Neurofeedback with low-cost, wearable electroencephalography (EEG) reduces symptoms in chronic Post-Traumatic Stress Disorder

Bois, Naomi Du; Bigirimana, Alain Desire; Korik, Attila; Kéthina, L. Gaju; Rutembesa, Eugène; Mutabaruka, Jean; Mutesa, Léon; Prasad, Girijesh; Jansen, Stefan; Coyle, Damien

doi:10.1016/j.jad.2021.08.071

Cited by 22 publications

(37 citation statements)

References 80 publications

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“…Regarding future work , anecdotal evidence (feedback from families/carers) has indicated that there is an apparent therapeutic benefit for the patient as they engage with a technology that they may have some influence over and indeed realise that, and are engaging/exercising the brain for an extended duration. A recent study used motor-imagery as an alternative treatment method in a study to examine the efficacy of neurofeedback, delivered using a low-cost EEG system, as a treatment for symptoms of post-traumatic stress disorder (PTSD) 82 . While the neurofeedback group alone demonstrated a clinically relevant reduction in symptom severity, post-trainingthe post-training scores for the motor-imagery group were reduced compared to the pre-training scores.…”

Section: Discussion Of the Topographical Analysismentioning

confidence: 99%

Towards electroencephalography-based consciousness assessment and cognitive function profiling in prolonged disorders of consciousness

Coyle

Korik

Bois

et al. 2022

Preprint

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Background: Electroencephalography (EEG) -based motor-imagery brain-computer interface (MI-BCI) systems can facilitate training of wilful modulation of sensorimotor oscillations in patients with prolonged disorders of consciousness, potentially enabling empirical assessment of awareness and movement independent responses and question answering. Methods: A multistage, ten session, protocol was evaluated with twenty-four (N = 24) patients who have prolonged disorders of consciousness (PDoC) (unresponsive wakefulness syndrome (UWS) or minimally conscious state (MCS)) or locked-in syndrome (LIS). Phase one assessed capacity to modulate brain activity and thus detect awareness, phase two involved motor-imagery training with neurofeedback, and phase three assessed patients’ motor-imagery response to closed questions, categorised to assess biographical, numerical, logical, and situational awareness. Results: Patients from all groups show significant capacity to modulate brain activity and respond to closed questions with motor imagery. A conservative approach to statistical testing was necessarily taken, due to a limited sample size and uneven groups. However, significant group differences were observed indicating patients with LIS outperform patients with PDoC. As patients diagnosed with UWS present evidence of command following in this protocol and thus could have MCS, significant differences between UWS and MCS across a range of tests were inconclusive although, in general, group performances are correlated with the level of awareness associated with clinical diagnosis. Conclusions: We conclude that the proposed multistage protocol involving progression from motor imagery training with neurofeedback to closed question responses under the correct conditions may be effective for movement-independent consciousness profiling in prolonged disorders of consciousness.

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Section: Discussion Of the Topographical Analysismentioning

confidence: 99%

Towards electroencephalography-based consciousness assessment and cognitive function profiling in prolonged disorders of consciousness

Coyle

Korik

Bois

et al. 2022

Preprint

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“…As accurate control of the avatar in the BrainDriver race requires each of the four 2-class classifiers to be pilot-specifically calibrated, data must be collected to train the 2-class classifiers. For this purpose we used another BCI game called NeuroSensi [ 20 , 21 ]. Additionally, to present the pilot with outputs from four classifiers simultaneously we used a novel paradigm referred to as the Triad game, which is introduced in this study for the first time.…”

Section: Methodsmentioning

confidence: 99%

Competing at the Cybathlon championship for people with disabilities: long-term motor imagery brain–computer interface training of a cybathlete who has tetraplegia

