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Qian Q, Cai S, Zhang X, Huang J, Chen Y, Wang A, Zhang M. Seeing is believing: Larger Colavita effect in school-aged children with attention-deficit/hyperactivity disorder. J Exp Child Psychol 2024; 238:105798. [PMID: 37844345 DOI: 10.1016/j.jecp.2023.105798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 08/07/2023] [Accepted: 09/25/2023] [Indexed: 10/18/2023]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder that leads to visually relevant compensatory activities and cognitive strategies in children. Previous studies have identified difficulties with audiovisual integration in children with ADHD, but the characteristics of the visual dominance effect when processing multisensory stimuli are not clear in children with ADHD. The current study used the Colavita paradigm to explore the visual dominance effect in school-aged children with ADHD. The results found that, compared with typically developing children, children with ADHD had a higher proportion of "visual-auditory" trials and a lower proportion of "simultaneous" trials. The study also found that the proportion of visual-auditory trials in children with ADHD decreased as their Swanson, Nolan, and Pelham-IV rating scale (SNAP-IV) inattention scores increased. The results showed that school-aged children with ADHD had a larger Colavita effect, which decreased with the severity of inattentive symptoms. This may be due to an overreliance on visual information and an abnormal integration time window. The connection between multisensory cognitive processing performance and clinical symptoms found in the current study provides empirical and theoretical support for the knowledge base of multisensory and cognitive abilities in disorders.
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Affiliation(s)
- Qinyue Qian
- Department of Psychology, Soochow University, Suzhou, Jiangsu 215123, China; Research Center for Psychology and Behavioral Sciences, Soochow University, Suzhou, Jiangsu 215123, China
| | - Shizhong Cai
- Department of Child and Adolescent Healthcare, Children's Hospital of Soochow University, Suzhou, Jiangsu 215003, China
| | - Xianghui Zhang
- Department of Psychology, Soochow University, Suzhou, Jiangsu 215123, China; Research Center for Psychology and Behavioral Sciences, Soochow University, Suzhou, Jiangsu 215123, China
| | - Jie Huang
- Department of Psychology, Soochow University, Suzhou, Jiangsu 215123, China; Research Center for Psychology and Behavioral Sciences, Soochow University, Suzhou, Jiangsu 215123, China
| | - Yan Chen
- Department of Child and Adolescent Healthcare, Children's Hospital of Soochow University, Suzhou, Jiangsu 215003, China.
| | - Aijun Wang
- Department of Psychology, Soochow University, Suzhou, Jiangsu 215123, China; Research Center for Psychology and Behavioral Sciences, Soochow University, Suzhou, Jiangsu 215123, China.
| | - Ming Zhang
- Department of Psychology, Soochow University, Suzhou, Jiangsu 215123, China; Research Center for Psychology and Behavioral Sciences, Soochow University, Suzhou, Jiangsu 215123, China; Department of Psychology, Suzhou University of Science and Technology, Suzhou, Jiangsu 215011, China; Faculty of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama 700-8530, Japan.
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2
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Kwasa JA, Noyce AL, Torres LM, Richardson BN, Shinn-Cunningham BG. Top-down auditory attention modulates neural responses more strongly in neurotypical than ADHD young adults. Brain Res 2023; 1798:148144. [PMID: 36328068 PMCID: PMC9749882 DOI: 10.1016/j.brainres.2022.148144] [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: 05/24/2022] [Revised: 10/24/2022] [Accepted: 10/26/2022] [Indexed: 11/06/2022]
Abstract
Human cognitive abilities naturally vary along a spectrum, even among those we call "neurotypical". Individuals differ in their ability to selectively attend to goal-relevant auditory stimuli. We sought to characterize this variability in a cohort of people with diverse attentional functioning. We recruited both neurotypical (N = 20) and ADHD (N = 25) young adults, all with normal hearing. Participants listened to one of three concurrent, spatially separated speech streams and reported the order of the syllables in that stream while we recorded electroencephalography (EEG). We tested both the ability to sustain attentional focus on a single "Target" stream and the ability to monitor the Target but flexibly either ignore or switch attention to an unpredictable "Interrupter" stream from another direction that sometimes appeared. Although differences in both stimulus structure and task demands affected behavioral performance, ADHD status did not. In both groups, the Interrupter evoked larger neural responses when it was to be attended compared to when it was irrelevant, including for the P3a "reorienting" response previously described as involuntary. This attentional modulation was weaker in ADHD listeners, even though their behavioral performance was the same. Across the entire cohort, individual performance correlated with the degree of top-down modulation of neural responses. These results demonstrate that listeners differ in their ability to modulate neural representations of sound based on task goals, while suggesting that adults with ADHD may have weaker volitional control of attentional processes than their neurotypical counterparts.
