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Bhavsar P, Shah P, Sinha S, Kumar D. Musical Neurofeedback Advancements, Feedback Modalities, and Applications: A Systematic Review. Appl Psychophysiol Biofeedback 2024:10.1007/s10484-024-09647-0. [PMID: 38837017 DOI: 10.1007/s10484-024-09647-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/20/2024] [Indexed: 06/06/2024]
Abstract
The field of EEG-Neurofeedback (EEG-NF) training has showcased significant promise in treating various mental disorders, while also emerging as a cognitive enhancer across diverse applications. The core principle of EEG-NF involves consciously guiding the brain in desired directions, necessitating active engagement in neurofeedback (NF) tasks over an extended period. Music listening tasks have proven to be effective stimuli for such training, influencing emotions, mood, and brainwave patterns. This has spurred the development of musical NF systems and training protocols. Despite these advancements, there exists a gap in systematic literature that comprehensively explores and discusses the various modalities of feedback mechanisms, its benefits, and the emerging applications. Addressing this gap, our review article presents a thorough literature survey encompassing studies on musical NF conducted over the past decade. This review highlights the several benefits and applications ranging from neurorehabilitation to therapeutic interventions, stress management, diagnostics of neurological disorders, and sports performance enhancement. While acknowledged for advantages and popularity of musical NF, there is an opportunity for growth in the literature in terms of the need for systematic randomized controlled trials to compare its effectiveness with other modalities across different tasks. Addressing this gap will involve developing standardized methodologies for studying protocols and optimizing parameters, presenting an exciting prospect for advancing the field.
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Affiliation(s)
- Punitkumar Bhavsar
- Department of Electronics and Communication, Visvesvaraya National Institute of Technology, Nagpur, India
| | - Pratikkumar Shah
- Department of Computer Science and Engineering, Indian Institute of Information Technology, Vadodara, India
| | - Saugata Sinha
- Department of Electronics and Communication, Visvesvaraya National Institute of Technology, Nagpur, India
| | - Deepesh Kumar
- School of Biomedical Engineering, Indian Institute of Technology (BHU), Varanasi, India.
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崔 兴, 秦 泽, 高 之, 万 旺, 顾 忠. [Applications and challenges of wearable electroencephalogram signals in depression recognition and personalized music intervention]. SHENG WU YI XUE GONG CHENG XUE ZA ZHI = JOURNAL OF BIOMEDICAL ENGINEERING = SHENGWU YIXUE GONGCHENGXUE ZAZHI 2023; 40:1093-1101. [PMID: 38151931 PMCID: PMC10753324 DOI: 10.7507/1001-5515.202210065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 05/09/2023] [Indexed: 12/29/2023]
Abstract
Rapid and accurate identification and effective non-drug intervention are the worldwide challenges in the field of depression. Electroencephalogram (EEG) signals contain rich quantitative markers of depression, but whole-brain EEG signals acquisition process is too complicated to be applied on a large-scale population. Based on the wearable frontal lobe EEG monitoring device developed by the authors' laboratory, this study discussed the application of wearable EEG signal in depression recognition and intervention. The technical principle of wearable EEG signals monitoring device and the commonly used wearable EEG devices were introduced. Key technologies for wearable EEG signals-based depression recognition and the existing technical limitations were reviewed and discussed. Finally, a closed-loop brain-computer music interface system for personalized depression intervention was proposed, and the technical challenges were further discussed. This review paper may contribute to the transformation of relevant theories and technologies from basic research to application, and further advance the process of depression screening and personalized intervention.
