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Jacques C, Quiquempoix M, Sauvet F, Le Van Quyen M, Gomez-Merino D, Chennaoui M. Interest of neurofeedback training for cognitive performance and risk of brain disorders in the military context. Front Psychol 2024; 15:1412289. [PMID: 39734770 PMCID: PMC11672796 DOI: 10.3389/fpsyg.2024.1412289] [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: 04/05/2024] [Accepted: 11/11/2024] [Indexed: 12/31/2024] Open
Abstract
Operational environments are characterized by a range of psycho-physiological constraints that can degrade combatants' performance and impact on their long-term health. Neurofeedback training (NFT), a non-invasive, safe and effective means of regulating brain activity, has been shown to be effective for mental disorders, as well as for cognitive and motor capacities and aiding sports performance in healthy individuals. Its value in helping soldiers in operational condition or suffering from post-traumatic stress (PTSD) is undeniable, but relatively unexplored. The aim of this narrative review is to show the applicability of NFT to enhance cognitive performance and to treat (or manage) PTSD symptoms in the military context. It provides an overview of NFT use cases before, during or after military operations, and in the treatment of soldiers suffering from PTSD. The position of NFT within the broad spectrum of performance enhancement techniques, as well as several key factors influencing the effectiveness of NFT are discussed. Finally, suggestions for the use of NFT in the military context (pre-training environments, and during and post-deployments to combat zones or field operations), future research directions, recommendations and caveats (e.g., on transfer to operational situations, inter-individual variability in responsiveness) are offered. This review is thus expected to draw clear perspectives for both researchers and armed forces regarding NFT for cognitive performance enhancement and PTSD treatment related to the military context.
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Affiliation(s)
- Clémentine Jacques
- URP 7330 VIFASOM, Université Paris Cité, Paris, France
- Unité Fatigue et Vigilance, Institut de Recherche Biomédicale des Armées (IRBA), Brétigny sur Orge, France
- Inserm U1145, Université Sorbonne UMRCR2/UMR7371 CNRS, Paris, France
- ThereSIS, THALES SIX GTS, Palaiseau, France
| | - Michael Quiquempoix
- URP 7330 VIFASOM, Université Paris Cité, Paris, France
- Unité Fatigue et Vigilance, Institut de Recherche Biomédicale des Armées (IRBA), Brétigny sur Orge, France
| | - Fabien Sauvet
- URP 7330 VIFASOM, Université Paris Cité, Paris, France
- Unité Fatigue et Vigilance, Institut de Recherche Biomédicale des Armées (IRBA), Brétigny sur Orge, France
| | | | - Danielle Gomez-Merino
- URP 7330 VIFASOM, Université Paris Cité, Paris, France
- Unité Fatigue et Vigilance, Institut de Recherche Biomédicale des Armées (IRBA), Brétigny sur Orge, France
| | - Mounir Chennaoui
- URP 7330 VIFASOM, Université Paris Cité, Paris, France
- Unité Fatigue et Vigilance, Institut de Recherche Biomédicale des Armées (IRBA), Brétigny sur Orge, France
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Wu YC, Yu HE, Yen CF, Yeh YC, Jian CR, Lin CW, Lin IM. The effects of swLORETA Z-score neurofeedback for patients comorbid with major depressive disorder and anxiety symptoms. J Affect Disord 2024; 350:340-349. [PMID: 38199411 DOI: 10.1016/j.jad.2024.01.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Revised: 11/28/2023] [Accepted: 01/03/2024] [Indexed: 01/12/2024]
Abstract
BACKGROUND Patients with major depressive disorder (MDD) exhibit atypical brain activities in the frontal, temporal, and parietal lobes. The study aimed to investigate the effects of standardized weighted low-resolution electromagnetic tomography Z-score neurofeedback (swLZNFB) on symptoms of depression and anxiety, electroencephalography (EEG) parameters, and deep brain activities in patients with MDD. METHOD Forty-eight patients with MDD comorbid with anxiety symptoms were assigned to the swLZNFB group and the control group. Participants completed the Beck Depression Inventory-II (BDI-II) and Beck Anxiety Inventory (BAI) and a 5-minute resting EEG at the pre-and post-tests. The swLZNFB group received ten sessions of one-hour treatment twice weekly. The control group received treatment as usual. The scores for BDI-II and BAI, number of EEG abnormalities, percentage of EEG abnormalities, and current source density (CSD) measured in the prefrontal cortex (PFC), anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), and amygdala were compared at pre-and post-tests between the two groups. RESULTS There were decreased scores of BDI-II and BAI, number of EEG abnormalities, and percentage of EEG abnormalities at post-test compared with pre-test in the swLZNFB group, and lower scores of BDI-II and BAI at post-test in the swLZNFB group compared with the control group. Moreover, decreased CSD of beta1 and beta3 in the PFC, ACC, PCC, and amygdala at post-test compared to pre-test in the swLZNFB group. LIMITATIONS Not a randomized controlled trial. CONCLUSION Ten sessions of swLZNFB reduced clinical symptoms and atypical brain activities, it serves as a potential psychological intervention for patients with MDD.
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Affiliation(s)
- Yin-Chen Wu
- Department of Psychology, College of Humanities and Social Sciences, Kaohsiung Medical University, Taiwan
| | - Hong-En Yu
- Department of Psychology, College of Humanities and Social Sciences, Kaohsiung Medical University, Taiwan
| | - Cheng-Fang Yen
- Department of Psychiatry, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Taiwan; Graduate Institute of Medicine, Department of Psychiatry, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Yi-Chun Yeh
- Department of Psychiatry, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Taiwan; Graduate Institute of Medicine, Department of Psychiatry, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Cian-Ruei Jian
- Department of Psychiatry, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Taiwan
| | - Chien-Wen Lin
- Department of Psychiatry, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Taiwan
| | - I-Mei Lin
- Department of Psychology, College of Humanities and Social Sciences, Kaohsiung Medical University, Taiwan; Department of Medical Research, Kaohsiung Medical University Hospital, Taiwan.
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Ribeiro TF, Carriello MA, de Paula EP, Garcia AC, da Rocha GL, Teive HAG. Clinical applications of neurofeedback based on sensorimotor rhythm: a systematic review and meta-analysis. Front Neurosci 2023; 17:1195066. [PMID: 38053609 PMCID: PMC10694284 DOI: 10.3389/fnins.2023.1195066] [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: 03/28/2023] [Accepted: 07/07/2023] [Indexed: 12/07/2023] Open
Abstract
Background Among the brain-machine interfaces, neurofeedback is a non-invasive technique that uses sensorimotor rhythm (SMR) as a clinical intervention protocol. This study aimed to investigate the clinical applications of SMR neurofeedback to understand its clinical effectiveness in different pathologies or symptoms. Methods A systematic review study with meta-analysis of the clinical applications of EEG-based SMR neurofeedback performed using pre-selected publication databases. A qualitative analysis of these studies was performed using the Consensus tool on the Reporting and Experimental Design of Neurofeedback studies (CRED-nf). The Meta-analysis of clinical efficacy was carried out using Review Manager software, version 5.4.1 (RevMan 5; Cochrane Collaboration, Oxford, UK). Results The qualitative analysis includes 44 studies, of which only 27 studies had some kind of control condition, five studies were double-blinded, and only three reported a blind follow-up throughout the intervention. The meta-analysis included a total sample of 203 individuals between stroke and fibromyalgia. Studies on multiple sclerosis, insomnia, quadriplegia, paraplegia, and mild cognitive impairment were excluded due to the absence of a control group or results based only on post-intervention scales. Statistical analysis indicated that stroke patients did not benefit from neurofeedback interventions when compared to other therapies (Std. mean. dif. 0.31, 95% CI 0.03-0.60, p = 0.03), and there was no significant heterogeneity among stroke studies, classified as moderate I2 = 46% p-value = 0.06. Patients diagnosed with fibromyalgia showed, by means of quantitative analysis, a better benefit for the group that used neurofeedback (Std. mean. dif. -0.73, 95% CI -1.22 to -0.24, p = 0.001). Thus, on performing the pooled analysis between conditions, no significant differences were observed between the neurofeedback intervention and standard therapy (0.05, CI 95%, -0.20 to -0.30, p = 0.69), with the presence of substantial heterogeneity I2 = 92.2%, p-value < 0.001. Conclusion We conclude that although neurofeedback based on electrophysiological patterns of SMR contemplates the interest of numerous researchers and the existence of research that presents promising results, it is currently not possible to point out the clinical benefits of the technique as a form of clinical intervention. Therefore, it is necessary to develop more robust studies with a greater sample of a more rigorous methodology to understand the benefits that the technique can provide to the population.
