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Hasegawa C, Ikeda T, Yoshimura Y, Kumazaki H, Saito DN, Yaoi K, An K, Takahashi T, Hirata M, Asada M, Kikuchi M. Reduced gamma oscillation during visual processing of the mother's face in children with autism spectrum disorder: A pilot study. PCN REPORTS : PSYCHIATRY AND CLINICAL NEUROSCIENCES 2023; 2:e68. [PMID: 38868414 PMCID: PMC11114405 DOI: 10.1002/pcn5.68] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 11/28/2022] [Accepted: 12/13/2022] [Indexed: 06/14/2024]
Abstract
Aim This study aimed to investigate gamma oscillations related to face processing of children with autism spectrum disorders and typically developed children using magnetoencephalography. Methods We developed stimuli that included naturalistic real-time eye-gaze situations between participants and their mothers. Eighteen young children with autism spectrum disorders (62-97 months) and 24 typically developed children (61-79 months) were included. The magnetoencephalography data were analyzed in the bilateral banks of the superior temporal sulcus, fusiform gyrus, and pericalcarine cortex for frequency ranges 30-59 and 61-90 Hz. The gamma oscillation normalized values were calculated to compare the face condition (children gazing at mother's face) and control measurements (baseline) using the following formula: (face - control)/(face + control). Results The results revealed significant differences in gamma oscillation normalized values in the low gamma band (30-59 Hz) in the right banks of the superior temporal sulcus, right fusiform gyrus, and right pericalcarine cortex between children with autism spectrum disorders and typically developed children. Furthermore, there were significant differences in gamma oscillation normalized values in the high gamma band (61-90 Hz) in the right banks of the superior temporal sulcus, bilateral fusiform gyrus, and bilateral pericalcarine cortex between the groups. Conclusion This report is the first magnetoencephalography study revealing atypical face processing in young children with autism spectrum disorders using relevant stimuli between participants and their mothers. Our naturalistic paradigm provides a useful assessment of social communication traits and a valuable insight into the underlying neural mechanisms in children with autism spectrum disorders.
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Affiliation(s)
- Chiaki Hasegawa
- Research Center for Child Mental DevelopmentKanazawa UniversityKanazawaJapan
- Japan Society for the Promotion of ScienceChiyoda‐kuTokyoJapan
- School of Psychological SciencesMacquarie UniversitySydneyAustralia
| | - Takashi Ikeda
- Research Center for Child Mental DevelopmentKanazawa UniversityKanazawaJapan
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of MedicineChiba University, and University of FukuiOsaka/Kanazawa/Hamamatsu/Chiba/FukuiJapan
- University of FukuiFukuiJapan
| | - Yuko Yoshimura
- Research Center for Child Mental DevelopmentKanazawa UniversityKanazawaJapan
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of MedicineChiba University, and University of FukuiOsaka/Kanazawa/Hamamatsu/Chiba/FukuiJapan
- Institute of Human and Social SciencesKanazawa UniversityKanazawaJapan
| | - Hirokazu Kumazaki
- Department of Future Psychiatric Medicine, Graduate School of Biomedical SciencesNagasaki UniversityNagasakiJapan
| | - Daisuke N. Saito
- Research Center for Child Mental DevelopmentKanazawa UniversityKanazawaJapan
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of MedicineChiba University, and University of FukuiOsaka/Kanazawa/Hamamatsu/Chiba/FukuiJapan
- Department of Psychology, Faculty of PsychologyYasuda Woman's UniversityHiroshimaJapan
| | - Ken Yaoi
- Research Center for Child Mental DevelopmentKanazawa UniversityKanazawaJapan
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of MedicineChiba University, and University of FukuiOsaka/Kanazawa/Hamamatsu/Chiba/FukuiJapan
| | - Kyung‐Min An
- Research Center for Child Mental DevelopmentKanazawa UniversityKanazawaJapan