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Affiliation(s)
- Jasmine A. Kwasa
- Neuroscience Institute, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA, 15213, United States, Department of Biomedical Engineering, Boston University, 1 Silber Way, Boston, MA, 02215, United States, Corresponding author at: 4825 Frew St, A52A Baker Hall, Pittsburgh, PA 15213, United States. (J.A. Kwasa)
| | - Abigail L. Noyce
- Neuroscience Institute, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA, 15213, United States
| | - Laura M. Torres
- Department of Biomedical Engineering, Boston University, 1 Silber Way, Boston, MA, 02215, United States
| | - Benjamin N. Richardson
- Neuroscience Institute, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA, 15213, United States
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3
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Fu T, Li B, Yin W, Huang S, Liu H, Song Y, Li X, Shang H, Zhou Y, Cheng D, Cao L, Dang CP. Sound localization and auditory selective attention in school-aged children with ADHD. Front Neurosci 2022; 16:1051585. [PMID: 36620456 PMCID: PMC9812578 DOI: 10.3389/fnins.2022.1051585] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 11/14/2022] [Indexed: 12/23/2022] Open
Abstract
This study aimed to identify the neurophysiologic bases of auditory attention deficits in children with attention-deficit/hyperactivity disorder (ADHD), focusing on the electroencephalography component of auditory spatial selective attention [the N2 anterior contralateral component (N2ac)]. EEG data were collected from 7- to 11-year-old children with ADHD (n = 54) and age-, sex-, and IQ-matched typically developing (TD) children (n = 61), while they performed an auditory spatial selective task. For behavior, the children with ADHD showed a shorter reaction time (RT) but a higher RT coefficient of variability (RTCV) than TD children. For ERPs, the TD group showed a significant "adult-like" N2ac component; however, the N2ac component was absent in children with ADHD. More importantly, the smaller N2ac component could predict longer RT in both groups, as well as higher severity of inattentive symptoms in children with ADHD. Our results indicated that 7- to 11-year-old TD children have developed an "adult-like" ability to balance auditory target selection and distractor suppression; the absence of N2ac in children with ADHD provided novel evidence supporting their dysfunctional auditory spatial selective attention.
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Affiliation(s)
- Tong Fu
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China,Institute of Psychiatry and Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Bingkun Li
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Weizhen Yin
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China,Institute of Psychiatry and Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Shitao Huang
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China,Institute of Psychiatry and Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Hongyu Liu
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yan Song
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China,Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China
| | - Xiaoli Li
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Herui Shang
- Department of Applied Psychology, Guangzhou Medical University, Guangzhou, China
| | - Yanling Zhou
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China,Institute of Psychiatry and Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Daomeng Cheng
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China,Institute of Psychiatry and Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Liping Cao
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China,Institute of Psychiatry and Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China,Liping Cao
| | - Cai-Ping Dang
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China,Department of Applied Psychology, Guangzhou Medical University, Guangzhou, China,Institute of Psychiatry and Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China,*Correspondence: Cai-Ping Dang
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4
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Shephard E, McEwen FS, Earnest T, Friedrich N, Mörtl I, Liang H, Woodhouse E, Tye C, Bolton PF. Oscillatory neural network alterations in young people with tuberous sclerosis complex and associations with co-occurring symptoms of autism spectrum disorder and attention-deficit/hyperactivity disorder. Cortex 2021; 146:50-65. [PMID: 34839218 DOI: 10.1016/j.cortex.2021.10.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 08/25/2021] [Accepted: 10/20/2021] [Indexed: 12/20/2022]
Abstract
Tuberous sclerosis complex (TSC) is a genetic disorder caused by mutations on the TSC1/TSC2 genes, which result in alterations in molecular signalling pathways involved in neurogenesis and hamartomas in the brain and other organs. TSC carries a high risk for autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), although the reasons for this are unclear. One proposal is that TSC-related alterations in molecular signalling during neurogenesis lead to atypical development of neural networks, which are involved in the occurrence of ASD and ADHD in TSC. We investigated this proposal in young people with TSC who have been studied longitudinally since their diagnosis in childhood. Electroencephalography (EEG) was used to examine oscillatory connectivity in functional neural networks and local and global network organisation during three tasks (resting-state, attentional and inhibitory control Go/Nogo task, upright and inverted face processing task) in participants with TSC (n = 48) compared to an age- and sex-matched group of typically developing Controls (n = 20). Compared to Controls, the TSC group showed hypoconnected neural networks in the alpha frequency during the resting-state and in the theta and alpha frequencies during the Go/Nogo task (P ≤ .008), as well as reduced local network organisation in the theta and alpha frequencies during the Go/Nogo task (F = 3.95, P = .010). There were no significant group differences in network metrics during the face processing task. Increased connectivity in the hypoconnected alpha-range resting-state network was associated with greater ASD and inattentive ADHD symptoms (rho≥.40, P ≤ .036). Reduced local network organisation in the theta-range during the Go/Nogo task was significantly associated with higher hyperactive/impulsive ADHD symptoms (rho = -.43, P = .041). These findings suggest that TSC is associated with widespread hypoconnectivity in neural networks and support the proposal that altered network function may be involved in the co-occurrence of ASD and ADHD in TSC.