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Affiliation(s)
- Tatiana Ferri Ribeiro
- Internal Medicine and Health Sciences, Federal University of Paraná (UFPR), Curitiba, Paraná, Brazil
| | - Marcelo Alves Carriello
- Internal Medicine and Health Sciences, Federal University of Paraná (UFPR), Curitiba, Paraná, Brazil
| | - Eugenio Pereira de Paula
- Physical Education (UFPR)—Invited Colaborador, Federal University of Paraná (UFPR), Curitiba, Paraná, Brazil
| | - Amanda Carvalho Garcia
- Internal Medicine and Health Sciences, Federal University of Paraná (UFPR), Curitiba, Paraná, Brazil
| | - Guilherme Luiz da Rocha
- Internal Medicine and Health Sciences, Federal University of Paraná (UFPR), Curitiba, Paraná, Brazil
| | - Helio Afonso Ghizoni Teive
- Internal Medicine and Health Sciences, Federal University of Paraná (UFPR), Curitiba, Paraná, Brazil
- Department of Clinical Medicine, UFPR, and Coordinator of the Movement Disorders Sector, Neurology Service, Clinic Hospital, Federal University of Paraná (UFPR), Curitiba, Paraná, Brazil
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Wang H, Hou Y, Zhan S, Li N, Liu J, Song P, Wang Y, Wang H. EEG Biofeedback Decreases Theta and Beta Power While Increasing Alpha Power in Insomniacs: An Open-Label Study. Brain Sci 2023; 13:1542. [PMID: 38002502 PMCID: PMC10670123 DOI: 10.3390/brainsci13111542] [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: 09/28/2023] [Revised: 10/27/2023] [Accepted: 10/30/2023] [Indexed: 11/26/2023] Open
Abstract
Insomnia, often associated with anxiety and depression, is a prevalent sleep disorder. Biofeedback (BFB) treatment can help patients gain voluntary control over physiological events such as by utilizing electroencephalography (EEG) and electromyography (EMG) power. Previous studies have rarely predicted biofeedback efficacy by measuring the changes in relative EEG power; therefore, we investigated the clinical efficacy of biofeedback for insomnia and its potential neural mechanisms. We administered biofeedback to 82 patients with insomnia, of whom 68 completed 10 sessions and 14 completed 20 sessions. The average age of the participants was 49.38 ± 12.78 years, with 26 men and 56 women. Each biofeedback session consisted of 5 min of EMG and 30 min of EEG feedback, with 2 min of data recorded before and after the session. Sessions were conducted every other day, and four scale measures were taken before the first, fifth, and tenth sessions and after the twentieth session. After 20 sessions of biofeedback treatment, scores on the Pittsburgh Sleep Quality Index (PSQI) were significantly reduced compared with those before treatment (-5.5 ± 1.43,t = -3.85, p = 0.006), and scores on the Beck Depression Inventory (BDI-II) (-7.15 ± 2.43, t = -2.94, p = 0.012) and the State-Trait Anxiety Inventory (STAI) (STAI-S: -12.36 ± 3.40, t = -3.63, p = 0.003; and STAI-T: -9.86 ± 2.38, t = -4.41, p = 0.001) were significantly lower after treatment than before treatment. Beta and theta power were significantly reduced after treatment, compared with before treatment (F = 6.25, p = 0.014; and F = 11.91, p = 0.001). Alpha power was increased after treatment, compared with before treatment, but the difference was not prominently significant (p > 0.05). EMG activity was significantly decreased after treatment, compared with before treatment (F = 2.11, p = 0.015). Our findings suggest that BFB treatment based on alpha power and prefrontal EMG relieves insomnia as well as anxiety and depression and may be associated with increased alpha power, decreased beta and theta power, and decreased EMG power.
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Affiliation(s)
- Huicong Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; (H.W.); (Y.H.); (S.Z.); (N.L.); (J.L.); (P.S.)
- Beijing Key Laboratory of Neuromodulation, Beijing 100053, China
- Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China
- Center for Sleep and Consciousness Disorders, Beijing Institute for Brain Disorders, Beijing 100053, China
- Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Yue Hou
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; (H.W.); (Y.H.); (S.Z.); (N.L.); (J.L.); (P.S.)
- Beijing Key Laboratory of Neuromodulation, Beijing 100053, China
- Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China
- Center for Sleep and Consciousness Disorders, Beijing Institute for Brain Disorders, Beijing 100053, China
- Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053, China
- Hebei Hospital of Xuanwu Hospital, Capital Medical University, Shijiazhuang 050030, China
- Neuromedical Technology Innovation Center of Hebei Province, Shijiazhuang 050030, China
| | - Shuqin Zhan
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; (H.W.); (Y.H.); (S.Z.); (N.L.); (J.L.); (P.S.)
- Beijing Key Laboratory of Neuromodulation, Beijing 100053, China
- Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China
- Center for Sleep and Consciousness Disorders, Beijing Institute for Brain Disorders, Beijing 100053, China
- Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Ning Li
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; (H.W.); (Y.H.); (S.Z.); (N.L.); (J.L.); (P.S.)
- Beijing Key Laboratory of Neuromodulation, Beijing 100053, China
- Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China
- Center for Sleep and Consciousness Disorders, Beijing Institute for Brain Disorders, Beijing 100053, China
- Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Jianghong Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; (H.W.); (Y.H.); (S.Z.); (N.L.); (J.L.); (P.S.)
- Beijing Key Laboratory of Neuromodulation, Beijing 100053, China
- Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China
- Center for Sleep and Consciousness Disorders, Beijing Institute for Brain Disorders, Beijing 100053, China
- Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Penghui Song
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; (H.W.); (Y.H.); (S.Z.); (N.L.); (J.L.); (P.S.)
- Beijing Key Laboratory of Neuromodulation, Beijing 100053, China
- Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China
- Center for Sleep and Consciousness Disorders, Beijing Institute for Brain Disorders, Beijing 100053, China
- Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Yuping Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; (H.W.); (Y.H.); (S.Z.); (N.L.); (J.L.); (P.S.)
- Beijing Key Laboratory of Neuromodulation, Beijing 100053, China
- Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China
- Center for Sleep and Consciousness Disorders, Beijing Institute for Brain Disorders, Beijing 100053, China
- Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053, China
- Hebei Hospital of Xuanwu Hospital, Capital Medical University, Shijiazhuang 050030, China
- Neuromedical Technology Innovation Center of Hebei Province, Shijiazhuang 050030, China
| | - Hongxing Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; (H.W.); (Y.H.); (S.Z.); (N.L.); (J.L.); (P.S.)
- Beijing Key Laboratory of Neuromodulation, Beijing 100053, China
- Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China
- Center for Sleep and Consciousness Disorders, Beijing Institute for Brain Disorders, Beijing 100053, China
- Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100053, China
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Patil AU, Lin C, Lee SH, Huang HW, Wu SC, Madathil D, Huang CM. Review of EEG-based neurofeedback as a therapeutic intervention to treat depression. Psychiatry Res 2023; 329:111591. [PMID: 36682174 PMCID: PMC9837232 DOI: 10.1016/j.pscychresns.2023.111591] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Revised: 11/24/2022] [Accepted: 01/08/2023] [Indexed: 01/15/2023]
Abstract
Depression, or major depressive disorder, is a common mental disorder that affects individuals' behavior, mood, and physical health, and its prevalence has increased during the lockdowns implemented to curb the COVID-19 pandemic. There is an urgent need to update the treatment recommendations for mental disorders during such crises. Conventional interventions to treat depression include long-term pharmacotherapy and cognitive behavioral therapy. Electroencephalogram-neurofeedback (EEG-NF) training has been suggested as a non-invasive option to treat depression with minimal side effects. In this systematic review, we summarize the recent literature on EEG-NF training for treating depression. The 12 studies included in our final sample reported that despite several issues related to EEG-NF practices, patients with depression showed significant cognitive, clinical, and neural improvements following EEG-NF training. Given its low cost and the low risk of side effects due to its non-invasive nature, we suggest that EEG-NF is worth exploring as an augmented tool for patients who already receive standard medications but remain symptomatic, and that EEG-NF training may be an effective intervention tool that can be utilized as a supplementary treatment for depression. We conclude by providing some suggestions related to experimental designs and standards to improve current EEG-NF training practices for treating depression.
