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Qian S, Yang Q, Cai C, Dong J, Cai S. Spatial-Temporal Characteristics of Brain Activity in Autism Spectrum Disorder Based on Hidden Markov Model and Dynamic Graph Theory: A Resting-State fMRI Study. Brain Sci 2024; 14:507. [PMID: 38790485 PMCID: PMC11118919 DOI: 10.3390/brainsci14050507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Revised: 05/13/2024] [Accepted: 05/14/2024] [Indexed: 05/26/2024] Open
Abstract
Autism spectrum disorder (ASD) is a common neurodevelopmental disorder. Functional magnetic resonance imaging (fMRI) can be used to measure the temporal correlation of blood-oxygen-level-dependent (BOLD) signals in the brain to assess the brain's intrinsic connectivity and capture dynamic changes in the brain. In this study, the hidden Markov model (HMM) and dynamic graph (DG) theory are used to study the spatial-temporal characteristics and dynamics of brain networks based on dynamic functional connectivity (DFC). By using HMM, we identified three typical brain states for ASD and healthy control (HC). Furthermore, we explored the correlation between HMM time-varying properties and clinical autism scale scores. Differences in brain topological characteristics and dynamics between ASD and HC were compared by DG analysis. The experimental results indicate that ASD is more inclined to enter a strongly connected HMM brain state, leading to the isolation of brain networks and alterations in the topological characteristics of brain networks, such as default mode network (DMN), ventral attention network (VAN), and visual network (VN). This work suggests that using different data-driven methods based on DFC to study brain network dynamics would have better information complementarity, which can provide a new direction for the extraction of neuro-biomarkers in the early diagnosis of ASD.
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Affiliation(s)
| | | | | | | | - Shuhui Cai
- Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Department of Electronic Science, Xiamen University, Xiamen 361005, China; (S.Q.); (Q.Y.); (C.C.); (J.D.)
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2
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Jia H, Wu X, Zhang X, Guo M, Yang C, Wang E. Resting-state EEG Microstate Features Can Quantitatively Predict Autistic Traits in Typically Developing Individuals. Brain Topogr 2024; 37:410-419. [PMID: 37833486 DOI: 10.1007/s10548-023-01010-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Accepted: 09/20/2023] [Indexed: 10/15/2023]
Abstract
Autism spectrum disorder (ASD) is not a discrete disorder and that symptoms of ASD (i.e., so-called "autistic traits") are found to varying degrees in the general population. Typically developing individuals with sub-clinical yet high-level autistic traits have similar abnormities both in behavioral performances and cortical activation patterns to individuals diagnosed with ASD. Thus it's crucial to develop objective and efficient tools that could be used in the assessment of autistic traits. Here, we proposed a novel machine learning-based assessment of the autistic traits using EEG microstate features derived from a brief resting-state EEG recording. The results showed that: (1) through the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and correlation analysis, the mean duration of microstate class D, the occurrence rate of microstate class A, the time coverage of microstate class D and the transition rate from microstate class B to D were selected to be crucial microstate features which could be used in autistic traits prediction; (2) in the support vector regression (SVR) model, which was constructed to predict the participants' autistic trait scores using these four microstate features, the out-of-sample predicted autistic trait scores showed a significant and good match with the self-reported scores. These results suggest that the resting-state EEG microstate analysis technique can be used to predict autistic trait to some extent.
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Affiliation(s)
- Huibin Jia
- Institute of Psychology and Behavior, Henan University, Kaifeng, 475004, China
- School of Psychology, Henan University, Kaifeng, 475004, China
| | - Xiangci Wu
- Institute of Psychology and Behavior, Henan University, Kaifeng, 475004, China
- School of Psychology, Henan University, Kaifeng, 475004, China
| | - Xiaolin Zhang
- Institute of Psychology and Behavior, Henan University, Kaifeng, 475004, China
- School of Psychology, Henan University, Kaifeng, 475004, China
| | - Meiling Guo
- Institute of Psychology and Behavior, Henan University, Kaifeng, 475004, China
- School of Psychology, Henan University, Kaifeng, 475004, China
| | - Chunying Yang
- School of Special Education, Zhengzhou Normal University, Zhengzhou, 450000, China.
| | - Enguo Wang
- Institute of Psychology and Behavior, Henan University, Kaifeng, 475004, China.
- School of Psychology, Henan University, Kaifeng, 475004, China.
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3
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Takarae Y, Zanesco A, Erickson CA, Pedapati EV. EEG Microstates as Markers for Cognitive Impairments in Fragile X Syndrome. Brain Topogr 2024; 37:432-446. [PMID: 37751055 DOI: 10.1007/s10548-023-01009-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Accepted: 09/12/2023] [Indexed: 09/27/2023]
Abstract
Fragile X syndrome (FXS) is one of the most common inherited causes of intellectual disabilities. While there is currently no cure for FXS, EEG is considered an important method to investigate the pathophysiology and evaluate behavioral and cognitive treatments. We conducted EEG microstate analysis to investigate resting brain dynamics in FXS participants. Resting-state recordings from 70 FXS participants and 71 chronological age-matched typically developing control (TDC) participants were used to derive microstates via modified k-means clustering. The occurrence, mean global field power (GFP), and global explained variance (GEV) of microstate C were significantly higher in the FXS group compared to the TDC group. The mean GFP was significantly negatively correlated with non-verbal IQ (NVIQ) in the FXS group, where lower NVIQ scores were associated with greater GFP. In addition, the occurrence, mean duration, mean GFP, and GEV of microstate D were significantly greater in the FXS group than the TDC group. The mean GFP and occurrence of microstate D were also correlated with individual alpha frequencies in the FXS group, where lower IAF frequencies accompanied greater microstate GFP and occurrence. Alterations in microstates C and D may be related to the two well-established cognitive characteristics of FXS, intellectual disabilities and attention impairments, suggesting that microstate parameters could serve as markers to study cognitive impairments and evaluate treatment outcomes in this population. Slowing of the alpha peak frequency and its correlation to microstate D parameters may suggest changes in thalamocortical dynamics in FXS, which could be specifically related to attention control. (250 words).
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Affiliation(s)
- Yukari Takarae
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, Sacramento, CA, USA.
- M.I.N.D. Institute, University of California, Davis, Sacramento, CA, USA.
| | - Anthony Zanesco
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Craig A Erickson
- Division of Child and Adolescent Psychiatry, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Psychiatry, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Ernest V Pedapati
- Division of Child and Adolescent Psychiatry, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Psychiatry, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
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4
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Das S, Zomorrodi R, Kirkovski M, Hill AT, Enticott PG, Blumberger DM, Rajji TK, Desarkar P. Atypical alpha band microstates produced during eyes-closed resting state EEG in autism. Prog Neuropsychopharmacol Biol Psychiatry 2024; 131:110958. [PMID: 38309329 DOI: 10.1016/j.pnpbp.2024.110958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 01/30/2024] [Accepted: 01/31/2024] [Indexed: 02/05/2024]
Abstract
Electroencephalogram (EEG) microstates, which represent quasi-stable patterns of scalp topography, are a promising tool that has the temporal resolution to study atypical spatial and temporal networks in autism spectrum disorder (ASD). While current literature suggests microstates are atypical in ASD, their clinical utility, i.e., relationship with the core behavioural characteristics of ASD, is not fully understood. The aim of this study was to examine microstate parameters in ASD, and examine the relationship between these parameters and core behavioural characteristics in ASD. We compared duration, occurrence, coverage, global explained variance percentage, global field power and spatial correlation of EEG microstates between autistic and neurotypical (NT) adults. Modified k-means cluster analysis was used on eyes-closed, resting state EEG from 30 ASD (10 females, 28.97 ± 9.34 years) and 30 age-equated NT (13 females, 29.33 ± 8.88 years) adults. Five optimal microstates, A to E, were selected to best represent the data. Five microstate maps explaining 80.44% of the NT and 78.44% of the ASD data were found. The ASD group was found to have atypical parameters of microstate A, C, D, and E. Of note, all parameters of microstate C in the ASD group were found to be significantly less than NT. While parameters of microstate D, and E were also found to significantly correlate with subscales of the Ritvo Autism Asperger Diagnostic Scale - Revised (RAADS-R), these findings did not survive a Bonferroni Correction. These findings, in combination with previous findings, highlight the potential clinical utility of EEG microstates and indicate their potential value as a neurophysiologic marker that can be further studied.
