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Morrone JM, Pedlar CR. Selective cortical adaptations associated with neural efficiency in visuospatial tasks - the comparison of electroencephalographic profiles of expert and novice artists. Neuropsychologia 2024; 198:108854. [PMID: 38493826 DOI: 10.1016/j.neuropsychologia.2024.108854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 03/01/2024] [Accepted: 03/14/2024] [Indexed: 03/19/2024]
Abstract
Visuospatial cognition encapsulates an individual's ability to efficiently navigate and make sense of the multimodal cues from their surroundings, and therefore has been linked to expert performance across multiple domains, including sports, performing arts, and highly skilled tasks, such as drawing (Morrone and Minini, 2023). As neural efficiency posits a task-specific functional reorganization facilitated by long-term training, the present study employs a visuospatial construction task as a means of investigating the neurophysiological adaptations associated with expert visuospatial cognitive performance. Electroencephalogram (EEG) data acquisitions were used to evaluate the event-related changes (ER%) and statistical topographic maps of nine expert versus nine novice artists. The expert artists displayed overall higher global ER% compared to the novices within task-active intervals. Significant increases in relative ER% were found in the theta (t (10) = 3.528, p = 0.003, CI = [27.3,120.9]), lower-alpha (t (10) = 3.751, p = 0.002, CI = [28.2,110.5]), upper-alpha (t (10) = 3.829, p = 0.002, CI = [50.2,189.8]), and low beta (t (10) = 4.342, p < 0.001, CI = [37.0,114.9]) frequency bands, when comparing the experts to the novice participants. These results were particularly found in the frontal (t (14) = 2.014, p = 0.032, CI = [7.7,245.4]) and occipital (t (14) = 2.647, p = 0.010, CI = [45.0,429.7]) regions. Further, a significant decrease in alpha ER% from lower to upper activity (t (8) = 4.475, p = 0.001, CI = [21.0, 65.8]) was found across cortical regions in the novice group. Notably, greater deviation between lower and upper-alpha activity was found across scalp locations in the novice group, compared to the experts. Overall, the findings demonstrate potential local and global EEG-based indices of selective cortical adaptations within a task requiring a high degree of visuospatial cognition, although further work is needed to replicate these findings across other domains.
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Affiliation(s)
- Jazmin M Morrone
- Faculty of Sport, Allied Health, and Performance Science, St Mary's University, Twickenham, London, UK
| | - Charles R Pedlar
- Faculty of Sport, Allied Health, and Performance Science, St Mary's University, Twickenham, London, UK; Institute of Sport, Exercise and Health, Division of Surgery and Interventional Science, University College London, UK
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2
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Mitiureva D, Sysoeva O, Proshina E, Portnova G, Khayrullina G, Martynova O. Comparative analysis of resting-state EEG functional connectivity in depression and obsessive-compulsive disorder. Psychiatry Res Neuroimaging 2024; 342:111828. [PMID: 38833944 DOI: 10.1016/j.pscychresns.2024.111828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 05/09/2024] [Accepted: 05/19/2024] [Indexed: 06/06/2024]
Abstract
Major depressive disorder (MDD) and obsessive-compulsive disorder (OCD) are psychiatric disorders that often co-occur. We aimed to investigate whether their high comorbidity could be traced not only by clinical manifestations, but also at the level of functional brain activity. In this paper, we examined the differences in functional connectivity (FC) at the whole-brain level and within the default mode network (DMN). Resting-state EEG was obtained from 43 controls, 26 OCD patients, and 34 MDD patients. FC was analyzed between 68 cortical sources, and between-group differences in the 4-30 Hz range were assessed via the Network Based Statistic method. The strength of DMN intra-connectivity was compared between groups in the theta, alpha and beta frequency bands. A cluster of 67 connections distinguished the OCD, MDD and control groups. The majority of the connections, 8 of which correlated with depressive symptom severity, were found to be weaker in the clinical groups. Only 3 connections differed between the clinical groups, and one of them correlated with OCD severity. The DMN strength was reduced in the clinical groups in the alpha and beta bands. It can be concluded that the high comorbidity of OCD and MDD can be traced at the level of FC.
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Affiliation(s)
- Dina Mitiureva
- Laboratory of Human Higher Nervous Activity, Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences, Moscow, Russia; Centre for Cognition & Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
| | - Olga Sysoeva
- Laboratory of Human Higher Nervous Activity, Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences, Moscow, Russia; Sirius Center for Cognitive Sciences, Sirius University of Science and Technology, Sochi, Russia
| | - Ekaterina Proshina
- Centre for Cognition & Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia.
| | - Galina Portnova
- Laboratory of Human Higher Nervous Activity, Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences, Moscow, Russia
| | - Guzal Khayrullina
- Laboratory of Human Higher Nervous Activity, Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences, Moscow, Russia; Centre for Cognition & Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
| | - Olga Martynova
- Laboratory of Human Higher Nervous Activity, Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences, Moscow, Russia; Department of Biology and Biotechnology, National Research University Higher School of Economics, Moscow, Russia
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Li B, Pastötter B, Zhong Y, Su N, Huang T, Zhao W, Hu X, Luo L, Yang C. Judgments of Learning Reactively Improve Memory by Enhancing Learning Engagement and Inducing Elaborative Processing: Evidence from an EEG Study. J Intell 2024; 12:44. [PMID: 38667711 PMCID: PMC11050784 DOI: 10.3390/jintelligence12040044] [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: 10/19/2023] [Revised: 02/21/2024] [Accepted: 04/03/2024] [Indexed: 04/28/2024] Open
Abstract
Making judgments of learning (JOLs) can reactively alter memory itself, a phenomenon termed the reactivity effect. The current study recorded electroencephalography (EEG) signals during the encoding phase of a word list learning task to explore the neurocognitive features associated with JOL reactivity. The behavioral results show that making JOLs reactively enhances recognition performance. The EEG results reveal that, compared with not making JOLs, making JOLs increases P200 and LPC amplitudes and decreases alpha and beta power. Additionally, the signals of event-related potentials (ERPs) and event-related desynchronizations (ERDs) partially mediate the reactivity effect. These findings support the enhanced learning engagement theory and the elaborative processing explanation to account for the JOL reactivity effect.
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Affiliation(s)
- Baike Li
- School of Psychology, Liaoning Normal University, Dalian 116029, China;
- Institute of Developmental Psychology, Faculty of Psychology, Beijing Normal University, Beijing 100875, China
| | - Bernhard Pastötter
- Department of Cognitive Psychology and Methodology, Trier University, D-54296 Trier, Germany;
| | - Yongen Zhong
- Institute of Developmental Psychology, Faculty of Psychology, Beijing Normal University, Beijing 100875, China
| | - Ningxin Su
- Collaborative Innovation Center of Assessment for Basic Education Quality, Beijing Normal University, Beijing 100875, China
| | - Ting Huang
- School of Humanities and Social Sciences, Beijing Institute of Technology, Beijing 100081, China
| | - Wenbo Zhao
- School of Social Development and Public Policy, Beijing Normal University, Beijing 100875, China;
| | - Xiao Hu
- Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education, Beijing Normal University, Beijing 100875, China
| | - Liang Luo
- Institute of Developmental Psychology, Faculty of Psychology, Beijing Normal University, Beijing 100875, China
| | - Chunliang Yang
- Institute of Developmental Psychology, Faculty of Psychology, Beijing Normal University, Beijing 100875, China
- Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education, Beijing Normal University, Beijing 100875, China
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4
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Jauny G, Mijalkov M, Canal-Garcia A, Volpe G, Pereira J, Eustache F, Hinault T. Linking structural and functional changes during aging using multilayer brain network analysis. Commun Biol 2024; 7:239. [PMID: 38418523 PMCID: PMC10902297 DOI: 10.1038/s42003-024-05927-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Accepted: 02/16/2024] [Indexed: 03/01/2024] Open
Abstract
Brain structure and function are intimately linked, however this association remains poorly understood and the complexity of this relationship has remained understudied. Healthy aging is characterised by heterogenous levels of structural integrity changes that influence functional network dynamics. Here, we use the multilayer brain network analysis on structural (diffusion weighted imaging) and functional (magnetoencephalography) data from the Cam-CAN database. We found that the level of similarity of connectivity patterns between brain structure and function in the parietal and temporal regions (alpha frequency band) is associated with cognitive performance in healthy older individuals. These results highlight the impact of structural connectivity changes on the reorganisation of functional connectivity associated with the preservation of cognitive function, and provide a mechanistic understanding of the concepts of brain maintenance and compensation with aging. Investigation of the link between structure and function could thus represent a new marker of individual variability, and of pathological changes.
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Affiliation(s)
- Gwendolyn Jauny
- Normandie Univ, UNICAEN, PSL Université Paris, EPHE, Inserm, U1077, CHU de Caen, Centre Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France
| | - Mite Mijalkov
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Anna Canal-Garcia
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Giovanni Volpe
- Department of Physics, Goteborg University, Goteborg, Sweden
| | - Joana Pereira
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Francis Eustache
- Normandie Univ, UNICAEN, PSL Université Paris, EPHE, Inserm, U1077, CHU de Caen, Centre Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France
| | - Thomas Hinault
- Normandie Univ, UNICAEN, PSL Université Paris, EPHE, Inserm, U1077, CHU de Caen, Centre Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, 14000, Caen, France.
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Jia Y, Kudo K, Jariwala N, Tarapore P, Nagarajan S, Subramaniam K. Causal role of medial superior frontal cortex on enhancing neural information flow and self-agency judgments in the self-agency network. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.13.24302764. [PMID: 38405834 PMCID: PMC10888992 DOI: 10.1101/2024.02.13.24302764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Self-agency is being aware of oneself as the agent of one's thoughts and actions. Self-agency is necessary for successful interactions with the outside world (reality-monitoring). Prior research has shown that the medial superior prefrontal gyri (mPFC/SFG) may represent one neural correlate underlying self-agency judgments. However, the causal relationship remains unknown. Here, we applied high-frequency 10Hz repetitive transcranial magnetic stimulation (rTMS) to modulate the excitability of the mPFC/SFG site that we have previously shown to mediate self-agency. For the first time, we delineate causal neural mechanisms, revealing precisely how rTMS modulates SFG excitability and impacts directional neural information flow in the self-agency network by implementing innovative magnetoencephalography (MEG) phase-transfer entropy (PTE) metrics, measured from pre-to-post rTMS. We found that, compared to control rTMS, enhancing SFG excitability by rTMS induced significant increases in information flow between SFG and specific cingulate and paracentral regions in the self-agency network in delta-theta, alpha, and gamma bands, which predicted improved self-agency judgments. This is the first multimodal imaging study in which we implement MEG PTE metrics of 5D imaging of space, frequency and time, to provide cutting-edge analyses of the causal neural mechanisms of how rTMS enhances SFG excitability and improves neural information flow between distinct regions in the self-agency network to potentiate improved self-agency judgments. Our findings provide a novel perspective for investigating causal neural mechanisms underlying self-agency and create a path towards developing novel neuromodulation interventions to improve self-agency that will be particularly useful for patients with psychosis who exhibit severe impairments in self-agency.
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Shetty SJ, Shetty S, Shettigar D, Pagilla V, Maiya GA. Effect of transcranial photobiomodulation on electrophysiological activity of brain in healthy individuals: A scoping review. J Clin Neurosci 2023; 117:156-167. [PMID: 37826867 DOI: 10.1016/j.jocn.2023.09.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 09/26/2023] [Accepted: 09/28/2023] [Indexed: 10/14/2023]
Abstract
BACKGROUND OBJECTIVE Transcranial photobiomodulation (tPBM) is a safe and non-invasive treatment that has recently emerged as an effective technique to apply near-infrared or red light to activate neural tissues. The objective is to review the literature on the effect of tPBM on electrophysiological activity in healthy individuals. METHODS Literature was searched through PubMed, Scopus, Web of Science, Cumulated Index to Nursing and Allied Health Literature (CINAHL), Embase, and Ovid for transcranial photobiomodulation therapy in healthy individuals age group 18-80 years of either gender having electroencephalography as an outcome. Critical appraisal of included Randomized Controlled Trials and non-randomized experimental studies was done using Joanna Briggs Institute (JBI) critical appraisal tool. RESULTS A database search yielded a total of 4156 results. After eliminating 2626 duplicates, 1530 records were left. 32 articles were considered for full-text screening after 1498 records were excluded through title and abstract screening. 10 articles were included in this review. tPBM has been found to increase the higher electrophysiological oscillations and there is inconclusive evidence targeting the lower oscillatory electrophysiological frequencies. CONCLUSION Transcranial photobiomodulation can have promising effects on the electrophysiological activity of the brain in healthy individuals.
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Affiliation(s)
- Shrija Jaya Shetty
- Centre for Diabetic Foot Care and Research, Department of Physiotherapy, Manipal College of Health Professions (MCHP), Manipal Academy of Higher Education (MAHE), Manipal 576104, Karnataka, India
| | - Saidan Shetty
- Department of Basic Medical Sciences, Manipal Academy of Higher Education (MAHE), Manipal 576104, Karnataka, India
| | - Deeksha Shettigar
- Centre for Diabetic Foot Care and Research, Department of Physiotherapy, Manipal College of Health Professions (MCHP), Manipal Academy of Higher Education (MAHE), Manipal 576104, Karnataka, India
| | - Vidyasagar Pagilla
- Department of Basic Medical Sciences, Manipal Academy of Higher Education (MAHE), Manipal 576104, Karnataka, India
| | - G Arun Maiya
- Centre for Diabetic Foot Care and Research, Department of Physiotherapy, Manipal College of Health Professions (MCHP), Manipal Academy of Higher Education (MAHE), Manipal 576104, Karnataka, India.
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7
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Huang Y, Deng Y, Kong L, Zhang X, Wei X, Mao T, Xu Y, Jiang C, Rao H. Vigilant attention mediates the association between resting EEG alpha oscillations and word learning ability. Neuroimage 2023; 281:120369. [PMID: 37690592 DOI: 10.1016/j.neuroimage.2023.120369] [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: 03/03/2023] [Revised: 09/05/2023] [Accepted: 09/08/2023] [Indexed: 09/12/2023] Open
Abstract
Individuals exhibit considerable variability in their capacity to learn and retain new information, including novel vocabulary. Prior research has established the importance of vigilance and electroencephalogram (EEG) alpha rhythm in the learning process. However, the interplay between vigilant attention, EEG alpha oscillations, and an individual's word learning ability (WLA) remains elusive. To address this knowledge gap, here we conducted two experiments with a total of 140 young and middle-aged adults who underwent resting EEG recordings prior to completing a paired-associate word learning task and a psychomotor vigilance test (PVT). The results of both experiments consistently revealed significant positive correlations between WLA and resting EEG alpha oscillations in the occipital and frontal regions. Furthermore, the association between resting EEG alpha oscillations and WLA was mediated by vigilant attention, as measured by the PVT. These findings provide compelling evidence supporting the crucial role of vigilant attention in linking EEG alpha oscillations to an individual's learning ability.