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Affiliation(s)
- Abhishek Uday Patil
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan; Center for Intelligent Drug Systems and Smart Bio-devices (IDS(2)B), National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Chemin Lin
- Department of Psychiatry, Chang Gung Memorial Hospital, Keelung, Taiwan; College of Medicine, Chang Gung University, Taoyuan, Taiwan; Community Medicine Research Center, Chang Gung Memorial Hospital, Keelung, Taiwan
| | - Shwu-Hua Lee
- College of Medicine, Chang Gung University, Taoyuan, Taiwan; Department of Psychiatry, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Hsu-Wen Huang
- Department of Linguistics and Translation, City University of Hong Kong, Hong Kong
| | - Shun-Chi Wu
- Department of Engineering and System Science, National Tsing Hua University, Hsinchu, Taiwan
| | - Deepa Madathil
- Jindal Institute of Behavioural Sciences, O.P. Jindal Global University, Haryana, India.
| | - Chih-Mao Huang
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan; Center for Intelligent Drug Systems and Smart Bio-devices (IDS(2)B), National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
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The Resting State of Taiwan EEG Normative Database: Z-Scores of Patients with Major Depressive Disorder as the Cross-Validation. Brain Sci 2023; 13:brainsci13020351. [PMID: 36831893 PMCID: PMC9954681 DOI: 10.3390/brainsci13020351] [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: 01/19/2023] [Revised: 02/10/2023] [Accepted: 02/15/2023] [Indexed: 02/22/2023] Open
Abstract
This study referred to the standard of electroencephalography (EEG) collection of normative databases and collected the Taiwan normative database to examine the reliability and validation of the Taiwan EEG normative database. We included 260 healthy participants and divided them into five groups in 10-year age-group segments and calculated the EEG means, standard deviation, and z-scores. Internal consistency reliability was verified at different frequencies between the three electrode locations in the Taiwan normative database. We recruited 221 major depressive disorder (MDD) patients for cross-validation between the Taiwan and NeuroGuide normative databases. There were high internal consistency reliabilities for delta, theta, alpha, beta, and high-beta at C3, Cz, and C4 in the HC group. There were high correlations between the two z-scores of the Taiwan and NeuroGuide normative databases in the frontal, central, parietal, temporal, and occipital lobes from MDD patients. The beta z-scores in the frontal lobe and central area, and the high-beta z-scores in the frontal, central, parietal, temporal, and occipital lobes were greater than one for MDD patients; in addition, the beta and high-beta absolute value z-scores in the whole brain were greater than the ones of MDD patients. The Taiwan EEG normative database has good psychometric characteristics of internal consistency reliability and cross-validation.
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Dehghani A, Soltanian-Zadeh H, Hossein-Zadeh GA. Probing fMRI brain connectivity and activity changes during emotion regulation by EEG neurofeedback. Front Hum Neurosci 2023; 16:988890. [PMID: 36684847 PMCID: PMC9853008 DOI: 10.3389/fnhum.2022.988890] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 12/13/2022] [Indexed: 01/09/2023] Open
Abstract
Despite the existence of several emotion regulation studies using neurofeedback, interactions among a small number of regions were evaluated, and therefore, further investigation is needed to understand the interactions of the brain regions involved in emotion regulation. We implemented electroencephalography (EEG) neurofeedback with simultaneous functional magnetic resonance imaging (fMRI) using a modified happiness-inducing task through autobiographical memories to upregulate positive emotion. Then, an explorative analysis of whole brain regions was done to understand the effect of neurofeedback on brain activity and the interaction of whole brain regions involved in emotion regulation. The participants in the control and experimental groups were asked to do emotion regulation while viewing positive images of autobiographical memories and getting sham or real (based on alpha asymmetry) EEG neurofeedback, respectively. The proposed multimodal approach quantified the effects of EEG neurofeedback in changing EEG alpha power, fMRI blood oxygenation level-dependent (BOLD) activity of prefrontal, occipital, parietal, and limbic regions (up to 1.9% increase), and functional connectivity in/between prefrontal, parietal, limbic system, and insula in the experimental group. New connectivity links were identified by comparing the brain functional connectivity between experimental conditions (Upregulation and View blocks) and also by comparing the brain connectivity of the experimental and control groups. Psychometric assessments confirmed significant changes in positive and negative mood states in the experimental group by neurofeedback. Based on the exploratory analysis of activity and connectivity among all brain regions involved in emotion regions, we found significant BOLD and functional connectivity increases due to EEG neurofeedback in the experimental group, but no learning effect was observed in the control group. The results reveal several new connections among brain regions as a result of EEG neurofeedback which can be justified according to emotion regulation models and the role of those regions in emotion regulation and recalling positive autobiographical memories.
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Affiliation(s)
- Amin Dehghani
- School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran,Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, United States,*Correspondence: Amin Dehghani, ,
| | - Hamid Soltanian-Zadeh
- School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran,Medical Image Analysis Lab, Department of Radiology and Research Administration, Henry Ford Health System, Detroit, MI, United States,School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Gholam-Ali Hossein-Zadeh
- School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran,School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
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Białkowska J, Mroczkowska D, Boraczyński M. Subjective Improvement of Sleep in Insomnia Patients Treated at a Day Rehabilitation Centre After the Use of EEG Neurofeedback Therapy – a Pilot Study. REHABILITACJA MEDYCZNA 2022. [DOI: 10.5604/01.3001.0016.0627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
Introduction: Insomnia affects nearly 1/3 of the worldwide population. Electroencephalography neurofeedback (EEG-NFB) is one of the methods used in applied psychophysiology, which can improve nightly sleep scheme.
Research objective: The aim of this pilot study was to assess the relative effect of a 20-day neurorehabilitation intervention based on EEG-NFB therapy in insomnia patients treated at a day rehabilitation centre.
Materials and methods: Seventy-four patients with insomnia: 28 women (mean age ± SD: 67.9 ± 8.84 years, range: 42–83 years) and 46 men (mean age ± SD: 63.0 ± 9.24 years, range: 42-80 years) were subjected to the EEG-NFB training-neurorehabilitation using the C4 protocol: sensorimotor rhythm (SMR) (12-15 Hz)/theta (4-7 Hz). The individual everyday EEG-NFB training consisted of 20, 30-minute sessions. Before and after the training, the data was collected from 12-electrode quantitative EEG (QEEG) tests. In addition, several standardised psychological questionnaires were performed: Pittsburgh Sleep Quality Index (PSQI), State-Trait Anxiety Inventory (STAI) and Beck Depression Inventory (BDI).
Results: The EEG-NFB therapy reduced anxiety (7.39 ± 1.0 vs. 6.12 ± 0.88 in STAI, p< 0.001) and improved patients' mood (17.6 ± 3.9 vs. 14.65 ± 3.39 in BDI, p< 0.001). During the PSQI test, the time of falling asleep and number of night awakenings were statistically reduced (both p<0.001). However, there was no significant difference in the -SMR amplitude between pre- to post-treatment (9.15 ± 3.11 and 8.62 ± 2.82, respectively, p=0.095).
Conclusions: Due to the subjective improvement of sleep quality, without statistically significant changes in the electrophysiological record (expressed by SMR amplitude), it is advisable to continue research with the use of EEG-NFB therapy.
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Affiliation(s)
- Joanna Białkowska
- Faculty of Health Sciences, Collegium Medicum, University of Warmia and Mazury in Olsztyn, Poland / Municipal Polyclinical Hospital in Olsztyn, Poland
| | - Dorota Mroczkowska
- Faculty of Health Sciences, Collegium Medicum, University of Warmia and Mazury in Olsztyn, Poland
| | - Michał Boraczyński
- Faculty of Health Sciences, Collegium Medicum, University of Warmia and Mazury in Olsztyn, Poland
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Behboodi A, Lee WA, Hinchberger VS, Damiano DL. Determining optimal mobile neurofeedback methods for motor neurorehabilitation in children and adults with non-progressive neurological disorders: a scoping review. J Neuroeng Rehabil 2022; 19:104. [PMID: 36171602 PMCID: PMC9516814 DOI: 10.1186/s12984-022-01081-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 09/08/2022] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Brain-computer interfaces (BCI), initially designed to bypass the peripheral motor system to externally control movement using brain signals, are additionally being utilized for motor rehabilitation in stroke and other neurological disorders. Also called neurofeedback training, multiple approaches have been developed to link motor-related cortical signals to assistive robotic or electrical stimulation devices during active motor training with variable, but mostly positive, functional outcomes reported. Our specific research question for this scoping review was: for persons with non-progressive neurological injuries who have the potential to improve voluntary motor control, which mobile BCI-based neurofeedback methods demonstrate or are associated with improved motor outcomes for Neurorehabilitation applications? METHODS We searched PubMed, Web of Science, and Scopus databases with all steps from study selection to data extraction performed independently by at least 2 individuals. Search terms included: brain machine or computer interfaces, neurofeedback and motor; however, only studies requiring a motor attempt, versus motor imagery, were retained. Data extraction included participant characteristics, study design details and motor outcomes. RESULTS From 5109 papers, 139 full texts were reviewed with 23 unique studies identified. All utilized EEG and, except for one, were on the stroke population. The most commonly reported functional outcomes were the Fugl-Meyer Assessment (FMA; n = 13) and the Action Research Arm Test (ARAT; n = 6) which were then utilized to assess effectiveness, evaluate design features, and correlate with training doses. Statistically and functionally significant pre-to post training changes were seen in FMA, but not ARAT. Results did not differ between robotic and electrical stimulation feedback paradigms. Notably, FMA outcomes were positively correlated with training dose. CONCLUSION This review on BCI-based neurofeedback training confirms previous findings of effectiveness in improving motor outcomes with some evidence of enhanced neuroplasticity in adults with stroke. Associative learning paradigms have emerged more recently which may be particularly feasible and effective methods for Neurorehabilitation. More clinical trials in pediatric and adult neurorehabilitation to refine methods and doses and to compare to other evidence-based training strategies are warranted.
