolbox (CAT12) integrated into the Statistical Parametric Mapping Software (Matlab Version R2021a). Results revealed significant correlations of inattention in multiple brain regions. Cortical gyrification was negatively correlated, whereas cortical thickness and fractal dimension were positively associated with inattention. The clusters showed widespread distribution across the cerebral cortex, with both hemispheres affected. The cortical regions most prominently affected included the precuneus, para-, pre-, and postcentral gyri, superior parietal lobe, and posterior cingulate cortex. This study highlights the importance of cortical alterations in attentional processes in adults with ADHD. Further research in this area is warranted to elucidate intricacies of inattention in adults with ADHD to potentially enhance diagnostic accuracy and inform personalized treatment strategies.
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Affiliation(s)
- Jonathan Laatsch
- Department of Psychiatry und Psychotherapy, University Hospital Bonn, Bonn, Germany.
| | - Frederike Stein
- Department of Psychiatry und Psychotherapy, University of Marburg, Marburg, Germany
| | - Simon Maier
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
| | - Swantje Matthies
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
| | - Esther Sobanski
- Department of Child and Adolescent Psychiatry Lucerne, Lucerne, Switzerland
- Department of Psychiatry and Psychotherapy, Medical Faculty of Mannheim, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Barbara Alm
- Department of Psychiatry and Psychotherapy, Medical Faculty of Mannheim, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Ludger Tebartz van Elst
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
| | - Axel Krug
- Department of Psychiatry und Psychotherapy, University Hospital Bonn, Bonn, Germany
| | - Alexandra Philipsen
- Department of Psychiatry und Psychotherapy, University Hospital Bonn, Bonn, Germany
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Yu J, Xu Q, Ma L, Huang Y, Zhu W, Liang Y, Wang Y, Tang W, Zhu C, Jiang X. Convergent functional change of frontoparietal network in obsessive-compulsive disorder: a voxel-based meta-analysis. Front Psychiatry 2024; 15:1401623. [PMID: 39041046 PMCID: PMC11260709 DOI: 10.3389/fpsyt.2024.1401623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Accepted: 06/11/2024] [Indexed: 07/24/2024] Open
Abstract
Background Obsessive-compulsive disorder (OCD) is a chronic psychiatric illness with complex clinical manifestations. Cognitive dysfunction may underlie OC symptoms. The frontoparietal network (FPN) is a key region involved in cognitive control. However, the findings of impaired FPN regions have been inconsistent. We employed meta-analysis to identify the fMRI-specific abnormalities of the FPN in OCD. Methods PubMed, Web of Science, Scopus, and EBSCOhost were searched to screen resting-state functional magnetic resonance imaging (rs-fMRI) studies exploring dysfunction in the FPN of OCD patients using three indicators: the amplitude of low-frequency fluctuation/fractional amplitude of low-frequency fluctuation (ALFF/fALFF), regional homogeneity (ReHo) and functional connectivity (FC). We compared all patients with OCD and control group in a primary analysis, and divided the studies by medication in secondary meta-analyses with the activation likelihood estimation (ALE) algorithm. Results A total of 31 eligible studies with 1359 OCD patients (756 men) and 1360 healthy controls (733 men) were included in the primary meta-analysis. We concluded specific changes in brain regions of FPN, mainly in the left dorsolateral prefrontal cortex (DLPFC, BA9), left inferior frontal gyrus (IFG, BA47), left superior temporal gyrus (STG, BA38), right posterior cingulate cortex (PCC, BA29), right inferior parietal lobule (IPL, BA40) and bilateral caudate. Additionally, altered connectivity within- and between-FPN were observed in the bilateral DLPFC, right cingulate gyrus and right thalamus. The secondary analyses showed improved convergence relative to the primary analysis. Conclusion OCD patients showed dysfunction FPN, including impaired local important nodal brain regions and hypoconnectivity within the FPN (mainly in the bilateral DLPFC), during the resting state. Moreover, FPN appears to interact with the salience network (SN) and default mode network (DMN) through pivotal brain regions. Consistent with the hypothesis of fronto-striatal circuit dysfunction, especially in the dorsal cognitive circuit, these findings provide strong evidence for integrating two pathophysiological models of OCD.
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Affiliation(s)
- Jianping Yu
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Qianwen Xu
- School of Psychology, Nanjing Normal University, Nanjing, China
| | - Lisha Ma
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yueqi Huang
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Wenjing Zhu
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yan Liang
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yunzhan Wang
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Wenxin Tang
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Cheng Zhu
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xiaoying Jiang
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
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Chen P, Wang J, Tang G, Chen G, Xiao S, Guo Z, Qi Z, Wang J, Wang Y. Large-scale network abnormality in behavioral addiction. J Affect Disord 2024; 354:743-751. [PMID: 38521138 DOI: 10.1016/j.jad.2024.03.034] [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: 08/22/2023] [Revised: 03/01/2024] [Accepted: 03/09/2024] [Indexed: 03/25/2024]
Abstract
BACKGROUND Researchers have endeavored to ascertain the network dysfunction associated with behavioral addiction (BA) through the utilization of resting-state functional connectivity (rsFC). Nevertheless, the identification of aberrant patterns within large-scale networks pertaining to BA has proven to be challenging. METHODS Whole-brain seed-based rsFC studies comparing subjects with BA and healthy controls (HC) were collected from multiple databases. Multilevel kernel density analysis was employed to ascertain brain networks in which BA was linked to hyper-connectivity or hypo-connectivity with each prior network. RESULTS Fifty-six seed-based rsFC publications (1755 individuals with BA and 1828 HC) were included in the meta-analysis. The present study indicate that individuals with BAs exhibit (1) hypo-connectivity within the fronto-parietal network (FN) and hypo- and hyper-connectivity within the ventral attention network (VAN); (2) hypo-connectivity between the FN and regions of the VAN, hypo-connectivity between the VAN and regions of the FN and default mode network (DMN), hyper-connectivity between the DMN and regions of the FN; (3) hypo-connectivity between the reward system and regions of the sensorimotor network (SS), DMN and VAN; (4) hypo-connectivity between the FN and regions of the SS, hyper-connectivity between the VAN and regions of the SS. CONCLUSIONS These findings provide impetus for a conceptual framework positing a model of BA characterized by disconnected functional coordination among large-scale networks.
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Affiliation(s)
- Pan Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Junjing Wang
- Department of Applied Psychology, Guangdong University of Foreign Studies, Guangzhou 510006, China
| | - Guixian Tang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Guanmao Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Shu Xiao
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Zixuan Guo
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Zhangzhang Qi
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Jurong Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Ying Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China.
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Du J, Liu Y, Zhu W. The altered functional status in vestibular migraine: A meta-analysis. Brain Behav 2024; 14:e3591. [PMID: 38849984 PMCID: PMC11161393 DOI: 10.1002/brb3.3591] [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: 12/03/2023] [Revised: 05/07/2024] [Accepted: 05/16/2024] [Indexed: 06/09/2024] Open
Abstract
PURPOSE Vestibular migraine (VM) is a disorder with prominent vestibular symptoms that are causally correlated with migraine and is the most prevalent neurological cause of episodic vertigo. Nevertheless, the functional underpinnings of VM remain largely unclear. This study aimed to reveal concordant alteration patterns of functional connectivity (FC) in VM patients. METHODS We searched literature measuring resting-state FC abnormalities of VM patients in PubMed, Embase, Cochrane, and Scopus databases before May 2023. Furthermore, we applied the anisotropic effect size-signed differential mapping (AES-SDM) to conduct a whole-brain voxel-wise meta-analysis to identify the convergence of FC alterations in VM patients. RESULTS Nine studies containing 251 VM patients and 257 healthy controls (HCs) were included. Relative to HCs, VM patients showed reduced activity in the left superior temporal gyrus and left midcingulate/paracingulate gyri, and increased activity in the precuneus, right superior parietal gyrus, and right middle frontal gyrus. Jackknife's analysis and subgroup analysis further supported the generalization and robustness of the main results. Furthermore, meta-regression analyses indicated that the Dizziness Handicap Inventory (DHI) ratings were positively correlated with the activity in the precuneus, while higher Headache Impact Test-6 and DHI scores were associated with lower activity within the left midcingulate/paracingulate gyri. CONCLUSIONS The study indicates that VM is associated with specific functional deficits of VM patients in crucial regions involved in the vestibular and pain networks and provides further information on the pathophysiological mechanisms of VM.
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Affiliation(s)
- Junyong Du
- Department of Neurology, Tongji Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Yong Liu
- School of Artificial IntelligenceBeijing University of Posts and TelecommunicationsBeijingChina
- School of Artificial IntelligenceUniversity of Chinese Academy of SciencesBeijingChina
| | - Wenhao Zhu
- Department of Neurology, Tongji Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
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10
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Chen Z, Xu T, Liu X, Becker B, Li W, Xia L, Zhao W, Zhang R, Huo Z, Hu B, Tang Y, Xiao Z, Feng Z, Chen J, Feng T. Cortical gradient perturbation in attention deficit hyperactivity disorder correlates with neurotransmitter-, cell type-specific and chromosome- transcriptomic signatures. Psychiatry Clin Neurosci 2024; 78:309-321. [PMID: 38334172 DOI: 10.1111/pcn.13649] [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: 10/03/2023] [Revised: 01/16/2024] [Accepted: 01/18/2024] [Indexed: 02/10/2024]
Abstract
AIMS This study aimed to illuminate the neuropathological landscape of attention deficit hyperactivity disorder (ADHD) by a multiscale macro-micro-molecular perspective from in vivo neuroimaging data. METHODS The "ADHD-200 initiative" repository provided multi-site high-quality resting-state functional connectivity (rsfc-) neuroimaging for ADHD children and matched typically developing (TD) cohort. Diffusion mapping embedding model to derive the functional connectome gradient detecting biologically plausible neural pattern was built, and the multivariate partial least square method to uncover the enrichment of neurotransmitomic, cellular and chromosomal gradient-transcriptional signatures of AHBA enrichment and meta-analytic decoding. RESULTS Compared to TD, ADHD children presented connectopic cortical gradient perturbations in almost all the cognition-involved brain macroscale networks (all pBH <0.001), but not in the brain global topology. As an intermediate phenotypic variant, such gradient perturbation was spatially enriched into distributions of GABAA/BZ and 5-HT2A receptors (all pBH <0.01) and co-varied with genetic transcriptional expressions (e.g. DYDC2, ATOH7, all pBH <0.01), associated with phenotypic variants in episodic memory and emotional regulations. Enrichment models demonstrated such gradient-transcriptional variants indicated the risk of both cell-specific and chromosome- dysfunctions, especially in enriched expression of oligodendrocyte precursors and endothelial cells (all pperm <0.05) as well enrichment into chromosome 18, 19 and X (pperm <0.05). CONCLUSIONS Our findings bridged brain macroscale neuropathological patterns to microscale/cellular biological architectures for ADHD children, demonstrating the neurobiologically pathological mechanism of ADHD into the genetic and molecular variants in GABA and 5-HT systems as well brain-derived enrichment of specific cellular/chromosomal expressions.
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Affiliation(s)
- Zhiyi Chen
- Experimental Research Center of Medical and Psychological Science, School of Psychology, Third Military Medical University, Chongqing, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Ting Xu
- Department of Psychology, The University of Hong Kong, Hong Kong, China
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Xuerong Liu
- Experimental Research Center of Medical and Psychological Science, School of Psychology, Third Military Medical University, Chongqing, China
| | - Benjamin Becker
- Department of Psychology, The University of Hong Kong, Hong Kong, China
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Wei Li
- Experimental Research Center of Medical and Psychological Science, School of Psychology, Third Military Medical University, Chongqing, China
| | - Lei Xia
- Experimental Research Center of Medical and Psychological Science, School of Psychology, Third Military Medical University, Chongqing, China
| | - Wenqi Zhao
- Experimental Research Center of Medical and Psychological Science, School of Psychology, Third Military Medical University, Chongqing, China
| | - Rong Zhang
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Zhenzhen Huo
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Bowen Hu
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Yancheng Tang
- School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Zhibing Xiao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Zhengzhi Feng
- Experimental Research Center of Medical and Psychological Science, School of Psychology, Third Military Medical University, Chongqing, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Ji Chen
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China
- Department of Psychiatry, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China
| | - Tingyong Feng
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
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11
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Zhang F, Li Y, Liu L, Liu Y, Wang P, Biswal BB. Corticostriatal causality analysis in children and adolescents with attention-deficit/hyperactivity disorder. Psychiatry Clin Neurosci 2024; 78:291-299. [PMID: 38444215 PMCID: PMC11469573 DOI: 10.1111/pcn.13650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 12/26/2023] [Accepted: 01/16/2024] [Indexed: 03/07/2024]
Abstract
AIM The effective connectivity between the striatum and cerebral cortex has not been fully investigated in attention-deficit/hyperactivity disorder (ADHD). Our objective was to explore the interaction effects between diagnosis and age on disrupted corticostriatal effective connectivity and to represent the modulation function of altered connectivity pathways in children and adolescents with ADHD. METHODS We performed Granger causality analysis on 300 participants from a publicly available Attention-Deficit/Hyperactivity Disorder-200 dataset. By computing the correlation coefficients between causal connections between striatal subregions and other cortical regions, we estimated the striatal inflow and outflow connection to represent intermodulation mechanisms in corticostriatal pathways. RESULTS Interactions between diagnosis and age were detected in the superior occipital gyrus within the visual network, medial prefrontal cortex, posterior cingulate gyrus, and inferior parietal lobule within the default mode network, which is positively correlated with hyperactivity/impulsivity severity in ADHD. Main effect of diagnosis exhibited a general higher cortico-striatal causal connectivity involving default mode network, frontoparietal network and somatomotor network in ADHD compared with comparisons. Results from high-order effective connectivity exhibited a disrupted information pathway involving the default mode-striatum-somatomotor-striatum-frontoparietal networks in ADHD. CONCLUSION The interactions detected in the visual-striatum-default mode networks pathway appears to be related to the potential distraction caused by long-term abnormal information input from the retina in ADHD. Higher causal connectivity and weakened intermodulation may indicate the pathophysiological process that distractions lead to the impairment of motion planning function and the inhibition/control of this unplanned motion signals in ADHD.