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Affiliation(s)
- 兴然 崔
- 东南大学 生物科学与医学工程学院(南京 210096)School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, P. R. China
| | - 泽光 秦
- 东南大学 生物科学与医学工程学院(南京 210096)School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, P. R. China
| | - 之琳 高
- 东南大学 生物科学与医学工程学院(南京 210096)School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, P. R. China
| | - 旺 万
- 东南大学 生物科学与医学工程学院(南京 210096)School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, P. R. China
| | - 忠泽 顾
- 东南大学 生物科学与医学工程学院(南京 210096)School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, P. R. China
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Fedotchev A, Parin S, Polevaya S, Zemlianaia A. EEG-based musical neurointerfaces in the correction of stress-induced states. BRAIN-COMPUTER INTERFACES 2021. [DOI: 10.1080/2326263x.2021.1964874] [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]
Affiliation(s)
- Alexander Fedotchev
- Department of Psychophysiology, Lobachevsky State University of Nizhni Novgorod, Nizhny Novgorod, Russia
- Department of Mechanisms of Reception, Institute of Cell Biophysics, Russian Academy of Sciences, Pushchino, Moscow Region, Russia
| | - Sergey Parin
- Department of Psychophysiology, Lobachevsky State University of Nizhni Novgorod, Nizhny Novgorod, Russia
| | - Sofia Polevaya
- Department of Psychophysiology, Lobachevsky State University of Nizhni Novgorod, Nizhny Novgorod, Russia
| | - Anna Zemlianaia
- Department of Psychophysiology, Moscow Research Institute of Psychiatry, Branch of the Serbsky‘ National Medical Research Center of Psychiatry and Narcology, Russian Ministry of Health, Moscow, Russia
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Hildt E. Affective Brain-Computer Music Interfaces-Drivers and Implications. Front Hum Neurosci 2021; 15:711407. [PMID: 34267633 PMCID: PMC8275997 DOI: 10.3389/fnhum.2021.711407] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 06/02/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- Elisabeth Hildt
- Center for the Study of Ethics in the Professions, Illinois Institute of Technology, Chicago, IL, United States
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Fedotchev A, Parin S, Polevaya S, Zemlianaia A. Human Body Rhythms in the Development of Non-Invasive Methods of Closed-Loop Adaptive Neurostimulation. J Pers Med 2021; 11:437. [PMID: 34065196 PMCID: PMC8161182 DOI: 10.3390/jpm11050437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 05/17/2021] [Accepted: 05/18/2021] [Indexed: 11/21/2022] Open
Abstract
The creation and improvement of non-invasive closed-loop brain stimulation technologies represent an exciting and rapidly expanding field of neuroscience. To identify the appropriate way to close the feedback loop in adaptive neurostimulation procedures, it was previously proposed to use on-line automatic sensory stimulation with the parameters modulated by the patient's own rhythmical processes, such as respiratory rate, heart rate, and electroencephalogram (EEG) rhythms. The current paper aims to analyze several recent studies demonstrating further development in this line of research. The advantages of using automatic closed-loop feedback from human endogenous rhythms in non-invasive adaptive neurostimulation procedures have been demonstrated for relaxation assistance, for the correction of stress-induced functional disturbances, for anxiety management, and for the cognitive rehabilitation of an individual. Several distinctive features of the approach are noted to delineate its further development.
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Affiliation(s)
- Alexander Fedotchev
- Institute of Cell Biophysics, Russian Academy of Sciences, 3 Institutskaya St., Pushchino, 142290 Moscow Region, Russia
| | - Sergey Parin
- Lobachevsky State University of Nizhni Novgorod, 23 Prospekt Gagarina, 603950 Nizhny Novgorod, Russia; (S.P.); (S.P.)
| | - Sofia Polevaya
- Lobachevsky State University of Nizhni Novgorod, 23 Prospekt Gagarina, 603950 Nizhny Novgorod, Russia; (S.P.); (S.P.)
| | - Anna Zemlianaia
- Moscow Research Institute of Psychiatry, Branch of the Serbsky’ National Medical Research Center of Psychiatry and Narcology, Russian Ministry of Health, 3 Poteshnaya St., 107076 Moscow, Russia;
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Fedotchev AI, Parin SB, Polevaya SA. The Principle of a Closed Feedback Loop of Human Endogenous Rhythms in Modern Neurofeedback and Adaptive Neurostimulation Technologies. Biophysics (Nagoya-shi) 2021. [DOI: 10.1134/s0006350921020056] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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Abstract
Brain-computer interfaces and wearable neurotechnologies are now used to measure real-time neural and physiologic signals from the human body and hold immense potential for advancements in medical diagnostics, prevention, and intervention. Given the future role that wearable neurotechnologies will likely serve in the health sector, a critical state-of-the-art assessment is necessary to gain a better understanding of their current strengths and limitations. In this chapter we present wearable electroencephalography systems that reflect groundbreaking innovations and improvements in real-time data collection and health monitoring. We focus on specifications reflecting technical advantages and disadvantages, discuss their use in fundamental and clinical research, their current applications, limitations, and future directions. While many methodological and ethical challenges remain, these systems host the potential to facilitate large-scale data collection far beyond the reach of traditional research laboratory settings.