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Affiliation(s)
- Yan Huang
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China; School of Foreign Languages, East China University of Science and Technology, Shanghai, China
| | - Yao Deng
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Lingda Kong
- Institute of Corpus, Shanghai International Studies University, Shanghai, China
| | - Xiumei Zhang
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Xiaobao Wei
- School of Foreign Languages, East China University of Science and Technology, Shanghai, China
| | - Tianxin Mao
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Yong Xu
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Caihong Jiang
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China.
| | - Hengyi Rao
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China; Center for Functional Neuroimaging, Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
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8
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Brown JA, Clancy KJ, Chen C, Zeng Y, Qin S, Ding M, Li W. Transcranial stimulation of alpha oscillations modulates brain state dynamics in sustained attention. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.27.542583. [PMID: 37398325 PMCID: PMC10312462 DOI: 10.1101/2023.05.27.542583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
The brain operates an advanced complex system to support mental activities. Cognition is thought to emerge from dynamic states of the complex brain system, which are organized spatially through large-scale neural networks and temporally via neural synchrony. However, specific mechanisms underlying these processes remain obscure. Applying high-definition alpha-frequency transcranial alternating-current stimulation (HD α-tACS) in a continuous performance task (CPT) during functional resonance imaging (fMRI), we causally elucidate these major organizational architectures in a key cognitive operation-sustained attention. We demonstrated that α-tACS enhanced both electroencephalogram (EEG) alpha power and sustained attention, in a correlated fashion. Akin to temporal fluctuations inherent in sustained attention, our hidden Markov modeling (HMM) of fMRI timeseries uncovered several recurrent, dynamic brain states, which were organized through a few major neural networks and regulated by the alpha oscillation. Specifically, during sustain attention, α-tACS regulated the temporal dynamics of the brain states by suppressing a Task-Negative state (characterized by activation of the default mode network/DMN) and Distraction state (with activation of the ventral attention and visual networks). These findings thus linked dynamic states of major neural networks and alpha oscillations, providing important insights into systems-level mechanisms of attention. They also highlight the efficacy of non-invasive oscillatory neuromodulation in probing the functioning of the complex brain system and encourage future clinical applications to improve neural systems health and cognitive performance.
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Affiliation(s)
- Joshua A. Brown
- Department of Psychology, Florida State University, Tallahassee, FL
| | - Kevin J. Clancy
- Department of Psychology, Florida State University, Tallahassee, FL
| | - Chaowen Chen
- Department of Psychology, Florida State University, Tallahassee, FL
- Tallahassee Memorial Healthcare, Tallahassee, FL
| | - Yimeng Zeng
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Mingzhou Ding
- J Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL
| | - Wen Li
- Department of Psychology, Florida State University, Tallahassee, FL
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Watanabe N, Miyoshi K, Jimura K, Shimane D, Keerativittayayut R, Nakahara K, Takeda M. Multimodal deep neural decoding reveals highly resolved spatiotemporal profile of visual object representation in humans. Neuroimage 2023; 275:120164. [PMID: 37169115 DOI: 10.1016/j.neuroimage.2023.120164] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 05/02/2023] [Accepted: 05/09/2023] [Indexed: 05/13/2023] Open
Abstract
Perception and categorization of objects in a visual scene are essential to grasp the surrounding situation. Recently, neural decoding schemes, such as machine learning in functional magnetic resonance imaging (fMRI), has been employed to elucidate the underlying neural mechanisms. However, it remains unclear as to how spatially distributed brain regions temporally represent visual object categories and sub-categories. One promising strategy to address this issue is neural decoding with concurrently obtained neural response data of high spatial and temporal resolution. In this study, we explored the spatial and temporal organization of visual object representations using concurrent fMRI and electroencephalography (EEG), combined with neural decoding using deep neural networks (DNNs). We hypothesized that neural decoding by multimodal neural data with DNN would show high classification performance in visual object categorization (faces or non-face objects) and sub-categorization within faces and objects. Visualization of the fMRI DNN was more sensitive than that in the univariate approach and revealed that visual categorization occurred in brain-wide regions. Interestingly, the EEG DNN valued the earlier phase of neural responses for categorization and the later phase of neural responses for sub-categorization. Combination of the two DNNs improved the classification performance for both categorization and sub-categorization compared with fMRI DNN or EEG DNN alone. These deep learning-based results demonstrate a categorization principle in which visual objects are represented in a spatially organized and coarse-to-fine manner, and provide strong evidence of the ability of multimodal deep learning to uncover spatiotemporal neural machinery in sensory processing.
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Affiliation(s)
- Noriya Watanabe
- Research Center for Brain Communication, Kochi University of Technology, Kami, Kochi, 782-8502, Japan
| | - Kosuke Miyoshi
- Narrative Nights, Inc., Yokohama, Kanagawa, 236-0011, Japan
| | - Koji Jimura
- Research Center for Brain Communication, Kochi University of Technology, Kami, Kochi, 782-8502, Japan; Department of Informatics, Gunma University, Maebashi, Gunma, 371-8510, Japan
| | - Daisuke Shimane
- Research Center for Brain Communication, Kochi University of Technology, Kami, Kochi, 782-8502, Japan
| | - Ruedeerat Keerativittayayut
- Research Center for Brain Communication, Kochi University of Technology, Kami, Kochi, 782-8502, Japan; Chulabhorn Royal Academy, Bangkok, 10210, Thailand
| | - Kiyoshi Nakahara
- Research Center for Brain Communication, Kochi University of Technology, Kami, Kochi, 782-8502, Japan
| | - Masaki Takeda
- Research Center for Brain Communication, Kochi University of Technology, Kami, Kochi, 782-8502, Japan.
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10
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Alterations in EEG functional connectivity in individuals with depression: A systematic review. J Affect Disord 2023; 328:287-302. [PMID: 36801418 DOI: 10.1016/j.jad.2023.01.126] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 01/22/2023] [Accepted: 01/30/2023] [Indexed: 02/19/2023]
Abstract
The brain works as an organised, network-like structure of functionally interconnected regions. Disruptions to interconnectivity in certain networks have been linked to symptoms of depression and impairments in cognition. Electroencephalography (EEG) is a low-burden tool by which differences in functional connectivity (FC) can be assessed. This systematic review aims to provide a synthesis of evidence relating to EEG FC in depression. A comprehensive electronic literature search for terms relating to depression, EEG, and FC was conducted on studies published before the end of November 2021, according to PRISMA guidelines. Studies comparing EEG measures of FC of individuals with depression to that of healthy control groups were included. Data was extracted by two independent reviewers, and the quality of EEG FC methods was assessed. Fifty-two studies assessing EEG FC in depression were identified: 36 assessed resting-state FC, and 16 assessed task-related or other (i.e., sleep) FC. Somewhat consistent findings in resting-state studies suggest for no differences between depression and control groups in EEG FC in the delta and gamma frequencies. However, while most resting-state studies noted a difference in alpha, theta, and beta, no clear conclusions could be drawn about the direction of the difference, due to considerable inconsistencies between study design and methodology. This was also true for task-related and other EEG FC. More robust research is needed to understand the true differences in EEG FC in depression. Given that the FC between brain regions drives behaviour, cognition, and emotion, characterising how FC differs in depression is essential for understanding the aetiology of depression.
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Lieberman JM, Rabellino D, Densmore M, Frewen PA, Steyrl D, Scharnowski F, Théberge J, Neufeld RWJ, Schmahl C, Jetly R, Narikuzhy S, Lanius RA, Nicholson AA. Posterior cingulate cortex targeted real-time fMRI neurofeedback recalibrates functional connectivity with the amygdala, posterior insula, and default-mode network in PTSD. Brain Behav 2023; 13:e2883. [PMID: 36791212 PMCID: PMC10013955 DOI: 10.1002/brb3.2883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 12/07/2022] [Accepted: 12/12/2022] [Indexed: 02/17/2023] Open
Abstract
BACKGROUND Alterations within large-scale brain networks-namely, the default mode (DMN) and salience networks (SN)-are present among individuals with posttraumatic stress disorder (PTSD). Previous real-time functional magnetic resonance imaging (fMRI) and electroencephalography neurofeedback studies suggest that regulating posterior cingulate cortex (PCC; the primary hub of the posterior DMN) activity may reduce PTSD symptoms and recalibrate altered network dynamics. However, PCC connectivity to the DMN and SN during PCC-targeted fMRI neurofeedback remains unexamined and may help to elucidate neurophysiological mechanisms through which these symptom improvements may occur. METHODS Using a trauma/emotion provocation paradigm, we investigated psychophysiological interactions over a single session of neurofeedback among PTSD (n = 14) and healthy control (n = 15) participants. We compared PCC functional connectivity between regulate (in which participants downregulated PCC activity) and view (in which participants did not exert regulatory control) conditions across the whole-brain as well as in a priori specified regions-of-interest. RESULTS During regulate as compared to view conditions, only the PTSD group showed significant PCC connectivity with anterior DMN (dmPFC, vmPFC) and SN (posterior insula) regions, whereas both groups displayed PCC connectivity with other posterior DMN areas (precuneus/cuneus). Additionally, as compared with controls, the PTSD group showed significantly greater PCC connectivity with the SN (amygdala) during regulate as compared to view conditions. Moreover, linear regression analyses revealed that during regulate as compared to view conditions, PCC connectivity to DMN and SN regions was positively correlated to psychiatric symptoms across all participants. CONCLUSION In summary, observations of PCC connectivity to the DMN and SN provide emerging evidence of neural mechanisms underlying PCC-targeted fMRI neurofeedback among individuals with PTSD. This supports the use of PCC-targeted neurofeedback as a means by which to recalibrate PTSD-associated alterations in neural connectivity within the DMN and SN, which together, may help to facilitate improved emotion regulation abilities in PTSD.
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Affiliation(s)
- Jonathan M Lieberman
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada.,Imaging, Lawson Health Research Institute, London, Ontario, Canada
| | - Daniela Rabellino
- Imaging, Lawson Health Research Institute, London, Ontario, Canada.,Department of Neuroscience, Western University, London, Ontario, Canada
| | - Maria Densmore
- Imaging, Lawson Health Research Institute, London, Ontario, Canada.,Department of Psychiatry, Western University, London, Ontario, Canada
| | - Paul A Frewen
- Department of Neuroscience, Western University, London, Ontario, Canada.,Department of Psychology, Western University, London, Ontario, Canada
| | - David Steyrl
- Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Vienna, Austria
| | - Frank Scharnowski
- Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Vienna, Austria
| | - Jean Théberge
- Imaging, Lawson Health Research Institute, London, Ontario, Canada.,Department of Psychiatry, Western University, London, Ontario, Canada.,Department of Medical Biophysics, Western University, London, Ontario, Canada.,Department of Diagnostic Imaging, St. Joseph's Healthcare, London, Ontario, Canada
| | - Richard W J Neufeld
- Department of Neuroscience, Western University, London, Ontario, Canada.,Department of Psychiatry, Western University, London, Ontario, Canada.,Department of Psychology, Western University, London, Ontario, Canada.,Department of Psychology, University of British Columbia, Okanagan, Kelowna, British Columbia, Canada
| | - Christian Schmahl
- Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health Mannheim, Heidelberg University, Heidelberg, Germany
| | - Rakesh Jetly
- The Institute of Mental Health Research, University of Ottawa, Royal Ottawa Hospital, Ontario, Canada
| | - Sandhya Narikuzhy
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada
| | - Ruth A Lanius
- Imaging, Lawson Health Research Institute, London, Ontario, Canada.,Department of Neuroscience, Western University, London, Ontario, Canada.,Department of Psychiatry, Western University, London, Ontario, Canada.,Homewood Research Institute, Guelph, Ontario, Canada
| | - Andrew A Nicholson
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada.,Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Vienna, Austria.,Department of Medical Biophysics, Western University, London, Ontario, Canada.,The Institute of Mental Health Research, University of Ottawa, Royal Ottawa Hospital, Ontario, Canada.,Homewood Research Institute, Guelph, Ontario, Canada.,Atlas Institute for Veterans and Families, Ottawa, Ontario, Canada.,School of Psychology, University of Ottawa, Ottawa, Canada
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12
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Tröndle M, Popov T, Pedroni A, Pfeiffer C, Barańczuk-Turska Z, Langer N. Decomposing age effects in EEG alpha power. Cortex 2023; 161:116-144. [PMID: 36933455 DOI: 10.1016/j.cortex.2023.02.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 12/09/2022] [Accepted: 02/03/2023] [Indexed: 02/24/2023]
Abstract
Increasing life expectancy is prompting the need to understand how the brain changes during healthy aging. Research utilizing electroencephalography (EEG) has found that the power of alpha oscillations decrease from adulthood on. However, non-oscillatory (aperiodic) components in the data may confound results and thus require re-investigation of these findings. Thus, the present report analyzed a pilot and two additional independent samples (total N = 533) of resting-state EEG from healthy young and elderly individuals. A newly developed algorithm was utilized that allows the decomposition of the measured signal into periodic and aperiodic signal components. By using multivariate sequential Bayesian updating of the age effect in each signal component, evidence across the datasets was accumulated. It was hypothesized that previously reported age-related alpha power differences will largely diminish when total power is adjusted for the aperiodic signal component. First, the age-related decrease in total alpha power was replicated. Concurrently, decreases of the intercept and slope (i.e. exponent) of the aperiodic signal component were observed. Findings on aperiodic-adjusted alpha power indicated that this general shift of the power spectrum leads to an overestimation of the true age effects in conventional analyses of total alpha power. Thus, the importance of separating neural power spectra into periodic and aperiodic signal components is highlighted. However, also after accounting for these confounding factors, the sequential Bayesian updating analysis provided robust evidence that aging is associated with decreased aperiodic-adjusted alpha power. While the relation of the aperiodic component and aperiodic-adjusted alpha power to cognitive decline demands further investigation, the consistent findings on age effects across independent datasets and high test-retest reliabilities support that these newly emerging measures are reliable markers of the aging brain. Hence, previous interpretations of age-related decreases in alpha power are reevaluated, incorporating changes in the aperiodic signal.