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Affiliation(s)
- Fanyu Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology. University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Yilu Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology. University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Lin Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology. University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Yefen Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology. University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Pan Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology. University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Bharat B. Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology. University of Electronic Science and Technology of China, Chengdu 611731, China
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, 07102, USA
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12
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Meghji S, Hilderley AJ, Murias K, Brooks BL, Andersen J, Fehlings D, Dlamini N, Kirton A, Carlson HL. Executive functioning, ADHD symptoms and resting state functional connectivity in children with perinatal stroke. Brain Imaging Behav 2024; 18:263-278. [PMID: 38038867 PMCID: PMC11156742 DOI: 10.1007/s11682-023-00827-w] [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] [Accepted: 11/19/2023] [Indexed: 12/02/2023]
Abstract
Perinatal stroke describes a group of focal, vascular brain injuries that occur early in development, often resulting in lifelong disability. Two types of perinatal stroke predominate, arterial ischemic stroke (AIS) and periventricular venous infarction (PVI). Though perinatal stroke is typically considered a motor disorder, other comorbidities commonly exist including attention-deficit hyperactivity disorder (ADHD) and deficits in executive function. Rates of ADHD symptoms are higher in children with perinatal stroke and deficits in executive function may also occur but underlying mechanisms are not known. We measured resting state functional connectivity in children with perinatal stroke using previously established dorsal attention, frontoparietal, and default mode network seeds. Associations with parental ratings of executive function and ADHD symptoms were examined. A total of 120 participants aged 6-19 years [AIS N = 31; PVI N = 30; Controls N = 59] were recruited. In comparison to typically developing peers, both the AIS and PVI groups showed lower intra- and inter-hemispheric functional connectivity values in the networks investigated. Group differences in between-network connectivity were also demonstrated, showing weaker anticorrelations between task-positive (frontoparietal and dorsal attention) and task-negative (default mode) networks in stroke groups compared to controls. Both within-network and between-network functional connectivity values were highly associated with parental reports of executive function and ADHD symptoms. These results suggest that differences in functional connectivity exist both within and between networks after perinatal stroke, the degree of which is associated with ADHD symptoms and executive function.
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Affiliation(s)
- Suraya Meghji
- Calgary Pediatric Stroke Program, Alberta Children's Hospital, 28 Oki Drive NW, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, 28 Oki Drive NW, Calgary, AB, Canada
| | - Alicia J Hilderley
- Calgary Pediatric Stroke Program, Alberta Children's Hospital, 28 Oki Drive NW, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, 28 Oki Drive NW, Calgary, AB, Canada
- Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Kara Murias
- Alberta Children's Hospital Research Institute, 28 Oki Drive NW, Calgary, AB, Canada
- Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - Brian L Brooks
- Alberta Children's Hospital Research Institute, 28 Oki Drive NW, Calgary, AB, Canada
- Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
- Neurosciences Program, Alberta Children's Hospital, Calgary, AB, Canada
- Department of Psychology, University of Calgary, Calgary, AB, Canada
| | - John Andersen
- Department of Pediatrics, University of Alberta, Edmonton, AB, Canada
| | - Darcy Fehlings
- Department of Pediatrics, University of Toronto, Toronto, ON, Canada
| | - Nomazulu Dlamini
- Department of Pediatrics, University of Toronto, Toronto, ON, Canada
- Children's Stroke Program, Division of Neurology, Hospital for Sick Children, Toronto, ON, Canada
| | - Adam Kirton
- Calgary Pediatric Stroke Program, Alberta Children's Hospital, 28 Oki Drive NW, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, 28 Oki Drive NW, Calgary, AB, Canada
- Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
- Department of Radiology, University of Calgary, Calgary, AB, Canada
| | - Helen L Carlson
- Calgary Pediatric Stroke Program, Alberta Children's Hospital, 28 Oki Drive NW, Calgary, AB, Canada.
- Alberta Children's Hospital Research Institute, 28 Oki Drive NW, Calgary, AB, Canada.
- Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.
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13
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Zhang R, Murray SB, Duval CJ, Wang DJJ, Jann K. Functional connectivity and complexity analyses of resting-state fMRI in pre-adolescents demonstrating the behavioral symptoms of ADHD. Psychiatry Res 2024; 334:115794. [PMID: 38367454 PMCID: PMC10947856 DOI: 10.1016/j.psychres.2024.115794] [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: 05/11/2023] [Revised: 01/31/2024] [Accepted: 02/11/2024] [Indexed: 02/19/2024]
Abstract
Attention deficit hyperactivity disorder (ADHD) has been characterized by impairments among distributed functional brain networks, e.g., the frontoparietal network (FPN), default mode network (DMN), reward and motivation-related circuits (RMN), and salience network (SAL). In the current study, we evaluated the complexity and functional connectivity (FC) of resting state fMRI (rsfMRI) in pre-adolescents with the behavioral symptoms of ADHD, for pathology-relevant networks. We leveraged data from the Adolescent Brain and Cognitive Development (ABCD) Study. The final study sample included 63 children demonstrating the behavioral features of ADHD and 92 healthy control children matched on age, sex, and pubertal development status. For selected regions in the relevant networks, ANCOVA compared multiscale entropy (MSE) and FC between the groups. Finally, differences in the association between MSE and FC were evaluated. We found significantly reduced MSE along with increased FC within the FPN of pre-adolescents demonstrating the behavior symptoms of ADHD compared to matched healthy controls. Significant partial correlations between MSE and FC emerged in the FPN and RMN in the healthy controls however the association was absent in the participants demonstrating the behavior symptoms of ADHD. The current findings of complexity and FC in ADHD pathology support hypotheses of altered function of inhibitory control networks in ADHD.
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Affiliation(s)
- Ru Zhang
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
| | - Stuart B Murray
- Department of Psychiatry and Behavioral Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Christina J Duval
- Department of Psychology, St. Louis University, St. Louis, MO, United States
| | - Danny J J Wang
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States
| | - Kay Jann
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States
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14
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Su S, Zhao J, Dai Y, Lin L, Zhou Q, Yan Z, Qian L, Cui W, Liu M, Zhang H, Yang Z, Chen Y. Altered neurovascular coupling in the children with attention-deficit/hyperactivity disorder: a comprehensive fMRI analysis. Eur Child Adolesc Psychiatry 2024; 33:1081-1091. [PMID: 37222790 DOI: 10.1007/s00787-023-02238-0] [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: 11/25/2022] [Accepted: 05/17/2023] [Indexed: 05/25/2023]
Abstract
The coupling between resting-state cerebral blood flow (CBF) and blood oxygenation level-dependent (BOLD) signals reflects the mechanism of neurovascular coupling (NVC), which have not been illustrated in attention-deficit/hyperactivity disorder (ADHD). Fifty ADHD and 42 age- and gender-matched typically developing controls (TDs) were enrolled. The NVC imaging metrics were investigated by exploring the Pearson correlation coefficients between CBF and BOLD-derived quantitative maps (ALFF, fALFF, DCP maps). Three types of NVC metrics (CBF-ALFF, CBF-fALFF, CBF-DCP coupling) were compared between ADHD and TDs group, and the inner association between altered NVC metrics and clinical variables in ADHD group was further analyzed. Compared to TDs, ADHD showed significantly reduced whole-brain CBF-ALFF coupling (P < 0.001). Among regional level (all PFDR < 0.05), ADHD showed significantly lower CBF-ALFF coupling in bilateral thalamus, default-mode network (DMN) involving left anterior cingulate (ACG.L) and right parahippocampal gyrus (PHG.R), execution control network (ECN) involving right middle orbital frontal gyrus (ORBmid.R) and right inferior frontal triangular gyrus (IFGtriang.R), and increased CBF-ALFF coupling in attention network (AN)-related left superior temporal gyrus (STG.L) and somatosensory network (SSN))-related left rolandic operculum (ROL.L). Furthermore, increased CBF-fALFF coupling was found in the visual network (VN)-related left cuneus and negatively correlated with the concentration index of ADHD (R = - 0.299, PFDR = 0.035). Abnormal regional NVC metrics were at widespread neural networks in ADHD, mainly involved in DMN, ECN, SSN, AN, VN and bilateral thalamus. Notably, this study reinforced the insights into the neural basis and pathophysiological mechanism underlying ADHD.
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Affiliation(s)
- Shu Su
- Department of Radiology, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Jing Zhao
- Department of Radiology, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Yan Dai
- Department of Radiology, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Liping Lin
- Department of Radiology, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Qin Zhou
- Department of Radiology, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Zi Yan
- Department of Radiology, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Long Qian
- Department of Biomedical Engineering, College of Engineering, Peking University, Beijing, China
| | - Wei Cui
- Department of Biomedical Engineering, College of Engineering, Peking University, Beijing, China
| | - Meina Liu
- Department of Pediatric, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Hongyu Zhang
- Department of Pediatric, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Zhiyun Yang
- Department of Radiology, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
| | - Yingqian Chen
- Department of Radiology, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
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15
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Mooney MA, Hermosillo RJM, Feczko E, Miranda-Dominguez O, Moore LA, Perrone A, Byington N, Grimsrud G, Rueter A, Nousen E, Antovich D, Feldstein Ewing SW, Nagel BJ, Nigg JT, Fair DA. Cumulative Effects of Resting-State Connectivity Across All Brain Networks Significantly Correlate with Attention-Deficit Hyperactivity Disorder Symptoms. J Neurosci 2024; 44:e1202232023. [PMID: 38286629 PMCID: PMC10919250 DOI: 10.1523/jneurosci.1202-23.2023] [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: 04/19/2023] [Revised: 11/30/2023] [Accepted: 12/18/2023] [Indexed: 01/31/2024] Open
Abstract
Identification of replicable neuroimaging correlates of attention-deficit hyperactivity disorder (ADHD) has been hindered by small sample sizes, small effects, and heterogeneity of methods. Given evidence that ADHD is associated with alterations in widely distributed brain networks and the small effects of individual brain features, a whole-brain perspective focusing on cumulative effects is warranted. The use of large, multisite samples is crucial for improving reproducibility and clinical utility of brain-wide MRI association studies. To address this, a polyneuro risk score (PNRS) representing cumulative, brain-wide, ADHD-associated resting-state functional connectivity was constructed and validated using data from the Adolescent Brain Cognitive Development (ABCD, N = 5,543, 51.5% female) study, and was further tested in the independent Oregon-ADHD-1000 case-control cohort (N = 553, 37.4% female). The ADHD PNRS was significantly associated with ADHD symptoms in both cohorts after accounting for relevant covariates (p < 0.001). The most predictive PNRS involved all brain networks, though the strongest effects were concentrated among the default mode and cingulo-opercular networks. In the longitudinal Oregon-ADHD-1000, non-ADHD youth had significantly lower PNRS (Cohen's d = -0.318, robust p = 5.5 × 10-4) than those with persistent ADHD (age 7-19). The PNRS, however, did not mediate polygenic risk for ADHD. Brain-wide connectivity was robustly associated with ADHD symptoms in two independent cohorts, providing further evidence of widespread dysconnectivity in ADHD. Evaluation in enriched samples demonstrates the promise of the PNRS approach for improving reproducibility in neuroimaging studies and unraveling the complex relationships between brain connectivity and behavioral disorders.
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Affiliation(s)
- Michael A Mooney
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon 97239
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon 97239
- Center for Mental Health Innovation, Oregon Health & Science University, Portland, Oregon 97239
| | - Robert J M Hermosillo
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota 55454
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
| | - Eric Feczko
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota 55454
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
| | - Oscar Miranda-Dominguez
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota 55454
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
- Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455
| | - Lucille A Moore
- Department of Neurology, Oregon Health & Science University, Portland, Oregon 97239
| | - Anders Perrone
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
| | - Nora Byington
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
| | - Gracie Grimsrud
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
| | - Amanda Rueter
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
| | - Elizabeth Nousen
- Center for Mental Health Innovation, Oregon Health & Science University, Portland, Oregon 97239
- Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, Oregon 97239
| | - Dylan Antovich
- Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, Oregon 97239
| | | | - Bonnie J Nagel
- Center for Mental Health Innovation, Oregon Health & Science University, Portland, Oregon 97239
- Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, Oregon 97239
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon 97239
| | - Joel T Nigg
- Center for Mental Health Innovation, Oregon Health & Science University, Portland, Oregon 97239
- Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, Oregon 97239
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon 97239
| | - Damien A Fair
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota 55454
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
- Institute of Child Development, College of Education and Human Development, University of Minnesota, Minneapolis, Minnesota 55455
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16
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Martino M, Magioncalda P. A three-dimensional model of neural activity and phenomenal-behavioral patterns. Mol Psychiatry 2024; 29:639-652. [PMID: 38114633 DOI: 10.1038/s41380-023-02356-w] [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: 07/18/2023] [Revised: 11/16/2023] [Accepted: 11/27/2023] [Indexed: 12/21/2023]
Abstract
How phenomenal experience and behavior are related to neural activity in physiology and psychopathology represents a fundamental question in neuroscience and psychiatry. The phenomenal-behavior patterns may be deconstructed into basic dimensions, i.e., psychomotricity, affectivity, and thought, which might have distinct neural correlates. This work provides a data overview on the relationship of these phenomenal-behavioral dimensions with brain activity across physiological and pathological conditions (including major depressive disorder, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, anxiety disorders, addictive disorders, Parkinson's disease, Tourette syndrome, Alzheimer's disease, and frontotemporal dementia). Accordingly, we propose a three-dimensional model of neural activity and phenomenal-behavioral patterns. In this model, neural activity is organized into distinct units in accordance with connectivity patterns and related input/output processing, manifesting in the different phenomenal-behavioral dimensions. (1) An external neural unit, which involves the sensorimotor circuit/brain's sensorimotor network and is connected with the external environment, processes external inputs/outputs, manifesting in the psychomotor dimension (processing of exteroception/somatomotor activity). External unit hyperactivity manifests in psychomotor excitation (hyperactivity/hyperkinesia/catatonia), while external unit hypoactivity manifests in psychomotor inhibition (retardation/hypokinesia/catatonia). (2) An internal neural unit, which involves the interoceptive-autonomic circuit/brain's salience network and is connected with the internal/body environment, processes internal inputs/outputs, manifesting in the affective dimension (processing of interoception/autonomic activity). Internal unit hyperactivity manifests in affective excitation (anxiety/dysphoria-euphoria/panic), while internal unit hypoactivity manifests in affective inhibition (anhedonia/apathy/depersonalization). (3) An associative neural unit, which involves the brain's associative areas/default-mode network and is connected with the external/internal units (but not with the environment), processes associative inputs/outputs, manifesting in the thought dimension (processing of ideas). Associative unit hyperactivity manifests in thought excitation (mind-wandering/repetitive thinking/psychosis), while associative unit hypoactivity manifests in thought inhibition (inattention/cognitive deficit/consciousness loss). Finally, these neural units interplay and dynamically combine into various neural states, resulting in the complex phenomenal experience and behavior across physiology and neuropsychiatric disorders.
