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Kujala J, Matveinen S, van Bijnen S, Parviainen T. The relationship between structural properties of frontal cortical regions and response inhibition in 6-14-year-old children. Brain Cogn 2024; 181:106220. [PMID: 39241458 DOI: 10.1016/j.bandc.2024.106220] [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: 05/13/2024] [Revised: 08/27/2024] [Accepted: 09/01/2024] [Indexed: 09/09/2024]
Abstract
Development of attentional skills and inhibitory control rely on maturational changes in the brain across childhood and youth. However, both brain anatomy and different components of attention and inhibition show notable individual variation. Research on ADHD and inhibitory training and control have shown that variations in the thickness and surface area of particularly inferior cortical structures are associated with attentional control. However, the intricacies of how the development of inhibitory control is associated with the anatomical variations beyond the general age- and gender-dependent differences have not been resolved. Here, we sought to address these questions by quantifying the cortical thickness and surface area in frontal cortical regions and inhibitory control using the stop signal task performance in 6-14-year-old children. Our results showed that the thickness of the left medial orbitofrontal cortex and the surface area of the left caudal anterior cingulate were associated with the inhibitory performance, beyond the variance that could be explained by the subjects' age and gender. The results highlight the importance of factoring in anatomical variations when following attentional development and the importance of evaluating multiple anatomical measures when aiming to link the properties of cortical structures with variations in cognitive performance.
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Affiliation(s)
- Jan Kujala
- Department of Psychology, University of Jyväskylä, Finland.
| | | | - Sam van Bijnen
- Department of Psychology, University of Jyväskylä, Finland; Centre for Interdisciplinary Brain Research, Department of Psychology, University of Jyväskylä, Finland
| | - Tiina Parviainen
- Department of Psychology, University of Jyväskylä, Finland; Centre for Interdisciplinary Brain Research, Department of Psychology, University of Jyväskylä, Finland
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2
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Yasunaga M, Miyaguchi H, Ishizuki C, Kita Y, Nakai A. Association between Motor Skills, Occupational Performance, and Mental Health in Japanese Children with Neurodevelopmental Disorders: A Cross-Sectional Correlational Study. CHILDREN (BASEL, SWITZERLAND) 2024; 11:899. [PMID: 39201834 PMCID: PMC11353002 DOI: 10.3390/children11080899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/20/2024] [Revised: 07/21/2024] [Accepted: 07/24/2024] [Indexed: 09/03/2024]
Abstract
BACKGROUND Motor skills have been linked to executive functions (EFs) in children with developmental coordination disorder (DCD). However, the traits of other neurodevelopmental disorders (NDDs), such as attention-deficit/hyperactivity disorder and autism spectrum disorder, remain overlooked. Therefore, this study explored the association between motor skills, occupational performance, and mental health in older kindergarten children with DCD and other NDDs. Overall, 95 participants aged 5-6 years were included in this study and divided into four groups: DCD traits (DCD-t), DCD-t + NDD traits (DCD-t + NDD-t), NDD-t-only, and typically developing children. Motor skills, EFs, and mental health were assessed using the DCD Questionnaire (DCDQ-J) and Movement Assessment Battery for Children-Second Edition, School Assessment of Motor and Process Skills (S-AMPS), and the Strengths and Difficulties Questionnaire (SDQ), respectively. The DCD-t + NDD-t group exhibited a strong correlation between the S-AMPS motor skill score and the DCDQ-J fine motor skill score (r = 0.88, p < 0.001) and between the total DCDQ-J score and the SDQ Total Difficulties Score (r = -0.94, p < 0.001). The findings indicate that children with DCD-t and NDD-t are more likely to experience EF and mental health problems than those with DCD-t only.
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Affiliation(s)
- Masanori Yasunaga
- Health and Counseling Center, Campus Life Health Support and Consultation Center, Osaka University, Toyonaka 560-0043, Japan;
| | - Hideki Miyaguchi
- Department of Human Behavior Science of Occupational Therapy, Graduate School of Biomedical & Health Sciences, Hiroshima University, Hiroshima 734-8551, Japan;
- University of Kochi He alth Scienses, Kochi 781-5103, Japan
| | - Chinami Ishizuki
- Department of Human Behavior Science of Occupational Therapy, Graduate School of Biomedical & Health Sciences, Hiroshima University, Hiroshima 734-8551, Japan;
| | - Yosuke Kita
- Department of Psychology, Faculty of Letters, Keio University, Tokyo 108-8345, Japan;
- Cognitive Brain Research Unit (CBRU), Faculty of Medicine, University of Helsinki, 00014 Helsinki, Finland
| | - Akio Nakai
- Research Institute for Education & Graduate School of Clinical Education, Mukogawa Women’s University, Nishinomiya 663-8558, Japan
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3
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Simon C, Bolton DAE, Meaney JF, Kenny RA, Simon VA, De Looze C, Knight S, Ruddy KL. White matter fibre density in the brain's inhibitory control network is associated with falling in low activity older adults. Eur J Neurosci 2024; 59:3184-3202. [PMID: 38638001 DOI: 10.1111/ejn.16327] [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: 11/30/2023] [Revised: 02/20/2024] [Accepted: 03/09/2024] [Indexed: 04/20/2024]
Abstract
Recent research has indicated that the relationship between age-related cognitive decline and falling may be mediated by the individual's capacity to quickly cancel or inhibit a motor response. This longitudinal investigation demonstrates that higher white matter fibre density in the motor inhibition network paired with low physical activity was associated with falling in elderly participants. We measured the density of white matter fibre tracts connecting key nodes in the inhibitory control network in a large sample (n = 414) of older adults. We modelled their self-reported frequency of falling over a 4-year period with white matter fibre density in pathways corresponding to the direct and hyperdirect cortical-subcortical loops implicated in the inhibitory control network. Only connectivity between right inferior frontal gyrus and right subthalamic nucleus was associated with falling as measured cross-sectionally. The connectivity was not, however, predictive of future falling when measured 2 and 4 years later. Higher white matter fibre density was associated with falling, but only in combination with low levels of physical activity. No such relationship existed for selected control brain regions that are not implicated in the inhibitory control network. Albeit statistically robust, the direction of this effect was counterintuitive (more dense connectivity associated with falling) and warrants further longitudinal investigation into whether white matter fibre density changes over time in a manner correlated with falling, and mediated by physical activity.
