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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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Tsai CJ, Lin HY, Gau SSF. Correlation of altered intrinsic functional connectivity with impaired self-regulation in children and adolescents with ADHD. Eur Arch Psychiatry Clin Neurosci 2024:10.1007/s00406-024-01787-y. [PMID: 38906983 DOI: 10.1007/s00406-024-01787-y] [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: 08/10/2023] [Accepted: 02/16/2024] [Indexed: 06/23/2024]
Abstract
BACKGROUND Attention-deficit hyperactivity disorder (ADHD) has a high prevalence of co-occurring impaired self-regulation (dysregulation), exacerbating adverse outcomes. Neural correlates underlying impaired self-regulation in ADHD remain inconclusive. We aimed to investigate the impact of dysregulation on intrinsic functional connectivity (iFC) in children with ADHD and the correlation of iFC with dysregulation among children with ADHD relative to typically developing controls (TDC). METHODS Resting-state functional MRI data of 71 children with ADHD (11.38 ± 2.44 years) and 117 age-matched TDC were used in the final analysis. We restricted our analyses to resting-state networks (RSNs) of interest derived from independent component analysis. Impaired self-regulation was estimated based on the Child Behavioral Checklist-Dysregulation Profile. RESULTS Children with ADHD showed stronger iFC than TDC in the left frontoparietal network, somatomotor network (SMN), visual network (VIS), default-mode network (DMN), and dorsal attention network (DAN) (FWE-corrected alpha < 0.05). After adding dysregulation levels as an extra regressor, the ADHD group only showed stronger iFC in the VIS and SMN. ADHD children with high dysregulation had higher precuneus iFC within DMN than ADHD children with low dysregulation. Angular gyrus iFC within DMN was positively correlated with dysregulation in the ADHD group but negatively correlated with dysregulation in the TDC group. Functional network connectivity showed ADHD had a greater DMN-DAN connection than TDC, regardless of the dysregulation level. CONCLUSIONS Our findings suggest that DMN connectivity may contribute to impaired self-regulation in ADHD. Impaired self-regulation should be considered categorical and dimensional moderators for the neural correlates of altered iFC in ADHD.
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Affiliation(s)
- Chia-Jui Tsai
- Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Hsiang-Yuan Lin
- Azrieli Adult Neurodevelopmental Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Susan Shur-Fen Gau
- Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan.
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, No. 7, Chung-Shan South Road, Taipei, 10002, Taiwan.
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University Hospital, Taipei, Taiwan.
- Department of Psychology, College of Science, National Taiwan University, Taipei, Taiwan.
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Sundermann B, Pfleiderer B, McLeod A, Mathys C. Seeing more than the Tip of the Iceberg: Approaches to Subthreshold Effects in Functional Magnetic Resonance Imaging of the Brain. Clin Neuroradiol 2024:10.1007/s00062-024-01422-2. [PMID: 38842737 DOI: 10.1007/s00062-024-01422-2] [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: 10/23/2023] [Accepted: 05/05/2024] [Indexed: 06/07/2024]
Abstract
Many functional magnetic resonance imaging (fMRI) studies and presurgical mapping applications rely on mass-univariate inference with subsequent multiple comparison correction. Statistical results are frequently visualized as thresholded statistical maps. This approach has inherent limitations including the risk of drawing overly-selective conclusions based only on selective results passing such thresholds. This article gives an overview of both established and newly emerging scientific approaches to supplement such conventional analyses by incorporating information about subthreshold effects with the aim to improve interpretation of findings or leverage a wider array of information. Topics covered include neuroimaging data visualization, p-value histogram analysis and the related Higher Criticism approach for detecting rare and weak effects. Further examples from multivariate analyses and dedicated Bayesian approaches are provided.
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Affiliation(s)
- Benedikt Sundermann
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus Oldenburg, Universitätsmedizin Oldenburg, Steinweg 13-17, 26122, Oldenburg, Germany.
- Research Center Neurosensory Science, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany.
- Clinic of Radiology, Medical Faculty, University of Münster, Münster, Germany.
| | - Bettina Pfleiderer
- Clinic of Radiology, Medical Faculty, University of Münster, Münster, Germany
| | - Anke McLeod
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus Oldenburg, Universitätsmedizin Oldenburg, Steinweg 13-17, 26122, Oldenburg, Germany
| | - Christian Mathys
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus Oldenburg, Universitätsmedizin Oldenburg, Steinweg 13-17, 26122, Oldenburg, Germany
- Research Center Neurosensory Science, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
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Cai L, Wei X, Qing Y, Lu M, Yi G, Wang J, Dong Y. Assessment of impaired consciousness using EEG-based connectivity features and convolutional neural networks. Cogn Neurodyn 2024; 18:919-930. [PMID: 38826674 PMCID: PMC11143130 DOI: 10.1007/s11571-023-09944-0] [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: 07/04/2022] [Revised: 12/18/2022] [Accepted: 02/10/2023] [Indexed: 03/05/2023] Open
Abstract
Growing electroencephalogram (EEG) studies have linked the abnormities of functional brain networks with disorders of consciousness (DOC). However, due to network data's high-dimensional and non-Euclidean properties, it is difficult to exploit the brain connectivity information that can effectively detect the consciousness levels of DOC patients via deep learning. To take maximum advantage of network information in assessing impaired consciousness, we utilized the functional connectivity with convolutional neural network (CNN) and employed three rearrangement schemes to improve the evaluation performance of brain networks. In addition, the gradient-weighted class activation mapping (Grad-CAM) was adopted to visualize the classification contributions of connections among different areas. We demonstrated that the classification performance was significantly enhanced by applying network rearrangement techniques compared to those obtained by the original connectivity matrix (with an accuracy of 75.0%). The highest classification accuracy (87.2%) was achieved by rearranging the alpha network based on the anatomical regions. The inter-region connections (i.e., frontal-parietal and frontal-occipital connectivity) played dominant roles in the classification of patients with different consciousness states. The effectiveness of functional connectivity in revealing individual differences in brain activity was further validated by the correlation between behavioral performance and connections among specific regions. These findings suggest that our proposed assessment model could detect the residual consciousness of patients.
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Affiliation(s)
- Lihui Cai
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Xile Wei
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Yang Qing
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Meili Lu
- School of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin, China
| | - Guosheng Yi
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Jiang Wang
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Yueqing Dong
- Xincheng Hospital of Tianjin University, Tianjin, China
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Watters H, Davis A, Fazili A, Daley L, LaGrow TJ, Schumacher EH, Keilholz S. Infraslow dynamic patterns in human cortical networks track a spectrum of external to internal attention. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.22.590625. [PMID: 38712098 PMCID: PMC11071428 DOI: 10.1101/2024.04.22.590625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Early efforts to understand the human cerebral cortex focused on localization of function, assigning functional roles to specific brain regions. More recent evidence depicts the cortex as a dynamic system, organized into flexible networks with patterns of spatiotemporal activity corresponding to attentional demands. In functional MRI (fMRI), dynamic analysis of such spatiotemporal patterns is highly promising for providing non-invasive biomarkers of neurodegenerative diseases and neural disorders. However, there is no established neurotypical spectrum to interpret the burgeoning literature of dynamic functional connectivity from fMRI across attentional states. In the present study, we apply dynamic analysis of network-scale spatiotemporal patterns in a range of fMRI datasets across numerous tasks including a left-right moving dot task, visual working memory tasks, congruence tasks, multiple resting state datasets, mindfulness meditators, and subjects watching TV. We find that cortical networks show shifts in dynamic functional connectivity across a spectrum that tracks the level of external to internal attention demanded by these tasks. Dynamics of networks often grouped into a single task positive network show divergent responses along this axis of attention, consistent with evidence that definitions of a single task positive network are misleading. Additionally, somatosensory and visual networks exhibit strong phase shifting along this spectrum of attention. Results were robust on a group and individual level, further establishing network dynamics as a potential individual biomarker. To our knowledge, this represents the first study of its kind to generate a spectrum of dynamic network relationships across such an axis of attention.
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Affiliation(s)
| | - Aleah Davis
- Agnes Scott College
- Georgia Institute of Technology School of Psychology
| | | | - Lauren Daley
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology
| | - TJ LaGrow
- Georgia Institute of Technology School of Electrical and Computer Engineering
| | | | - Shella Keilholz
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology
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6
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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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7
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Chumin EJ, Cutts SA, Risacher SL, Apostolova LG, Farlow MR, McDonald BC, Wu YC, Betzel R, Saykin AJ, Sporns O. Edge time series components of functional connectivity and cognitive function in Alzheimer's disease. Brain Imaging Behav 2024; 18:243-255. [PMID: 38008852 PMCID: PMC10844434 DOI: 10.1007/s11682-023-00822-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/04/2023] [Indexed: 11/28/2023]
Abstract
Understanding the interrelationships of brain function as measured by resting-state magnetic resonance imaging and neuropsychological/behavioral measures in Alzheimer's disease is key for advancement of neuroimaging analysis methods in clinical research. The edge time-series framework recently developed in the field of network neuroscience, in combination with other network science methods, allows for investigations of brain-behavior relationships that are not possible with conventional functional connectivity methods. Data from the Indiana Alzheimer's Disease Research Center sample (53 cognitively normal control, 47 subjective cognitive decline, 32 mild cognitive impairment, and 20 Alzheimer's disease participants) were used to investigate relationships between functional connectivity components, each derived from a subset of time points based on co-fluctuation of regional signals, and measures of domain-specific neuropsychological functions. Multiple relationships were identified with the component approach that were not found with conventional functional connectivity. These involved attentional, limbic, frontoparietal, and default mode systems and their interactions, which were shown to couple with cognitive, executive, language, and attention neuropsychological domains. Additionally, overlapping results were obtained with two different statistical strategies (network contingency correlation analysis and network-based statistics correlation). Results demonstrate that connectivity components derived from edge time-series based on co-fluctuation reveal disease-relevant relationships not observed with conventional static functional connectivity.
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Affiliation(s)
- Evgeny J Chumin
- Department of Psychological and Brain Sciences, Indiana University (IU), Psychology Building 308, 1101 E 10th St, Bloomington, IN, 47405, USA.
- Indiana University Network Sciences Institute, IU, Bloomington, IN, USA.
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA.
- Indiana Alzheimer's Disease Research Center, IUSM, Indianapolis, IN, USA.
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, USA.
| | - Sarah A Cutts
- Department of Psychological and Brain Sciences, Indiana University (IU), Psychology Building 308, 1101 E 10th St, Bloomington, IN, 47405, USA
- Program in Neuroscience, IU, Bloomington, IN, USA
| | - Shannon L Risacher
- Indiana University Network Sciences Institute, IU, Bloomington, IN, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, IUSM, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, USA
| | - Liana G Apostolova
- Indiana University Network Sciences Institute, IU, Bloomington, IN, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, IUSM, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, USA
- Department of Neurology, IUSM, Indianapolis, IN, USA
| | - Martin R Farlow
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, IUSM, Indianapolis, IN, USA
- Department of Neurology, IUSM, Indianapolis, IN, USA
| | - Brenna C McDonald
- Indiana University Network Sciences Institute, IU, Bloomington, IN, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, IUSM, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, USA
- Department of Neurology, IUSM, Indianapolis, IN, USA
| | - Yu-Chien Wu
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, IUSM, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, USA
| | - Richard Betzel
- Department of Psychological and Brain Sciences, Indiana University (IU), Psychology Building 308, 1101 E 10th St, Bloomington, IN, 47405, USA
- Indiana University Network Sciences Institute, IU, Bloomington, IN, USA
- Program in Neuroscience, IU, Bloomington, IN, USA
| | - Andrew J Saykin
- Indiana University Network Sciences Institute, IU, Bloomington, IN, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, IUSM, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, USA
- Department of Neurology, IUSM, Indianapolis, IN, USA
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University (IU), Psychology Building 308, 1101 E 10th St, Bloomington, IN, 47405, USA
- Indiana University Network Sciences Institute, IU, Bloomington, IN, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, IUSM, Indianapolis, IN, USA
- Program in Neuroscience, IU, Bloomington, IN, USA
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, USA
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8
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Chumin EJ, Cutts SA, Risacher SL, Apostolova LG, Farlow MR, McDonald BC, Wu YC, Betzel R, Saykin AJ, Sporns O. Edge Time Series Components of Functional Connectivity and Cognitive Function in Alzheimer's Disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.13.23289936. [PMID: 38014005 PMCID: PMC10680898 DOI: 10.1101/2023.05.13.23289936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Understanding the interrelationships of brain function as measured by resting-state magnetic resonance imaging and neuropsychological/behavioral measures in Alzheimer's disease is key for advancement of neuroimaging analysis methods in clinical research. The edge time-series framework recently developed in the field of network neuroscience, in combination with other network science methods, allows for investigations of brain-behavior relationships that are not possible with conventional functional connectivity methods. Data from the Indiana Alzheimer's Disease Research Center sample (53 cognitively normal control, 47 subjective cognitive decline, 32 mild cognitive impairment, and 20 Alzheimer's disease participants) were used to investigate relationships between functional connectivity components, each derived from a subset of time points based on co-fluctuation of regional signals, and measures of domain-specific neuropsychological functions. Multiple relationships were identified with the component approach that were not found with conventional functional connectivity. These involved attentional, limbic, frontoparietal, and default mode systems and their interactions, which were shown to couple with cognitive, executive, language, and attention neuropsychological domains. Additionally, overlapping results were obtained with two different statistical strategies (network contingency correlation analysis and network-based statistics correlation). Results demonstrate that connectivity components derived from edge time-series based on co-fluctuation reveal disease-relevant relationships not observed with conventional static functional connectivity.
