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Schiller B, Sperl MFJ, Kleinert T, Nash K, Gianotti LRR. EEG Microstates in Social and Affective Neuroscience. Brain Topogr 2024; 37:479-495. [PMID: 37523005 PMCID: PMC11199304 DOI: 10.1007/s10548-023-00987-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 07/05/2023] [Indexed: 08/01/2023]
Abstract
Social interactions require both the rapid processing of multifaceted socio-affective signals (e.g., eye gaze, facial expressions, gestures) and their integration with evaluations, social knowledge, and expectations. Researchers interested in understanding complex social cognition and behavior face a "black box" problem: What are the underlying mental processes rapidly occurring between perception and action and why are there such vast individual differences? In this review, we promote electroencephalography (EEG) microstates as a powerful tool for both examining socio-affective states (e.g., processing whether someone is in need in a given situation) and identifying the sources of heterogeneity in socio-affective traits (e.g., general willingness to help others). EEG microstates are identified by analyzing scalp field maps (i.e., the distribution of the electrical field on the scalp) over time. This data-driven, reference-independent approach allows for identifying, timing, sequencing, and quantifying the activation of large-scale brain networks relevant to our socio-affective mind. In light of these benefits, EEG microstates should become an indispensable part of the methodological toolkit of laboratories working in the field of social and affective neuroscience.
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Affiliation(s)
- Bastian Schiller
- Laboratory for Biological Psychology, Clinical Psychology, and Psychotherapy, Albert-Ludwigs-University of Freiburg, Freiburg, Germany.
- Freiburg Brain Imaging Center, University Medical Center, Albert-Ludwigs-University of Freiburg, Freiburg, Germany.
| | - Matthias F J Sperl
- Department of Clinical Psychology and Psychotherapy, University of Giessen, Giessen, Germany
- Center for Mind, Brain and Behavior, Universities of Marburg and Giessen (Research Campus Central Hessen), Marburg, Germany
| | - Tobias Kleinert
- Laboratory for Biological Psychology, Clinical Psychology, and Psychotherapy, Albert-Ludwigs-University of Freiburg, Freiburg, Germany
- Department of Ergonomics, Leibniz Research Centre for Working Environment and Human Factors (IfADo), Dortmund, Germany
| | - Kyle Nash
- Department of Psychology, University of Alberta, Edmonton, Canada.
| | - Lorena R R Gianotti
- Department of Social Neuroscience and Social Psychology, Institute of Psychology, University of Bern, Bern, Switzerland.
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Nazare K, Tomescu MI. Valence-specific EEG microstate modulations during self-generated affective states. Front Psychol 2024; 15:1300416. [PMID: 38855303 PMCID: PMC11160840 DOI: 10.3389/fpsyg.2024.1300416] [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: 09/23/2023] [Accepted: 04/26/2024] [Indexed: 06/11/2024] Open
Abstract
Introduction This study aims to explore the temporal dynamics of brain networks involved in self-generated affective states, specifically focusing on modulating these states in both positive and negative valences. The overarching goal is to contribute to a deeper understanding of the neurodynamic patterns associated with affective regulation, potentially informing the development of biomarkers for therapeutic interventions in mood and anxiety disorders. Methods Utilizing EEG microstate analysis during self-generated affective states, we investigated the temporal dynamics of five distinct microstates across different conditions, including baseline resting state and self-generated states of positive valence (e.g., awe, contentment) and negative valence (e.g., anger, fear). Results The study revealed noteworthy modulations in microstate dynamics during affective states. Additionally, valence-specific mechanisms of spontaneous affective regulation were identified. Negative valence affective states were characterized by the heightened presence of attention-associated microstates and reduced occurrence of salience-related microstates during negative valence states. In contrast, positive valence affective states manifested a prevalence of microstates related to visual/autobiographical memory and a reduced presence of auditory/language-associated microstates compared to both baseline and negative valence states. Discussion This study contributes to the field by employing EEG microstate analysis to discern the temporal dynamics of brain networks involved in self-generated affective states. Insights from this research carry significant implications for understanding neurodynamic patterns in affective regulation. The identification of valence-specific modulations and mechanisms has potential applications in developing biomarkers for mood and anxiety disorders, offering novel avenues for therapeutic interventions.