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Affiliation(s)
- Ahad Behboodi
- Rehabilitation Medicine Department, National Institutes of Health, Bethesda, MD USA
| | - Walker A. Lee
- Rehabilitation Medicine Department, National Institutes of Health, Bethesda, MD USA
| | | | - Diane L. Damiano
- Rehabilitation Medicine Department, National Institutes of Health, Bethesda, MD USA
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10
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Moore PT. Infra-low frequency neurofeedback and insomnia as a model of CNS dysregulation. Front Hum Neurosci 2022; 16:959491. [PMID: 36211128 PMCID: PMC9534730 DOI: 10.3389/fnhum.2022.959491] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 07/12/2022] [Indexed: 11/13/2022] Open
Abstract
This paper will review what is conventionally known of sleep homeostasis and focus on insomnia as a primary manifestation of brain dysregulation, whether as a solitary symptom or as part of a larger syndrome such as post-traumatic stress disorder, PTSD. It will discuss in brief behavioral/mindfulness treatments that have been used to treat neurologic diseases, as this is germane to the phenomenology of neurofeedback (NF). It will explore how neurofeedback may work at the subconscious level and cover the current clinical experience of the effectiveness of this technique in the treatment of insomnia. It will conclude with a case presentation.
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11
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Patil AU, Madathil D, Fan YT, Tzeng OJL, Huang CM, Huang HW. Neurofeedback for the Education of Children with ADHD and Specific Learning Disorders: A Review. Brain Sci 2022; 12:brainsci12091238. [PMID: 36138974 PMCID: PMC9497239 DOI: 10.3390/brainsci12091238] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 09/03/2022] [Accepted: 09/07/2022] [Indexed: 12/02/2022] Open
Abstract
Neurofeedback (NF) is a type of biofeedback in which an individual’s brain activity is measured and presented to them to support self-regulation of ongoing brain oscillations and achieve specific behavioral and neurophysiological outcomes. NF training induces changes in neurophysiological circuits that are associated with behavioral changes. Recent evidence suggests that the NF technique can be used to train electrical brain activity and facilitate learning among children with learning disorders. Toward this aim, this review first presents a generalized model for NF systems, and then studies involving NF training for children with disorders such as dyslexia, attention-deficit/hyperactivity disorder (ADHD), and other specific learning disorders such as dyscalculia and dysgraphia are reviewed. The discussion elaborates on the potential for translational applications of NF in educational and learning settings with details. This review also addresses some issues concerning the role of NF in education, and it concludes with some solutions and future directions. In order to provide the best learning environment for children with ADHD and other learning disorders, it is critical to better understand the role of NF in educational settings. The review provides the potential challenges of the current systems to aid in highlighting the issues undermining the efficacy of current systems and identifying solutions to address them. The review focuses on the use of NF technology in education for the development of adaptive teaching methods and the best learning environment for children with learning disabilities.
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Affiliation(s)
- Abhishek Uday Patil
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan
| | - Deepa Madathil
- Jindal Institute of Behavioural Sciences, O.P. Jindal Global University, Haryana 131001, India
| | - Yang-Tang Fan
- Graduate Institute of Medicine, Yuan Ze University, Taoyuan 320315, Taiwan
| | - Ovid J. L. Tzeng
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan
- Centre for Intelligent Drug Systems and Smart Bio-Devices (IDSB), National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan
- College of Humanities and Social Sciences, Taipei Medical University, Taipei 106339, Taiwan
- Department of Educational Psychology and Counseling, National Taiwan Normal University, Taipei 106308, Taiwan
- Hong Kong Institute for Advanced Studies, City University of Hong Kong, Hong Kong
| | - Chih-Mao Huang
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan
- Centre for Intelligent Drug Systems and Smart Bio-Devices (IDSB), National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan
| | - Hsu-Wen Huang
- Department of Linguistics and Translation, City University of Hong Kong, Hong Kong
- Correspondence: ; Tel.: +852-3442-2579
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12
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Effect of neurofeedback therapy on neurological post-COVID-19 complications (A pilot study). PLoS One 2022; 17:e0271350. [PMID: 35895740 PMCID: PMC9328527 DOI: 10.1371/journal.pone.0271350] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 06/28/2022] [Indexed: 11/19/2022] Open
Abstract
Objective
Anxiety, fatigue and depression are common neurological manifestations after COVID-19. So far, post-COVID complications were treated by rehabilitation, oxygen therapy and immunotherapy. Effects of neurofeedback on post-COVID complications and their potential interrelatedness have not been studied yet. In this pilot study, we investigated the effectiveness of neurofeedback (Othmer method) for treatment of fatigue, anxiety, and depression after COVID-19.
Methods
10 participants met inclusion criteria for having positive anamnesis of at least one of the following complications following COVID-19: fatigue, anxiety, and depression which were measured by questionnaires. ANOVA was used for calculating differences in questionnaire score before and after neurofeedback. Pearson’s correlation coefficient was used to calculate correlations between anxiety, depression and fatigue.
Results
After five neurofeedback sessions, there came to significant reduction of severity of post-COVID anxiety and depression persisting for at least one month. Effect of neurofeedback on fatigue was insignificant. Severity of anxiety, fatigue and depression as well as reductions in depression and fatigue were positively correlated with each other.
Conclusion
These findings showed effectiveness neurofeedback for reducing anxiety and depression after COVID-19 and for studying correlations between neurological complications after COVID-19. However, since our pilot clinical trial was open-label, it is hard to differentiate between neurofeedback-specific and unspecific effects on our participants. Future randomized controlled trials with more robust sample are necessary to investigate feasibility of neurofeedback for post-COVID neurological complications. The study has identification number trial ID ISRCTN49037874 in ISRCTN register of clinical trials (Retrospectively registered).
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13
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Orendáčová M, Kvašňák E. Possible Mechanisms Underlying Neurological Post-COVID Symptoms and Neurofeedback as a Potential Therapy. Front Hum Neurosci 2022; 16:837972. [PMID: 35431842 PMCID: PMC9010738 DOI: 10.3389/fnhum.2022.837972] [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: 12/17/2021] [Accepted: 01/26/2022] [Indexed: 12/13/2022] Open
Abstract
Theoretical considerations related to neurological post-COVID complications have become a serious issue in the COVID pandemic. We propose 3 theoretical hypotheses related to neurological post-COVID complications. First, pathophysiological processes responsible for long-term neurological complications caused by COVID-19 might have 2 phases: (1) Phase of acute Sars-CoV-2 infection linked with the pathogenesis responsible for the onset of COVID-19-related neurological complications and (2) the phase of post-acute Sars-CoV-2 infection linked with the pathogenesis responsible for long-lasting persistence of post-COVID neurological problems and/or exacerbation of another neurological pathologies. Second, post-COVID symptoms can be described and investigated from the perspective of dynamical system theory exploiting its fundamental concepts such as system parameters, attractors and criticality. Thirdly, neurofeedback may represent a promising therapy for neurological post-COVID complications. Based on the current knowledge related to neurofeedback and what is already known about neurological complications linked to acute COVID-19 and post-acute COVID-19 conditions, we propose that neurofeedback modalities, such as functional magnetic resonance-based neurofeedback, quantitative EEG-based neurofeedback, Othmer's method of rewarding individual optimal EEG frequency and heart rate variability-based biofeedback, represent a potential therapy for improvement of post-COVID symptoms.
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Affiliation(s)
- Mária Orendáčová
- Department of Medical Biophysics and Medical Informatics, Third Faculty of Medicine, Charles University in Prague, Prague, Czechia
| | - Eugen Kvašňák
- Department of Medical Biophysics and Medical Informatics, Third Faculty of Medicine, Charles University in Prague, Prague, Czechia
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14
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Kwan Y, Yoon S, Suh S, Choi S. A Randomized Controlled Trial Comparing Neurofeedback and Cognitive-Behavioral Therapy for Insomnia Patients: Pilot Study. Appl Psychophysiol Biofeedback 2022; 47:95-106. [PMID: 35147813 DOI: 10.1007/s10484-022-09534-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/04/2022] [Indexed: 11/02/2022]
Abstract
Insomnia is a common disease that negatively affects patients both mentally and physically. While insomnia disorder is mainly characterized by hyperarousal, a few studies that have directly intervened with cortical arousal. This study was conducted to investigate the effect of a neurofeedback protocol for reducing cortical arousal on insomnia compared to cognitive-behavioral treatment for insomnia (CBT-I). Seventeen adults with insomnia, free of other psychiatric illnesses, were randomly assigned to neurofeedback or CBT-I. All participants completed questionnaires on insomnia [Insomnia Severity Index (ISI)], sleep quality [Pittsburgh Sleep Quality Index (PSQI)], and dysfunctional cognition [Dysfunctional Beliefs and Attitudes about Sleep Scale (DBAS-16)]. The neurofeedback group showed decreases in beta waves and increases in theta and alpha waves in various areas of the electroencephalogram (EEG), indicating lowered cortical arousal. The ISI and PSQI scores were significantly decreased, and sleep efficiency and sleep satisfaction were increased compared to the pre-treatment scores in both groups. DBAS scores decreased only in the CBT-I group (NF p = 0.173; CBT-I p = 0.012). This study confirmed that neurofeedback training could alleviate the symptoms of insomnia by reducing cortical hyperarousal in patients, despite the limited effect in reducing cognitive dysfunction compared to CBT-I.