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Affiliation(s)
- Evgeny J. Chumin
- Department of Psychological and Brain Sciences, Indiana University (IU), Bloomington, IN, United States
- Indiana University Network Sciences Institute, IU, Bloomington, IN, United States
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, United States
- Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, United States
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, United States
| | - Sarah A. Cutts
- Department of Psychological and Brain Sciences, Indiana University (IU), Bloomington, IN, United States
- Program in Neuroscience, IU, Bloomington, IN, United States
| | - Shannon L. Risacher
- Indiana University Network Sciences Institute, IU, Bloomington, IN, United States
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, United States
- Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, United States
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, United States
| | - Liana G. Apostolova
- Indiana University Network Sciences Institute, IU, Bloomington, IN, United States
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, United States
- Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, United States
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, United States
- Department of Neurology, IUSM, Indianapolis, IN, United States
| | - Martin R. Farlow
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, United States
- Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, United States
- Department of Neurology, IUSM, Indianapolis, IN, United States
| | - Brenna C. McDonald
- Indiana University Network Sciences Institute, IU, Bloomington, IN, United States
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, United States
- Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, United States
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, United States
- Department of Neurology, IUSM, Indianapolis, IN, United States
| | - Yu-Chien Wu
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, United States
- Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, United States
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, United States
| | - Richard Betzel
- Department of Psychological and Brain Sciences, Indiana University (IU), Bloomington, IN, United States
- Indiana University Network Sciences Institute, IU, Bloomington, IN, United States
- Program in Neuroscience, IU, Bloomington, IN, United States
| | - Andrew J. Saykin
- Indiana University Network Sciences Institute, IU, Bloomington, IN, United States
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, United States
- Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, United States
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, United States
- Department of Neurology, IUSM, Indianapolis, IN, United States
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University (IU), Bloomington, IN, United States
- Indiana University Network Sciences Institute, IU, Bloomington, IN, United States
- Stark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, United States
- Indiana Alzheimer’s Disease Research Center, IUSM, Indianapolis, IN, United States
- Program in Neuroscience, IU, Bloomington, IN, United States
- Department of Radiology and Imaging Sciences, IUSM, Indianapolis, IN, United States
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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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10
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Liang S, Huang L, Zhan S, Zeng Y, Zhang Q, Zhang Y, Wang X, Peng L, Lin B, Xu H. Altered morphological characteristics and structural covariance connectivity associated with verbal working memory performance in ADHD children. Br J Radiol 2023; 96:20230409. [PMID: 37750842 PMCID: PMC10607391 DOI: 10.1259/bjr.20230409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Revised: 07/24/2023] [Accepted: 08/10/2023] [Indexed: 09/27/2023] Open
Abstract
OBJECTIVES Deficits in verbal working memory (VWM) observed in attention deficit hyperactivity disorder (ADHD) children can persist into adulthood. Although previous studies have identified brain regions that are activated during VWM tasks, the neural mechanisms underlying the relationship between VWM deficits remain unclear. The objective of this study was to investigate the structural covariance network connectivity and brain morphology changes that are associated with VWM performance in ADHD children. METHODS For this study, we selected 26 ADHD children and 26 healthy control (HC) participants. Participants were instructed to perform an n-back VWM task and their accuracy and response times were subsequently recorded. This research utilised voxel-based morphometry to measure the grey matter (GM) volume and conducted structural covariance connectivity network analysis to explore the changes of brain in ADHD. RESULTS Voxel-based morphometry analysis showed that lower GM volume in the right cerebellum lobule VI and the left parahippocampal gryus in ADHD children. Moreover, a positive correlation was found between the GM volume in the right cerebellum lobule VI and the accuracy of 2-back VWM task with verbal, small reward, and delayed feedback (VSD). Structural covariance network analysis found decreased structural connectivity between right cerebellum lobule VI and right precentral gyrus, right postcentral gyrus, left paracentral lobule, right superior parietal gyrus, and left hippocampus in ADHD children. CONCLUSIONS The low GM volume and altered structural covariance connectivity in the right cerebellum lobule VI might potentially affect VWM performance in ADHD children. ADVANCES IN KNOWLEDGE The innovation of this study lies in its more focused discussion on the morphological characteristics and structural covariance connectivity of VWM deficits in ADHD children, and the innovative finding of a positive correlation between grey matter volume in the right cerebellum lobule VI and accuracy in completing the 2-back VWM task with verbal instructions, small reward, and delayed feedback (VSD). This expands upon previous research by elucidating the specific brain structures involved in VWM deficits in ADHD children and highlights the potential importance of the cerebellum in this cognitive process. Overall, these innovative findings advance our understanding of the neural basis of ADHD and may have important implications for the development of targeted interventions for VWM deficits.
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Affiliation(s)
| | - Li Huang
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Shiqi Zhan
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Yi Zeng
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Qingqing Zhang
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Yusi Zhang
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Xiuxiu Wang
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Lixin Peng
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Bohong Lin
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Hui Xu
- School of Mental Health, Wenzhou Medical University, Wenzhou, China
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11
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Parlatini V, Itahashi T, Lee Y, Liu S, Nguyen TT, Aoki YY, Forkel SJ, Catani M, Rubia K, Zhou JH, Murphy DG, Cortese S. White matter alterations in Attention-Deficit/Hyperactivity Disorder (ADHD): a systematic review of 129 diffusion imaging studies with meta-analysis. Mol Psychiatry 2023; 28:4098-4123. [PMID: 37479785 PMCID: PMC10827669 DOI: 10.1038/s41380-023-02173-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Revised: 06/23/2023] [Accepted: 06/28/2023] [Indexed: 07/23/2023]
Abstract
Aberrant anatomical brain connections in attention-deficit/hyperactivity disorder (ADHD) are reported inconsistently across diffusion weighted imaging (DWI) studies. Based on a pre-registered protocol (Prospero: CRD42021259192), we searched PubMed, Ovid, and Web of Knowledge until 26/03/2022 to conduct a systematic review of DWI studies. We performed a quality assessment based on imaging acquisition, preprocessing, and analysis. Using signed differential mapping, we meta-analyzed a subset of the retrieved studies amenable to quantitative evidence synthesis, i.e., tract-based spatial statistics (TBSS) studies, in individuals of any age and, separately, in children, adults, and high-quality datasets. Finally, we conducted meta-regressions to test the effect of age, sex, and medication-naïvety. We included 129 studies (6739 ADHD participants and 6476 controls), of which 25 TBSS studies provided peak coordinates for case-control differences in fractional anisotropy (FA)(32 datasets) and 18 in mean diffusivity (MD)(23 datasets). The systematic review highlighted white matter alterations (especially reduced FA) in projection, commissural and association pathways of individuals with ADHD, which were associated with symptom severity and cognitive deficits. The meta-analysis showed a consistent reduced FA in the splenium and body of the corpus callosum, extending to the cingulum. Lower FA was related to older age, and case-control differences did not survive in the pediatric meta-analysis. About 68% of studies were of low quality, mainly due to acquisitions with non-isotropic voxels or lack of motion correction; and the sensitivity analysis in high-quality datasets yielded no significant results. Findings suggest prominent alterations in posterior interhemispheric connections subserving cognitive and motor functions affected in ADHD, although these might be influenced by non-optimal acquisition parameters/preprocessing. Absence of findings in children may be related to the late development of callosal fibers, which may enhance case-control differences in adulthood. Clinicodemographic and methodological differences were major barriers to consistency and comparability among studies, and should be addressed in future investigations.
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Affiliation(s)
- Valeria Parlatini
- Sackler Institute of Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK.
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK.
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK.
| | - Takashi Itahashi
- Medical Institute of Developmental Disabilities Research, Showa University, 6-11-11 Kita-karasuyama, Setagaya-ku, Tokyo, Japan
| | - Yeji Lee
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Sungkyunkwan University (SKKU), Suwon, 16419, Republic of Korea
| | - Siwei Liu
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Thuan T Nguyen
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Integrative Sciences and Engineering Programme, National University of Singapore, Singapore, Singapore
| | - Yuta Y Aoki
- Medical Institute of Developmental Disabilities Research, Showa University, 6-11-11 Kita-karasuyama, Setagaya-ku, Tokyo, Japan
- Department of Psychiatry, Aoki Clinic, Tokyo, Japan
| | - Stephanie J Forkel
- Donders Centre for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Centre for Neuroimaging Sciences, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
- Departments of Neurosurgery, Technical University of Munich School of Medicine, Munich, Germany
| | - Marco Catani
- Sackler Institute of Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK
| | - Katya Rubia
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK
| | - Juan H Zhou
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Integrative Sciences and Engineering Programme, National University of Singapore, Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
| | - Declan G Murphy
- Sackler Institute of Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK
| | - 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, NY, USA
- Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Nottingham, UK
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12
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Reimann GE, Stier AJ, Moore TM, Durham EL, Jeong HJ, Cardenas-Iniguez C, Dupont RM, Pines JR, Berman MG, Lahey BB, Kaczkurkin AN. Atypical Functional Network Properties and Associated Dimensions of Child Psychopathology During Rest and Task Performance. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2023; 3:541-549. [PMID: 37519454 PMCID: PMC10382736 DOI: 10.1016/j.bpsgos.2022.07.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 07/15/2022] [Accepted: 07/20/2022] [Indexed: 10/15/2022] Open
Abstract
Background When brain networks deviate from typical development, this is thought to contribute to varying forms of psychopathology. However, research has been limited by the reliance on discrete diagnostic categories that overlook the potential for psychological comorbidity and the dimensional nature of symptoms. Methods This study examined the topology of functional networks in association with 4 bifactor-defined psychopathology dimensions-general psychopathology, internalizing symptoms, conduct problems, and attention-deficit/hyperactivity disorder symptoms-via the Child Behavior Checklist in a sample of 3568 children from the ABCD (Adolescent Brain Cognitive Development) Study. Local and global graph theory metrics were calculated at rest and during tasks of reward processing, inhibition, and working memory. Results Greater attention-deficit/hyperactivity disorder symptoms were associated with reduced modularity across rest and tasks as well as reduced local efficiency in motor networks at rest. Results survived sensitivity analyses for medication and socioeconomic status. Greater conduct problem symptoms were associated with reduced modularity on working memory and reward processing tasks; however, these results did not persist after sensitivity analyses. General psychopathology and internalizing symptoms showed no significant network associations. Conclusions Our findings suggest reduced efficiency in topology in those with greater attention-deficit/hyperactivity disorder symptoms across 4 critical cognitive states, with conduct problems also showing network deficits, although less consistently. This may suggest that modularity deficits are a neurobiological marker of externalizing behavior in children. Such specificity has not been demonstrated before using graph theory metrics and has the potential to redefine our understanding of network deficits in children with psychopathology symptoms.
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Affiliation(s)
| | - Andrew J. Stier
- Department of Psychology, University of Chicago, Chicago, Illinois
| | - Tyler M. Moore
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | | | - Hee Jung Jeong
- Department of Psychology, Vanderbilt University, Nashville, Tennessee
| | - Carlos Cardenas-Iniguez
- Department of Population and Public Health Sciences, Keck School of Medicine of the University of Southern California, Los Angeles, California
| | | | - Julia R. Pines
- Department of Psychology, Vanderbilt University, Nashville, Tennessee
| | - Marc G. Berman
- Department of Psychology, University of Chicago, Chicago, Illinois
- University of Chicago Neuroscience Institute, University of Chicago, Chicago, Illinois
| | - Benjamin B. Lahey
- Departments of Health Studies and Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois
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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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14
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Deng H, Huang Z, Li Z, Cao L, He Y, Sun N, Zeng Y, Wu J. Systematic bibliometric and visualized analysis of research hotspots and trends in attention-deficit hyperactivity disorder neuroimaging. Front Neurosci 2023; 17:1098526. [PMID: 37056309 PMCID: PMC10086162 DOI: 10.3389/fnins.2023.1098526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 02/17/2023] [Indexed: 03/30/2023] Open
Abstract
IntroductionThis study focused on the research hotspots and development trends of the neuroimaging of attention deficit hyperactivity disorder (ADHD) in the past thirty years.MethodsThe Web of Science database was searched for articles about ADHD neuroimaging from January 1992 to September 2022. CiteSpace was used to analyze the co-occurrence of keywords in literature, partnerships between authors, institutions, and countries, the sudden occurrence of keywords, clustering of keywords over time, and analysis of references, cited authors, and cited journals.Results2,621 articles were included. More and more articles have been published every year in the last years. These articles mainly come from 435 institutions and 65 countries/regions led by the United States. King's College London had the highest number of publications. The study identified 634 authors, among which Buitelaar, J. K. published the largest number of articles and Castellanos, F. X. was co-cited most often. The most productive and cited journal was Biological psychiatry. In recent years, burst keywords were resting-state fMRI, machine learning, functional connectivity, and networks. And a timeline chart of the cluster of keywords showed that “children” had the longest time span.ConclusionsIncreased attention has been paid to ADHD neuroimaging. This work might assist researchers to identify new insight on potential collaborators and cooperative institutions, hot topics, and research directions.
