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Geffen R, Braun C. Effects of Geometric Sound on Brainwave Activity Patterns, Autonomic Nervous System Markers, Emotional Response, and Faraday Wave Pattern Morphology. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE : ECAM 2024; 2024:9844809. [PMID: 38586300 PMCID: PMC10997421 DOI: 10.1155/2024/9844809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 12/28/2023] [Accepted: 01/31/2024] [Indexed: 04/09/2024]
Abstract
This study introduces Geometric Sound as a subfield of spatial sound featuring audio stimuli which are sonic holograms of mathematically defined 3D shapes. The effects of Geometric Sound on human physiology were investigated through EEG, heart rate, blood pressure, and a combination of questionnaires monitoring 50 healthy participants in two separate experiments. The impact of Geometric Sound on Faraday wave pattern morphology was further studied. The shapes examined, pyramid, cube, and sphere, exhibited varying significant effects on autonomic nervous system markers, brainwave power amplitude, topology, and connectivity patterns, in comparison to both the control (traditional stereo), and recorded baseline where no sound was presented. Brain activity in the Alpha band exhibited the most significant results, additional noteworthy results were observed across analysis paradigms in all frequency bands. Geometric Sound was found to significantly reduce heart rate and blood pressure and enhance relaxation and general well-being. Changes in EEG, heart rate, and blood pressure were primarily shape-dependent, and to a lesser extent sex-dependent. Pyramid Geometric Sound yielded the most significant results in most analysis paradigms. Faraday Waves patterns morphology analysis indicated that identical frequencies result in patterns that correlate with the excitation Geometric Sound shape. We suggest that Geometric Sound shows promise as a noninvasive therapeutic approach for physical and psychological conditions, stress-related disorders, depression, anxiety, and neurotrauma. Further research is warranted to elucidate underlying mechanisms and expand its applications.
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Affiliation(s)
| | - Christoph Braun
- Tübingen University, MEG-Center, Tübingen 72074, Germany
- HIH Hertie Institute for Clinical Brain Research, Tübingen, Germany
- CIMeC Center for Mind/Brain Sciences, University of Trento, Trento, Italy
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Mikhaylets E, Razorenova AM, Chernyshev V, Syrov N, Yakovlev L, Boytsova J, Kokurina E, Zhironkina Y, Medvedev S, Kaplan A. SDA: a data-driven algorithm that detects functional states applied to the EEG of Guhyasamaja meditation. Front Neuroinform 2024; 17:1301718. [PMID: 38348138 PMCID: PMC10859925 DOI: 10.3389/fninf.2023.1301718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 12/27/2023] [Indexed: 02/15/2024] Open
Abstract
The study presents a novel approach designed to detect time-continuous states in time-series data, called the State-Detecting Algorithm (SDA). The SDA operates on unlabeled data and detects optimal change-points among intrinsic functional states in time-series data based on an ensemble of Ward's hierarchical clustering with time-connectivity constraint. The algorithm chooses the best number of states and optimal state boundaries, maximizing clustering quality metrics. We also introduce a series of methods to estimate the performance and confidence of the SDA when the ground truth annotation is unavailable. These include information value analysis, paired statistical tests, and predictive modeling analysis. The SDA was validated on EEG recordings of Guhyasamaja meditation practice with a strict staged protocol performed by three experienced Buddhist practitioners in an ecological setup. The SDA used neurophysiological descriptors as inputs, including PSD, power indices, coherence, and PLV. Post-hoc analysis of the obtained EEG states revealed significant differences compared to the baseline and neighboring states. The SDA was found to be stable with respect to state order organization and showed poor clustering quality metrics and no statistical significance between states when applied to randomly shuffled epochs (i.e., surrogate subject data used as controls). The SDA can be considered a general data-driven approach that detects hidden functional states associated with the mental processes evolving during meditation or other ongoing mental and cognitive processes.
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Affiliation(s)
- Ekaterina Mikhaylets
- Faculty of Computer Science, Faculty of Economic Sciences, HSE University, Moscow, Russia
| | - Alexandra M. Razorenova
- Faculty of Computer Science, Faculty of Economic Sciences, HSE University, Moscow, Russia
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russia
| | - Vsevolod Chernyshev
- Faculty of Computer Science, Faculty of Economic Sciences, HSE University, Moscow, Russia
| | - Nikolay Syrov
- Baltic Center for Neurotechnology and Artificial Intelligence, Immanuel Kant Baltic Federal University, Kaliningrad, Russia
| | - Lev Yakovlev
- Baltic Center for Neurotechnology and Artificial Intelligence, Immanuel Kant Baltic Federal University, Kaliningrad, Russia
| | - Julia Boytsova
- Academician Natalya Bekhtereva Foundation, St. Petersburg, Russia
| | - Elena Kokurina
- Academician Natalya Bekhtereva Foundation, St. Petersburg, Russia
| | | | | | - Alexander Kaplan
- Baltic Center for Neurotechnology and Artificial Intelligence, Immanuel Kant Baltic Federal University, Kaliningrad, Russia
- Laboratory for Neurophysiology and Neuro-Computer Interfaces, Lomonosov Moscow State University, Moscow, Russia
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Richter CG, Li CM, Turnbull A, Haft SL, Schneider D, Luo J, Lima DP, Lin FV, Davidson RJ, Hoeft F. Brain imaging studies of emotional well-being: a scoping review. Front Psychol 2024; 14:1328523. [PMID: 38250108 PMCID: PMC10799564 DOI: 10.3389/fpsyg.2023.1328523] [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: 10/26/2023] [Accepted: 12/06/2023] [Indexed: 01/23/2024] Open
Abstract
This scoping review provides an overview of previous empirical studies that used brain imaging techniques to investigate the neural correlates of emotional well-being (EWB). We compiled evidence on this topic into one accessible and usable document as a foundation for future research into the relationship between EWB and the brain. PRISMA 2020 guidelines were followed. We located relevant articles by searching five electronic databases with 95 studies meeting our inclusion criteria. We explored EWB measures, brain imaging modalities, research designs, populations studied, and approaches that are currently in use to characterize and understand EWB across the literature. Of the key concepts related to EWB, the vast majority of studies investigated positive affect and life satisfaction, followed by sense of meaning, goal pursuit, and quality of life. The majority of studies used functional MRI, followed by EEG and event-related potential-based EEG to study the neural basis of EWB (predominantly experienced affect, affective perception, reward, and emotion regulation). It is notable that positive affect and life satisfaction have been studied significantly more often than the other three aspects of EWB (i.e., sense of meaning, goal pursuit, and quality of life). Our findings suggest that future studies should investigate EWB in more diverse samples, especially in children, individuals with clinical disorders, and individuals from various geographic locations. Future directions and theoretical implications are discussed, including the need for more longitudinal studies with ecologically valid measures that incorporate multi-level approaches allowing researchers to better investigate and evaluate the relationships among behavioral, environmental, and neural factors. Systematic review registration https://osf.io/t9cf6/.