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Affiliation(s)
- Sushmit Das
- Centre for Addiction and Mental Health, Toronto, Canada; Azrieli Adult Neurodevelopmental Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Reza Zomorrodi
- Centre for Addiction and Mental Health, Toronto, Canada; Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Melissa Kirkovski
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia; Institute for Health and Sport, Victoria University, Melbourne, Australia
| | - Aron T Hill
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia; Department of Psychiatry, Central Clinical School, Monash University, Melbourne, Australia
| | - Peter G Enticott
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia
| | - Daniel M Blumberger
- Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Tarek K Rajji
- Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada; Toronto Dementia Research Alliance, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Pushpal Desarkar
- Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Azrieli Adult Neurodevelopmental Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada; Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.
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5
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Zanesco AP. Normative Temporal Dynamics of Resting EEG Microstates. Brain Topogr 2024; 37:243-264. [PMID: 37702825 DOI: 10.1007/s10548-023-01004-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 08/23/2023] [Indexed: 09/14/2023]
Abstract
The large-scale electrophysiological events known as electroencephalographic microstates provide an important window into the intrinsic activity of whole-brain neuronal networks. The spontaneous activity of coordinated brain networks, including the ongoing temporal dynamics expressed by microstates, are thought to reflect individuals' neurocognitive functioning, and predict development, disease progression, and psychological differences among varied populations. A comprehensive understanding of human brain function therefore requires characterizing typical and atypical patterns in the temporal dynamics of microstates. But population-level estimates of normative microstate temporal dynamics are still unknown. To address this gap, I conducted a systematic search of the literature and accompanying meta-analysis of the average dynamics of microstates obtained from studies investigating spontaneous brain activity in individuals during periods of eyes-closed and eyes-open rest. Meta-analyses provided estimates of the average temporal dynamics of microstates across 93 studies totaling 6583 unique individual participants drawn from diverse populations. Results quantified the expected range of plausible estimates of average microstate dynamics across study samples, as well as characterized heterogeneity resulting from sampling variability and systematic differences in development, clinical diagnoses, or other study methodological factors. Specifically, microstate dynamics significantly differed for samples with specific developmental differences or clinical diagnoses, relative to healthy, typically developing samples. This research supports the notion that microstates and their dynamics reflect functionally relevant properties of large-scale brain networks, encoding typical and atypical neurocognitive functioning.
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Affiliation(s)
- Anthony P Zanesco
- Department of Psychology, University of Miami, Coral Gables, FL, USA.
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6
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Brown KL, Gartstein MA. Microstate analysis in infancy. Infant Behav Dev 2023; 70:101785. [PMID: 36423552 DOI: 10.1016/j.infbeh.2022.101785] [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: 03/02/2022] [Revised: 10/22/2022] [Accepted: 11/02/2022] [Indexed: 11/22/2022]
Abstract
BACKGROUND Microstate analysis is an emerging method for investigating global brain connections using electroencephalography (EEG). Microstates have been colloquially referred to as the "atom of thought," meaning that from these underlying networks comes coordinated neural processing and cognition. The present study examined microstates at 6-, 8-, and 10-months of age. It was hypothesized that infants would demonstrate distinct microstates comparable to those identified in adults that also parallel resting-state networks using fMRI. An additional exploratory aim was to examine the relationship between microstates and temperament, assessed via parent reports, to further demonstrate microstate analysis as a viable tool for examining the relationship between neural networks, cognitive processes as well as emotional expression embodied in temperament attributes. METHODS The microstates analysis was performed with infant EEG data when the infant was either 6- (n = 12), 8- (n = 16), or 10-months (n = 6) old. The resting-state task involved watching a 1-minute video segment of Baby Einstein while listening to the accompanying music. Parents completed the IBQ-R to assess infant temperament. RESULTS Four microstate topographies were extracted. Microstate 1 had an isolated posterior activation; Microstate 2 had a symmetric occipital to prefrontal orientation; Microstate 3 had a left occipital to right frontal orientation; and Microstate 4 had a right occipital to left frontal orientation. At 10-months old, Microstate 3, thought to reflect auditory/language processing, became activated more often, for longer periods of time, covering significantly more time across the task and was more likely to be transitioned into. This finding is interpreted as consistent with language acquisition and phonological processing that emerges around 10-months. Microstate topographies and parameters were also correlated with differing temperament broadband and narrowband scales on the IBQ-R. CONCLUSION Three microstates emerged that appear comparable to underlying networks identified in adult and infant microstate literature and fMRI studies. Each of the temperament domains was related to specific microstates and their parameters. These networks also correspond with auditory and visual processing as well as the default mode network found in prior research and can lead to new investigations examining differences across stimulus presentations to further explain how infants begin to recognize, respond to, and engage with the world around them.
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Affiliation(s)
- Kara L Brown
- Department of Psychology, Washington State University, USA.
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7
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Kang J, Fan X, Zhong Y, Casanova MF, Sokhadze EM, Li X, Niu Z, Geng X. Transcranial Direct Current Stimulation Modulates EEG Microstates in Low-Functioning Autism: A Pilot Study. BIOENGINEERING (BASEL, SWITZERLAND) 2023; 10:bioengineering10010098. [PMID: 36671670 PMCID: PMC9855011 DOI: 10.3390/bioengineering10010098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Revised: 12/28/2022] [Accepted: 01/08/2023] [Indexed: 01/13/2023]
Abstract
Autism spectrum disorder (ASD) is a heterogeneous disorder that affects several behavioral domains of neurodevelopment. Transcranial direct current stimulation (tDCS) is a new method that modulates motor and cognitive function and may have potential applications in ASD treatment. To identify its potential effects on ASD, differences in electroencephalogram (EEG) microstates were compared between children with typical development (n = 26) and those with ASD (n = 26). Furthermore, children with ASD were divided into a tDCS (experimental) and sham stimulation (control) group, and EEG microstates and Autism Behavior Checklist (ABC) scores before and after tDCS were compared. Microstates A, B, and D differed significantly between children with TD and those with ASD. In the experimental group, the scores of microstates A and C and ABC before tDCS differed from those after tDCS. Conversely, in the control group, neither the EEG microstates nor the ABC scores before the treatment period (sham stimulation) differed from those after the treatment period. This study indicates that tDCS may become a viable treatment for ASD.
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Affiliation(s)
- Jiannan Kang
- College of Electronic & Information Engineering, Hebei University, Baoding 071000, China
| | - Xiwang Fan
- Clinical Research Center for Mental Disorders, Shanghai Pudong New Area Mental Health Center, School of Medicine, Tongji University, Shanghai 200124, China
| | - Yiwen Zhong
- Clinical Research Center for Mental Disorders, Shanghai Pudong New Area Mental Health Center, School of Medicine, Tongji University, Shanghai 200124, China
| | - Manuel F. Casanova
- Department of Biomedical Sciences, University of South Carolina School of Medicine Greenville Campus, Greenville Health System, Greenville, SC 29605, USA
| | - Estate M. Sokhadze
- Department of Biomedical Sciences, University of South Carolina School of Medicine Greenville Campus, Greenville Health System, Greenville, SC 29605, USA
| | - Xiaoli Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100859, China
| | - Zikang Niu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100859, China
- Correspondence: (Z.N.); (X.G.)
| | - Xinling Geng
- School of Biomedical Engineering, Capital Medical University, Beijing 100069, China
- Correspondence: (Z.N.); (X.G.)
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8
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Intellectually able adults with autism spectrum disorder show typical resting-state EEG activity. Sci Rep 2022; 12:19016. [PMID: 36347938 PMCID: PMC9643446 DOI: 10.1038/s41598-022-22597-z] [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: 07/20/2022] [Accepted: 10/17/2022] [Indexed: 11/11/2022] Open
Abstract
There is broad interest in discovering quantifiable physiological biomarkers for psychiatric disorders to aid diagnostic assessment. However, finding biomarkers for autism spectrum disorder (ASD) has proven particularly difficult, partly due to high heterogeneity. Here, we recorded five minutes eyes-closed rest electroencephalography (EEG) from 186 adults (51% with ASD and 49% without ASD) and investigated the potential of EEG biomarkers to classify ASD using three conventional machine learning models with two-layer cross-validation. Comprehensive characterization of spectral, temporal and spatial dimensions of source-modelled EEG resulted in 3443 biomarkers per recording. We found no significant group-mean or group-variance differences for any of the EEG features. Interestingly, we obtained validation accuracies above 80%; however, the best machine learning model merely distinguished ASD from the non-autistic comparison group with a mean balanced test accuracy of 56% on the entirely unseen test set. The large drop in model performance between validation and testing, stress the importance of rigorous model evaluation, and further highlights the high heterogeneity in ASD. Overall, the lack of significant differences and weak classification indicates that, at the group level, intellectually able adults with ASD show remarkably typical resting-state EEG.