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Affiliation(s)
- Haiyin Deng
- Department of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Zhenming Huang
- Department of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Zhaoying Li
- Department of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Lei Cao
- Department of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Youze He
- Department of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Ning Sun
- Rehabilitation Medicine Center and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Yi Zeng
- Department of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Jingsong Wu
- Department of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
- Innovation and Transformation Center, Fujian University of Traditional Chinese Medicine, Fuzhou, China
- *Correspondence: Jingsong Wu
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15
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Rafi H, Delavari F, Perroud N, Derome M, Debbané M. The continuum of attention dysfunction: Evidence from dynamic functional network connectivity analysis in neurotypical adolescents. PLoS One 2023; 18:e0279260. [PMID: 36662797 PMCID: PMC9858399 DOI: 10.1371/journal.pone.0279260] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 12/04/2022] [Indexed: 01/21/2023] Open
Abstract
The question of whether attention-related disorders such as attention-deficit/hyperactivity disorder (ADHD) are best understood as clinical categories or as extreme ends of a spectrum is an ongoing debate. Assessing individuals with varying degrees of attention problems and utilizing novel methodologies to assess relationships between attention and brain activity may provide key information to support the spectrum hypothesis. We scanned 91 neurotypical adolescents during rest using functional magnetic resonance imaging. We conducted static and dynamic functional network connectivity (FNC) analysis and correlated findings to behavioral metrics of ADHD, attention problems, and impulsivity. We found that dynamic FNC analysis detects significant differences in large-scale neural connectivity as a function of individual differences in attention and impulsivity that are obscured in static analysis. We show ADHD manifestations and attention problems are associated with diminished Salience Network-centered FNC and that ADHD manifestations and impulsivity are associated with prolonged periods of dynamically hyperconnected states. Importantly, our meta-state analysis results reveal a relationship between ADHD manifestations and exhibiting variable and volatile dynamic behavior such as changing meta-states more often and traveling over a greater dynamic range. These findings in non-clinical adolescents provide support for the continuum model of attention disorders.
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Affiliation(s)
- Halima Rafi
- Faculty of Psychology and Educational Sciences, Developmental Clinical Psychology Research Unit, University of Geneva, Geneva, Switzerland
- Department of Psychiatry, Developmental Neuroimaging and Psychopathology Laboratory, University of Geneva, Geneva, Switzerland
| | - Farnaz Delavari
- Department of Psychiatry, Developmental Neuroimaging and Psychopathology Laboratory, University of Geneva, Geneva, Switzerland
- Medical Image Processing Lab, Institute of Bioengineering, EPFL, Lausanne, Switzerland
| | - Nader Perroud
- Department of Psychiatry, Service of Psychiatric Specialties, University Hospitals of Geneva, Geneva, Switzerland
| | - Mélodie Derome
- Faculty of Psychology and Educational Sciences, Developmental Clinical Psychology Research Unit, University of Geneva, Geneva, Switzerland
- Department of Psychiatry, Developmental Neuroimaging and Psychopathology Laboratory, University of Geneva, Geneva, Switzerland
| | - Martin Debbané
- Faculty of Psychology and Educational Sciences, Developmental Clinical Psychology Research Unit, University of Geneva, Geneva, Switzerland
- Department of Psychiatry, Developmental Neuroimaging and Psychopathology Laboratory, University of Geneva, Geneva, Switzerland
- Research Department of Clinical, Educational & Health Psychology, University College London, London, United Kingdom
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Characterizing different cognitive and neurobiological profiles in a community sample of children using a non-parametric approach: An fMRI study. Dev Cogn Neurosci 2023; 60:101198. [PMID: 36652896 PMCID: PMC9853310 DOI: 10.1016/j.dcn.2023.101198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 12/06/2022] [Accepted: 01/11/2023] [Indexed: 01/14/2023] Open
Abstract
Executive Functions (EF) is an umbrella term for a set of mental processes geared towards goal-directed behavior supporting academic skills such as reading abilities. One of the brain's functional networks implicated in EF is the Default Mode Network (DMN). The current study uses measures of inhibitory control, a main sub-function of EF, to create cognitive and neurobiological "inhibitory control profiles" and relate them to reading abilities in a large sample (N = 5055) of adolescents aged 9-10 from the Adolescent Brain Cognitive Development (ABCD) study. Using a Latent Profile Analysis (LPA) approach, data related to inhibitory control was divided into four inhibition classes. For each class, functional connectivity within the DMN was calculated from resting-state data, using a non-parametric algorithm for detecting group similarities. These inhibitory control profiles were then related to reading abilities. The four inhibitory control groups showed significantly different reading abilities, with neurobiologically different DMN segregation profiles for each class versus controls. The current study demonstrates that a community sample of children is not entirely homogeneous and is composed of different subgroups that can be differentiated both behaviorally/cognitively and neurobiologically, by focusing on inhibitory control and the DMN. Educational implications relating these results to reading abilities are noted.
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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: 6] [Impact Index Per Article: 6.0] [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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Oliveira-Saraiva D, Ferreira HA. Normative model detects abnormal functional connectivity in psychiatric disorders. Front Psychiatry 2023; 14:1068397. [PMID: 36873218 PMCID: PMC9975396 DOI: 10.3389/fpsyt.2023.1068397] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 01/23/2023] [Indexed: 02/17/2023] Open
Abstract
INTRODUCTION The diagnosis of psychiatric disorders is mostly based on the clinical evaluation of the patient's signs and symptoms. Deep learning binary-based classification models have been developed to improve the diagnosis but have not yet reached clinical practice, in part due to the heterogeneity of such disorders. Here, we propose a normative model based on autoencoders. METHODS We trained our autoencoder on resting-state functional magnetic resonance imaging (rs-fMRI) data from healthy controls. The model was then tested on schizophrenia (SCZ), bipolar disorder (BD), and attention-deficit hyperactivity disorder (ADHD) patients to estimate how each patient deviated from the norm and associate it with abnormal functional brain networks' (FBNs) connectivity. Rs-fMRI data processing was conducted within the FMRIB Software Library (FSL), which included independent component analysis and dual regression. Pearson's correlation coefficients between the extracted blood oxygen level-dependent (BOLD) time series of all FBNs were calculated, and a correlation matrix was generated for each subject. RESULTS AND DISCUSSION We found that the functional connectivity related to the basal ganglia network seems to play an important role in the neuropathology of BD and SCZ, whereas in ADHD, its role is less evident. Moreover, the abnormal connectivity between the basal ganglia network and the language network is more specific to BD. The connectivity between the higher visual network and the right executive control and the connectivity between the anterior salience network and the precuneus networks are the most relevant in SCZ and ADHD, respectively. The results demonstrate that the proposed model could identify functional connectivity patterns that characterize different psychiatric disorders, in agreement with the literature. The abnormal connectivity patterns from the two independent SCZ groups of patients were similar, demonstrating that the presented normative model was also generalizable. However, the group-level differences did not withstand individual-level analysis implying that psychiatric disorders are highly heterogeneous. These findings suggest that a precision-based medical approach, focusing on each patient's specific functional network changes may be more beneficial than the traditional group-based diagnostic classification.
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Affiliation(s)
- Duarte Oliveira-Saraiva
- Institute of Biophysics and Biomedical Engineering, Faculty of Sciences of the University of Lisbon, Lisbon, Portugal
| | - Hugo Alexandre Ferreira
- Institute of Biophysics and Biomedical Engineering, Faculty of Sciences of the University of Lisbon, Lisbon, Portugal
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Sripada C, Gard AM, Angstadt M, Taxali A, Greathouse T, McCurry K, Hyde LW, Weigard A, Walczyk P, Heitzeg M. Socioeconomic resources are associated with distributed alterations of the brain's intrinsic functional architecture in youth. Dev Cogn Neurosci 2022; 58:101164. [PMID: 36274574 PMCID: PMC9589163 DOI: 10.1016/j.dcn.2022.101164] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 09/25/2022] [Accepted: 10/14/2022] [Indexed: 01/26/2023] Open
Abstract
Little is known about how exposure to limited socioeconomic resources (SER) in childhood gets "under the skin" to shape brain development, especially using rigorous whole-brain multivariate methods in large, adequately powered samples. The present study examined resting state functional connectivity patterns from 5821 youth in the Adolescent Brain Cognitive Development (ABCD) study, employing multivariate methods across three levels: whole-brain, network-wise, and connection-wise. Across all three levels, SER was associated with widespread alterations across the connectome. However, critically, we found that parental education was the primary driver of neural associations with SER. These parental education associations with the developing connectome exhibited notable concentrations in somatosensory and subcortical regions, and they were partially accounted for by home enrichment activities, child's cognitive abilities, and child's grades, indicating interwoven links between parental education, child stimulation, and child cognitive performance. These results add a new data-driven, multivariate perspective on links between household SER and the child's developing functional connectome.
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Affiliation(s)
- Chandra Sripada
- Department of Psychiatry, University of Michigan, Ann Arbor, USA.
| | - Arianna M Gard
- Department of Psychology and Neuroscience and Cognitive Neuroscience Program, University of Maryland, College Park, USA
| | - Mike Angstadt
- Department of Psychiatry, University of Michigan, Ann Arbor, USA
| | - Aman Taxali
- Department of Psychiatry, University of Michigan, Ann Arbor, USA
| | | | | | - Luke W Hyde
- Department of Psychology and Survey Research Center at the Institute for Social Research, University of Michigan, Ann Arbor, USA
| | | | - Peter Walczyk
- Department of Psychiatry, University of Michigan, Ann Arbor, USA
| | - Mary Heitzeg
- Department of Psychiatry, University of Michigan, Ann Arbor, USA
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20
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Blomberg R, Signoret C, Danielsson H, Perini I, Rönnberg J, Capusan AJ. Aberrant resting-state connectivity of auditory, ventral attention/salience and default-mode networks in adults with attention deficit hyperactivity disorder. Front Neurosci 2022; 16. [PMID: 36148149 PMCID: PMC9485623 DOI: 10.3389/fnins.2022.972730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2022] [Accepted: 08/12/2022] [Indexed: 11/18/2022] Open
Abstract
Background Numerous resting-state studies on attention deficit hyperactivity disorder (ADHD) have reported aberrant functional connectivity (FC) between the default-mode network (DMN) and the ventral attention/salience network (VA/SN). This finding has commonly been interpreted as an index of poorer DMN regulation associated with symptoms of mind wandering in ADHD literature. However, a competing perspective suggests that dysfunctional organization of the DMN and VA/SN may additionally index increased sensitivity to the external environment. The goal of the current study was to test this latter perspective in relation to auditory distraction by investigating whether ADHD-adults exhibit aberrant FC between DMN, VA/SN, and auditory networks. Methods Twelve minutes of resting-state fMRI data was collected from two adult groups: ADHD (n = 17) and controls (n = 17); from which the FC between predefined regions comprising the DMN, VA/SN, and auditory networks were analyzed. Results A weaker anticorrelation between the VA/SN and DMN was observed in ADHD. DMN and VA/SN hubs also exhibited aberrant FC with the auditory network in ADHD. Additionally, participants who displayed a stronger anticorrelation between the VA/SN and auditory network at rest, also performed better on a cognitively demanding behavioral task that involved ignoring a distracting auditory stimulus. Conclusion Results are consistent with the hypothesis that auditory distraction in ADHD is linked to aberrant interactions between DMN, VA/SN, and auditory systems. Our findings support models that implicate dysfunctional organization of the DMN and VA/SN in the disorder and encourage more research into sensory interactions with these major networks.
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Affiliation(s)
- Rina Blomberg
- Department of Behavioral Sciences and Learning, Linköping University, Linköping, Sweden
- Linnaeus Center HEAD, Linköping University, Linköping, Sweden
- Swedish Institute for Disability Research, Linköping University, Linköping, Sweden
- *Correspondence: Rina Blomberg,
| | - Carine Signoret
- Department of Behavioral Sciences and Learning, Linköping University, Linköping, Sweden
- Linnaeus Center HEAD, Linköping University, Linköping, Sweden
- Swedish Institute for Disability Research, Linköping University, Linköping, Sweden
| | - Henrik Danielsson
- Department of Behavioral Sciences and Learning, Linköping University, Linköping, Sweden
- Linnaeus Center HEAD, Linköping University, Linköping, Sweden
- Swedish Institute for Disability Research, Linköping University, Linköping, Sweden
| | - Irene Perini
- Center for Social and Affective Neuroscience, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden
| | - Jerker Rönnberg
- Department of Behavioral Sciences and Learning, Linköping University, Linköping, Sweden
- Linnaeus Center HEAD, Linköping University, Linköping, Sweden
- Swedish Institute for Disability Research, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden
| | - Andrea Johansson Capusan
- Center for Social and Affective Neuroscience, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
- Department of Psychiatry and Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
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21
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Leisman G, Melillo R. Front and center: Maturational dysregulation of frontal lobe functional neuroanatomic connections in attention deficit hyperactivity disorder. Front Neuroanat 2022; 16:936025. [PMID: 36081853 PMCID: PMC9446472 DOI: 10.3389/fnana.2022.936025] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 07/29/2022] [Indexed: 12/21/2022] Open
Abstract
Frontal lobe function may not universally explain all forms of attention deficit hyperactivity disorder (ADHD) but the frontal lobe hypothesis described supports an internally consistent model for integrating the numerous behaviors associated with ADHD. The paper examines the developmental trajectories of frontal and prefrontal lobe development, framing ADHD as maturational dysregulation concluding that the cognitive, motor, and behavioral abilities of the presumptive majority of ADHD children may not primarily be disordered or dysfunctional but reflect maturational dysregulation that is inconsistent with the psychomotor and cognitive expectations for the child’s chronological and mental age. ADHD children demonstrate decreased activation of the right and middle prefrontal cortex. Prefrontal and frontal lobe regions have an exuberant network of shared pathways with the diencephalic region, also having a regulatory function in arousal as well as with the ascending reticular formation which has a capacity for response suppression to task-irrelevant stimuli. Prefrontal lesions oftentimes are associated with the regulatory breakdown of goal-directed activity and impulsivity. In conclusion, a presumptive majority of childhood ADHD may result from maturational dysregulation of the frontal lobes with effects on the direct, indirect and/or, hyperdirect pathways.