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Affiliation(s)
- Colin Simon
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - David A E Bolton
- Department of Kinesiology and Health Science, Utah State University, Logan, Utah, USA
| | - James F Meaney
- Centre for Advanced Medical Imaging (CAMI), St James's Hospital, Dublin, Ireland
| | - Rose Anne Kenny
- The Irish Longitudinal Study on Ageing (TILDA), Trinity College Dublin, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
- Mercer's Institute for Successful Ageing (MISA), St James's Hospital, Dublin, Ireland
| | - Vivienne A Simon
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Céline De Looze
- The Irish Longitudinal Study on Ageing (TILDA), Trinity College Dublin, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Silvin Knight
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
- Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
| | - Kathy L Ruddy
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin, Ireland
- School of Psychology, Queen's University Belfast, Belfast, UK
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4
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Karavallil Achuthan S, Stavrinos D, Argueta P, Vanderburgh C, Holm HB, Kana RK. Thalamic functional connectivity and sensorimotor processing in neurodevelopmental disorders. Front Neurosci 2023; 17:1279909. [PMID: 38161799 PMCID: PMC10755010 DOI: 10.3389/fnins.2023.1279909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 11/08/2023] [Indexed: 01/03/2024] Open
Abstract
One of the earliest neurobiological findings in autism has been the differences in the thalamocortical pathway connectivity, suggesting the vital role thalamus plays in human experience. The present functional MRI study investigated resting-state functional connectivity of the thalamus in 49 (autistic, ADHD, and neurotypical) young adults. All participants underwent structural MRI and eyes-open resting state functional MRI scans. After preprocessing the imaging data using Conn's connectivity toolbox, a seed-based functional connectivity analysis was conducted using bilateral thalamus as primary seeds. Autistic participants showed stronger thalamic connectivity, relative to ADHD and neurotypical participants, between the right thalamus and right precentral gyrus, right pars opercularis-BA44, right postcentral gyrus, and the right superior parietal lobule (RSPL). Autistic participants also showed significantly increased connectivity between the left thalamus and the right precentral gyrus. Furthermore, regression analyses revealed a significant relationship between autistic traits and left thalamic-precentral connectivity (R2 = 0.1113), as well as between autistic traits and right postcentral gyrus and RSPL connectivity (R2 = 0.1204) in autistic participants compared to ADHD. These findings provide significant insights into the role of thalamus in coordinating neural information processing and its alterations in neurodevelopmental disorders.
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Affiliation(s)
- Smitha Karavallil Achuthan
- Department of Psychology and the Center for Innovative Research in Autism, The University of Alabama, Tuscaloosa, AL, United States
| | - Despina Stavrinos
- Department of Psychology and the Institute of Social Science Research, The University of Alabama, Tuscaloosa, AL, United States
| | - Paula Argueta
- Department of Psychology and the Center for Innovative Research in Autism, The University of Alabama, Tuscaloosa, AL, United States
| | - Caroline Vanderburgh
- Department of Psychology and the Center for Innovative Research in Autism, The University of Alabama, Tuscaloosa, AL, United States
| | - Haley B. Holm
- Children’s Hospital of Atlanta, Atlanta, GA, United States
| | - Rajesh K. Kana
- Department of Psychology and the Center for Innovative Research in Autism, The University of Alabama, Tuscaloosa, AL, United States
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5
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Schachar RJ. Fifty years of executive control research in attention-deficit/hyperactivity disorder:What we have learned and still need to know. Neurosci Biobehav Rev 2023; 155:105461. [PMID: 37949153 DOI: 10.1016/j.neubiorev.2023.105461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 11/02/2023] [Accepted: 11/03/2023] [Indexed: 11/12/2023]
Abstract
For 50 years, attention-deficit/hyperactivity disorder (ADHD) has been considered a disorder of executive control (EC), the higher-order, cognitive skills that support self-regulation, goal attainment and what we generally call "attention." This review surveys our current understanding of the nature of EC as it pertains to ADHD and considers the evidence in support of eight hypotheses that can be derived from the EC theory of ADHD. This paper provides a resource for practitioners to aid in clinical decision-making. To support theory building, I draw a parallel between the EC theory of ADHD and the common gene-common variant model of complex traits such as ADHD. The conclusion offers strategies for advancing collaborative research.
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Affiliation(s)
- Russell J Schachar
- Department of Psychiatry, The Hospital for Sick Children and University of Toronto, Research Institute, The Hospital for Sick Children, 555 University Avenue, Toronto, Ontario M5G1X8, Canada.