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Affiliation(s)
- Marius Tröndle
- Department of Psychology, University of Zurich, Methods of Plasticity Research, Zurich, Switzerland; University Research Priority Program (URPP) Dynamics of Healthy Aging, Zurich, Switzerland; Neuroscience Center Zurich (ZNZ), Zurich, Switzerland.
| | - Tzvetan Popov
- Department of Psychology, University of Zurich, Methods of Plasticity Research, Zurich, Switzerland; University Research Priority Program (URPP) Dynamics of Healthy Aging, Zurich, Switzerland
| | - Andreas Pedroni
- Department of Psychology, University of Zurich, Methods of Plasticity Research, Zurich, Switzerland; University Research Priority Program (URPP) Dynamics of Healthy Aging, Zurich, Switzerland
| | - Christian Pfeiffer
- Department of Psychology, University of Zurich, Methods of Plasticity Research, Zurich, Switzerland
| | - Zofia Barańczuk-Turska
- Department of Psychology, University of Zurich, Methods of Plasticity Research, Zurich, Switzerland; University Research Priority Program (URPP) Dynamics of Healthy Aging, Zurich, Switzerland; Institute of Mathematics, University of Zurich, Switzerland
| | - Nicolas Langer
- Department of Psychology, University of Zurich, Methods of Plasticity Research, Zurich, Switzerland; University Research Priority Program (URPP) Dynamics of Healthy Aging, Zurich, Switzerland; Neuroscience Center Zurich (ZNZ), Zurich, Switzerland
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13
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Jia Y, Jariwala N, Hinkley LBN, Nagarajan S, Subramaniam K. Abnormal resting-state functional connectivity underlies cognitive and clinical symptoms in patients with schizophrenia. Front Hum Neurosci 2023; 17:1077923. [PMID: 36875232 PMCID: PMC9976937 DOI: 10.3389/fnhum.2023.1077923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Accepted: 01/31/2023] [Indexed: 02/17/2023] Open
Abstract
Introduction The cognitive and psychotic symptoms in patients with schizophrenia (SZ) are thought to result from disrupted brain network connectivity. Methods We capitalize on the high spatiotemporal resolution of magnetoencephalography imaging (MEG) to record spontaneous neuronal activity in resting state networks in 21 SZ compared with 21 healthy controls (HC). Results We found that SZ showed significant global disrupted functional connectivity in delta-theta (2-8 Hz), alpha (8-12 Hz), and beta (12-30 Hz) frequencies, compared to HC. Disrupted global connectivity in alpha frequencies with bilateral frontal cortices was associated with more severe clinical psychopathology (i.e., positive psychotic symptoms). Specifically, aberrant connectivity in beta frequencies between the left primary auditory cortex and cerebellum, was linked to greater hallucination severity in SZ. Disrupted connectivity in delta-theta frequencies between the medial frontal and left inferior frontal cortex was associated with impaired cognition. Discussion The multivariate techniques employed in the present study highlight the importance of applying our source reconstruction techniques which leverage the high spatial localization abilities of MEG for estimating neural source activity using beamforming methods such as SAM (synthetic aperture morphometry) to reconstruct the source of brain activity, together with functional connectivity assessments, assayed with imaginary coherence metrics, to delineate how neurophysiological dysconnectivity in specific oscillatory frequencies between distinct regions underlie the cognitive and psychotic symptoms in SZ. The present findings employ powerful techniques in spatial and time-frequency domains to provide potential neural biomarkers underlying neuronal network dysconnectivity in SZ that will inform the development of innovations in future neuromodulation treatment development.
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Affiliation(s)
- Yingxin Jia
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Namasvi Jariwala
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Leighton B. N. Hinkley
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Srikantan Nagarajan
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Karuna Subramaniam
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, United States
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14
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Jia Y, Kudo K, Hinkley LBN, Fisher M, Vinogradov S, Nagarajan S, Subramaniam K. Abnormal Information Flow in Schizophrenia Is Linked to Psychosis. Schizophr Bull 2022; 48:1384-1393. [PMID: 36073155 PMCID: PMC9673273 DOI: 10.1093/schbul/sbac075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND AND HYPOTHESIS Prior research has shown that patients with schizophrenia (SZ) show disruption in brain network connectivity that is thought to underlie their cognitive and psychotic symptoms. However, most studies examining functional network disruption in schizophrenia have focused on the temporally correlated coupling of the strength of network connections. Here, we move beyond correlative metrics to assay causal computations of connectivity changes in directed neural information flow, assayed from a neural source to a target in SZ. STUDY DESIGN This study describes a whole-brain magnetoencephalography-imaging approach to examine causal computations of connectivity changes in directed neural information flow between brain regions during resting states, quantified by phase-transfer entropy (PTE) metrics, assayed from a neural source to an endpoint, in 21 SZ compared with 21 healthy controls (HC), and associations with cognitive and clinical psychotic symptoms in SZ. STUDY RESULTS We found that SZ showed significant disruption in information flow in alpha (8-12 Hz) and beta (12-30 Hz) frequencies, compared to HC. Reduced information flow in alpha frequencies from the precuneus to the medio-ventral occipital cortex was associated with more severe clinical psychopathology (ie, positive psychotic symptoms), while reduced information flow between insula and middle temporal gyrus was associated with worsening cognitive symptoms. CONCLUSIONS The present findings highlight the importance of delineating dysfunction in neural information flow in specific oscillatory frequencies between distinct regions that underlie the cognitive and psychotic symptoms in SZ, and provide potential neural biomarkers that could lead to innovations in future neuromodulation treatment development.
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Affiliation(s)
- Yingxin Jia
- Department of Radiology and Biomedical Imaging, University of California, San, Francisco, CA 94143, USA
| | - Kiwamu Kudo
- Department of Radiology and Biomedical Imaging, University of California, San, Francisco, CA 94143, USA
- Medical Imaging Business Center, Ricoh Company, Ltd., Kanazawa, Japan
| | - Leighton B N Hinkley
- Department of Radiology and Biomedical Imaging, University of California, San, Francisco, CA 94143, USA
| | - Melissa Fisher
- Department of Psychiatry, University of Minnesota, Minneapolis, MN 55454, USA
| | - Sophia Vinogradov
- Department of Psychiatry, University of Minnesota, Minneapolis, MN 55454, USA
| | - Srikantan Nagarajan
- Department of Radiology and Biomedical Imaging, University of California, San, Francisco, CA 94143, USA
| | - Karuna Subramaniam
- Department of Psychiatry, University of California, San Francisco, CA 94143, USA
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15
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Huang Y, Deng Y, Jiang X, Chen Y, Mao T, Xu Y, Jiang C, Rao H. Resting-state occipito-frontal alpha connectome is linked to differential word learning ability in adult learners. Front Neurosci 2022; 16:953315. [PMID: 36188469 PMCID: PMC9521374 DOI: 10.3389/fnins.2022.953315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 08/18/2022] [Indexed: 11/19/2022] Open
Abstract
Adult language learners show distinct abilities in acquiring a new language, yet the underlying neural mechanisms remain elusive. Previous studies suggested that resting-state brain connectome may contribute to individual differences in learning ability. Here, we recorded electroencephalography (EEG) in a large cohort of 106 healthy young adults (50 males) and examined the associations between resting-state alpha band (8–12 Hz) connectome and individual learning ability during novel word learning, a key component of new language acquisition. Behavioral data revealed robust individual differences in the performance of the novel word learning task, which correlated with their performance in the language aptitude test. EEG data showed that individual resting-state alpha band coherence between occipital and frontal regions positively correlated with differential word learning performance (p = 0.001). The significant positive correlations between resting-state occipito-frontal alpha connectome and differential world learning ability were replicated in an independent cohort of 35 healthy adults. These findings support the key role of occipito-frontal network in novel word learning and suggest that resting-state EEG connectome may be a reliable marker for individual ability during new language learning.
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Affiliation(s)
- Yan Huang
- Center for Magnetic Resonance Imaging Research, Key Laboratory of Applied Brain and Cognitive Sciences, Shanghai International Studies University, Shanghai, China
- School of Foreign Languages, East China University of Science and Technology, Shanghai, China
- Institute of Linguistics, Shanghai International Studies University, Shanghai, China
| | - Yao Deng
- Center for Magnetic Resonance Imaging Research, Key Laboratory of Applied Brain and Cognitive Sciences, Shanghai International Studies University, Shanghai, China
| | - Xiaoming Jiang
- Institute of Linguistics, Shanghai International Studies University, Shanghai, China
| | - Yiyuan Chen
- Center for Magnetic Resonance Imaging Research, Key Laboratory of Applied Brain and Cognitive Sciences, Shanghai International Studies University, Shanghai, China
- Institute of Linguistics, Shanghai International Studies University, Shanghai, China
| | - Tianxin Mao
- Center for Magnetic Resonance Imaging Research, Key Laboratory of Applied Brain and Cognitive Sciences, Shanghai International Studies University, Shanghai, China
| | - Yong Xu
- Center for Magnetic Resonance Imaging Research, Key Laboratory of Applied Brain and Cognitive Sciences, Shanghai International Studies University, Shanghai, China
| | - Caihong Jiang
- Center for Magnetic Resonance Imaging Research, Key Laboratory of Applied Brain and Cognitive Sciences, Shanghai International Studies University, Shanghai, China
| | - Hengyi Rao
- Center for Magnetic Resonance Imaging Research, Key Laboratory of Applied Brain and Cognitive Sciences, Shanghai International Studies University, Shanghai, China
- Institute of Linguistics, Shanghai International Studies University, Shanghai, China
- Center for Functional Neuroimaging, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
- *Correspondence: Hengyi Rao,
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16
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Trambaiolli LR, Cassani R, Biazoli CE, Cravo AM, Sato JR, Falk TH. Multimodal resting-state connectivity predicts affective neurofeedback performance. Front Hum Neurosci 2022; 16:977776. [PMID: 36158618 PMCID: PMC9493361 DOI: 10.3389/fnhum.2022.977776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 08/03/2022] [Indexed: 11/13/2022] Open
Abstract
Neurofeedback has been suggested as a potential complementary therapy to different psychiatric disorders. Of interest for this approach is the prediction of individual performance and outcomes. In this study, we applied functional connectivity-based modeling using electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) modalities to (i) investigate whether resting-state connectivity predicts performance during an affective neurofeedback task and (ii) evaluate the extent to which predictive connectivity profiles are correlated across EEG and fNIRS techniques. The fNIRS oxyhemoglobin and deoxyhemoglobin concentrations and the EEG beta and gamma bands modulated by the alpha frequency band (beta-m-alpha and gamma-m-alpha, respectively) recorded over the frontal cortex of healthy subjects were used to estimate functional connectivity from each neuroimaging modality. For each connectivity matrix, relevant edges were selected in a leave-one-subject-out procedure, summed into "connectivity summary scores" (CSS), and submitted as inputs to a support vector regressor (SVR). Then, the performance of the left-out-subject was predicted using the trained SVR model. Linear relationships between the CSS across both modalities were evaluated using Pearson's correlation. The predictive model showed a mean absolute error smaller than 20%, and the fNIRS oxyhemoglobin CSS was significantly correlated with the EEG gamma-m-alpha CSS (r = -0.456, p = 0.030). These results support that pre-task electrophysiological and hemodynamic resting-state connectivity are potential predictors of neurofeedback performance and are meaningfully coupled. This investigation motivates the use of joint EEG-fNIRS connectivity as outcome predictors, as well as a tool for functional connectivity coupling investigation.
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Affiliation(s)
- Lucas R. Trambaiolli
- Basic Neuroscience Division, McLean Hospital–Harvard Medical School, Belmont, MA, United States
| | - Raymundo Cassani
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Claudinei E. Biazoli
- Center for Mathematics, Computing and Cognition, Federal University of ABC, São Bernardo do Campo, Brazil
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, United Kingdom
| | - André M. Cravo
- Center for Mathematics, Computing and Cognition, Federal University of ABC, São Bernardo do Campo, Brazil
| | - João R. Sato
- Center for Mathematics, Computing and Cognition, Federal University of ABC, São Bernardo do Campo, Brazil
- Big Data, Hospital Israelita Albert Einstein, São Paulo, Brazil
| | - Tiago H. Falk
- Institut National de la Recherche Scientifique, University of Quebec, Montreal, QC, Canada
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17
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Das A, de Los Angeles C, Menon V. Electrophysiological foundations of the human default-mode network revealed by intracranial-EEG recordings during resting-state and cognition. Neuroimage 2022; 250:118927. [PMID: 35074503 PMCID: PMC8928656 DOI: 10.1016/j.neuroimage.2022.118927] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 01/18/2022] [Accepted: 01/20/2022] [Indexed: 12/01/2022] Open
Abstract
Investigations using noninvasive functional magnetic resonance imaging (fMRI) have provided significant insights into the unique functional organization and profound importance of the human default mode network (DMN), yet these methods are limited in their ability to resolve network dynamics across multiple timescales. Electrophysiological techniques are critical to address these challenges, yet few studies have explored the neurophysiological underpinnings of the DMN. Here we investigate the electrophysiological organization of the DMN in a common large-scale network framework consistent with prior fMRI studies. We used intracranial EEG (iEEG) recordings, and evaluated intra- and cross-network interactions during resting-state and its modulation during a cognitive task involving episodic memory formation. Our analysis revealed significantly greater intra-DMN phase iEEG synchronization in the slow-wave (< 4 Hz), while DMN interactions with other brain networks was higher in the beta (12-30 Hz) and gamma (30-80 Hz) bands. Crucially, slow-wave intra-DMN synchronization was observed in the task-free resting-state and during both verbal memory encoding and recall. Compared to resting-state, slow-wave intra-DMN phase synchronization was significantly higher during both memory encoding and recall. Slow-wave intra-DMN phase synchronization increased during successful memory retrieval, highlighting its behavioral relevance. Finally, analysis of nonlinear dynamic causal interactions revealed that the DMN is a causal outflow network during both memory encoding and recall. Our findings identify frequency specific neurophysiological signatures of the DMN which allow it to maintain stability and flexibility, intrinsically and during task-based cognition, provide novel insights into the electrophysiological foundations of the human DMN, and elucidate network mechanisms by which it supports cognition.
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Affiliation(s)
- Anup Das
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305 USA.
| | - Carlo de Los Angeles
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305 USA
| | - Vinod Menon
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305 USA; Department of Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94305 USA; Stanford Neurosciences Institute, Stanford University School of Medicine, Stanford, CA 94305 USA.
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18
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Lu R, Xi J, Zhang X, Shi J. High fluid intelligence is characterized by flexible allocation of attentional resources: Evidence from EEG. Neuropsychologia 2022; 164:108094. [PMID: 34822859 DOI: 10.1016/j.neuropsychologia.2021.108094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 11/17/2021] [Accepted: 11/21/2021] [Indexed: 11/19/2022]
Abstract
Recently, the integrated control hypothesis (Lu et al., 2020) was proposed to explain the relationship between fluid intelligence (Gf) and attentional resource allocation. This hypothesis suggested that individuals with higher Gf tend to flexibly and adaptively allocate their limited resources according to the task type and task difficulty rather than simply exert more or fewer resources in any condition. To examine this hypothesis, the present study used electroencephalogram (EEG) indicators (i.e., frontal theta-ERS and parietal-occipital alpha-ERD) as the measurements of participants' resource allocation during the exploration task and exploitation task with different difficulties. The results found that higher Gf individuals tend to allocate fewer resources in all difficulty levels in the exploitation task compared to average Gf participants. In contrast, in the exploration task, higher Gf participants would allocate more resources in the medium- and high-difficulty levels than average Gf participants, but this phenomenon was only found in males. These findings provided supportive evidence for the integrated control hypothesis that flexible and adaptive attentional control ability are important characteristics of human intelligence.