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Affiliation(s)
- Gerry Leisman
- Movement and Cognition Laboratory, Department of Physical Therapy, University of Haifa, Haifa, Israel
- Department of Neurology, University of Medical Sciences of Havana, Havana, Cuba
- *Correspondence: Gerry Leisman,
| | - Robert Melillo
- Movement and Cognition Laboratory, Department of Physical Therapy, University of Haifa, Haifa, Israel
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22
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Chiang HL, Tseng WYI, Wey HY, Gau SSF. Shared intrinsic functional connectivity alterations as a familial risk marker for ADHD: a resting-state functional magnetic resonance imaging study with sibling design. Psychol Med 2022; 52:1736-1745. [PMID: 33046145 DOI: 10.1017/s0033291720003529] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND Although aberrant intrinsic functional connectivity has been reported in attention-deficit/hyperactivity disorder (ADHD), we have a limited understanding of whether connectivity alterations are related to the familial risk of ADHD. METHODS Fifty-three probands with ADHD, their unaffected siblings (n = 53) and typically developing controls (n = 53) underwent resting-state functional magnetic resonance imaging scans. A seed-based approach with the bilateral precuneus/posterior cingulate cortex (PCC) was used to derive a whole-brain functional connectivity map in each subject. The differences in functional connectivity among the three groups were tested with one-way ANOVA using randomized permutation. Comparisons between two groups were also performed to examine the increase or decrease in connectivity. The severity of ADHD symptoms was used to identify brain regions where symptom severity is correlated to the strength of intrinsic functional connectivity. RESULTS When compared to controls, both probands and unaffected siblings showed increased functional connectivity in the left insula and left inferior frontal gyrus. The connectivity in these regions was linked to better performance in response inhibition in the control group but absent in other groups. Higher ADHD symptom severity was correlated with increased functional connectivity in bilateral fronto-parietal-temporal regions only noted in probands with ADHD. CONCLUSIONS Alterations in resting-state functional connectivities with the precuneus/PCC, hubs of default-mode network, account for the underlying familial risks of ADHD. Since the left insula and left inferior frontal gyri are key regions of the salience and frontoparietal network, respectively, future studies focusing on alterations of cross-network functional connectivity as the familial risk of ADHD are suggested.
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Affiliation(s)
- Huey-Ling Chiang
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
- Department of Psychiatry, Far Eastern Memorial Hospital, New Taipei City, Taiwan
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, USA
| | - Wen-Yih Isaac Tseng
- Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Hsiao-Ying Wey
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, USA
| | - Susan Shur-Fen Gau
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
- Graduate Institute of Clinical Medicine, and Graduate Institute of Brain and Mind Sciences, National Taiwan University College of Medicine, Taipei, Taiwan
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23
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Nandakumar N, Hsu D, Ahmed R, Venkataraman A. DeepEZ: A Graph Convolutional Network for Automated Epileptogenic Zone Localization from Resting-State fMRI Connectivity. IEEE Trans Biomed Eng 2022; 70:216-227. [PMID: 35776823 PMCID: PMC9841829 DOI: 10.1109/tbme.2022.3187942] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
OBJECTIVE Epileptogenic zone (EZ) localization is a crucial step during diagnostic work up and therapeutic planning in medication refractory epilepsy. In this paper, we present the first deep learning approach to localize the EZ based on resting-state fMRI (rs-fMRI) data. METHODS Our network, called DeepEZ, uses a cascade of graph convolutions that emphasize signal propagation along expected anatomical pathways. We also integrate domain-specific information, such as an asymmetry term on the predicted EZ and a learned subject-specific bias to mitigate environmental confounds. RESULTS We validate DeepEZ on rs-fMRI collected from 14 patients with focal epilepsy at the University of Wisconsin Madison. Using cross validation, we demonstrate that DeepEZ achieves consistently high EZ localization performance (Accuracy: 0.88 ± 0.03; AUC: 0.73 ± 0.03) that far outstripped any of the baseline methods. This performance is notable given the variability in EZ locations and scanner type across the cohort. CONCLUSION Our results highlight the promise of using DeepEZ as an accurate and noninvasive therapeutic planning tool for medication refractory epilepsy. SIGNIFICANCE While prior work in EZ localization focused on identifying localized aberrant signatures, there is growing evidence that epileptic seizures affect inter-regional connectivity in the brain. DeepEZ allows clinicians to harness this information from noninvasive imaging that can easily be integrated into the existing clinical workflow.
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Affiliation(s)
- Naresh Nandakumar
- Department of Electrical and Computer Engineering, Johns Hopkins University, USA
| | - David Hsu
- Department of Neurology, University of Wisconsin, USA
| | - Raheel Ahmed
- Department of Neurosurgery, University of Wisconsin, USA
| | - Archana Venkataraman
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218 USA
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24
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Saad JF, Griffiths KR, Kohn MR, Braund TA, Clarke S, Williams LM, Korgaonkar MS. Intrinsic Functional Connectivity in the Default Mode Network Differentiates the Combined and Inattentive Attention Deficit Hyperactivity Disorder Types. Front Hum Neurosci 2022; 16:859538. [PMID: 35754775 PMCID: PMC9218495 DOI: 10.3389/fnhum.2022.859538] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 05/20/2022] [Indexed: 12/24/2022] Open
Abstract
Neuroimaging studies have revealed neurobiological differences in ADHD, particularly studies examining connectivity disruption and anatomical network organization. However, the underlying pathophysiology of ADHD types remains elusive as it is unclear whether dysfunctional network connections characterize the underlying clinical symptoms distinguishing ADHD types. Here, we investigated intrinsic functional network connectivity to identify neural signatures that differentiate the combined (ADHD-C) and inattentive (ADHD-I) presentation types. Applying network-based statistical (NBS) and graph theoretical analysis to task-derived intrinsic connectivity data from completed fMRI scans, we evaluated default mode network (DMN) and whole-brain functional network topology in a cohort of 34 ADHD participants (aged 8–17 years) defined using DSM-IV criteria as predominantly inattentive (ADHD-I) type (n = 15) or combined (ADHD-C) type (n = 19), and 39 age and gender-matched typically developing controls. ADHD-C were characterized from ADHD-I by reduced network connectivity differences within the DMN. Additionally, reduced connectivity within the DMN was negatively associated with ADHD-RS hyperactivity-impulsivity subscale score. Compared with controls, ADHD-C but not ADHD-I differed by reduced connectivity within the DMN; inter-network connectivity between the DMN and somatomotor networks; the DMN and limbic networks; and between the somatomotor and cingulo-frontoparietal, with ventral attention and dorsal attention networks. However, graph-theoretical measures did not significantly differ between groups. These findings provide insight into the intrinsic networks underlying phenotypic differences between ADHD types. Furthermore, these intrinsic functional connectomic signatures support neurobiological differences underlying clinical variations in ADHD presentations, specifically reduced within and between functional connectivity of the DMN in the ADHD-C type.
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Affiliation(s)
- Jacqueline F Saad
- Brain Dynamics Centre, Westmead Institute for Medical Research, The University of Sydney, Sydney, NSW, Australia.,School of Medicine, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Kristi R Griffiths
- Brain Dynamics Centre, Westmead Institute for Medical Research, The University of Sydney, Sydney, NSW, Australia
| | - Michael R Kohn
- Brain Dynamics Centre, Westmead Institute for Medical Research, The University of Sydney, Sydney, NSW, Australia.,Centre for Research Into Adolescent's Health, Department of Adolescent and Young Adult Medicine, Westmead Hospital, Sydney, NSW, Australia
| | - Taylor A Braund
- Brain Dynamics Centre, Westmead Institute for Medical Research, The University of Sydney, Sydney, NSW, Australia.,School of Medicine, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.,Black Dog Institute, University of New South Wales, Sydney, NSW, Australia.,School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - Simon Clarke
- Brain Dynamics Centre, Westmead Institute for Medical Research, The University of Sydney, Sydney, NSW, Australia.,Centre for Research Into Adolescent's Health, Department of Adolescent and Young Adult Medicine, Westmead Hospital, Sydney, NSW, Australia
| | - Leanne M Williams
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States.,Sierra Pacific Mental Illness Research Education and Clinical Center, VA Palo Alto Health Care System, Palo Alto, CA, United States
| | - Mayuresh S Korgaonkar
- Brain Dynamics Centre, Westmead Institute for Medical Research, The University of Sydney, Sydney, NSW, Australia.,School of Medicine, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
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25
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Wang R, Fan Y, Wu Y, Zang YF, Zhou C. Lifespan associations of resting-state brain functional networks with ADHD symptoms. iScience 2022; 25:104673. [PMID: 35832890 PMCID: PMC9272385 DOI: 10.1016/j.isci.2022.104673] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 04/26/2022] [Accepted: 06/21/2022] [Indexed: 12/04/2022] Open
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is increasingly being diagnosed in both children and adults, but the neural mechanisms that underlie its distinct symptoms and whether children and adults share the same mechanism remain poorly understood. Here, we used a nested-spectral partition approach to study resting-state brain networks of ADHD patients (n = 97) and healthy controls (HCs, n = 97) across the lifespan (7–50 years). Compared to the linear lifespan associations of brain segregation and integration with age in HCs, ADHD patients have a quadratic association in the whole-brain and in most functional systems, whereas the limbic system dominantly affected by ADHD has a linear association. Furthermore, the limbic system better predicts hyperactivity, and the salient attention system better predicts inattention. These predictions are shared in children and adults with ADHD. Our findings reveal a lifespan association of brain networks with ADHD and provide potential shared neural bases of distinct ADHD symptoms in children and adults. ADHD patients have a quadratic association with age in brain functional networks Limbic system better predicts hyperactivity across the lifespan Salient attention system better predicts the inattention across the lifespan The predictions on symptom scores are shared in ADHD children and adults
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26
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Mizuno Y, Cai W, Supekar K, Makita K, Takiguchi S, Tomoda A, Menon V. Methylphenidate remediates aberrant brain network dynamics in children with attention-deficit/hyperactivity disorder: a randomized controlled trial. Neuroimage 2022; 257:119332. [PMID: 35640787 PMCID: PMC9286726 DOI: 10.1016/j.neuroimage.2022.119332] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 04/20/2022] [Accepted: 05/24/2022] [Indexed: 12/15/2022] Open
Abstract
Methylphenidate is a widely used first-line treatment for attention deficit/hyperactivity disorder (ADHD), but the underlying circuit mechanisms are poorly understood. Here we investigate whether a single dose of osmotic release oral system methylphenidate can remediate attention deficits and aberrancies in functional circuit dynamics in cognitive control networks, which have been implicated in ADHD. In a randomized placebo-controlled double-blind crossover design, 27 children with ADHD were scanned twice with resting-state functional MRI and sustained attention was examined using a continuous performance task under methylphenidate and placebo conditions; 49 matched typically-developing (TD) children were scanned once for comparison. Dynamic time-varying cross-network interactions between the salience (SN), frontoparietal (FPN), and default mode (DMN) networks were examined in children with ADHD under both administration conditions and compared with TD children. Methylphenidate improved sustained attention on a continuous performance task in children with ADHD, when compared to the placebo condition. Children with ADHD under placebo showed aberrancies in dynamic time-varying cross-network interactions between the SN, FPN and DMN, which were remediated by methylphenidate. Multivariate classification analysis confirmed that methylphenidate remediates aberrant dynamic brain network interactions. Furthermore, dynamic time-varying network interactions under placebo conditions predicted individual differences in methylphenidate-induced improvements in sustained attention in children with ADHD. These findings suggest that a single dose of methylphenidate can remediate deficits in sustained attention and aberrant brain circuit dynamics in cognitive control circuits in children with ADHD. Findings identify a novel brain circuit mechanism underlying a first-line pharmacological treatment for ADHD, and may inform clinically useful biomarkers for evaluating treatment outcomes.