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6
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Karavallil Achuthan S, Stavrinos D, Holm HB, Anteraper SA, Kana RK. Alterations of Functional Connectivity in Autism and Attention-Deficit/Hyperactivity Disorder Revealed by Multi-Voxel Pattern Analysis. Brain Connect 2023; 13:528-540. [PMID: 37522594 DOI: 10.1089/brain.2023.0006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/01/2023] Open
Abstract
Background: Autism and attention-deficit/hyperactivity disorder (ADHD) are comorbid neurodevelopmental disorders that share common and distinct neurobiological mechanisms, with disrupted brain connectivity patterns being a hallmark feature of both conditions. It is challenging to gain a mechanistic understanding of the underlying disorder, because brain connectivity changes in autism and ADHD are heterogeneous. Objectives: The present resting state functional MRI (rs-fMRI) study focuses on investigating the shared and distinct resting state-fMRI connectivity (rsFC) patterns in autistic and ADHD adults using multi-voxel pattern analysis (MVPA). By identifying spatial patterns of fMRI activity across a given time course, MVPA is an innovative and powerful method for generating seed regions of interest (ROIs) without a priori hypotheses. Methods: We performed a data-driven, whole-brain, connectome-wide MVPA on rs-fMRI data collected from 15 autistic, 19 ADHD, and 15 neurotypical (NT) young adults. Results: MVPA identified cerebellar vermis 9, precuneus, and the right cerebellum VI for autistic versus NT, right inferior frontal gyrus and vermis 9 for ADHD versus NT, and right dorsolateral prefrontal cortex for autistic versus ADHD as significant clusters. Post hoc seed-to-voxel analyses using these clusters as seed ROIs were performed for further characterization of group differences. The cerebellum VI, vermis, and precuneus in autistic adults, and the vermis and frontal regions in ADHD showed different connectivity patterns in comparison with NT. Conclusions: The study characterizes the rsFC profile of cerebellum with key cortical areas in autism and ADHD, and it emphasizes the importance of studying the role of the functional connectivity of the cerebellum in neurodevelopmental disorders.
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Affiliation(s)
- Smitha Karavallil Achuthan
- Department of Psychology & The Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, Alabama, USA
| | - Despina Stavrinos
- Department of Psychology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Haley B Holm
- Children's Hospital of Atlanta, Atlanta, Georgia, USA
| | - Sheeba Arnold Anteraper
- Stephens Family Clinical Research Institute, Carle Illinois Advanced Imaging Center, Urbana, Illinois, USA
| | - Rajesh K Kana
- Department of Psychology & The Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, Alabama, USA
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Aksiotis V, Myachykov A, Tumyalis A. Stop-signal delay reflects response selection duration in stop-signal task. Atten Percept Psychophys 2023; 85:1976-1989. [PMID: 37415061 DOI: 10.3758/s13414-023-02752-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/13/2023] [Indexed: 07/08/2023]
Abstract
The stop-signal task (SST) is widely used for studying the speed of the latent process of response inhibition. The SST patterns are typically explained by a horse-race model (HRM) with supposed Go and Stop processes. However, HRM does not agree with the sequential-stage model of response control. As a result, the exact relationship between the response selection, the response execution stages, and the Stop process remains unclear. We propose that response selection occurs within the stop-signal delay (SSD) period, and that the competition between the Go and Stop processes occurs within the response execution period. To confirm this, we conducted two experiments. In Experiment 1, participants carried out a modified SST task with an additional stimulus category - Cued-Go. In the Cued-Go trials, cues were followed by imperative Go signals. The Cue-Go period duration was dynamically adjusted by an adaptive algorithm based on the response times reflecting the individual response selection duration. In Experiment 2, Cued-Go stimuli were followed by Stop Signals in half of the trials and response inhibition efficiency was calculated. The results of Experiment 1 indicate that SSD reflects the duration of the response selection process. The results of Experiment 2 show that this process has an independent and small effect on the effectiveness of controlled inhibition of the target response. Based on our findings, we propose a two-stage model of response inhibition in SST, with the first stage including response selection process and the second stage response inhibition following the SS presentation.
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Affiliation(s)
- Vladislav Aksiotis
- Centre for Bioelectric Interfaces, Institute for Cognitive Neuroscience, Higher School of Economics, Krivokolenniy Pereulok 3, Moscow, 101000, Russian Federation
| | - Andriy Myachykov
- Department of Psychology, Northumbria University, Newcastle-upon-Tyne, NE1 8ST, UK
- Centre for Cognition and Decision making, Institute for Cognitive Neuroscience, HSE University, Krivokolenniy Pereulok 3, Moscow, Russian Federation, 101000
| | - Alexey Tumyalis
- Centre for Bioelectric Interfaces, Institute for Cognitive Neuroscience, Higher School of Economics, Krivokolenniy Pereulok 3, Moscow, 101000, Russian Federation.
- Laboratory of Medical Neurointerfaces and Artificial Intellect, Federal Center of Brain Research and Neurotechnologies of the Federal Medical Biological Agency, Ostrovityanova st. 1, bld. 10, Moscow, Russian Federation, 117513.
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8
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Lukito S, O'Daly OG, Lythgoe DJ, Hodsoll J, Maltezos S, Pitts M, Simonoff E, Rubia K. Reduced inferior fronto-insular-thalamic activation during failed inhibition in young adults with combined ASD and ADHD compared to typically developing and pure disorder groups. Transl Psychiatry 2023; 13:133. [PMID: 37087490 PMCID: PMC10122665 DOI: 10.1038/s41398-023-02431-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 04/05/2023] [Accepted: 04/12/2023] [Indexed: 04/24/2023] Open
Abstract
Autism spectrum disorder (ASD) often co-occurs with attention-deficit/hyperactivity disorder (ADHD) and people with these conditions have frontostriatal functional atypicality during motor inhibition. We compared the neural and neurocognitive correlates of motor inhibition and performance monitoring in young adult males with "pure" and combined presentations with age-and sex-matched typically developing controls, to explore shared or disorder-specific atypicality. Males aged 20-27 years with typical development (TD; n = 22), ASD (n = 21), combined diagnoses ASD + ADHD (n = 23), and ADHD (n = 25) were compared using a modified tracking fMRI stop-signal task that measures motor inhibition and performance monitoring while controlling for selective attention. In addition, they performed a behavioural go/no-go task outside the scanner. While groups did not differ behaviourally during successful stop trials, the ASD + ADHD group relative to other groups had underactivation in typical performance monitoring regions of bilateral anterior insula/inferior frontal gyrus, right posterior thalamus, and right middle temporal gyrus/hippocampus during failed inhibition, which was associated with increased stop-signal reaction time. In the behavioural go/no-go task, both ADHD groups, with and without ASD, had significantly lower motor inhibition performance compared to TD controls. In conclusion, only young adult males with ASD + ADHD had neurofunctional atypicality in brain regions associated with performance monitoring, while inhibition difficulties on go/no-go task performance was shared with ADHD. The suggests that young people with ASD + ADHD are most severely impaired during motor inhibition tasks compared to ASD and ADHD but do not reflect a combination of the difficulties associated with the pure disorders.
