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Diotaiuti P, Corrado S, Tosti B, Spica G, Di Libero T, D’Oliveira A, Zanon A, Rodio A, Andrade A, Mancone S. Evaluating the effectiveness of neurofeedback in chronic pain management: a narrative review. Front Psychol 2024; 15:1369487. [PMID: 38770259 PMCID: PMC11104502 DOI: 10.3389/fpsyg.2024.1369487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 03/28/2024] [Indexed: 05/22/2024] Open
Abstract
The prevalence and impact of chronic pain in individuals worldwide necessitate effective management strategies. This narrative review specifically aims to assess the effectiveness of neurofeedback, an emerging non-pharmacological intervention, on the management of chronic pain. The methodology adopted for this review involves a meticulous search across various scientific databases. The search was designed to capture a broad range of studies related to neurofeedback and chronic pain management. To ensure the quality and relevance of the included studies, strict inclusion and exclusion criteria were applied. These criteria focused on the study design, population, intervention type, and reported outcomes. The review synthesizes the findings from a diverse array of studies, including randomized controlled trials, observational studies, and case reports. Key aspects evaluated include the types of neurofeedback used (such as EEG biofeedback), the various chronic pain conditions addressed (like fibromyalgia, neuropathic pain, and migraines), and the methodologies employed in these studies. The review highlights the underlying mechanisms by which neurofeedback may influence pain perception and management, exploring theories related to neural plasticity, pain modulation, and psychological factors. The results of the review reveal a positive correlation between neurofeedback interventions and improved pain management. Several studies report significant reductions on pain intensity, improved quality of life, and decreased reliance on medication following neurofeedback therapy. The review also notes variations in the effectiveness of different neurofeedback protocols and individual responses to treatment. Despite the promising results, the conclusion of the review emphasizes the need for further research. It calls for larger, well-designed clinical trials to validate the findings, to understand the long-term implications of neurofeedback therapy, and to optimize treatment protocols for individual patients.
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Affiliation(s)
- Pierluigi Diotaiuti
- Department of Human Sciences, Society and Health, University of Cassino and Southern Lazio, Cassino, Lazio, Italy
| | - Stefano Corrado
- Department of Human Sciences, Society and Health, University of Cassino and Southern Lazio, Cassino, Lazio, Italy
| | - Beatrice Tosti
- Department of Human Sciences, Society and Health, University of Cassino and Southern Lazio, Cassino, Lazio, Italy
| | - Giuseppe Spica
- Department of Human Sciences, Society and Health, University of Cassino and Southern Lazio, Cassino, Lazio, Italy
| | - Tommaso Di Libero
- Department of Human Sciences, Society and Health, University of Cassino and Southern Lazio, Cassino, Lazio, Italy
| | - Anderson D’Oliveira
- Department of Physical Education, CEFID, Santa Catarina State University, Florianopolis, Santa Catarina, Brazil
| | - Alessandra Zanon
- Department of Human Sciences, Society and Health, University of Cassino and Southern Lazio, Cassino, Lazio, Italy
| | - Angelo Rodio
- Department of Human Sciences, Society and Health, University of Cassino and Southern Lazio, Cassino, Lazio, Italy
| | - Alexandro Andrade
- Department of Physical Education, CEFID, Santa Catarina State University, Florianopolis, Santa Catarina, Brazil
| | - Stefania Mancone
- Department of Human Sciences, Society and Health, University of Cassino and Southern Lazio, Cassino, Lazio, Italy
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Rockholt MM, Kenefati G, Doan LV, Chen ZS, Wang J. In search of a composite biomarker for chronic pain by way of EEG and machine learning: where do we currently stand? Front Neurosci 2023; 17:1186418. [PMID: 37389362 PMCID: PMC10301750 DOI: 10.3389/fnins.2023.1186418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 05/12/2023] [Indexed: 07/01/2023] Open
Abstract
Machine learning is becoming an increasingly common component of routine data analyses in clinical research. The past decade in pain research has witnessed great advances in human neuroimaging and machine learning. With each finding, the pain research community takes one step closer to uncovering fundamental mechanisms underlying chronic pain and at the same time proposing neurophysiological biomarkers. However, it remains challenging to fully understand chronic pain due to its multidimensional representations within the brain. By utilizing cost-effective and non-invasive imaging techniques such as electroencephalography (EEG) and analyzing the resulting data with advanced analytic methods, we have the opportunity to better understand and identify specific neural mechanisms associated with the processing and perception of chronic pain. This narrative literature review summarizes studies from the last decade describing the utility of EEG as a potential biomarker for chronic pain by synergizing clinical and computational perspectives.