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Affiliation(s)
- Yoshifumi Mizuno
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA; Research Center for Child Mental Development, University of Fukui, Fukui, 910-1193, Japan; Division of Developmental Higher Brain Functions, United Graduate School of Child Development, University of Fukui, Fukui, 910-1193, Japan; Department of Child and Adolescent Psychological Medicine, University of Fukui Hospital, Fukui, 910-1193, Japan.
| | - Weidong Cai
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA 94304, USA; Maternal & Child Health Research Institute, Stanford University, Stanford, CA 94304, USA
| | - Kaustubh Supekar
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA 94304, USA; Maternal & Child Health Research Institute, Stanford University, Stanford, CA 94304, USA
| | - Kai Makita
- Research Center for Child Mental Development, University of Fukui, Fukui, 910-1193, Japan; Division of Developmental Higher Brain Functions, United Graduate School of Child Development, University of Fukui, Fukui, 910-1193, Japan
| | - Shinichiro Takiguchi
- Division of Developmental Higher Brain Functions, United Graduate School of Child Development, University of Fukui, Fukui, 910-1193, Japan; Department of Child and Adolescent Psychological Medicine, University of Fukui Hospital, Fukui, 910-1193, Japan
| | - Akemi Tomoda
- Research Center for Child Mental Development, University of Fukui, Fukui, 910-1193, Japan; Division of Developmental Higher Brain Functions, United Graduate School of Child Development, University of Fukui, Fukui, 910-1193, Japan; Department of Child and Adolescent Psychological Medicine, University of Fukui Hospital, Fukui, 910-1193, Japan.
| | - Vinod Menon
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA; Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94304, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA 94304, USA; Maternal & Child Health Research Institute, Stanford University, Stanford, CA 94304, USA
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27
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Frontal corticostriatal functional connectivity reveals task positive and negative network dysregulation in relation to ADHD, sex, and inhibitory control. Dev Cogn Neurosci 2022; 54:101101. [PMID: 35338900 PMCID: PMC8956922 DOI: 10.1016/j.dcn.2022.101101] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 03/18/2022] [Accepted: 03/18/2022] [Indexed: 01/21/2023] Open
Abstract
Frontal corticostriatal circuits (FCSC) are involved in self-regulation of cognition, emotion, and motor function. While these circuits are implicated in attention-deficit/hyperactivity disorder (ADHD), the literature establishing FCSC associations with ADHD is inconsistent. This may be due to study variability in considerations of how fMRI motion regression was handled between groups, or study specific differences in age, sex, or the striatal subregions under investigation. Given the importance of these domains in ADHD it is crucial to consider the complex interactions of age, sex, striatal subregions and FCSC in ADHD presentation and diagnosis. In this large-scale study of 362 8-12 year-old children with ADHD (n = 165) and typically developing (TD; n = 197) children, we investigate associations between FCSC with ADHD diagnosis and symptoms, sex, and go/no-go (GNG) task performance. Results include: (1) increased striatal connectivity with age across striatal subregions with most of the frontal cortex, (2) increased frontal-limbic striatum connectivity among boys with ADHD only, mostly in default mode network (DMN) regions not associated with age, and (3) increased frontal-motor striatum connectivity to regions of the DMN were associated with greater parent-rated inattention problems, particularly among the ADHD group. Although diagnostic group differences were no longer significant when strictly controlling for head motion, with motion possibly reflecting the phenotypic variance of ADHD itself, the spatial distribution of all symptom, age, sex, and other ADHD group effects were nearly identical to the initial results. These results demonstrate differential associations of FCSC between striatal subregions with the DMN and FPN in relation to age, ADHD, sex, and inhibitory control.
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28
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González-Madruga K, Staginnus M, Fairchild G. Alterations in Structural and Functional Connectivity in ADHD: Implications for Theories of ADHD. Curr Top Behav Neurosci 2022; 57:445-481. [PMID: 35583796 DOI: 10.1007/7854_2022_345] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Attention-Deficit/Hyperactivity Disorder (ADHD) is increasingly viewed as a disorder of brain connectivity. We review connectivity-based theories of ADHD including the default mode network (DMN) interference and multiple network hypotheses. We outline the main approaches used to study brain connectivity in ADHD: diffusion tensor imaging and resting-state functional connectivity. We discuss the basic principles underlying these methods and the main analytical approaches used and consider what the findings have told us about connectivity alterations in ADHD. The most replicable finding in the diffusion tensor imaging literature on ADHD is lower fractional anisotropy in the corpus callosum, a key commissural tract which connects the brain's hemispheres. Meta-analyses of resting-state functional connectivity studies have failed to identify spatial convergence across studies, with the exception of meta-analyses focused on specific networks which have reported within-network connectivity alterations in the DMN and between the DMN and the fronto-parietal control and salience networks. Overall, methodological heterogeneity between studies and differences in sample characteristics are major barriers to progress in this area. In addition, females, adults and medication-naïve/unmedicated individuals are under-represented in connectivity studies, comorbidity needs to be assessed more systematically, and longitudinal research is needed to investigate whether ADHD is characterized by maturational delays in connectivity.
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29
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Zhao Y, Nebel MB, Caffo BS, Mostofsky SH, Rosch KS. Beyond Massive Univariate Tests: Covariance Regression Reveals Complex Patterns of Functional Connectivity Related to Attention-Deficit/Hyperactivity Disorder, Age, Sex, and Response Control. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2022; 2:8-16. [PMID: 35528865 PMCID: PMC9074810 DOI: 10.1016/j.bpsgos.2021.06.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Background Studies of brain functional connectivity (FC) typically involve massive univariate tests, performing statistical analysis on each individual connection. In this study, we apply a novel whole-matrix regression approach referred to as covariate assisted principal regression to identify resting-state FC brain networks associated with attention-deficit/hyperactivity disorder (ADHD) and response control. Methods Participants included 8- to 12-year-old children with ADHD (n = 115; 29 girls) and typically developing control children (n = 102; 35 girls) who completed a resting-state functional magnetic resonance imaging scan and a Go/NoGo task. We modeled three sets of covariates to identify resting-state networks associated with an ADHD diagnosis, sex, and response inhibition (commission errors) and variability (ex-Gaussian parameter tau). Results The first network includes FC between striatal-cognitive control (CC) network subregions and thalamic-default mode network (DMN) subregions and is positively related to age. The second consists of FC between CC-visual-somatomotor regions and between CC-DMN subregions and is positively associated with response variability in boys with ADHD. The third consists of FC within the DMN and between DMN-CC-visual regions and differs between boys with and without ADHD. The fourth consists of FC between visual-somatomotor regions and between visual-DMN regions and differs between girls and boys with ADHD and is associated with response inhibition and variability in boys with ADHD. Unique networks were also identified in each of the three models, suggesting some specificity to the covariates of interest. Conclusions These findings demonstrate the utility of our novel covariance regression approach to studying functional brain networks relevant for development, behavior, and psychopathology.
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30
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Jones JS, The Calm Team, Astle DE. A transdiagnostic data-driven study of children's behaviour and the functional connectome. Dev Cogn Neurosci 2021; 52:101027. [PMID: 34700195 PMCID: PMC8551598 DOI: 10.1016/j.dcn.2021.101027] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 10/06/2021] [Accepted: 10/19/2021] [Indexed: 10/24/2022] Open
Abstract
Behavioural difficulties are seen as hallmarks of many neurodevelopmental conditions. Differences in functional brain organisation have been observed in these conditions, but little is known about how they are related to a child's profile of behavioural difficulties. We investigated whether behavioural difficulties are associated with how the brain is functionally organised in an intentionally heterogeneous and transdiagnostic sample of 957 children aged 5-15. We used consensus community detection to derive data-driven profiles of behavioural difficulties and constructed functional connectomes from a subset of 238 children with resting-state functional Magnetic Resonance Imaging (fMRI) data. We identified three distinct profiles of behaviour that were characterised by principal difficulties with hot executive function, cool executive function, and learning. Global organisation of the functional connectome did not differ between the groups, but multivariate patterns of connectivity at the level of Intrinsic Connectivity Networks (ICNs), nodes, and hubs significantly predicted group membership in held-out data. Fronto-parietal connector hubs were under-connected in all groups relative to a comparison sample and children with hot vs cool executive function difficulties were distinguished by connectivity in ICNs associated with cognitive control, emotion processing, and social cognition. This demonstrates both general and specific neurodevelopmental risk factors in the functional connectome.
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Affiliation(s)
- Jonathan S Jones
- MRC Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge CB2 7EF, UK.
| | - The Calm Team
- MRC Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge CB2 7EF, UK
| | - Duncan E Astle
- MRC Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge CB2 7EF, UK
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31
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Sripada C, Angstadt M, Taxali A, Kessler D, Greathouse T, Rutherford S, Clark DA, Hyde LW, Weigard A, Brislin SJ, Hicks B, Heitzeg M. Widespread attenuating changes in brain connectivity associated with the general factor of psychopathology in 9- and 10-year olds. Transl Psychiatry 2021; 11:575. [PMID: 34753911 PMCID: PMC8578613 DOI: 10.1038/s41398-021-01708-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 10/18/2021] [Accepted: 10/26/2021] [Indexed: 12/14/2022] Open
Abstract
Convergent research identifies a general factor ("P factor") that confers transdiagnostic risk for psychopathology. Large-scale networks are key organizational units of the human brain. However, studies of altered network connectivity patterns associated with the P factor are limited, especially in early adolescence when most mental disorders are first emerging. We studied 11,875 9- and 10-year olds from the Adolescent Brain and Cognitive Development (ABCD) study, of whom 6593 had high-quality resting-state scans. Network contingency analysis was used to identify altered interconnections associated with the P factor among 16 large-scale networks. These connectivity changes were then further characterized with quadrant analysis that quantified the directionality of P factor effects in relation to neurotypical patterns of positive versus negative connectivity across connections. The results showed that the P factor was associated with altered connectivity across 28 network cells (i.e., sets of connections linking pairs of networks); pPERMUTATION values < 0.05 FDR-corrected for multiple comparisons. Higher P factor scores were associated with hypoconnectivity within default network and hyperconnectivity between default network and multiple control networks. Among connections within these 28 significant cells, the P factor was predominantly associated with "attenuating" effects (67%; pPERMUTATION < 0.0002), i.e., reduced connectivity at neurotypically positive connections and increased connectivity at neurotypically negative connections. These results demonstrate that the general factor of psychopathology produces attenuating changes across multiple networks including default network, involved in spontaneous responses, and control networks involved in cognitive control. Moreover, they clarify mechanisms of transdiagnostic risk for psychopathology and invite further research into developmental causes of distributed attenuated connectivity.
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Affiliation(s)
- Chandra Sripada
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.
| | - Mike Angstadt
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Aman Taxali
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Daniel Kessler
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
- Department of Statistics, University of Michigan, Ann Arbor, MI, USA
| | | | - Saige Rutherford
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - D Angus Clark
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Luke W Hyde
- Department of Psychology and Survey Research Center at the Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Alex Weigard
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Sarah J Brislin
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Brian Hicks
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Mary Heitzeg
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
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Li J, Liu J, Zhong Y, Wang H, Yan B, Zheng K, Wei L, Lu H, Li B. Causal Interactions Between the Default Mode Network and Central Executive Network in Patients with Major Depression. Neuroscience 2021; 475:93-102. [PMID: 34487819 DOI: 10.1016/j.neuroscience.2021.08.033] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Revised: 08/25/2021] [Accepted: 08/26/2021] [Indexed: 11/15/2022]
Abstract
Two different but interacting neural systems exist in the human brain: the task positive networks and task negative networks. One of the most important task positive networks is the central executive network (CEN), while the task negative network generally refers to the default mode network (DMN), which usually demonstrates task-induced deactivation. Although previous studies have clearly shown the association of both the CEN and DMN with major depressive disorder (MDD), how the causal interactions between these two networks change in depressed patients remains unclear. In the current study, 99 subjects (43 patients with MDD and 56 healthy controls) were recruited with their resting-state fMRI data collected. After data preprocessing, spectral dynamic causal modeling (spDCM) was used to investigate the causal interactions within and between the DMN and CEN. Group commonalities and differences in causal interaction patterns within and between the CEN and DMN in patients and controls were assessed by a parametric empirical Bayes (PEB) model. Both subject groups demonstrated significant effective connectivity between regions of the CEN and DMN. In particular, we detected inhibitory influences from the CEN to the DMN with node-level PEB analyses, which may help to explain the anticorrelations between these two networks consistently reported in previous studies. Compared with healthy controls, patients with MDD showed increased effective connectivity within the CEN and decreased connectivity from regions of the CEN to DMN, suggesting impaired control of the DMN by the CEN in these patients. These findings might provide new insights into the neural substrates of MDD.
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Affiliation(s)
- Jiaming Li
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi 710032, China; School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Jian Liu
- Network Center, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Yufang Zhong
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Huaning Wang
- Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Baoyu Yan
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Kaizhong Zheng
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Lei Wei
- Network Center, Fourth Military Medical University, Xi'an, Shaanxi 710032, China
| | - Hongbing Lu
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi 710032, China.
| | - Baojuan Li
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi 710032, China.
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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 2021; 2:350-367. [DOI: 10.1016/j.bpsgos.2021.10.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [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
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Cui X, Ding C, Wei J, Xue J, Wang X, Wang B, Xiang J. Analysis of Dynamic Network Reconfiguration in Adults with Attention-Deficit/Hyperactivity Disorder Based Multilayer Network. Cereb Cortex 2021; 31:4945-4957. [PMID: 34023872 DOI: 10.1093/cercor/bhab133] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 04/15/2021] [Accepted: 04/15/2021] [Indexed: 11/12/2022] Open
Abstract
Attention-deficit/hyperactivity disorder (ADHD) has been reported exist abnormal topology structure in the brain network. However, these studies often treated the brain as a static monolithic structure, and dynamic characteristics were ignored. Here, we investigated how the dynamic network reconfiguration in ADHD patients differs from that in healthy people. Specifically, we acquired resting-state functional magnetic resonance imaging data from a public dataset including 40 ADHD patients and 50 healthy people. A novel model of a "time-varying multilayer network" and metrics of recruitment and integration were applied to describe group differences. The results showed that the integration scores of ADHD patients were significantly lower than those of controls at every level. The recruitment scores were lower than healthy people except for the whole-brain level. It is worth noting that the subcortical network and the thalamus in ADHD patients exhibited reduced alliance preference both within and between functional networks. In addition, we also found that recruitment and integration coefficients showed a significant correlation with symptom severity in some regions. Our results demonstrate that the capability to communicate within or between some functional networks is impaired in ADHD patients. These evidences provide a new opportunity for studying the characteristics of ADHD brain networks.