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Affiliation(s)
- Elizabeth Shephard
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, UK; Department of Psychiatry, University of São Paulo, Brazil.
| | - Fiona S McEwen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, UK; Department of Psychology, Queen Mary University of London, UK
| | - Thomas Earnest
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, UK
| | - Nina Friedrich
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, UK
| | - Isabelle Mörtl
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, UK
| | - Holan Liang
- Population, Policy and Practice Department, UCL Great Ormond Street Institute of Child Health, London, UK
| | - Emma Woodhouse
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, UK
| | | | - Charlotte Tye
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, UK; Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, UK
| | - Patrick F Bolton
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, UK; The Maudsley NIHR Biomedical Research Centre in Mental Health, King's College London and South London and Maudsley NHS Foundation Trust, London, UK
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5
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McColgan P, Joubert J, Tabrizi SJ, Rees G. The human motor cortex microcircuit: insights for neurodegenerative disease. Nat Rev Neurosci 2020; 21:401-415. [PMID: 32555340 DOI: 10.1038/s41583-020-0315-1] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/04/2020] [Indexed: 12/22/2022]
Abstract
The human motor cortex comprises a microcircuit of five interconnected layers with different cell types. In this Review, we use a layer-specific and cell-specific approach to integrate physiological accounts of this motor cortex microcircuit with the pathophysiology of neurodegenerative diseases affecting motor functions. In doing so we can begin to link motor microcircuit pathology to specific disease stages and clinical phenotypes. Based on microcircuit physiology, we can make future predictions of axonal loss and microcircuit dysfunction. With recent advances in high-resolution neuroimaging we can then test these predictions in humans in vivo, providing mechanistic insights into neurodegenerative disease.
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Affiliation(s)
- Peter McColgan
- Huntington's Disease Research Centre, UCL Institute of Neurology, University College London, London, UK.
| | - Julie Joubert
- Huntington's Disease Research Centre, UCL Institute of Neurology, University College London, London, UK
| | - Sarah J Tabrizi
- Huntington's Disease Research Centre, UCL Institute of Neurology, University College London, London, UK.,Dementia Research Institute at UCL, London, UK
| | - Geraint Rees
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, UK.,UCL Institute of Cognitive Neuroscience, University College London, London, UK
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6
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Tombor L, Kakuszi B, Papp S, Réthelyi J, Bitter I, Czobor P. Decreased resting gamma activity in adult attention deficit/hyperactivity disorder. World J Biol Psychiatry 2019; 20:691-702. [PMID: 29457912 DOI: 10.1080/15622975.2018.1441547] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Objectives: To delineate task-free gamma activity in adult ADHD and healthy control subjects based on high-density EEG recordings. Relationship of gamma activity with symptom severity was also examined, since gamma activity is considered to be an index of network functions in the brain that underlie higher-order cognitive processes.Methods: Spontaneous EEG was recorded in adult ADHD subjects (N = 42; 25 methylphenidate-naïve and 17 on methylphenidate treatment) and controls (N = 59) with eyes open. EEG absolute power gamma was investigated in the gamma1 (30.25-39 Hz) and gamma2 (39.25-48 Hz) frequency bands.Results: Gamma1 and gamma2 activity was diminished in ADHD compared with healthy control subjects. The difference between ADHD and controls was the most pronounced in the right centroparietal region for both gamma1 and gamma2. Inverse associations were found between gamma1 and gamma2 activity and ADHD symptoms in centroparietal scalp regions.Conclusions: Gamma activity is reduced in adult ADHD, and the reduction has a predominantly right centroparietal distribution. Our findings are consistent with childhood ADHD literature with respect to diminished posterior gamma activity in patients, which may reflect altered dorsal attention network functions. Gamma abnormalities might provide a link between neurophysiological functioning and neuropsychological deficiencies, thereby offering an opportunity to investigate the neurobiological mechanisms that underlie the clinical symptoms of ADHD.