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Affiliation(s)
- Karina Nazare
- CINETic Center, Department of Research and Development, National University of Theatre and Film “I.L. Caragiale”, Bucharest, Romania
- Faculty of Automatic Control and Computers, POLITEHNICA University of Bucharest, Bucharest, Romania
| | - Miralena I. Tomescu
- CINETic Center, Department of Research and Development, National University of Theatre and Film “I.L. Caragiale”, Bucharest, Romania
- Department of Psychology, Faculty of Educational Sciences, University “Stefan cel Mare” of Suceava, Suceava, Romania
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Tarailis P, Koenig T, Michel CM, Griškova-Bulanova I. The Functional Aspects of Resting EEG Microstates: A Systematic Review. Brain Topogr 2024; 37:181-217. [PMID: 37162601 DOI: 10.1007/s10548-023-00958-9] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 04/11/2023] [Indexed: 05/11/2023]
Abstract
A growing body of clinical and cognitive neuroscience studies have adapted a broadband EEG microstate approach to evaluate the electrical activity of large-scale cortical networks. However, the functional aspects of these microstates have not yet been systematically reviewed. Here, we present an overview of the existing literature and systematize the results to provide hints on the functional role of electrical brain microstates. Studies that evaluated and manipulated the temporal properties of resting-state microstates and utilized questionnaires, task-initiated thoughts, specific tasks before or between EEG session(s), pharmacological interventions, neuromodulation approaches, or localized sources of the extracted microstates were selected. Fifty studies that met the inclusion criteria were included. A new microstate labeling system has been proposed for a comprehensible comparison between the studies, where four classical microstates are referred to as A-D, and the others are labeled by the frequency of their appearance. Microstate A was associated with both auditory and visual processing and links to subjects' arousal/arousability. Microstate B showed associations with visual processing related to self, self-visualization, and autobiographical memory. Microstate C was related to processing personally significant information, self-reflection, and self-referential internal mentation rather than autonomic information processing. In contrast, microstate E was related to processing interoceptive and emotional information and to the salience network. Microstate D was associated with executive functioning. Microstate F is suggested to be a part of the Default Mode Network and plays a role in personally significant information processing, mental simulations, and theory of mind. Microstate G is potentially linked to the somatosensory network.
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Affiliation(s)
- Povilas Tarailis
- Life Sciences Centre, Institute of Biosciences, Vilnius University, Vilnius, Lithuania
| | - Thomas Koenig
- Translational Research Center, University Hospital of Psychiatry, University of Bern, Bern, Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Laboratory, Department of Fundamental Neuroscience, University of Geneva, Geneva, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
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Su K, Wang L, Wang Z, Ma J, Zhang C, Bi H, Wu J. The effect of acupuncture at the Taiyang acupoint on visual function and EEG microstates in myopia. Front Integr Neurosci 2023; 17:1234471. [PMID: 38035147 PMCID: PMC10684943 DOI: 10.3389/fnint.2023.1234471] [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: 06/04/2023] [Accepted: 09/06/2023] [Indexed: 12/02/2023] Open
Abstract
Objective Acupuncture has certain effects to improve myopia visual function, but its neural mechanism is unclear. In this study, we acupunctured at the right Taiyang acupoint of myopic patients to analyze the effects of acupuncture on visual function and electroencephalographic activity and to investigate the correlation between improvements in visual function and changes in the brain. Methods In this study, a total of 21 myopic patients were recruited. The contrast sensitivity (CS) of the subjects was examined before and after acupuncture, and electroencephalography (EEG) data of the entire acupuncture process were recorded. Results The study found that compared with before acupuncture, the CS of both eyes in myopic patients at each spatial frequency was increased after acupuncture; compared with the resting state, the contribution of microstate C was decreased during the post-acupuncture state, and the transition probability between microstate A and microstate C was reduced; in addition, the contribution of microstate C was negatively correlated with CS at both 12 and 18 cpd. Conclusion The contrast sensitivity of myopic patients was improved after acupuncture at the Taiyang acupoint (20 min), which may be related to microstate C.