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of MedicineChiba University, and University of FukuiOsaka/Kanazawa/Hamamatsu/Chiba/FukuiJapan
- School of PsychologyUniversity of BirminghamBirminghamUK
- Centre for Human Brain Health, School of PsychologyUniversity of BirminghamBirminghamUK
| | - Tetsuya Takahashi
- Research Center for Child Mental DevelopmentKanazawa UniversityKanazawaJapan
- Uozu Shinkei SanatoriumUozuJapan
- Department of NeuropsychiatryUniversity of FukuiFukuiJapan
| | - Masayuki Hirata
- Department of Neurological Diagnosis and Restoration, Graduate School of MedicineOsaka UniversitySuitaJapan
- Department of Neurosurgery Osaka University Medical SchoolSuitaJapan
- Center for Information and Neural NetworksNational Institute of Information and Communications TechnologySuitaJapan
- Open and Transdisciplinary Research Initiatives, Symbiotic Intelligent System Research CenterOsaka UniversitySuitaJapan
| | - Minoru Asada
- Center for Information and Neural NetworksNational Institute of Information and Communications TechnologySuitaJapan
- Open and Transdisciplinary Research Initiatives, Symbiotic Intelligent System Research CenterOsaka UniversitySuitaJapan
- International Professional University of Technology in OsakaOsakaJapan
- Chubu University Academy of Emerging SciencesKasugaiJapan
| | - Mitsuru Kikuchi
- Research Center for Child Mental DevelopmentKanazawa UniversityKanazawaJapan
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of MedicineChiba University, and University of FukuiOsaka/Kanazawa/Hamamatsu/Chiba/FukuiJapan
- Department of Psychiatry and NeurobiologyKanazawa UniversityKanazawaJapan
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Fred AL, Kumar SN, Kumar Haridhas A, Ghosh S, Purushothaman Bhuvana H, Sim WKJ, Vimalan V, Givo FAS, Jousmäki V, Padmanabhan P, Gulyás B. A Brief Introduction to Magnetoencephalography (MEG) and Its Clinical Applications. Brain Sci 2022; 12:788. [PMID: 35741673 PMCID: PMC9221302 DOI: 10.3390/brainsci12060788] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 06/01/2022] [Accepted: 06/08/2022] [Indexed: 11/30/2022] Open
Abstract
Magnetoencephalography (MEG) plays a pivotal role in the diagnosis of brain disorders. In this review, we have investigated potential MEG applications for analysing brain disorders. The signal-to-noise ratio (SNRMEG = 2.2 db, SNREEG < 1 db) and spatial resolution (SRMEG = 2−3 mm, SREEG = 7−10 mm) is higher for MEG than EEG, thus MEG potentially facilitates accurate monitoring of cortical activity. We found that the direct electrophysiological MEG signals reflected the physiological status of neurological disorders and play a vital role in disease diagnosis. Single-channel connectivity, as well as brain network analysis, using MEG data acquired during resting state and a given task has been used for the diagnosis of neurological disorders such as epilepsy, Alzheimer’s, Parkinsonism, autism, and schizophrenia. The workflow of MEG and its potential applications in the diagnosis of disease and therapeutic planning are also discussed. We forecast that computer-aided algorithms will play a prominent role in the diagnosis and prediction of neurological diseases in the future. The outcome of this narrative review will aid researchers to utilise MEG in diagnostics.
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Affiliation(s)
- Alfred Lenin Fred
- Department of CSE, Mar Ephraem College of Engineering and Technology, Marthandam 629171, Tamil Nadu, India; (A.L.F.); (F.A.S.G.)
| | | | - Ajay Kumar Haridhas
- Department of ECE, Mar Ephraem College of Engineering and Technology, Marthandam 629171, Tamil Nadu, India;
| | - Sayantan Ghosh
- Department of Integrative Biology, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India;
| | - Harishita Purushothaman Bhuvana
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
| | - Wei Khang Jeremy Sim
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
| | - Vijayaragavan Vimalan
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
| | - Fredin Arun Sedly Givo
- Department of CSE, Mar Ephraem College of Engineering and Technology, Marthandam 629171, Tamil Nadu, India; (A.L.F.); (F.A.S.G.)