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9
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Event-related microstate dynamics represents working memory performance. Neuroimage 2022; 263:119669. [PMID: 36206941 DOI: 10.1016/j.neuroimage.2022.119669] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 09/30/2022] [Accepted: 10/03/2022] [Indexed: 11/21/2022] Open
Abstract
In recent years, EEG microstate analysis has attracted much attention as a tool for characterizing the spatial and temporal dynamics of large-scale electrophysiological activities in the human brain. Canonical 4 states (classes A, B, C, and D) have been widely reported, and they have been pointed out for their relationships with cognitive functions and several psychiatric disorders such as schizophrenia, in particular, through their static parameters such as average duration, occurrence, coverage, and transition probability. However, the relationships between event-related microstate changes and their related cognitive functions, as is often analyzed in event-related potentials under time-locked frameworks, is still not well understood. Furthermore, not enough attention has been paid to the relationship between microstate dynamics and static characteristics. To clarify the relationships between the static microstate parameters and dynamic microstate changes, and between the dynamics and working memory (WM) function, we first examined the temporal profiles of the microstates during the N-back task. We found significant event-related microstate dynamics that differed predominantly with WM loads, which were not clearly observed in the static parameters. Furthermore, in the 2-back condition, patterns of state transitions from class A to C in the high- and low-performance groups showed prominent differences at 50-300 ms after stimulus onset. We also confirmed that the transition patterns of the specific time periods were able to predict the performance level (low or high) in the 2-back condition at a significant level, where a specific transition between microstates, namely from class A to C with specific polarity, contributed to the prediction robustly. Taken together, our findings indicate that event-related microstate dynamics at 50-300 ms after onset may be essential for WM function. This suggests that event-related microstate dynamics can reflect more highly-refined brain functions.
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10
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The pro-inflammatory factors contribute to the EEG microstate abnormalities in patients with major depressive disorder. Brain Behav Immun Health 2022; 26:100523. [PMID: 36267834 PMCID: PMC9576533 DOI: 10.1016/j.bbih.2022.100523] [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: 05/28/2022] [Revised: 09/19/2022] [Accepted: 09/25/2022] [Indexed: 11/22/2022] Open
Abstract
Pro-inflammatory factors may be associated with abnormalities in functional brain networks, which may be a mechanism in the pathogenesis of major depressive disorder (MDD). Electroencephalogram (EEG) microstates reflect the functioning of brain networks. However, the relationship between pro-inflammatory factors and the microstate abnormalities in patients with MDD is poorly understood. 24 MDD patients and 24 age-and sex-matched healthy controls (HC) were recruited. Montgomery-Asberg Depression Rating Scale(MADRS) were assessed. Serum (interleukin- 2(IL- 2), tumor necrosis factor-α (TNF-α) and hs-C-reactive protein (CRP)and EEG data were collected. K-means clustering was performed to characterize different microstates. For each microstate, duration, occurrence and coverage were estimated. Four microstates (e.g. A, B, C, D) were characterized, MDD group showed lower duration, occurrence and coverage of microstate B and microstate D, while higher duration of microstate A and microstate C and levels of IL-2, TNF-α, hs-CRP than HC group. The duration, occurrence and coverage of microstate D were negatively correlated with levels of pro-inflammatory factors (IL-2, TNF- α and hs- CRP) (all P < 0.05). Serum pro-inflammatory induced the abnormalities of microstate D. Together, these findings add to the understanding of the pathophysiology of MDD and point to pro-inflammatory factors contribute to EEG microstate abnormalities in patients with MDD.
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Bagdasarov A, Roberts K, Bréchet L, Brunet D, Michel CM, Gaffrey MS. Spatiotemporal dynamics of EEG microstates in four- to eight-year-old children: Age- and sex-related effects. Dev Cogn Neurosci 2022; 57:101134. [PMID: 35863172 PMCID: PMC9301511 DOI: 10.1016/j.dcn.2022.101134] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 06/13/2022] [Accepted: 07/08/2022] [Indexed: 11/22/2022] Open
Abstract
The ultrafast spatiotemporal dynamics of large-scale neural networks can be examined using resting-state electroencephalography (EEG) microstates, representing transient periods of synchronized neural activity that evolve dynamically over time. In adults, four canonical microstates have been shown to explain most topographic variance in resting-state EEG. Their temporal structures are age-, sex- and state-dependent, and are susceptible to pathological brain states. However, no studies have assessed the spatial and temporal properties of EEG microstates exclusively during early childhood, a critical period of rapid brain development. Here we sought to investigate EEG microstates recorded with high-density EEG in a large sample of 103, 4-8-year-old children. Using data-driven k-means cluster analysis, we show that the four canonical microstates reported in adult populations already exist in early childhood. Using multiple linear regressions, we demonstrate that the temporal dynamics of two microstates are associated with age and sex. Source localization suggests that attention- and cognitive control-related networks govern the topographies of the age- and sex-dependent microstates. These novel findings provide unique insights into functional brain development in children captured with EEG microstates.
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Affiliation(s)
- Armen Bagdasarov
- Department of Psychology & Neuroscience, Duke University, Reuben-Cooke Building, 417 Chapel Drive, Durham, NC 27708, USA.
| | - Kenneth Roberts
- Duke Institute for Brain Sciences, Duke University, 308 Research Drive, Durham, NC, USA
| | - Lucie Bréchet
- Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland
| | - Denis Brunet
- Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland; Center for Biomedical Imaging (CIBM) Lausanne, EPFL AVP CP CIBM Station 6, 1015 Lausanne Switzerland
| | - Christoph M Michel
- Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland; Center for Biomedical Imaging (CIBM) Lausanne, EPFL AVP CP CIBM Station 6, 1015 Lausanne Switzerland
| | - Michael S Gaffrey
- Department of Psychology & Neuroscience, Duke University, Reuben-Cooke Building, 417 Chapel Drive, Durham, NC 27708, USA
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12
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EEG microstate temporal Dynamics Predict depressive symptoms in College Students. Brain Topogr 2022; 35:481-494. [PMID: 35790705 DOI: 10.1007/s10548-022-00905-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Accepted: 05/19/2022] [Indexed: 11/02/2022]
Abstract
Previous studies on resting-state electroencephalographic responses in patients with depressive disorders have identified electroencephalogram (EEG) parameters as potential biomarkers for the early detection and diagnosis of depressive disorders. However, these studies did not investigate the relationship between resting-state EEG microstates and the early detection of depressive symptoms in preclinical individuals. To explore the possible association between resting-state EEG microstate temporal dynamics and depressive symptoms among college students, EEG microstate analysis was performed on eyes-closed resting-state EEG data for approximately 5 min from 34 undergraduates with high intensity of depressive symptoms and 34 age- and sex-matched controls with low intensity of depressive symptoms. Five microstate classes (A-E) were identified to best explain the datasets of both groups. Compared to controls, the mean duration, occurrence, and coverage of microstate class B increased significantly, whereas the occurrence and coverage of microstate classes D and E decreased significantly in individuals with high intensity of depressive symptoms. Additionally, the presence of microstate class B was positively correlated with participants' Beck Depression Inventory-II (BDI-II) scores, and the presence of microstate classes D and E were negatively correlated with their BDI-II scores. Further, individuals with high intensity of depressive symptoms had higher transition probabilities of A→B, B→A, B→C, B→D, and C→B, with lower transition probabilities of A→D, A→E, D→A, D→E, E→A, E→C, and E→D than controls. These results highlight resting-state EEG microstate temporal dynamics as potential biomarkers for the early detection and timely treatment of depression in college students.