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Affiliation(s)
- Matteo Martino
- Graduate Institute of Mind Brain and Consciousness, Taipei Medical University, Taipei, Taiwan.
| | - Paola Magioncalda
- Graduate Institute of Mind Brain and Consciousness, Taipei Medical University, Taipei, Taiwan.
- International Master/Ph.D. Program in Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.
- Department of Radiology, Taipei Medical University-Shuang Ho Hospital, New Taipei City, Taiwan.
- Department of Medical Research, Taipei Medical University-Shuang Ho Hospital, New Taipei City, Taiwan.
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17
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Faraone SV, Bellgrove MA, Brikell I, Cortese S, Hartman CA, Hollis C, Newcorn JH, Philipsen A, Polanczyk GV, Rubia K, Sibley MH, Buitelaar JK. Attention-deficit/hyperactivity disorder. Nat Rev Dis Primers 2024; 10:11. [PMID: 38388701 DOI: 10.1038/s41572-024-00495-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/16/2024] [Indexed: 02/24/2024]
Abstract
Attention-deficit/hyperactivity disorder (ADHD; also known as hyperkinetic disorder) is a common neurodevelopmental condition that affects children and adults worldwide. ADHD has a predominantly genetic aetiology that involves common and rare genetic variants. Some environmental correlates of the disorder have been discovered but causation has been difficult to establish. The heterogeneity of the condition is evident in the diverse presentation of symptoms and levels of impairment, the numerous co-occurring mental and physical conditions, the various domains of neurocognitive impairment, and extensive minor structural and functional brain differences. The diagnosis of ADHD is reliable and valid when evaluated with standard diagnostic criteria. Curative treatments for ADHD do not exist but evidence-based treatments substantially reduce symptoms and/or functional impairment. Medications are effective for core symptoms and are usually well tolerated. Some non-pharmacological treatments are valuable, especially for improving adaptive functioning. Clinical and neurobiological research is ongoing and could lead to the creation of personalized diagnostic and therapeutic approaches for this disorder.
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Affiliation(s)
- Stephen V Faraone
- Departments of Psychiatry and of Neuroscience and Physiology, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, USA.
| | - Mark A Bellgrove
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia
| | - Isabell Brikell
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Samuele Cortese
- Centre for Innovation in Mental Health, School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK
- Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of Medicine, University of Southampton, Southampton, UK
- Solent NHS Trust, Southampton, UK
- Hassenfeld Children's Hospital at NYU Langone, New York University Child Study Center, New York City, NY, USA
- DiMePRe-J-Department of Precision and Rigenerative Medicine-Jonic Area, University of Bari "Aldo Moro", Bari, Italy
| | - Catharina A Hartman
- Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Chris Hollis
- National Institute for Health and Care Research (NIHR) MindTech MedTech Co-operative and NIHR Nottingham Biomedical Research Centre, Institute of Mental Health, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Jeffrey H Newcorn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alexandra Philipsen
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
| | - Guilherme V Polanczyk
- Department of Psychiatry, Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil
| | - Katya Rubia
- Department of Child & Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neurosciences, King's College London, London, UK
- Department of Child & Adolescent Psychiatry, Transcampus Professor KCL-Dresden, Technical University, Dresden, Germany
| | | | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboudumc, Nijmegen, Netherlands
- Karakter Child and Adolescent Psychiatry University Center, Nijmegen, Netherlands
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18
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Shao G, Xu G, Huo C, Nie Z, Zhang Y, Yi L, Wang D, Shao Z, Weng S, Sun J, Li Z. Effect of the VR-guided grasping task on the brain functional network. BIOMEDICAL OPTICS EXPRESS 2024; 15:77-94. [PMID: 38223191 PMCID: PMC10783918 DOI: 10.1364/boe.504669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 11/20/2023] [Accepted: 11/21/2023] [Indexed: 01/16/2024]
Abstract
Virtual reality (VR) technology has been demonstrated to be effective in rehabilitation training with the assistance of VR games, but its impact on brain functional networks remains unclear. In this study, we used functional near-infrared spectroscopy imaging to examine the brain hemodynamic signals from 18 healthy participants during rest and grasping tasks with and without VR game intervention. We calculated and compared the graph theory-based topological properties of the brain networks using phase locking values (PLV). The results revealed significant differences in the brain network properties when VR games were introduced compared to the resting state. Specifically, for the VR-guided grasping task, the modularity of the brain network was significantly higher than the resting state, and the average clustering coefficient of the motor cortex was significantly lower compared to that of the resting state and the simple grasping task. Correlation analyses showed that a higher clustering coefficient, local efficiency, and modularity were associated with better game performance during VR game participation. This study demonstrates that a VR game task intervention can better modulate the brain functional network compared to simple grasping movements and may be more beneficial for the recovery of grasping abilities in post-stroke patients with hand paralysis.
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Affiliation(s)
- Guangjian Shao
- School of Mechatronic Engineering and Automation, Foshan University, Foshan, China
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids, Beijing, China
| | - Gongcheng Xu
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids, Beijing, China
| | - Congcong Huo
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids, Beijing, China
| | - Zichao Nie
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids, Beijing, China
| | - Yizheng Zhang
- School of Mechatronic Engineering and Automation, Foshan University, Foshan, China
| | - Li Yi
- School of Mechatronic Engineering and Automation, Foshan University, Foshan, China
| | - Dongyang Wang
- School of Mechatronic Engineering and Automation, Foshan University, Foshan, China
| | - Zhiyong Shao
- School of Mechatronic Engineering and Automation, Foshan University, Foshan, China
| | - Shanfan Weng
- School of Medicine, Foshan University, Foshan, China
| | - Jinyan Sun
- School of Medicine, Foshan University, Foshan, China
| | - Zengyong Li
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids, Beijing, China
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19
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Tolonen T, Roine T, Alho K, Leppämäki S, Tani P, Koski A, Laine M, Salmi J. Abnormal wiring of the structural connectome in adults with ADHD. Netw Neurosci 2023; 7:1302-1325. [PMID: 38144696 PMCID: PMC10631790 DOI: 10.1162/netn_a_00326] [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: 02/01/2023] [Accepted: 06/19/2023] [Indexed: 12/26/2023] Open
Abstract
Current knowledge of white matter changes in large-scale brain networks in adult attention-deficit/hyperactivity disorder (ADHD) is scarce. We collected diffusion-weighted magnetic resonance imaging data in 40 adults with ADHD and 36 neurotypical controls and used constrained spherical deconvolution-based tractography to reconstruct whole-brain structural connectivity networks. We used network-based statistic (NBS) and graph theoretical analysis to investigate differences in these networks between the ADHD and control groups, as well as associations between structural connectivity and ADHD symptoms assessed with the Adult ADHD Self-Report Scale or performance in the Conners Continuous Performance Test 2 (CPT-2). NBS revealed decreased connectivity in the ADHD group compared to the neurotypical controls in widespread unilateral networks, which included subcortical and corticocortical structures and encompassed dorsal and ventral attention networks and visual and somatomotor systems. Furthermore, hypoconnectivity in a predominantly left-frontal network was associated with higher amount of commission errors in CPT-2. Graph theoretical analysis did not reveal topological differences between the groups or associations between topological properties and ADHD symptoms or task performance. Our results suggest that abnormal structural wiring of the brain in adult ADHD is manifested as widespread intrahemispheric hypoconnectivity in networks previously associated with ADHD in functional neuroimaging studies.
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Affiliation(s)
- Tuija Tolonen
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Timo Roine
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
- Turku Brain and Mind Center, University of Turku, Turku, Finland
| | - Kimmo Alho
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
- AMI Centre, Aalto Neuroimaging, Aalto University, Espoo, Finland
| | | | - Pekka Tani
- Department of Psychiatry, Helsinki University Hospital, Helsinki, Finland
| | - Anniina Koski
- Department of Psychiatry, Helsinki University Hospital, Helsinki, Finland
| | - Matti Laine
- Turku Brain and Mind Center, University of Turku, Turku, Finland
- Department of Psychology, Åbo Akademi University, Turku, Finland
| | - Juha Salmi
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
- AMI Centre, Aalto Neuroimaging, Aalto University, Espoo, Finland
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20
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Feng Y, Zhu Y, Guo X, Luo X, Dang C, Liu Q, Xu C, Kang S, Yin G, Liang T, Wang Y, Liu L, Sun L. Exploring the Potential "Brain-Cognition-Behavior" Relationship in Children With ADHD Based on Resting-State Brain Local Activation and Functional Connectivity. J Atten Disord 2023; 27:1638-1649. [PMID: 37688472 DOI: 10.1177/10870547231197206] [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] [Indexed: 09/11/2023]
Abstract
OBJECTIVE Exploring how abnormal brain function in children with ADHD affects executive function and ultimately leads to behavioral impairment provides a theoretical basis for clinically targeted neurotherapy and cognitive training. METHOD Amplitude of low frequency fluctuations (ALFF), regional homogeneity (ReHo), and seed-based FC were analyzed in 53 ADHD and 52 healthy controls. The "brain-cognition-behavior" relationship was further explored using mediation analysis. RESULTS ADHD showed abnormal local activation in the middle temporal gyrus (MTG), inferior occipital gyrus and inferior frontal gyrus (IFG) and reduced FC between the IFG and the cerebellum. ADHD diagnosis may affect ALFF of MTG and further modulate shift and finally affect inattentive symptoms. It may also affect the total symptoms through the FC of the IFG with the cerebellum. CONCLUSION ADHD showed extensive spontaneous activity abnormalities and frontal-cerebellar FC impairments. Localized functional abnormalities in the MTG may affect the shift in EF, resulting in attention deficit behavior.
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Affiliation(s)
- Yuan Feng
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Yu Zhu
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Xiaojie Guo
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Xiangsheng Luo
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Chen Dang
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Qianrong Liu
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Chenyang Xu
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Simin Kang
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Gaohan Yin
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Taizhu Liang
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Yufeng Wang
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Lu Liu
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Li Sun
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorders & Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
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21
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Mulder D, Aarts E, Arias Vasquez A, Bloemendaal M. A systematic review exploring the association between the human gut microbiota and brain connectivity in health and disease. Mol Psychiatry 2023; 28:5037-5061. [PMID: 37479779 PMCID: PMC11041764 DOI: 10.1038/s41380-023-02146-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 06/02/2023] [Accepted: 06/16/2023] [Indexed: 07/23/2023]
Abstract
A body of pre-clinical evidence shows how the gut microbiota influence brain functioning, including brain connectivity. Linking measures of brain connectivity to the gut microbiota can provide important mechanistic insights into the bi-directional gut-brain communication. In this systematic review, we therefore synthesized the available literature assessing this association, evaluating the degree of consistency in microbiota-connectivity associations. Following the PRISMA guidelines, a PubMed search was conducted, including studies published up to September 1, 2022. We identified 16 studies that met the inclusion criteria. Several bacterial genera, including Prevotella, Bacteroides, Ruminococcus, Blautia, and Collinsella were most frequently reported in association with brain connectivity. Additionally, connectivity of the salience (specifically the insula and anterior cingulate cortex), default mode, and frontoparietal networks were most frequently associated with the gut microbiota, both in terms of microbial diversity and composition. There was no discernible pattern in the association between microbiota and brain connectivity. Altogether, based on our synthesis, there is evidence for an association between the gut microbiota and brain connectivity. However, many findings were poorly replicated across studies, and the specificity of the association is yet unclear. The current studies show substantial inter-study heterogeneity in methodology and reporting, limiting the robustness and reproducibility of the findings and emphasizing the need to harmonize methodological approaches. To enhance comparability and replicability, future research should focus on further standardizing processing pipelines and employing data-driven multivariate analysis strategies.
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Affiliation(s)
- Danique Mulder
- Department of Psychiatry, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands
| | - Esther Aarts
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Alejandro Arias Vasquez
- Department of Psychiatry, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands.
- Department of Human Genetics, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.
| | - Mirjam Bloemendaal
- Department of Psychiatry, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands
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22
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Hirata R, Yoshimura S, Kobayashi K, Aki M, Shibata M, Ueno T, Miyagi T, Oishi N, Murai T, Fujiwara H. Differences between subclinical attention-deficit/hyperactivity and autistic traits in default mode, salience, and frontoparietal network connectivities in young adult Japanese. Sci Rep 2023; 13:19724. [PMID: 37957246 PMCID: PMC10643712 DOI: 10.1038/s41598-023-47034-7] [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: 02/28/2023] [Accepted: 11/08/2023] [Indexed: 11/15/2023] Open
Abstract
Attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are associated with attentional impairments, with both commonalities and differences in the nature of their attention deficits. This study aimed to investigate the neural correlates of ADHD and ASD traits in healthy individuals, focusing on the functional connectivity (FC) of attention-related large-scale brain networks (LSBNs). The participants were 61 healthy individuals (30 men; age, 21.9 ± 1.9 years). The Adult ADHD Self-Report Scale (ASRS) and Autism Spectrum Quotient (AQ) were administered as indicators of ADHD and ASD traits, respectively. Performance in the continuous performance test (CPT) was used as a behavioural measure of sustained attentional function. Functional magnetic resonance imaging scans were performed during the resting state (Rest) and auditory oddball task (Odd). Considering the critical role in attention processing, we focused our analyses on the default mode (DMN), frontoparietal (FPN), and salience (SN) networks. Region of interest (ROI)-to-ROI analyses (false discovery rate < 0.05) were performed to determine relationships between psychological measures with within-network FC (DMN, FPN, and SN) as well as with between-network FC (DMN-FPN, DMN-SN, and FPN-SN). ASRS scores, but not AQ scores, were correlated with less frequent commission errors and shorter reaction times in the CPT. During Odd, significant positive correlations with ASRS were demonstrated in multiple FCs within DMN, while significant positive correlations with AQ were demonstrated in multiple FCs within FPN. AQs were negatively correlated with FPN-SN FCs. During Rest, AQs were negatively and positively correlated with one FC within the SN and multiple FCs between the DMN and SN, respectively. These findings of the ROI-to-ROI analysis were only partially replicated in a split-half replication analysis, a replication analysis with open-access data sets, and a replication analysis with a structure-based atlas. The better CPT performance by individuals with subclinical ADHD traits suggests positive effects of these traits on sustained attention. Differential associations between LSBN FCs and ASD/ADHD traits corroborate the notion of differences in sustained and selective attention between clinical ADHD and ASD.