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Affiliation(s)
- Runhao Lu
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China; MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, UK
| | - Jie Xi
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xingli Zhang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Jiannong Shi
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
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19
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Transcranial stimulation of alpha oscillations up-regulates the default mode network. Proc Natl Acad Sci U S A 2022; 119:2110868119. [PMID: 34969856 PMCID: PMC8740757 DOI: 10.1073/pnas.2110868119] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/12/2021] [Indexed: 12/26/2022] Open
Abstract
The default mode network (DMN) is the most-prominent intrinsic connectivity network, serving as a key architecture of the brain's functional organization. Conversely, dysregulated DMN is characteristic of major neuropsychiatric disorders. However, the field still lacks mechanistic insights into the regulation of the DMN and effective interventions for DMN dysregulation. The current study approached this problem by manipulating neural synchrony, particularly alpha (8 to 12 Hz) oscillations, a dominant intrinsic oscillatory activity that has been increasingly associated with the DMN in both function and physiology. Using high-definition alpha-frequency transcranial alternating current stimulation (α-tACS) to stimulate the cortical source of alpha oscillations, in combination with simultaneous electroencephalography and functional MRI (EEG-fMRI), we demonstrated that α-tACS (versus Sham control) not only augmented EEG alpha oscillations but also strengthened fMRI and (source-level) alpha connectivity within the core of the DMN. Importantly, increase in alpha oscillations mediated the DMN connectivity enhancement. These findings thus identify a mechanistic link between alpha oscillations and DMN functioning. That transcranial alpha modulation can up-regulate the DMN further highlights an effective noninvasive intervention to normalize DMN functioning in various disorders.
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20
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Nicholson AA, Rabellino D, Densmore M, Frewen PA, Steryl D, Scharnowski F, Théberge J, Neufeld RWJ, Schmahl C, Jetly R, Lanius RA. Differential mechanisms of posterior cingulate cortex downregulation and symptom decreases in posttraumatic stress disorder and healthy individuals using real-time fMRI neurofeedback. Brain Behav 2022; 12:e2441. [PMID: 34921746 PMCID: PMC8785646 DOI: 10.1002/brb3.2441] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 10/25/2021] [Accepted: 11/09/2021] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Intrinsic connectivity networks, including the default mode network (DMN), are frequently disrupted in individuals with posttraumatic stress disorder (PTSD). The posterior cingulate cortex (PCC) is the main hub of the posterior DMN, where the therapeutic regulation of this region with real-time fMRI neurofeedback (NFB) has yet to be explored. METHODS We investigated PCC downregulation while processing trauma/stressful words over 3 NFB training runs and a transfer run without NFB (total n = 29, PTSD n = 14, healthy controls n = 15). We also examined the predictive accuracy of machine learning models in classifying PTSD versus healthy controls during NFB training. RESULTS Both the PTSD and healthy control groups demonstrated reduced reliving symptoms in response to trauma/stressful stimuli, where the PTSD group additionally showed reduced symptoms of distress. We found that both groups were able to downregulate the PCC with similar success over NFB training and in the transfer run, although downregulation was associated with unique within-group decreases in activation within the bilateral dmPFC, bilateral postcentral gyrus, right amygdala/hippocampus, cingulate cortex, and bilateral temporal pole/gyri. By contrast, downregulation was associated with increased activation in the right dlPFC among healthy controls as compared to PTSD. During PCC downregulation, right dlPFC activation was negatively correlated to PTSD symptom severity scores and difficulties in emotion regulation. Finally, machine learning algorithms were able to classify PTSD versus healthy participants based on brain activation during NFB training with 80% accuracy. CONCLUSIONS This is the first study to investigate PCC downregulation with real-time fMRI NFB in both PTSD and healthy controls. Our results reveal acute decreases in symptoms over training and provide converging evidence for EEG-NFB targeting brain networks linked to the PCC.
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Affiliation(s)
- Andrew A Nicholson
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada.,Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Vienna, Austria
| | - Daniela Rabellino
- Department of Neuroscience, Western University, London, Ontario, Canada.,Imaging, Lawson Health Research Institute, London, Ontario, Canada
| | - Maria Densmore
- Imaging, Lawson Health Research Institute, London, Ontario, Canada.,Department of Psychiatry, Western University, London, Ontario, Canada
| | - Paul A Frewen
- Department of Neuroscience, Western University, London, Ontario, Canada.,Department of Psychology, Western University, London, Ontario, Canada
| | - David Steryl
- Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Vienna, Austria
| | - Frank Scharnowski
- Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Vienna, Austria
| | - Jean Théberge
- Imaging, Lawson Health Research Institute, London, Ontario, Canada.,Department of Medical Biophysics, Western University, London, Ontario, Canada.,Department of Psychiatry, Western University, London, Ontario, Canada.,Department of Diagnostic Imaging, St. Joseph's Healthcare, London, Ontario, Canada
| | - Richard W J Neufeld
- Department of Neuroscience, Western University, London, Ontario, Canada.,Department of Psychology, Western University, London, Ontario, Canada.,Department of Psychiatry, Western University, London, Ontario, Canada.,Department of Psychology, University of British Columbia, Okanagan, Kelowna, British Columbia, Canada
| | - Christian Schmahl
- Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health Mannheim, Heidelberg University, Heidelberg, Germany
| | - Rakesh Jetly
- Canadian Forces, Health Services, Ottawa, Ontario, Canada
| | - Ruth A Lanius
- Department of Neuroscience, Western University, London, Ontario, Canada.,Imaging, Lawson Health Research Institute, London, Ontario, Canada.,Department of Psychiatry, Western University, London, Ontario, Canada
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21
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du Bois N, Bigirimana AD, Korik A, Kéthina LG, Rutembesa E, Mutabaruka J, Mutesa L, Prasad G, Jansen S, Coyle DH. Neurofeedback with low-cost, wearable electroencephalography (EEG) reduces symptoms in chronic Post-Traumatic Stress Disorder. J Affect Disord 2021; 295:1319-1334. [PMID: 34706446 DOI: 10.1016/j.jad.2021.08.071] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Revised: 07/19/2021] [Accepted: 08/25/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND The study examines the effectiveness of both neurofeedback and motor-imagery brain-computer interface (BCI) training, which promotes self-regulation of brain activity, using low-cost electroencephalography (EEG)-based wearable neurotechnology outside a clinical setting, as a potential treatment for post-traumatic stress disorder (PTSD) in Rwanda. METHODS Participants received training/treatment sessions along with a pre- and post- intervention clinical assessment, (N = 29; control n = 9, neurofeedback (NF, 7 sessions) n = 10, and motor-imagery (MI, 6 sessions) n = 10). Feedback was presented visually via a videogame. Participants were asked to regulate (NF) or intentionally modulate (MI) brain activity to affect/control the game. RESULTS The NF group demonstrated an increase in resting-state alpha 8-12 Hz bandpower following individual training sessions, termed alpha 'rebound' (Pz channel, p = 0.025, all channels, p = 0.024), consistent with previous research findings. This alpha 'rebound', unobserved in the MI group, produced a clinically relevant reduction in symptom severity in NF group, as revealed in three of seven clinical outcome measures: PCL-5 (p = 0.005), PTSD screen (p = 0.005), and HTQ (p = 0.005). LIMITATIONS Data collection took place in environments that posed difficulties in controlling environmental factors. Nevertheless, this limitation improves ecological validity, as neurotechnology treatments must be deployable outside controlled environments, to be a feasible technological treatment. CONCLUSIONS The study produced the first evidence to support a low-cost, neurotechnological solution for neurofeedback as an effective treatment of PTSD for victims of acute trauma in conflict zones in a developing country.
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Affiliation(s)
- N du Bois
- Intelligent Systems Research Centre, Ulster University (UU), Magee Campus, NI, United Kingdom
| | - A D Bigirimana
- Intelligent Systems Research Centre, Ulster University (UU), Magee Campus, NI, United Kingdom
| | - A Korik
- Intelligent Systems Research Centre, Ulster University (UU), Magee Campus, NI, United Kingdom
| | - L Gaju Kéthina
- Department of Clinical Psychology, College of Medicine and Health Sciences, University of Rwanda (UR), Huye, Rwanda
| | - E Rutembesa
- Department of Clinical Psychology, College of Medicine and Health Sciences, University of Rwanda (UR), Huye, Rwanda
| | - J Mutabaruka
- Department of Clinical Psychology, College of Medicine and Health Sciences, University of Rwanda (UR), Huye, Rwanda
| | - L Mutesa
- Centre for Human Genetics, School of Medicine and Pharmacy, College of Medicine and Health Sciences, University of Rwanda (UR), Huye, Rwanda
| | - G Prasad
- Intelligent Systems Research Centre, Ulster University (UU), Magee Campus, NI, United Kingdom
| | - S Jansen
- Department of Clinical Psychology, College of Medicine and Health Sciences, University of Rwanda (UR), Huye, Rwanda
| | - D H Coyle
- Intelligent Systems Research Centre, Ulster University (UU), Magee Campus, NI, United Kingdom.
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22
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Daniel Arzate-Mena J, Abela E, Olguín-Rodríguez PV, Ríos-Herrera W, Alcauter S, Schindler K, Wiest R, Müller MF, Rummel C. Stationary EEG pattern relates to large-scale resting state networks - An EEG-fMRI study connecting brain networks across time-scales. Neuroimage 2021; 246:118763. [PMID: 34863961 DOI: 10.1016/j.neuroimage.2021.118763] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Revised: 11/17/2021] [Accepted: 11/24/2021] [Indexed: 11/25/2022] Open
Abstract
Relating brain dynamics acting on time scales that differ by at least an order of magnitude is a fundamental issue in brain research. The same is true for the observation of stable dynamical structures in otherwise highly non-stationary signals. The present study addresses both problems by the analysis of simultaneous resting state EEG-fMRI recordings of 53 patients with epilepsy. Confirming previous findings, we observe a generic and temporally stable average correlation pattern in EEG recordings. We design a predictor for the General Linear Model describing fluctuations around the stationary EEG correlation pattern and detect resting state networks in fMRI data. The acquired statistical maps are contrasted to several surrogate tests and compared with maps derived by spatial Independent Component Analysis of the fMRI data. By means of the proposed EEG-predictor we observe core nodes of known fMRI resting state networks with high specificity in the default mode, the executive control and the salience network. Our results suggest that both, the stationary EEG pattern as well as resting state fMRI networks are different expressions of the same brain activity. This activity is interpreted as the dynamics on (or close to) a stable attractor in phase space that is necessary to maintain the brain in an efficient operational mode. We discuss that this interpretation is congruent with the theoretical framework of complex systems as well as with the brain's energy balance.
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Affiliation(s)
- J Daniel Arzate-Mena
- Instituto de Investigación en Ciencias Básicas y Aplicadas, Universidad Autónoma del Estado de Morelos,Cuernavaca Morelos, Mexico
| | - Eugenio Abela
- Center for Neuropsychiatrics, Psychiatric Services Aargau AG, Windisch, Switzerland
| | | | - Wady Ríos-Herrera
- Facultad de Psicología Universidad Nacional Autónoma de México, Mexico City, Mexico; Centro de Ciencias de la Complejidad (C3), Universisdad Nacional Autónoma de México, Mexico City 04510, Mexico
| | - Sarael Alcauter
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, México
| | - Kaspar Schindler
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging, University Institute for Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Markus F Müller
- Centro de Investigación en Ciencias, Universidad Autónoma del Estado de Morelos (UAEM), Cuernavaca, Morelos, Mexico; Centro de Ciencias de la Complejidad (C3), Universisdad Nacional Autónoma de México, Mexico City 04510, Mexico; Centro Internacional de Ciencias A. C., Cuernavaca, México
| | - Christian Rummel
- Support Center for Advanced Neuroimaging, University Institute for Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
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23
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Babaeeghazvini P, Rueda-Delgado LM, Gooijers J, Swinnen SP, Daffertshofer A. Brain Structural and Functional Connectivity: A Review of Combined Works of Diffusion Magnetic Resonance Imaging and Electro-Encephalography. Front Hum Neurosci 2021; 15:721206. [PMID: 34690718 PMCID: PMC8529047 DOI: 10.3389/fnhum.2021.721206] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Accepted: 09/10/2021] [Indexed: 11/13/2022] Open
Abstract
Implications of structural connections within and between brain regions for their functional counterpart are timely points of discussion. White matter microstructural organization and functional activity can be assessed in unison. At first glance, however, the corresponding findings appear variable, both in the healthy brain and in numerous neuro-pathologies. To identify consistent associations between structural and functional connectivity and possible impacts for the clinic, we reviewed the literature of combined recordings of electro-encephalography (EEG) and diffusion-based magnetic resonance imaging (MRI). It appears that the strength of event-related EEG activity increases with increased integrity of structural connectivity, while latency drops. This agrees with a simple mechanistic perspective: the nature of microstructural white matter influences the transfer of activity. The EEG, however, is often assessed for its spectral content. Spectral power shows associations with structural connectivity that can be negative or positive often dependent on the frequencies under study. Functional connectivity shows even more variations, which are difficult to rank. This might be caused by the diversity of paradigms being investigated, from sleep and resting state to cognitive and motor tasks, from healthy participants to patients. More challenging, though, is the potential dependency of findings on the kind of analysis applied. While this does not diminish the principal capacity of EEG and diffusion-based MRI co-registration, it highlights the urgency to standardize especially EEG analysis.
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Affiliation(s)
- Parinaz Babaeeghazvini
- Department of Human Movements Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Science Institute (AMS), Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Institute for Brain and Behaviour Amsterdam (iBBA), Faculty of Behavioural and Movement Sciences, Vrije Universiteit, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Laura M. Rueda-Delgado
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, KU Leuven, Leuven, Belgium
- Trinity Centre for Biomedical Engineering, Trinity College Dublin, The University of Dublin, Dublin, Ireland
| | - Jolien Gooijers
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, KU Leuven, Leuven, Belgium
- KU Leuven Brain Institute (LBI), Leuven, Belgium
| | - Stephan P. Swinnen
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, KU Leuven, Leuven, Belgium
- KU Leuven Brain Institute (LBI), Leuven, Belgium
| | - Andreas Daffertshofer
- Department of Human Movements Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Science Institute (AMS), Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Institute for Brain and Behaviour Amsterdam (iBBA), Faculty of Behavioural and Movement Sciences, Vrije Universiteit, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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24
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Kutafina E, Heiligers A, Popovic R, Brenner A, Hankammer B, Jonas SM, Mathiak K, Zweerings J. Tracking of Mental Workload with a Mobile EEG Sensor. SENSORS 2021; 21:s21155205. [PMID: 34372445 PMCID: PMC8348794 DOI: 10.3390/s21155205] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 07/23/2021] [Accepted: 07/28/2021] [Indexed: 12/04/2022]
Abstract
The aim of the present investigation was to assess if a mobile electroencephalography (EEG) setup can be used to track mental workload, which is an important aspect of learning performance and motivation and may thus represent a valuable source of information in the evaluation of cognitive training approaches. Twenty five healthy subjects performed a three-level N-back test using a fully mobile setup including tablet-based presentation of the task and EEG data collection with a self-mounted mobile EEG device at two assessment time points. A two-fold analysis approach was chosen including a standard analysis of variance and an artificial neural network to distinguish the levels of cognitive load. Our findings indicate that the setup is feasible for detecting changes in cognitive load, as reflected by alterations across lobes in different frequency bands. In particular, we observed a decrease of occipital alpha and an increase in frontal, parietal and occipital theta with increasing cognitive load. The most distinct levels of cognitive load could be discriminated by the integrated machine learning models with an accuracy of 86%.