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Affiliation(s)
- Yunna Kwan
- Department of Psychology, Duksung Women's University, Seoul, Republic of Korea.,Department of Psychiatry, Wonju Severance Christian Hospital, Wonju, Republic of Korea
| | - Soyoung Yoon
- Department of Psychology, Duksung Women's University, Seoul, Republic of Korea
| | - Sooyeon Suh
- Department of Psychology, Sungshin Women's University, Seoul, Republic of Korea
| | - Sungwon Choi
- Department of Psychology, Duksung Women's University, Seoul, Republic of Korea.
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15
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Lambert-Beaudet F, Journault WG, Rudziavic Provençal A, Bastien CH. Neurofeedback for insomnia: Current state of research. World J Psychiatry 2021; 11:897-914. [PMID: 34733650 PMCID: PMC8546766 DOI: 10.5498/wjp.v11.i10.897] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Revised: 05/18/2021] [Accepted: 08/27/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Chronic insomnia affects about 6%-13% of the Canadian population. Although treatments already exist, they each have their own issues. Neurofeedback is a neuromodulation technique that specifically targets abnormal brain activity and is gaining attention as a possible insomnia treatment.
AIM To review the latest studies pertaining to the use of neurofeedback in the treatment of insomnia.
METHODS In this non-systematic review, only experimental studies assessing the effects of neurofeedback on patients with insomnia were targeted across four bibliographic databases.
RESULTS A total of 12 studies were retained. All neurofeedback studies included in this study showed a clear improvement of subjective sleep. However, data concerning objective improvement are contradictory. Most studies regarding surface and z-score neurofeedback show that neurofeedback targeting the sensorimotor rhythm in the sensorimotor cortex may help improve subjective sleep. A placebo effect seems also to be present in some studies. Several limitations were present in each study.
CONCLUSION While studies concerning neurofeedback as a treatment for insomnia are encouraging, many methodological barriers remain to be resolved to prove its efficacy unequivocally. More studies using robust design parameters, as well as the replication of existing studies, are necessary to support neurofeedback as an effective treatment for insomnia.
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Affiliation(s)
| | | | | | - Célyne H Bastien
- Department of Psychology, School of Psychology Laval University, Québec G1V0A6, Canada
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16
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Pérez-Elvira R, Oltra-Cucarella J, Carrobles JA, Moltó J, Flórez M, Parra S, Agudo M, Saez C, Guarino S, Costea RM, Neamtu B. Enhancing the Effects of Neurofeedback Training: The Motivational Value of the Reinforcers. Brain Sci 2021; 11:brainsci11040457. [PMID: 33916676 PMCID: PMC8067059 DOI: 10.3390/brainsci11040457] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 04/01/2021] [Accepted: 04/02/2021] [Indexed: 11/16/2022] Open
Abstract
The brain activity that is measured by electroencephalography (EEG) can be modified through operant conditioning, specifically using neurofeedback (NF). NF has been applied to several disorders claiming that a change in the erratic brain activity would be accompanied by a reduction of the symptoms. However, the expected results are not always achieved. Some authors have suggested that the lack of an adequate response may be due to an incorrect application of the operant conditioning principles. A key factor in operant conditioning is the use of reinforcers and their value in modifying behavior, something that is not always sufficiently taken into account. This work aims to clarify the relevance of the motivational value versus the purely informational value of the reinforcer. In this study, 113 subjects were randomly assigned two different reinforcer conditions: a selected reinforcer—the subjects subjectively selected the reinforcers—or an imposed reinforcer—the reinforcers were assigned by the experimenter—and both groups undertook NF sessions to enhance the sensorimotor rhythm (SMR). In addition, the selected reinforcer group was divided into two subgroups: one receiving real NF and the other one sham NF. There were no significant differences between the groups at baseline in terms of SMR amplitude. After the intervention, only those subjects belonging to the selected reinforcer group and receiving real NF increased their SMR. Our results provide evidence for the importance of the motivational value of the reinforcer in Neurofeedback success.
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Affiliation(s)
- Rubén Pérez-Elvira
- Neuropsychophysiology Laboratory, NEPSA Rehabilitación Neurológica, 3003 Salamanca, Spain; (R.P.-E.); (M.A.); (C.S.)
| | - Javier Oltra-Cucarella
- Department of Health Psychology, Universidad Miguel Hernández de Elche, 03202 Elche, Spain
- Correspondence:
| | - José Antonio Carrobles
- Biological and Health Psychology Department, Universidad Autónoma de Madrid, 28049 Madrid, Spain;
| | - Jorge Moltó
- PSYD-Neurofeedback, 46022 Valencia, Spain; (J.M.); (M.F.)
| | | | | | - María Agudo
- Neuropsychophysiology Laboratory, NEPSA Rehabilitación Neurológica, 3003 Salamanca, Spain; (R.P.-E.); (M.A.); (C.S.)
| | - Clara Saez
- Neuropsychophysiology Laboratory, NEPSA Rehabilitación Neurológica, 3003 Salamanca, Spain; (R.P.-E.); (M.A.); (C.S.)
| | - Sergio Guarino
- NEPSA Rehabilitación Neurológica, 47001 Valladolid, Spain;
| | - Raluca Maria Costea
- Research Department (Ceforaten), Sibiu Pediatric Hospital, 550178 Sibiu, Romania; (R.M.C.); (B.N.)
- Faculty of Medicine Lucian Blaga, University from Sibiu, 550169 Sibiu, Romania
| | - Bogdan Neamtu
- Research Department (Ceforaten), Sibiu Pediatric Hospital, 550178 Sibiu, Romania; (R.M.C.); (B.N.)
- Faculty of Medicine Lucian Blaga, University from Sibiu, 550169 Sibiu, Romania
- Faculty of Engineering, Lucian Blaga, University from Sibiu, 550025 Sibiu, Romania
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17
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Melo DLM, Carvalho LBC, Prado LBF, Prado GF. Biofeedback Therapies for Chronic Insomnia: A Systematic Review. Appl Psychophysiol Biofeedback 2020; 44:259-269. [PMID: 31123938 DOI: 10.1007/s10484-019-09442-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
The treatment of insomnia is still a challenge in clinical practice. This systematic review of randomized and quasi-randomized clinical trials aims to summarize the evidence for the use of biofeedback techniques in the treatment of chronic insomnia. Studies that compared biofeedback with other techniques of cognitive behavioral therapy, placebo, or absence of treatment were selected. The outcomes evaluated included sleep onset latency, total sleep time, sleep fragmentation, sleep efficiency and subjective sleep quality. Comparing to placebo and absence of treatment, some studies suggest possible benefits from the use of biofeedback for chronic insomnia in decreasing sleep onset latency and number of awakenings; however, there was marked divergence among included studies. There was no evidence of improvement in total sleep time, sleep efficiency and subjective sleep quality. Moreover, the maintenance of long-term benefits lacks evidence for any outcome. In the majority of outcomes evaluated, no significant differences in the effectiveness of biofeedback compared with other cognitive behavioral therapy techniques were observed. This systematic review found conflicting evidence for the effectiveness of biofeedback techniques in the treatment of chronic insomnia. Inter- and intra-group clinical heterogeneity among studies could be a reasonable explanation for the divergent results. These findings emphasize the need of performing further randomized clinical trials of higher methodological quality in order to better delineate the effectiveness of biofeedback on chronic insomnia treatment.
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Affiliation(s)
- Denise Lima Medeiros Melo
- Department of Neurology, Neuro-Sono Sleep Center, Federal University of Sao Paulo-UNIFESP, R. Cláudio Rossi, 394, São Paulo, SP, CEP 01547-000, Brazil.
| | - Luciane Bizari Coin Carvalho
- Department of Neurology, Neuro-Sono Sleep Center, Federal University of Sao Paulo-UNIFESP, R. Cláudio Rossi, 394, São Paulo, SP, CEP 01547-000, Brazil
| | - Lucila Bizari Fernandes Prado
- Department of Neurology, Neuro-Sono Sleep Center, Federal University of Sao Paulo-UNIFESP, R. Cláudio Rossi, 394, São Paulo, SP, CEP 01547-000, Brazil
| | - Gilmar Fernandes Prado
- Department of Neurology, Neuro-Sono Sleep Center, Federal University of Sao Paulo-UNIFESP, R. Cláudio Rossi, 394, São Paulo, SP, CEP 01547-000, Brazil
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18
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Coben R, Hammond DC, Arns M. 19 Channel Z-Score and LORETA Neurofeedback: Does the Evidence Support the Hype? Appl Psychophysiol Biofeedback 2020; 44:1-8. [PMID: 30255461 PMCID: PMC6373269 DOI: 10.1007/s10484-018-9420-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Neurofeedback is a well-investigated treatment for ADHD and epilepsy, especially when restricted to standard protocols such as theta/beta, slow cortical potentials and sensori-motor rhythm neurofeedback. Advances in any field are welcome and other techniques are being pursued. Manufacturers and clinicians are marketing ‘superior’ neurofeedback approaches including 19 channel Z-score neurofeedback (ZNFB) and 3-D LORETA neurofeedback (with or without Z-scores; LNFB). We conducted a review of the empirical literature to determine if such claims were warranted. This review included the above search terms in Pubmed, Google scholar and any references that met our criteria from the ZNFB publication list and was restricted to group based studies examining improvement in a clinical population that underwent peer review (book chapters, magazine articles or conference presentations are not included since these are not peer reviewed). Fifteen relevant studies emerged with only six meeting our criterion. Based on review of these studies it was concluded that empirical validation of these approaches is sorely lacking. There is no empirical data that supports the notion that 19-channel z-score neurofeedback is effective or superior. The quality of studies for LNFB was better compared to ZNFB and some suggestion for efficacy was demonstrated for ADHD and Tinnitus distress. However, these findings need to be replicated, extended to other populations and have yet to show any “superiority.” Our conclusions continue to emphasize the pervasive lack of evidence supporting these approaches to neurofeedback and the implications of this are discussed.