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Affiliation(s)
- Risa Hirata
- Department of Neuropsychiatry, Kyoto University Hospital, 54 Shogoinkawaracho, Sakyo-ku, Kyoto, 6068397, Japan
| | - Sayaka Yoshimura
- Faculty of Human Health Science, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Organization for Promotion of Neurodevelopmental Disorder Research, Kyoto, Japan
| | - Key Kobayashi
- Department of Neuropsychiatry, Graduate School of Medicine, University of Kyoto, Kyoto, Japan
| | - Morio Aki
- Department of Neuropsychiatry, Graduate School of Medicine, University of Kyoto, Kyoto, Japan
| | - Mami Shibata
- Department of Neuropsychiatry, Graduate School of Medicine, University of Kyoto, Kyoto, Japan
| | - Tsukasa Ueno
- Department of Neuropsychiatry, Graduate School of Medicine, University of Kyoto, Kyoto, Japan
- Integrated Clinical Education Center, Kyoto University Hospital, Kyoto, Japan
| | - Takashi Miyagi
- Department of Neuropsychiatry, Graduate School of Medicine, University of Kyoto, Kyoto, Japan
| | - Naoya Oishi
- Medical Innovation Center, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Toshiya Murai
- Department of Neuropsychiatry, Kyoto University Hospital, 54 Shogoinkawaracho, Sakyo-ku, Kyoto, 6068397, Japan
- Department of Neuropsychiatry, Graduate School of Medicine, University of Kyoto, Kyoto, Japan
| | - Hironobu Fujiwara
- Department of Neuropsychiatry, Kyoto University Hospital, 54 Shogoinkawaracho, Sakyo-ku, Kyoto, 6068397, Japan.
- Department of Neuropsychiatry, Graduate School of Medicine, University of Kyoto, Kyoto, Japan.
- Artificial Intelligence Ethics and Society Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan.
- The General Research Division, Osaka University Research Center on Ethical, Legal and Social Issues, Kyoto, Japan.
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23
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Jones JS, Monaghan A, Leyland-Craggs A, Astle DE. Testing the triple network model of psychopathology in a transdiagnostic neurodevelopmental cohort. Neuroimage Clin 2023; 40:103539. [PMID: 37992501 PMCID: PMC10709083 DOI: 10.1016/j.nicl.2023.103539] [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: 11/02/2023] [Accepted: 11/07/2023] [Indexed: 11/24/2023]
Abstract
AIM The triple network model of psychopathology posits that altered connectivity between the Salience (SN), Central Executive (CEN), and Default Mode Networks (DMN) may underlie neurodevelopmental conditions. However, this has yet to be tested in a transdiagnostic sample of young people. METHOD We investigated this in 175 children (60 girls) that represent a heterogeneous population who are experiencing neurodevelopmental difficulties in cognition and behavior, and 60 comparison children (33 girls). Hyperactivity/impulsivity and inattention were assessed by parent-report. Resting-state functional Magnetic Resonance Imaging data were acquired and functional connectivity was calculated between independent network components and regions of interest. We then examined whether connectivity between the SN, CEN and DMN was dimensionally related to hyperactivity/impulsivity and inattention, whilst controlling for age, gender, and motion. RESULTS Hyperactivity/impulsivity was associated with increased functional connectivity between the SN, CEN, and DMN in at-risk children, whereas it was associated with decreased functional connectivity between the CEN and DMN in comparison children. These effects replicated in an adult parcellation of brain function and when using increasingly stringent exclusion criteria for in-scanner motion. CONCLUSION Triple network connectivity characterizes transdiagnostic neurodevelopmental difficulties with hyperactivity/impulsivity. We suggest that this may arise from delayed network segregation, difficulties sustaining CEN activity to regulate behavior, and/or a heightened developmental mismatch between neural systems implicated in cognitive control relative to those implicated in reward/affect processing.
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Affiliation(s)
- Jonathan S Jones
- MRC Cognition and Brain Sciences Unit, University of Cambridge, UK.
| | - Alicja Monaghan
- MRC Cognition and Brain Sciences Unit, University of Cambridge, UK
| | | | - Duncan E Astle
- MRC Cognition and Brain Sciences Unit, University of Cambridge, UK; Department of Psychiatry, University of Cambridge, UK
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24
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Luo N, Luo X, Zheng S, Yao D, Zhao M, Cui Y, Zhu Y, Calhoun VD, Sun L, Sui J. Aberrant brain dynamics and spectral power in children with ADHD and its subtypes. Eur Child Adolesc Psychiatry 2023; 32:2223-2234. [PMID: 35996018 PMCID: PMC10576687 DOI: 10.1007/s00787-022-02068-6] [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: 11/29/2021] [Accepted: 08/08/2022] [Indexed: 12/16/2022]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children, usually categorized as three subtypes, predominant inattention (ADHD-I), predominant hyperactivity-impulsivity (ADHD-HI), and a combined subtype (ADHD-C). Yet, common and unique abnormalities of electroencephalogram (EEG) across different subtypes remain poorly understood. Here, we leveraged microstate characteristics and power features to investigate temporal and frequency abnormalities in ADHD and its subtypes using high-density EEG on 161 participants (54 ADHD-Is and 53 ADHD-Cs and 54 healthy controls). Four EEG microstates were identified. The coverage of salience network (state C) were decreased in ADHD compared to HC (p = 1.46e-3), while the duration and contribution of frontal-parietal network (state D) were increased (p = 1.57e-3; p = 1.26e-4). Frequency power analysis also indicated that higher delta power in the fronto-central area (p = 6.75e-4) and higher power of theta/beta ratio in the bilateral fronto-temporal area (p = 3.05e-3) were observed in ADHD. By contrast, remarkable subtype differences were found primarily on the visual network (state B), of which ADHD-C have higher occurrence and coverage than ADHD-I (p = 9.35e-5; p = 1.51e-8), suggesting that children with ADHD-C might exhibit impulsivity of opening their eyes in an eye-closed experiment, leading to hyper-activated visual network. Moreover, the top discriminative features selected from support vector machine model with recursive feature elimination (SVM-RFE) well replicated the above results, which achieved an accuracy of 72.7% and 73.8% separately in classifying ADHD and two subtypes. To conclude, this study highlights EEG microstate dynamics and frequency features may serve as sensitive measurements to detect the subtle differences in ADHD and its subtypes, providing a new window for better diagnosis of ADHD.
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Affiliation(s)
- Na Luo
- Institute of Automation, Chinese Academy of Sciences, Brainnetome Center and National Laboratory of Pattern Recognition, Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiangsheng Luo
- Peking University Sixth Hospital and, Peking University Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University) and National Clinical Research Center for Mental Disorders, (Peking University Sixth Hospital), Beijing, 100191, China
| | - Suli Zheng
- Peking University Sixth Hospital and, Peking University Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University) and National Clinical Research Center for Mental Disorders, (Peking University Sixth Hospital), Beijing, 100191, China
| | - Dongren Yao
- Massachusetts Eye and Ear Infirmary, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, 02114, USA
| | - Min Zhao
- Institute of Automation, Chinese Academy of Sciences, Brainnetome Center and National Laboratory of Pattern Recognition, Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yue Cui
- Institute of Automation, Chinese Academy of Sciences, Brainnetome Center and National Laboratory of Pattern Recognition, Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yu Zhu
- Peking University Sixth Hospital and, Peking University Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University) and National Clinical Research Center for Mental Disorders, (Peking University Sixth Hospital), Beijing, 100191, China
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, 30303, USA
| | - Li Sun
- Peking University Sixth Hospital and, Peking University Institute of Mental Health, Beijing, 100191, China.
- NHC Key Laboratory of Mental Health (Peking University) and National Clinical Research Center for Mental Disorders, (Peking University Sixth Hospital), Beijing, 100191, China.
| | - Jing Sui
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, 30303, USA.
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
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25
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Hajebrahimi F, Gohel S, Scheiman M, Sangoi A, Iring-Sanchez S, Morales C, Santos EM, Alvarez TL. Altered Large-Scale Resting-State Functional Network Connectivity in Convergence Insufficiency Young Adults Compared With Binocularly Normal Controls. Invest Ophthalmol Vis Sci 2023; 64:29. [PMID: 37982763 PMCID: PMC10668612 DOI: 10.1167/iovs.64.14.29] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 10/26/2023] [Indexed: 11/21/2023] Open
Abstract
Purpose To investigate the underlying resting-state functional connectivity (RSFC) of symptomatic convergence insufficiency (CI) compared with binocularly normal controls (BNC) using functional magnetic resonance imaging (fMRI) under The Convergence Insufficiency Neuro‑mechanism Adult Population Study (NCT03593031). Methods A total of 101 participants were eligible for this study. After removing datasets with motion artifacts, 49 CI and 47 BNC resting-state functional magnetic resonance imaging datasets were analyzed. CI was diagnosed with the following signs: (1) receded near point of convergence of 6 cm or greater, (2) decreased positive fusional vergence of less than 15∆ or failing Sheard's criteria of twice the near phoria, (3) near phoria of at least 4∆ more exophoric compared with the distance phoria, and (4) symptoms using the Convergence Insufficiency Symptom Survey (score of ≥21). RSFC was assessed using a group-level independent components analysis and dual regression. A behavioral correlation analysis using linear regression method was performed between clinical measures and RSFC using the significant difference between the CI and BNC. Results On average, a decreased RSFC was observed within the frontoparietal network, default mode network and visual network in patients with CI, compared with the participants with BNC (P < 0.05, corrected for multiple comparisons). The default mode network RSFC strength was significantly correlated with the PFV, near point of convergence, and difference between the horizontal phoria at near compared with far (P < 0.05). Conclusions Results support altered RSFC in patients with CI compared with participants with BNC and suggest that these differences in underlying neurophysiology may in part be in connection with the differences in optometric visual function used to diagnose CI.
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Affiliation(s)
- Farzin Hajebrahimi
- Department of Health Informatics, Rutgers University School of Health Professions, Newark, New Jersey, United States
| | - Suril Gohel
- Department of Health Informatics, Rutgers University School of Health Professions, Newark, New Jersey, United States
| | - Mitchell Scheiman
- Pennsylvania College of Optometry, Salus University, Philadelphia, Pennsylvania, United States
| | - Ayushi Sangoi
- Biomedical Engineering, New Jersey Institute of Technology, Newark, New Jersey, United States
| | - Stephanie Iring-Sanchez
- Biomedical Engineering, New Jersey Institute of Technology, Newark, New Jersey, United States
| | - Cristian Morales
- Biomedical Engineering, New Jersey Institute of Technology, Newark, New Jersey, United States
| | - Elio M. Santos
- Biomedical Engineering, New Jersey Institute of Technology, Newark, New Jersey, United States
| | - Tara L. Alvarez
- Biomedical Engineering, New Jersey Institute of Technology, Newark, New Jersey, United States
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Su S, Chen Y, Qian L, Dai Y, Yan Z, Lin L, Zhang H, Liu M, Zhao J, Yang Z. Evaluation of individual-based morphological brain network alterations in children with attention-deficit/hyperactivity disorder: a multi-method investigation. Eur Child Adolesc Psychiatry 2023; 32:2281-2289. [PMID: 36056264 DOI: 10.1007/s00787-022-02072-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 08/19/2022] [Indexed: 11/03/2022]
Abstract
To investigate the topological organization of individual-based morphological brain networks (MBNs) in attention-deficit/hyperactivity disorder (ADHD) children with different methods. A total of 60 ADHD children and 60 typically developing (TD) controls matched for age and gender were enrolled. Each participant underwent a structural 3D T1-weighted scan. Based on the inter-regional morphological similarity of GM regions, Kullback-Leibler-based similarity (KLS), Multivariate Euclidean Distance (MED), and Tijms's method were used to construct individual-based MBNs, respectively. The between-group difference of global and nodal network topological profiles was estimated, and partial correlation analysis was used for further analysis. According to KLS and MED-based network, ADHD showed a decreased global efficiency (Eglob) and increased characteristic path length (Lp) compared to the TD group, while Tijms's method-based network showed no between-group difference in global and nodal profiles. Nodal profiles were significantly decreased in the bilateral caudate, and nodal efficiency of the bilateral caudate was negatively correlated with clinical symptom severity of ADHD (P < 0.05, FDR-corrected) by the KLS-based network. Nodal betweenness was significantly decreased in the left inferior occipital gyrus and correlated with clinical symptom severity of ADHD (P < 0.05, FDR-corrected) by the MED-based network. ADHD was found to have a significantly less integrated organization and a shift to a "weaker small-worldness" pattern, while abnormal nodal profiles were mainly in the corpus striatum and default-mode networks. Our study highlights the crucial role of abnormal morphological connectivity patterns in understanding the brain maturational effects in ADHD and enriching the insights into MBNs at an individual level.
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Affiliation(s)
- Shu Su
- Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Yingqian Chen
- Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Long Qian
- MR Research, GE Healthcare, Beijing, China
| | - Yan Dai
- Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Zi Yan
- Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Liping Lin
- Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Hongyu Zhang
- Department of Pediatric, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Meina Liu
- Department of Pediatric, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Jing Zhao
- Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
| | - Zhiyun Yang
- Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
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Abed M, Mansureh HH, Masoud GAL, Elaheh H, Mohammad-Hossein NHK, Yamin BD, Abdol-Hossein V. Construction of Meta-Thinking Educational Program Based on Mental-Brain Simulation ( MTMBS) and Evaluating its Effectiveness on Executive Functions, Emotion Regulation, and Impulsivity in Children With ADHD: A Resting-State Functional MRI Study. J Atten Disord 2023; 27:1223-1251. [PMID: 36843348 DOI: 10.1177/10870547231155436] [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: 02/28/2023]
Abstract
OBJECTIVE The aim of present research was to make a Meta-Thinking educational program based on mental-brain simulation and to evaluate its effectiveness on executive functions, emotion regulation and impulsivity in children with ADHD. METHODS The research method was Embedded Design: Embedded Experimental Model. The research sample included 32 children with ADHD who were randomly assigned to two experimental and control groups. The intervention was implemented for eight sessions of 1.5 hr for the experimental group, and fMRI images were taken from them, while the control group didn't receive any treatment. Finally, using semi-structured interviews, coherent information was collected from the parents of the experimental group about the changes made. Data were analyzed with SPSS-24, MAXQDA, fMRIprep, and FSL software. RESULTS The Meta-Thinking Educational Program had effect on performance of ADHD children and suppressed brain regions related to DMN. CONCLUSION The Implementation of this educational program plays a vital role in improving psychological problems of children with ADHD.