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Affiliation(s)
- Caroline G. Richter
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, United States
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, United States
| | - Celine Mylx Li
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, United States
- Department of Psychology, University of California, Berkeley, Berkeley, CA, United States
| | - Adam Turnbull
- Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY, United States
- CogT Lab, Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States
| | - Stephanie L. Haft
- Department of Psychology, University of California, Berkeley, Berkeley, CA, United States
| | - Deborah Schneider
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, United States
| | - Jie Luo
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, United States
| | - Denise Pinheiro Lima
- Intensive Care Pediatrician, Pediatric Intensive Care Unit, Hospital Moinhos de Vento, Porto Alegre, Brazil
| | - Feng Vankee Lin
- CogT Lab, Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States
| | - Richard J. Davidson
- Center for Healthy Minds, University of Wisconsin, Madison, WI, United States
- Department of Psychology, University of Wisconsin, Madison, WI, United States
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin, Madison, WI, United States
- Department of Psychiatry, University of Wisconsin, Madison, WI, United States
| | - Fumiko Hoeft
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, United States
- Haskins Laboratories, New Haven, CT, United States
- Brain Imaging Research Center (BIRC), University of Connecticut, Storrs, CT, United States
- Department of Psychiatry and Behavioral Sciences, and Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
- Department of Neuropsychiatry, Keio University School of Medicine, Shinanomachi Shinjuku Tokyo, Tokyo, Japan
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Lazarou I, Oikonomou VP, Mpaltadoros L, Grammatikopoulou M, Alepopoulos V, Stavropoulos TG, Bezerianos A, Nikolopoulos S, Kompatsiaris I, Tsolaki M. Eliciting brain waves of people with cognitive impairment during meditation exercises using portable electroencephalography in a smart-home environment: a pilot study. Front Aging Neurosci 2023; 15:1167410. [PMID: 37388185 PMCID: PMC10306118 DOI: 10.3389/fnagi.2023.1167410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 05/03/2023] [Indexed: 07/01/2023] Open
Abstract
Objectives Meditation imparts relaxation and constitutes an important non-pharmacological intervention for people with cognitive impairment. Moreover, EEG has been widely used as a tool for detecting brain changes even at the early stages of Alzheimer's Disease (AD). The current study investigates the effect of meditation practices on the human brain across the AD spectrum by using a novel portable EEG headband in a smart-home environment. Methods Forty (40) people (13 Healthy Controls-HC, 14 with Subjective Cognitive Decline-SCD and 13 with Mild Cognitive Impairment-MCI) participated practicing Mindfulness Based Stress Reduction (Session 2-MBSR) and a novel adaptation of the Kirtan Kriya meditation to the Greek culture setting (Session 3-KK), while a Resting State (RS) condition was undertaken at baseline and follow-up (Session 1-RS Baseline and Session 4-RS Follow-Up). The signals were recorded by using the Muse EEG device and brain waves were computed (alpha, theta, gamma, and beta). Results Analysis was conducted on four-electrodes (AF7, AF8, TP9, and TP10). Statistical analysis included the Kruskal-Wallis (KW) nonparametric analysis of variance. The results revealed that both states of MBSR and KK lead to a marked difference in the brain's activation patterns across people at different cognitive states. Wilcoxon Signed-ranks test indicated for HC that theta waves at TP9, TP10 and AF7, AF8 in Session 3-KK were statistically significantly reduced compared to Session 1-RS Z = -2.271, p = 0.023, Z = -3.110, p = 0.002 and Z = -2.341, p = 0.019, Z = -2.132, p = 0.033, respectively. Conclusion The results showed the potential of the parameters used between the various groups (HC, SCD, and MCI) as well as between the two meditation sessions (MBSR and KK) in discriminating early cognitive decline and brain alterations in a smart-home environment without medical support.
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Affiliation(s)
- Ioulietta Lazarou
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Vangelis P. Oikonomou
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Lampros Mpaltadoros
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Margarita Grammatikopoulou
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Vasilis Alepopoulos
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Thanos G. Stavropoulos
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Anastasios Bezerianos
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Spiros Nikolopoulos
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Ioannis Kompatsiaris
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
| | - Magda Tsolaki
- Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
- 1st Department of Neurology, Faculty of Health Sciences, G.H. “AHEPA”, School of Medicine, Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece
- Greek Association of Alzheimer’s Disease and Related Disorders (GAADRD), Thessaloniki, Greece
- Laboratory of Neurodegenerative Diseases, Center for Interdisciplinary Research and Innovation (CIRI–AUTh), Aristotle University of Thessaloniki, Thessaloniki, Greece
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Majeed U, Aftab MF, Baloch DM, Ahmed S, Yusuf IM, Hasan MA, Qureshi MS. Modulation of Heart and Brain Function by Surah Al-Rehman Recitation Among Distressed Diabetic Patients in Pakistan. JOURNAL OF RELIGION AND HEALTH 2022; 61:3852-3865. [PMID: 34554380 DOI: 10.1007/s10943-021-01431-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 09/13/2021] [Indexed: 06/13/2023]
Abstract
Distress causes psychophysiological alterations that affect autonomic function. The current study explores psychophysiological modulation in diabetic distress in response to Surah Al-Rehman recitation. A single-group experimental study with before and after intervention assessments was conducted during April 2018 to February 2019 in which participants (n = 10) listened to Surah Al-Rehman recitation. Blood pressure, blood glucose, cortisol, ECG and EEG were recorded before and after recitation. Significant reduction in systolic blood pressure, increase in low frequency and absolute alpha power at Fp2 were observed. Heartbeat evoked potentials (HEP) were also significantly modulated at Fp1, Fp2 and F4. These findings suggest that Surah Al-Rehman modulated baroreflex activity thereby reducing sympathetic activity and improved heart brain coherence as reflected by HEP.