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Affiliation(s)
- Robert Coben
- Integrated Neuroscience Services, 92 W. Sunbridge Drive, Fayetteville, AR, 72701, USA
| | | | - Martijn Arns
- Department of Experimental Psychology, Utrecht University, Utrecht, The Netherlands. .,Research Institute Brainclinics, Nijmegen, The Netherlands. .,neuroCare Group, Munich, Germany.
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19
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Cha HS, Han CH, Im CH. Prediction of Individual User's Dynamic Ranges of EEG Features from Resting-State EEG Data for Evaluating Their Suitability for Passive Brain-Computer Interface Applications. SENSORS 2020; 20:s20040988. [PMID: 32059543 PMCID: PMC7071472 DOI: 10.3390/s20040988] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Revised: 02/07/2020] [Accepted: 02/10/2020] [Indexed: 11/16/2022]
Abstract
With the recent development of low-cost wearable electroencephalogram (EEG) recording systems, passive brain-computer interface (pBCI) applications are being actively studied for a variety of application areas, such as education, entertainment, and healthcare. Various EEG features have been employed for the implementation of pBCI applications; however, it is frequently reported that some individuals have difficulty fully enjoying the pBCI applications because the dynamic ranges of their EEG features (i.e., its amplitude variability over time) were too small to be used in the practical applications. Conducting preliminary experiments to search for the individualized EEG features associated with different mental states can partly circumvent this issue; however, these time-consuming experiments were not necessary for the majority of users whose dynamic ranges of EEG features are large enough to be used for pBCI applications. In this study, we tried to predict an individual user's dynamic ranges of the EEG features that are most widely employed for pBCI applications from resting-state EEG (RS-EEG), with the ultimate goal of identifying individuals who might need additional calibration to become suitable for the pBCI applications. We employed a machine learning-based regression model to predict the dynamic ranges of three widely used EEG features known to be associated with the brain states of valence, relaxation, and concentration. Our results showed that the dynamic ranges of EEG features could be predicted with normalized root mean squared errors of 0.2323, 0.1820, and 0.1562, respectively, demonstrating the possibility of predicting the dynamic ranges of the EEG features for pBCI applications using short resting EEG data.
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Affiliation(s)
| | | | - Chang-Hwan Im
- Correspondence: ; Tel.: +82-2-2220-2322; Fax: +82-2-2296-5943
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20
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Groeneveld KM, Mennenga AM, Heidelberg RC, Martin RE, Tittle RK, Meeuwsen KD, Walker LA, White EK. Z-Score Neurofeedback and Heart Rate Variability Training for Adults and Children with Symptoms of Attention-Deficit/Hyperactivity Disorder: A Retrospective Study. Appl Psychophysiol Biofeedback 2019; 44:291-308. [PMID: 31119405 PMCID: PMC6834758 DOI: 10.1007/s10484-019-09439-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
ADHD is a common condition that causes suffering for those affected and economic loss for society at large. The current standard treatment for ADHD includes stimulant medications, which are not effective for all patients, may include side effects, and can be non-medically misused. Z-score neurofeedback (NFB) and heart rate variability (HRV) biofeedback are alternative treatment strategies that have been associated with Attention-Deficit/Hyperactivity Disorder (ADHD) symptom improvement. We utilized a retrospective pre-post study design to quantify the change in clients' ADHD symptoms after combined NFB + HRV treatment (which included simultaneous z-score training at four sites). We also assessed whether relevant physiological measures changed in accordance with the protocol, which would be consistent with effective NFB + HRV training. Adults (n = 39) and children (n = 100) with Borderline or Clinical ADHD classifications by the Achenbach System of Empirically Based Assessment (ASEBA) received 30 sessions of NFB + HRV training. Measures were compared before and after treatment for the ASEBA, the Integrated Visual and Auditory Continuous Performance Test (IVA), ADHD medication use, HRV and breathing parameters, and quantitative electroencephalogram (QEEG) parameters. Average ASEBA Attention-Deficit/Hyperactive Problems score improved after treatment for adults and children (p < 0.0001), with Cohen effect sizes (dz) of -1.21 and -1.17, respectively. 87.2% of adults and 80.0% of children experienced improvements of a magnitude greater than or equal to the Minimal Clinically Important Difference. After treatment, 70.8% of adults and 52.8% of children who began in the ASEBA Clinical range, and 80.0% of adults and 63.8% of children who began in the ASEBA Borderline range, were classified in the Normal range. IVA scores also improved after treatment. Changes in HRV and breathing pattern after treatment were consistent with the protocol. QEEG parameters after treatment were closer to the age-based normative mean, which is consistent with effective z-score NFB training.
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Affiliation(s)
| | - Anna M. Mennenga
- Neurocore, 201 Monroe Avenue NW Suite 300, Grand Rapids, MI 49503 USA
| | | | - Rachel E. Martin
- Neurocore, 201 Monroe Avenue NW Suite 300, Grand Rapids, MI 49503 USA
| | - Rachel K. Tittle
- Neurocore, 201 Monroe Avenue NW Suite 300, Grand Rapids, MI 49503 USA
| | - Kyle D. Meeuwsen
- Neurocore, 201 Monroe Avenue NW Suite 300, Grand Rapids, MI 49503 USA
| | - Linda A. Walker
- Neurocore, 201 Monroe Avenue NW Suite 300, Grand Rapids, MI 49503 USA
- Saybrook University, Alameda, CA USA
| | - Elyse K. White
- Neurocore, 201 Monroe Avenue NW Suite 300, Grand Rapids, MI 49503 USA
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21
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Omejc N, Rojc B, Battaglini PP, Marusic U. Review of the therapeutic neurofeedback method using electroencephalography: EEG Neurofeedback. Bosn J Basic Med Sci 2019; 19:213-220. [PMID: 30465705 DOI: 10.17305/bjbms.2018.3785] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Accepted: 08/02/2018] [Indexed: 11/16/2022] Open
Abstract
Electroencephalographic neurofeedback (EEG-NFB) represents a broadly used method that involves a real-time EEG signal measurement, immediate data processing with the extraction of the parameter(s) of interest, and feedback to the individual in a real-time. Using such a feedback loop, the individual may gain better control over the neurophysiological parameters, by inducing changes in brain functioning and, consequently, behavior. It is used as a complementary treatment for a variety of neuropsychological disorders and improvement of cognitive capabilities, creativity or relaxation in healthy subjects. In this review, various types of EEG-NFB training are described, including training of slow cortical potentials (SCPs) and frequency and coherence training, with their main results and potential limitations. Furthermore, some general concerns about EEG-NFB methodology are presented, which still need to be addressed by the NFB community. Due to the heterogeneity of research designs in EEG-NFB protocols, clear conclusions on the effectiveness of this method are difficult to draw. Despite that, there seems to be a well-defined path for the EEG-NFB research in the future, opening up possibilities for improvement.
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Affiliation(s)
- Nina Omejc
- Department of Psychology, Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Koper, Slovenia Graduate School of Neural and Behavioural Sciences, University of Tübingen, Germany.
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Hammond DC. Integrating Clinical Hypnosis and Neurofeedback. AMERICAN JOURNAL OF CLINICAL HYPNOSIS 2019; 61:302-321. [PMID: 31017552 DOI: 10.1080/00029157.2018.1501550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Hypnosis and neurofeedback each provide unique therapeutic strengths and opportunities. This article provides an overview of some of the research on neurofeedback and hypnosis. The author's perspective and recommendations are provided on the relative clinical utility of using either neurofeedback or hypnosis as the initial treatment of choice with various clinical conditions.