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Affiliation(s)
- Ekaterina Kutafina
- Institute of Medical Informatics, Medical Faculty, RWTH Aachen University, 52074 Aachen, Germany; (R.P.); (B.H.)
- Faculty of Applied Mathematics, AGH University of Science and Technology, 30-059 Krakow, Poland
- Correspondence:
| | - Anne Heiligers
- Department of Psychiatry, Psychotherapy and Psychosomatics, School of Medicine, RWTH Aachen University, 52074 Aachen, Germany; (A.H.); (K.M.); (J.Z.)
| | - Radomir Popovic
- Institute of Medical Informatics, Medical Faculty, RWTH Aachen University, 52074 Aachen, Germany; (R.P.); (B.H.)
| | - Alexander Brenner
- Institute of Medical Informatics, University of Münster, 48149 Münster, Germany;
| | - Bernd Hankammer
- Institute of Medical Informatics, Medical Faculty, RWTH Aachen University, 52074 Aachen, Germany; (R.P.); (B.H.)
| | - Stephan M. Jonas
- Department of Informatics, Technical University of Munich, 85748 Garching, Germany;
| | - Klaus Mathiak
- Department of Psychiatry, Psychotherapy and Psychosomatics, School of Medicine, RWTH Aachen University, 52074 Aachen, Germany; (A.H.); (K.M.); (J.Z.)
| | - Jana Zweerings
- Department of Psychiatry, Psychotherapy and Psychosomatics, School of Medicine, RWTH Aachen University, 52074 Aachen, Germany; (A.H.); (K.M.); (J.Z.)
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25
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Li F, Jiang L, Liao Y, Si Y, Yi C, Zhang Y, Zhu X, Yang Z, Yao D, Cao Z, Xu P. Brain variability in dynamic resting-state networks identified by fuzzy entropy: a scalp EEG study. J Neural Eng 2021; 18. [PMID: 34153948 DOI: 10.1088/1741-2552/ac0d41] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 06/21/2021] [Indexed: 11/12/2022]
Abstract
Objective.Exploring the temporal variability in spatial topology during the resting state attracts growing interest and becomes increasingly useful to tackle the cognitive process of brain networks. In particular, the temporal brain dynamics during the resting state may be delineated and quantified aligning with cognitive performance, but few studies investigated the temporal variability in the electroencephalogram (EEG) network as well as its relationship with cognitive performance.Approach.In this study, we proposed an EEG-based protocol to measure the nonlinear complexity of the dynamic resting-state network by applying the fuzzy entropy. To further validate its applicability, the fuzzy entropy was applied into simulated and two independent datasets (i.e. decision-making and P300).Main results.The simulation study first proved that compared to the existing methods, this approach could not only exactly capture the pattern dynamics in time series but also overcame the magnitude effect of time series. Concerning the two EEG datasets, the flexible and robust network architectures of the brain cortex at rest were identified and distributed at the bilateral temporal lobe and frontal/occipital lobe, respectively, whose variability metrics were found to accurately classify different groups. Moreover, the temporal variability of resting-state network property was also either positively or negatively related to individual cognitive performance.Significance.This outcome suggested the potential of fuzzy entropy for evaluating the temporal variability of the dynamic resting-state brain networks, and the fuzzy entropy is also helpful for uncovering the fluctuating network variability that accounts for the individual decision differences.
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Affiliation(s)
- Fali Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Lin Jiang
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Yuanyuan Liao
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Yajing Si
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China.,School of Psychology, Xinxiang Medical University, Xinxiang 453003, People's Republic of China
| | - Chanli Yi
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Yangsong Zhang
- School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang 621010, People's Republic of China
| | - Xianjun Zhu
- The Sichuan Provincial Key Laboratory for Human Disease Gene Study, Prenatal Diagnosis Center, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.,Research Unit for Blindness Prevention of Chinese Academy of Medical Sciences (2019RU026), Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, People's Republic of China
| | - Zhenglin Yang
- The Sichuan Provincial Key Laboratory for Human Disease Gene Study, Prenatal Diagnosis Center, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.,Research Unit for Blindness Prevention of Chinese Academy of Medical Sciences (2019RU026), Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, People's Republic of China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Zehong Cao
- Discipline of Information and Communication Technology, University of Tasmania, TAS, Australia
| | - Peng Xu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
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26
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Moore M, Maclin EL, Iordan AD, Katsumi Y, Larsen RJ, Bagshaw AP, Mayhew S, Shafer AT, Sutton BP, Fabiani M, Gratton G, Dolcos F. Proof-of-concept evidence for trimodal simultaneous investigation of human brain function. Hum Brain Mapp 2021; 42:4102-4121. [PMID: 34160860 PMCID: PMC8357002 DOI: 10.1002/hbm.25541] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 04/04/2021] [Accepted: 05/13/2021] [Indexed: 12/03/2022] Open
Abstract
The link between spatial (where) and temporal (when) aspects of the neural correlates of most psychological phenomena is not clear. Elucidation of this relation, which is crucial to fully understand human brain function, requires integration across multiple brain imaging modalities and cognitive tasks that reliably modulate the engagement of the brain systems of interest. By overcoming the methodological challenges posed by simultaneous recordings, the present report provides proof‐of‐concept evidence for a novel approach using three complementary imaging modalities: functional magnetic resonance imaging (fMRI), event‐related potentials (ERPs), and event‐related optical signals (EROS). Using the emotional oddball task, a paradigm that taps into both cognitive and affective aspects of processing, we show the feasibility of capturing converging and complementary measures of brain function that are not currently attainable using traditional unimodal or other multimodal approaches. This opens up unprecedented possibilities to clarify spatiotemporal integration of brain function.
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Affiliation(s)
- Matthew Moore
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Edward L Maclin
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Alexandru D Iordan
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA
| | - Yuta Katsumi
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Psychology, Northeastern University, Boston, Massachusetts, USA
| | - Ryan J Larsen
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Andrew P Bagshaw
- Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, UK
| | - Stephen Mayhew
- Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, UK
| | - Andrea T Shafer
- Centre for Neuroscience, University of Alberta, Alta., Canada; now at Laboratory of Behavioral Neuroscience, Brain Imaging and Behavior Section, National Institute on Aging, Baltimore, Maryland, USA
| | - Bradley P Sutton
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Monica Fabiani
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Psychology, University of Illinois at Urbana-Champaign, Champaign, Illinois, USA
| | - Gabriele Gratton
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Psychology, University of Illinois at Urbana-Champaign, Champaign, Illinois, USA
| | - Florin Dolcos
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Psychology, University of Illinois at Urbana-Champaign, Champaign, Illinois, USA
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27
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Kraus B, Salvador CE, Kamikubo A, Hsiao NC, Hu JF, Karasawa M, Kitayama S. Oscillatory alpha power at rest reveals an independent self: A cross-cultural investigation. Biol Psychol 2021; 163:108118. [PMID: 34019966 DOI: 10.1016/j.biopsycho.2021.108118] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 05/03/2021] [Accepted: 05/14/2021] [Indexed: 11/19/2022]
Abstract
In the current cultural psychology literature, it is commonly assumed that the personal self is cognitively more salient for those with an independent (vs. interdependent) self-construal (SC). So far, however, this assumption remains largely untested. Here, we drew on evidence that resting state alpha power (RSAP) reflects mental processes constituting the personal self, and tested whether RSAP is positively correlated with independent (vs. interdependent) SC. Study 1 tested European Americans and Taiwanese, whereas Study 2 tested European Americans and Japanese (total N = 164). A meta-analysis performed on the combined data confirmed a reliable association between independent (vs. interdependent) SC and RSAP. However, this association was only reliable when participants had their eyes closed. Even though European Americans were consistently more independent than East Asians, RSAP was no greater for European Americans than for East Asians. Our data helps explore a missing link in the theorizing of contemporary cultural psychology.
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Affiliation(s)
- Brian Kraus
- Northwestern University, Department of Psychology, United States.
| | | | - Aya Kamikubo
- Tokyo Woman's Christian University, Graduate School of Humanities and Sciences, Japan
| | - Nai-Ching Hsiao
- National Cheng Kung University, Department of Psychology, Taiwan
| | - Jon-Fan Hu
- National Cheng Kung University, Department of Psychology, Taiwan
| | - Mayumi Karasawa
- Tokyo Woman's Christian University, Department of Communication, Japan
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28
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Ghaderi AH, Jahan A, Akrami F, Moghadam Salimi M. Transcranial photobiomodulation changes topology, synchronizability, and complexity of resting state brain networks. J Neural Eng 2021; 18. [PMID: 33873167 DOI: 10.1088/1741-2552/abf97c] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Accepted: 04/19/2021] [Indexed: 02/06/2023]
Abstract
Objective. Transcranial photobiomodulation (tPBM) is a recently proposed non-invasive brain stimulation approach with various effects on the nervous system from the cells to the whole brain networks. Specially in the neural network level, tPBM can alter the topology and synchronizability of functional brain networks. However, the functional properties of the neural networks after tPBM are still poorly clarified.Approach. Here, we employed electroencephalography and different methods (conventional and spectral) in the graph theory analysis to track the significant effects of tPBM on the resting state brain networks. The non-parametric statistical analysis showed that just one short-term tPBM session over right medial frontal pole can significantly change both topological (i.e. clustering coefficient, global efficiency, local efficiency, eigenvector centrality) and dynamical (i.e. energy, largest eigenvalue, and entropy) features of resting state brain networks.Main results. The topological results revealed that tPBM can reduce local processing, centrality, and laterality. Furthermore, the increased centrality of central electrode was observed.Significance. These results suggested that tPBM can alter topology of resting state brain network to facilitate the neural information processing. On the other hand, the dynamical results showed that tPBM reduced stability of synchronizability and increased complexity in the resting state brain networks. These effects can be considered in association with the increased complexity of connectivity patterns among brain regions and the enhanced information propagation in the resting state brain networks. Overall, both topological and dynamical features of brain networks suggest that although tPBM decreases local processing (especially in the right hemisphere) and disrupts synchronizability of network, but it can increase the level of information transferring and processing in the brain network.
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Affiliation(s)
- Amir Hossein Ghaderi
- Centre for Vision Research, York University, Toronto, Canada.,Department of psychology, University of Calgary, Calgary, Canada.,Iranian Neurowave Lab, Isfahan, Iran
| | - Ali Jahan
- Department of Speech Therapy, Faculty of Rehabilitation Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Fatemeh Akrami
- Iranian Neurowave Lab, Isfahan, Iran.,Faculty of Health Management and Information, Iran University of Medical Science, Tehran, Iran
| | - Maryam Moghadam Salimi
- Department of Physical Therapy, Faculty of Rehabilitation Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
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29
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Fakhraei L, Francoeur M, Balasubramani PP, Tang T, Hulyalkar S, Buscher N, Mishra J, Ramanathan DS. Electrophysiological Correlates of Rodent Default-Mode Network Suppression Revealed by Large-Scale Local Field Potential Recordings. Cereb Cortex Commun 2021; 2:tgab034. [PMID: 34296178 PMCID: PMC8166125 DOI: 10.1093/texcom/tgab034] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Revised: 04/13/2021] [Accepted: 04/14/2021] [Indexed: 11/13/2022] Open
Abstract
The default-mode network (DMN) in humans consists of a set of brain regions that, as measured with functional magnetic resonance imaging (fMRI), show both intrinsic correlations with each other and suppression during externally oriented tasks. Resting-state fMRI studies have previously identified similar patterns of intrinsic correlations in overlapping brain regions in rodents (A29C/posterior cingulate cortex, parietal cortex, and medial temporal lobe structures). However, due to challenges with performing rodent behavior in an MRI machine, it is still unclear whether activity in rodent DMN regions are suppressed during externally oriented visual tasks. Using distributed local field potential measurements in rats, we have discovered that activity in DMN brain regions noted above show task-related suppression during an externally oriented visual task at alpha and low beta-frequencies. Interestingly, this suppression (particularly in posterior cingulate cortex) was linked with improved performance on the task. Using electroencephalography recordings from a similar task in humans, we identified a similar suppression of activity in posterior cingulate cortex at alpha/low beta-frequencies. Thus, we have identified a common electrophysiological marker of DMN suppression in both rodents and humans. This observation paves the way for future studies using rodents to probe circuit-level functioning of DMN function. SIGNIFICANCE Here we show that alpha/beta frequency oscillations in rats show key features of DMN activity, including intrinsic correlations between DMN brain regions, task-related suppression, and interference with attention/decision-making. We found similar task-related suppression at alpha/low beta-frequencies of DMN activity in humans.
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Affiliation(s)
- Leila Fakhraei
- Mental Health Service, VA San Diego Healthcare System., La Jolla, CA 92161, USA
- Department of Psychiatry, UC San Diego, La Jolla, CA 92093, USA
| | - Miranda Francoeur
- Mental Health Service, VA San Diego Healthcare System., La Jolla, CA 92161, USA
- Department of Psychiatry, UC San Diego, La Jolla, CA 92093, USA
| | | | - Tianzhi Tang
- Mental Health Service, VA San Diego Healthcare System., La Jolla, CA 92161, USA
- Department of Psychiatry, UC San Diego, La Jolla, CA 92093, USA
| | - Sidharth Hulyalkar
- Mental Health Service, VA San Diego Healthcare System., La Jolla, CA 92161, USA
- Department of Psychiatry, UC San Diego, La Jolla, CA 92093, USA
| | - Nathalie Buscher
- Mental Health Service, VA San Diego Healthcare System., La Jolla, CA 92161, USA
- Department of Psychiatry, UC San Diego, La Jolla, CA 92093, USA
| | - Jyoti Mishra
- Department of Psychiatry, UC San Diego, La Jolla, CA 92093, USA
| | - Dhakshin S Ramanathan
- Mental Health Service, VA San Diego Healthcare System., La Jolla, CA 92161, USA
- Department of Psychiatry, UC San Diego, La Jolla, CA 92093, USA
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Michels L, Riese F, Meyer R, Kälin AM, Leh SE, Unschuld PG, Luechinger R, Hock C, O'Gorman R, Kollias S, Gietl A. EEG-fMRI Signal Coupling Is Modulated in Subjects With Mild Cognitive Impairment and Amyloid Deposition. Front Aging Neurosci 2021; 13:631172. [PMID: 33967737 PMCID: PMC8104007 DOI: 10.3389/fnagi.2021.631172] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 03/10/2021] [Indexed: 12/13/2022] Open
Abstract
Cognitive impairment indicates disturbed brain physiology which can be due to various mechanisms including Alzheimer's pathology. Combined functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) recordings (EEG-fMRI) can assess the interplay between complementary measures of brain activity and EEG changes to be localized to specific brain regions. We used a two-step approach, where we first examined changes related to a syndrome of mild cognitive impairment irrespective of pathology and then studied the specific impact of amyloid pathology. After detailed clinical and neuropsychological characterization as well as a positron emission tomography (PET) scans with the tracer 11-[C]-Pittsburgh Compound B to estimate cerebral amyloid deposition, 14 subjects with mild cognitive impairment (MCI) (mean age 75.6 SD: 8.9) according to standard criteria and 21 cognitively healthy controls (HCS) (mean age 71.8 SD: 4.2) were assessed with EEG-fMRI. Thalamo-cortical alpha-fMRI signal coupling was only observed in HCS. Additional EEG-fMRI signal coupling differences between HCS and MCI were observed in parts of the default mode network, salience network, fronto-parietal network, and thalamus. Individuals with significant cerebral amyloid deposition (amyloid-positive MCI and HCS combined compared to amyloid-negative HCS) displayed abnormal EEG-fMRI signal coupling in visual, fronto-parietal regions but also in the parahippocampus, brain stem, and cerebellum. This finding was paralleled by stronger absolute fMRI signal in the parahippocampus and weaker absolute fMRI signal in the inferior frontal gyrus in amyloid-positive subjects. We conclude that the thalamocortical coupling in the alpha band in HCS more closely reflects previous findings observed in younger adults, while in MCI there is a clearly aberrant coupling in several networks dominated by an anticorrelation in the posterior cingulate cortex. While these findings may broadly indicate physiological changes in MCI, amyloid pathology was specifically associated with abnormal fMRI signal responses and disrupted coupling between brain oscillations and fMRI signal responses, which especially involve core regions of memory: the hippocampus, para-hippocampus, and lateral prefrontal cortex.