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Affiliation(s)
- Umair Majeed
- Jinnah Sindh Medical University, Rafiqui H.J. Shaheed Road, Karachi, Sindh, 75510, Pakistan
| | - Meha Fatima Aftab
- Dow Institute of Medical Technology, Dow University of Health Sciences, 111 Suparco Rd, Gulzar-e-Hijri Gulzar E Hijri Scheme 33, Karachi, Sindh, 75270, Pakistan.
| | - Deedag Murad Baloch
- Jinnah Sindh Medical University, Rafiqui H.J. Shaheed Road, Karachi, Sindh, 75510, Pakistan
| | - Sana Ahmed
- Dow Institute of Medical Technology, Dow University of Health Sciences, 111 Suparco Rd, Gulzar-e-Hijri Gulzar E Hijri Scheme 33, Karachi, Sindh, 75270, Pakistan
| | - Imran M Yusuf
- Transformation International Society, SB-23 & 24، Main University Rd, Gulshan Block 13 C Gulshan-e-Iqbal, Karachi, Karachi, Sindh, 75300, Pakistan
| | - Muhammad Abul Hasan
- Department of Biomedical Engineering, NED University of Engineering and Technology, Main University Rd, Karachi, Karachi, Sindh, 75270, Pakistan
- Neurocomputation Laboratory, National Center for Artificial Intelligence, Karachi, Pakistan
| | - Muhammad Sameer Qureshi
- Dow Institute of Medical Technology, Dow University of Health Sciences, 111 Suparco Rd, Gulzar-e-Hijri Gulzar E Hijri Scheme 33, Karachi, Sindh, 75270, Pakistan
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Volodina M, Smetanin N, Lebedev M, Ossadtchi A. Cortical and autonomic responses during staged Taoist meditation: Two distinct meditation strategies. PLoS One 2021; 16:e0260626. [PMID: 34855823 PMCID: PMC8638869 DOI: 10.1371/journal.pone.0260626] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 11/12/2021] [Indexed: 11/28/2022] Open
Abstract
Meditation is a consciousness state associated with specific physiological and neural correlates. Numerous investigations of these correlates reported controversial results which prevented a consistent depiction of the underlying neurophysiological processes. Here we investigated the dynamics of multiple neurophysiological indicators during a staged meditation session. We measured the physiological changes at rest and during the guided Taoist meditation in experienced meditators and naive subjects. We recorded EEG, respiration, galvanic skin response, and photoplethysmography. All subjects followed the same instructions split into 16 stages. In the experienced meditators group we identified two subgroups with different physiological markers dynamics. One subgroup showed several signs of general relaxation evident from the changes in heart rate variability, respiratory rate, and EEG rhythmic activity. The other subgroup exhibited mind concentration patterns primarily noticeable in the EEG recordings while no autonomic responses occurred. The duration and type of previous meditation experience or any baseline indicators we measured did not explain the segregation of the meditators into these two groups. These results suggest that two distinct meditation strategies could be used by experienced meditators, which partly explains the inconsistent results reported in the earlier studies evaluating meditation effects. Our findings are also relevant to the development of the high-end biofeedback systems.
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Affiliation(s)
- Maria Volodina
- Center for Bioelectric Interfaces, HSE University, Moscow, Russia
| | - Nikolai Smetanin
- Center for Bioelectric Interfaces, HSE University, Moscow, Russia
| | - Mikhail Lebedev
- Center for Bioelectric Interfaces, HSE University, Moscow, Russia
| | - Alexei Ossadtchi
- Center for Bioelectric Interfaces, HSE University, Moscow, Russia
- Artificial intelligence Research Institute, Moscow, Russia
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Gupta SS, Manthalkar RR, Gajre SS. Mindfulness intervention for improving cognitive abilities using EEG signal. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.103072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Day MA, Matthews N, Mattingley JB, Ehde DM, Turner AP, Williams RM, Jensen MP. Change in Brain Oscillations as a Mechanism of Mindfulness-Meditation, Cognitive Therapy, and Mindfulness-Based Cognitive Therapy for Chronic Low Back Pain. PAIN MEDICINE 2021; 22:1804-1813. [PMID: 33561289 DOI: 10.1093/pm/pnab049] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
OBJECTIVE Psychological treatments for chronic low back pain (CLBP) are effective. However, limited research has investigated their neurophysiological mechanisms. This study examined electroencephalography- (EEG-) assessed brain oscillation changes as potential mechanisms of cognitive therapy (CT), mindfulness-meditation (MM), and mindfulness-based cognitive therapy (MBCT) for CLBP. The a priori bandwidths of interest were changes in theta, alpha and beta power, measured at pre- and post-treatment. DESIGN A secondary analysis of a clinical trial. SETTING University of Queensland Psychology Clinic. SUBJECTS Adults (N = 57) with CLBP who completed pre- and post-treatment EEG and pain outcome assessments. METHODS EEG data were examined for five regions of interest (ROIs); the primary outcome was pain intensity. RESULTS A significant reduction in theta (P=.015) and alpha (P=.006) power in the left frontal ROI across all treatments was found, although change in theta and alpha power in this region was not differentially associated with outcome across treatments. There were significant reductions in beta power in all five ROIs across all treatments (P≤.013). Beta power reduction in the central ROI showed a significant association with reduced pain intensity in MBCT only (P=.028). Changes in other regions were not statistically significant. CONCLUSIONS These findings provide support for the capacity of psychological CLBP treatments to induce changes in brain activity. The reduced beta power in all five ROIs indicated that all three treatments engendered a state of lowered cortical arousal. The growing body of research in this area could potentially inform novel directions towards remedying central nervous system abnormalities associated with CLBP.