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Affiliation(s)
- Kangna Su
- Medical College of Optometry and Ophthalmology, Shandong University of Traditional Chinese Medicine, Jinan, China
- Shandong Academy of Eye Disease Prevention and Therapy, Shandong Provincial Key Laboratory of Integrated Traditional Chinese and Western Medicine for Prevention and Therapy of Ocular Diseases, Shandong Provincial Clinical Research Center of Ophthalmology and Children Visual Impairment Prevention and Control, Shandong Engineering Technology Research Center of Visual Intelligence, Shandong Academy of Health and Myopia Prevention and Control of Children and Adolescents, Jinan, China
- Ophthalmology Department of Northwest University First Hospital, Xi’an, Shaanxi, China
| | - Lihan Wang
- Shandong Academy of Eye Disease Prevention and Therapy, Shandong Provincial Key Laboratory of Integrated Traditional Chinese and Western Medicine for Prevention and Therapy of Ocular Diseases, Shandong Provincial Clinical Research Center of Ophthalmology and Children Visual Impairment Prevention and Control, Shandong Engineering Technology Research Center of Visual Intelligence, Shandong Academy of Health and Myopia Prevention and Control of Children and Adolescents, Jinan, China
- Affiliated Eye Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Zhongqing Wang
- Medical College of Optometry and Ophthalmology, Shandong University of Traditional Chinese Medicine, Jinan, China
- Shandong Academy of Eye Disease Prevention and Therapy, Shandong Provincial Key Laboratory of Integrated Traditional Chinese and Western Medicine for Prevention and Therapy of Ocular Diseases, Shandong Provincial Clinical Research Center of Ophthalmology and Children Visual Impairment Prevention and Control, Shandong Engineering Technology Research Center of Visual Intelligence, Shandong Academy of Health and Myopia Prevention and Control of Children and Adolescents, Jinan, China
| | - Jiayao Ma
- Medical College of Optometry and Ophthalmology, Shandong University of Traditional Chinese Medicine, Jinan, China
- Shandong Academy of Eye Disease Prevention and Therapy, Shandong Provincial Key Laboratory of Integrated Traditional Chinese and Western Medicine for Prevention and Therapy of Ocular Diseases, Shandong Provincial Clinical Research Center of Ophthalmology and Children Visual Impairment Prevention and Control, Shandong Engineering Technology Research Center of Visual Intelligence, Shandong Academy of Health and Myopia Prevention and Control of Children and Adolescents, Jinan, China
| | - Chao Zhang
- Affiliated Eye Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Hongsheng Bi
- Medical College of Optometry and Ophthalmology, Shandong University of Traditional Chinese Medicine, Jinan, China
- Shandong Academy of Eye Disease Prevention and Therapy, Shandong Provincial Key Laboratory of Integrated Traditional Chinese and Western Medicine for Prevention and Therapy of Ocular Diseases, Shandong Provincial Clinical Research Center of Ophthalmology and Children Visual Impairment Prevention and Control, Shandong Engineering Technology Research Center of Visual Intelligence, Shandong Academy of Health and Myopia Prevention and Control of Children and Adolescents, Jinan, China
- Affiliated Eye Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Jianfeng Wu
- Medical College of Optometry and Ophthalmology, Shandong University of Traditional Chinese Medicine, Jinan, China
- Shandong Academy of Eye Disease Prevention and Therapy, Shandong Provincial Key Laboratory of Integrated Traditional Chinese and Western Medicine for Prevention and Therapy of Ocular Diseases, Shandong Provincial Clinical Research Center of Ophthalmology and Children Visual Impairment Prevention and Control, Shandong Engineering Technology Research Center of Visual Intelligence, Shandong Academy of Health and Myopia Prevention and Control of Children and Adolescents, Jinan, China
- Affiliated Eye Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
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Li W, Cheng S, Wang H, Chang Y. EEG microstate changes according to mental fatigue induced by aircraft piloting simulation: An exploratory study. Behav Brain Res 2023; 438:114203. [PMID: 36356722 DOI: 10.1016/j.bbr.2022.114203] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 11/04/2022] [Accepted: 11/04/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND A continuous flight task load can induce fatigue and lead to changes in electroencephalography (EEG). EEG microstates can reflect the activities of large-scale neural networks during mental fatigue. This exploratory experiment explored the effects of mental fatigue induced by continuous simulated flight multitasking on EEG microstate indices. METHODS Twenty-four participants performed continuous 2-hour aircraft piloting simulation while EEG were recorded. The Stanford sleepiness scale (SSS) and critical flicker fusion frequency (CFF) were measured before and after the task. Microstate analysis was applied to EEG. Four microstate classes (A-D) were identified during the pre-task, post-task, beginning, and end phases. The effects of mental fatigue were analyzed. RESULTS Compared with the pre-task, the post-task had a higher global explained variance (GEV) and time parameters of class C but lower occurrence and coverage of class D. The end had a higher GEV but lower duration and coverage of class D than at the beginning. After 2 h of multitasking, the transition probability between A and D, and between B and D decreased but between A and C increased. Subjective fatigue scores were negatively correlated with occurrence and coverage of class D. Task performance was negatively correlated with duration and coverage of class C but positively correlated with duration and occurrence of class B. CONCLUSION Time parameters and transition probability of EEG microstates can detect mental fatigue induced by continuous aircraft piloting simulation. The global brain network activation of mental fatigue can be detected by EEG microstates that can evaluate flight fatigue.