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Affiliation(s)
- László Tombor
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Brigitta Kakuszi
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Szilvia Papp
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - János Réthelyi
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - István Bitter
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Pál Czobor
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
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7
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He B, Astolfi L, Valdés-Sosa PA, Marinazzo D, Palva SO, Bénar CG, Michel CM, Koenig T. Electrophysiological Brain Connectivity: Theory and Implementation. IEEE Trans Biomed Eng 2019; 66:10.1109/TBME.2019.2913928. [PMID: 31071012 PMCID: PMC6834897 DOI: 10.1109/tbme.2019.2913928] [Citation(s) in RCA: 90] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
We review the theory and algorithms of electrophysiological brain connectivity analysis. This tutorial is aimed at providing an introduction to brain functional connectivity from electrophysiological signals, including electroencephalography (EEG), magnetoencephalography (MEG), electrocorticography (ECoG), stereoelectroencephalography (SEEG). Various connectivity estimators are discussed, and algorithms introduced. Important issues for estimating and mapping brain functional connectivity with electrophysiology are discussed.
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Affiliation(s)
- Bin He
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, USA
| | - Laura Astolfi
- Department of Computer, Control and Management Engineering, University of Rome Sapienza, and with IRCCS Fondazione Santa Lucia, Rome, Italy
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8
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Albajara Sáenz A, Villemonteix T, Massat I. Structural and functional neuroimaging in attention-deficit/hyperactivity disorder. Dev Med Child Neurol 2019; 61:399-405. [PMID: 30276811 DOI: 10.1111/dmcn.14050] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/14/2018] [Indexed: 01/13/2023]
Abstract
Over the last decade, there has been a dramatic increase in the number of neuroimaging studies in attention-deficit/hyperactivity disorder (ADHD). In terms of brain structure, magnetic resonance imaging (MRI), and diffusion tensor imaging studies have evidenced differences in volume, surface-based measures (cortical thickness, surface area, and gyrification), and white matter integrity in different cerebral regions, in children and adults with ADHD compared to population norms. Abnormalities in the basal ganglia, prefrontal structures, and the corpus callosum have been the most consistently reported findings across studies. Hemodynamic (functional MRI, functional near-infrared spectroscopy, positron emission tomography, single-photon emission computed tomography) and magnetoencephalography measurements have also shown differences in neural activity during the execution of neuropsychological tasks and during rest, in widespread regions of the brain. Importantly, multimodal studies combining structural and functional methods have shown an intercorrelation between structural and functional abnormalities in ADHD. Further longitudinal studies are needed to clarify the effects of age and medication on brain structure and function in individuals with ADHD. WHAT THIS PAPER ADDS: In attention-deficit/hyperactivity disorder (ADHD), the brain is characterized by abnormal neural network interplay. Structural and functional cerebral abnormalities in ADHD are intercorrelated. Currently there is no neural biomarker that can be used in diagnosis. Longitudinal studies have shed light on the brain correlates of ADHD over the lifespan. The effects of stimulant intake on the brain correlates of ADHD remain unclear.
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Affiliation(s)
- Ariadna Albajara Sáenz
- UR2NF/Neuropsychology and Functional Neuroimaging Research Group, Centre for Research in Cognition and Neurosciences, Neurosciences Institute, Université Libre de Bruxelles, Brussels, Belgium
| | - Thomas Villemonteix
- UR2NF/Neuropsychology and Functional Neuroimaging Research Group, Centre for Research in Cognition and Neurosciences, Neurosciences Institute, Université Libre de Bruxelles, Brussels, Belgium.,Laboratoire de Psychopathologie et Neuropsychologie, Universite de Vincennes, Paris, France
| | - Isabelle Massat
- UR2NF/Neuropsychology and Functional Neuroimaging Research Group, Centre for Research in Cognition and Neurosciences, Neurosciences Institute, Université Libre de Bruxelles, Brussels, Belgium.,National Fund of Scientific Research, Brussels, Belgium.,Laboratory of Experimental Neurology, Université Libre de Bruxelles, Brussels, Belgium
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9
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Shephard E, Tye C, Ashwood KL, Azadi B, Johnson MH, Charman T, Asherson P, McLoughlin G, Bolton PF. Oscillatory neural networks underlying resting-state, attentional control and social cognition task conditions in children with ASD, ADHD and ASD+ADHD. Cortex 2019; 117:96-110. [PMID: 30954695 DOI: 10.1016/j.cortex.2019.03.005] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2018] [Revised: 02/26/2019] [Accepted: 03/06/2019] [Indexed: 10/27/2022]