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Lovato N, Miller CB, Gordon CJ, Grunstein RR, Lack L. The efficacy of biofeedback for the treatment of insomnia: a critical review. Sleep Med 2018; 56:192-200. [PMID: 30846410 DOI: 10.1016/j.sleep.2018.12.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Revised: 11/26/2018] [Accepted: 12/03/2018] [Indexed: 11/30/2022]
Abstract
BACKGROUND The popularity of biofeedback as a non-pharmacological treatment option for insomnia has increased in recent times despite inconsistent empirical evidence for its therapeutic efficacy. OBJECTIVE The purpose of the current review was to systematically assess the efficacy of using biofeedback to treat insomnia. METHODS AND RESULTS A search of electronic databases (PubMED, MEDLINE, OvidSP, Ovid EMBASE, PsychInfo, The Cochrane Library including Cochrane Reviews), clinical trials databases and registries (Clinical Trials Database [US], Australian New Zealand Clinical Trials Registry [ANZCTR]) and online journal (eg, SLEEP, Sleep Medicine) identified 92 studies. Of these, 50 publications were descriptive or review papers about use of biofeedback for the treatment of insomnia, while an additional 37 did not meet the detailed inclusion criteria (ie not original research, participants do not meet the diagnostic criteria for insomnia). Six full-text articles met inclusion criteria and were included in this review. Methodological flaws including poor study design (small sample size, lack of control group) limit the validity of the body of work in this field to date and fail adequately to account for other unspecified factors likely to drive the observed changes, such as care and attention of those administering the treatment, as well as the expectations and motivations of the patient. CONCLUSION There is an urgent need for future studies to clarify the role of unspecific placebo effects when reporting biofeedback effects for the treatment of insomnia.
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Affiliation(s)
- Nicole Lovato
- Adelaide Institute for Sleep Health, A Flinders Centre of Research Excellence, Flinders University of South Australia, Australia; CRC for Alertness, Safety and Productivity, Melbourne, VIC, Australia.
| | | | - Christopher J Gordon
- CRC for Alertness, Safety and Productivity, Melbourne, VIC, Australia; CIRUS, Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, NSW, Australia; Sydney Nursing School, The University of Sydney, Sydney, NSW, Australia
| | - Ronald R Grunstein
- CRC for Alertness, Safety and Productivity, Melbourne, VIC, Australia; CIRUS, Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, NSW, Australia; Department of Respiratory Medicine, Royal Prince Alfred Hospital, Sydney, NSW, Australia
| | - Leon Lack
- Adelaide Institute for Sleep Health, A Flinders Centre of Research Excellence, Flinders University of South Australia, Australia; School of Psychology, Flinders University of South Australia, Australia
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Coben R, Middlebrooks M, Lightstone H, Corbell M. Four Channel Multivariate Coherence Training: Development and Evidence in Support of a New Form of Neurofeedback. Front Neurosci 2018; 12:729. [PMID: 30364276 PMCID: PMC6193115 DOI: 10.3389/fnins.2018.00729] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2018] [Accepted: 09/21/2018] [Indexed: 11/13/2022] Open
Abstract
As the field of neurofeedback and neuromodulation grows, trends toward using neurofeedback to treat problems of brain dysfunction have emerged. While the use of connectivity based fMRI guided neurofeedback has shown itself to be efficacious, the expense related to the treatment calls for a more practical solution. The use of QEEG guided neurofeedback in the treatment has shown promise as an emerging treatment. To date, EEG based neurofeedback approaches have used technology with limited sophistication. We designed a new form of neurofeedback that uses four channels of EEG with a multivariate calculation of coherence metrics. Following a mathematical presentation of this model, we present findings of a multi-site study with clinical subjects with various diagnoses. We compared this form of multivariate coherence neurofeedback to the more standard two channel coherence training. Findings showed that there was a significant difference between the groups with four channel multivariate coherence neurofeedback leading to greater changes in EEG metrics. Compared to two channel coherence training, four channel multivariate coherence neurofeedback led to a greater than 50% change in power and 400% in coherence values per session. The significance of these findings is discussed in relation to complex calculations of effective connectivity and how this might lead to even greater enhancements in neurofeedback efficacy.
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Affiliation(s)
- Robert Coben
- Integrated Neuroscience Services, Fayetteville, AR, United States
| | | | | | - Madeleine Corbell
- Department of Psychological Science, University of Arkansas, Fayetteville, AR, United States
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25
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Night Games and Sleep: Physiological, Neuroendocrine, and Psychometric Mechanisms. Int J Sports Physiol Perform 2018; 13:867-873. [DOI: 10.1123/ijspp.2016-0809] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Context: Night games are a regular occurrence for team-sport athletes, yet sleep complaints following night competitions are common. The mechanisms responsible for reported sleep difficulty in athletes are not understood. Methods: An observational crossover design investigating a night netball game and a time-matched rest day in 12 netball athletes was conducted to ascertain differences in physiological (core temperature), psychometric (state and trait), and neuroendocrine (adrenaline, noradrenaline, and cortisol) responses. Results: Following the night game, athletes experienced reduced sleep durations, lower sleep efficiency, early awakenings, and poorer subjective sleep ratings compared with the rest day. No differences were found between core temperature, state psychometric measures, and cortisol at bedtime. Adrenaline and noradrenaline concentrations were elevated compared with the time-matched rest day prior to (26.92 [15.88] vs 12.90 [5.71] and 232.6 [148.1] vs 97.83 [36.43] nmol/L, respectively) and following the night game (18.67 [13.26] vs 11.92 [4.56] and 234.1 [137.2] vs 88.58 [54.08] nmol/L, respectively); however, the concentrations did not correlate to the sleep variables (duration, efficiency, and sleep-onset latency). A correlation (rs = −.611) between sleep efficiency and hyperarousal (trait psychometric measure) was found. Conclusions: Athletes experienced poor sleep following a night game. Furthermore, results suggest that athletes who have a tendency toward a high trait arousal may be more susceptible to sleep complaints following a night game. These data expand knowledge and refute frequently hypothesized explanations for poor sleep following night competition. The results may also help support staff and coaches target strategies for individual athletes at a higher risk of sleep complaints.
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Tang HYJ, Riegel B, McCurry SM, Vitiello MV. Open-Loop Audio-Visual Stimulation (AVS): A Useful Tool for Management of Insomnia? Appl Psychophysiol Biofeedback 2016; 41:39-46. [PMID: 26294268 DOI: 10.1007/s10484-015-9308-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Audio Visual Stimulation (AVS), a form of neurofeedback, is a non-pharmacological intervention that has been used for both performance enhancement and symptom management. We review the history of AVS, its two sub-types (close- and open-loop), and discuss its clinical implications. We also describe a promising new application of AVS to improve sleep, and potentially decrease pain. AVS research can be traced back to the late 1800s. AVS's efficacy has been demonstrated for both performance enhancement and symptom management. Although AVS is commonly used in clinical settings, there is limited literature evaluating clinical outcomes and mechanisms of action. One of the challenges to AVS research is the lack of standardized terms, which makes systematic review and literature consolidation difficult. Future studies using AVS as an intervention should; (1) use operational definitions that are consistent with the existing literature, such as AVS, Audio-visual Entrainment, or Light and Sound Stimulation, (2) provide a clear rationale for the chosen training frequency modality, (3) use a randomized controlled design, and (4) follow the Consolidated Standards of Reporting Trials and/or related guidelines when disseminating results.
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Affiliation(s)
- Hsin-Yi Jean Tang
- Health Science Center, School of Nursing, University of Washington, 1959 NE Pacific St., Box 357263, Seattle, WA, 98195-7263, USA.
| | - Barbara Riegel
- Edith Clemmer Steinbright Chair of Gerontology, School of Nursing, University of Pennsylvania, Philadelphia, PA, 19106, USA
| | - Susan M McCurry
- School of Nursing, University of Washington, Seattle, WA, 98195, USA
| | - Michael V Vitiello
- Psychiatry and Behavioral Sciences, School of Medicine, University of Washington, Seattle, WA, 98195, USA
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Data-Driven User Feedback: An Improved Neurofeedback Strategy considering the Interindividual Variability of EEG Features. BIOMED RESEARCH INTERNATIONAL 2016; 2016:3939815. [PMID: 27631005 PMCID: PMC5007429 DOI: 10.1155/2016/3939815] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2016] [Accepted: 07/25/2016] [Indexed: 11/17/2022]
Abstract
It has frequently been reported that some users of conventional neurofeedback systems can experience only a small portion of the total feedback range due to the large interindividual variability of EEG features. In this study, we proposed a data-driven neurofeedback strategy considering the individual variability of electroencephalography (EEG) features to permit users of the neurofeedback system to experience a wider range of auditory or visual feedback without a customization process. The main idea of the proposed strategy is to adjust the ranges of each feedback level using the density in the offline EEG database acquired from a group of individuals. Twenty-two healthy subjects participated in offline experiments to construct an EEG database, and five subjects participated in online experiments to validate the performance of the proposed data-driven user feedback strategy. Using the optimized bin sizes, the number of feedback levels that each individual experienced was significantly increased to 139% and 144% of the original results with uniform bin sizes in the offline and online experiments, respectively. Our results demonstrated that the use of our data-driven neurofeedback strategy could effectively increase the overall range of feedback levels that each individual experienced during neurofeedback training.