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Affiliation(s)
- Xiaohong Cui
- College of Information and Computer, Taiyuan University of Technology, Taiyuan 030600, China
| | - Congli Ding
- College of Information and Computer, Taiyuan University of Technology, Taiyuan 030600, China
| | - Jing Wei
- College of Information and Computer, Taiyuan University of Technology, Taiyuan 030600, China
| | - Jiayue Xue
- College of Information and Computer, Taiyuan University of Technology, Taiyuan 030600, China
| | - Xiaoyue Wang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan 030600, China
| | - Bin Wang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan 030600, China
| | - Jie Xiang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan 030600, China
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Rubia K, Westwood S, Aggensteiner PM, Brandeis D. Neurotherapeutics for Attention Deficit/Hyperactivity Disorder (ADHD): A Review. Cells 2021; 10:cells10082156. [PMID: 34440925 PMCID: PMC8394071 DOI: 10.3390/cells10082156] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 08/07/2021] [Accepted: 08/18/2021] [Indexed: 01/19/2023] Open
Abstract
This review focuses on the evidence for neurotherapeutics for attention deficit/hyperactivity disorder (ADHD). EEG-neurofeedback has been tested for about 45 years, with the latest meta-analyses of randomised controlled trials (RCT) showing small/medium effects compared to non-active controls only. Three small studies piloted neurofeedback of frontal activations in ADHD using functional magnetic resonance imaging or near-infrared spectroscopy, finding no superior effects over control conditions. Brain stimulation has been applied to ADHD using mostly repetitive transcranial magnetic and direct current stimulation (rTMS/tDCS). rTMS has shown mostly negative findings on improving cognition or symptoms. Meta-analyses of tDCS studies targeting mostly the dorsolateral prefrontal cortex show small effects on cognitive improvements with only two out of three studies showing clinical improvements. Trigeminal nerve stimulation has been shown to improve ADHD symptoms with medium effect in one RCT. Modern neurotherapeutics are attractive due to their relative safety and potential neuroplastic effects. However, they need to be thoroughly tested for clinical and cognitive efficacy across settings and beyond core symptoms and for their potential for individualised treatment.
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Affiliation(s)
- Katya Rubia
- Department of Child & Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neurosciences, King’s College London, De Crespigny Park, London SE5 8AF, UK;
- Department of Social Genetics and Developmental Psychiatry, Institute of Psychiatry, Psychology & Neurosciences, King’s College London, De Crespigny Park, London SE5 8AF, UK
- Department of Child & Adolescent Psychiatry, Transcampus, Dresden University, 01307 Dresden, Germany
- Correspondence:
| | - Samuel Westwood
- Department of Child & Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neurosciences, King’s College London, De Crespigny Park, London SE5 8AF, UK;
- Department of Social Genetics and Developmental Psychiatry, Institute of Psychiatry, Psychology & Neurosciences, King’s College London, De Crespigny Park, London SE5 8AF, UK
- Department of Psychology, Wolverhampton University, Wolverhampton WV1 1LY, UK
| | - Pascal-M. Aggensteiner
- Department of Child and Adolescent Psychiatry and Psychotherapy, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, 68159 Mannheim, Germany; (P.-M.A.); (D.B.)
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, 68159 Mannheim, Germany; (P.-M.A.); (D.B.)
- Department of Child and Adolescent Psychiatry and Psychotherapy, Hospital of Psychiatry, Psychiatric Hospital University, University of Zürich, 8032 Zürich, Switzerland
- Neuroscience Center Zürich, Swiss Federal Institute of Technology and University of Zürich, 8057 Zürich, Switzerland
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Ahmadi M, Kazemi K, Kuc K, Cybulska-Klosowicz A, Helfroush MS, Aarabi A. Resting state dynamic functional connectivity in children with attention deficit/hyperactivity disorder. J Neural Eng 2021; 18. [PMID: 34289458 DOI: 10.1088/1741-2552/ac16b3] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 07/21/2021] [Indexed: 11/11/2022]
Abstract
Attention deficit/hyperactivity disorder (ADHD) is characterized by inattention, hyperactivity and impulsivity. In this study, we investigated group differences in dynamic functional connectivity (dFC) between 113 children with inattentive (46 ADHDI) and combined (67 ADHDC) ADHD and 76 typically developing (TD) children using resting-state functional MRI data. For dynamic connectivity analysis, the data were first decomposed into 100 independent components, among which 88 were classified into eight well-known resting-state networks (RSNs). Three discrete FC states were then identified using k-means clustering and used to estimate transition probabilities between states in both patient and control groups using a hidden Markov model. Our results showed state-dependent alterations in intra and inter-network connectivity in both ADHD subtypes in comparison with TD. Spending less time than healthy controls in state 1, both ADHDIand ADHDCwere characterized with weaker intra-hemispheric connectivity with functional asymmetries. In this state, ADHDIfurther showed weaker inter-hemispheric connectivity. The patients spent more time in state 2, exhibiting characteristic abnormalities in corticosubcortical and corticocerebellar connectivity. In state 3, a less frequently state observed across the ADHD and TD children, ADHDCwas differentiated from ADHDIby significant alterations in FC between bilateral temporal regions and other brain areas in comparison with TD. Across all three states, several strategic brain regions, mostly bilateral, exhibited significant alterations in both static functional connectivity (sFC) and dFC in the ADHD groups compared to TD, including inferior, middle and superior temporal gyri, middle frontal gyri, insula, anterior cingulum cortex, precuneus, calcarine, fusiform, superior motor area, and cerebellum. Our results show distributed abnormalities in sFC and dFC between different large-scale RSNs including cortical and subcortical regions in both ADHD subtypes compared to TD. Our findings show that the dynamic changes in brain FC can better explain the underlying pathophysiology of ADHD such as deficits in visual cognition, attention, memory and emotion processing, and cognitive and motor control.
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Affiliation(s)
- Maliheh Ahmadi
- Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran
| | - Kamran Kazemi
- Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran
| | - Katarzyna Kuc
- SWPS University of Social Sciences and Humanities, Warsaw, Poland
| | - Anita Cybulska-Klosowicz
- Laboratory of Emotions Neurobiology, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
| | | | - Ardalan Aarabi
- Laboratory of Functional Neuroscience and Pathologies (LNFP EA4559), University Research Center (CURS), University Hospital, Amiens, France.,Faculty of Medicine, University of Picardy Jules Verne, Amiens, France
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Levakov G, Faskowitz J, Avidan G, Sporns O. Mapping individual differences across brain network structure to function and behavior with connectome embedding. Neuroimage 2021; 242:118469. [PMID: 34390875 PMCID: PMC8464439 DOI: 10.1016/j.neuroimage.2021.118469] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 07/29/2021] [Accepted: 08/10/2021] [Indexed: 01/21/2023] Open
Abstract
The connectome, a comprehensive map of the brain’s anatomical connections, is often summarized as a matrix comprising all dyadic connections among pairs of brain regions. This representation cannot capture higher-order relations within the brain graph. Connectome embedding (CE) addresses this limitation by creating compact vectorized representations of brain nodes capturing their context in the global network topology. Here, nodes “context” is defined as random walks on the brain graph and as such, represents a generative model of diffusive communication around nodes. Applied to group-averaged structural connectivity, CE was previously shown to capture relations between inter-hemispheric homologous brain regions and uncover putative missing edges from the network reconstruction. Here we extend this framework to explore individual differences with a novel embedding alignment approach. We test this approach in two lifespan datasets (NKI: n = 542; Cam-CAN: n = 601) that include diffusion-weighted imaging, resting-state fMRI, demographics and behavioral measures. We demonstrate that modeling functional connectivity with CE substantially improves structural to functional connectivity mapping both at the group and subject level. Furthermore, age-related differences in this structure-function mapping, are preserved and enhanced. Importantly, CE captures individual differences by out-of-sample prediction of age and intelligence. The resulting predictive accuracy was higher compared to using structural connectivity and functional connectivity. We attribute these findings to the capacity of the CE to incorporate aspects of both anatomy (the structural graph) and function (diffusive communication). Our novel approach allows mapping individual differences in the connectome through structure to function and behavior.
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Affiliation(s)
- Gidon Levakov
- Department of Cognitive and Brain Sciences, Ben-Gurion University of the Negev, Israel; Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Israel.
| | - Joshua Faskowitz
- Department of Psychological and Brain Sciences, Indiana University, USA; Program in Neuroscience, Indiana University, USA
| | - Galia Avidan
- Department of Cognitive and Brain Sciences, Ben-Gurion University of the Negev, Israel; Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Israel; Department of Psychology, Ben-Gurion University of the Negev, Israel
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University, USA; Program in Neuroscience, Indiana University, USA
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Inhibition-related modulation of salience and frontoparietal networks predicts cognitive control ability and inattention symptoms in children with ADHD. Mol Psychiatry 2021; 26:4016-4025. [PMID: 31664176 PMCID: PMC7188596 DOI: 10.1038/s41380-019-0564-4] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 09/24/2019] [Accepted: 10/12/2019] [Indexed: 01/09/2023]
Abstract
Attention-deficit hyperactivity disorder (ADHD) is associated with pervasive impairments in attention and cognitive control. Although brain circuits underlying these impairments have been extensively investigated with resting-state fMRI, little is known about task-evoked functional brain circuits and their relation to cognitive control deficits and inattention symptoms in children with ADHD. Children with ADHD and age, gender and head motion matched typically developing (TD) children completed a Go/NoGo fMRI task. We used multivariate and dimensional analyses to investigate impairments in two core cognitive control systems: (i) cingulo-opercular "salience" network (SN) anchored in the right anterior insula, dorsal anterior cingulate cortex (rdACC), and ventrolateral prefrontal cortex (rVLPFC) and (ii) dorsal frontoparietal "central executive" (FPN) network anchored in right dorsolateral prefrontal cortex (rDLPFC) and posterior parietal cortex (rPPC). We found that multivariate patterns of task-evoked effective connectivity between brain regions in SN and FPN distinguished the ADHD and TD groups, with rDLPFC-rPPC connectivity emerging as the most distinguishing link. Task-evoked rdACC-rVLPFC connectivity was positively correlated with NoGo accuracy, and negatively correlated with severity of inattention symptoms. Brain-behavior relationships were robust against potential age, gender, and head motion confounds. Our findings highlight aberrancies in task-evoked modulation of SN and FPN connectivity in children with ADHD. Crucially, cingulo-frontal connectivity was a common locus of deficits in cognitive control and clinical measures of inattention symptoms. Our study provides insights into a parsimonious systems neuroscience model of cognitive control deficits in ADHD, and suggests specific circuit biomarkers for predicting treatment outcomes in childhood ADHD.
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Duffy KA, Rosch KS, Nebel MB, Seymour KE, Lindquist MA, Pekar JJ, Mostofsky SH, Cohen JR. Increased integration between default mode and task-relevant networks in children with ADHD is associated with impaired response control. Dev Cogn Neurosci 2021; 50:100980. [PMID: 34252881 PMCID: PMC8278154 DOI: 10.1016/j.dcn.2021.100980] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 06/03/2021] [Accepted: 06/17/2021] [Indexed: 01/22/2023] Open
Abstract
Default mode network (DMN) dysfunction is theorized to play a role in attention lapses and task errors in children with attention-deficit/hyperactivity disorder (ADHD). In ADHD, the DMN is hyperconnected to task-relevant networks, and both increased functional connectivity and reduced activation are related to poor task performance. The current study extends existing literature by considering interactions between the DMN and task-relevant networks from a brain network perspective and by assessing how these interactions relate to response control. We characterized both static and time-varying functional brain network organization during the resting state in 43 children with ADHD and 43 age-matched typically developing (TD) children. We then related aspects of network integration to go/no-go performance. We calculated participation coefficient (PC), a measure of a region’s inter-network connections, for regions of the DMN, canonical cognitive control networks (fronto-parietal, salience/cingulo-opercular), and motor-related networks (somatomotor, subcortical). Mean PC was higher in children with ADHD as compared to TD children, indicating greater integration across networks. Further, higher and less variable PC was related to greater commission error rate in children with ADHD. Together, these results inform our understanding of the role of the DMN and its interactions with task-relevant networks in response control deficits in ADHD. The DMN is more integrated with task-relevant networks in children with ADHD. Higher and less variable DMN integration relates to poorer response control in ADHD. DMN dysfunction may play a key role in response control deficits in ADHD.