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Affiliation(s)
- Steve Lukito
- Department of Child and Adolescent Psychiatry, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK.
| | - Owen G O'Daly
- Department of Neuroimaging, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
| | - David J Lythgoe
- Department of Neuroimaging, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
| | - John Hodsoll
- Department of Biostatistics and Health Informatics, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
| | - Stefanos Maltezos
- The Adult Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism National Service, Behavioural and Developmental Psychiatry Clinical Academic Group, South London and Maudsley Foundation NHS Trust, London, UK
| | - Mark Pitts
- The Adult Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism National Service, Behavioural and Developmental Psychiatry Clinical Academic Group, South London and Maudsley Foundation NHS Trust, London, UK
| | - Emily Simonoff
- Department of Child and Adolescent Psychiatry, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
| | - Katya Rubia
- Department of Child and Adolescent Psychiatry, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
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Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder: Shared or Unique Neurocognitive Profiles? Res Child Adolesc Psychopathol 2023; 51:17-31. [PMID: 36006496 PMCID: PMC9763138 DOI: 10.1007/s10802-022-00958-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/13/2022] [Indexed: 10/15/2022]
Abstract
Attention-deficit/hyperactivity (ADHD) and autism spectrum (ASD) disorders are commonly co-occurring conditions characterized by neurocognitive impairments. Few studies have directly compared neurocognitive profiles in ADHD and ASD and fewer still have controlled for comorbidity of ADHD and ASD. All direct comparisons have been in clinic samples, leaving the question of generalizability of results unaddressed. We compared neurocognitive performance in clinically ascertained ASD (n = 261) and ADHD (n = 423) cases and controls (n = 162), 6.0-17.9 years of age. We also compared ASD (n = 190) and ADHD (n = 926) cases ascertained in the community with controls (n = 14,842) of similar age. Using the stop-signal task (SST), we measured response inhibition (stop-signal reaction time-SSRT), sustained attention (defined as reaction time variability-RTV), and reaction time (RT). We controlled for comorbidity using ADHD and ASD trait scores and categorically-defined ADHD. Compared with controls, both clinic ADHD and ASD had significantly longer SSRT and RTV than controls and did not differ from each other. ADHD traits accounted for neurocognitive impairment in ASD, but not vice versa. There were no group differences for RT. Similar patterns of neurocognitive impairment were observed in the community sample. In the largest direct comparison of ADHD and ASD to date, we found impaired response inhibition and sustained attention in both disorders. However, neurocognitive impairment in ASD was almost completely accounted for by comorbid ADHD. Results generalized in the community sample indicating that referral bias alone did not drive results. Response inhibition and sustained attention likely play a role in ADHD and ASD.
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10
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He W, Liu W, Mao M, Cui X, Yan T, Xiang J, Wang B, Li D. Reduced Modular Segregation of White Matter Brain Networks in Attention Deficit Hyperactivity Disorder. J Atten Disord 2022; 26:1591-1604. [PMID: 35373644 DOI: 10.1177/10870547221085505] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
OBJECTIVE Despite studies reporting alterations in the brain networks of patients with ADHD, alterations in the modularity of white matter (WM) networks are still unclear. METHOD Based on the results of module division by generalized Louvain algorithm, the modularity of ADHD was evaluated. The correlation between the modular changes of ADHD and its clinical characteristics was analyzed. RESULTS The participation coefficient and the connectivity between modules of ADHD increased, and the modularity coefficient decreased. Provincial hubs of ADHD did not change, and the number of connector hubs increased. All results showed that the modular segregation of WM networks of ADHD decreased. Modules with reduced modular segregation are mainly responsible for language and motor functions. Moreover, modularity showed evident correlation with the symptoms of ADHD. CONCLUSION The modularity changes in WM network provided a novel insight into the understanding of brain cognitive alterations in ADHD.