| | - Veikko Jousmäki
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Aalto NeuroImaging, Department of Neuroscience and Biomedical Engineering, Aalto University, 12200 Espoo, Finland
| | - Parasuraman Padmanabhan
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
| | - Balázs Gulyás
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
- Department of Clinical Neuroscience, Karolinska Institute, 17176 Stockholm, Sweden
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3
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Lu CI, Greenwald M, Lin YY, Bowyer SM. Music, Math, and Working Memory: Magnetoencephalography Mapping of Brain Activation in Musicians. Front Hum Neurosci 2022; 16:866256. [PMID: 35652006 PMCID: PMC9150842 DOI: 10.3389/fnhum.2022.866256] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 03/25/2022] [Indexed: 11/13/2022] Open
Abstract
Musical transposing is highly demanding of working memory, as it involves mentally converting notes from one musical key (i.e., pitch scale) to another key for singing or instrumental performance. Because musical transposing involves mental adjustment of notes up or down by a specific amount, it may share cognitive elements with arithmetical operations of addition and subtraction. We compared brain activity during high and low working memory load conditions of musical transposing versus math calculations in classically trained musicians. Magnetoencephalography (MEG) was sensitive to differences of task and working memory load. Frontal-occipital connections were highly active during transposing, but not during math calculations. Right motor and premotor regions were highly active in the more difficult condition of the transposing task. Multiple frontal lobe regions were highly active across tasks, including the left medial frontal area during both transposing and calculation tasks but the right medial frontal area only during calculations. In the more difficult calculation condition, right temporal regions were highly active. In coherence analyses and neural synchrony analyses, several similarities were seen across calculation tasks; however, latency analyses were sensitive to differences in task complexity across the calculation tasks due to the high temporal resolution of MEG. MEG can be used to examine musical cognition and the neural consequences of music training. Further systematic study of brain activity during high versus low memory load conditions of music and other cognitive tasks is needed to illuminate the neural bases of enhanced working memory ability in musicians as compared to non-musicians.
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Affiliation(s)
- Ching-I Lu
- Department of Communication Sciences and Disorders, Wayne State University, Detroit, MI, United States
- *Correspondence: Ching-I Lu,
| | - Margaret Greenwald
- Department of Communication Sciences and Disorders, Wayne State University, Detroit, MI, United States
- Department of Neurology, Wayne State University, Detroit, MI, United States
| | - Yung-Yang Lin
- Institute of Brain Science and Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Critical Care Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
- Yung-Yang Lin,
| | - Susan M. Bowyer
- Department of Neurology, Wayne State University, Detroit, MI, United States
- Department of Neurology, Henry Ford Health System, Detroit, MI, United States
- Department of Physics, Oakland University, Rochester, MI, United States
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Khodatars M, Shoeibi A, Sadeghi D, Ghaasemi N, Jafari M, Moridian P, Khadem A, Alizadehsani R, Zare A, Kong Y, Khosravi A, Nahavandi S, Hussain S, Acharya UR, Berk M. Deep learning for neuroimaging-based diagnosis and rehabilitation of Autism Spectrum Disorder: A review. Comput Biol Med 2021; 139:104949. [PMID: 34737139 DOI: 10.1016/j.compbiomed.2021.104949] [Citation(s) in RCA: 80] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 10/02/2021] [Accepted: 10/13/2021] [Indexed: 01/23/2023]
Abstract
Accurate diagnosis of Autism Spectrum Disorder (ASD) followed by effective rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) techniques can aid physicians to apply automatic diagnosis and rehabilitation procedures. AI techniques comprise traditional machine learning (ML) approaches and deep learning (DL) techniques. Conventional ML methods employ various feature extraction and classification techniques, but in DL, the process of feature extraction and classification is accomplished intelligently and integrally. DL methods for diagnosis of ASD have been focused on neuroimaging-based approaches. Neuroimaging techniques are non-invasive disease markers potentially useful for ASD diagnosis. Structural and functional neuroimaging techniques provide physicians substantial information about the structure (anatomy and structural connectivity) and function (activity and functional connectivity) of the brain. Due to the intricate structure and function of the brain, proposing optimum procedures for ASD diagnosis with neuroimaging data without exploiting powerful AI techniques like DL may be challenging. In this paper, studies conducted with the aid of DL networks to distinguish ASD are investigated. Rehabilitation tools provided for supporting ASD patients utilizing DL networks are also assessed. Finally, we will present important challenges in the automated detection and rehabilitation of ASD and propose some future works.