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13
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Babiloni C, Noce G, Di Bonaventura C, Lizio R, Eldellaa A, Tucci F, Salamone EM, Ferri R, Soricelli A, Nobili F, Famà F, Arnaldi D, Palma E, Cifelli P, Marizzoni M, Stocchi F, Bruno G, Di Gennaro G, Frisoni GB, Del Percio C. Alzheimer's Disease with Epileptiform EEG Activity: Abnormal Cortical Sources of Resting State Delta Rhythms in Patients with Amnesic Mild Cognitive Impairment. J Alzheimers Dis 2022; 88:903-931. [PMID: 35694930 DOI: 10.3233/jad-220442] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Patients with amnesic mild cognitive impairment due to Alzheimer's disease (ADMCI) typically show a "slowing" of cortical resting-state eyes-closed electroencephalographic (rsEEG) rhythms. Some of them also show subclinical, non-convulsive, and epileptiform EEG activity (EEA) with an unclear relationship with that "slowing." OBJECTIVE Here we tested the hypothesis that the "slowing" of rsEEG rhythms is related to EEA in ADMCI patients. METHODS Clinical and instrumental datasets in 62 ADMCI patients and 38 normal elderly (Nold) subjects were available in a national archive. No participant had received a clinical diagnosis of epilepsy. The eLORETA freeware estimated rsEEG cortical sources. The area under the receiver operating characteristic curve (AUROCC) indexed the accuracy of eLORETA solutions in the classification between ADMCI-EEA and ADMCI-noEEA individuals. RESULTS EEA was observed in 15% (N = 8) of the ADMCI patients. The ADMCI-EEA group showed: 1) more abnormal Aβ 42 levels in the cerebrospinal fluid as compared to the ADMCI-noEEA group and 2) higher temporal and occipital delta (<4 Hz) rsEEG source activities as compared to the ADMCI-noEEA and Nold groups. Those source activities showed moderate accuracy (AUROCC = 0.70-0.75) in the discrimination between ADMCI-noEEA versus ADMCI-EEA individuals. CONCLUSION It can be speculated that in ADMCI-EEA patients, AD-related amyloid neuropathology may be related to an over-excitation in neurophysiological low-frequency (delta) oscillatory mechanisms underpinning cortical arousal and quiet vigilance.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy.,Hospital San Raffaele Cassino, Cassino (FR), Italy
| | | | - Carlo Di Bonaventura
- Epilepsy Unit, Department of Neurosciences/Mental Health, Sapienza University of Rome, Rome, Italy
| | | | - Ali Eldellaa
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Federico Tucci
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Enrico M Salamone
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy.,Epilepsy Unit, Department of Neurosciences/Mental Health, Sapienza University of Rome, Rome, Italy
| | | | - Andrea Soricelli
- IRCCS Synlab SDN, Naples, Italy.,Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | - Flavio Nobili
- Clinical Neurology, IRCCS Hospital Policlinico San Martino, Genoa, Italy.,Department of Neuroscience (DiNOGMI), University of Genoa, Genoa, Italy
| | - Francesco Famà
- Clinical Neurology, IRCCS Hospital Policlinico San Martino, Genoa, Italy
| | - Dario Arnaldi
- Clinical Neurology, IRCCS Hospital Policlinico San Martino, Genoa, Italy
| | - Eleonora Palma
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy.,Pasteur Institute-Cenci Bolognetti Foundation, Rome, Italy
| | - Pierangelo Cifelli
- IRCCS Neuromed, Pozzilli, (IS), Italy.,Department of Applied and Biotechnological Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Moira Marizzoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | | | - Giuseppe Bruno
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | | | - Giovanni B Frisoni
- Department of Applied and Biotechnological Clinical Sciences, University of L'Aquila, L'Aquila, Italy.,Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Claudio Del Percio
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
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14
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Li Y, Chen G, Lv J, Hou L, Dong Z, Wang R, Su M, Yu S. Abnormalities in resting-state EEG microstates are a vulnerability marker of migraine. J Headache Pain 2022; 23:45. [PMID: 35382739 PMCID: PMC8981824 DOI: 10.1186/s10194-022-01414-y] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 03/15/2022] [Indexed: 12/31/2022] Open
Abstract
Background Resting-state EEG microstates are thought to reflect brief activations of several interacting components of resting-state brain networks. Surprisingly, we still know little about the role of these microstates in migraine. In the present study, we attempted to address this issue by examining EEG microstates in patients with migraine without aura (MwoA) during the interictal period and comparing them with those of a group of healthy controls (HC). Methods Resting-state EEG was recorded in 61 MwoA patients (50 females) and 66 HC (50 females). Microstate parameters were compared between the two groups. We computed four widely identified canonical microstate classes A-D. Results Microstate classes B and D displayed higher time coverage and occurrence in the MwoA patient group than in the HC group, while microstate class C exhibited significantly lower time coverage and occurrence in the MwoA patient group. Meanwhile, the mean duration of microstate class C was significantly shorter in the MwoA patient group than in the HC group. Moreover, among the MwoA patient group, the duration of microstate class C correlated negatively with clinical measures of headache-related disability as assessed by the six-item Headache Impact Test (HIT-6). Finally, microstate syntax analysis showed significant differences in transition probabilities between the two groups, primarily involving microstate classes B, C, and D. Conclusions By exploring EEG microstate characteristics at baseline we were able to explore the neurobiological mechanisms underlying altered cortical excitability and aberrant sensory, affective, and cognitive processing, thus deepening our understanding of migraine pathophysiology.
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15
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Al Zoubi O, Mayeli A, Misaki M, Tsuchiyagaito A, Zotev V, Refai H, Paulus M, Bodurka J. Canonical EEG microstates transitions reflect switching among BOLD resting state networks and predict fMRI signal. J Neural Eng 2022; 18:10.1088/1741-2552/ac4595. [PMID: 34937003 PMCID: PMC11008726 DOI: 10.1088/1741-2552/ac4595] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 12/22/2021] [Indexed: 11/12/2022]
Abstract
Objective.Electroencephalography (EEG) microstates (MSs), which reflect a large topographical representation of coherent electrophysiological brain activity, are widely adopted to study cognitive processes mechanisms and aberrant alterations in brain disorders. MS topographies are quasi-stable lasting between 60-120 ms. Some evidence suggests that MS are the electrophysiological signature of resting-state networks (RSNs). However, the spatial and functional interpretation of MS and their association with functional magnetic resonance imaging (fMRI) remains unclear.Approach. In a cohort of healthy subjects (n= 52), we conducted several statistical and machine learning (ML) approaches analyses on the association among MS spatio-temporal dynamics and the blood-oxygenation-level dependent (BOLD) simultaneous EEG-fMRI data using statistical and ML approaches.Main results.Our results using a generalized linear model showed that MS transitions were largely and negatively associated with BOLD signals in the somatomotor, visual, dorsal attention, and ventral attention fMRI networks with limited association within the default mode network. Additionally, a novel recurrent neural network (RNN) confirmed the association between MS transitioning and fMRI signal while revealing that MS dynamics can model BOLD signals and vice versa.Significance.Results suggest that MS transitions may represent the deactivation of fMRI RSNs and provide evidence that both modalities measure common aspects of undergoing brain neuronal activities. These results may help to better understand the electrophysiological interpretation of MS.
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Affiliation(s)
- Obada Al Zoubi
- Laureate Institute for Brain Research, Tulsa, OK, United States of America
- Electrical and Computer Engineering, University of Oklahoma, Tulsa, OK, United States of America
- Harvard Medical School, Boston, United States of America
| | - Ahmad Mayeli
- Laureate Institute for Brain Research, Tulsa, OK, United States of America
- Electrical and Computer Engineering, University of Oklahoma, Tulsa, OK, United States of America
| | - Masaya Misaki
- Laureate Institute for Brain Research, Tulsa, OK, United States of America
| | - Aki Tsuchiyagaito
- Laureate Institute for Brain Research, Tulsa, OK, United States of America
| | - Vadim Zotev
- Laureate Institute for Brain Research, Tulsa, OK, United States of America
| | | | - Hazem Refai
- Electrical and Computer Engineering, University of Oklahoma, Tulsa, OK, United States of America
| | - Martin Paulus
- Laureate Institute for Brain Research, Tulsa, OK, United States of America
| | - Jerzy Bodurka
- Laureate Institute for Brain Research, Tulsa, OK, United States of America
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States of America
- Deceased
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16
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Das S, Zomorrodi R, Enticott PG, Kirkovski M, Blumberger DM, Rajji TK, Desarkar P. Resting state electroencephalography microstates in autism spectrum disorder: A mini-review. Front Psychiatry 2022; 13:988939. [PMID: 36532178 PMCID: PMC9752812 DOI: 10.3389/fpsyt.2022.988939] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 11/09/2022] [Indexed: 12/04/2022] Open
Abstract
Atypical spatial organization and temporal characteristics, found via resting state electroencephalography (EEG) microstate analysis, have been associated with psychiatric disorders but these temporal and spatial parameters are less known in autism spectrum disorder (ASD). EEG microstates reflect a short time period of stable scalp potential topography. These canonical microstates (i.e., A, B, C, and D) and more are identified by their unique topographic map, mean duration, fraction of time covered, frequency of occurrence and global explained variance percentage; a measure of how well topographical maps represent EEG data. We reviewed the current literature for resting state microstate analysis in ASD and identified eight publications. This current review indicates there is significant alterations in microstate parameters in ASD populations as compared to typically developing (TD) populations. Microstate parameters were also found to change in relation to specific cognitive processes. However, as microstate parameters are found to be changed by cognitive states, the differently acquired data (e.g., eyes closed or open) resting state EEG are likely to produce disparate results. We also review the current understanding of EEG sources of microstates and the underlying brain networks.