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Affiliation(s)
- Melissa A Day
- School of Psychology, University of Queensland, Brisbane, QLD, Australia.,Department of Rehabilitation Medicine, University of Washington, Seattle, Washington, USA
| | - Natasha Matthews
- School of Psychology, University of Queensland, Brisbane, QLD, Australia
| | - Jason B Mattingley
- School of Psychology, University of Queensland, Brisbane, QLD, Australia.,Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Dawn M Ehde
- Department of Rehabilitation Medicine, University of Washington, Seattle, Washington, USA
| | - Aaron P Turner
- Department of Rehabilitation Medicine, University of Washington, Seattle, Washington, USA.,Rehabilitation Care Service/Polytrauma, VA Puget Sound Health Care System, Seattle, Washington, USA
| | - Rhonda M Williams
- Department of Rehabilitation Medicine, University of Washington, Seattle, Washington, USA.,Rehabilitation Care Service/Polytrauma, VA Puget Sound Health Care System, Seattle, Washington, USA
| | - Mark P Jensen
- Department of Rehabilitation Medicine, University of Washington, Seattle, Washington, USA
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Kaur C, Singh P, Sahni S. EEG Artifact Removal System for Depression Using a Hybrid Denoising Approach. Basic Clin Neurosci 2021; 12:465-476. [PMID: 35154587 PMCID: PMC8817173 DOI: 10.32598/bcn.2021.1388.2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2019] [Revised: 03/09/2020] [Accepted: 06/30/2021] [Indexed: 11/20/2022] Open
Abstract
INTRODUCTION Several computer-aided diagnosis systems for depression are suggested for use by clinicians to authorize the diagnosis. EEG may be used as an objective analysis tool for identifying depression in the initial stage to avoid it from reaching a severe and permanent state. However, artifact contamination reduces the accuracy in EEG signal processing systems. METHODS This work proposes a novel denoising method based on Empirical Mode Decomposition (EMD) (with Detrended Fluctuation Analysis (DFA) and wavelet packet transform. Initially, real EEG recordings corresponding to depression patients are decomposed into various mode functions by applying EMD. Then, DFA is used as the mode selection criteria. Further Wavelet Packets Decomposition (WPD)-based evaluation is applied to extract the cleaner signal. RESULTS Simulations were conducted on real EEG databases for depression to demonstrate the effects of the proposed techniques. To conclude the efficacy of the proposed technique, SNR and MAE were identified. The obtained results indicated improved signal-to-noise ratio and lower values of MAE for the combined EMD-DFA-WPD technique. Additionally, Random Forest and SVM (Support Vector Machine)-based classification revealed the improved accuracy of 98.51% and 98.10% for the proposed denoising technique. Whereas the accuracy of the EMD- DFA is 98.01% and 95.81% and EMD combined with DWT technique equaled98.0% and 97.21% for the EMD- DFA technique for RF and SVM, respectively, compared to the proposed method. Furthermore, the classification performance for both classifiers was compared with and without denoising to highlight the effects of the proposed technique. CONCLUSION Proposed denoising system results in better classification of depressed and healthy individuals resulting in a better diagnosing system. These results can be further analyzed using other approaches as a solution to the mode mixing problem of the EMD approach.
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Affiliation(s)
- Chamandeep Kaur
- Department of Electronics and Communication Engineering, Panjab University Chandigarh, Chandigarh, India
| | - Preeti Singh
- Department of Electronics and Communication Engineering, Panjab University Chandigarh, Chandigarh, India.,Corresponding Author: Preeti Singh, PhD. Address:Department of Electronics and Communication Engineering, Panjab University Chandigarh, Chandigarh, India.Tel:+91 (998) 8898773E-mail:
| | - Sukhtej Sahni
- Department of Psychiatry, Cheema Medical Complex, Mohali, India
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Klee D, Colgan DD, Hanes D, Oken B. The effects of an internet-based mindfulness meditation intervention on electrophysiological markers of attention. Int J Psychophysiol 2020; 158:103-113. [PMID: 33080294 PMCID: PMC7736517 DOI: 10.1016/j.ijpsycho.2020.10.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 09/30/2020] [Accepted: 10/08/2020] [Indexed: 01/02/2023]
Abstract
Evidence suggests that mindfulness meditation training has the potential to train aspects of attention. However, the neurophysiological mechanisms underpinning the attentional benefits from mindfulness remain unclear. This randomized controlled trial examined changes in electrophysiological markers of attention before and after completion of a 6-week internet-based mindfulness intervention. EEG and ERP data were collected from 64 generally healthy, mildly stressed older adults. Participants were randomized to an internet-based mindfulness-based stress reduction course (IMMI), an internet-based health and wellness education course, or a waitlist control condition. Attentional N2 and P3 evoked potentials were derived from active and passive auditory oddball paradigms. Participants in the IMMI group showed significantly greater differences in P3 peak-trough amplitude between the active and passive oddball paradigms at endpoint relative to controls. There were no significant relationships between the intervention and N2 potentials. Our data demonstrate a measurable increase in attentional control when discriminating or directing attention away from auditory stimuli for older adult participants who received mindfulness training. These findings lend support to the use of the P3 as a neurophysiological measure of meditation engagement and intervention efficacy.