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Affiliation(s)
- Marjane Khodatars
- Dept. of Medical Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran
| | - Afshin Shoeibi
- Faculty of Electrical Engineering, FPGA Lab, K. N. Toosi University of Technology, Tehran, Iran; Computer Engineering Department, Ferdowsi University of Mashhad, Mashhad, Iran.
| | - Delaram Sadeghi
- Dept. of Medical Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran
| | - Navid Ghaasemi
- Faculty of Electrical Engineering, FPGA Lab, K. N. Toosi University of Technology, Tehran, Iran; Computer Engineering Department, Ferdowsi University of Mashhad, Mashhad, Iran
| | - Mahboobeh Jafari
- Electrical and Computer Engineering Faculty, Semnan University, Semnan, Iran
| | - Parisa Moridian
- Faculty of Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Ali Khadem
- Department of Biomedical Engineering, Faculty of Electrical Engineering, K. N. Toosi University of Technology, Tehran, Iran.
| | - Roohallah Alizadehsani
- Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Victoria, 3217, Australia
| | - Assef Zare
- Faculty of Electrical Engineering, Gonabad Branch, Islamic Azad University, Gonabad, Iran
| | - Yinan Kong
- School of Engineering, Macquarie University, Sydney, 2109, Australia
| | - Abbas Khosravi
- Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Victoria, 3217, Australia
| | - Saeid Nahavandi
- Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Victoria, 3217, Australia
| | | | - U Rajendra Acharya
- Ngee Ann Polytechnic, Singapore, 599489, Singapore; Dept. of Biomedical Informatics and Medical Engineering, Asia University, Taichung, Taiwan; Dept. of Biomedical Engineering, School of Science and Technology, Singapore University of Social Sciences, Singapore
| | - Michael Berk
- Deakin University, IMPACT - the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Barwon Health, Geelong, Australia; Orygen, The National Centre of Excellence in Youth Mental Health, Centre for Youth Mental Health, Florey Institute for Neuroscience and Mental Health and the Department of Psychiatry, The University of Melbourne, Melbourne, Australia
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5
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McCrackin SD, Itier RJ. I can see it in your eyes: Perceived gaze direction impacts ERP and behavioural measures of affective theory of mind. Cortex 2021; 143:205-222. [PMID: 34455372 DOI: 10.1016/j.cortex.2021.05.024] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 04/12/2021] [Accepted: 05/21/2021] [Indexed: 10/20/2022]
Abstract
Looking at someone's eyes is thought to be important for affective theory of mind (aTOM), our ability to infer their emotional state. However, it is unknown whether an individual's gaze direction influences our aTOM judgements and what the time course of this influence might be. We presented participants with sentences describing individuals in positive, negative or neutral scenarios, followed by direct or averted gaze neutral face pictures of those individuals. Participants made aTOM judgements about each person's mental state, including their affective valence and arousal, and we investigated whether the face gaze direction impacted those judgements. Participants rated that gazers were feeling more positive when they displayed direct gaze as opposed to averted gaze, and that they were feeling more aroused during negative contexts when gaze was averted as opposed to direct. Event-related potentials associated with face perception and affective processing were examined using mass-univariate analyses to track the time-course of this eye-gaze and affective processing interaction at a neural level. Both positive and negative trials were differentiated from neutral trials at many stages of processing. This included the early N200 and EPN components, believed to reflect automatic emotion areas activation and attentional selection respectively. This also included the later P300 and LPP components, thought to reflect elaborative cognitive appraisal of emotional content. Critically, sentence valence and gaze direction interacted over these later components, which may reflect the incorporation of eye-gaze in the cognitive evaluation of another's emotional state. The results suggest that gaze perception directly impacts aTOM processes, and that altered eye-gaze processing in clinical populations may contribute to associated aTOM impairments.
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Affiliation(s)
| | - Roxane J Itier
- Department of Psychology, University of Waterloo, Waterloo, Canada.