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Affiliation(s)
- Mika M. Rockholt
- Department of Anesthesiology, Perioperative Care and Pain Management, New York University Grossman School of Medicine, New York, NY, United States
| | - George Kenefati
- Department of Anesthesiology, Perioperative Care and Pain Management, New York University Grossman School of Medicine, New York, NY, United States
| | - Lisa V. Doan
- Department of Anesthesiology, Perioperative Care and Pain Management, New York University Grossman School of Medicine, New York, NY, United States
| | - Zhe Sage Chen
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, United States
- Department of Neuroscience & Physiology, Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, United States
- Department of Biomedical Engineering, New York University Tandon School of Engineering, Brooklyn, NY, United States
| | - Jing Wang
- Department of Anesthesiology, Perioperative Care and Pain Management, New York University Grossman School of Medicine, New York, NY, United States
- Department of Neuroscience & Physiology, Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, United States
- Department of Biomedical Engineering, New York University Tandon School of Engineering, Brooklyn, NY, United States
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Zebhauser PT, Hohn VD, Ploner M. Resting-state electroencephalography and magnetoencephalography as biomarkers of chronic pain: a systematic review. Pain 2023; 164:1200-1221. [PMID: 36409624 PMCID: PMC10184564 DOI: 10.1097/j.pain.0000000000002825] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 10/28/2022] [Accepted: 11/04/2022] [Indexed: 11/22/2022]
Abstract
ABSTRACT Reliable and objective biomarkers promise to improve the assessment and treatment of chronic pain. Resting-state electroencephalography (EEG) is broadly available, easy to use, and cost efficient and, therefore, appealing as a potential biomarker of chronic pain. However, results of EEG studies are heterogeneous. Therefore, we conducted a systematic review (PROSPERO CRD42021272622) of quantitative resting-state EEG and magnetoencephalography (MEG) studies in adult patients with different types of chronic pain. We excluded populations with severe psychiatric or neurologic comorbidity. Risk of bias was assessed using a modified Newcastle-Ottawa Scale. Semiquantitative data synthesis was conducted using modified albatross plots. We included 76 studies after searching MEDLINE, Web of Science Core Collection, Cochrane Central Register of Controlled Trials, and EMBASE. For cross-sectional studies that can serve to develop diagnostic biomarkers, we found higher theta and beta power in patients with chronic pain than in healthy participants. For longitudinal studies, which can yield monitoring and/or predictive biomarkers, we found no clear associations of pain relief with M/EEG measures. Similarly, descriptive studies that can yield diagnostic or monitoring biomarkers showed no clear correlations of pain intensity with M/EEG measures. Risk of bias was high in many studies and domains. Together, this systematic review synthesizes evidence on how resting-state M/EEG might serve as a diagnostic biomarker of chronic pain. Beyond, this review might help to guide future M/EEG studies on the development of pain biomarkers.
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Affiliation(s)
- Paul Theo Zebhauser
- Department of Neurology, School of Medicine, Technical University of Munich (TUM), Munich, Germany
| | - Vanessa D. Hohn
- Department of Neurology, School of Medicine, Technical University of Munich (TUM), Munich, Germany
| | - Markus Ploner
- Department of Neurology, School of Medicine, Technical University of Munich (TUM), Munich, Germany
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Richard S, Gabriel S, John S, Emmanuel M, John-Mary V. The focused quantitative EEG bio-marker in studying childhood atrophic encephalopathy. Sci Rep 2022; 12:13437. [PMID: 35927445 PMCID: PMC9352776 DOI: 10.1038/s41598-022-17062-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 07/20/2022] [Indexed: 11/12/2022] Open
Abstract
Although it is a normal involution process in advanced age, brain atrophy—also termed atrophic encephalopathy—can also occur prematurely in childhood as a consequential effect of brain tissues injury through trauma or central nervous system infection, though in both normal and premature occurrences this condition always presents with loss of volume relative to the skull. A common tool for the functional study of brain activities is an electroencephalogram, but analyses of this have reportedly identified mismatches between qualitative and quantitative forms, particularly in the use of Delta-alpha ratio (DAR) indices, meaning that the values may be case dependent. The current study thus examines the value of Focused Occipital Beta-Alpha Ratio (FOBAR) as a modified biomarker for evaluating brain functional changes resulting from brain atrophy. This cross-sectional design study involves 260 patients under 18 years of age. Specifically, 207 patients with brain atrophy are compared with 53 control subjects with CT scan-proven normal brain volume. All the children underwent digital electroencephalography with brain mapping. Results show that alpha posterior dominant rhythm was present in 88 atrophic children and 44 controls. Beta as posterior dominant rhythm was present in an overwhelming 91.5% of atrophic subjects, with 0.009 p-values. The focused occipital Beta-alpha ratio correlated significantly with brain volume loss presented in diagonal brain fraction. The FOBAR and DAR values of the QEEG showed no significant correlation. This work concludes that QEEG cerebral dysfunctional studies may be etiologically and case dependent from the nature of the brain injury. Also, the focused Beta-alpha ratio of the QEEG is a prospective and potential biomarker of consideration in studying childhood atrophic encephalopathy.