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Affiliation(s)
- Sushmit Das
- Centre for Addiction and Mental Health, Toronto, ON, Canada.,Azrieli Adult Neurodevelopmental Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Reza Zomorrodi
- Centre for Addiction and Mental Health, Toronto, ON, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Peter G Enticott
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC, Australia
| | - Melissa Kirkovski
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC, Australia.,Institute for Health and Sport, Victoria University, Melbourne, VIC, Australia
| | - Daniel M Blumberger
- Centre for Addiction and Mental Health, Toronto, ON, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Tarek K Rajji
- Centre for Addiction and Mental Health, Toronto, ON, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Pushpal Desarkar
- Centre for Addiction and Mental Health, Toronto, ON, Canada.,Azrieli Adult Neurodevelopmental Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
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17
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Prillinger K, Radev ST, Amador de Lara G, Klöbl M, Lanzenberger R, Plener PL, Poustka L, Konicar L. Repeated Sessions of Transcranial Direct Current Stimulation on Adolescents With Autism Spectrum Disorder: Study Protocol for a Randomized, Double-Blind, and Sham-Controlled Clinical Trial. Front Psychiatry 2021; 12:680525. [PMID: 34526918 PMCID: PMC8435587 DOI: 10.3389/fpsyt.2021.680525] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Accepted: 07/26/2021] [Indexed: 01/03/2023] Open
Abstract
Background: Social-emotional difficulties are a core symptom of autism spectrum disorder (ASD). Accordingly, individuals with ASD have problems with social cognition such as recognizing emotions from other peoples' faces. Various results from functional magnetic resonance imaging and electroencephalography studies as well as eye-tracking data reveal a neurophysiological basis of these deficits by linking them to abnormal brain activity. Thus, an intervention targeting the neural origin of ASD impairments seems warranted. A safe method able to influence neural activity is transcranial direct current stimulation (tDCS). This non-invasive brain stimulation method has already demonstrated promising results in several neuropsychiatric disorders in adults and children. The aim of this project is to investigate the effects of tDCS on ASD symptoms and their neural correlates in children and adolescents with ASD. Method: This study is designed as a double-blind, randomized, and sham-controlled trial with a target sample size of 20 male participants (aged 12-17 years) diagnosed with ASD. Before randomization, the participants will be stratified into comorbid depression, comorbid ADHS/conduct disorder, or no-comorbidity groups. The intervention phase comprises 10 sessions of anodal or sham tDCS applied over the left prefrontal cortex within 2 consecutive weeks. To engage the targeted brain regions, participants will perform a social cognition training during the stimulation. TDCS-induced effects on ASD symptoms and involved neural circuits will be investigated through psychological, neurophysiological, imaging, and behavioral data at pre- and post-measurements. Tolerability will be evaluated using a standardized questionnaire. Follow-up assessments 1 and 6 months after the intervention will examine long-lasting effects. Discussion: The results of this study will provide insights into the changeability of social impairments in ASD by investigating social and emotional abilities on different modalities following repeated sessions of anodal tDCS with an intra-simulation training. Furthermore, this trial will elucidate the tolerability and the potential of tDCS as a new treatment approach for ASD in adolescents. Clinical Trial Registration: The study is ongoing and has been registered in the German Registry of Clinical Trials (DRKS00017505) on 02/07/2019.
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Affiliation(s)
- Karin Prillinger
- Department of Child and Adolescent Psychiatry, Medical University of Vienna, Vienna, Austria
| | - Stefan T. Radev
- Department of Child and Adolescent Psychiatry, Medical University of Vienna, Vienna, Austria
- Institute of Psychology, University of Heidelberg, Heidelberg, Germany
| | - Gabriel Amador de Lara
- Department of Child and Adolescent Psychiatry, Medical University of Vienna, Vienna, Austria
| | - Manfred Klöbl
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Paul L. Plener
- Department of Child and Adolescent Psychiatry, Medical University of Vienna, Vienna, Austria
- Department of Child and Adolescent Psychiatry and Psychotherapy, University of Ulm, Ulm, Germany
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Lilian Konicar
- Department of Child and Adolescent Psychiatry, Medical University of Vienna, Vienna, Austria
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18
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Bochet A, Sperdin HF, Rihs TA, Kojovic N, Franchini M, Jan RK, Michel CM, Schaer M. Early alterations of large-scale brain networks temporal dynamics in young children with autism. Commun Biol 2021; 4:968. [PMID: 34400754 PMCID: PMC8367954 DOI: 10.1038/s42003-021-02494-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 07/30/2021] [Indexed: 11/08/2022] Open
Abstract
Autism spectrum disorders (ASD) are associated with disruption of large-scale brain network. Recently, we found that directed functional connectivity alterations of social brain networks are a core component of atypical brain development at early developmental stages in ASD. Here, we investigated the spatio-temporal dynamics of whole-brain neuronal networks at a subsecond scale in 113 toddlers and preschoolers (66 with ASD) using an EEG microstate approach. We first determined the predominant microstates using established clustering methods. We identified five predominant microstate (labeled as microstate classes A-E) with significant differences in the temporal dynamics of microstate class B between the groups in terms of increased appearance and prolonged duration. Using Markov chains, we found differences in the dynamic syntax between several maps in toddlers and preschoolers with ASD compared to their TD peers. Finally, exploratory analysis of brain-behavioral relationships within the ASD group suggested that the temporal dynamics of some maps were related to conditions comorbid to ASD during early developmental stages.
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Affiliation(s)
- Aurélie Bochet
- Department of Psychiatry, University of Geneva, Geneva, Switzerland.
| | | | - Tonia Anahi Rihs
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - Nada Kojovic
- Department of Psychiatry, University of Geneva, Geneva, Switzerland
| | | | - Reem Kais Jan
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates
| | - Christoph Martin Michel
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - Marie Schaer
- Department of Psychiatry, University of Geneva, Geneva, Switzerland
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19
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Zhang M, Li Z, Wang L, Yang S, Zou F, Wang Y, Wu X, Luo Y. The Resting-State Electroencephalogram Microstate Correlations With Empathy and Their Moderating Effect on the Relationship Between Empathy and Disgust. Front Hum Neurosci 2021; 15:626507. [PMID: 34262440 PMCID: PMC8273331 DOI: 10.3389/fnhum.2021.626507] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 05/17/2021] [Indexed: 01/10/2023] Open
Abstract
Humans have a natural ability to understand the emotions and feelings of others, whether one actually witnesses the situation of another, perceives it from a photograph, reads about it in a fiction book, or merely imagines it. This is the phenomenon of empathy, which requires us to mentally represent external information to experience the emotions of others. Studies have shown that individuals with high empathy have high anterior insula and adjacent frontal operculum activation when they are aware of negative emotions in others. As a negative emotion, disgust processing involves insula coupling. What are the neurophysiological characteristics for regulating the levels of empathy and disgust? To answer this question, we collected electroencephalogram microstates (EEG-ms) of 196 college students at rest and used the Disgust Scale and Interpersonal Reactivity Index. The results showed that: (1) there was a significant positive correlation between empathy and disgust sensitivity; (2) the empathy score and the intensity of transition possibility between EEG-ms C and D were significantly positively correlated; and (3) the connection strength between the transition possibility of EEG-ms C and D could adjust the relationship between the disgust sensitivity score and the empathy score. This study provides new neurophysiological characteristics for an understanding of the regulate relationship between empathy and disgust and provides a new perspective on emotion and attention.