Abstract
Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are common and impairing neurodevelopmental disorders that frequently co-occur. The neurobiological mechanisms involved in ASD and ADHD are not fully understood. However, alterations in large-scale neural networks have been proposed as core deficits in both ASD and ADHD and may help to disentangle the neurobiological basis of these disorders and their co-occurrence. In this study, we examined similarities and differences in large-scale oscillatory neural networks between boys aged 8-13 years with ASD (n = 19), ADHD (n = 18), ASD + ADHD (n = 29) and typical development (Controls, n = 26). Oscillatory neural networks were computed using graph-theoretical methods from electroencephalographic (EEG) data collected during an eyes-open resting-state and attentional control and social cognition tasks in which we previously reported disorder-specific atypicalities in oscillatory power and event-related potentials (ERPs). We found that children with ASD showed significant hypoconnectivity in large-scale networks during all three task conditions compared to children without ASD. In contrast, children with ADHD showed significant hyperconnectivity in large-scale networks during the attentional control and social cognition tasks, but not during the resting-state, compared to children without ADHD. Children with co-occurring ASD + ADHD did not differ from children with ASD when paired with this group and vice versa when paired with the ADHD group, indicating that these children showed both ASD-like hypoconnectivity and ADHD-like hyperconnectivity. Our findings suggest that ASD and ADHD are associated with distinct alterations in large-scale oscillatory networks, and these atypicalities present together in children with both disorders. These alterations appear to be task-independent in ASD but task-related in ADHD, and may underlie other neurocognitive atypicalities in these disorders.
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Affiliation(s)
- Elizabeth Shephard
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK.
| | - Charlotte Tye
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK
| | - Karen L Ashwood
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK
| | - Bahar Azadi
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK
| | - Mark H Johnson
- Centre for Brain and Cognitive Development, School of Psychology, Birkbeck, University of London, UK; Department of Psychology, University of Cambridge, UK
| | - Tony Charman
- Department of Psychology, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, UK
| | - Philip Asherson
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, UK
| | - Grainne McLoughlin
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, UK
| | - Patrick F Bolton
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK
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10
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Rohr CS, Arora A, Cho IYK, Katlariwala P, Dimond D, Dewey D, Bray S. Functional network integration and attention skills in young children. Dev Cogn Neurosci 2018; 30:200-211. [PMID: 29587178 PMCID: PMC6969078 DOI: 10.1016/j.dcn.2018.03.007] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Revised: 02/12/2018] [Accepted: 03/15/2018] [Indexed: 12/17/2022] Open
Abstract
Children acquire attention skills rapidly during early childhood as their brains undergo vast neural development. Attention is well studied in the adult brain, yet due to the challenges associated with scanning young children, investigations in early childhood are sparse. Here, we examined the relationship between age, attention and functional connectivity (FC) during passive viewing in multiple intrinsic connectivity networks (ICNs) in 60 typically developing girls between 4 and 7 years whose sustained, selective and executive attention skills were assessed. Visual, auditory, sensorimotor, default mode (DMN), dorsal attention (DAN), ventral attention (VAN), salience, and frontoparietal ICNs were identified via Independent Component Analysis and subjected to a dual regression. Individual spatial maps were regressed against age and attention skills, controlling for age. All ICNs except the VAN showed regions of increasing FC with age. Attention skills were associated with FC in distinct networks after controlling for age: selective attention positively related to FC in the DAN; sustained attention positively related to FC in visual and auditory ICNs; and executive attention positively related to FC in the DMN and visual ICN. These findings suggest distributed network integration across this age range and highlight how multiple ICNs contribute to attention skills in early childhood.
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Affiliation(s)
- Christiane S Rohr
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.
| | - Anish Arora
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Ivy Y K Cho
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Prayash Katlariwala
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Dennis Dimond
- Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Deborah Dewey
- Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Signe Bray
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.
