Prospective Studies
Research Papers
New treatment strategy for chronic low back pain with alpha wave neurofeedback
The lifetime prevalence of low back pain is 83%. Since there is a lack of evidence for therapeutic effect by cognitive behavioral therapy (CBT) or physical therapy (PT), it is necessary to develop objective physiological indexes and effective treatments. We conducted a prospective longitudinal study to evaluate the treatment effects of CBT, PT, and neurofeedback training (NFT) during alpha wave NFT. The early-chronic cases within 1 year and late-chronic cases over 1 year after the diagnosis of chronic low back pain were classified into six groups: Controls, CBTs, PTs, NFTs, CBT-NFTs, PT-NFTs. We evaluated the difference in EEG, psychosocial factors, scores of low back pain before/after the intervention. Therapeutic effect was clearly more effective in the early-chronic cases. We found that the intensity of alpha waves increased significantly after therapeutic intervention in the NFT groups, but did not have the main effect of reducing low back pain; the interaction between CBT and NFT reduced low back pain. Factors that enhance therapeutic effect are early intervention, increased alpha waves, and self-efficacy due to parallel implementation of CBT/PT and NFT. A treatment protocol in which alpha wave neurofeedback training is subsidiarily used with CBT or PT should be developed in the future.
View Full Paper →Acute and chronic management of posttraumatic headache in children: A systematic review
OBJECTIVES: The goal of this paper is to provide a compilation of the evidence for the treatment of posttraumatic headache (PTH) in the pediatric population. Headache features and timing of therapy were considered. BACKGROUND: Headache is the most common symptom following mild traumatic brain injury (mTBI), affecting more than 80% of children and adolescents. It is unclear whether treatment for PTH should be tailored based on headache characteristics, particularly the presence of migraine features, and/or chronicity of the headache. METHODS: Systematic literature searches of PubMed, Embase, Scopus, and Cochrane databases (1985-2021, limited to English) were performed, and key characteristics of included studies were entered into RedCAP® (Prospero ID CRD42020198703). Articles and conference abstracts that described randomized controlled trials (RCTs), cohort studies, retrospective analyses, and case series were included. Participants included youth under 18 years of age with acute (<3 months) and persistent (≥3 months) PTH. Studies that commented on headache improvement in response to therapy were included. RESULTS: Twenty-seven unique studies met criteria for inclusion describing abortive pharmacologic therapies (9), preventative pharmacotherapies (5), neuromodulation (1), procedures (5), physical therapy and exercise (6), and behavioral therapy (2). Five RCTs were identified. Studies that focused on abortive pharmacotherapies were completed in the first 2 weeks post-mTBI, whereas other treatment modalities focused on outcomes 1 month to over 1-year post-injury. Few studies reported on migrainous features (7), personal history of migraine (7), or family history of migraine (3). CONCLUSIONS: There is limited evidence on the timing and types of therapies that are effective for treating PTH in the pediatric population. Prospective studies that account for headache characteristics and thoughtfully address the timing of therapies and outcome measurement are needed.
View Full Paper →Unified Retrospective EEG Motion Educated Artefact Suppression for EEG-fMRI to Suppress Magnetic Field Gradient Artefacts During Motion
The data quality of simultaneously acquired electroencephalography and functional magnetic resonance imaging (EEG-fMRI) can be strongly affected by motion. Recent work has shown that the quality of fMRI data can be improved by using a Moiré-Phase-Tracker (MPT)-camera system for prospective motion correction. The use of the head position acquired by the MPT-camera-system has also been shown to correct motion-induced voltages, ballistocardiogram (BCG) and gradient artefact residuals separately. In this work we show the concept of an integrated framework based on the general linear model to provide a unified motion informed model of in-MRI artefacts. This model (retrospective EEG motion educated gradient artefact suppression, REEG-MEGAS) is capable of correcting voltage-induced, BCG and gradient artefact residuals of EEG data acquired simultaneously with prospective motion corrected fMRI. In our results, we have verified that applying REEG-MEGAS correction to EEG data acquired during subject motion improves the data quality in terms of motion induced voltages and also GA residuals in comparison to standard Artefact Averaging Subtraction and Retrospective EEG Motion Artefact Suppression. Besides that, we provide preliminary evidence that although adding more regressors to a model may slightly affect the power of physiological signals such as the alpha-rhythm, its application may increase the overall quality of a dataset, particularly when strongly affected by motion. This was verified by analysing the EEG traces, power spectra density and the topographic distribution from two healthy subjects. We also have verified that the correction by REEG-MEGAS improves higher frequency artefact correction by decreasing the power of Gradient Artefact harmonics. Our method showed promising results for decreasing the power of artefacts for frequencies up to 250 Hz. Additionally, REEG-MEGAS is a hybrid framework that can be implemented for real time prospective motion correction of EEG and fMRI data. Among other EEG-fMRI applications, the approach described here may benefit applications such as EEG-fMRI neurofeedback and brain computer interface, which strongly rely on the prospective acquisition and application of motion artefact removal.