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Affiliation(s)
- Meng Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Department of Psychology, Xinxiang Medical University, Xinxiang, China
| | - Zhaoxian Li
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Department of Psychology, Xinxiang Medical University, Xinxiang, China
| | - Li Wang
- Department of Psychology, Xinxiang Medical University, Xinxiang, China
| | - Shiyan Yang
- Department of Psychology, Xinxiang Medical University, Xinxiang, China
| | - Feng Zou
- Department of Psychology, Xinxiang Medical University, Xinxiang, China
| | - Yufeng Wang
- Department of Psychology, Xinxiang Medical University, Xinxiang, China
| | - Xin Wu
- Department of Psychology, Xinxiang Medical University, Xinxiang, China
| | - Yanyan Luo
- School of Nursing, Xinxiang Medical University, Xinxiang, China
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20
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Resting-State EEG Microstates Parallel Age-Related Differences in Allocentric Spatial Working Memory Performance. Brain Topogr 2021; 34:442-460. [PMID: 33871737 PMCID: PMC8195770 DOI: 10.1007/s10548-021-00835-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Accepted: 03/30/2021] [Indexed: 11/08/2022]
Abstract
Alterations of resting-state EEG microstates have been associated with various neurological disorders and behavioral states. Interestingly, age-related differences in EEG microstate organization have also been reported, and it has been suggested that resting-state EEG activity may predict cognitive capacities in healthy individuals across the lifespan. In this exploratory study, we performed a microstate analysis of resting-state brain activity and tested allocentric spatial working memory performance in healthy adult individuals: twenty 25–30-year-olds and twenty-five 64–75-year-olds. We found a lower spatial working memory performance in older adults, as well as age-related differences in the five EEG microstate maps A, B, C, C′ and D, but especially in microstate maps C and C′. These two maps have been linked to neuronal activity in the frontal and parietal brain regions which are associated with working memory and attention, cognitive functions that have been shown to be sensitive to aging. Older adults exhibited lower global explained variance and occurrence of maps C and C′. Moreover, although there was a higher probability to transition from any map towards maps C, C′ and D in young and older adults, this probability was lower in older adults. Finally, although age-related differences in resting-state EEG microstates paralleled differences in allocentric spatial working memory performance, we found no evidence that any individual or combination of resting-state EEG microstate parameter(s) could reliably predict individual spatial working memory performance. Whether the temporal dynamics of EEG microstates may be used to assess healthy cognitive aging from resting-state brain activity requires further investigation.
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21
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Jia H, Gao F, Yu D. Altered Temporal Structure of Neural Phase Synchrony in Patients With Autism Spectrum Disorder. Front Psychiatry 2021; 12:618573. [PMID: 34899403 PMCID: PMC8660096 DOI: 10.3389/fpsyt.2021.618573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2020] [Accepted: 10/20/2021] [Indexed: 12/02/2022] Open
Abstract
Functional connectivity, quantified by phase synchrony, between brain regions is known to be aberrant in patients with autism spectrum disorder (ASD). Here, we evaluated the long-range temporal correlations of time-varying phase synchrony (TV-PS) of electrocortical oscillations in patients with ASD as well as typically developing people using detrended fluctuation analysis (DFA) after validating the scale-invariance of the TV-PS time series. By comparing the DFA exponents between the two groups, we found that those of the TV-PS time series of high-gamma oscillations were significantly attenuated in patients with ASD. Furthermore, the regions involved in aberrant TV-PS time series were mainly within the social ability and cognition-related cortical networks. These results support the notion that abnormal social functions observed in patients with ASD may be caused by the highly volatile phase synchrony states of electrocortical oscillations.
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Affiliation(s)
- Huibin Jia
- Institute of Cognition, Brain and Health, Henan University, Kaifeng, China.,School of Psychology, Henan University, Kaifeng, China.,Institute of Psychology and Behavior, Henan University, Kaifeng, China.,Key Laboratory of Child Development and Learning Science of Ministry of Education, Research Center for Learning Science, School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China
| | - Fei Gao
- Department of Pain Medicine, Peking University People's Hospital, Beijing, China
| | - Dongchuan Yu
- Key Laboratory of Child Development and Learning Science of Ministry of Education, Research Center for Learning Science, School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China
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22
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Nagabhushan Kalburgi S, Whitten AP, Key AP, Bodfish JW. Children With Autism Produce a Unique Pattern of EEG Microstates During an Eyes Closed Resting-State Condition. Front Hum Neurosci 2020; 14:288. [PMID: 33132865 PMCID: PMC7579608 DOI: 10.3389/fnhum.2020.00288] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Accepted: 06/26/2020] [Indexed: 11/23/2022] Open
Abstract
Although fMRI studies have produced considerable evidence for differences in the spatial connectivity of resting-state brain networks in persons with autism spectrum disorder (ASD) relative to typically developing (TD) peers, little is known about the temporal dynamics of these brain networks in ASD. The aim of this study was to examine the EEG microstate architecture in children with ASD as compared to TD at rest in two separate conditions – eyes-closed (EC) and eyes-open (EO). EEG microstate analysis was performed on resting-state data of 13 ASD and 13 TD children matched on age, gender, and IQ. We found that children with ASD and TD peers produced topographically similar canonical microstates at rest. Group differences in the duration and frequency of these microstates were found primarily in the EC resting-state condition. In line with previous fMRI findings that have reported differences in spatial connectivity within the salience network (previously correlated with the activity of microstate C) in ASD, we found that the duration of activation of microstate C was increased, and the frequency of microstate C was decreased in ASD as compared to TD in EC resting-state. Functionally, these results may be reflective of alterations in interoceptive processes in ASD. These results suggest a unique pattern of EEG microstate architecture in ASD relative to TD during resting-states and also that EEG microstate parameters in ASD are susceptible to differences in resting-state conditions.
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Affiliation(s)
| | | | - Alexandra P Key
- Vanderbilt Kennedy Center, Nashville, TN, United States.,Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - James W Bodfish
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, United States.,Vanderbilt University Medical Center, Nashville, TN, United States.,Vanderbilt Kennedy Center, Nashville, TN, United States.,Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
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23
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Emotional working memory training reduces rumination and alters the EEG microstate in anxious individuals. NEUROIMAGE-CLINICAL 2020; 28:102488. [PMID: 33395979 PMCID: PMC7689328 DOI: 10.1016/j.nicl.2020.102488] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 10/26/2020] [Indexed: 12/17/2022]
Abstract
Rumination is an important etiological factor of anxiety pathology, with its mechanism related to the deficit of working memory. The current study examined whether working memory training (WM-T) and emotional working memory training (EWM-T) could reduce rumination in anxious individuals. The participants with high trait anxiety underwent 21 days of mobile applications-based WM-T (n = 34), EWM-T (n = 36) or placebo control (n = 36), with questionnaires, cognitive tasks, and resting electroencephalogram (EEG) as the pre-post-test indicators. The results revealed that two training groups obtained comparable operation span increases (WM-T: d = 0.53; EWM-T: d = 0.65), updating improvement (WM-T: d = 0.43; EWM-T: d = 0.60) and shifting improvement (WM-T: d = 0.49; EWM-T: d = 0.72). Furthermore, compared to the control group, the EWM-T showed significant self-reported rumination reduction (d = 0.69), increased inhibition ability (d = 0.72), as well as modification of resting EEG microstate C parameters (Duration C: d = 0.42, Coverage C: d = 0.39), which were closely related to rumination level (r ~ 0.4). The WM-T group also showed the potential to reduced self-reported rumination (d = 0.45), but with the absence of the observable inhibition improvement and resting EEG changes. The correlation analysis suggested that the emotional benefits of WM-T depending more on improved updating and shifting, and that of EWM-T depending more on improved inhibition ability. The advantage to add emotional distractions into general working memory training for targeting rumination related anxiety has been discussed.