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Zhang R, Murray SB, Duval CJ, Wang DJ, Jann K. Functional Connectivity and Complexity Analyses of Resting-State fMRI in Pre-Adolescents with ADHD. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.17.23294136. [PMID: 37662367 PMCID: PMC10473793 DOI: 10.1101/2023.08.17.23294136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Attention deficit hyperactivity disorder (ADHD) has been characterized by impairments among distributed functional brain networks, e.g., the frontoparietal network (FPN), default mode network (DMN), and reward and motivation-related circuits (RMN). In the current study, we evaluated the complexity and functional connectivity (FC) of resting state fMRI (rsfMRI) in pre-adolescents with ADHD for pathology-relevant networks. We leveraged data from the Adolescent Brain and Cognitive Development (ABCD) Study. The final study sample included 63 children with ADHD and 92 healthy control children matched on age, sex, and pubertal development status. For selected regions in relevant networks, ANCOVA compared multiscale entropy (MSE) and FC between the groups. Finally, differences in the association between MSE and FC were evaluated. We found significantly reduced MSE along with increased FC within the FPN of pre-adolescents with ADHD compared to matched healthy controls. Significant partial correlations between MSE and FC emerged in fewer regions in the participants with ADHD than in the controls. The observation of reduced entropy is consistent with existing literature using rsfMRI and other neuroimaging modalities. The current findings of complexity and FC in ADHD support hypotheses of altered function of inhibitory control networks in ADHD.
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Affiliation(s)
- Ru Zhang
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Stuart B. Murray
- Department of Psychiatry and Behavioral Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Christina J. Duval
- Department of Psychiatry and Behavioral Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Danny J.J. Wang
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Kay Jann
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
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Wu L, Su S, Dai Y, Qiu H, Lin L, Zou M, Qian L, Liu M, Zhang H, Chen Y, Yang Z. Disrupted Small-World Networks in Children with Drug-Naïve Attention-Deficit/Hyperactivity Disorder: A DTI-Based Network Analysis. Dev Neurosci 2023; 46:201-209. [PMID: 37531941 DOI: 10.1159/000533128] [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: 12/30/2022] [Accepted: 07/03/2023] [Indexed: 08/04/2023] Open
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders, while the potential neurological mechanisms are poorly understood. To explore the alterations in the white matter (WM) structural connectome in children with drug-naïve ADHD, forty-nine ADHD and 51 age- and gender-matched typically developing (TD) children aged 6-14 years were enrolled. WM structural connectivity based on deterministic diffusion tensor imaging (DTI) was constructed in 90 cortical and subcortical regions, and topological parameters of the resulting graphs were calculated. Network metrics were compared between two groups. The concentration index and the total cancellation test scores of digit cancellation test were used to evaluate clinical symptom severity in ADHD. Then, a partial correlation analysis was performed to explore the relationship between significant topologic metrics and clinical symptom severity. Compared to TD group, ADHD showed an increase in the characteristic path length (Lp), normalized clustering coefficient (γ), small worldness (σ), and a decrease in the global efficiency (Eglob) (all p < 0.05). Furthermore, ADHD showed reduced nodal centralities mainly in the regions of default mode network (DMN), central executive network (CEN), basal ganglia, and bilateral thalamus (all p < 0.05). After performing Benjamini-Hochberg's procedure, only the left orbital part of superior frontal gyrus and the left caudate were statistically significant (p < 0.05, FDR-corrected). In addition, the concentration index of ADHD was negatively correlated with the nodal betweenness of the left orbital part of the middle frontal gyrus (r = -0.302, p = 0.042). Our findings revealed an ADHD-related shift of WM network topology toward "regularization" pattern, characterized by decreased global network integration, which is also reflected by changed nodal centralities involving DMN, CEN, basal ganglia, and bilateral thalamus. ADHD could be understood by examining the dysfunction of large-scale spatially distributed neural networks.
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Affiliation(s)
- Liuhui Wu
- Department of Radiology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China,
| | - Shu Su
- Department of Radiology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yan Dai
- Department of Radiology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Huaqiong Qiu
- Department of Radiology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Liping Lin
- Department of Radiology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Mengsha Zou
- Department of Radiology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Long Qian
- Department of Biomedical Engineering, College of Engineering, Peking University, Beijing, China
| | - Meina Liu
- Department of Pediatrics, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Hongyu Zhang
- Department of Pediatrics, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yingqian Chen
- Department of Radiology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zhiyun Yang
- Department of Radiology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
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León JJ, Fernández-Martin P, González-Rodríguez A, Rodríguez-Herrera R, García-Pinteño J, Pérez-Fernández C, Sánchez-Kuhn A, Amaya-Pascasio L, Soto-Ontoso M, Martínez-Sánchez P, Sánchez-Santed F, Flores P. Decision-making and frontoparietal resting-state functional connectivity among impulsive-compulsive diagnoses. Insights from a Bayesian approach. Addict Behav 2023; 143:107683. [PMID: 36963236 DOI: 10.1016/j.addbeh.2023.107683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 02/20/2023] [Accepted: 02/24/2023] [Indexed: 03/13/2023]
Abstract
The Iowa Gambling Task (IGT) is one of the most widely used paradigms for assessing decision-making. An impairment in this process may be linked to several psychopathological disorders, such as obsessive-compulsive disorder (OCD), substance abuse disorder (SUD) or attention-deficit/hyperactivity disorder (ADHD), which could make it a good candidate for being consider a transdiagnostic domain. Resting-state functional connectivity (rsFC) has been proposed as a promising biomarker of decision-making. In this study, we aimed to identify idiosyncratic decision-making profiles among healthy people and impulsive-compulsive spectrum patients during the IGT, and to investigate the role of frontoparietal network (FPN) rsFC as a possible biomarker of different decision-making patterns. Using functional near-infrared spectroscopy (fNIRS), rsFC of 114 adults (34 controls; 25 OCD; 41 SUD; 14 ADHD) was obtained. Then, they completed the IGT. Hybrid clustering methods based on individual deck choices yielded three decision-makers subgroups. Cluster 1 (n = 27) showed a long-term advantageous strategy. Cluster 2 (n = 25) presented a maladaptive decision-making strategy. Cluster 3 (n = 62) did not develop a preference for any deck during the task. Interestingly, the proportion of participants in each cluster was not different between diagnostic groups. A Bayesian general linear model showed no credible differences in the IGT performance between diagnostic groups nor credible evidence to support the role of FPN rsFC as a biomarker of decision-making under the IGT context. This study highlights the importance of exploring in depth the behavioral and neurophysiological variables that may drive decision-making in clinical and healthy populations.
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Affiliation(s)
- J J León
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - P Fernández-Martin
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - A González-Rodríguez
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - R Rodríguez-Herrera
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - J García-Pinteño
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - C Pérez-Fernández
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - A Sánchez-Kuhn
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - L Amaya-Pascasio
- Department of Neurology and Stroke Centre. Torrecárdenas University Hospital, Spain.
| | - M Soto-Ontoso
- Mental Health Departament. Torrecárdenas University Hospital, Spain.
| | - P Martínez-Sánchez
- Department of Neurology and Stroke Centre. Torrecárdenas University Hospital, Spain.
| | - F Sánchez-Santed
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - P Flores
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
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Mu S, Wu H, Zhang J, Chang C. Subcortical structural covariance predicts symptoms in children with different subtypes of ADHD. Cereb Cortex 2023:7161770. [PMID: 37183180 DOI: 10.1093/cercor/bhad165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 04/20/2023] [Accepted: 04/21/2023] [Indexed: 05/16/2023] Open
Abstract
Attention-deficit/hyperactivity disorder has increasingly been conceptualized as a disorder of abnormal brain connectivity. However, far less is known about the structural covariance in different subtypes of this disorder and how those differences may contribute to the symptomology of these subtypes. In this study, we used a combined volumetric-based methodology and structural covariance approach to investigate structural covariance of subcortical brain volume in attention-deficit/hyperactivity disorder-combined and attention-deficit/hyperactivity disorder-inattentive patients. In addition, a linear support vector machine was used to predict patient's attention-deficit/hyperactivity disorder symptoms. Results showed that compared with TD children, those with attention-deficit/hyperactivity disorder-combined exhibited decreased volume of both the left and right pallidum. Moreover, we found increased right hippocampal volume in attention-deficit/hyperactivity disorder-inattentive children. Furthermore and when compared with the TD group, both attention-deficit/hyperactivity disorder-combined and attention-deficit/hyperactivity disorder-inattentive groups showed greater nonhomologous inter-regional correlations. The abnormal structural covariance network in the attention-deficit/hyperactivity disorder-combined group was located in the left amygdala-left putamen/left pallidum/right pallidum and right pallidum-left pallidum; in the attention-deficit/hyperactivity disorder-inattentive group, this difference was noted in the left hippocampus-left amygdala/left putamen/right putamen and right hippocampus-left amygdala. Additionally, different combinations of abnormalities in subcortical structural covariance were predictive of symptom severity in different attention-deficit/hyperactivity disorder subtypes. Collectively, our findings demonstrated that structural covariance provided valuable diagnostic markers for attention-deficit/hyperactivity disorder subtypes.
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Affiliation(s)
- ShuHua Mu
- School of Psychology, Shenzhen University, Shenzhen, Guangdong 518060, China
| | - HuiJun Wu
- School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, Guangdong 518055, China
| | - Jian Zhang
- School of Pharmacy, Shenzhen University Medical School, Shenzhen University, Shenzhen, Guangdong 518055, China
| | - ChunQi Chang
- School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, Guangdong 518055, China
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32
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Fassbender C. Advancing Our Understanding of the Neural Basis of Attention-Deficit/Hyperactivity Disorder by Observing Longitudinal Changes in Resting-State Networks. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:485-487. [PMID: 37150581 DOI: 10.1016/j.bpsc.2023.03.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 03/13/2023] [Indexed: 05/09/2023]
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Sonuga-Barke EJS, Becker SP, Bölte S, Castellanos FX, Franke B, Newcorn JH, Nigg JT, Rohde LA, Simonoff E. Annual Research Review: Perspectives on progress in ADHD science - from characterization to cause. J Child Psychol Psychiatry 2023; 64:506-532. [PMID: 36220605 PMCID: PMC10023337 DOI: 10.1111/jcpp.13696] [Citation(s) in RCA: 40] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/08/2022] [Indexed: 12/20/2022]
Abstract
The science of attention-deficit/hyperactivity disorder (ADHD) is motivated by a translational goal - the discovery and exploitation of knowledge about the nature of ADHD to the benefit of those individuals whose lives it affects. Over the past fifty years, scientific research has made enormous strides in characterizing the ADHD condition and in understanding its correlates and causes. However, the translation of these scientific insights into clinical benefits has been limited. In this review, we provide a selective and focused survey of the scientific field of ADHD, providing our personal perspectives on what constitutes the scientific consensus, important new leads to be highlighted, and the key outstanding questions to be addressed going forward. We cover two broad domains - clinical characterization and, risk factors, causal processes and neuro-biological pathways. Part one focuses on the developmental course of ADHD, co-occurring characteristics and conditions, and the functional impact of living with ADHD - including impairment, quality of life, and stigma. In part two, we explore genetic and environmental influences and putative mediating brain processes. In the final section, we reflect on the future of the ADHD construct in the light of cross-cutting scientific themes and recent conceptual reformulations that cast ADHD traits as part of a broader spectrum of neurodivergence.
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Affiliation(s)
- Edmund J S Sonuga-Barke
- School of Academic Psychiatry, Institute of Psychology, Psychiatry & Neuroscience, King’s College London. UK
- Department of Child & Adolescent Psychiatry, Aarhus University, Denmark
| | - Stephen P. Becker
- Division of Behavioral Medicine and Clinical Psychology, Cincinnati Children’s Hospital Medical Center, United States
- Department of Pediatrics, University of Cincinnati College of Medicine, United States
| | - Sven Bölte
- Department of Women’s and Children’s Health, Karolinska Institutet, Sweden
- Division of Child and Adolescent Psychiatry, Center for Psychiatry Research, Stockholm County Council, Sweden
| | - Francisco Xavier Castellanos
- Department of Child and Adolescent Psychiatry, New York University Grossman School of Medicine, USA
- Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Barbara Franke
- Departments of Human Genetics and Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | | | - Joel T. Nigg
- Department of Psychiatry, Oregon Health and Science University, USA
| | - Luis Augusto Rohde
- ADHD Outpatient Program & Developmental Psychiatry Program, Hospital de Clinica de Porto Alegre, Federal University of Rio Grande do Sul, Brazil; National Institute of Developmental Psychiatry, Brazil
| | - Emily Simonoff
- School of Academic Psychiatry, Institute of Psychology, Psychiatry & Neuroscience, King’s College London. UK
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Liu G, Lu W, Qiu J, Shi L. Identifying individuals with attention‐deficit/hyperactivity disorder based on multisite resting‐state functional magnetic resonance imaging: A radiomics analysis. Hum Brain Mapp 2023; 44:3433-3445. [PMID: 36971664 PMCID: PMC10171499 DOI: 10.1002/hbm.26290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 12/17/2022] [Accepted: 03/13/2023] [Indexed: 03/29/2023] Open
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders, characterized by symptoms of age-inappropriate inattention, hyperactivity, and impulsivity. Apart from behavioral symptoms investigated by psychiatric methods, there is no standard biological test to diagnose ADHD. This study aimed to explore whether the radiomics features based on resting-state functional magnetic resonance (rs-fMRI) have more discriminative power for the diagnosis of ADHD. The rs-fMRI of 187 subjects with ADHD and 187 healthy controls were collected from 5 sites of ADHD-200 Consortium. A total of four preprocessed rs-fMRI images including regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF), voxel-mirrored homotopic connectivity (VMHC) and network degree centrality (DC) were used in this study. From each of the four images, we extracted 93 radiomics features within each of 116 automated anatomical labeling brain areas, resulting in a total of 43,152 features for each subject. After dimension reduction and feature selection, 19 radiomics features were retained (5 from ALFF, 9 from ReHo, 3 from VMHC and 2 from DC). By training and optimizing a support vector machine model using the retained features of training dataset, we achieved the accuracy of 76.3% and 77.0% (areas under curve = 0.811 and 0.797) in the training and testing datasets, respectively. Our findings demonstrate that radiomics can be a novel strategy for fully utilizing rs-fMRI information to distinguish ADHD from healthy controls. The rs-fMRI-based radiomics features have the potential to be neuroimaging biomarkers for ADHD.