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Affiliation(s)
- Wenbo He
- Taiyuan University of Technology, Shanxi, China
| | - Weichen Liu
- Taiyuan University of Technology, Shanxi, China
| | - Min Mao
- Taiyuan University of Technology, Shanxi, China
| | | | - Ting Yan
- Shanxi Medical University, Taiyuan, China
| | - Jie Xiang
- Taiyuan University of Technology, Shanxi, China
| | - Bin Wang
- Taiyuan University of Technology, Shanxi, China
| | - Dandan Li
- Taiyuan University of Technology, Shanxi, China
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11
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Doi H, Kanai C, Ohta H. Transdiagnostic and sex differences in cognitive profiles of autism spectrum disorder and attention-deficit/hyperactivity disorder. Autism Res 2022; 15:1130-1141. [PMID: 35347878 DOI: 10.1002/aur.2712] [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: 06/15/2021] [Revised: 02/28/2022] [Accepted: 03/15/2022] [Indexed: 11/09/2022]
Abstract
An increasing number of studies have shown that autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) share symptoms and aetiologies. However, transdiagnostic comparisons between ASD and ADHD is complicated due to the sex differences within each condition. To clarify the similarities and differences in the cognitive functioning between ASD and ADHD, while considering potential sex differences, this study compared cognitive profiles assessed by the WAIS-III between the four groups created by orthogonally combining diagnosis and sex based on the data from 277 ASD males, 86 ASD females, 99 ADHD males and 64 ADHD females. The analysis revealed three major findings. First, performance IQ and perceptual organization index were higher in ADHD males than in ASD males and ADHD females. Second, Gaussian mixture model fitting revealed two clusters underlying the distribution of subindex scores. The percentage of being classified into the cluster that scored lower in all the subindices was higher in females than in males irrespective of diagnosis. Third, feature importance for classification of ASD and ADHD yielded by random forest classifier, a supervised machine learning algorithm, revealed that autism quotient was most informative feature in classifying ASD and ADHD in males, while the discrepancy between verbal and performance intelligence quotient was in females, indicating that the set of behavioral features contributing to classification differs between males and females. Thus, these findings indicate that sex as well as diagnosis is critical in determining the cognitive profiles of people with ASD and ADHD. LAY SUMMARY: The present study compared profiles of cognitive functions measured by Wechsler Adult Intelligence Scale between males and females with ASD and ADHD. The analyses revealed clear sex differences in cognitive functions in both ASD and ADHD and that the set of cognitive functions useful in classifying ASD and ADHD differed between males and females. Thus, biological sex seems to be a critical factor in determining the cognitive profiles of people with ASD and ADHD.
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Affiliation(s)
- Hirokazu Doi
- School of Science and Engineering, Kokushikan University, Tokyo, Japan
| | - Chieko Kanai
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan.,Faculty of Humanities, Wayo Women's University, Ichikawa, Japan
| | - Haruhisa Ohta
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
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12
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Yu M, Gao X, Niu X, Zhang M, Yang Z, Han S, Cheng J, Zhang Y. Meta-analysis of structural and functional alterations of brain in patients with attention-deficit/hyperactivity disorder. Front Psychiatry 2022; 13:1070142. [PMID: 36683981 PMCID: PMC9853532 DOI: 10.3389/fpsyt.2022.1070142] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 12/05/2022] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND A large and growing body of neuroimaging research has concentrated on patients with attention-deficit/hyperactivity disorder (ADHD), but with inconsistent conclusions. This article was intended to investigate the common and certain neural alterations in the structure and function of the brain in patients with ADHD and further explore the differences in brain alterations between adults and children with ADHD. METHODS We conducted an extensive literature search of whole-brain voxel-based morphometry (VBM) and functional magnetic resonance imaging (fMRI) studies associated with ADHD. Two separate meta-analyses with the seed-based d mapping software package for functional neural activation and gray matter volume (GMV) were carried out, followed by a joint analysis and a subgroup analysis. RESULTS This analysis included 29 VBM studies and 36 fMRI studies. Structurally, VBM analysis showed that the largest GMV diminutions in patients with ADHD were in several frontal-parietal brain regions, the limbic system, and the corpus callosum. Functionally, fMRI analysis discovered significant hypoactivation in several frontal-temporal brain regions, the right postcentral gyrus, the left insula, and the corpus callosum. CONCLUSION This study showed that abnormal alterations in the structure and function of the left superior frontal gyrus and the corpus callosum may be the key brain regions involved in the pathogenesis of ADHD in patients and may be employed as an imaging metric for patients with ADHD pending future research. In addition, this meta-analysis discovered neuroanatomical or functional abnormalities in other brain regions in patients with ADHD as well as findings that can be utilized to guide future research.
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Affiliation(s)
- Miaomiao Yu
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Xinyu Gao
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Xiaoyu Niu
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Mengzhe Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Zhengui Yang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
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13
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Maron DN, Bowe SJ, Spencer-Smith M, Mellahn OJ, Perrykkad K, Bellgrove MA, Johnson BP. Oculomotor deficits in attention deficit hyperactivity disorder (ADHD): A systematic review and comprehensive meta-analysis. Neurosci Biobehav Rev 2021; 131:1198-1213. [PMID: 34655657 DOI: 10.1016/j.neubiorev.2021.10.012] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 10/04/2021] [Accepted: 10/10/2021] [Indexed: 02/01/2023]
Abstract
Atypical motor coordination and cognitive processes, such as response inhibition and working memory, have been extensively researched in individuals with attention deficit hyperactivity disorder (ADHD). Oculomotor neural circuits overlap extensively with regions involved in motor planning and cognition, therefore studies of oculomotor function may offer unique insights into motor and cognitive control in ADHD. We performed a series of pairwise meta-analyses based on data from 26 oculomotor studies in ADHD to examine whether there were differences in performance on visually-guided saccade, gap, antisaccade, memory-guided, pursuit eye movements and fixation tasks. These analyses revealed oculomotor disturbances in ADHD, particularly for difficulties relating to saccade inhibition, memorizing visual target locations and initiating antisaccades. There was no evidence for pursuit eye movement disturbances or saccade dysmetria. Investigating oculomotor abnormalities in ADHD may provide insight into top-down cognitive control processes and motor control, and may serve as a promising biomarker in ADHD research and clinical practice.
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Affiliation(s)
- Dalia N Maron
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, 18 Innovation Walk, Monash University, VIC, 3800, Australia
| | - Steven J Bowe
- Deakin Biostatistics Unit, Faculty of Health, Deakin University, Geelong, VIC, 3220, Australia
| | - Megan Spencer-Smith
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, 18 Innovation Walk, Monash University, VIC, 3800, Australia
| | - Olivia J Mellahn
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, 18 Innovation Walk, Monash University, VIC, 3800, Australia
| | - Kelsey Perrykkad
- Cognition and Philosophy Lab, Philosophy Department, School of Philosophical, Historical and International Studies, Monash University, VIC, 3800, Australia
| | - Mark A Bellgrove
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, 18 Innovation Walk, Monash University, VIC, 3800, Australia
| | - Beth P Johnson
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, 18 Innovation Walk, Monash University, VIC, 3800, Australia.