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6
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Wang J, Wang X, Wang X, Zhang H, Zhou Y, Chen L, Li Y, Wu L. Increased EEG coherence in long-distance and short-distance connectivity in children with autism spectrum disorders. Brain Behav 2020; 10:e01796. [PMID: 32815287 PMCID: PMC7559606 DOI: 10.1002/brb3.1796] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 07/20/2020] [Accepted: 07/21/2020] [Indexed: 12/20/2022] Open
Abstract
INTRODUCTION Autism spectrum disorder (ASD) is a complex and prevalent neurodevelopmental disorder characterized by deficits in social communication and social interaction as well as repetitive behaviors. Alterations in function connectivity are widely recognized in recent electroencephalogram (EEG) studies. However, most studies have not reached consistent conclusions, which could be due to the developmental nature and the heterogeneity of ASD. METHODS Here, EEG coherence analysis was used in a cohort of children with ASD (n = 13) and matched typically developing controls (TD, n = 15) to examine the functional connectivity characteristics in long-distance and short-distance electrode pairs. Subsequently, we explore the association between the connectivity strength of coherence and symptom severity in children with ASD. RESULTS Compared with TD group, individuals with ASD showed increased coherence in short-distance electrode pairs in the right temporal-parietal region (delta, alpha, beta bands), left temporal-parietal region (all frequency bands), occipital region (theta, alpha, beta bands), right central-parietal region (delta, alpha, beta bands), and the prefrontal region (only beta band). In the long-distance coherence analysis, the ASD group showed increased coherence in bilateral frontal region, temporal region, parietal region, and frontal-occipital region in alpha and beta bands. The strength of such connections was associated with symptom severity. DISCUSSION Our study indicates that abnormal connectivity patterns in neuroelectrophysiology may be of critical importance to acknowledge the underlying brain mechanism.
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Affiliation(s)
- Jia Wang
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China
| | - Xiaomin Wang
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China
| | - Xuelai Wang
- Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huiying Zhang
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China
| | - Yong Zhou
- Heilongjiang Province Center for Disease Control and Prevention, Harbin, China
| | - Lei Chen
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China
| | - Yutong Li
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China
| | - Lijie Wu
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China
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Bulica B, Sidiropoulos C, Mahajan A, Zillgitt A, Kaminski P, Bowyer SM. Sensorimotor Integration and GABA-ergic Activity in Embouchure Dystonia: An Assessment with Magnetoencephalography. Tremor Other Hyperkinet Mov (N Y) 2019; 9:tre-09-709. [PMID: 31632836 PMCID: PMC6765227 DOI: 10.7916/tohm.v0.709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Accepted: 08/29/2019] [Indexed: 12/01/2022] Open
Abstract
Background Embouchure dystonia (ED) is a task-specific dystonia affecting musicians thought to be related to alteration in sensorimotor processing and loss of cortical inhibition. Case Report Magnetoencephalography-coherence source imaging (MEG-CSI) was used to map connectivity between brain regions by imaging neuronal oscillations that are coherent across the brain in patient with ED at rest and while using the index finger to evoke dystonia normally triggered by playing the flute. Discussion During rest, there was increased coherence in the bilateral frontal and parietal regions that became more focal during dystonia. Diffuse hyperexcitability and increased coherence persisted in bilateral parietal regions as well as the bilateral frontal regions.
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Affiliation(s)
- Bisena Bulica
- Department of Neurology, Henry Ford Hospital, Detroit, MI, USA,To whom correspondence should be addressed. E-mail:
| | - Christos Sidiropoulos
- Department of Neurology and Ophthalmology, Michigan State University, East Lansing, MI, USA
| | - Abhimanyu Mahajan
- Division of Movement Disorders, Department of Neurology, University of Cincinnati, Cincinnati, OH, USA
| | - Andrew Zillgitt
- Department of Neurology, Beaumont Neuroscience Center, Royal Oak, MI, USA
| | | | - Susan M. Bowyer
- Department of Neurology, Henry Ford Hospital, Detroit, MI, USA