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Marzbani H, Marateb HR, Mansourian M. Neurofeedback: A Comprehensive Review on System Design, Methodology and Clinical Applications. Basic Clin Neurosci 2016; 7:143-58. [PMID: 27303609 PMCID: PMC4892319 DOI: 10.15412/j.bcn.03070208] [Citation(s) in RCA: 151] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Neurofeedback is a kind of biofeedback, which teaches self-control of brain functions to subjects by measuring brain waves and providing a feedback signal. Neurofeedback usually provides the audio and or video feedback. Positive or negative feedback is produced for desirable or undesirable brain activities, respectively. In this review, we provided clinical and technical information about the following issues: (1) Various neurofeedback treatment protocols i.e. alpha, beta, alpha/theta, delta, gamma, and theta; (2) Different EEG electrode placements i.e. standard recording channels in the frontal, temporal, central, and occipital lobes; (3) Electrode montages (unipolar, bipolar); (4) Types of neurofeedback i.e. frequency, power, slow cortical potential, functional magnetic resonance imaging, and so on; (5) Clinical applications of neurofeedback i.e. treatment of attention deficit hyperactivity disorder, anxiety, depression, epilepsy, insomnia, drug addiction, schizophrenia, learning disabilities, dyslexia and dyscalculia, autistic spectrum disorders and so on as well as other applications such as pain management, and the improvement of musical and athletic performance; and (6) Neurofeedback softwares. To date, many studies have been conducted on the neurofeedback therapy and its effectiveness on the treatment of many diseases. Neurofeedback, like other treatments, has its own pros and cons. Although it is a non-invasive procedure, its validity has been questioned in terms of conclusive scientific evidence. For example, it is expensive, time-consuming and its benefits are not long-lasting. Also, it might take months to show the desired improvements. Nevertheless, neurofeedback is known as a complementary and alternative treatment of many brain dysfunctions. However, current research does not support conclusive results about its efficacy.
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Affiliation(s)
- Hengameh Marzbani
- Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran
| | - Hamid Reza Marateb
- Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran
| | - Marjan Mansourian
- Department of Biostatistics and Epidemiology, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
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Krigbaum G, Wigton NL. A Methodology of Analysis for Monitoring Treatment Progression with 19-Channel Z-Score Neurofeedback (19ZNF) in a Single-Subject Design. Appl Psychophysiol Biofeedback 2016; 40:139-49. [PMID: 25777656 DOI: 10.1007/s10484-015-9274-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
19-Channel Z-Score Neurofeedback (19ZNF) is a modality using 19-electrodes with real-time normative database z-scores, suggesting effective clinical outcomes in fewer sessions than traditional neurofeedback. Thus, monitoring treatment progression and clinical outcome is necessary. The area of focus in this study was a methodology of quantitative analysis for monitoring treatment progression and clinical outcome with 19ZNF. This methodology is noted as the Sites-of-Interest, which included repeated measures analyses of variance (rANOVA) and t-tests for z-scores; it was conducted on 10 cases in a single subject design. To avoid selection bias, the 10 sample cases were randomly selected from a pool of 17 cases that met the inclusion criteria. Available client outcome measures (including self-report) are briefly discussed. The results showed 90% of the pre-post comparisons moved in the targeted direction (z = 0) and of those, 96% (80% Bonferroni corrected) of the t-tests and 96% (91% Bonferroni corrected) of the rANOVAs were statistically significant; thus indicating a progression towards the mean in 15 or fewer 19ZNF sessions. All cases showed and reported improvement in all outcome measures (including quantitative electroencephalography assessment) at case termination.
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Affiliation(s)
- Genomary Krigbaum
- Marian University College of Osteopathic Medicine, 3200 Cold Spring Road, Indianapolis, IN, 46222-1997, USA,
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McFarland DJ, Sarnacki WA, Wolpaw JR. Effects of training pre-movement sensorimotor rhythms on behavioral performance. J Neural Eng 2015; 12:066021. [PMID: 26529119 PMCID: PMC4843806 DOI: 10.1088/1741-2560/12/6/066021] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
OBJECTIVE Brain-computer interface (BCI) technology might contribute to rehabilitation of motor function. This speculation is based on the premise that modifying the electroencephalographic (EEG) activity will modify behavior, a proposition for which there is limited empirical data. The present study asked whether learned modulation of pre-movement sensorimotor rhythm (SMR) activity can affect motor performance in normal human subjects. APPROACH Eight individuals first performed a joystick-based cursor-movement task with variable warning periods. Targets appeared randomly on a video monitor and subjects moved the cursor to the target and pressed a select button within 2 s. SMR features in the pre-movement EEG that correlated with performance speed and accuracy were identified. The subjects then learned to increase or decrease these features to control a two-target BCI task. Following successful BCI training, they were asked to increase or decrease SMR amplitude in order to initiate the joystick task. MAIN RESULTS After BCI training, pre-movement SMR amplitude was correlated with performance in subjects with initial poor performance: lower amplitude was associated with faster and more accurate movement. The beneficial effect on performance of lower SMR amplitude was greater in subjects with lower initial performance levels. SIGNIFICANCE These results indicate that BCI-based SMR training can affect a standard motor behavior. They provide a rationale for studies that integrate such training into rehabilitation protocols and examine its capacity to enhance restoration of useful motor function.
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Affiliation(s)
- Dennis J McFarland
- National Center for Adaptive Neurotechnologies, Wadsworth Center, New York State Department of Health, PO box509, Empire State Plaza, Albany, NY 12201-0509, USA
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Abstract
The purpose of this review is to discuss how new advances in neuroimaging and functional network analyses are applied to electroencephalography (EEG) biofeedback or neurofeedback. Clinical efficacy of one or a few scalp EEG recordings used in the treatment of attention-deficit hyperactivity disorder (ADHD) has been repeatedly demonstrated over the past 34 years. However, a problem is that improved clinical outcome often requires 40 to 80 sessions, which is expensive and difficult for patient compliance. This review cites the scientific literature of direct measures of the nodes and connections between nodes in the attention and default mode networks that are correlated with ADHD using functional magnetic resonance imaging, positron emission tomography, and EEG inverse solutions such as low-resolution electromagnetic tomography. Three-dimensional EEG biofeedback that targets dysregulation in Brodmann areas of the attention and default networks provides increased specificity and can result in improved clinical outcome in fewer sessions.
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Affiliation(s)
- Robert W. Thatcher
- EEG and NeuroImaging Laboratory, Applied Neuroscience Research Institute, Seminole, FL
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van Reekum R. Complex case: a biofeedback intervention to control impulsiveness in a severely personality disordered forensic patient. Personal Ment Health 2013; 7:177-80. [PMID: 24343945 DOI: 10.1002/pmh.1233] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Rob van Reekum
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
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Thatcher RW. Latest Developments in LiveZ-Score Training: Symptom Check List, Phase Reset, and LoretaZ-Score Biofeedback. ACTA ACUST UNITED AC 2013. [DOI: 10.1080/10874208.2013.759032] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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Horowitz S. Neurofeedback Therapy in Clinical Applications and for Cognitive Enhancement. ACTA ACUST UNITED AC 2012. [DOI: 10.1089/act.2012.18503] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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Wallhäusser-Franke E, Schredl M, Delb W. Tinnitus and insomnia: is hyperarousal the common denominator? Sleep Med Rev 2012; 17:65-74. [PMID: 22750224 DOI: 10.1016/j.smrv.2012.04.003] [Citation(s) in RCA: 63] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2012] [Revised: 04/12/2012] [Accepted: 04/13/2012] [Indexed: 10/28/2022]
Abstract
Tinnitus is an auditory sensation that is generated by aberrant activation within the auditory system. Sleep disturbances are a frequent problem in the tinnitus population. They are known to worsen the distress caused by the tinnitus which in turn worsens sleep quality. Beyond that, disturbed sleep is a risk factor for mental health problems and distressing tinnitus is often associated with enhanced depressivity, anxiety, and somatic symptom severity. Moreover there is evidence that therapies which alleviate tinnitus-related distress have a positive influence on sleep quality and help interrupt this vicious cycle. This suggests that distressing tinnitus and insomnia may both be promoted by similar physiological mechanisms. One candidate mechanism is hyperarousal caused by enhanced activation of the sympathetic nervous system. There is increasing evidence for hyperarousal in insomnia patients, and animal models of tinnitus and insomnia show conspicuous similarities in the activation pattern of limbic and autonomous brain regions. In this article we review the evidence for this hypothesis which may have implications for therapeutic intervention in tinnitus patients with comorbid insomnia.
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Affiliation(s)
- Elisabeth Wallhäusser-Franke
- Medical Faculty Mannheim, Heidelberg University, Department of Phoniatrics and Audiology, Tridomus House C, Ludolf-Krehl-Str. 13-17, 68167 Mannheim, Germany.
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