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14
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Dickstein DP, Barthelemy CM, Jenkins GA, DeYoung LLA, Gilbert AC, Radoeva P, Kim KL, MacPherson HA. This Is Your Brain on Irritability: A Clinician's Guide to Understanding How We Know What We Know Now, and What We Need to Know in the Future, About Irritability in Children and Adolescents. Child Adolesc Psychiatr Clin N Am 2021; 30:649-666. [PMID: 34053692 DOI: 10.1016/j.chc.2021.04.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Irritability is a common reason why children and adolescents are brought for psychiatric care. Although research is advancing what is known about the underlying brain and behavior mechanisms of irritability, clinicians often are shut out of that research. This article explains some of these research methods, providing brief summaries of what is known about brain/behavior mechanisms in disorders involving irritability, including bipolar disorder, disruptive mood dysregulation disorder, attention-deficit/hyperactivity disorder, and autism spectrum disorder. Greater access to these methods may help clinicians now and in the future, with such mechanisms translated into improved care, as occurs in the treatment of childhood leukemia.
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Affiliation(s)
- Daniel P Dickstein
- PediMIND Program, Mclean Hospital, 115 Mill Street, Belmont, MA, USA; Simches Center of Excellence in Child and Adolescent Psychiatry, McLean Hospital, Harvard Medical School.
| | - Christine M Barthelemy
- PediMIND Program, Mclean Hospital, 115 Mill Street, Belmont, MA, USA; Simches Center of Excellence in Child and Adolescent Psychiatry, McLean Hospital, Harvard Medical School
| | - Gracie A Jenkins
- PediMIND Program, Mclean Hospital, 115 Mill Street, Belmont, MA, USA; Simches Center of Excellence in Child and Adolescent Psychiatry, McLean Hospital, Harvard Medical School
| | - Lena L A DeYoung
- PediMIND Program, Mclean Hospital, 115 Mill Street, Belmont, MA, USA; Simches Center of Excellence in Child and Adolescent Psychiatry, McLean Hospital, Harvard Medical School
| | - Anna C Gilbert
- Division of Child Psychiatry, Brown University (Prior PediMIND Program Members)
| | - Petya Radoeva
- Division of Child Psychiatry, Brown University (Prior PediMIND Program Members)
| | - Kerri L Kim
- Division of Child Psychiatry, Brown University (Prior PediMIND Program Members)
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15
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Albajara Sáenz A, Villemonteix T, Van Schuerbeek P, Baijot S, Septier M, Defresne P, Delvenne V, Passeri G, Raeymaekers H, Victoor L, Willaye E, Peigneux P, Deconinck N, Massat I. Motor Abnormalities in Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder Are Associated With Regional Grey Matter Volumes. Front Neurol 2021; 12:666980. [PMID: 34017307 PMCID: PMC8129495 DOI: 10.3389/fneur.2021.666980] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 03/26/2021] [Indexed: 12/27/2022] Open
Abstract
Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) are associated with motor impairments, with some children holding a comorbid diagnosis of Developmental Coordination Disorder (DCD). However, DCD is underdiagnosed in these populations and the volume abnormalities that contribute to explaining these motor impairments are poorly understood. In this study, motor abilities as measured by the Developmental Coordination Disorder Questionnaire (DCDQ) were compared between children with ADHD, children with ASD and typically developing (TD) children, aged 8–12 years old. Additionally, the association between the DCDQ scores (general coordination, fine motor/handwriting, control during movement, total) and regional volume abnormalities were explored in 6 regions of interest (pre-central gyrus, post-central gyrus, inferior parietal cortex, superior frontal gyrus, middle frontal gyrus, medial frontal gyrus), within each group and across all participants. Children with ASD and children with ADHD showed impaired motor abilities in all the DCDQ-derived scores compared to TD children. Additionally, most children with ASD or ADHD had an indication or suspicion of DCD. Within the ASD group, coordination abilities were associated with the volume of the right medial frontal gyrus, and within the ADHD group, the total DCDQ score was associated with the volume of the right superior frontal gyrus. This study underlines the importance of routinely checking motor abilities in populations with ASD or ADHD in clinical practise and contributes to the understanding of structural abnormalities subtending motor impairments in these disorders.