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Oshima F, William M, Takahashi N, Tsuchiyagaito A, Kuwabara H, Shiina A, Seto M, Hongo M, Iwama Y, Hirano Y, Sutoh C, Taguchi K, Yoshida T, Kawasaki Y, Ozawa Y, Masuya J, Sato N, Nakamura S, Kuno M, Takahashi J, Ohtani T, Matsuzawa D, Inada N, Kuroda M, Ando M, Hori A, Nakagawa A, Shimizu E. Cognitive-behavioral family therapy as psychoeducation for adolescents with high-functioning autism spectrum disorders: Aware and Care for my Autistic Traits (ACAT) program study protocol for a pragmatic multisite randomized controlled trial. Trials 2020; 21:814. [PMID: 32993775 PMCID: PMC7526096 DOI: 10.1186/s13063-020-04750-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Accepted: 09/17/2020] [Indexed: 11/23/2022] Open
Abstract
Background One aim of an autism spectrum disorder (ASD) diagnosis is to obtain special support for the disorder, though this does not guarantee practical support. We developed a psychoeducational program using cognitive-behavioral therapy (CBT) and Aware and Care for my Autistic Traits (ACAT) for Japanese adolescents with high-functioning ASD and their parents. Methods This multisite study is a randomized controlled trial. In total, 24 participants will be assigned to the ACAT group and 24 to the treatment-as-usual (TAU) group. The ACAT group will receive a weekly 100-min session for 6 weeks, regular medical care, and one follow-up session. In this ongoing clinical trial, we will compare the scores of the measures recorded in the pre- and post-intervention stages between the ACAT and TAU groups. A total of 41 patients out of a target of 48 have participated in the trial to date. The primary outcome measure is the Autism Knowledge Questionnaire. Secondary outcome measures include Barriers to Access to Care Evaluation 3rd Edition, the Strengths and Difficulties Questionnaire, the Vineland Adaptive Behavior Scales second edition, the Parenting Resilience Elements Questionnaire, the General Health Questionnaire 12, and the Depression Self-Rating Scale for Children assessments, as well as an electroencephalographic recording. Discussion It is expected that participants in the ACAT group will significantly increase their self-understanding and awareness of ASD symptoms compared to those in the TAU group. Additionally, the ACAT group is expected to exhibit improved social adaptation and mental health if children and parents are able to better understand the ASD characteristics through sessions. This intervention will contribute to the establishment of an effective evidence-based treatment strategy for adolescents with ASD. Trial registration UMIN Register 000029851. Registered on January 06, 2018
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Affiliation(s)
- Fumiyo Oshima
- Research Center for Child Mental Development, Chiba University, 1-8-1 Inohana Chuouku, Chiba, 260-8670, Japan.
| | - Mandy William
- Research Department of Clinical, Educational & Health Psychology, University College London, London, UK
| | - Noriko Takahashi
- Fukushima University Child Mental Health-Care Center, Fukushima, Japan
| | - Aki Tsuchiyagaito
- Research Center for Child Mental Development, Chiba University, 1-8-1 Inohana Chuouku, Chiba, 260-8670, Japan.,Laureate Instituto for Brain Research, Tulsa, OK, USA
| | - Hitoshi Kuwabara
- Department of Psychiatry, Hamamatsu University School of Medicine, Shizuoka, Japan
| | - Akihiro Shiina
- Chiba University Center for Forensic Mental Health, Chiba, Japan
| | - Mikuko Seto
- Research Center for Child Mental Development, Chiba University, 1-8-1 Inohana Chuouku, Chiba, 260-8670, Japan
| | - Minako Hongo
- Research Center for Child Mental Development, Chiba University, 1-8-1 Inohana Chuouku, Chiba, 260-8670, Japan
| | - Yui Iwama
- Research Center for Child Mental Development, Chiba University, 1-8-1 Inohana Chuouku, Chiba, 260-8670, Japan
| | - Yoshiyuki Hirano
- Research Center for Child Mental Development, Chiba University, 1-8-1 Inohana Chuouku, Chiba, 260-8670, Japan
| | - Chihiro Sutoh
- Research Center for Child Mental Development, Chiba University, 1-8-1 Inohana Chuouku, Chiba, 260-8670, Japan
| | - Kayoko Taguchi
- Research Center for Child Mental Development, Chiba University, 1-8-1 Inohana Chuouku, Chiba, 260-8670, Japan
| | - Tokiko Yoshida
- Research Center for Child Mental Development, Chiba University, 1-8-1 Inohana Chuouku, Chiba, 260-8670, Japan
| | - Yohei Kawasaki
- Biostatistics Section, Clinical Research Center, Chiba University Hospital, Chiba, Japan
| | - Yoshihito Ozawa
- Biostatistics Section, Clinical Research Center, Chiba University Hospital, Chiba, Japan
| | - Jiro Masuya
- Fukushima University Child Mental Health-Care Center, Fukushima, Japan.,Department of Psychiatry, Tokyo Medical University Ibaraki Medical Center, Ibaraki, Japan
| | - Noriyuki Sato
- Fukushima University Child Mental Health-Care Center, Fukushima, Japan
| | - Shizuka Nakamura
- Fukushima University Child Mental Health-Care Center, Fukushima, Japan
| | - Masaru Kuno
- Research Center for Child Mental Development, Chiba University, 1-8-1 Inohana Chuouku, Chiba, 260-8670, Japan
| | - Jumpei Takahashi
- Research Center for Child Mental Development, Chiba University, 1-8-1 Inohana Chuouku, Chiba, 260-8670, Japan
| | - Toshiyuki Ohtani
- Research Center for Child Mental Development, Chiba University, 1-8-1 Inohana Chuouku, Chiba, 260-8670, Japan
| | - Daisuke Matsuzawa
- Research Center for Child Mental Development, Chiba University, 1-8-1 Inohana Chuouku, Chiba, 260-8670, Japan
| | - Naoko Inada
- Department of Psychology, Faculty of Liberal Arts, Teikyo University, Tokyo, Japan
| | - Miho Kuroda
- Department of Human Care, Nagoya University of Arts and Sciences, Nagoya, Japan
| | - Mika Ando
- Department of Psychiatry, Hibarigaoka Hospital, Fukushima, Japan
| | | | - Akiko Nakagawa
- Research Center for Child Mental Development, Chiba University, 1-8-1 Inohana Chuouku, Chiba, 260-8670, Japan
| | - Eiji Shimizu
- Research Center for Child Mental Development, Chiba University, 1-8-1 Inohana Chuouku, Chiba, 260-8670, Japan
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Cao W, Wang F, Zhang C, Lei G, Jiang Q, Shen W, Yang S. Microstate in resting state: an EEG indicator of tinnitus? Acta Otolaryngol 2020; 140:564-569. [PMID: 32302256 DOI: 10.1080/00016489.2020.1743878] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Background: Tinnitus was a subjective auditory phantom phenomenon which could be highly distressing and had no objective indicators for evaluation.Objectives: The aim of this study was to investigate whether and how did electroencephalography (EEG) microstates of subjective tinnitus patients change in resting state and whether could be an objective indicator for tinnitus.Material and Methods: We enrolled chronic subjective tinnitus patients and matched age and gender with healthy controls. EEG recording, microstate analysis and statistical analysis were performed.Results: We finally had 10 male and 8 female age-matched participants in tinnitus group and healthy control group. Statistical differences were found in the microstate A, C and D durations between the two groups (class A, p = .024; class B, p = .018; class D, p = .029). Microstate durations of class A and D had linear correlation with VAS scores in tinnitus patients (microstate A [R spare = 0.43, p = .003*]; microstate D [R spare = 0.46, p = .002*]).Conclusions: Microstates had changed in chronic tinnitus patients and provided an indicator or perspective to explore the mechanisms of tinnitus. The maintenance of chronic subjective tinnitus may be related to changes in cerebral cortex activity.