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Lajiness-O'Neill R, Brennan JR, Moran JE, Richard AE, Flores AM, Swick C, Goodcase R, Andersen T, McFarlane K, Rusiniak K, Kovelman I, Wagley N, Ugolini M, Albright J, Bowyer SM. Patterns of altered neural synchrony in the default mode network in autism spectrum disorder revealed with magnetoencephalography (MEG): Relationship to clinical symptomatology. Autism Res 2017; 11:434-449. [PMID: 29251830 DOI: 10.1002/aur.1908] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Revised: 11/05/2017] [Accepted: 11/28/2017] [Indexed: 01/02/2023]
Abstract
Disrupted neural synchrony may be a primary electrophysiological abnormality in autism spectrum disorders (ASD), altering communication between discrete brain regions and contributing to abnormalities in patterns of connectivity within identified neural networks. Studies exploring brain dynamics to comprehensively characterize and link connectivity to large-scale cortical networks and clinical symptoms are lagging considerably. Patterns of neural coherence within the Default Mode Network (DMN) and Salience Network (SN) during resting state were investigated in 12 children with ASD (MAge = 9.2) and 13 age and gender-matched neurotypicals (NT) (MAge = 9.3) with magnetoencephalography. Coherence between 231 brain region pairs within four frequency bands (theta (4-7 Hz), alpha, (8-12 Hz), beta (13-30 Hz), and gamma (30-80 Hz)) was calculated. Relationships between neural coherence and social functioning were examined. ASD was characterized by lower synchronization across all frequencies, reaching clinical significance in the gamma band. Lower gamma synchrony between fronto-temporo-parietal regions was observed, partially consistent with diminished default mode network (DMN) connectivity. Lower gamma coherence in ASD was evident in cross-hemispheric connections between: angular with inferior/middle frontal; middle temporal with middle/inferior frontal; and within right-hemispheric connections between angular, middle temporal, and inferior/middle frontal cortices. Lower gamma coherence between left angular and left superior frontal, right inferior/middle frontal, and right precuneus and between right angular and inferior/middle frontal cortices was related to lower social/social-communication functioning. Results suggest a pattern of lower gamma band coherence in a subset of regions within the DMN in ASD (angular and middle temporal cortical areas) related to lower social/social-communicative functioning. Autism Res 2018, 11: 434-449. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY Communication between different areas of the brain was observed in children with ASD and neurotypical children while awake, but not working on a task. Magnetoencephalography was used to measure tiny magnetic fields naturally generated via brain activity. The brains of children with ASD showed less communication between areas that are important for social information processing compared to the brains of neurotypical children. The amount of communication between these areas was associated with social and social communication difficulties.
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Affiliation(s)
- Renée Lajiness-O'Neill
- Eastern Michigan University, Ypsilanti, Michigan.,Center for Human Growth and Development, University of Michigan, Ann Arbor, Michigan
| | | | | | | | | | - Casey Swick
- Eastern Michigan University, Ypsilanti, Michigan
| | | | | | | | | | - Ioulia Kovelman
- Center for Human Growth and Development, University of Michigan, Ann Arbor, Michigan.,Department of Psychology, Ann Arbor, Michigan
| | - Neelima Wagley
- Center for Human Growth and Development, University of Michigan, Ann Arbor, Michigan.,Department of Psychology, Ann Arbor, Michigan
| | | | | | - Susan M Bowyer
- University of Massachusetts, Amherst, Massachusetts.,Wayne State University, Detroit, Michigan.,Oakland University, Rochester, Michigan
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9
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Atypical Processing of Gaze Cues and Faces Explains Comorbidity between Autism Spectrum Disorder (ASD) and Attention Deficit/Hyperactivity Disorder (ADHD). J Autism Dev Disord 2017; 47:1496-1509. [PMID: 28255758 PMCID: PMC5385202 DOI: 10.1007/s10803-017-3078-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
This study investigated the neurobiological basis of comorbidity between autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD). We compared children with ASD, ADHD or ADHD+ASD and typically developing controls (CTRL) on behavioural and electrophysiological correlates of gaze cue and face processing. We measured effects of ASD, ADHD and their interaction on the EDAN, an ERP marker of orienting visual attention towards a spatially cued location and the N170, a right-hemisphere lateralised ERP linked to face processing. We identified atypical gaze cue and face processing in children with ASD and ADHD+ASD compared with the ADHD and CTRL groups. The findings indicate a neurobiological basis for the presence of comorbid ASD symptoms in ADHD. Further research using larger samples is needed.