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Klein M, Onnink M, van Donkelaar M, Wolfers T, Harich B, Shi Y, Dammers J, Arias-Vásquez A, Hoogman M, Franke B. Brain imaging genetics in ADHD and beyond - Mapping pathways from gene to disorder at different levels of complexity. Neurosci Biobehav Rev 2017; 80:115-155. [PMID: 28159610 PMCID: PMC6947924 DOI: 10.1016/j.neubiorev.2017.01.013] [Citation(s) in RCA: 58] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2016] [Revised: 12/08/2016] [Accepted: 01/09/2017] [Indexed: 01/03/2023]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is a common and often persistent neurodevelopmental disorder. Beyond gene-finding, neurobiological parameters, such as brain structure, connectivity, and function, have been used to link genetic variation to ADHD symptomatology. We performed a systematic review of brain imaging genetics studies involving 62 ADHD candidate genes in childhood and adult ADHD cohorts. Fifty-one eligible research articles described studies of 13 ADHD candidate genes. Almost exclusively, single genetic variants were studied, mostly focussing on dopamine-related genes. While promising results have been reported, imaging genetics studies are thus far hampered by methodological differences in study design and analysis methodology, as well as limited sample sizes. Beyond reviewing imaging genetics studies, we also discuss the need for complementary approaches at multiple levels of biological complexity and emphasize the importance of combining and integrating findings across levels for a better understanding of biological pathways from gene to disease. These may include multi-modal imaging genetics studies, bioinformatic analyses, and functional analyses of cell and animal models.
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Affiliation(s)
- Marieke Klein
- Department of Human Genetics, Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Marten Onnink
- Department of Human Genetics, Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Marjolein van Donkelaar
- Department of Human Genetics, Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Thomas Wolfers
- Department of Human Genetics, Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Benjamin Harich
- Department of Human Genetics, Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Yan Shi
- Department of Human Genetics, Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Janneke Dammers
- Department of Human Genetics, Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands; Department of Psychiatry, Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Alejandro Arias-Vásquez
- Department of Human Genetics, Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands; Department of Psychiatry, Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands; Department of Cognitive Neuroscience, Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Martine Hoogman
- Department of Human Genetics, Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Barbara Franke
- Department of Human Genetics, Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands; Department of Psychiatry, Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.
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12
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Edgar JC, Fisk CL, Chen YH, Stone-Howell B, Hunter MA, Huang M, Bustillo JR, Cañive JM, Miller GA. By our bootstraps: Comparing methods for measuring auditory 40 Hz steady-state neural activity. Psychophysiology 2017; 54:1110-1127. [PMID: 28421620 DOI: 10.1111/psyp.12876] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2016] [Revised: 03/10/2017] [Accepted: 03/16/2017] [Indexed: 11/29/2022]
Abstract
Although the 40 Hz auditory steady-state response (ASSR) is of clinical interest, the construct validity of EEG and MEG measures of 40 Hz ASSR cortical microcircuits is unclear. This study evaluated several MEG and EEG metrics by leveraging findings of (a) an association between the 40 Hz ASSR and age in the left but not right hemisphere, and (b) right- > left-hemisphere differences in the strength of the 40 Hz ASSR. The contention is that, if an analysis method does not demonstrate a left 40 Hz ASSR and age relationship or hemisphere differences, then the obtained measures likely have low validity. Fifty-three adults were presented 500 Hz stimuli modulated at 40 Hz while MEG and EEG were collected. ASSR activity was examined as a function of phase similarity (intertrial coherence) and percent change from baseline (total power). A variety of head models (spherical and realistic) and a variety of dipole source modeling strategies (dipole source localization and dipoles fixed to Heschl's gyri) were compared. Several sensor analysis strategies were also tested. EEG sensor measures failed to detect left 40 Hz ASSR and age associations or hemisphere differences. A comparison of MEG and EEG head-source models showed similarity in the 40 Hz ASSR measures and in estimating age and left 40 Hz ASSR associations, indicating good construct validity across models. Given a goal of measuring the 40 Hz ASSR cortical microcircuits, a source-modeling approach was shown to be superior in measuring this construct versus methods that rely on EEG sensor measures.