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Vandewouw MM, Brian J, Crosbie J, Schachar RJ, Iaboni A, Georgiades S, Nicolson R, Kelley E, Ayub M, Jones J, Taylor MJ, Lerch JP, Anagnostou E, Kushki A. Identifying Replicable Subgroups in Neurodevelopmental Conditions Using Resting-State Functional Magnetic Resonance Imaging Data. JAMA Netw Open 2023; 6:e232066. [PMID: 36912839 PMCID: PMC10011941 DOI: 10.1001/jamanetworkopen.2023.2066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 01/22/2023] [Indexed: 03/14/2023] Open
Abstract
Importance Neurodevelopmental conditions, such as autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and obsessive-compulsive disorder (OCD), have highly heterogeneous and overlapping phenotypes and neurobiology. Data-driven approaches are beginning to identify homogeneous transdiagnostic subgroups of children; however, findings have yet to be replicated in independently collected data sets, a necessity for translation into clinical settings. Objective To identify subgroups of children with and without neurodevelopmental conditions with shared functional brain characteristics using data from 2 large, independent data sets. Design, Setting, and Participants This case-control study used data from the Province of Ontario Neurodevelopmental (POND) network (study recruitment began June 2012 and is ongoing; data were extracted April 2021) and the Healthy Brain Network (HBN; study recruitment began May 2015 and is ongoing; data were extracted November 2020). POND and HBN data are collected from institutions across Ontario and New York, respectively. Participants who had diagnoses of ASD, ADHD, and OCD or were typically developing (TD); were aged between 5 and 19 years; and successfully completed the resting-state and anatomical neuroimaging protocol were included in the current study. Main Outcomes and Measures The analyses consisted of a data-driven clustering procedure on measures derived from each participant's resting-state functional connectome, performed independently on each data set. Differences between each pair of leaves in the resulting clustering decision trees in the demographic and clinical characteristics were tested. Results Overall, 551 children and adolescents were included from each data set. POND included 164 participants with ADHD; 217 with ASD; 60 with OCD; and 110 with TD (median [IQR] age, 11.87 [9.51-14.76] years; 393 [71.2%] male participants; 20 [3.6%] Black, 28 [5.1%] Latino, and 299 [54.2%] White participants) and HBN included 374 participants with ADHD; 66 with ASD; 11 with OCD; and 100 with TD (median [IQR] age, 11.50 [9.22-14.20] years; 390 [70.8%] male participants; 82 [14.9%] Black, 57 [10.3%] Hispanic, and 257 [46.6%] White participants). In both data sets, subgroups with similar biology that differed significantly in intelligence as well as hyperactivity and impulsivity problems were identified, yet these groups showed no consistent alignment with current diagnostic categories. For example, there was a significant difference in Strengths and Weaknesses ADHD Symptoms and Normal Behavior Hyperactivity/Impulsivity subscale (SWAN-HI) between 2 subgroups in the POND data (C and D), with subgroup D having increased hyperactivity and impulsivity traits compared with subgroup C (median [IQR], 2.50 [0.00-7.00] vs 1.00 [0.00-5.00]; U = 1.19 × 104; P = .01; η2 = 0.02). A significant difference in SWAN-HI scores between subgroups g and d in the HBN data was also observed (median [IQR], 1.00 [0.00-4.00] vs 0.00 [0.00-2.00]; corrected P = .02). There were no differences in the proportion of each diagnosis between the subgroups in either data set. Conclusions and Relevance The findings of this study suggest that homogeneity in the neurobiology of neurodevelopmental conditions transcends diagnostic boundaries and is instead associated with behavioral characteristics. This work takes an important step toward translating neurobiological subgroups into clinical settings by being the first to replicate our findings in independently collected data sets.
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Affiliation(s)
- Marlee M. Vandewouw
- Autism Research Centre, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
| | - Jessica Brian
- Autism Research Centre, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada
- Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
| | - Jennifer Crosbie
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Department of Psychiatry, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Russell J. Schachar
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Department of Psychiatry, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Alana Iaboni
- Autism Research Centre, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada
| | - Stelios Georgiades
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada
| | - Robert Nicolson
- Department of Psychiatry, Western University, London, Ontario, Canada
| | - Elizabeth Kelley
- Department of Psychology, Queen’s University, Kingston, Ontario, Canada
- Centre for Neuroscience Studies, Queen’s University, Kingston, Ontario, Canada
- Department of Psychiatry, Queen’s University, Kingston, Ontario, Canada
| | - Muhammad Ayub
- Department of Psychiatry, Queen’s University, Kingston, Ontario, Canada
| | - Jessica Jones
- Department of Psychology, Queen’s University, Kingston, Ontario, Canada
- Centre for Neuroscience Studies, Queen’s University, Kingston, Ontario, Canada
- Department of Psychiatry, Queen’s University, Kingston, Ontario, Canada
| | - Margot J. Taylor
- Program in Neurosciences & Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
- Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
| | - Jason P. Lerch
- Program in Neurosciences & Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Evdokia Anagnostou
- Autism Research Centre, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada
- Program in Neurosciences & Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Azadeh Kushki
- Autism Research Centre, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
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Morand-Beaulieu S, Wu J, Mayes LC, Grantz H, Leckman JF, Crowley MJ, Sukhodolsky DG. Increased Alpha-Band Connectivity During Tic Suppression in Children With Tourette Syndrome Revealed by Source Electroencephalography Analyses. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:241-250. [PMID: 33991741 PMCID: PMC8589865 DOI: 10.1016/j.bpsc.2021.05.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 04/08/2021] [Accepted: 05/04/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND Tourette syndrome (TS) is a neurodevelopmental disorder involving chronic motor and phonic tics. Most individuals with TS can suppress their tics for at least a short period of time. Yet, the brain correlates of tic suppression are still poorly understood. METHODS In the current study, high-density electroencephalography was recorded during a resting-state and a tic suppression session in 72 children with TS. Functional connectivity between cortical regions was assessed in the alpha band (8-13 Hz) using an electroencephalography source connectivity method. Graph theory and network-based statistics were used to assess the global network topology and to identify brain regions showing increased connectivity during tic suppression. RESULTS Graph theoretical analyses revealed distinctive global network topology during tic suppression, relative to rest. Using network-based statistics, we found a subnetwork of increased connectivity during tic suppression (p < .001). That subnetwork encompassed many cortical areas, including the right superior frontal gyrus and the left precuneus, which are involved in the default mode network. We also found a condition-by-age interaction, suggesting age-mediated increases in connectivity during tic suppression. CONCLUSIONS These results suggest that children with TS suppress their tics through a brain circuit involving distributed cortical regions, many of which are part of the default mode network. Brain connectivity during tic suppression also increases as youths with TS mature. These results highlight a mechanism by which children with TS may control their tics, which could be relevant for future treatment studies.
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Affiliation(s)
| | - Jia Wu
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut
| | - Linda C Mayes
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut
| | - Heidi Grantz
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut
| | - James F Leckman
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut
| | - Michael J Crowley
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut
| | - Denis G Sukhodolsky
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut.
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37
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Lin H, Haider SP, Kaltenhauser S, Mozayan A, Malhotra A, Constable RT, Scheinost D, Ment LR, Konrad K, Payabvash S. Population level multimodal neuroimaging correlates of attention-deficit hyperactivity disorder among children. Front Neurosci 2023; 17:1138670. [PMID: 36908780 PMCID: PMC9992191 DOI: 10.3389/fnins.2023.1138670] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 02/07/2023] [Indexed: 02/24/2023] Open
Abstract
Objectives Leveraging a large population-level morphologic, microstructural, and functional neuroimaging dataset, we aimed to elucidate the underlying neurobiology of attention-deficit hyperactivity disorder (ADHD) in children. In addition, we evaluated the applicability of machine learning classifiers to predict ADHD diagnosis based on imaging and clinical information. Methods From the Adolescents Behavior Cognitive Development (ABCD) database, we included 1,798 children with ADHD diagnosis and 6,007 without ADHD. In multivariate logistic regression adjusted for age and sex, we examined the association of ADHD with different neuroimaging metrics. The neuroimaging metrics included fractional anisotropy (FA), neurite density (ND), mean-(MD), radial-(RD), and axial diffusivity (AD) of white matter (WM) tracts, cortical region thickness and surface areas from T1-MPRAGE series, and functional network connectivity correlations from resting-state fMRI. Results Children with ADHD showed markers of pervasive reduced microstructural integrity in white matter (WM) with diminished neural density and fiber-tracks volumes - most notable in the frontal and parietal lobes. In addition, ADHD diagnosis was associated with reduced cortical volume and surface area, especially in the temporal and frontal regions. In functional MRI studies, ADHD children had reduced connectivity among default-mode network and the central and dorsal attention networks, which are implicated in concentration and attention function. The best performing combination of feature selection and machine learning classifier could achieve a receiver operating characteristics area under curve of 0.613 (95% confidence interval = 0.580-0.645) to predict ADHD diagnosis in independent validation, using a combination of multimodal imaging metrics and clinical variables. Conclusion Our study highlights the neurobiological implication of frontal lobe cortex and associate WM tracts in pathogenesis of childhood ADHD. We also demonstrated possible potentials and limitations of machine learning models to assist with ADHD diagnosis in a general population cohort based on multimodal neuroimaging metrics.
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Affiliation(s)
- Huang Lin
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany
| | - Stefan P. Haider
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
| | - Simone Kaltenhauser
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
| | - Ali Mozayan
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
| | - Ajay Malhotra
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
| | - R. Todd Constable
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
| | - Dustin Scheinost
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
| | - Laura R. Ment
- Department of Pediatrics, Yale School of Medicine, New Haven, CT, United States
- Department of Neurology, Yale School of Medicine, New Haven, CT, United States
| | - Kerstin Konrad
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany
- Jülich Research Centre, JARA Brain Institute II, Molecular Neuroscience and Neuroimaging (INM-11), Jülich, Germany
| | - Seyedmehdi Payabvash
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
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38
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da Silva BS, Grevet EH, Silva LCF, Ramos JKN, Rovaris DL, Bau CHD. An overview on neurobiology and therapeutics of attention-deficit/hyperactivity disorder. DISCOVER MENTAL HEALTH 2023; 3:2. [PMID: 37861876 PMCID: PMC10501041 DOI: 10.1007/s44192-022-00030-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Accepted: 12/29/2022] [Indexed: 10/21/2023]
Abstract
Attention-Deficit/Hyperactivity Disorder (ADHD) is a prevalent psychiatric condition characterized by developmentally inappropriate symptoms of inattention and/or hyperactivity/impulsivity, which leads to impairments in the social, academic, and professional contexts. ADHD diagnosis relies solely on clinical assessment based on symptom evaluation and is sometimes challenging due to the substantial heterogeneity of the disorder in terms of clinical and pathophysiological aspects. Despite the difficulties imposed by the high complexity of ADHD etiology, the growing body of research and technological advances provide good perspectives for understanding the neurobiology of the disorder. Such knowledge is essential to refining diagnosis and identifying new therapeutic options to optimize treatment outcomes and associated impairments, leading to improvements in all domains of patient care. This review is intended to be an updated outline that addresses the etiological and neurobiological aspects of ADHD and its treatment, considering the impact of the "omics" era on disentangling the multifactorial architecture of ADHD.
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Affiliation(s)
- Bruna Santos da Silva
- ADHD and Developmental Psychiatry Programs, Hospital de Clínicas de Porto Alegre, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil
- Department of Genetics and Graduate Program in Genetics and Molecular Biology, Instituto de Biociências, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil
- Department of Physiology and Biophysics, Instituto de Ciencias Biomedicas Universidade de Sao Paulo, São Paulo, Brazil
- Laboratory of Physiological Genomics of Mental Health (PhysioGen Lab), Institute of Biomedical Sciences, University of Sao Paulo, São Paulo, Brazil
| | - Eugenio Horacio Grevet
- ADHD and Developmental Psychiatry Programs, Hospital de Clínicas de Porto Alegre, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil
- Department of Psychiatry and Graduate Program in Psychiatry and Behavioral Sciences, Faculdade de Medicina, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil
| | - Luiza Carolina Fagundes Silva
- ADHD and Developmental Psychiatry Programs, Hospital de Clínicas de Porto Alegre, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil
- Department of Psychiatry and Graduate Program in Psychiatry and Behavioral Sciences, Faculdade de Medicina, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil
| | - João Kleber Neves Ramos
- Department of Physiology and Biophysics, Instituto de Ciencias Biomedicas Universidade de Sao Paulo, São Paulo, Brazil
- Laboratory of Physiological Genomics of Mental Health (PhysioGen Lab), Institute of Biomedical Sciences, University of Sao Paulo, São Paulo, Brazil
| | - Diego Luiz Rovaris
- Department of Physiology and Biophysics, Instituto de Ciencias Biomedicas Universidade de Sao Paulo, São Paulo, Brazil
- Laboratory of Physiological Genomics of Mental Health (PhysioGen Lab), Institute of Biomedical Sciences, University of Sao Paulo, São Paulo, Brazil
| | - Claiton Henrique Dotto Bau
- ADHD and Developmental Psychiatry Programs, Hospital de Clínicas de Porto Alegre, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil.
- Department of Genetics and Graduate Program in Genetics and Molecular Biology, Instituto de Biociências, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil.
- Department of Psychiatry and Graduate Program in Psychiatry and Behavioral Sciences, Faculdade de Medicina, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil.