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Affiliation(s)
- Daniel Klee
- Oregon Health & Science University, Department of Neurology, United States of America.
| | | | - Douglas Hanes
- National University of Natural Medicine, United States of America
| | - Barry Oken
- Oregon Health & Science University, Department of Neurology, United States of America; Oregon Health & Science University, Departments of Behavioral Neuroscience and Biomedical Engineering, United States of America
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Tinga AM, Nyklíček I, Jansen MP, de Back TT, Louwerse MM. Respiratory Biofeedback Does Not Facilitate Lowering Arousal in Meditation Through Virtual Reality. Appl Psychophysiol Biofeedback 2020; 44:51-59. [PMID: 30377895 PMCID: PMC6373281 DOI: 10.1007/s10484-018-9421-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
The current study examined the effectiveness of respiratory biofeedback in lowering subjective and objective arousal after stress. Participants were presented with a meditation session in virtual reality while subjective and objective arousal were measured, the latter measured through ECG and EEG. Three conditions were used: (a) a respiratory biofeedback condition, in which visual feedback was paired to breathing; (b) a control feedback placebo condition, in which visual feedback was not paired to breathing; and (c) a control no-feedback condition, in which no visual feedback was used. Subjective and objective arousal decreased during meditation after stress in all conditions, demonstrating recovery after stress during meditation in virtual reality. However, the reduction in arousal (on all outcome measures combined and heart rate specifically) was largest in the control feedback placebo condition, in which no biofeedback was used, indicating that respiratory biofeedback had no additional value in reducing arousal. The findings of the current study highlight the importance of including a control feedback placebo condition in order to establish the exact additional value of biofeedback and offer insights in applying cost-effective virtual reality meditation training.
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Affiliation(s)
- Angelica M Tinga
- Department of Cognitive Science & Artificial Intelligence, Tilburg University, Dante Building, Room D 330, Warandelaan 2, 5037 AB, Tilburg, The Netherlands.
| | - Ivan Nyklíček
- Department of Medical and Clinical Psychology, Tilburg University, Tilburg, The Netherlands
| | - Michel P Jansen
- Department of Electrical Engineering, Mathematics, and Computer Science, University of Twente, Enschede, The Netherlands
| | - Tycho T de Back
- Department of Cognitive Science & Artificial Intelligence, Tilburg University, Dante Building, Room D 330, Warandelaan 2, 5037 AB, Tilburg, The Netherlands
| | - Max M Louwerse
- Department of Cognitive Science & Artificial Intelligence, Tilburg University, Dante Building, Room D 330, Warandelaan 2, 5037 AB, Tilburg, The Netherlands
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Gorantla VR, Tedesco S, Chandanathil M, Maity S, Bond V, Lewis C, Millis RM. Associations of Alpha and Beta Interhemispheric EEG Coherences with Indices of Attentional Control and Academic Performance. Behav Neurol 2020; 2020:4672340. [PMID: 32089751 PMCID: PMC7025044 DOI: 10.1155/2020/4672340] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2019] [Accepted: 01/18/2020] [Indexed: 11/18/2022] Open
Abstract
Introduction. Heretofore, research on optimizing academic performance has suffered from an inability to translate what is known about an individual's learning behaviors to how effectively they are able to use the critical nodes and hubs in their cerebral cortex for learning. A previous study from our laboratory suggests that lower theta-beta ratios (TBRs) measured by EEG may be associated with higher academic performance in a medical school curriculum. METHODS In this study, we tested the hypothesis that TBR and academic performance may be correlated with EEG coherence, a measure of brain connectivity. We analyzed the interhemispheric coherences of the subjects involved in our prior study. TBR and coherence measurements were made at 19 scalp electrode recording sites and 171 electrode combinations with eyes open and closed (EO, EC). Control data were acquired during a session of acclimation to the research protocol 3 d before an initial examination in anatomy-physiology (control exam) and were repeated five weeks later, 3 d before a second exam covering different anatomy-physiology topics (comparison exam). RESULTS Between the control and comparison exams, beta coherences increased significantly at the frontal pole, frontal, parietal, midtemporal, posterior temporal, and occipital recording sites under the EO condition and at the inferior frontal, central, midtemporal, and posterior temporal sites under the EC condition. Alpha coherences increased significantly at the same sites and under the same EO/EC conditions as found for the beta coherences. The beta coherences were negatively correlated with the TBR and were positively correlated with the comparison exam score at the midfrontal electrode site (F3-F4) but only under the EO condition. Beta and alpha coherences at the midfrontal, inferior frontal midtemporal, posterior temporal, and occipital sites were also negatively correlated with the average TBR under the EO condition. CONCLUSIONS Lower TBR, an indicator of attentional control, was associated with higher alpha and beta interhemispheric coherences measured with eyes open at sites overlying the frontal, temporal, and occipital cortices. Changes in EEG coherences and TBRs might be useful as neurophysiological measures of neuroplasticity and the efficacy of strategies for preventing academic underachievement and treatments for improving academic performance.
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Affiliation(s)
- Vasavi R. Gorantla
- Department of Basic Sciences, American University of Antigua College of Medicine, Antigua and Barbuda
| | - Sarah Tedesco
- Department of Basic Sciences, American University of Antigua College of Medicine, Antigua and Barbuda
| | - Merin Chandanathil
- Department of Basic Sciences, American University of Antigua College of Medicine, Antigua and Barbuda
| | - Sabyasachi Maity
- Department of Basic Sciences, American University of Antigua College of Medicine, Antigua and Barbuda
| | - Vernon Bond
- Exercise and Nutritional Sciences Laboratory, Howard University Cancer Center and the Department of Human Performance and Leisure Studies, Washington DC 20060, USA
| | - Courtney Lewis
- Department of Clinical Medicine, American University of Antigua College of Medicine, Antigua and Barbuda
| | - Richard M. Millis
- Department of Basic Sciences, American University of Antigua College of Medicine, Antigua and Barbuda
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Alawieh H, Dawy Z, Yaacoub E, Abbas N, El-Imad J. A Real-Time ECG Feature Extraction Algorithm for Detecting Meditation Levels within a General Measurement Setup. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2019:99-103. [PMID: 31945854 DOI: 10.1109/embc.2019.8857832] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
This paper presents a setup for the real-time extraction of Electroencephalography (EEG) and Electrocardiogram (ECG) features indicating the level of focus, relaxation, or meditation of a given subject. An algorithm for detecting meditation in real-time using the extracted ECG features is designed and shown to lead to accurate results using an online ECG measurement dataset. Similar methods can be used for EEG data, such that the proposed measurement setup can be used, for example, for investigating the effect of virtual reality based EEG training, with and without neurofeedback, on the capability of subjects to focus, relax, or meditate.