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Affiliation(s)
- Lars Michels
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, Zurich, Switzerland
| | - Florian Riese
- Department of Geriatric Psychiatry, Psychiatric University Hospital Zurich (PUK), Zurich, Switzerland.,University Research Priority Programs (URPP) ≪Dynamics of Healthy Aging≫, University of Zurich, Zurich, Switzerland
| | - Rafael Meyer
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Andrea M Kälin
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Sandra E Leh
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Paul G Unschuld
- Department of Geriatric Psychiatry, Psychiatric University Hospital Zurich (PUK), Zurich, Switzerland.,Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland.,Geriatric Psychiatry, Geneva University Hospitals (HUG), Geneva, Switzerland
| | - Roger Luechinger
- Institute of Biomedical Engineering, University and Eidgenössische Technische Hochschule (ETH) Zurich, Zurich, Switzerland
| | - Christoph Hock
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland.,Neurimmune AG, Schlieren, Switzerland
| | - Ruth O'Gorman
- Center for Magnetic Resonance Research, University Children's Hospital Zurich, Zurich, Switzerland
| | - Spyros Kollias
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, Zurich, Switzerland
| | - Anton Gietl
- Department of Geriatric Psychiatry, Psychiatric University Hospital Zurich (PUK), Zurich, Switzerland.,Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
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31
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Alhanbali S, Munro KJ, Dawes P, Perugia E, Millman RE. Associations between pre-stimulus alpha power, hearing level and performance in a digits-in-noise task. Int J Audiol 2021; 61:197-204. [PMID: 33794733 DOI: 10.1080/14992027.2021.1899314] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
OBJECTIVE Baseline electroencephalography (EEG) alpha power, i.e. that measured prior to stimulus presentation, is a potential objective predictor of task performance. Here we assessed the predictive power of EEG alpha on performance accuracy in a digits-in-noise recognition task, factoring in hearing thresholds and age. DESIGN EEG alpha power, recorded while participants listened to target digits presented in a noise background, was analysed during two different baseline periods: i) a pre-stimulus baseline (pre-STIM) free from any acoustic stimulus, and ii) a pre-target baseline (pre-TARG) recorded in background noise only. STUDY SAMPLE Eighty-five participants with either normal hearing or aided hearing impairment (age range: 55-85 years old, 42 male). RESULTS Hierarchical multiple regression analyses indicated that i) lower hearing thresholds and, to a lesser extent, higher pre-STIM alpha power were associated with improved performance accuracy ii) alpha power in pre-STIM and pre-TARG were highly correlated across individuals but pre-TARG alpha power was not a significant predictor of performance accuracy. CONCLUSION Investigations of baseline EEG alpha power as a predictor of speech-in-noise performance accuracy should control for associations between hearing thresholds and measures of EEG baseline periods.
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Affiliation(s)
- Sara Alhanbali
- Manchester Centre for Audiology and Deafness, School of Health Sciences, University of Manchester, Manchester, UK.,Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.,Department of Hearing and Speech Science, School of Rehabilitation Sciences, The University of Jordan, Amman, Jordan
| | - Kevin J Munro
- Manchester Centre for Audiology and Deafness, School of Health Sciences, University of Manchester, Manchester, UK.,Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Piers Dawes
- Manchester Centre for Audiology and Deafness, School of Health Sciences, University of Manchester, Manchester, UK.,Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Emanuele Perugia
- Manchester Centre for Audiology and Deafness, School of Health Sciences, University of Manchester, Manchester, UK.,Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Rebecca E Millman
- Manchester Centre for Audiology and Deafness, School of Health Sciences, University of Manchester, Manchester, UK.,Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
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32
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Borserio BJ, Sharpley CF, Bitsika V, Sarmukadam K, Fourie PJ, Agnew LL. Default mode network activity in depression subtypes. Rev Neurosci 2021; 32:597-613. [PMID: 33583166 DOI: 10.1515/revneuro-2020-0132] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 01/12/2021] [Indexed: 01/07/2023]
Abstract
Depression continues to carry a major disease burden worldwide, with limitations on the success of traditional pharmacological or psychological treatments. Recent approaches have therefore focused upon the neurobiological underpinnings of depression, and on the "individualization" of depression symptom profiles. One such model of depression has divided the standard diagnostic criteria into four "depression subtypes", with neurological and behavioral pathways. At the same time, attention has been focused upon the region of the brain known as the "default mode network" (DMN) and its role in attention and problem-solving. However, to date, no review has been published of the links between the DMN and the four subtypes of depression. By searching the literature studies from the last 20 years, 62 relevant papers were identified, and their findings are described for the association they demonstrate between aspects of the DMN and the four depression subtypes. It is apparent from this review that there are potential positive clinical and therapeutic outcomes from focusing upon DMN activation and connectivity, via psychological therapies, transcranial magnetic stimulation, and some emerging pharmacological models.
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Affiliation(s)
- Bernard J Borserio
- Brain-Behaviour Research Group, University of New England, Armidale, NSW, Australia
| | - Christopher F Sharpley
- Brain-Behaviour Research Group, University of New England, Armidale, NSW, Australia.,School of Science and Technology, University of New England, Queen Elizabeth Drive, Armidale, NSW2351, Australia
| | - Vicki Bitsika
- Brain-Behaviour Research Group, University of New England, Armidale, NSW, Australia
| | - Kimaya Sarmukadam
- Brain-Behaviour Research Group, University of New England, Armidale, NSW, Australia
| | - Phillip J Fourie
- Brain-Behaviour Research Group, University of New England, Armidale, NSW, Australia
| | - Linda L Agnew
- Brain-Behaviour Research Group, University of New England, Armidale, NSW, Australia
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Dell'Acqua C, Ghiasi S, Messerotti Benvenuti S, Greco A, Gentili C, Valenza G. Increased functional connectivity within alpha and theta frequency bands in dysphoria: A resting-state EEG study. J Affect Disord 2021; 281:199-207. [PMID: 33326893 DOI: 10.1016/j.jad.2020.12.015] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 11/20/2020] [Accepted: 12/05/2020] [Indexed: 02/08/2023]
Abstract
BACKGROUND The understanding of neurophysiological correlates underlying the risk of developing depression may have a significant impact on its early and objective identification. Research has identified abnormal resting-state electroencephalography (EEG) power and functional connectivity patterns in major depression. However, the entity of dysfunctional EEG dynamics in dysphoria is yet unknown. METHODS 32-channel EEG was recorded in 26 female individuals with dysphoria and in 38 age-matched, female healthy controls. EEG power spectra and alpha asymmetry in frontal and posterior channels were calculated in a 4-minute resting condition. An EEG functional connectivity analysis was conducted through phase locking values, particularly mean phase coherence. RESULTS While individuals with dysphoria did not differ from controls in EEG spectra and asymmetry, they exhibited dysfunctional brain connectivity. Particularly, in the theta band (4-8 Hz), participants with dysphoria showed increased connectivity between right frontal and central areas and right temporal and left occipital areas. Moreover, in the alpha band (8-12 Hz), dysphoria was associated with increased connectivity between right and left prefrontal cortex and between frontal and central-occipital areas bilaterally. LIMITATIONS All participants belonged to the female gender and were relatively young. Mean phase coherence did not allow to compute the causal and directional relation between brain areas. CONCLUSIONS An increased EEG functional connectivity in the theta and alpha bands characterizes dysphoria. These patterns may be associated with the excessive self-focus and ruminative thinking that typifies depressive symptoms. EEG connectivity patterns may represent a promising measure to identify individuals with a higher risk of developing depression.
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Affiliation(s)
- Carola Dell'Acqua
- Department of General Psychogy, University of Padua, Via Venezia 8 - 35131, Padua, Italy; Padova Neuroscience Center (PNC), University of Padua, Via Orus 2/B - 35131, Padua, Italy.
| | - Shadi Ghiasi
- Department of Information Engineering & Bioengineering and Robotics Research Center E. Piaggio, School of Engineering, University of Pisa, Pisa, Italy
| | - Simone Messerotti Benvenuti
- Department of General Psychogy, University of Padua, Via Venezia 8 - 35131, Padua, Italy; Padova Neuroscience Center (PNC), University of Padua, Via Orus 2/B - 35131, Padua, Italy
| | - Alberto Greco
- Department of Information Engineering & Bioengineering and Robotics Research Center E. Piaggio, School of Engineering, University of Pisa, Pisa, Italy
| | - Claudio Gentili
- Department of General Psychogy, University of Padua, Via Venezia 8 - 35131, Padua, Italy; Padova Neuroscience Center (PNC), University of Padua, Via Orus 2/B - 35131, Padua, Italy
| | - Gaetano Valenza
- Department of Information Engineering & Bioengineering and Robotics Research Center E. Piaggio, School of Engineering, University of Pisa, Pisa, Italy
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Beppi C, Ribeiro Violante I, Scott G, Sandrone S. EEG, MEG and neuromodulatory approaches to explore cognition: Current status and future directions. Brain Cogn 2021; 148:105677. [PMID: 33486194 DOI: 10.1016/j.bandc.2020.105677] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Revised: 12/26/2020] [Accepted: 12/27/2020] [Indexed: 01/04/2023]
Abstract
Neural oscillations and their association with brain states and cognitive functions have been object of extensive investigation over the last decades. Several electroencephalography (EEG) and magnetoencephalography (MEG) analysis approaches have been explored and oscillatory properties have been identified, in parallel with the technical and computational advancement. This review provides an up-to-date account of how EEG/MEG oscillations have contributed to the understanding of cognition. Methodological challenges, recent developments and translational potential, along with future research avenues, are discussed.
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Affiliation(s)
- Carolina Beppi
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland; Department of Neurology, University Hospital Zurich and University of Zurich, Zurich, Switzerland; Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
| | - Inês Ribeiro Violante
- Computational, Cognitive and Clinical Neuroscience Laboratory (C3NL), Department of Brain Sciences, Imperial College London, London, United Kingdom; School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom.
| | - Gregory Scott
- Computational, Cognitive and Clinical Neuroscience Laboratory (C3NL), Department of Brain Sciences, Imperial College London, London, United Kingdom.
| | - Stefano Sandrone
- Computational, Cognitive and Clinical Neuroscience Laboratory (C3NL), Department of Brain Sciences, Imperial College London, London, United Kingdom.
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Nicholson AA, Ros T, Densmore M, Frewen PA, Neufeld RWJ, Théberge J, Jetly R, Lanius RA. A randomized, controlled trial of alpha-rhythm EEG neurofeedback in posttraumatic stress disorder: A preliminary investigation showing evidence of decreased PTSD symptoms and restored default mode and salience network connectivity using fMRI. Neuroimage Clin 2020; 28:102490. [PMID: 33395981 PMCID: PMC7708928 DOI: 10.1016/j.nicl.2020.102490] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 10/20/2020] [Accepted: 10/27/2020] [Indexed: 12/19/2022]
Abstract
OBJECTIVE The default-mode network (DMN) and salience network (SN) have been shown to display altered connectivity in posttraumatic stress disorder (PTSD). Restoring aberrant connectivity within these networks with electroencephalogram neurofeedback (EEG-NFB) has been shown previously to be associated with acute decreases in symptoms. Here, we conducted a double-blind, sham-controlled randomized trial of alpha-rhythm EEG-NFB in participants with PTSD (n = 36) over 20-weeks. Our aim was to provide mechanistic evidence underlying clinical improvements by examining changes in network connectivity via fMRI. METHODS We randomly assigned participants with a primary diagnosis of PTSD to either the experimental group (n = 18) or sham-control group (n = 18). We collected resting-state fMRI scans pre- and post-NFB intervention, for both the experimental and sham-control PTSD groups. We further compared baseline brain connectivity measures pre-NFB to age-matched healthy controls (n = 36). RESULTS With regard to the primary outcome measure of PTSD severity, we found a significant main effect of time in the absence of a group × time interaction. Nevertheless, we found significantly decreased PTSD severity scores in the experimental NFB group only, when comparing post-NFB (dz = 0.71) and 3-month follow-up scores (dz = 0.77) to baseline measures. Interestingly, we found evidence to suggest a shift towards normalization of DMN and SN connectivity post-NFB in the experimental group only. Both decreases in PTSD severity and NFB performance were correlated to DMN and SN connectivity post-NFB in the experimental group. Critically, remission rates of PTSD were significant higher in the experimental group (61.1%) as compared to the sham-control group (33.3%). CONCLUSION The current study shows mechanistic evidence for therapeutic changes in DMN and SN connectivity that are known to be associated with PTSD psychopathology with no patient dropouts. This preliminary investigation merits further research to demonstrate fully the clinical efficacy of EEG-NFB as an adjunctive therapy for PTSD.
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Affiliation(s)
- Andrew A Nicholson
- Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Austria
| | - Tomas Ros
- Departments of Neuroscience and Psychiatry, University of Geneva, Campus Biotech, Geneva, Switzerland
| | - Maria Densmore
- Departments of Neuroscience, Western University, London, ON, Canada; Imaging, Lawson Health Research Institute, London, ON, Canada
| | - Paul A Frewen
- Departments of Neuroscience, Western University, London, ON, Canada; Departments of Psychology, Western University, London, ON, Canada
| | - Richard W J Neufeld
- Departments of Neuroscience, Western University, London, ON, Canada; Departments of Psychiatry, Western University, London, ON, Canada; Departments of Psychology, Western University, London, ON, Canada
| | - Jean Théberge
- Departments of Psychiatry, Western University, London, ON, Canada; Departments of Psychology, Western University, London, ON, Canada; Departments of Medical Imaging, Western University, London, ON, Canada; Imaging, Lawson Health Research Institute, London, ON, Canada; Department of Diagnostic Imaging, St. Joseph's Healthcare, London, ON, Canada
| | - Rakesh Jetly
- Canadian Forces, Health Services, Ottawa, Ontario, Canada
| | - Ruth A Lanius
- Departments of Neuroscience, Western University, London, ON, Canada; Departments of Psychiatry, Western University, London, ON, Canada; Imaging, Lawson Health Research Institute, London, ON, Canada.