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Affiliation(s)
- J Christopher Edgar
- Children's Hospital of Philadelphia and University of Pennsylvania, Philadelphia, Pennsylvania
| | - Charles L Fisk
- Children's Hospital of Philadelphia and University of Pennsylvania, Philadelphia, Pennsylvania
| | - Yu-Han Chen
- Children's Hospital of Philadelphia and University of Pennsylvania, Philadelphia, Pennsylvania
| | - Breannan Stone-Howell
- University of New Mexico School of Medicine, Department of Psychiatry, Center for Psychiatric Research, Albuquerque, New Mexico.,New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, New Mexico
| | - Michael A Hunter
- University of New Mexico School of Medicine, Department of Psychiatry, Center for Psychiatric Research, Albuquerque, New Mexico.,New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, New Mexico
| | - Mingxiong Huang
- University of California, San Diego, Department of Radiology, San Diego, California.,San Diego VA Healthcare System, Department of Radiology, San Diego, California
| | - Juan R Bustillo
- University of New Mexico School of Medicine, Department of Psychiatry, Center for Psychiatric Research, Albuquerque, New Mexico
| | - José M Cañive
- University of New Mexico School of Medicine, Department of Psychiatry, Center for Psychiatric Research, Albuquerque, New Mexico.,New Mexico Raymond G. Murphy VA Healthcare System, Psychiatry Research, Albuquerque, New Mexico
| | - Gregory A Miller
- University of California, Los Angeles, Department of Psychology and Department of Psychiatry and Biobehavioral Sciences, Los Angeles, California
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Wilson TW, Heinrichs-Graham E, Proskovec AL, McDermott TJ. Neuroimaging with magnetoencephalography: A dynamic view of brain pathophysiology. Transl Res 2016; 175:17-36. [PMID: 26874219 PMCID: PMC4959997 DOI: 10.1016/j.trsl.2016.01.007] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2015] [Revised: 01/15/2016] [Accepted: 01/18/2016] [Indexed: 01/12/2023]
Abstract
Magnetoencephalography (MEG) is a noninvasive, silent, and totally passive neurophysiological imaging method with excellent temporal resolution (∼1 ms) and good spatial precision (∼3-5 mm). In a typical experiment, MEG data are acquired as healthy controls or patients with neurologic or psychiatric disorders perform a specific cognitive task, or receive sensory stimulation. The resulting data are generally analyzed using standard electrophysiological methods, coupled with advanced image reconstruction algorithms. To date, the total number of MEG instruments and associated users is significantly smaller than comparable human neuroimaging techniques, although this is likely to change in the near future with advances in the technology. Despite this small base, MEG research has made a significant impact on several areas of translational neuroscience, largely through its unique capacity to quantify the oscillatory dynamics of activated brain circuits in humans. This review focuses on the clinical areas where MEG imaging has arguably had the greatest impact in regard to the identification of aberrant neural dynamics at the regional and network level, monitoring of disease progression, determining how efficacious pharmacologic and behavioral interventions modulate neural systems, and the development of neural markers of disease. Specifically, this review covers recent advances in understanding the abnormal neural oscillatory dynamics that underlie Parkinson's disease, autism spectrum disorders, human immunodeficiency virus (HIV)-associated neurocognitive disorders, cerebral palsy, attention-deficit hyperactivity disorder, cognitive aging, and post-traumatic stress disorder. MEG imaging has had a major impact on how clinical neuroscientists understand the brain basis of these disorders, and its translational influence is rapidly expanding with new discoveries and applications emerging continuously.
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Affiliation(s)
- Tony W Wilson
- Department of Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center (UNMC), Omaha, Neb; Center for Magnetoencephalography, UNMC, Omaha, Neb; Department of Neurological Sciences, UNMC, Omaha, Neb.
| | - Elizabeth Heinrichs-Graham
- Department of Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center (UNMC), Omaha, Neb; Center for Magnetoencephalography, UNMC, Omaha, Neb
| | - Amy L Proskovec
- Center for Magnetoencephalography, UNMC, Omaha, Neb; Department of Psychology, University of Nebraska - Omaha, Neb
| | - Timothy J McDermott
- Department of Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center (UNMC), Omaha, Neb; Center for Magnetoencephalography, UNMC, Omaha, Neb
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MEG Analysis of Neural Interactions in Attention-Deficit/Hyperactivity Disorder. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2016; 2016:8450241. [PMID: 27118965 PMCID: PMC4828555 DOI: 10.1155/2016/8450241] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/24/2015] [Accepted: 03/07/2016] [Indexed: 11/30/2022]
Abstract
The aim of the present study was to explore the interchannel relationships of resting-state brain activity in patients with attention-deficit/hyperactivity disorder (ADHD), one of the most common mental disorders that develop in children. Magnetoencephalographic (MEG) signals were recorded using a 148-channel whole-head magnetometer in 13 patients with ADHD (range: 8–12 years) and 14 control subjects (range: 8–13 years). Three complementary measures (coherence, phase-locking value, and Euclidean distance) were calculated in the conventional MEG frequency bands: delta, theta, alpha, beta, and gamma. Our results showed that the interactions among MEG channels are higher for ADHD patients than for control subjects in all frequency bands. Statistically significant differences were observed for short-distance values within right-anterior and central regions, especially at delta, beta, and gamma-frequency bands (p < 0.05; Mann-Whitney U test with false discovery rate correction). These frequency bands also showed statistically significant differences in long-distance interactions, mainly among anterior and central regions, as well as among anterior, central, and other areas. These differences might reflect alterations during brain development in children with ADHD. Our results support the role of frontal abnormalities in ADHD pathophysiology, which may reflect a delay in cortical maturation in the frontal cortex.