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Namazi H, Aghasian E, Ala TS. Complexity-based classification of EEG signal in normal subjects and patients with epilepsy. Technol Health Care 2020; 28:57-66. [DOI: 10.3233/thc-181579] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
| | - Erfan Aghasian
- School of Engineering and ICT, University of Tasmania, Hobart, TAS, Australia
| | - Tirdad Seifi Ala
- Hearing Sciences (Scottish Section), Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Glasgow, UK
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15
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Jerath R, Beveridge C, Jensen M. On the Hierarchical Organization of Oscillatory Assemblies: Layered Superimposition and a Global Bioelectric Framework. Front Hum Neurosci 2019; 13:426. [PMID: 31866845 PMCID: PMC6904282 DOI: 10.3389/fnhum.2019.00426] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2018] [Accepted: 11/18/2019] [Indexed: 01/23/2023] Open
Abstract
Bioelectric oscillations occur throughout the nervous system of nearly all animals, revealed to play an important role in various aspects of cognitive activity such as information processing and feature binding. Modern research into this dynamic and intrinsic bioelectric activity of neural cells continues to raise questions regarding their role in consciousness and cognition. In this theoretical article, we assert a novel interpretation of the hierarchical nature of "brain waves" by identifying that the superposition of multiple oscillations varying in frequency corresponds to the superimposing of the contents of consciousness and cognition. In order to describe this isomorphism, we present a layered model of the global functional oscillations of various frequencies which act as a part of a unified metastable continuum described by the Operational Architectonics theory and suggested to be responsible for the emergence of the phenomenal mind. We detail the purposes, functions, and origins of each layer while proposing our main theory that the superimposition of these oscillatory layers mirrors the superimposition of the components of the integrated phenomenal experience as well as of cognition. In contrast to the traditional view that localizations of high and low-frequency activity are spatially distinct, many authors have suggested a hierarchical nature to oscillations. Our theoretical interpretation is founded in four layers which correlate not only in frequency but in evolutionary development. As other authors have done, we explore how these layers correlate to the phenomenology of human experience. Special importance is placed on the most basal layer of slow oscillations in coordinating and grouping all of the other layers. By detailing the isomorphism between the phenomenal and physiologic aspects of how lower frequency layers provide a foundation for higher frequency layers to be organized upon, we provide a further means to elucidate physiological and cognitive mechanisms of mind and for the well-researched outcomes of certain voluntary breathing patterns and meditative practices which modulate the mind and have therapeutic effects for psychiatric and other disorders.
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Affiliation(s)
- Ravinder Jerath
- Charitable Medical Healthcare Foundation, Augusta, GA, United States
| | - Connor Beveridge
- Charitable Medical Healthcare Foundation, Augusta, GA, United States
| | - Michael Jensen
- Department of Medical Illustration, Augusta University, Augusta, GA, United States
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16
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Yousefzadeh F, Pirzad Jahromi G, Mokari Manshadi E, Hatef B. The Effect of Prostration (Sajdah) on the Prefrontal Brain Activity: A Pilot Study. Basic Clin Neurosci 2019; 10:257-268. [PMID: 31462980 PMCID: PMC6712630 DOI: 10.32598/bcn.9.10.195] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2017] [Revised: 10/05/2017] [Accepted: 05/28/2018] [Indexed: 11/20/2022] Open
Abstract
Introduction "Sajdah", a prostration position, is part of Muslim daily prayers. It seems to have several effects on the brain and heart function. This study aimed to investigate the prefrontal brain activity after 10 seconds of Sajdah in the direction of Qibla (the direction that a Muslim prays) while putting the forehead on the ground. Methods Three women and two men participated in this pilot study. Linear (absolute and relative power of θ (4-8Hz), α 1 (8-10 Hz), α 2 (10-12 Hz), β 1 (12-16 Hz), β 2 (16-20 Hz), β 3 (20-30 Hz), γ 1 (30-40 Hz), γ 2 (40-50 Hz) and non-linear features (approximate entropy, Katz fractal dimension, Petrosian fractal dimension, spectral entropy, and sample entropy) from Fps channel were calculated. Results The relative β to γ band, approximate and sample entropy, Petrosian fractal dimension and mean of amplitude decreased in open eye state in women. While θ to γ bands in the closed eye state decreased after Sajdah in women. The absolute γ bands in closed eye state and relative β band in open eye state increased after Sajdah in men. Conclusion The pilot study showed that 10 seconds of Sajdah has effects on brain activity and sometimes showed the opposite effect on genders.