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Affiliation(s)
- Wenbin Li
- Department of Aerospace Hygiene, Faculty of Aerospace Medicine, Air Force Medical University, Xi'an, China
| | - Shan Cheng
- Department of Aerospace Medical Equipment, Faculty of Aerospace Medicine, Air Force Medical University, Xi'an, China
| | - Hang Wang
- Department of Aerospace Ergonomics, Faculty of Aerospace Medicine, Air Force Medical University, Xi'an, China.
| | - Yaoming Chang
- Department of Aerospace Hygiene, Faculty of Aerospace Medicine, Air Force Medical University, Xi'an, China.
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Computer assisted identification of stress, anxiety, depression (SAD) in students: A state-of-the-art review. Med Eng Phys 2022; 110:103900. [PMID: 36273998 DOI: 10.1016/j.medengphy.2022.103900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 08/09/2022] [Accepted: 10/02/2022] [Indexed: 11/05/2022]
Abstract
Stress, depression, and anxiety are a person's physiological states that emerge from various body features such as speech, body language, eye contact, facial expression, etc. Physiological emotion is a part of human life and is associated with psychological activities. Sad emotion is relatable to negative thoughts and recognized in three stages containing stress, anxiety, and depression. These stages of Physiological emotion show various common and distinguished symptoms. The present study explores stress, depression, and anxiety symptoms in student life. The study reviews the psychological features generated through various body parts to identify psychological activities. Environmental factors, including a daily routine, greatly trigger psychological activities. The psychological disorder may affect mental and physical health adversely. The correct recognition of such disorder is expensive and time-consuming as it requires accurate datasets of symptoms. In the present study, an attempt has been made to investigate the effectiveness of computerized automated techniques that include machine learning algorithms for identifying stress, anxiety, and depression mental disorder. The proposed paper reviews the machine learning-based algorithms applied over datasets containing questionnaires, audio, video, etc., to recognize sad details. During the review process, the proposed study found that artificial intelligence and machine learning techniques are well recommended and widely utilized in most of the existing literature for measuring psychological disorders. The various machine learning-based algorithms are applied over datasets containing questionnaires, audio, video, etc., to recognize sad details. There has been continuous monitoring for the body symptoms established in the various existing literature to identify psychological states. The present review reveals the study of excellence and competence of machine learning techniques in detecting psychological disorders' stress, depression, and anxiety parameters. This paper shows a systematic review of some existing computer vision-based models with their merits and demerits.