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Norman LJ, Sudre G, Price J, Shastri GG, Shaw P. Evidence from "big data" for the default-mode hypothesis of ADHD: a mega-analysis of multiple large samples. Neuropsychopharmacology 2023; 48:281-289. [PMID: 36100657 PMCID: PMC9751118 DOI: 10.1038/s41386-022-01408-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 07/10/2022] [Accepted: 07/16/2022] [Indexed: 12/26/2022]
Abstract
We sought to identify resting-state characteristics related to attention deficit/hyperactivity disorder, both as a categorical diagnosis and as a trait feature, using large-scale samples which were processed according to a standardized pipeline. In categorical analyses, we considered 1301 subjects with diagnosed ADHD, contrasted against 1301 unaffected controls (total N = 2602; 1710 males (65.72%); mean age = 10.86 years, sd = 2.05). Cases and controls were 1:1 nearest neighbor matched on in-scanner motion and key demographic variables and drawn from multiple large cohorts. Associations between ADHD-traits and resting-state connectivity were also assessed in a large multi-cohort sample (N = 10,113). ADHD diagnosis was associated with less anticorrelation between the default mode and salience/ventral attention (B = 0.009, t = 3.45, p-FDR = 0.004, d = 0.14, 95% CI = 0.004, 0.014), somatomotor (B = 0.008, t = 3.49, p-FDR = 0.004, d = 0.14, 95% CI = 0.004, 0.013), and dorsal attention networks (B = 0.01, t = 4.28, p-FDR < 0.001, d = 0.17, 95% CI = 0.006, 0.015). These results were robust to sensitivity analyses considering comorbid internalizing problems, externalizing problems and psychostimulant medication. Similar findings were observed when examining ADHD traits, with the largest effect size observed for connectivity between the default mode network and the dorsal attention network (B = 0.0006, t = 5.57, p-FDR < 0.001, partial-r = 0.06, 95% CI = 0.0004, 0.0008). We report significant ADHD-related differences in interactions between the default mode network and task-positive networks, in line with default mode interference models of ADHD. Effect sizes (Cohen's d and partial-r, estimated from the mega-analytic models) were small, indicating subtle group differences. The overlap between the affected brain networks in the clinical and general population samples supports the notion of brain phenotypes operating along an ADHD continuum.
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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, USA.
- Section on Neurobehavioral and Clinical Research, Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
| | - 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, USA
| | - 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, USA
| | - Gauri G Shastri
- Intramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Philip Shaw
- Office of the Clinical Director, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, 20892, USA
- Section on Neurobehavioral and Clinical Research, Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
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40
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Henry TR, Fogleman ND, Nugiel T, Cohen JR. Effect of methylphenidate on functional controllability: a preliminary study in medication-naïve children with ADHD. Transl Psychiatry 2022; 12:518. [PMID: 36528602 PMCID: PMC9759578 DOI: 10.1038/s41398-022-02283-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 11/18/2022] [Accepted: 12/05/2022] [Indexed: 12/23/2022] Open
Abstract
Methylphenidate (MPH) is the recommended first-line treatment for attention-deficit/hyperactivity disorder (ADHD). While MPH's mechanism of action as a dopamine and noradrenaline transporter blocker is well known, how this translates to ADHD-related symptom mitigation is still unclear. As functional connectivity is reliably altered in ADHD, with recent literature indicating dysfunctional connectivity dynamics as well, one possible mechanism is through altering brain network dynamics. In a double-blind, placebo-controlled MPH crossover trial, 19 medication-naïve children with ADHD underwent two functional MRI scanning sessions (one on MPH and one on placebo) that included a resting state scan and two inhibitory control tasks; 27 typically developing (TD) children completed the same protocol without medication. Network control theory, which quantifies how brain activity reacts to system inputs based on underlying connectivity, was used to assess differences in average and modal functional controllability during rest and both tasks between TD children and children with ADHD (on and off MPH) and between children with ADHD on and off MPH. Children with ADHD on placebo exhibited higher average controllability and lower modal controllability of attention, reward, and somatomotor networks than TD children. Children with ADHD on MPH were statistically indistinguishable from TD children on almost all controllability metrics. These findings suggest that MPH may stabilize functional network dynamics in children with ADHD, both reducing reactivity of brain organization and making it easier to achieve brain states necessary for cognitively demanding tasks.
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Affiliation(s)
- Teague R Henry
- Department of Psychology and School of Data Science, University of Virginia, Charlottesville, VA, USA.
| | - Nicholas D Fogleman
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tehila Nugiel
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jessica R Cohen
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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41
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Liu N, Liu Q, Yang Z, Xu J, Fu G, Zhou Y, Li H, Wang Y, Liu L, Qian Q. Different functional alteration in attention-deficit/hyperactivity disorder across developmental age groups: A meta-analysis and an independent validation of resting-state functional connectivity studies. CNS Neurosci Ther 2022; 29:60-69. [PMID: 36468409 PMCID: PMC9804052 DOI: 10.1111/cns.14032] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 03/21/2022] [Accepted: 10/09/2022] [Indexed: 12/09/2022] Open
Abstract
BACKGROUND Attention-deficit/hyperactivity disorder (ADHD) is a highly complex and heterogeneous disorder. Abnormal brain connectivity in ADHD might be influenced by developmental ages which might lead to the lacking of significant spatial convergence across studies. However, the developmental patterns and mechanisms of ADHD brain connectivity remain to be fully uncovered. METHODS In the present study, we searched PubMed, Scopus, Web of Science, and Embase for seed-based whole-brain resting-state functional connectivity studies of ADHD published through October 12th, 2020. The seeds meeting inclusion criteria were categorized into the cortex group and subcortex group, as previous studies suggested that the cortex and subcortex have different temporal patterns of development. Activation likelihood estimation meta-analysis was performed to investigate the abnormal connectivity in different age groups (all-age group, younger: <12 years, older: ≥12 years). Moreover, significant convergence of reported foci was used as seeds for validation with our independent dataset. RESULTS As with previous studies, scarce results were found in the all-age group. However, we found that the younger group consistently exhibited hyper-connectivity between different parts of the cortex and left middle frontal gyrus, and hypo-connectivity between different parts of the cortex and left putamen/pallidus/amygdala. Whereas, the older group (mainly for adults) showed hyper-connectivity between the cortex and right precuneus/sub-gyral/cingulate gyrus. Besides, the abnormal cortico-cortical and cortico-subcortical functional connectivity in children, and the abnormal cortico-cortical functional connectivity in adults were verified in our independent dataset. CONCLUSION Our study emphasizes the importance of developmental age effects on the study of brain networks in ADHD. Further, we proposed that cortico-cortical and cortico-subcortical connectivity might play an important role in the pathophysiology of children with ADHD, while abnormal cortico-cortical connections were more important for adults with ADHD. This work provided a potential new insight to understand the neurodevelopmental mechanisms and possible clinical application of ADHD.
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Affiliation(s)
- Ningning Liu
- Peking University Sixth Hospital, Institute of Mental HealthBeijingChina,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
| | - Qianrong Liu
- Peking University Sixth Hospital, Institute of Mental HealthBeijingChina,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
| | - Ziqi Yang
- Peking University Sixth Hospital, Institute of Mental HealthBeijingChina,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
| | - Jie Xu
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Magnetic Resonance Imaging Center, Center for Brain Disorders and Cognitive Sciences, Shenzhen UniversityShenzhenChina,Department of Biomedical Sciences of Cells & Systems, Section Cognitive Neuroscience, University Medical Center Groningen, University of GroningenGroningenThe Netherlands
| | - Guanghui Fu
- Peking University Sixth Hospital, Institute of Mental HealthBeijingChina,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
| | - Yi Zhou
- Peking University Sixth Hospital, Institute of Mental HealthBeijingChina,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
| | - Haimei Li
- Peking University Sixth Hospital, Institute of Mental HealthBeijingChina,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
| | - Yufeng Wang
- Peking University Sixth Hospital, Institute of Mental HealthBeijingChina,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
| | - Lu Liu
- Peking University Sixth Hospital, Institute of Mental HealthBeijingChina,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
| | - Qiujin Qian
- Peking University Sixth Hospital, Institute of Mental HealthBeijingChina,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
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Marcos-Vidal L, Martínez-García M, Martín de Blas D, Navas-Sánchez FJ, Pretus C, Ramos-Quiroga JA, Richarte V, Vilarroya Ó, Sepulcre J, Desco M, Carmona S. Local Functional Connectivity as a Parsimonious Explanation of the Main Frameworks for ADHD in Medication-Naïve Adults. J Atten Disord 2022; 26:1788-1801. [PMID: 35684934 DOI: 10.1177/10870547221101646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Objective: Neuroimaging studies in children with ADHD indicate that their brain exhibits an atypical functional connectivity pattern characterized by increased local connectivity and decreased distant connectivity. We aim to evaluate if the local and distant distribution of functional connectivity is also altered in adult samples with ADHD who have never received medication before. Methods: We compared local and distant functional connectivity between 31 medication-naïve adults with ADHD and 31 healthy controls and tested whether this pattern was associated with symptoms severity scores. Results: ADHD sample showed increased local connectivity in the dACC and the SFG and decreased local connectivity in the PCC. Conclusion: Results parallel those obtained in children samples suggesting a deficient integration within the DMN and segregation between DMN, FPN, and VAN. These results are consistent with the three main frameworks that explain ADHD: the neurodevelopmental delay hypothesis, the DMN interference hypothesis, and multi-network models.
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Affiliation(s)
- Luis Marcos-Vidal
- Universidad Carlos III de Madrid, Madrid, Spain.,Instituto de Investigación Gregorio Marañón, Madrid, Spain.,Centro de Investigación Biomédica En Red de Salud Mental, Madrid, Spain
| | - Magdalena Martínez-García
- Instituto de Investigación Gregorio Marañón, Madrid, Spain.,Centro de Investigación Biomédica En Red de Salud Mental, Madrid, Spain
| | | | | | - Clara Pretus
- Unitat de Reserca en Neurociencia Cognitiva, Departament de Psiquiatría i Neurociencia Legal, Universitat Autònoma de Barcelona, Spain.,Hospital del Mar Medical Research Institute, Barcelona, Spain
| | - Josep Antoni Ramos-Quiroga
- Centro de Investigación Biomédica En Red de Salud Mental, Madrid, Spain.,Psychiatry Department, Vall d'Hebron University Hospital, Barcelona, Spain.,Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute, Barcelona, Spain
| | - Vanesa Richarte
- Centro de Investigación Biomédica En Red de Salud Mental, Madrid, Spain.,Psychiatry Department, Vall d'Hebron University Hospital, Barcelona, Spain.,Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute, Barcelona, Spain
| | - Óscar Vilarroya
- Unitat de Reserca en Neurociencia Cognitiva, Departament de Psiquiatría i Neurociencia Legal, Universitat Autònoma de Barcelona, Spain.,Hospital del Mar Medical Research Institute, Barcelona, Spain
| | - Jorge Sepulcre
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.,Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Manuel Desco
- Universidad Carlos III de Madrid, Madrid, Spain.,Instituto de Investigación Gregorio Marañón, Madrid, Spain.,Centro de Investigación Biomédica En Red de Salud Mental, Madrid, Spain.,Fundación Centro Nacional de Investigaciones Cardiovasculares Carlos III, Madrid, Spain
| | - Susanna Carmona
- Universidad Carlos III de Madrid, Madrid, Spain.,Instituto de Investigación Gregorio Marañón, Madrid, Spain.,Centro de Investigación Biomédica En Red de Salud Mental, Madrid, Spain
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43
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Kaiser A, Broeder C, Cohen JR, Douw L, Reneman L, Schrantee A. Effects of a single-dose methylphenidate challenge on resting-state functional connectivity in stimulant-treatment naive children and adults with ADHD. Hum Brain Mapp 2022; 43:4664-4675. [PMID: 35781371 PMCID: PMC9491277 DOI: 10.1002/hbm.25981] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 05/17/2022] [Accepted: 05/27/2022] [Indexed: 11/09/2022] Open
Abstract
Prior studies suggest that methylphenidate, the primary pharmacological treatment for attention-deficit/hyperactivity disorder (ADHD), alters functional brain connectivity. As the neurotransmitter systems targeted by methylphenidate undergo significant alterations throughout development, the effects of methylphenidate on functional connectivity may also be modulated by age. Therefore, we assessed the effects of a single methylphenidate challenge on brain network connectivity in stimulant-treatment naïve children and adults with ADHD. We obtained resting-state functional MRI from 50 boys (10-12 years of age) and 49 men (23-40 years of age) with ADHD (DSM IV, all subtypes), before and after an oral challenge with 0.5 mg/kg methylphenidate; and from 11 boys and 12 men as typically developing controls. Connectivity strength (CS), eigenvector centrality (EC), and betweenness centrality (BC) were calculated for the striatum, thalamus, dorsal anterior cingulate cortex (dACC), and prefrontal cortex (PFC). In line with our hypotheses, we found that methylphenidate decreased measures of connectivity and centrality in the striatum and thalamus in children with ADHD, but increased the same metrics in adults with ADHD. Surprisingly, we found no major effects of methylphenidate in the dACC and PFC in either children or adults. Interestingly, pre-methylphenidate, participants with ADHD showed aberrant connectivity and centrality compared to controls predominantly in frontal regions. Our findings demonstrate that methylphenidate's effects on connectivity of subcortical regions are age-dependent in stimulant-treatment naïve participants with ADHD, likely due to ongoing maturation of dopamine and noradrenaline systems. These findings highlight the importance for future studies to take a developmental perspective when studying the effects of methylphenidate treatment.
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Affiliation(s)
- Antonia Kaiser
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
| | - Caroline Broeder
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
| | - Jessica R. Cohen
- Department of Psychology and NeuroscienceUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Linda Douw
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMCVrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Liesbeth Reneman
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
| | - Anouk Schrantee
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
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44
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Marcos-Vidal L, Martínez-García M, Martín-de Blas D, Navas-Sánchez FJ, Pretus C, Ramos-Quiroga JA, Richarte V, Vilarroya Ó, Sepulcre J, Desco M, Carmona S. Local Functional Connectivity as a Parsimonious Explanation of the Main Frameworks for ADHD in Medication-Naïve Adults. J Atten Disord 2022; 26:1563-1575. [PMID: 35947490 DOI: 10.1177/10870547211031998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
OBJECTIVE Neuroimaging studies in children with ADHD indicate that their brain exhibits an atypical functional connectivity pattern characterized by increased local connectivity and decreased distant connectivity. We aim to evaluate if the local and distant distribution of functional connectivity is also altered in adult samples with ADHD who have never received medication before. METHODS We compared local and distant functional connectivity between 31 medication-naïve adults with ADHD and 31 healthy controls and tested whether this pattern was associated with symptoms severity scores. RESULTS ADHD sample showed increased local connectivity in the dACC and the SFG and decreased local connectivity in the PCC. CONCLUSION Results parallel those obtained in children samples suggesting a deficient integration within the DMN and segregation between DMN, FPN, and VAN. These results are consistent with the three main frameworks that explain ADHD: the neurodevelopmental delay hypothesis, the DMN interference hypothesis and multi-network models.