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Affiliation(s)
| | - Gila Pirzad Jahromi
- Neuroscience Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Ehsan Mokari Manshadi
- Neuroscience Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Boshra Hatef
- Neuroscience Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran
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Schoenberg PLA, Vago DR. Mapping meditative states and stages with electrophysiology: concepts, classifications, and methods. Curr Opin Psychol 2019; 28:211-217. [DOI: 10.1016/j.copsyc.2019.01.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 01/07/2019] [Accepted: 01/13/2019] [Indexed: 01/01/2023]
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18
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Harne BP, Tahseen AA, Hiwale AS, Dhekekar RS. Survey on Om meditation: Its effects on the human body and Om meditation as a tool for stress management. PSYCHOLOGICAL THOUGHT 2019. [DOI: 10.5964/psyct.v12i1.275] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Meditation and yoga both have positive effects on physical, as well as mental health. Om mantra chanting, a simple and easy to practice, also comes under the aspect of meditation. The “Om” mantra is also considered as the very name of the absolute. Om meditation not only affects the various parts of the brain, such as pre-frontal cortex, vagus nerve, amygdala and others but also affects the heart rate and respiratory rate. Considering the healing effects of Om meditation, through this paper, we are trying to explore all the relevant work done in the field of Om meditation. The survey includes a large number of papers covering the research previously conducted by many researchers, their results and different techniques adopted to study the effect of Om meditation on human beings. Studies on Om meditation are categorized under four different heads: Neuroimaging studies, EEG studies, evoked potentials studies and other methods studies. Even though the existing research evidenced capability of Om meditation in curing anxiety and depression, more rigorous studies with better design, with larger sample size and with different control groups are required. Especially the need to explore untouched research areas of Loud Om meditation using EEG is suggested in the paper. Furthermore, future research directions are also suggested.
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Matiz A, Crescentini C, Fabbro A, Budai R, Bergamasco M, Fabbro F. Spontaneous eye movements during focused-attention mindfulness meditation. PLoS One 2019; 14:e0210862. [PMID: 30677056 PMCID: PMC6345481 DOI: 10.1371/journal.pone.0210862] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Accepted: 01/03/2019] [Indexed: 11/22/2022] Open
Abstract
Oculometric measures have been proven to be useful markers of mind-wandering during visual tasks such as reading. However, little is known about ocular activity during mindfulness meditation, a mental practice naturally involving mind-wandering episodes. In order to explore this issue, we extracted closed-eyes ocular movement measurements via a covert technique (EEG recordings) from expert meditators during two repetitions of a 7-minute mindfulness meditation session, focusing on the breath, and two repetitions of a 7-minute instructed mind-wandering task. Power spectral density was estimated on both the vertical and horizontal components of eye movements. The results show a significantly smaller average amplitude of eye movements in the delta band (1–4 Hz) during mindfulness meditation than instructed mind-wandering. Moreover, participants’ meditation expertise correlated significantly with this average amplitude during both tasks, with more experienced meditators generally moving their eyes less than less experienced meditators. These findings suggest the potential use of this measure to detect mind-wandering episodes during mindfulness meditation and to assess meditation performance.
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Affiliation(s)
- Alessio Matiz
- PERCRO Laboratory, Scuola Superiore “Sant’Anna”, Pisa, Italy
- * E-mail:
| | - Cristiano Crescentini
- Department of Languages and Literatures, Communication, Education and Society, University of Udine, Udine, Italy
| | - Anastasia Fabbro
- Department of Psychology, University of Rome La Sapienza, Rome, Italy
- Department of Medicine, University of Udine, Udine, Italy
| | - Riccardo Budai
- Department of Neuroscience, University-Hospital “S. Maria della Misericordia”, Udine, Italy
| | | | - Franco Fabbro
- PERCRO Laboratory, Scuola Superiore “Sant’Anna”, Pisa, Italy
- Department of Medicine, University of Udine, Udine, Italy
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Jensen MP, Battalio SL, Chan JF, Edwards KA, Day MA, Sherlin LH, Ehde DM. USE OF NEUROFEEDBACK AND MINDFULNESS TO ENHANCE RESPONSE TO HYPNOSIS TREATMENT IN INDIVIDUALS WITH MULTIPLE SCLEROSIS: Results From a Pilot Randomized Clinical Trial. Int J Clin Exp Hypn 2018; 66:231-264. [PMID: 29856281 DOI: 10.1080/00207144.2018.1460546] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Abstract
This pilot study evaluated the possibility that 2 interventions hypothesized to increase slower brain oscillations (e.g., theta) may enhance the efficacy of hypnosis treatment, given evidence that hypnotic responding is associated with slower brain oscillations. Thirty-two individuals with multiple sclerosis and chronic pain, fatigue, or both, were randomly assigned to 1 of 2 interventions thought to increase slow wave activity (mindfulness meditation or neurofeedback training) or no enhancing intervention, and then given 5 sessions of self-hypnosis training targeting their presenting symptoms. The findings supported the potential for both neurofeedback and mindfulness to enhance response to hypnosis treatment. Research using larger sample sizes to determine the generalizability of these findings is warranted.
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Affiliation(s)
| | | | - Joy F Chan
- a University of Washington , Seattle , USA
| | | | - Melissa A Day
- b The University of Queensland , Brisbane , Australia
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21
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Jin MJ, Kim JS, Kim S, Hyun MH, Lee SH. An Integrated Model of Emotional Problems, Beta Power of Electroencephalography, and Low Frequency of Heart Rate Variability after Childhood Trauma in a Non-Clinical Sample: A Path Analysis Study. Front Psychiatry 2018; 8:314. [PMID: 29403401 PMCID: PMC5786859 DOI: 10.3389/fpsyt.2017.00314] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Accepted: 12/29/2017] [Indexed: 01/30/2023] Open
Abstract
Childhood trauma is known to be related to emotional problems, quantitative electroencephalography (EEG) indices, and heart rate variability (HRV) indices in adulthood, whereas directions among these factors have not been reported yet. This study aimed to evaluate pathway models in young and healthy adults: (1) one with physiological factors first and emotional problems later in adulthood as results of childhood trauma and (2) one with emotional problems first and physiological factors later. A total of 103 non-clinical volunteers were included. Self-reported psychological scales, including the Childhood Trauma Questionnaire (CTQ), State-Trait Anxiety Inventory, Beck Depression Inventory, and Affective Lability Scale were administered. For physiological evaluation, EEG record was performed during resting eyes closed condition in addition to the resting-state HRV, and the quantitative power analyses of eight EEG bands and three HRV components were calculated in the frequency domain. After a normality test, Pearson's correlation analysis to make path models and path analyses to examine them were conducted. The CTQ score was significantly correlated with depression, state and trait anxiety, affective lability, and HRV low-frequency (LF) power. LF power was associated with beta2 (18-22 Hz) power that was related to affective lability. Affective lability was associated with state anxiety, trait anxiety, and depression. Based on the correlation and the hypothesis, two models were composed: a model with pathways from CTQ score to affective lability, and a model with pathways from CTQ score to LF power. The second model showed significantly better fit than the first model (AICmodel1 = 63.403 > AICmodel2 = 46.003), which revealed that child trauma could affect emotion, and then physiology. The specific directions of relationships among emotions, the EEG, and HRV in adulthood after childhood trauma was discussed.