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Affiliation(s)
- Kelly A Duffy
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Keri S Rosch
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, USA; Department of Neuropsychology, Kennedy Krieger Institute, Baltimore, MD, USA; Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Mary Beth Nebel
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| | - Karen E Seymour
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, USA; Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, USA; Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Martin A Lindquist
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - James J Pekar
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA; Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
| | - Stewart H Mostofsky
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, USA; Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| | - Jessica R Cohen
- Department of Psychology and Neuroscience, 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; Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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40
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Abbas AK, Azemi G, Amiri S, Ravanshadi S, Omidvarnia A. Effective connectivity in brain networks estimated using EEG signals is altered in children with ADHD. Comput Biol Med 2021; 134:104515. [PMID: 34126282 DOI: 10.1016/j.compbiomed.2021.104515] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Revised: 05/16/2021] [Accepted: 05/21/2021] [Indexed: 11/18/2022]
Abstract
This study presents a methodology developed for estimating effective connectivity in brain networks (BNs) using multichannel scalp EEG recordings. The methodology uses transfer entropy as an information transfer measure to detect pair-wise directed information transfer between EEG signals within δ, θ, α, β and γ-bands. The developed methodology is then used to study the properties of directed BNs in children with attention-deficit hyperactivity disorder (ADHD) and compare them with that of the healthy controls using both statistical and receiver operating characteristic (ROC) analyses. The results indicate that directed information transfer between scalp EEG electrodes in the ADHD subjects differs significantly compared to the healthy ones. The results of the statistical and ROC analyses of frequency-specific graph measures demonstrate their highly discriminative ability between the two groups. Specifically, the graph measures extracted from the estimated directed BNs in the β-band show the highest discrimination between the ADHD and control groups. These findings are in line with the fact that β-band reflects active concentration, motor activity, and anxious mental states. The reported results show that the developed methodology has the capacity to be used for investigating patterns of directed BNs in neuropsychiatric disorders.
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Affiliation(s)
- Ali Kareem Abbas
- Faculty of Electrical and Computer Engineering, Razi University, Kermanshah, Iran
| | - Ghasem Azemi
- Faculty of Electrical and Computer Engineering, Razi University, Kermanshah, Iran; Department of Cognitive Science, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, Australia.
| | - Sajad Amiri
- Faculty of Electrical and Computer Engineering, Razi University, Kermanshah, Iran
| | - Samin Ravanshadi
- Faculty of Electrical and Computer Engineering, Razi University, Kermanshah, Iran
| | - Amir Omidvarnia
- Institute of Bioengineering, Center for Neuroprosthetics, Center for Biomedical Imaging, EPFL, Lausanne, Switzerland; Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
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Idris Z, Zakaria Z, Halim SA, Razak SA, Ghani ARI, Abdullah JM. Disconnecting surgery at alveus and cornu ammonis of hippocampus, amygdala superficialis, and amygdala medial nuclei for epilepsy associated with attention deficit hyperactivity disorder. Childs Nerv Syst 2021; 37:1797-1802. [PMID: 32949261 DOI: 10.1007/s00381-020-04893-z] [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] [Received: 08/01/2020] [Accepted: 09/16/2020] [Indexed: 10/23/2022]
Abstract
The neural basis for epilepsy and attention deficit hyperactivity disorder (ADHD) is currently incompletely known. We reported a young girl with both epilepsy and ADHD, who had a calcified lesion in the right basolateral amygdalo-hippocampal region extending to the ventral striatum. The child underwent disconnecting surgery and biopsy of the lesion. Fascinatingly, the child's behavior changed immediately after the surgery from inattentive and impulsive to nearly normal behavior experiencing no more breakthrough seizures since after 3 years of surgery. The Schaltenbrand Wahren Brain Atlas revealed alveus, cornu ammonis, amygdala superficialis, and medium as the disconnected region in this surgery.
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Affiliation(s)
- Zamzuri Idris
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kubang Kerian, Kota Bharu, Kelantan, Malaysia. .,Brain And Behaviour Cluster, School of Medical Sciences, Universiti Sains Malaysia, Health Campus, 16150 Kubang Kerian, Kota Bharu, Kelantan, Malaysia. .,Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Health Campus, Jalan Raja Perempuan Zainab 2, 16150, Kota Bharu, Kelantan, Malaysia.
| | - Zaitun Zakaria
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kubang Kerian, Kota Bharu, Kelantan, Malaysia.,Brain And Behaviour Cluster, School of Medical Sciences, Universiti Sains Malaysia, Health Campus, 16150 Kubang Kerian, Kota Bharu, Kelantan, Malaysia.,Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Health Campus, Jalan Raja Perempuan Zainab 2, 16150, Kota Bharu, Kelantan, Malaysia
| | - Sanihah Abdul Halim
- Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Health Campus, Jalan Raja Perempuan Zainab 2, 16150, Kota Bharu, Kelantan, Malaysia.,Neurology Unit, Department of Internal Medicine, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kubang Kerian, Kota Bharu, Kelantan, Malaysia
| | - Salmi Abd Razak
- Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Health Campus, Jalan Raja Perempuan Zainab 2, 16150, Kota Bharu, Kelantan, Malaysia.,Department of Pediatrics, School of Medical Sciences, Universiti Sains Malaysia, 16150, Kubang Kerian, Kelantan, Malaysia
| | - Abdul Rahman Izaini Ghani
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kubang Kerian, Kota Bharu, Kelantan, Malaysia.,Brain And Behaviour Cluster, School of Medical Sciences, Universiti Sains Malaysia, Health Campus, 16150 Kubang Kerian, Kota Bharu, Kelantan, Malaysia.,Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Health Campus, Jalan Raja Perempuan Zainab 2, 16150, Kota Bharu, Kelantan, Malaysia
| | - Jafri Malin Abdullah
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kubang Kerian, Kota Bharu, Kelantan, Malaysia.,Brain And Behaviour Cluster, School of Medical Sciences, Universiti Sains Malaysia, Health Campus, 16150 Kubang Kerian, Kota Bharu, Kelantan, Malaysia.,Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Health Campus, Jalan Raja Perempuan Zainab 2, 16150, Kota Bharu, Kelantan, Malaysia
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Bleich-Cohen M, Gurevitch G, Carmi N, Medvedovsky M, Bregman N, Nevler N, Elman K, Ginou A, Zangen A, Ash EL. A functional magnetic resonance imaging investigation of prefrontal cortex deep transcranial magnetic stimulation efficacy in adults with attention deficit/hyperactive disorder: A double blind, randomized clinical trial. Neuroimage Clin 2021; 30:102670. [PMID: 34215144 PMCID: PMC8102620 DOI: 10.1016/j.nicl.2021.102670] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 02/19/2021] [Accepted: 04/08/2021] [Indexed: 02/09/2023]
Abstract
ADHD is one of the most prevalent neurocognitive disorders. Deep Transcranial Magnetic Stimulation (dTMS) is a non-invasive neuromodulation tool that holds promise in treatment of neurocognitive disorders. Hypoactivity of the prefrontal cortex (PFC) has been observed in ADHD. This study examined the clinical, cognitive, and neural effects of dTMS to the PFC in adults with ADHD by using functional magnetic resonance imaging (fMRI). High frequency repetitive dTMS was applied to either the right or left PFC in 62 adults with ADHD in a randomized, double blind, placebo controlled protocol with 3 study groups: 2 treatment arms (rPFC, or lPFC) and a Sham arm. The study included 15 dTMS/cognitive training treatment sessions. Clinical effects were assessed with the Conners Adult ADHD Rating Scale (CAARS) self-report and the Clinical Global Impression score (CGI) as primary outcome measures. Self-report/observer questionnaires and computerized cognitive testing were also performed to assess clinical and cognitive effects. Neural effects were assessed with fMRI using working-memory (WM) and resting-state paradigms. While the study did not show improvement in the primary endpoints, significant improvements were observed in the CAARS (self-report) inattention/memory sub-scale, as well as increased activations in the rDLPFC, right parietal-cortex and right insula/IFG during WM conditions after treatment in the right stimulation group. Increased rDLPFC activation was associated with larger symptom improvement in the right stimulation group. This study indicates that dTMS is effective in modulating attention related brain networks, and is a feasible technique that may improve attention symptoms in adults with ADHD.
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Affiliation(s)
- Maya Bleich-Cohen
- Sagol Brain Institute, Tel Aviv Sourasky Medical Center, Tel Aviv 6423906, Israel; Brainsway Ltd, Jerusalem 9777518, Israel.
| | - Guy Gurevitch
- Sagol Brain Institute, Tel Aviv Sourasky Medical Center, Tel Aviv 6423906, Israel; Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Noa Carmi
- Sagol Brain Institute, Tel Aviv Sourasky Medical Center, Tel Aviv 6423906, Israel
| | - Mordekhay Medvedovsky
- Department of Neurology, Agnes Ginges Center of Neurogenetics, Hadassah-Hebrew University Medical Center, Jerusalem 91120, Israel
| | - Noa Bregman
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel; Department of Neurology, Tel Aviv Sourasky Medical Center, Tel Aviv 6423906, Israel
| | - Naomi Nevler
- Department of Neurology, Tel Aviv Sourasky Medical Center, Tel Aviv 6423906, Israel
| | - Karin Elman
- Department of Neurology, Tel Aviv Sourasky Medical Center, Tel Aviv 6423906, Israel
| | - Amit Ginou
- Brainsway Ltd, Jerusalem 9777518, Israel
| | - Abraham Zangen
- Brain Stimulation and Behavior Lab, The Zlotowski Center for Neuroscience, Ben Gurion University, Beer Sheva 8410501, Israel
| | - Elissa L Ash
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel; Department of Neurology, Tel Aviv Sourasky Medical Center, Tel Aviv 6423906, Israel
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43
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Yoo JH, Kim JI, Kim BN, Jeong B. Exploring characteristic features of attention-deficit/hyperactivity disorder: findings from multi-modal MRI and candidate genetic data. Brain Imaging Behav 2021; 14:2132-2147. [PMID: 31321662 DOI: 10.1007/s11682-019-00164-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
The current study examined whether machine learning features best distinguishing attention-deficit/hyperactivity disorder (ADHD) from typically developing children (TDC) can explain clinical phenotypes using multi-modal neuroimaging and genetic data. Cortical morphology, diffusivity scalars, resting-state functional connectivity and polygenic risk score (PS) from norepinephrine, dopamine and glutamate genes were extracted from 47 ADHD and 47 matched TDC. Using random forests, classification accuracy was measured for each uni- and multi-modal model. The optimal model was used to explain symptom severity or task performance and its robustness was validated in the independent dataset including 18 ADHD and 18 TDC. The model consisting of cortical thickness and volume features achieved the best accuracy of 85.1%. Morphological changes across insula, sensory/motor, and inferior frontal cortex were also found as key predictors. Those explained 18.0% of ADHD rating scale, while dynamic regional homogeneity within default network explained 6.4% of the omission errors in continuous performance test. Ensemble of PS to optimal model showed minor effect on accuracy. Validation analysis achieved accuracy of 69.4%. Current findings suggest that structural deformities relevant to salience detection, sensory processing, and response inhibition may be robust classifiers and symptom predictors of ADHD. Altered local functional connectivity across default network predicted attentional lapse. However, further investigation is needed to clarify roles of genetic predisposition.
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Affiliation(s)
- Jae Hyun Yoo
- Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea
| | - Johanna Inhyang Kim
- Department of Psychiatry, Hanyang University Medical Center, 222-1 Wangsimni-ro, Seongdong-gu, Seoul, 04763, Republic of Korea
| | - Bung-Nyun Kim
- Division of Child and Adolescent Psychiatry, Department of Neuropsychiatry, Seoul National University Hospital College of Medicine, 101 Daehak-no, Chongno-gu, Seoul, 03080, Republic of Korea.
| | - Bumseok Jeong
- Laboratory of Computational Affective Neuroscience and Development, Graduate School of Medical Science and Engineering, Korea Advanced Institute for Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea. .,KI for Health Science and Technology, KAIST Institute, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea.