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Affiliation(s)
- Luis Marcos-Vidal
- Universidad Carlos III de Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,Health Institute Carlos III, Madrid, Spain
| | - Magdalena Martínez-García
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,Health Institute Carlos III, Madrid, Spain
| | | | | | - Clara Pretus
- Universitat Autònoma de Barcelona, Spain.,Fundació Institut Mar d'Investigacions Mèdiques, Barcelona, Spain
| | - Josep Antoni Ramos-Quiroga
- Health Institute Carlos III, Madrid, Spain.,Vall d'Hebron University Hospital, Barcelona, Spain.,Vall d'Hebron Research Institute, Barcelona, Spain
| | - Vanesa Richarte
- Health Institute Carlos III, Madrid, Spain.,Vall d'Hebron University Hospital, Barcelona, Spain.,Vall d'Hebron Research Institute, Barcelona, Spain
| | - Óscar Vilarroya
- Universitat Autònoma de Barcelona, Spain.,Fundació Institut Mar d'Investigacions Mèdiques, Barcelona, Spain
| | - Jorge Sepulcre
- Massachusetts General Hospital and Harvard Medical School, Charlestown, USA
| | - Manuel Desco
- Universidad Carlos III de Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,Health Institute Carlos III, Madrid, Spain.,Fundación Centro Nacional de Investigaciones Cardiovasculares Carlos III, Madrid, Spain
| | - Susanna Carmona
- Universidad Carlos III de Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain.,Health Institute Carlos III, Madrid, Spain
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45
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Kowalczyk OS, Mehta MA, O’Daly OG, Criaud M. Task-Based Functional Connectivity in Attention-Deficit/Hyperactivity Disorder: A Systematic Review. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2022; 2:350-367. [PMID: 36324660 PMCID: PMC9616264 DOI: 10.1016/j.bpsgos.2021.10.006] [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] [Received: 08/02/2021] [Revised: 10/07/2021] [Accepted: 10/11/2021] [Indexed: 11/30/2022] Open
Abstract
Altered neurocognitive functioning is a key feature of attention-deficit/hyperactivity disorder (ADHD), and increasing numbers of studies assess task-based functional connectivity in the disorder. We systematically reviewed and critically appraised functional magnetic resonance imaging (fMRI) task-based functional connectivity studies in ADHD. A systematic search conducted up to September 2020 found 34 studies, including 51 comparisons. Comparisons were divided into investigations of ADHD neuropathology (37 comparing ADHD and typical development, 2 comparing individuals with ADHD and their nonsymptomatic siblings, 2 comparing remitted and persistent ADHD, and 1 exploring ADHD symptom severity) and the effects of interventions (8 investigations of stimulant effects and 1 study of fMRI neurofeedback). Large heterogeneity in study methodologies prevented a meta-analysis; thus, the data were summarized as a narrative synthesis. Across cognitive domains, functional connectivity in the cingulo-opercular, sensorimotor, visual, subcortical, and executive control networks in ADHD consistently differed from neurotypical populations. Furthermore, literature comparing individuals with ADHD and their nonsymptomatic siblings as well as adults with ADHD and their remitted peers showed ADHD-related abnormalities in similar sensorimotor and subcortical (primarily striatal) networks. Interventions modulated those dysfunctional networks, with the most consistent action on functional connections with the striatum, anterior cingulate cortex, occipital regions, and midline default mode network structures. Although methodological issues limited many of the reviewed studies, the use of task-based functional connectivity approaches has the potential to broaden the understanding of the neural underpinnings of ADHD and the mechanisms of action of ADHD treatments.
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Affiliation(s)
- Olivia S. Kowalczyk
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Mitul A. Mehta
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Owen G. O’Daly
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Marion Criaud
- Department of Child & Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
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46
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Jackson TB, Bernard JA. Cerebellar and basal ganglia motor network predicts trait depression and hyperactivity. Front Behav Neurosci 2022; 16:953303. [PMID: 36187378 PMCID: PMC9523104 DOI: 10.3389/fnbeh.2022.953303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 08/30/2022] [Indexed: 11/23/2022] Open
Abstract
In the human brain, the cerebellum (CB) and basal ganglia (BG) are implicated in cognition-, emotion-, and motor-related cortical processes and are highly interconnected, both to cortical regions via separate, trans-thalamic pathways and to each other via subcortical disynaptic pathways. We previously demonstrated a distinction between cognitive and motor CB-BG networks (CCBN, MCBN, respectively) as it relates to cortical network integration in healthy young adults, suggesting the subcortical networks separately support cortical networks. The CB and BG are also implicated in the pathophysiology of schizophrenia, Parkinson's, and compulsive behavior; thus, integration within subcortical CB-BG networks may be related to transdiagnostic symptomology. Here, we asked whether CCBN or MCBN integration predicted Achenbach Self-Report scores for anxiety, depression, intrusive thoughts, hyperactivity and inactivity, and cognitive performance in a community sample of young adults. We computed global efficiency for each CB-BG network and 7 canonical resting-state networks for all right-handed participants in the Human Connectome Project 1200 release with a complete set of preprocessed resting-state functional MRI data (N = 783). We used multivariate regression to control for substance abuse and age, and permutation testing with exchangeability blocks to control for family relationships. MCBN integration negatively predicted depression and hyperactivity, and positively predicted cortical network integration. CCBN integration predicted cortical network integration (except for the emotional network) and marginally predicted a positive relationship with hyperactivity, indicating a potential dichotomy between cognitive and motor CB-BG networks and hyperactivity. These results highlight the importance of CB-BG interactions as they relate to motivation and symptoms of depression.
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Affiliation(s)
- T. Bryan Jackson
- Department of Psychological and Brain Sciences, Texas A&M University, College Station, TX, United States
- *Correspondence: T. Bryan Jackson
| | - Jessica A. Bernard
- Department of Psychological and Brain Sciences, Texas A&M University, College Station, TX, United States
- Texas A&M Institute for Neuroscience, Texas A&M University, College Station, TX, United States
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47
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Behavioral and brain functional characteristics of children with Attention-Deficit/Hyperactivity disorder and anxiety trait. Brain Imaging Behav 2022; 16:2657-2665. [PMID: 36076128 DOI: 10.1007/s11682-022-00722-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 08/25/2022] [Accepted: 08/26/2022] [Indexed: 11/02/2022]
Abstract
The current study aimed to explore the behavioral, daily-life executive functional, and brain functional connectivity patterns in children with attention-deficit/hyperactivity disorder (ADHD) and anxiety. A total of 246 children with non-comorbid ADHD and 91 healthy controls (HCs) participated in the current study, among whom 175 subjects went through resting-state functional magnetic resonance imaging (fMRI) scans. The ADHD participants were divided into two subgroups: ADHD with a high level of anxiety (ADHD + ANX) and ADHD with a low level of anxiety (ADHD-ANX). The Child Behavior Checklist (CBCL) and the Behavior Rating Inventory of Executive Function (BRIEF) were used to capture the behavioral and daily-life executive functional characteristics. Independent component analysis with dual regression models was applied to the fMRI data. All statistical models were estimated with age and sex as covariates. Compared with the ADHD-ANX group, the ADHD + ANX group showed more withdrawn, somatic, social, thought, attention, delinquent, and aggressive problems (all corrected p < 0.05). The ADHD + ANX group also displayed more impaired emotional control and working memory than the ADHD-ANX (all corrected p < 0.05). The ADHD-ANX group, but not the ADHD + ANX group, showed elevated functional connectivity within the default mode network compared with the HC group. The mean function connectivity within the default mode network significantly mediated the correlation between anxiety level and attention problems. In sum, anxiety in children with ADHD was associated with more social, emotional, and behavioral problems, more impaired daily-life executive function, and altered brain function. Our work provides important information on the heterogeneity of ADHD.
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48
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Long Y, Pan N, Ji S, Qin K, Chen Y, Zhang X, He M, Suo X, Yu Y, Wang S, Gong Q. Distinct brain structural abnormalities in attention-deficit/hyperactivity disorder and substance use disorders: A comparative meta-analysis. Transl Psychiatry 2022; 12:368. [PMID: 36068207 PMCID: PMC9448791 DOI: 10.1038/s41398-022-02130-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Revised: 08/16/2022] [Accepted: 08/18/2022] [Indexed: 11/09/2022] Open
Abstract
As two common mental disorders during the period of adolescence that extend to early adulthood, attention-deficit/hyperactivity disorder (ADHD) and substance use disorders (SUDs) have considerable diagnostic co-occurrence and shared neuropsychological impairments. Our study aimed to identify overlapping and distinct brain structural abnormalities associated with ADHD and SUDs among adolescents and young adults. A systematic literature search on voxel-based morphometry (VBM) studies of ADHD and SUDs was conducted in PubMed and Web of Science. Data were extracted and analyzed to identify brain abnormalities using Seed-based d-Mapping software. Data-driven functional decoding was conducted to identify the psychophysiological functioning associated with brain alterations. 13 and 14 VBM studies for ADHD (619 patients and 483 controls) and SUDs (516 patients and 413 controls), respectively, were included. Patterns of decreased gray matter volume (GMV) were found in the left precentral gyrus, bilateral superior frontal gyri, and left inferior frontal gyrus in the ADHD group compared to the control group. In contrast, individuals with SUDs, relative to controls, were characterized by increased GMV in the left putamen and insula. Comparative analysis indicated larger regional GMV in the right inferior parietal lobule and smaller volumes in the left putamen and left precentral gyrus in the ADHD group than in the SUDs group. Dissociable brain structural abnormalities in adolescents and young adults with ADHD and SUDs potentially implicate different pathogeneses and provide a reference for differential diagnosis and early detection for shared symptomology and comorbidity.
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Affiliation(s)
- Yajing Long
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Nanfang Pan
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Shiyu Ji
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Department of Biochemistry and Molecular Biology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Kun Qin
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Department of Psychiatry, University of Cincinnati, Cincinnati, OH, USA
| | - Ying Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Xun Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Min He
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Xueling Suo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Yifan Yu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Song Wang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China.
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, China.
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49
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Bu X, Gao Y, Liang K, Chen Y, Guo L, Huang X. Investigation of white matter functional networks underlying different behavioral profiles in attention-deficit/hyperactivity disorder. PSYCHORADIOLOGY 2022; 2:69-77. [PMID: 38665605 PMCID: PMC10917226 DOI: 10.1093/psyrad/kkac012] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 09/29/2022] [Accepted: 10/10/2022] [Indexed: 04/28/2024]
Abstract
Background Cortical functional network alterations have been widely accepted as the neural basis of attention-deficit/hyperactivity disorder (ADHD). Recently, white matter has also been recognized as a novel neuroimaging marker of psychopathology and has been used as a complement to cortical functional networks to investigate brain-behavior relationships. However, disorder-specific features of white matter functional networks (WMFNs) are less well understood than those of gray matter functional networks. In the current study, we constructed WMFNs using a new strategy to characterize behavior-related network features in ADHD. Methods We recruited 46 drug-naïve boys with ADHD and 46 typically developing (TD) boys, and used clustering analysis on resting-state functional magnetic resonance imaging data to generate WMFNs in each group. Intrinsic activity within each network was extracted, and the associations between network activity and behavior measures were assessed using correlation analysis. Results Nine WMFNs were identified for both ADHD and TD participants. However, boys with ADHD showed a splitting of the inferior corticospinal-cerebellar network and lacked a cognitive control network. In addition, boys with ADHD showed increased activity in the dorsal attention network and somatomotor network, which correlated positively with attention problems and hyperactivity symptom scores, respectively, while they presented decreased activity in the frontoparietal network and frontostriatal network in association with poorer performance in response inhibition, working memory, and verbal fluency. Conclusions We discovered a dual pattern of white matter network activity in drug-naïve ADHD boys, with hyperactive symptom-related networks and hypoactive cognitive networks. These findings characterize two distinct types of WMFN in ADHD psychopathology.
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Affiliation(s)
- Xuan Bu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan 610041, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Yingxue Gao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan 610041, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Kaili Liang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan 610041, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Ying Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan 610041, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Lanting Guo
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Xiaoqi Huang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan 610041, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
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50
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Rezaei M, Zare H, Hakimdavoodi H, Nasseri S, Hebrani P. Classification of drug-naive children with attention-deficit/hyperactivity disorder from typical development controls using resting-state fMRI and graph theoretical approach. Front Hum Neurosci 2022; 16:948706. [PMID: 36061501 PMCID: PMC9433545 DOI: 10.3389/fnhum.2022.948706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 07/29/2022] [Indexed: 11/15/2022] Open
Abstract
Background and objectives The study of brain functional connectivity alterations in children with Attention-Deficit/Hyperactivity Disorder (ADHD) has been the subject of considerable investigation, but the biological mechanisms underlying these changes remain poorly understood. Here, we aim to investigate the brain alterations in patients with ADHD and Typical Development (TD) children and accurately classify ADHD children from TD controls using the graph-theoretical measures obtained from resting-state fMRI (rs-fMRI). Materials and methods We investigated the performances of rs-fMRI data for classifying drug-naive children with ADHD from TD controls. Fifty six drug-naive ADHD children (average age 11.86 ± 2.21 years; 49 male) and 56 age matched TD controls (average age 11.51 ± 1.77 years, 44 male) were included in this study. The graph measures extracted from rs-fMRI functional connectivity were used as features. Extracted network-based features were fed to the RFE feature selection algorithm to select the most discriminating subset of features. We trained and tested Support Vector Machine (SVM), Random Forest (RF), and Gradient Boosting (GB) using Peking center data from ADHD-200 database to classify ADHD and TD children using discriminative features. In addition to the machine learning approach, the statistical analysis was conducted on graph measures to discover the differences in the brain network of patients with ADHD. Results An accuracy of 78.2% was achieved for classifying drug-naive children with ADHD from TD controls employing the optimal features and the GB classifier. We also performed a hub node analysis and found that the number of hubs in TD controls and ADHD children were 8 and 5, respectively, indicating that children with ADHD have disturbance of critical communication regions in their brain network. The findings of this study provide insight into the neurophysiological mechanisms underlying ADHD. Conclusion Pattern recognition and graph measures of the brain networks, based on the rs-fMRI data, can efficiently assist in the classification of ADHD children from TD controls.
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Affiliation(s)
- Masoud Rezaei
- Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Hoda Zare
- Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Hamidreza Hakimdavoodi
- Neuroimaging and Analysis Group, Research Center for Science and Technology in Medicine, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Shahrokh Nasseri
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
- *Correspondence: Shahrokh Nasseri,
| | - Paria Hebrani
- Psychiatry and Behavioral Sciences Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
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