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Fingelkurts AA, Fingelkurts AA, Kallio-Tamminen T. Selfhood triumvirate: From phenomenology to brain activity and back again. Conscious Cogn 2020; 86:103031. [DOI: 10.1016/j.concog.2020.103031] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 08/21/2020] [Accepted: 10/05/2020] [Indexed: 12/21/2022]
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37
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Diminished large-scale functional brain networks in absolute pitch during the perception of naturalistic music and audiobooks. Neuroimage 2020; 216:116513. [DOI: 10.1016/j.neuroimage.2019.116513] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Revised: 12/16/2019] [Accepted: 12/31/2019] [Indexed: 12/26/2022] Open
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Posttraumatic Stress Disorder Is Associated with α Dysrhythmia across the Visual Cortex and the Default Mode Network. eNeuro 2020; 7:ENEURO.0053-20.2020. [PMID: 32690671 PMCID: PMC7405069 DOI: 10.1523/eneuro.0053-20.2020] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 06/15/2020] [Accepted: 06/19/2020] [Indexed: 12/26/2022] Open
Abstract
Anomalies in default mode network (DMN) activity and α (8–12 Hz) oscillations have been independently observed in posttraumatic stress disorder (PTSD). Recent spatiotemporal analyses suggest that α oscillations support DMN functioning via interregional synchronization and sensory cortical inhibition. Therefore, we examined a unifying pathology of α deficits in the visual-cortex-DMN system in PTSD. Human patients with PTSD (N = 25) and two control groups, patients with generalized anxiety disorder (GAD; N = 24) and healthy controls (HCs; N = 20), underwent a standard eyes-open resting state (S-RS) and a modified resting state (M-RS) of passively viewing salient images (known to deactivate the DMN). High-density electroencephalogram (hdEEG) were recorded, from which intracortical α activity (power and connectivity/Granger causality) was extracted using the exact low-resolution electromagnetic tomography (eLORETA). Patients with PTSD (vs GAD/HC) demonstrated attenuated α power in the visual cortex (VC) and key hubs of the DMN [posterior cingulate cortex (PCC) and medial prefrontal cortex (mPFC)] at both states, the severity of which further correlated with hypervigilance symptoms. With increased visual input (at M-RS vs S-RS), patients with PTSD further demonstrated reduced α-frequency directed connectivity within the DMN (PCC→mPFC) and, importantly, from the VC to both DMN hubs (VC→PCC and VC→mPFC), linking α deficits in the two systems. These interrelated α deficits align with DMN hypoactivity/hypoconnectivity, sensory disinhibition, and hypervigilance in PTSD, representing a unifying neural underpinning of these anomalies. The identification of visual-cortex-DMN α dysrhythmia in PTSD further presents a novel therapeutic target, promoting network-based intervention of neural oscillations.
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Wang C, Kang M, Li Z, Li Y, Guan M, Zou Z, Wu M, Lou W, Xu J. Altered relation of resting-state alpha rhythm with blood oxygen level dependent signal in healthy aging: Evidence by EEG-fMRI fusion analysis. Clin Neurophysiol 2020; 131:2105-2114. [PMID: 32682238 DOI: 10.1016/j.clinph.2020.05.025] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Revised: 04/12/2020] [Accepted: 05/10/2020] [Indexed: 10/24/2022]
Abstract
OBJECTIVE The goal of this study is to explore the changes of spatial correlates of alpha rhythm in the aged adults. METHODS Electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) data were simultaneously recorded from 27 young and 19 elderly adults at resting state with their eyes closed. Alpha rhythm power fluctuation was extracted from EEG signal of parietal-occipital region and was fused with fMRI data by correlating alpha rhythm with blood oxygen level dependent (BOLD) signal using general linear models. RESULTS For both young adults and the elderly, the regions correlated with alpha rhythm power were widely distributed in cortical and subcortical regions. However, compared to young adults, correlations between alpha rhythm and the activity of thalamus and frontal regions were significantly reduced in the elderly. In addition, an increased correlation with alpha rhythm was found in frontal, insula and cingulate gyrus regions in the elderly. CONCLUSIONS Changes in the roles of the above brain regions may be present in the generation or modulation of alpha rhythm due to age advancing. SIGNIFICANCE This study provides novel insight into the alteration of the spatial correlates of alpha rhythm in the elderly by using simultaneous EEG-fMRI data fusion analysis.
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Affiliation(s)
- Chao Wang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China; National Engineering Research Center for Healthcare Devices, Guangzhou, China
| | - Mengfei Kang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China; National Engineering Research Center for Healthcare Devices, Guangzhou, China
| | - Zhonglin Li
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China
| | - Yongli Li
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China; Department of Health Management, Henan Provincial People's Hospital, Zhengzhou, China
| | - Min Guan
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China
| | - Zhi Zou
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China
| | - Min Wu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China; National Engineering Research Center for Healthcare Devices, Guangzhou, China
| | - Wutao Lou
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
| | - Jin Xu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China; National Engineering Research Center for Healthcare Devices, Guangzhou, China.
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Xu J, Ke Y, Liu S, Song X, Xu C, Zhou G, Ming D. Task-irrelevant Auditory Event-related Potentials as Mental Workload Indicators: A Between-task Comparison Study . ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2020:3216-3219. [PMID: 33018689 DOI: 10.1109/embc44109.2020.9175957] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Real-time monitoring of mental workload (MWL) is a crucial step to build closed-loop adaptive aiding systems for human-machine systems. MWL estimators based on spontaneous electroencephalography (EEG) and event-related potentials (ERPs) have shown great potentials to achieve this goal. However, the previous studies show that the between-task robustness of these EEG/ERP-based MWL estimators is still an unsolved intractable question. This study attempts to examine the task-irrelevant auditory event-related potentials (tir-aERPs) as MWL indicators. A working memory task (verbal n-back) and a visuo-motor task (multi-attribute task battery, MATB), both with two difficulty levels (easy and hard), were used in the experiment, along with task-irrelevant auditory probes that did not need any response from the participants. EEG was recorded from ten participants when they were performing the tasks. The tir-aERPs elicited by the auditory probes were extracted and analyzed. The results show that the amplitudes of N1, early P3a (eP3a) and the late reorienting negativity (RON) significantly decreased with the increasing MWL in both n-back and MATB. Task type has no obvious influence on the amplitudes and topological layout of the MWL-sensitive tir-aERPs features. These results suggest that the tir-aERPs are potentially more constant MWL indicators across very different task types. Therefore, the tir-aERPs should be taken into consideration in future task-independent MWL monitoring studies.
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Trambaiolli LR, Biazoli CE. Resting-state global EEG connectivity predicts depression and anxiety severity. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2020:3707-3710. [PMID: 33018806 DOI: 10.1109/embc44109.2020.9176161] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
There is a recent interest in finding neurophysiological biomarkers which will facilitate the diagnosis and understanding of the neural basis of different psychiatric disorders. In this paper, we evaluated the resting-state global EEG connectivity as a potential biomarker for depressive and anxiety symptoms. For this, we evaluated a population of 119 subjects, including 75 healthy subjects and 44 patients with major depressive disorder. We calculated the global connectivity (spectral coherence) in a setup of 60 EEG channels, for six different spectral bands: theta, alpha1, alpha2, beta1, beta2, and gamma. These global connectivity scores were used to train a Support Vector Regressor to predict symptoms measured by the Beck Depression Inventory (BDI) and the Spielberger Trait Anxiety Inventory (TAI). Experiments showed a significant prediction of both symptoms, with a mean absolute error (MAE) of 8.07±6.98 and 11.52±8.7 points, respectively. Among the most discriminating features, the global connectivity in the alpha2 band (10.0-12.0Hz) presented significantly positive Spearman's correlation with the depressive (rho = 0.32, pFDR <0.01), and the anxiety symptoms (rho = 0.26, pFDR<0.01).Clinical relevance-This study demonstrates that EEG global connectivity can be used to predict depression and anxiety symptoms measured by widely used questionnaires.
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Safron A. An Integrated World Modeling Theory (IWMT) of Consciousness: Combining Integrated Information and Global Neuronal Workspace Theories With the Free Energy Principle and Active Inference Framework; Toward Solving the Hard Problem and Characterizing Agentic Causation. Front Artif Intell 2020; 3:30. [PMID: 33733149 PMCID: PMC7861340 DOI: 10.3389/frai.2020.00030] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 04/03/2020] [Indexed: 01/01/2023] Open
Abstract
The Free Energy Principle and Active Inference Framework (FEP-AI) begins with the understanding that persisting systems must regulate environmental exchanges and prevent entropic accumulation. In FEP-AI, minds and brains are predictive controllers for autonomous systems, where action-driven perception is realized as probabilistic inference. Integrated Information Theory (IIT) begins with considering the preconditions for a system to intrinsically exist, as well as axioms regarding the nature of consciousness. IIT has produced controversy because of its surprising entailments: quasi-panpsychism; subjectivity without referents or dynamics; and the possibility of fully-intelligent-yet-unconscious brain simulations. Here, I describe how these controversies might be resolved by integrating IIT with FEP-AI, where integrated information only entails consciousness for systems with perspectival reference frames capable of generating models with spatial, temporal, and causal coherence for self and world. Without that connection with external reality, systems could have arbitrarily high amounts of integrated information, but nonetheless would not entail subjective experience. I further describe how an integration of these frameworks may contribute to their evolution as unified systems theories and models of emergent causation. Then, inspired by both Global Neuronal Workspace Theory (GNWT) and the Harmonic Brain Modes framework, I describe how streams of consciousness may emerge as an evolving generation of sensorimotor predictions, with the precise composition of experiences depending on the integration abilities of synchronous complexes as self-organizing harmonic modes (SOHMs). These integrating dynamics may be particularly likely to occur via richly connected subnetworks affording body-centric sources of phenomenal binding and executive control. Along these connectivity backbones, SOHMs are proposed to implement turbo coding via loopy message-passing over predictive (autoencoding) networks, thus generating maximum a posteriori estimates as coherent vectors governing neural evolution, with alpha frequencies generating basic awareness, and cross-frequency phase-coupling within theta frequencies for access consciousness and volitional control. These dynamic cores of integrated information also function as global workspaces, centered on posterior cortices, but capable of being entrained with frontal cortices and interoceptive hierarchies, thus affording agentic causation. Integrated World Modeling Theory (IWMT) represents a synthetic approach to understanding minds that reveals compatibility between leading theories of consciousness, thus enabling inferential synergy.
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Affiliation(s)
- Adam Safron
- Indiana University, Bloomington, IN, United States
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Wirsich J, Giraud AL, Sadaghiani S. Concurrent EEG- and fMRI-derived functional connectomes exhibit linked dynamics. Neuroimage 2020; 219:116998. [PMID: 32480035 DOI: 10.1016/j.neuroimage.2020.116998] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 05/07/2020] [Accepted: 05/26/2020] [Indexed: 12/18/2022] Open
Abstract
Long-range connectivity has become the most studied feature of human functional Magnetic Resonance Imaging (fMRI), yet the spatial and temporal relationship between its whole-brain dynamics and electrophysiological connectivity remains largely unknown. FMRI-derived functional connectivity exhibits spatial reconfigurations or time-varying dynamics at infraslow (<0.1Hz) speeds. Conversely, electrophysiological connectivity is based on cross-region coupling of fast oscillations (~1-100Hz). It is unclear whether such fast oscillation-based coupling varies at infraslow speeds, temporally coinciding with infraslow dynamics across the fMRI-based connectome. If so, does the association of fMRI-derived and electrophysiological dynamics spatially vary over the connectome across the functionally distinct electrophysiological oscillation bands? In two concurrent electroencephalography (EEG)-fMRI resting-state datasets, oscillation-based coherence in all canonical bands (delta through gamma) indeed reconfigured at infraslow speeds in tandem with fMRI-derived connectivity changes in corresponding region-pairs. Interestingly, irrespective of EEG frequency-band the cross-modal tie of connectivity dynamics comprised a large proportion of connections distributed across the entire connectome. However, there were frequency-specific differences in the relative strength of the cross-modal association. This association was strongest in visual to somatomotor connections for slower EEG-bands, and in connections involving the Default Mode Network for faster EEG-bands. Methodologically, the findings imply that neural connectivity dynamics can be reliably measured by fMRI despite heavy susceptibility to noise, and by EEG despite shortcomings of source reconstruction. Biologically, the findings provide evidence that contrast with known territories of oscillation power, oscillation coupling in all bands slowly reconfigures in a highly distributed manner across the whole-brain connectome.
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Affiliation(s)
- Jonathan Wirsich
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Department of Psychology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
| | - Anne-Lise Giraud
- Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland
| | - Sepideh Sadaghiani
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Department of Psychology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
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Kustermann T, Ata Nguepnjo Nguissi N, Pfeiffer C, Haenggi M, Kurmann R, Zubler F, Oddo M, Rossetti AO, De Lucia M. Brain functional connectivity during the first day of coma reflects long-term outcome. NEUROIMAGE-CLINICAL 2020; 27:102295. [PMID: 32563037 PMCID: PMC7305428 DOI: 10.1016/j.nicl.2020.102295] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Revised: 04/30/2020] [Accepted: 05/04/2020] [Indexed: 01/02/2023]
Abstract
Coma patients show different connectivity patterns depending on long-term outcome. Time-variance of functional connectivity is an early prognostic marker for coma patients. Connectivity patterns observed in chronic patients may develop early after coma onset.
Objective In patients with disorders of consciousness (DOC), properties of functional brain networks at rest are informative of the degree of consciousness impairment and of long-term outcome. Here we investigate whether connectivity differences between patients with favorable and unfavorable outcome are already present within 24 h of coma onset. Methods We prospectively recorded 63-channel electroencephalography (EEG) at rest during the first day of coma after cardiac arrest. We analyzed 98 adults, of whom 57 survived beyond unresponsive wakefulness. Functional connectivity was estimated by computing the ‘debiased weighted phase lag index’ over epochs of five seconds duration. We evaluated the network’s topological features, including clustering coefficient, path length, modularity and participation coefficient and computed their variance over time. Finally, we estimated the predictive value of these topological features for patients’ outcomes by splitting the patient sample in training and test datasets. Results Group-level analysis revealed lower clustering coefficient, higher modularity and path length variance in patients with favorable compared to those with unfavorable outcomes (p < 0.01). Within all features, the path length variance in the network provided the best positive predictive value (PPV) for favorable outcome and specificity for unfavorable outcome in the test dataset (PPV: 0.83, p < 0.01; specificity: 0.86, p < 0.01) with above-chance negative predictive value and accuracy. Of note, the exclusion of patients with epileptiform activity (20 in total) eliminates all false positive predictions (n = 6) for path length variance. Interpretation Topological features of functional connectivity differ as a function of long-term outcome in patients on the first day of coma. These differences are not interpretable in terms of consciousness levels as all patients were in a deep unconscious state. The time variance of path length is informative of comatose patients’ outcome, as patients with favorable outcome exhibit a richer repertoire of path length than those with unfavorable outcomes.