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Research on Top Archer’s EEG Microstates and Source Analysis in Different States. Brain Sci 2022; 12:brainsci12081017. [PMID: 36009079 PMCID: PMC9405655 DOI: 10.3390/brainsci12081017] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 07/08/2022] [Accepted: 07/28/2022] [Indexed: 01/25/2023] Open
Abstract
The electroencephalograph (EEG) microstate is a method used to describe the characteristics of the EEG signal through the brain scalp electrode potential’s spatial distribution; as such, it reflects the changes in the brain’s functional state. The EEGs of 13 elite archers from China’s national archery team and 13 expert archers from China’s provincial archery team were recorded under the alpha rhythm during the resting state (with closed eyes) and during archery aiming. By analyzing the differences between the EEG microstate parameters and the correlation between these parameters with archery performance, as well as by combining our findings through standardized low-resolution brain electromagnetic tomography source analysis (sLORETA), we explored the changes in the neural activity of professional archers of different levels, under different states. The results of the resting state study demonstrated that the duration, occurrence, and coverage in microstate D of elite archers were significantly higher than those of expert archers and that their other microstates had the greatest probability of transferring to microstate D. During the archery aiming state, the average transition probability of the other microstates transferring to microstate in the left temporal region was the highest observed in the two groups of archers. Moreover, there was a significant negative correlation between the duration and coverage of microstates in the frontal region of elite archers and their archery performance. Our findings indicate that elite archers are more active in the dorsal attention system and demonstrate a higher neural efficiency during the resting state. When aiming, professional archers experience an activation of brain regions associated with archery by suppressing brain regions unrelated to archery tasks. These findings provide a novel theoretical basis for the study of EEG microstate dynamics in archery and related cognitive motor tasks, particularly from the perspective of the subject’s mental state.
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Byun K, Aristizabal S, Wu Y, Mullan AF, Carlin JD, West CP, Mazurek KA. Investigating How Auditory and Visual Stimuli Promote Recovery After Stress With Potential Applications for Workplace Stress and Burnout: Protocol for a Randomized Trial. Front Psychol 2022; 13:897241. [PMID: 35719506 PMCID: PMC9201821 DOI: 10.3389/fpsyg.2022.897241] [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: 03/15/2022] [Accepted: 05/11/2022] [Indexed: 11/13/2022] Open
Abstract
Background Work-related stress is one of the top sources of stress amongst working adults. Relaxation rooms are one organizational strategy being used to reduce workplace stress. Amongst healthcare workers, relaxation rooms have been shown to improve perceived stress levels after 15 min of use. However, few studies have examined physiological and cognitive changes after stress, which may inform why relaxation rooms reduce perceived stress. Understanding the biological mechanisms governing why perceived stress improves when using a relaxation room could lead to more effective strategies to address workplace stress. Objective The purpose of this research study is to understand how physiological measures, cognitive performance, and perceived stress change after acute stress and whether certain sensory features of a relaxation room are more effective at promoting recovery from stress. Methods 80 healthy adults will perform a stress induction task (Trier Social Stress Test, TSST) to evaluate how physiological and cognitive responses after stress are affected by sensory features of a relaxation room. After the stress induction task, participants will recover for 40 min in a MindBreaks™ relaxation room containing auditory and visual stimuli designed to promote relaxation. Participants will be randomized into four cohorts to experience auditory and visual stimuli; auditory stimuli; visual stimuli; or no stimuli in the room. Measures of heart rate and neural activity will be continuously monitored using wearable devices. Participants will perform working memory assessments and rate their perceived stress levels throughout the experiment. These measures will be compared before and after the stress induction task to determine how different sensory stimuli affect the rate at which individuals recover. Results Recruitment started in December 2021 and will continue until December 2022 or until enrollment is completed. Final data collection and subsequent analysis are anticipated by December 2022. We expect all trial results will be available by early 2023. Discussion Findings will provide data and information about which sensory features of a relaxation room are most effective at promoting recovery after acute stress. This information will be useful in determining how these features might be effective at creating individualized and organizational strategies for mitigating the effects of workplace stress.