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Affiliation(s)
- Sungura Richard
- Department of Health and Biomedical Sciences, School of Life Science, Nelson Mandela-African Institution of Science and Technology, Arusha, Tanzania.
| | - Shirima Gabriel
- Department of Health and Biomedical Sciences, School of Life Science, Nelson Mandela-African Institution of Science and Technology, Arusha, Tanzania
| | - Spitsbergen John
- Department of Neuroscience, Western Michigan University, Kalamazoo, MI, USA
| | - Mpolya Emmanuel
- Department of Health and Biomedical Sciences, School of Life Science, Nelson Mandela-African Institution of Science and Technology, Arusha, Tanzania
| | - Vianney John-Mary
- Department of Health and Biomedical Sciences, School of Life Science, Nelson Mandela-African Institution of Science and Technology, Arusha, Tanzania
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Hamed R, Mizrachi L, Granovsky Y, Issachar G, Yuval-Greenberg S, Bar-Shalita T. Neurofeedback Therapy for Sensory Over-Responsiveness-A Feasibility Study. SENSORS 2022; 22:s22051845. [PMID: 35270991 PMCID: PMC8914621 DOI: 10.3390/s22051845] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 02/21/2022] [Accepted: 02/22/2022] [Indexed: 12/22/2022]
Abstract
Background: Difficulty in modulating multisensory input, specifically the sensory over-responsive (SOR) type, is linked to pain hypersensitivity and anxiety, impacting daily function and quality of life in children and adults. Reduced cortical activity recorded under resting state has been reported, suggestive of neuromodulation as a potential therapeutic modality. This feasibility study aimed to explore neurofeedback intervention in SOR. Methods: Healthy women with SOR (n = 10) underwent an experimental feasibility study comprising four measurement time points (T1—baseline; T2—preintervention; T3—postintervention; T4—follow-up). Outcome measures included resting-state EEG recording, in addition to behavioral assessments of life satisfaction, attaining functional goals, pain sensitivity, and anxiety. Intervention targeted the upregulation of alpha oscillatory power over ten sessions. Results: No changes were detected in all measures between T1 and T2. Exploring the changes in brain activity between T2 and T4 revealed power enhancement in delta, theta, beta, and gamma oscillatory bands, detected in the frontal region (p = 0.03−<0.001; Cohen’s d = 0.637−1.126) but not in alpha oscillations. Furthermore, a large effect was found in enhancing life satisfaction and goal attainment (Cohen’s d = 1.18; 1.04, respectively), and reduced pain sensitivity and anxiety trait (Cohen’s d = 0.70). Conclusion: This is the first study demonstrating the feasibility of neurofeedback intervention in SOR.
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Affiliation(s)
- Ruba Hamed
- Department of Occupational Therapy, Faculty of Medicine, School of Health Professions, Tel Aviv University, Tel Aviv 6997801, Israel; (R.H.); (L.M.)
| | - Limor Mizrachi
- Department of Occupational Therapy, Faculty of Medicine, School of Health Professions, Tel Aviv University, Tel Aviv 6997801, Israel; (R.H.); (L.M.)
| | - Yelena Granovsky
- Laboratory of Clinical Neurophysiology, Department of Neurology, Faculty of Medicine, Rambam Health Care Campus, Technion, Haifa 3109601, Israel;
| | - Gil Issachar
- Biomedical Engineering Department, Faculty of Engineering, Tel Aviv University, Tel Aviv 6997801, Israel;
| | - Shlomit Yuval-Greenberg
- School of Psychological Sciences, Tel Aviv University, Tel Aviv 6997801, Israel;
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Tami Bar-Shalita
- Department of Occupational Therapy, Faculty of Medicine, School of Health Professions, Tel Aviv University, Tel Aviv 6997801, Israel; (R.H.); (L.M.)
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 6997801, Israel
- Correspondence: ; Tel.: +972-525437631
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