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Affiliation(s)
- Ariadna Albajara Sáenz
- Neuropsychology and Functional Neuroimaging Research Group (UR2NF) at the Centre for Research in Cognition and Neurosciences, Université Libre de Bruxelles, Brussels, Belgium
| | - Thomas Villemonteix
- Neuropsychology and Functional Neuroimaging Research Group (UR2NF) at the Centre for Research in Cognition and Neurosciences, Université Libre de Bruxelles, Brussels, Belgium.,Paris 8 Vincennes - St Denis University, Laboratoire de Psychopathologie et Neuropsychologie, Saint Denis, France
| | | | - Simon Baijot
- Neuropsychology and Functional Neuroimaging Research Group (UR2NF) at the Centre for Research in Cognition and Neurosciences, Université Libre de Bruxelles, Brussels, Belgium.,Hôpital Universitaire des Enfants Reine Fabiola (HUDERF), Université Libre de Bruxelles, Brussels, Belgium
| | - Mathilde Septier
- Hôpital Universitaire Robert Debré, Paris, France.,Institut de Psychiatrie et de Neurosciences de Paris Inserm U894 Team 1, Paris, France
| | - Pierre Defresne
- Fondation SUSA (Service Universitaire Spéécialisé pour personnes avec Autisme), Université de Mons, Mons, Belgium
| | - Véronique Delvenne
- Hôpital Universitaire des Enfants Reine Fabiola (HUDERF), Université Libre de Bruxelles, Brussels, Belgium
| | - Gianfranco Passeri
- Hôpital Universitaire des Enfants Reine Fabiola (HUDERF), Université Libre de Bruxelles, Brussels, Belgium
| | - Hubert Raeymaekers
- Department of Radiology, Universitair Ziekenhuis Brussel, Brussels, Belgium
| | - Laurent Victoor
- PsyPluriel, Centre Européen de Psychologie Médicale, Brussels, Belgium
| | - Eric Willaye
- Fondation SUSA (Service Universitaire Spéécialisé pour personnes avec Autisme), Université de Mons, Mons, Belgium
| | - Philippe Peigneux
- Neuropsychology and Functional Neuroimaging Research Group (UR2NF) at the Centre for Research in Cognition and Neurosciences, Université Libre de Bruxelles, Brussels, Belgium
| | - Nicolas Deconinck
- Hôpital Universitaire des Enfants Reine Fabiola (HUDERF), Université Libre de Bruxelles, Brussels, Belgium
| | - Isabelle Massat
- Neuropsychology and Functional Neuroimaging Research Group (UR2NF) at the Centre for Research in Cognition and Neurosciences, Université Libre de Bruxelles, Brussels, Belgium.,Laboratory of Experimental Neurology, Université Libre de Bruxelles, Brussels, Belgium.,National Fund of Scientific Research, Brussels, Belgium.,Department of Neurology, Erasme Hospital, Brussels, Belgium
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16
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Hollestein V, Buitelaar JK, Brandeis D, Banaschewski T, Kaiser A, Hohmann S, Oranje B, Gooskens B, Durston S, Williams SCR, Lythgoe DJ, Naaijen J. Developmental changes in fronto-striatal glutamate and their association with functioning during inhibitory control in autism spectrum disorder and obsessive compulsive disorder. NEUROIMAGE-CLINICAL 2021; 30:102622. [PMID: 33765540 PMCID: PMC8022251 DOI: 10.1016/j.nicl.2021.102622] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 02/16/2021] [Accepted: 03/03/2021] [Indexed: 12/18/2022]
Abstract
Multi-center, longitudinal, transdiagnostic study of glutamate and neural activity. Differing roles of glutamate on activity in striatum during inhibitory control. Glutamate concentrations in ACC decrease over time in ASD adolescents. Differing neural mechanisms of compulsivity in OCD and repetitive behaviors in ASD.
Autism spectrum disorder (ASD) and obsessive compulsive disorder (OCD) show overlapping symptomatology and deficits in inhibitory control, which are associated with altered functioning and glutamatergic signaling in fronto-striatal circuitry. These parameters have never been examined together. The purpose of the current study was to investigate functioning during inhibitory control and its association with fronto-striatal glutamate concentrations across these disorders using a multi-center, longitudinal approach. Adolescents with ASD (n = 24), OCD (n = 15) and controls (n = 35) underwent two magnetic resonance imaging (MRI) sessions with a one-year interval. This included proton magnetic resonance spectroscopy (1H-MRS; n = 74) and functional MRI during an inhibitory control task (n = 53). We investigated 1H-MRS data and fMRI data separately as well as integrated in a multimodal analysis using linear models focusing on diagnosis and continuous measures of overlapping compulsivity symptoms. ACC glutamate was reduced over time in the ASD group compared with controls, while striatal glutamate decreased over time independent of diagnosis. Increased compulsive behavior seemed to be associated with increased striatal activity during failed inhibitory control. The integrated analyses showed differential involvement of increased striatal glutamate during failed but decreased striatal glutamate during successful inhibitory control in the OCD group compared to controls and ASD, suggesting different underlying mechanisms for OCD compared to ASD.
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Affiliation(s)
- Viola Hollestein
- Department of Cognitive Neuroscience, Donders Institute of Brain, Cognition and Behaviour, Radboud University Medical Center, the Netherlands.
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute of Brain, Cognition and Behaviour, Radboud University Medical Center, the Netherlands; Karakter Child and Adolescent Psychiatry University Center, Nijmegen, the Netherlands.
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty, Mannheim/Heidelberg University, Mannheim, Germany; Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zurich, Switzerland; Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich, Zurich, Switzerland; ETH Zurich, Zurich, Switzerland.
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty, Mannheim/Heidelberg University, Mannheim, Germany.
| | - Anna Kaiser
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty, Mannheim/Heidelberg University, Mannheim, Germany.
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty, Mannheim/Heidelberg University, Mannheim, Germany.
| | - Bob Oranje
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
| | - Bram Gooskens
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
| | - Sarah Durston
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
| | - Steven C R Williams
- Department of Neuroimaging, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, United Kingdom.
| | - David J Lythgoe
- Department of Neuroimaging, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, United Kingdom.
| | - Jilly Naaijen
- Department of Cognitive Neuroscience, Donders Institute of Brain, Cognition and Behaviour, Radboud University Medical Center, the Netherlands; Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, the Netherlands.