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Edgar JC, Fisk CL, Liu S, Pandey J, Herrington JD, Schultz RT, Roberts TPL. Translating Adult Electrophysiology Findings to Younger Patient Populations: Difficulty Measuring 40-Hz Auditory Steady-State Responses in Typically Developing Children and Children with Autism Spectrum Disorder. Dev Neurosci 2016; 38:1-14. [PMID: 26730806 DOI: 10.1159/000441943] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2015] [Accepted: 10/23/2015] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND x03B3; (∼30-80 Hz) brain rhythms are thought to be abnormal in neurodevelopmental disorders such as schizophrenia and autism spectrum disorder (ASD). In adult populations, auditory 40-Hz click trains or 40-Hz amplitude-modulated tones are used to assess the integrity of superior temporal gyrus (STG) 40-Hz x03B3;-band circuits. As STG 40-Hz auditory steady-state responses (ASSRs) are not fully developed in children, tasks using these stimuli may not be optimal in younger patient populations. The present study examined this issue in typically developing (TD) children as well as in children with ASD, using source localization to directly assess activity in the principal generators of the 40-Hz ASSR in the left and right primary/secondary auditory cortices. METHODS 40-Hz amplitude-modulated tones of 1 s duration were binaurally presented while magnetoencephalography data were obtained from 48 TD children (45 males; 7-14 years old) and 42 ASD children (38 males; 8-14 years old). T1-weighted structural MRI was obtained. Using single dipoles anatomically constrained to each participant's left and right Heschl's Gyrus, left and right 40-Hz ASSR total power (TP) and intertrial coherence (ITC) measures were obtained. Associations between 40-Hz ASSR TP, ITC and age as well as STG gray matter cortical thickness (CT) were assessed. Group STG function and structure differences were also examined. RESULTS TD and ASD did not differ in 40-Hz ASSR TP or ITC. In TD and ASD, age was associated with left and right 40-Hz ASSR ITC (p < 0.01). The interaction term was not significant, indicating in both groups a ∼0.01/year increase in ITC. 40-Hz ASSR TP and ITC were greater in the right than left STG. Groups did not differ in STG CT, and no associations were observed between 40-Hz ASSR activity and STG CT. Finally, right STG transient x03B3; (50-100 ms and 30-50 Hz) was greater in TD versus ASD (significant for TP, trend for ITC). CONCLUSIONS The 40-Hz ASSR develops, in part, via an age-related increase in neural synchrony. Greater right than left 40-Hz ASSRs (ITC and TP) suggested earlier maturation of right versus left STG neural network(s). Given a ∼0.01/year increase in ITC, 40-Hz ASSRs were weak or absent in many of the younger participants, suggesting that 40-Hz driving stimuli are not optimal for examining STG 40-Hz auditory neural circuits in younger populations. Given the caveat that 40-Hz auditory steady-state neural networks are poorly assessed in children, the present analyses did not point to atypical development of STG 40-Hz ASSRs in higher-functioning children with ASD. Although groups did not differ in 40-Hz auditory steady-state activity, replicating previous studies, there was evidence for greater right STG transient x03B3; activity in TD versus ASD.
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Affiliation(s)
- J Christopher Edgar
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa., USA
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Muthukumaraswamy SD. The use of magnetoencephalography in the study of psychopharmacology (pharmaco-MEG). J Psychopharmacol 2014; 28:815-29. [PMID: 24920134 DOI: 10.1177/0269881114536790] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Magnetoencephalography (MEG) is a neuroimaging technique that allows direct measurement of the magnetic fields generated by synchronised ionic neural currents in the brain with moderately good spatial resolution and high temporal resolution. Because chemical neuromodulation can cause changes in neuronal processing on the millisecond time-scale, the combination of MEG with pharmacological interventions (pharmaco-MEG) is a powerful tool for measuring the effects of experimental modulations of neurotransmission in the living human brain. Importantly, pharmaco-MEG can be used in both healthy humans to understand normal brain function and in patients to understand brain pathologies and drug-treatment effects. In this paper, the physiological and technical basis of pharmaco-MEG is introduced and contrasted with other pharmacological neuroimaging techniques. Ongoing developments in MEG analysis techniques such as source-localisation, functional and effective connectivity analyses, which have allowed for more powerful inferences to be made with recent pharmaco-MEG data, are described. Studies which have utilised pharmaco-MEG across a range of neurotransmitter systems (GABA, glutamate, acetylcholine, dopamine and serotonin) are reviewed.
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