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Affiliation(s)
- Thomas Kustermann
- Laboratoire de Recherche en Neuroimagerie (LREN), University Hospital (CHUV) & University of Lausanne, Switzerland.
| | | | | | - Matthias Haenggi
- Department of Intensive Care Medicine, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Rebekka Kurmann
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Frédéric Zubler
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - Mauro Oddo
- Department of Intensive Care Medicine, University Hospital (CHUV) & University of Lausanne, Switzerland
| | - Andrea O Rossetti
- Department of Neurology, University Hospital (CHUV) & University of Lausanne, Switzerland
| | - Marzia De Lucia
- Laboratoire de Recherche en Neuroimagerie (LREN), University Hospital (CHUV) & University of Lausanne, Switzerland
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Beckmann KM, Wang-Leandro A, Dennler M, Carrera I, Richter H, Bektas RN, Steiner A, Haller S. Resting state networks of the canine brain under sevoflurane anaesthesia. PLoS One 2020; 15:e0231955. [PMID: 32302373 PMCID: PMC7164650 DOI: 10.1371/journal.pone.0231955] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Accepted: 04/05/2020] [Indexed: 12/13/2022] Open
Abstract
Resting-state functional Magnetic Resonance Imaging (rs-fMRI) has become an established technique in humans and reliably determines several resting state networks (RSNs) simultaneously. Limited data exist about RSN in dogs. The aim of this study was to investigate the RSNs in 10 healthy beagle dogs using a 3 tesla MRI scanner and subsequently perform group-level independent component analysis (ICA) to identify functionally connected brain networks. Rs-fMRI sequences were performed under steady state sevoflurane inhalation anaesthesia. Anaesthetic depth was titrated to the minimum level needed for immobilisation and mechanical ventilation of the patient. This required a sevoflurane MAC between 0.8 to 1.2. Group-level ICA dimensionality of 20 components revealed distributed sensory, motor and higher-order networks in the dogs’ brain. We identified in total 7 RSNs (default mode, primary and higher order visual, auditory, two putative motor-somatosensory and one putative somatosensory), which are common to other mammals including humans. Identified RSN are remarkably similar to those identified in awake dogs. This study proves the feasibility of rs-fMRI in anesthetized dogs and describes several RSNs, which may set the basis for investigating pathophysiological characteristics of various canine brain diseases.
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Affiliation(s)
- Katrin M. Beckmann
- Neurology Department, Clinic of Small Animal Surgery, Vetsuisse Faculty Zurich, Zurich, Switzerland
- * E-mail:
| | - Adriano Wang-Leandro
- Department of Diagnostics and Clinical Services, Clinic for Diagnostic Imaging, Vetsuisse-Faculty Zurich, Zurich, Switzerland
| | - Matthias Dennler
- Department of Diagnostics and Clinical Services, Clinic for Diagnostic Imaging, Vetsuisse-Faculty Zurich, Zurich, Switzerland
| | - Ines Carrera
- Willows Veterinary Centre and Referral Service, Shirley, United Kingdom
| | - Henning Richter
- Department of Diagnostics and Clinical Services, Clinic for Diagnostic Imaging, Vetsuisse-Faculty Zurich, Zurich, Switzerland
| | - Rima N. Bektas
- Department of Diagnostics and Clinical Services, Section of Anaesthesiology, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland
| | - Aline Steiner
- Department of Diagnostics and Clinical Services, Section of Anaesthesiology, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland
| | - Sven Haller
- Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden
- Faculty of Medicine of the University of Geneva, Geneva, Switzerland
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Sharma S, Sasidharan A, Marigowda V, Vijay M, Sharma S, Mukundan CS, Pandit L, Masthi NRR. Indian classical music with incremental variation in tempo and octave promotes better anxiety reduction and controlled mind wandering-A randomised controlled EEG study. Explore (NY) 2020; 17:115-121. [PMID: 32249198 DOI: 10.1016/j.explore.2020.02.013] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 01/12/2020] [Accepted: 02/20/2020] [Indexed: 11/26/2022]
Abstract
Studies have reported the benefits of music-listening in stress-reduction using musical pieces of specific scale or 'Raaga'. But the influence of lower-level musical properties (like tempo, octave, timbre, etc.) lack research backing. Carnatic music concerts use incremental modulations in tempo and octave (e.g.: 'Ragam-Tanam-Pallavi') to elevate the mood of audiences. Therefore, the current study aimed to examine the anxiolytic effect of this musical property. A randomised controlled cross-over study with 21 male undergraduate medical students was followed. 11 participants listened to 'Varying music' (VM: instrumental music with incremental variations in tempo and octave) and 10 listened to 'Stable music' (SM: instrumental music without such variations), thrice daily for 6 days, both clips recorded in Raaga-Kaapi and silence being the control intervention. Electroencephalography (EEG) and Electrocardiography (for heart rate variability or HRV) were done on all 6 days. Beck's Anxiety inventory and State-trait anxiety scale were administered on Day-1 and Day-6. A significant anxiety score reduction was seen only in VM. VM showed marked decrease in lower frequency EEG power in bilateral temporo-parieto-occipital regions compared to silence, whereas SM showed increase in higher frequencies. Relatively, VM showed more midline power reduction (i.e., lower default mode network or DMN activity) and SM showed greater left-dominant alpha/beta asymmetry (i.e., greater right brain activation). During both music interventions HRV remained stable, unlike silence intervention. We speculate that, gradual transition between lower-slower and higher-faster music portions of VM induces a 'controlled-mind wandering' state involving balanced switching between heightened mind wandering ('attention to self') and reduced mind wandering ('attention to music') states, respectively. Therefore, music-selection has remarkable influence on stress-management and warrants further research.
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Affiliation(s)
- Sushma Sharma
- Kempegowda Institute of Medical Sciences (KIMS), Bengaluru, Karnataka, India
| | - Arun Sasidharan
- Axxonet Brain Research Laboratory (ABRL), Axxonet System Technologies Pvt. Ltd., Bengaluru, Karnataka, India.
| | - Vrinda Marigowda
- Axxonet Brain Research Laboratory (ABRL), Axxonet System Technologies Pvt. Ltd., Bengaluru, Karnataka, India
| | - Mohini Vijay
- Axxonet Brain Research Laboratory (ABRL), Axxonet System Technologies Pvt. Ltd., Bengaluru, Karnataka, India
| | - Sumit Sharma
- Axxonet Brain Research Laboratory (ABRL), Axxonet System Technologies Pvt. Ltd., Bengaluru, Karnataka, India
| | - Chetan Satyajit Mukundan
- Axxonet Brain Research Laboratory (ABRL), Axxonet System Technologies Pvt. Ltd., Bengaluru, Karnataka, India
| | - Lakshmi Pandit
- Kempegowda Institute of Medical Sciences (KIMS), Bengaluru, Karnataka, India
| | - N R Ramesh Masthi
- Kempegowda Institute of Medical Sciences (KIMS), Bengaluru, Karnataka, India
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Nicholson AA, Ros T, Jetly R, Lanius RA. Regulating posttraumatic stress disorder symptoms with neurofeedback: Regaining control of the mind. JOURNAL OF MILITARY, VETERAN AND FAMILY HEALTH 2020. [DOI: 10.3138/jmvfh.2019-0032] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Neurofeedback is emerging as a psychophysiological treatment where self-regulation is achieved through online feedback of neural states. Novel personalized medicine approaches are particularly important for the treatment of posttraumatic stress disorder (PTSD), as symptom presentation of the disorder, as well as responses to treatment, are highly heterogeneous. Learning to achieve control of specific neural substrates through neurofeedback has been shown to display therapeutic evidence in patients with a wide variety of psychiatric disorders, including PTSD. This article outlines the neural mechanisms underlying neurofeedback and examines converging evidence for the efficacy of neurofeedback as an adjunctive treatment for PTSD via both electroencephalography (EEG) and real-time functional magnetic resonance imaging (fMRI) modalities. Further, implications for the treatment of PTSD via neurofeedback in the military member and Veteran population is examined.
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Affiliation(s)
- Andrew A. Nicholson
- Department of Psychological Research and Research Methods, University of Vienna, Vienna, Austria
- Neurology and Imaging of Cognition Lab, University of Geneva, Geneva, Switzerland
- Canadian Forces Health Services Group, Department of National Defence, Government of Canada, Ottawa
- Department of Psychology, Western University, London, Ontario
| | - Tomas Ros
- Department of Psychological Research and Research Methods, University of Vienna, Vienna, Austria
- Neurology and Imaging of Cognition Lab, University of Geneva, Geneva, Switzerland
- Canadian Forces Health Services Group, Department of National Defence, Government of Canada, Ottawa
- Department of Psychology, Western University, London, Ontario
| | - Rakesh Jetly
- Department of Psychological Research and Research Methods, University of Vienna, Vienna, Austria
- Neurology and Imaging of Cognition Lab, University of Geneva, Geneva, Switzerland
- Canadian Forces Health Services Group, Department of National Defence, Government of Canada, Ottawa
- Department of Psychology, Western University, London, Ontario
| | - Ruth A. Lanius
- Department of Psychological Research and Research Methods, University of Vienna, Vienna, Austria
- Neurology and Imaging of Cognition Lab, University of Geneva, Geneva, Switzerland
- Canadian Forces Health Services Group, Department of National Defence, Government of Canada, Ottawa
- Department of Psychology, Western University, London, Ontario
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Winter U, LeVan P, Borghardt TL, Akin B, Wittmann M, Leyens Y, Schmidt S. Content-Free Awareness: EEG-fcMRI Correlates of Consciousness as Such in an Expert Meditator. Front Psychol 2020; 10:3064. [PMID: 32132942 PMCID: PMC7040185 DOI: 10.3389/fpsyg.2019.03064] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Accepted: 12/26/2019] [Indexed: 11/21/2022] Open
Abstract
The minimal neural correlate of the conscious state, regardless of the neural activity correlated with the ever-changing contents of experience, has still not been identified. Different attempts have been made, mainly by comparing the normal waking state to seemingly unconscious states, such as deep sleep or general anesthesia. A more direct approach would be the neuroscientific investigation of conscious states that are experienced as free of any specific phenomenal content. Here we present serendipitous data on content-free awareness (CFA) during an EEG-fMRI assessment reported by an extraordinarily qualified meditator with over 50,000 h of practice. We focused on two specific cortical networks related to external and internal awareness, i.e., the dorsal attention network (DAN) and the default mode network (DMN), to explore the neural correlates of this experience. The combination of high-resolution EEG and ultrafast fMRI enabled us to analyze the dynamic aspects of fMRI connectivity informed by EEG power analysis. The neural correlates of CFA were characterized by a sharp decrease in alpha power and an increase in theta power as well as increases in functional connectivity in the DAN and decreases in the posterior DMN. We interpret these findings as correlates of a top-down-initiated attentional state excluding external sensory stimuli and internal mentation from conscious experience. We conclude that the investigation of states of CFA could provide valuable input for new methodological and conceptual approaches in the search for the minimal neural correlate of consciousness.
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Affiliation(s)
- Ulf Winter
- Department of Psychosomatic Medicine and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
| | - Pierre LeVan
- Department of Radiology - Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany.,Departments of Radiology and Paediatrics, Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
| | | | - Burak Akin
- Department of Radiology - Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany.,Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
| | - Marc Wittmann
- Institute for Frontier Areas of Psychology and Mental Health, Freiburg im Breisgau, Germany
| | - Yeshe Leyens
- Department of Psychosomatic Medicine and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
| | - Stefan Schmidt
- Department of Psychosomatic Medicine and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
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Yan Y, Qian T, Xu X, Han H, Ling Z, Zhou W, Liu H, Hong B. Human cortical networking by probabilistic and frequency-specific coupling. Neuroimage 2020; 207:116363. [PMID: 31740339 DOI: 10.1016/j.neuroimage.2019.116363] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 11/03/2019] [Accepted: 11/13/2019] [Indexed: 11/26/2022] Open
Abstract
Large-scale cortical networking patterns have been established based on the correlation of slow fluctuations of resting fMRI signals. However, the electrophysiological mechanism of cortical networking remained to be elucidated. With large-scale human ECoG recording, we developed a novel approach for functional network parcellation on the basis of probabilistic co-activation of cortical sites in spatio-temporal microstates. The parcellated networks were verified by electrical cortical stimulation (ECS) and somatosensory evoked potentials recording, which showed significantly higher accuracy than the traditional long-term correlation method. This provides direct electrophysiological evidence supporting the dynamic nature of cortical networking. Further analysis revealed that the brain-wide connectivity is likely established on the coupling of ECoG power envelop over a common carrier frequency ranging from alpha to low-beta (8-32Hz). Surprisingly, the cortical networking pattern over this specific frequency was found to be consistent across various tasks, which resembles the resting networks. The high similarity between the above functional network parcellation and the fMRI resting network atlas in individuals also suggested the slow power-envelope coupling of band-limited neural oscillations as the electrophysiological basis of spontaneous BOLD signals. Collectively, our findings on direct human recording revealed a probabilistic and frequency specific coupling mechanism for large-scale cortical networking shared by task and resting brain.
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Affiliation(s)
- Yuxiang Yan
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China
| | - Tianyi Qian
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China
| | - Xin Xu
- Department of Neurosurgery, Chinese PLA General Hospital, Beijing, 100853, China
| | - Hao Han
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China
| | - Zhipei Ling
- Department of Neurosurgery, Chinese PLA General Hospital, Beijing, 100853, China
| | - Wenjin Zhou
- Epilepsy Center, Yuquan Hospital, Tsinghua University, Beijing, 100040, China
| | - Hesheng Liu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA, 02129, USA.
| | - Bo Hong
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, 100084, China.
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Sadaghiani S, Wirsich J. Intrinsic connectome organization across temporal scales: New insights from cross-modal approaches. Netw Neurosci 2020; 4:1-29. [PMID: 32043042 PMCID: PMC7006873 DOI: 10.1162/netn_a_00114] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Accepted: 11/11/2019] [Indexed: 12/17/2022] Open
Abstract
The discovery of a stable, whole-brain functional connectivity organization that is largely independent of external events has drastically extended our view of human brain function. However, this discovery has been primarily based on functional magnetic resonance imaging (fMRI). The role of this whole-brain organization in fast oscillation-based connectivity as measured, for example, by electroencephalography (EEG) and magnetoencephalography (MEG) is only beginning to emerge. Here, we review studies of intrinsic connectivity and its whole-brain organization in EEG, MEG, and intracranial electrophysiology with a particular focus on direct comparisons to connectome studies in fMRI. Synthesizing this literature, we conclude that irrespective of temporal scale over four orders of magnitude, intrinsic neurophysiological connectivity shows spatial similarity to the connectivity organization commonly observed in fMRI. A shared structural connectivity basis and cross-frequency coupling are possible mechanisms contributing to this similarity. Acknowledging that a stable whole-brain organization governs long-range coupling across all timescales of neural processing motivates researchers to take "baseline" intrinsic connectivity into account when investigating brain-behavior associations, and further encourages more widespread exploration of functional connectomics approaches beyond fMRI by using EEG and MEG modalities.
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Affiliation(s)
- Sepideh Sadaghiani
- Psychology Department, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Jonathan Wirsich
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
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