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Farré‐Colomés À, Gerhardt S, Luderer M, Sobanski E, Kiefer F, Vollstädt‐Klein S. Common and distinct neural connectivity in attention‐deficit/hyperactivity disorder and alcohol use disorder studied using resting‐state functional magnetic resonance imaging. Alcohol Clin Exp Res 2021; 45:948-960. [DOI: 10.1111/acer.14593] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 02/10/2021] [Accepted: 03/02/2021] [Indexed: 12/11/2022]
Affiliation(s)
- Àlvar Farré‐Colomés
- Department of Addictive Behavior and Addiction Medicine Central Institute of Mental Health Medical Faculty Mannheim University of Heidelberg Mannheim Germany
| | - Sarah Gerhardt
- Department of Addictive Behavior and Addiction Medicine Central Institute of Mental Health Medical Faculty Mannheim University of Heidelberg Mannheim Germany
| | - Mathias Luderer
- Department of Psychiatry Psychosomatic Medicine and Psychotherapy University Hospital Goethe University Frankfurt Germany
| | - Esther Sobanski
- Department of Psychiatry and Psychotherapy Central Institute of Mental Health Medical Faculty Mannheim University of Heidelberg Mannheim Germany
- Department of Child and Adolescent Psychiatry University Medical Center Mainz Mainz Germany
| | - Falk Kiefer
- Department of Addictive Behavior and Addiction Medicine Central Institute of Mental Health Medical Faculty Mannheim University of Heidelberg Mannheim Germany
- Mannheim Center for Translational Neurosciences (MCTN) Medical Faculty Mannheim University of Heidelberg Mannheim Germany
- Feuerlein Center on Translational Addiction Medicine University of Heidelberg Heidelberg Germany
| | - Sabine Vollstädt‐Klein
- Department of Addictive Behavior and Addiction Medicine Central Institute of Mental Health Medical Faculty Mannheim University of Heidelberg Mannheim Germany
- Mannheim Center for Translational Neurosciences (MCTN) Medical Faculty Mannheim University of Heidelberg Mannheim Germany
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Norr ME, Hect JL, Lenniger CJ, Van den Heuvel M, Thomason ME. An examination of maternal prenatal BMI and human fetal brain development. J Child Psychol Psychiatry 2021; 62:458-469. [PMID: 32779186 PMCID: PMC7875456 DOI: 10.1111/jcpp.13301] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 06/23/2020] [Accepted: 06/26/2020] [Indexed: 01/27/2023]
Abstract
BACKGROUND Prenatal development is a time when the brain is acutely vulnerable to insult and alteration by environmental factors (e.g., toxins, maternal health). One important risk factor is maternal obesity (Body Mass Index > 30). Recent research indicates that high maternal BMI during pregnancy is associated with increased risk for numerous physical health, cognitive, and mental health problems in offspring across the lifespan. It is possible that heightened maternal prenatal BMI influences the developing brain even before birth. METHODS The present study examines this possibility at the level of macrocircuitry in the human fetal brain. Using a data-driven strategy for parcellating the brain into subnetworks, we test whether MRI functional connectivity within or between fetal neural subnetworks varies with maternal prenatal BMI in 109 fetuses between the ages of 26 and 39weeks. RESULTS We discovered that strength of connectivity between two subnetworks, left anterior insula/inferior frontal gyrus (aIN/IFG) and bilateral prefrontal cortex (PFC), varied with maternal BMI. At the level of individual aIN/IFG-PFC connections, we observed both increased and decreased between-network connectivity with a tendency for increased within-hemisphere connectivity and reduced cross-hemisphere connectivity in higher BMI pregnancies. Maternal BMI was not associated with global differences in network topography based on network-based statistical analyses. CONCLUSIONS Overall effects were localized in regions that will later support behavioral regulation and integrative processes, regions commonly associated with obesity-related deficits. By establishing onset in neural differences prior to birth, this study supports a model in which maternal BMI-related risk is associated with fetal connectome-level brain organization with implications for offspring long-term cognitive development and mental health.
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Affiliation(s)
- Megan E. Norr
- Department of Psychology, University of California Berkeley, Berkeley, CA, USA
| | - Jasmine L. Hect
- Department of Psychology, Wayne State University, Detroit, MI, USA
| | - Carly J. Lenniger
- Department of Child and Adolescent Psychiatry, New York University Medical Center, New York, NY, USA
| | - Martijn Van den Heuvel
- Dutch Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands
| | - Moriah E. Thomason
- Department of Child and Adolescent Psychiatry, New York University Medical Center, New York, NY, USA
- Department of Population Health, New York Medical Center, New York University, New York, NY, USA
- Neuroscience Institute, New York Medical Center, New York University, New York, NY, USA
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46
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Tichenor SE, Johnson CA, Yaruss JS. A Preliminary Investigation of Attention-Deficit/Hyperactivity Disorder Characteristics in Adults Who Stutter. JOURNAL OF SPEECH, LANGUAGE, AND HEARING RESEARCH : JSLHR 2021; 64:839-853. [PMID: 33647218 DOI: 10.1044/2020_jslhr-20-00237] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Purpose Recent studies have shown that many children who stutter may have elevated characteristics of attention-deficit/hyperactivity disorder (ADHD). Although childhood ADHD commonly persists into adulthood, it is unclear how many adults who stutter experience aspects of ADHD (e.g., inattention or hyperactivity/impulsivity). This study sought to increase understanding of how ADHD characteristics might affect individuals who stutter by evaluating (a) whether elevated ADHD characteristics are common in adults who stutter, (b) whether elevated ADHD characteristics in adults who stutter were significantly associated with greater adverse impact related to stuttering, and (c) whether individual differences in Repetitive Negative Thinking (RNT) and Effortful Control influenced this relationship. Method Two hundred fifty-four adults who stutter completed the Adult ADHD Self-Report Scale, the Perseverative Thinking Questionnaire, the Adult Temperament Questionnaire short form, and the Overall Assessment of the Speaker's Experience of Stuttering. Data were analyzed via multiple linear regression to determine whether the number of inattention or hyperactivity/impulsivity characteristics was significantly associated with RNT, Effortful Control, or Adverse Impact related to stuttering. Results Almost one quarter of participants (23.2%; 60/254) self-reported experiencing six or more inattention characteristics, while fewer participants (8.3%; 21/254) self-reported experiencing six or more hyperactivity/impulsivity characteristics. Participants with lower Effortful Control and higher levels of both RNT and Adverse Impact were significantly more likely to self-report experiencing more inattention characteristics. Discussion Many adults who stutter may exhibit previously unaccounted for characteristics of ADHD, especially inattention. Results highlight the value of continued research on the intersectionality of stuttering, ADHD, and attention, and the importance of individualizing therapy to the needs of each unique person who stutters.
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Structural brain network topology underpinning ADHD and response to methylphenidate treatment. Transl Psychiatry 2021; 11:150. [PMID: 33654073 PMCID: PMC7925571 DOI: 10.1038/s41398-021-01278-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2020] [Revised: 01/21/2021] [Accepted: 02/12/2021] [Indexed: 02/03/2023] Open
Abstract
Behavioural disturbances in attention deficit hyperactivity disorder (ADHD) are thought to be due to dysfunction of spatially distributed, interconnected neural systems. While there is a fast-growing literature on functional dysconnectivity in ADHD, far less is known about the structural architecture underpinning these disturbances and how it may contribute to ADHD symptomology and treatment prognosis. We applied graph theoretical analyses on diffusion MRI tractography data to produce quantitative measures of global network organisation and local efficiency of network nodes. Support vector machines (SVMs) were used for comparison of multivariate graph measures of 37 children and adolescents with ADHD relative to 26 age and gender matched typically developing children (TDC). We also explored associations between graph measures and functionally-relevant outcomes such as symptom severity and prediction of methylphenidate (MPH) treatment response. We found that multivariate patterns of reduced local efficiency, predominantly in subcortical regions (SC), were able to distinguish between ADHD and TDC groups with 76% accuracy. For treatment prognosis, higher global efficiency, higher local efficiency of the right supramarginal gyrus and multivariate patterns of increased local efficiency across multiple networks at baseline also predicted greater symptom reduction after 6 weeks of MPH treatment. Our findings demonstrate that graph measures of structural topology provide valuable diagnostic and prognostic markers of ADHD, which may aid in mechanistic understanding of this complex disorder.
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48
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Wang LJ, Lin LC, Lee SY, Wu CC, Chou WJ, Hsu CF, Tseng HH, Lin WC. l-Cystine is associated with the dysconnectivity of the default-mode network and salience network in attention-deficit/hyperactivity disorder. Psychoneuroendocrinology 2021; 125:105105. [PMID: 33338922 DOI: 10.1016/j.psyneuen.2020.105105] [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] [Received: 08/19/2020] [Revised: 11/04/2020] [Accepted: 12/06/2020] [Indexed: 11/16/2022]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. Distributed dysconnectivity within both the default-mode network (DMN) and the salience network (SN) has been observed in ADHD. L-cystine may serve as a neuroprotective molecule and signaling pathway, as well as a biomarker of ADHD. The purpose of this study was to explore whether differential brain network connectivity is associated with peripheral L-cystine levels in ADHD patients. We recruited a total of 31 drug-naïve patients with ADHD (mean age: 10.4 years) and 29 healthy controls (mean age: 10.3 years) that underwent resting state functional magnetic resonance imaging scans. Functional connectomes were generated for each subject, and we examined the cross-sectional group difference in functional connectivity (FC) within and between DMN and SN. L-cystine plasma levels were determined using high-performance chemical isotope labeling (CIL)-based liquid chromatography-mass spectrometry (LC-MS). Compared to the control group, the ADHD group showed decreased FC of dorsal DMN (p = 0.031), as well as decreased FC of precuneus-post SN (p = 0.006) and ventral DMN-post SN (p = 0.001). The plasma L-cystine levels of the ADHD group were significantly higher than in the control group (p = 0.002). Furthermore, L-cystine levels were negatively correlated with FC of precuneus-post SN (r = -0.404, p = 0.045) and ventral DMN-post SN (r = -0.540, p = 0.007). The findings suggest that decreased synergies of DMN and SN may serve as neurobiomarkers for ADHD, while L-cystine may be involved in the pathophysiology of network dysconnectivity. Future studies on the molecular mechanism of the cystine-glutamate system in brain network connectivity are warranted.
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Affiliation(s)
- Liang-Jen Wang
- Department of Child and Adolescent Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Liang-Chun Lin
- Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Taiwan; Chang Gung University College of Medicine, Taiwan
| | - Sheng-Yu Lee
- Department of Psychiatry, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan; Department of Psychiatry, College of Medicine, Graduate Institute of Medicine, School of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Chih-Ching Wu
- Department of Medical Biotechnology and Laboratory Science, Chang Gung University, Taoyuan, Taiwan; Department of Otolaryngology-Head & Neck Surgery, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan; Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan; Research Center for Emerging Viral Infections, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Wen-Jiun Chou
- Department of Child and Adolescent Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Chia-Fen Hsu
- Division of Clinical Psychology, Graduate Institute of Behavioral Sciences, Chang Gung University, Taoyuan, Taiwan; Department of Child Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Huai-Hsuan Tseng
- Department of Psychiatry, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Wei-Che Lin
- Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Taiwan; Chang Gung University College of Medicine, Taiwan.
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Zink N, Lenartowicz A, Markett S. A new era for executive function research: On the transition from centralized to distributed executive functioning. Neurosci Biobehav Rev 2021; 124:235-244. [PMID: 33582233 DOI: 10.1016/j.neubiorev.2021.02.011] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 02/04/2021] [Indexed: 02/07/2023]
Abstract
"Executive functions" (EFs) is an umbrella term for higher cognitive control functions such as working memory, inhibition, and cognitive flexibility. One of the most challenging problems in this field of research has been to explain how the wide range of cognitive processes subsumed as EFs are controlled without an all-powerful but ill-defined central executive in the brain. Efforts to localize control mechanisms in circumscribed brain regions have not led to a breakthrough in understanding how the brain controls and regulates itself. We propose to re-conceptualize EFs as emergent consequences of highly distributed brain processes that communicate with a pool of highly connected hub regions, thus precluding the need for a central executive. We further discuss how graph-theory driven analysis of brain networks offers a unique lens on this problem by providing a reference frame to study brain connectivity in EFs in a holistic way and helps to refine our understanding of the mechanisms underlying EFs by providing new, testable hypotheses and resolves empirical and theoretical inconsistencies in the EF literature.
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Affiliation(s)
- Nicolas Zink
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, United States.
| | - Agatha Lenartowicz
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, United States
| | - Sebastian Markett
- Department of Psychology, Humboldt University Berlin, Berlin, Germany
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50
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Lin H, Lin Q, Li H, Wang M, Chen H, Liang Y, Bu X, Wang W, Yi Y, Zhao Y, Zhang X, Xie Y, Du S, Yang C, Huang X. Functional Connectivity of Attention-Related Networks in Drug-Naïve Children With ADHD. J Atten Disord 2021; 25:377-388. [PMID: 30259777 DOI: 10.1177/1087054718802017] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Objective: This study aimed to explore alterations of seed-based functional connectivity (FC) in dorsal attention network (DAN), ventral attention network (VAN), and default mode network (DMN) in ADHD children. Method: A voxel-based comparison of FC maps between 46 drug-naïve children with ADHD and 31 healthy controls (HCs) and correlation analysis between connectivity features and behavior were performed. Results: Compared with the HCs, children with ADHD were characterized by hyperconnectivity between DAN and regions of DMN and by hyperconnectivity between DMN and a set of regions involved in somatosensory, visual, and auditory cortices. No significant group different FC was found between VAN and the whole brain. Higher FC between DMN and somatosensory, visual, and auditory cortex was associated with better performance in attention and executive function. Conclusion: The dysregulation of networks in children with ADHD not only involves the DAN and DMN but also the somatosensory, motor, visual, and auditory networks.
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Affiliation(s)
- Haixi Lin
- The First Affiliated Hospital of Wenzhou Medical University, China
| | - Qingxia Lin
- The First Affiliated Hospital of Wenzhou Medical University, China
| | - Hailong Li
- West China Hospital of Sichuan University, Chengdu, China
| | - Meihao Wang
- The First Affiliated Hospital of Wenzhou Medical University, China
| | - Hong Chen
- The First Affiliated Hospital of Wenzhou Medical University, China
| | - Yan Liang
- The First Affiliated Hospital of Wenzhou Medical University, China
| | - Xuan Bu
- West China Hospital of Sichuan University, Chengdu, China
| | - Weiqian Wang
- The First Affiliated Hospital of Wenzhou Medical University, China
| | - Yanhong Yi
- The First Affiliated Hospital of Wenzhou Medical University, China
| | - Yongzhong Zhao
- The First Affiliated Hospital of Wenzhou Medical University, China
| | - Xiaoyan Zhang
- The First Affiliated Hospital of Wenzhou Medical University, China
| | - Yupeng Xie
- The First Affiliated Hospital of Wenzhou Medical University, China
| | - Songmei Du
- The First Affiliated Hospital of Wenzhou Medical University, China
| | - Chuang Yang
- The First Affiliated Hospital of Wenzhou Medical University, China
| | - Xiaoqi Huang
- West China Hospital of Sichuan University, Chengdu, China
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