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Affiliation(s)
- Kunjoon Byun
- Well Living Lab, Rochester, MN, United States
- Delos Living LLC., New York, NY, United States
| | - Sara Aristizabal
- Well Living Lab, Rochester, MN, United States
- Delos Living LLC., New York, NY, United States
| | - Yihan Wu
- Graduate Program in Cognitive Science, University of Minnesota-Twin Cities, Minneapolis, MN, United States
| | - Aidan F. Mullan
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States
| | - Jeremiah D. Carlin
- Well Living Lab, Rochester, MN, United States
- Delos Living LLC., New York, NY, United States
| | - Colin P. West
- Division of General Internal Medicine, Department of Medicine, Mayo Clinic, Rochester, MN, United States
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States
| | - Kevin A. Mazurek
- Well Living Lab, Rochester, MN, United States
- Delos Living LLC., New York, NY, United States
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, United States
- Department of Neuroscience, The Del Monte Institute for Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, United States
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Walter Y, Koenig T. Neural network involvement for religious experiences in worship measured by EEG microstate analysis. Soc Neurosci 2022; 17:258-275. [PMID: 35613474 DOI: 10.1080/17470919.2022.2083228] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
To date, not much is known about large-scale brain activation patterns in religious states of mind and previous studies have not set an emphasis on experience. The present study investigated the phenomenon of religious experiences through microstate analysis, and it was the first neurocognitive research to tackle the dimension of experience directly. Hence, a total of 60 evangelical Christians participated in an experiment where they were asked to engage in worship and try to connect with God. With a bar slider, people were able to continuously rate how strongly they sensed God's presence at any given moment. A selection of songs was used to help in the induction of the desired experience. With 64 electroencephalography (EEG) electrodes, the brain activity was assessed and analyzed with five clusters of microstate classes. First, we hypothesized that the neural network for multisensory integration was involved in the religious experience. Second, we hypothesized that the same was true for the Default Mode Network (DMN). Our results suggested an association between the auditory network and the religious experience, and an association with the salience network as well as with the DMN. No associations with the network thought to be involved with multisensory integration was detected.
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Affiliation(s)
- Yoshija Walter
- Laboratory for Cognitive Neurosciences, University of Fribourg, Switzerland.,University Hospital of Psychiatry and Psychotherapy, Translational Research Center, University of Bern, Switzerland
| | - Thomas Koenig
- University Hospital of Psychiatry and Psychotherapy, Translational Research Center, University of Bern, Switzerland
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Terpou BA, Shaw SB, Théberge J, Férat V, Michel CM, McKinnon MC, Lanius RA, Ros T. Spectral decomposition of EEG microstates in post-traumatic stress disorder. NEUROIMAGE: CLINICAL 2022; 35:103135. [PMID: 36002969 PMCID: PMC9421541 DOI: 10.1016/j.nicl.2022.103135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 06/09/2022] [Accepted: 07/27/2022] [Indexed: 11/25/2022] Open
Abstract
EEG microstates reveal significant temporal differences in PTSD. Microstate E (with centro-posterior maximum) is temporally underrepresented in PTSD. In PTSD, microstate E has a reduced occurrence and a shorter mean duration. Spectral decomposition of EEG microstates improves microstate-based classification. Alpha band SVM features yield the highest classification accuracy of PTSD (76%).
Microstates offer a promising framework to study fast-scale brain dynamics in the resting-state electroencephalogram (EEG). However, microstate dynamics have yet to be investigated in post-traumatic stress disorder (PTSD), despite research demonstrating resting-state alterations in PTSD. We performed microstate-based segmentation of resting-state EEG in a clinical population of participants with PTSD (N = 61) and a non-traumatized, healthy control group (N = 61). Microstate-based measures (i.e., occurrence, mean duration, time coverage) were compared group-wise using broadband (1–30 Hz) and frequency-specific (i.e., delta, theta, alpha, beta bands) decompositions. In the broadband comparisons, the centro-posterior maximum microstate (map E) occurred significantly less frequently (d = -0.64, pFWE = 0.03) and had a significantly shorter mean duration in participants with PTSD as compared to controls (d = -0.71, pFWE < 0.01). These differences were reflected in the narrow frequency bands as well, with lower frequency bands like delta (d = -0.78, pFWE < 0.01), theta (d = -0.74, pFWE = 0.01), and alpha (d = -0.65, pFWE = 0.02) repeating these group-level trends, only with larger effect sizes. Interestingly, a support vector machine classification analysis comparing broadband and frequency-specific measures revealed that models containing only alpha band features significantly out-perform broadband models. When classifying PTSD, the classification accuracy was 76 % and 65 % for the alpha band and the broadband model, respectively (p = 0.03). Taken together, we provide original evidence supporting the clinical utility of microstates as diagnostic markers of PTSD and demonstrate that filtering EEG into distinct frequency bands significantly improves microstate-based classification of a psychiatric disorder.
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