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17
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Gao X, Zhang M, Yang Z, Wen M, Huang H, Zheng R, Wang W, Wei Y, Cheng J, Han S, Zhang Y. Structural and Functional Brain Abnormalities in Internet Gaming Disorder and Attention-Deficit/Hyperactivity Disorder: A Comparative Meta-Analysis. Front Psychiatry 2021; 12:679437. [PMID: 34276447 PMCID: PMC8281314 DOI: 10.3389/fpsyt.2021.679437] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 05/21/2021] [Indexed: 12/20/2022] Open
Abstract
Background: Patients with Internet gaming disorder (IGD) and attention-deficit/hyperactivity disorder (ADHD) have high comorbidity but it is still unknown whether these disorders have shared and distinctive neuroimage alterations. Objective: The aim of this meta-analysis was to identify shared and disorder-specific structural, functional, and multimodal abnormalities between IGD and ADHD. Methods: A systematic literature search was conducted for whole-brain voxel-based morphometry (VBM) and functional magnetic resonance imaging (fMRI) studies comparing people with IGD or ADHD with healthy controls. Regional gray matter volume (GMV) and fMRI differences were compared over the patient groups and then a quantitative comparison was performed to find abnormalities (relative to controls) between IGD and ADHD using seed-based d mapping meta-analytic methods. Result: The meta-analysis contained 14 IGD VBM studies (contrasts covering 333 IGDs and 335 HCs), 26 ADHD VBM studies (1,051 patients with ADHD and 887 controls), 30 IGD fMRI studies (603 patients with IGD and 564 controls), and 29 ADHD fMRI studies (878 patients with ADHD and 803 controls). Structurally, VBM analysis showed disorder-specific GMV abnormality in the putamen among IGD subjects and orbitofrontal cortex in ADHD and shared GMV in the prefrontal cortex. Functionally, fMRI analysis discovered that IGD-differentiating increased activation in the precuneus and shared abnormal activation in anterior cingulate cortex, insular, and striatum. Conclusion: IGD and ADHD have shared and special structural and functional alterations. IGD has disorder-differentiating structural alterations in the putamen and ADHD has alterations in the orbitofrontal cortex. Disorder-differentiating fMRI activations were predominantly observed in the precuneus among IGD subjects and shared impairing function connection was in the rewards circuit (including ACC, OFC, and striatum).
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Affiliation(s)
- Xinyu Gao
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
| | - Mengzhe Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
| | - Zhengui Yang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
| | - Mengmeng Wen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
| | - Huiyu Huang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
| | - Ruiping Zheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
| | - Weijian Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
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18
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Chu KC, Lu HK, Huang MC, Lin SJ, Liu WI, Huang YS, Hsu JF, Wang CH. Using Mobile Electroencephalography and Actigraphy to Diagnose Attention-Deficit/Hyperactivity Disorder: Case-Control Comparison Study. JMIR Ment Health 2020; 7:e12158. [PMID: 32558658 PMCID: PMC7351267 DOI: 10.2196/12158] [Citation(s) in RCA: 4] [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: 09/14/2018] [Revised: 06/30/2019] [Accepted: 03/29/2020] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Children with attention-deficit/hyperactivity disorder (ADHD), a neurobehavioral disorder, display behaviors of inattention, hyperactivity, or impulsivity, which can affect their ability to learn and establish proper family and social relationships. Various tools are currently used by child and adolescent psychiatric clinics to diagnose, evaluate, and collect information and data. The tools allow professional physicians to assess if patients need further treatment, following a thorough and careful clinical diagnosis process. OBJECTIVE We aim to determine potential indicators extracted from a mobile electroencephalography (EEG) device (Mindset; NeuroSky) and an actigraph (MotionWatch 8; CamNtech) and to validate them for diagnosis of ADHD. The 3 indicators are (1) attention, measured by the EEG; (2) meditation, measured by the EEG; and (3) activity, measured by the actigraph. METHODS A total of 63 participants were recruited. The case group comprised 40 boys and 9 girls, while the control group comprised 5 boys and 9 girls. The groups were age matched. The test was divided into 3 stages-pretest, in-test, and posttest-with a testing duration of 20 minutes each. We used correlation analysis, repeated measures analysis of variance, and regression analysis to investigate which indicators can be used for ADHD diagnosis. RESULTS With the EEG indicators, the analysis results show a significant correlation of attention with both hit reaction time (RT) interstimulus interval (ISI) change (r=-0.368; P=.003) and hit standard error (SE) ISI change (r=-0.336; P=.007). This indicates that the higher the attention of the participants, the smaller both the hit RT change and the hit SE ISI change. With the actigraph indicator, confidence index (r=0.352; P=.005), omissions (r=0.322; P=.01), hit RT SE (r=0.393; P=.001), and variability (r=0.351; P=.005) were significant. This indicates that the higher the activity amounts, the higher the impulsive behavior of the participants and the more target omissions in the continuous performance test (CPT). The results show that the participants with ADHD present a significant difference in activity amounts (P<0.001). The actigraph outperforms the EEG in screening ADHD. CONCLUSIONS When the participants with ADHD are stimulated under restricted conditions, they will present different amounts of activity than in unrestricted conditions due to participants' inability to exercise control over their concentration. This finding could be a new electronic physiological biomarker of ADHD. An actigraph can be used to detect the amount of activity exhibited and to help physicians diagnose the disorder in order to develop more objective, rapid auxiliary diagnostic tools.
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Affiliation(s)
- Kuo-Chung Chu
- Department of Information Management, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan
| | - Hsin-Ke Lu
- Department of Information Management, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan.,Department of Information Technology, Taipei City Government, Taipei, Taiwan
| | - Ming-Chun Huang
- Department of Electrical, Computer, and Systems Engineering, Case Western Reserve University, Cleveland, OH, United States
| | - Shr-Jie Lin
- Department of Information Management, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan.,Department of Computer Center, Cheng Hsin General Hospital, Taipei, Taiwan
| | - Wen-I Liu
- Department of Nursing, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan
| | - Yu-Shu Huang
- Department of Child Psychiatry and Sleep Center, Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Jen-Fu Hsu
- Division of Neonatology, Department of Pediatrics, Chang Gung Memorial Hospital and Chang Gung University, Taoyuan, Taiwan
| | - Chih-Huan Wang
- Department of Psychology, Zhejiang Normal University, Zhejiang, China
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