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Affiliation(s)
- Wei Cao
- Medical School, Nankai University, Tianjin, China
- ColIege of Otolaryngology Head and Neck Surgery, Chinese PLA General Hospital, Beijing, China
- National Clinical Research Center for Otolaryngologic Diseases, Beijing, China
- Key Lab of Hearing Science, Ministry of Education, China
- Beijing Key Lab of Hearing Impairment for Prevention and Treatment, Beijing, China
| | - Fangyuan Wang
- ColIege of Otolaryngology Head and Neck Surgery, Chinese PLA General Hospital, Beijing, China
- National Clinical Research Center for Otolaryngologic Diseases, Beijing, China
- Key Lab of Hearing Science, Ministry of Education, China
- Beijing Key Lab of Hearing Impairment for Prevention and Treatment, Beijing, China
| | - Chi Zhang
- ColIege of Otolaryngology Head and Neck Surgery, Chinese PLA General Hospital, Beijing, China
- National Clinical Research Center for Otolaryngologic Diseases, Beijing, China
- Key Lab of Hearing Science, Ministry of Education, China
- Beijing Key Lab of Hearing Impairment for Prevention and Treatment, Beijing, China
| | - Guangxiong Lei
- Xiangnan University, Chenzhou, China
- Department of Otorhinolaryngology, Head and Neck Surgery, Affiliated Hospital of Xiangnan University, Chenzhou, China
| | - Qingqing Jiang
- ColIege of Otolaryngology Head and Neck Surgery, Chinese PLA General Hospital, Beijing, China
- National Clinical Research Center for Otolaryngologic Diseases, Beijing, China
- Key Lab of Hearing Science, Ministry of Education, China
- Beijing Key Lab of Hearing Impairment for Prevention and Treatment, Beijing, China
| | - Weidong Shen
- ColIege of Otolaryngology Head and Neck Surgery, Chinese PLA General Hospital, Beijing, China
- National Clinical Research Center for Otolaryngologic Diseases, Beijing, China
- Key Lab of Hearing Science, Ministry of Education, China
- Beijing Key Lab of Hearing Impairment for Prevention and Treatment, Beijing, China
| | - Shiming Yang
- Medical School, Nankai University, Tianjin, China
- ColIege of Otolaryngology Head and Neck Surgery, Chinese PLA General Hospital, Beijing, China
- National Clinical Research Center for Otolaryngologic Diseases, Beijing, China
- Key Lab of Hearing Science, Ministry of Education, China
- Beijing Key Lab of Hearing Impairment for Prevention and Treatment, Beijing, China
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26
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Portnova GV, Ivanova O, Proskurnina EV. Effects of EEG examination and ABA-therapy on resting-state EEG in children with low-functioning autism. AIMS Neurosci 2020; 7:153-167. [PMID: 32607418 PMCID: PMC7321768 DOI: 10.3934/neuroscience.2020011] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 06/01/2020] [Indexed: 12/15/2022] Open
Abstract
Objective We aimed to study the effects of EEG examination and ABA-therapy on resting-state EEG in children with low-functioning autism and tactile defensiveness. Methods We have performed this study with three cohorts of preschoolers: children with autistic spectrum disorder (ASD) who needed applied behavior analysis (ABA) therapy due to their tactile defensiveness; children with ASD who didn't need ABA therapy; and the control group of healthy children. Number of microstates was determined in the initial and final parts of the resting-state EEGs. Results and conclusions Children with higher tactile defensiveness for the most part had specific EEG microstates associated with unpleasant emotions and senses. The EEG microstates of children with ASD who did not need ABA therapy, had more similarities with the EEG microstates of typically developing children except for temporary changes. Meanwhile, the children with tactile defensiveness demonstrated typical patterns of EEG microstates from start to finish of the procedure.
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Affiliation(s)
- Galina V Portnova
- Institute of Higher Nervous Activity and Neurophysiology of RAS, 5A Butlerova St., Moscow 117485, Russia
| | - Oxana Ivanova
- FSBI Federal medical center Rosimushchestvo, 31 Kalanchevskaya str., 107078, Moscow, Russia
| | - Elena V Proskurnina
- Research Centre for Medical Genetics, 1 Moskvorechye St., Moscow 115522, Russia
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27
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D'Croz-Baron DF, Baker M, Michel CM, Karp T. EEG Microstates Analysis in Young Adults With Autism Spectrum Disorder During Resting-State. Front Hum Neurosci 2019; 13:173. [PMID: 31244624 PMCID: PMC6581708 DOI: 10.3389/fnhum.2019.00173] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2019] [Accepted: 05/13/2019] [Indexed: 11/13/2022] Open
Abstract
Electroencephalography (EEG) is a useful tool to inspect the brain activity in resting state and allows to characterize spontaneous brain activity that is not detected when a subject is cognitively engaged. Moreover, taking advantage of the high time resolution in EEG, it is possible to perform fast topographical reference-free analysis, since different scalp potential fields correspond to changes in the underlying sources within the brain. In this study, the spontaneous EEG resting state (eyes closed) was compared between 10 young adults ages 18-30 years with autism spectrum disorder (ASD) and 13 neurotypical controls. A microstate analysis was applied, focusing on four temporal parameters: mean duration, the frequency of occurrence, the ratio of time coverage, and the global explained variance (GEV). Using data that were acquired from a 65-channel EEG system, six resting-state topographies that best describe the dataset across all subjects were identified by running a two-step cluster analysis labeled as microstate classes A-F. The results indicated that microstates B and E displayed statistically significant differences between both groups among the temporal parameters evaluated. Classes B, D, E, and F were consistently more present in ASD, and class C in controls. The combination of these findings with the putative functional significance of the different classes suggests that during resting state, the ASD group was more focused on visual scene reconstruction, while the control group was more engaged with self-memory retrieval. Furthermore, from a connectivity perspective, the resting-state networks that have been previously associated with each microstate class overlap the brain regions implicated in impaired social communication and repetitive behaviors that characterize ASD.
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Affiliation(s)
- David F D'Croz-Baron
- Autumn's Dawn Neuroimaging, Cognition, and Engineering Laboratory, Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX, United States
| | - Mary Baker
- Autumn's Dawn Neuroimaging, Cognition, and Engineering Laboratory, Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX, United States
| | - Christoph M Michel
- Functional Brain Mapping Laboratory, Department of Basic Neuroscience, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Tanja Karp
- Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX, United States
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28
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Jan RK, Rihs TA, Kojovic N, Sperdin HF, Franchini M, Custo A, Tomescu MI, Michel CM, Schaer M. Neural Processing of Dynamic Animated Social Interactions in Young Children With Autism Spectrum Disorder: A High-Density Electroencephalography Study. Front Psychiatry 2019; 10:582. [PMID: 31507462 PMCID: PMC6714589 DOI: 10.3389/fpsyt.2019.00582] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2019] [Accepted: 07/23/2019] [Indexed: 01/22/2023] Open
Abstract
Background: Atypical neural processing of social visual information contributes to impaired social cognition in autism spectrum disorder. However, evidence for early developmental alterations in neural processing of social contingencies is scarce. Most studies in the literature have been conducted in older children and adults. Here, we aimed to investigate alterations in neural processing of social visual information in children with autism spectrum disorder compared to age-matched typically developing peers. Methods: We used a combination of 129-channel electroencephalography and high-resolution eye-tracking to study differences in the neural processing of dynamic cartoons containing human-like social interactions between 14 male children with autism spectrum disorder and 14 typically developing male children, aged 2-5 years. Using a microstate approach, we identified four prototypical maps in both groups and compared the temporal characteristics and inverse solutions (activation of neural sources) of these maps between groups. Results: Inverse solutions of the group maps that were most dominant during free viewing of the dynamic cartoons indicated decreased prefrontal and cingulate activation, impaired activation of the premotor cortex, and increased activation of parietal, temporal, occipital, and cerebellar regions in children with autism spectrum disorder compared to their typically developing peers. Conclusions: Our findings suggest that impairments in brain regions involved in processing social contingencies embedded in dynamic cartoons are present from an early age in autism spectrum disorder. To the best of our knowledge, this is the first study to investigate neural processing of social interactions of children with autism spectrum disorder using dynamic semi-naturalistic stimuli.
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Affiliation(s)
- Reem K Jan
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates.,Developmental Imaging and Psychopathology Lab, Department of Psychiatry, University of Geneva, Geneva, Switzerland.,Functional Brain Mapping Laboratory, Department of Fundamental Neuroscience, University Medical School, Geneva, Switzerland
| | - Tonia A Rihs
- Functional Brain Mapping Laboratory, Department of Fundamental Neuroscience, University Medical School, Geneva, Switzerland
| | - Nada Kojovic
- Developmental Imaging and Psychopathology Lab, Department of Psychiatry, University of Geneva, Geneva, Switzerland
| | - Holger F Sperdin
- Developmental Imaging and Psychopathology Lab, Department of Psychiatry, University of Geneva, Geneva, Switzerland
| | - Martina Franchini
- Developmental Imaging and Psychopathology Lab, Department of Psychiatry, University of Geneva, Geneva, Switzerland
| | - Anna Custo
- Functional Brain Mapping Laboratory, Department of Fundamental Neuroscience, University Medical School, Geneva, Switzerland
| | - Miralena I Tomescu
- Functional Brain Mapping Laboratory, Department of Fundamental Neuroscience, University Medical School, Geneva, Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Laboratory, Department of Fundamental Neuroscience, University Medical School, Geneva, Switzerland
| | - Marie Schaer
- Developmental Imaging and Psychopathology Lab, Department of Psychiatry, University of Geneva, Geneva, Switzerland
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