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Ehrlich SK, Agres KR, Guan C, Cheng G. A closed-loop, music-based brain-computer interface for emotion mediation. PLoS One 2019; 14:e0213516. [PMID: 30883569 PMCID: PMC6422328 DOI: 10.1371/journal.pone.0213516] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2018] [Accepted: 02/23/2019] [Indexed: 11/29/2022] Open
Abstract
Emotions play a critical role in rational and intelligent behavior; a better fundamental knowledge of them is indispensable for understanding higher order brain function. We propose a non-invasive brain-computer interface (BCI) system to feedback a person’s affective state such that a closed-loop interaction between the participant’s brain responses and the musical stimuli is established. We realized this concept technically in a functional prototype of an algorithm that generates continuous and controllable patterns of synthesized affective music in real-time, which is embedded within a BCI architecture. We evaluated our concept in two separate studies. In the first study, we tested the efficacy of our music algorithm by measuring subjective affective responses from 11 participants. In a second pilot study, the algorithm was embedded in a real-time BCI architecture to investigate affective closed-loop interactions in 5 participants. Preliminary results suggested that participants were able to intentionally modulate the musical feedback by self-inducing emotions (e.g., by recalling memories), suggesting that the system was able not only to capture the listener’s current affective state in real-time, but also potentially provide a tool for listeners to mediate their own emotions by interacting with music. The proposed concept offers a tool to study emotions in the loop, promising to cast a complementary light on emotion-related brain research, particularly in terms of clarifying the interactive, spatio-temporal dynamics underlying affective processing in the brain.
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Affiliation(s)
- Stefan K. Ehrlich
- Chair for Cognitive Systems, Department of Electrical and Computer Engineering, Technische Universität München (TUM), Munich, Germany
- * E-mail:
| | - Kat R. Agres
- Institute of High Performance Computing, Social and Cognitive Computing Department, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
- Yong Siew Toh Conservatory of Music, National University of Singapore (NUS), Singapore, Singapore
| | - Cuntai Guan
- School of Computer Science and Engineering, Nanyang Technological University (NTU), Singapore, Singapore
| | - Gordon Cheng
- Chair for Cognitive Systems, Department of Electrical and Computer Engineering, Technische Universität München (TUM), Munich, Germany
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Zemlyanaya AA, Radchenko GS, Fedotchev AI. [Music therapy procedures controlled by the brain potentials in treatment of functional disorders]. Zh Nevrol Psikhiatr Im S S Korsakova 2018; 118:103-106. [PMID: 29652315 DOI: 10.17116/jnevro201811831103-106] [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: 11/18/2022]
Abstract
Twenty years ago, the Korsakov's Journal of Neurology and Psychiatry has published the article of Ya.I. Levin 'Brain music in the treatment of patients with insomnia'. This publication was the starting point for an innovative approach to preventing and correcting functional disorders of a person via musical or music-like stimuli that are controlled by the brain potentials of patient's. This approach called 'Music of the brain' is fully consistent with modern ideas about preventive neuroscience as a new field of scientific research at the intersection of neuroscience and preventive medicine. In this review, the authors analyze initial studies on the effects of music on the brain and discuss their limitations. To increase the effectiveness of the approach, a unique combination of musical therapy with the neurofeedback method, the technology of musical neurofeedback, has been developed. Results of the application of developed technology for treatment of human functional disorders are presented, and promising directions for further research are outlined.
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Affiliation(s)
- A A Zemlyanaya
- Federal Medical Research Center for Psychiatry and Narcology, Moscow, Russia
| | - G S Radchenko
- Lobachevsky State University, Nizhni Novgorod, Russia
| | - A I Fedotchev
- Institute of Cell Biophysics, Russian Academy of Sciences, Pushchino, Moscow Region, Russia
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