Korik

McCreadie

McShane

et al. 2022

J NeuroEngineering Rehabil

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Background The brain–computer interface (BCI) race at the Cybathlon championship, for people with disabilities, challenges teams (BCI researchers, developers and pilots with spinal cord injury) to control an avatar on a virtual racetrack without movement. Here we describe the training regime and results of the Ulster University BCI Team pilot who has tetraplegia and was trained to use an electroencephalography (EEG)-based BCI intermittently over 10 years, to compete in three Cybathlon events. Methods A multi-class, multiple binary classifier framework was used to decode three kinesthetically imagined movements (motor imagery of left arm, right arm, and feet), and relaxed state. Three game paradigms were used for training i.e., NeuroSensi, Triad, and Cybathlon Race: BrainDriver. An evaluation of the pilot’s performance is presented for two Cybathlon competition training periods—spanning 20 sessions over 5 weeks prior to the 2019 competition, and 25 sessions over 5 weeks in the run up to the 2020 competition. Results Having participated in BCI training in 2009 and competed in Cybathlon 2016, the experienced pilot achieved high two-class accuracy on all class pairs when training began in 2019 (decoding accuracy > 90%, resulting in efficient NeuroSensi and Triad game control). The BrainDriver performance (i.e., Cybathlon race completion time) improved significantly during the training period, leading up to the competition day, ranging from 274–156 s (255 ± 24 s to 191 ± 14 s mean ± std), over 17 days (10 sessions) in 2019, and from 230–168 s (214 ± 14 s to 181 ± 4 s), over 18 days (13 sessions) in 2020. However, on both competition occasions, towards the race date, the performance deteriorated significantly. Conclusions The training regime and framework applied were highly effective in achieving competitive race completion times. The BCI framework did not cope with significant deviation in electroencephalography (EEG) observed in the sessions occurring shortly before and during the race day. Changes in cognitive state as a result of stress, arousal level, and fatigue, associated with the competition challenge and performance pressure, were likely contributing factors to the non-stationary effects that resulted in the BCI and pilot achieving suboptimal performance on race day. Trial registration not registered

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“… Forest plot of meta-analysis of EEG-NFT on overall PTSD symptoms. vander Kolket et al (2016) [ 29 ] du Bois et al (2021) [ 30 ]; Leem et al (2021) [ 31 ]; Noohi et al (2017) [ 32 ]. …”

Section: Figurementioning

confidence: 99%

“… Forest plot for meta-analysis of the effect of neuro-feedback training on PTSD diagnosis. Misaki et al (2018) [ 26 ]; Misaki et al (2021) [ 27 ]; Zotev et al (2018) [ 28 ]; vander Kolket et al (2016) [ 29 ] du Bois et al (2021) [ 30 ]; Leem et al (2021) [ 31 ]. …”

Section: Figurementioning

confidence: 99%

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Efficacy of Neuro-Feedback Training for PTSD Symptoms: A Systematic Review and Meta-Analysis

Park²

2022

IJERPH

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If the negative emotions experienced in life become trauma, they affect daily life. Neuro-feedback technology has recently been introduced as a treatment, but many different neuro-feedback protocols and methods exits. This study conducted a meta-analysis of neuro-feedback training for post-traumatic stress disorder (PTSD) symptoms to evaluate the effects of functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG)-based neuro-feedback training. A search of PubMed, the Cochrane Library, Web of Science, Science Direct, and ClinicalTrials.gov was conducted from January 2011 to December 2021. The studies’ quality was assessed using the Cochrane risk of bias tool and publication bias was assessed by Egger’s regression test. Seven studies that met the inclusion criteria were used for the systematic review and meta-analysis. EEG was more effective than fMRI for PTSD symptoms, and the effect on PTSD symptoms was higher than on anxiety and depression. There was no difference in the effectiveness of the training sessions. Our findings showed that EEG-based neuro-feedback training was more helpful for training PTSD symptoms. Additionally, the methods were also shown to be valid for evaluating clinical PTSD diagnoses. Further research is needed to establish a gold standard protocol for the EEG-based neuro-feedback training (EEG-NFT) method for PTSD symptoms.

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Neurofeedback with low-cost, wearable electroencephalography (EEG) reduces symptoms in chronic Post-Traumatic Stress Disorder

Cited by 22 publications

References 80 publications

Towards electroencephalography-based consciousness assessment and cognitive function profiling in prolonged disorders of consciousness

Towards electroencephalography-based consciousness assessment and cognitive function profiling in prolonged disorders of consciousness

Competing at the Cybathlon championship for people with disabilities: long-term motor imagery brain–computer interface training of a cybathlete who has tetraplegia

Efficacy of Neuro-Feedback Training for PTSD Symptoms: A Systematic Review and Meta-Analysis

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