View Full Paper →Comparison of effects between SMR/delta-ratio and beta1/theta-ratio neurofeedback training for older adults with Mild Cognitive Impairment: a protocol for a randomized controlled trial
BACKGROUND: Older adults with Mild Cognitive Impairment (MCI) are at high risk of progressing to Alzheimer's disease (AD). Slowing down the effect of dementia by enhancing brain plasticity represents one of the most prominent challenges. Neurofeedback (NF) has shown promising results in improving working memory but has never been evaluated in people with MCI. We aim to examine whether NF training can decrease cognitive disorders, targeting memory, attention functions and brain electrical activity in elderly patients with MCI. METHODS: In this single-blind, randomized controlled trial (RCT) protocol, we will investigate the effects of two NF training protocols on cognitive performances and on brain electrical activity. Sixty MCI patients will be assigned either to an intervention program or to psycho-pedagogical care as a control condition. Participants in the intervention group will attend 30 sessions of sensorimotor/delta-ratio NF training or beta1/theta-ratio NF training. Neuropsychological assessment, questionnaires and electroencephalography (EEG) assessment parameters will be used as dependent variables in three periods: at baseline (T0), immediately after the last NF training session at 4 months (T1) and at 3-month follow-up (T2). The primary outcome will be the change in attention measured with the Trail Making Test B. Secondary outcome will be the changes in cognitive performance and in EEG activities. DISCUSSION: If the results of our study show improvement in cognitive performances of older adults with MCI, this non-invasive, low-cost technique may deserve better consideration as a therapeutic intervention to delay cognitive decline and dementia. Consequently, research in NF will need to review and develop the rigor of its application in gerontology. TRIAL REGISTRATION: ClinicalTrials.gov, ID: NCT03526692 . Registered on 16 May 2018.
View Full Paper →Increasing Performance of Professional Soccer Players and Elite Track and Field Athletes with Peak Performance Training and Biofeedback: A Pilot Study
The aim of this pilot study was to investigate the effects of an intervention consisting of mental coaching combined with either electro encephalogram (EEG) alpha power feedback or heart rate variability (HRV) feedback on HRV, EEG outcomes and self-reported factors related to stress, performance, recovery and sleep quality in elite athletes. A prospective pilot study was performed with two distinct cohorts. Soccer players were provided with four sessions of mental coaching combined with daily HRV biofeedback (Group A); track and field athletes were provided with four sessions of mental coaching in combination with daily neurofeedback (Group B). Measurements were performed at baseline, post intervention and at 5 weeks follow-up. Objective measures: EEG and ECG. Subjective measures: Numeric Rating Scale for performance, Pittsburgh Sleep Quality Index, Rest and Stress Questionnaire and Sports Improvement-60. Group characteristics were too distinct to compare the interventions. Linear mixed models were used to analyze differences within groups over time. In Group A, significant changes over time were present in alpha power at 5 of 7 EEG locations (p < 0.01-0.03). LF/HF ratio significantly increased (p = 0.02) and the concentration (p = 0.02) and emotional scale (p = 0.03) of the SIM-60 increased significantly (p = 0.04). In Group B, the HRV low frequency power and recovery scale of the REST-Q significantly increased (p = 0.02 and <0.01 resp.). Other measures remained stable or improved non-significantly. A mental coaching program combined with either HRV or EEG alpha power feedback may increase HRV and alpha power and may lead to better performance-related outcomes and stress reduction. Further research is needed to elucidate the effects of either type of feedback and to compare effects with a control group.
View Full Paper →The effect of EEG biofeedback on reducing postcancer cognitive impairment
BACKGROUND AND HYPOTHESES: Postcancer cognitive impairment (PCCI) is observed in a substantial number of breast cancer survivors, persisting for as long as 20 years in some subgroups. Although compensatory strategies are frequently suggested, no restorative interventions have yet been identified. This study examined the feasibility of EEG biofeedback ("neurofeedback") and its potential effectiveness in reducing PCCI as well as the fatigue, sleep disturbance, and psychological symptoms that frequently accompany PCCI. STUDY DESIGN: This was a 6-month prospective study with a waitlist control period followed by an active intervention. Participants were female breast cancer survivors (n = 23), 6 to 60 months postchemotherapy, with self-reported cognitive impairment. METHODS: Four self-report outcome measures (Functional Assessment of Cancer Therapy-Cognitive Function [FACT-Cog], Functional Assessment of Chronic Illness Therapy-Fatigue [FACIT-Fatigue], Pittsburgh Sleep Quality Index [PSQI], and Brief Symptom Inventory [BSI]-18) were administered 3 times during a 10-week waitlist control period, 3 times during a 10-week (20-session) neurofeedback training regimen, and once at 4 weeks postneurofeedback. RESULTS: All 23 participants completed the study, demonstrating the feasibility of EEG biofeedback in this population. Initially, the sample demonstrated significant dysfunction on all measures compared with general population norms. Repeated-measures ANOVAs revealed strongly significant improvements (P < .001) on all 4 cognitive measures (perceived cognitive impairment, comments from others, perceived cognitive abilities, and impact on quality of life [QOL]), the fatigue scale, and the 4 psychological scales (somatization, depression, anxiety and global severity index) as well as on 3 of 8 sleep scales (quality, daytime dysfunction, and global). Two of the other sleep scales (latency and disturbance) were significant at P < .01, and 1 (use of medication) at P < .05; 2 were not significant. Improvements were generally linear across the course of training, and were maintained at the follow-up testing. At the follow-up testing, the sample no longer differed significantly from normative populations on 3 of the 4 FACT-Cog measures (impairment, impact on QOL, and comments), FACIT-Fatigue, PSQI sleep quality and habitual efficiency, or any of the BSI-18 measures of psychological disturbance. CONCLUSIONS: Data from this limited study suggest that EEG biofeedback has potential for reducing the negative cognitive and emotional sequelae of cancer treatment as well as improving fatigue and sleep patterns.
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