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Affiliation(s)
- Min Jin Jin
- Clinical Emotion and Cognition Research Laboratory, Inje University, Goyang, South Korea
- Department of Psychology, Chung-Ang University, Seoul, South Korea
| | - Ji Sun Kim
- Clinical Emotion and Cognition Research Laboratory, Inje University, Goyang, South Korea
- Department of Psychiatry, Soonchunhyang University Cheonan Hospital, Cheonan, South Korea
| | - Sungkean Kim
- Clinical Emotion and Cognition Research Laboratory, Inje University, Goyang, South Korea
- Department of Biomedical Engineering, Hanyang University, Seoul, South Korea
| | - Myoung Ho Hyun
- Department of Psychology, Chung-Ang University, Seoul, South Korea
| | - Seung-Hwan Lee
- Clinical Emotion and Cognition Research Laboratory, Inje University, Goyang, South Korea
- Department of Psychiatry, Inje University, Ilsan-Paik Hospital, Goyang, South Korea
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Lee YH, Hsieh YJ, Shiah YJ, Lin YH, Chen CY, Tyan YC, GengQiu J, Hsu CY, Chen SCJ. A cross-sectional evaluation of meditation experience on electroencephalography data by artificial neural network and support vector machine classifiers. Medicine (Baltimore) 2017; 96:e6612. [PMID: 28422856 PMCID: PMC5406072 DOI: 10.1097/md.0000000000006612] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
To quantitate the meditation experience is a subjective and complex issue because it is confounded by many factors such as emotional state, method of meditation, and personal physical condition. In this study, we propose a strategy with a cross-sectional analysis to evaluate the meditation experience with 2 artificial intelligence techniques: artificial neural network and support vector machine. Within this analysis system, 3 features of the electroencephalography alpha spectrum and variant normalizing scaling are manipulated as the evaluating variables for the detection of accuracy. Thereafter, by modulating the sliding window (the period of the analyzed data) and shifting interval of the window (the time interval to shift the analyzed data), the effect of immediate analysis for the 2 methods is compared. This analysis system is performed on 3 meditation groups, categorizing their meditation experiences in 10-year intervals from novice to junior and to senior. After an exhausted calculation and cross-validation across all variables, the high accuracy rate >98% is achievable under the criterion of 0.5-minute sliding window and 2 seconds shifting interval for both methods. In a word, the minimum analyzable data length is 0.5 minute and the minimum recognizable temporal resolution is 2 seconds in the decision of meditative classification. Our proposed classifier of the meditation experience promotes a rapid evaluation system to distinguish meditation experience and a beneficial utilization of artificial techniques for the big-data analysis.
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Affiliation(s)
- Yu-Hao Lee
- Department of Electrical Engineering, National Cheng Kung University, Tainan
| | - Ya-Ju Hsieh
- Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University
| | - Yung-Jong Shiah
- Graduate Institute of Counseling Psychology and Rehabilitation Counseling, National Kaohsiung Normal University
| | - Yu-Huei Lin
- Department of Electrical Engineering, National Cheng Kung University, Tainan
| | - Chiao-Yun Chen
- Department of Medical Imaging, Kaohsiung Medical University Hospital
| | - Yu-Chang Tyan
- Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University
- Center for Infectious Disease and Cancer Research, Kaohsiung Medical University
- Institute of Medical Science and Technology, National Sun Yat-sen University
- Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University
- Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
| | | | - Chung-Yao Hsu
- Department of Neurology, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Sharon Chia-Ju Chen
- Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University
- Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
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Maskeliunas R, Damasevicius R, Martisius I, Vasiljevas M. Consumer-grade EEG devices: are they usable for control tasks? PeerJ 2016; 4:e1746. [PMID: 27014511 PMCID: PMC4806709 DOI: 10.7717/peerj.1746] [Citation(s) in RCA: 122] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2015] [Accepted: 02/09/2016] [Indexed: 11/20/2022] Open
Abstract
We present the evaluation of two well-known, low-cost consumer-grade EEG devices: the Emotiv EPOC and the Neurosky MindWave. Problems with using the consumer-grade EEG devices (BCI illiteracy, poor technical characteristics, and adverse EEG artefacts) are discussed. The experimental evaluation of the devices, performed with 10 subjects asked to perform concentration/relaxation and blinking recognition tasks, is given. The results of statistical analysis show that both devices exhibit high variability and non-normality of attention and meditation data, which makes each of them difficult to use as an input to control tasks. BCI illiteracy may be a significant problem, as well as setting up of the proper environment of the experiment. The results of blinking recognition show that using the Neurosky device means recognition accuracy is less than 50%, while the Emotiv device has achieved a recognition accuracy of more than 75%; for tasks that require concentration and relaxation of subjects, the Emotiv EPOC device has performed better (as measured by the recognition accuracy) by ∼9%. Therefore, the Emotiv EPOC device may be more suitable for control tasks using the attention/meditation level or eye blinking than the Neurosky MindWave device.
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Affiliation(s)
- Rytis Maskeliunas
- Multimedia Engineering Department, Kaunas University of Technology, Kaunas, Lithuania
| | | | - Ignas Martisius
- Computer Science Department, Kaunas University of Technology, Kaunas, Lithuania
| | - Mindaugas Vasiljevas
- Software Engineering Department, Kaunas University of Technology, Kaunas, Lithuania
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