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10
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O’Reilly C, Lewis JD, Elsabbagh M. Is functional brain connectivity atypical in autism? A systematic review of EEG and MEG studies. PLoS One 2017; 12:e0175870. [PMID: 28467487 PMCID: PMC5414938 DOI: 10.1371/journal.pone.0175870] [Citation(s) in RCA: 176] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2016] [Accepted: 03/31/2017] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Although it is well recognized that autism is associated with altered patterns of over- and under-connectivity, specifics are still a matter of debate. Little has been done so far to synthesize available literature using whole-brain electroencephalography (EEG) and magnetoencephalography (MEG) recordings. OBJECTIVES 1) To systematically review the literature on EEG/MEG functional and effective connectivity in autism spectrum disorder (ASD), 2) to synthesize and critically appraise findings related with the hypothesis that ASD is characterized by long-range underconnectivity and local overconnectivity, and 3) to provide, based on the literature, an analysis of tentative factors that are likely to mediate association between ASD and atypical connectivity (e.g., development, topography, lateralization). METHODS Literature reviews were done using PubMed and PsychInfo databases. Abstracts were screened, and only relevant articles were analyzed based on the objectives of this paper. Special attention was paid to the methodological characteristics that could have created variability in outcomes reported between studies. RESULTS Our synthesis provides relatively strong support for long-range underconnectivity in ASD, whereas the status of local connectivity remains unclear. This observation was also mirrored by a similar relationship with lower frequencies being often associated with underconnectivity and higher frequencies being associated with both under- and over-connectivity. Putting together these observations, we propose that ASD is characterized by a general trend toward an under-expression of lower-band wide-spread integrative processes compensated by more focal, higher-frequency, locally specialized, and segregated processes. Further investigation is, however, needed to corroborate the conclusion and its generalizability across different tasks. Of note, abnormal lateralization in ASD, specifically an elevated left-over-right EEG and MEG functional connectivity ratio, has been also reported consistently across studies. CONCLUSIONS The large variability in study samples and methodology makes a systematic quantitative analysis (i.e. meta-analysis) of this body of research impossible. Nevertheless, a general trend supporting the hypothesis of long-range functional underconnectivity can be observed. Further research is necessary to more confidently determine the status of the hypothesis of short-range overconnectivity. Frequency-band specific patterns and their relationships with known symptoms of autism also need to be further clarified.
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Affiliation(s)
- Christian O’Reilly
- Douglas Mental Health University Institute, 6875 Boulevard Lasalle, Verdun, Canada
- Department of Psychiatry, McGill University, 1033 Pine Avenue West, Montreal, QC, Canada
| | - John D. Lewis
- McGill Center for Integrative Neuroscience, Montreal Neurological Institute, McGill University, 3801 University Street, Montréal, QC, Canada
| | - Mayada Elsabbagh
- Douglas Mental Health University Institute, 6875 Boulevard Lasalle, Verdun, Canada
- Department of Psychiatry, McGill University, 1033 Pine Avenue West, Montreal, QC, Canada
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Rapid and Objective Assessment of Neural Function in Autism Spectrum Disorder Using Transient Visual Evoked Potentials. PLoS One 2016; 11:e0164422. [PMID: 27716799 PMCID: PMC5055293 DOI: 10.1371/journal.pone.0164422] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Accepted: 09/23/2016] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVE There is a critical need to identify biomarkers and objective outcome measures that can be used to understand underlying neural mechanisms in autism spectrum disorder (ASD). Visual evoked potentials (VEPs) offer a noninvasive technique to evaluate the functional integrity of neural mechanisms, specifically visual pathways, while probing for disease pathophysiology. METHODS Transient VEPs (tVEPs) were obtained from 96 unmedicated children, including 37 children with ASD, 36 typically developing (TD) children, and 23 unaffected siblings (SIBS). A conventional contrast-reversing checkerboard condition was compared to a novel short-duration condition, which was developed to enable objective data collection from severely affected populations who are often excluded from electroencephalographic (EEG) studies. RESULTS Children with ASD showed significantly smaller amplitudes compared to TD children at two of the earliest critical VEP components, P60-N75 and N75-P100. SIBS showed intermediate responses relative to ASD and TD groups. There were no group differences in response latency. Frequency band analyses indicated significantly weaker responses for the ASD group in bands encompassing gamma-wave activity. Ninety-two percent of children with ASD were able to complete the short-duration condition compared to 68% for the standard condition. CONCLUSIONS The current study establishes the utility of a short-duration tVEP test for use in children at varying levels of functioning and describes neural abnormalities in children with idiopathic ASD. Implications for excitatory/inhibitory balance as well as the potential application of VEP for use in clinical trials are discussed.
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