Effect of neurofeedback training on depression and fatigue in patients with multiple sclerosis

Functional near-infrared spectroscopy-based neurofeedback training regulates time-on-task effects and enhances sustained cognitive performance

Time-on-task effect is a common consequence of long-term cognitive demand work, which reflects reduced behavioral performance and increases the risk of accidents. Neurofeedback is a neuromodulation method that can guide individuals to regulate their brain activity and manifest as changes in related symptoms and cognitive behaviors. This study aimed to examine the effects of functional near-infrared spectroscopy-based neurofeedback training on time-on-task effects and sustained cognitive performance. A randomized, single-blind, sham-controlled study was performed: 17 participants received feedback signals of their own dorsolateral prefrontal cortex activity (neurofeedback group), and 16 participants received feedback signals of dorsolateral prefrontal cortex activity from the neurofeedback group (sham-neurofeedback group). All participants received 5 neurofeedback training sessions and completed 2 sustained cognitive tasks, including a 2-back task and a psychomotor vigilance task, to evaluate behavioral performance changes following neurofeedback training. Results showed that neurofeedback relative to the sham-neurofeedback group exhibited increased dorsolateral prefrontal cortex activation, increased accuracy in the 2-back task, and decreased mean response time in the psychomotor vigilance task after neurofeedback training. In addition, the neurofeedback group showed slower decline performance during the sustained 2-back task after neurofeedback training compared with sham-neurofeedback group. These findings demonstrate that neurofeedback training could regulate time-on-task effects on difficult task and enhance performance on sustained cognitive tasks by increasing dorsolateral prefrontal cortex activity.

Review of EEG-based neurofeedback as a therapeutic intervention to treat depression

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.

Efficacy of bio- and neurofeedback for depression: a meta-analysis

BACKGROUND

For many years, biofeedback and neurofeedback have been implemented in the treatment of depression. However, the effectiveness of these techniques on depressive symptomatology is still controversial. Hence, we conducted a meta-analysis of studies extracted from PubMed, Scopus, Web of Science and Embase.

METHODS

Two different strings were considered for each of the two objectives of the study: A first group comprising studies patients with major depressive disorder (MDD) and a second group including studies targeting depressive symptomatology reduction in other mental or medical conditions.

RESULTS

In the first group of studies including patients with MDD, the within-group analyses yielded an effect size of Hedges' g = 0.717, while the between-group analysis an effect size of Hedges' g = 1.050. Moderator analyses indicate that treatment efficacy is only significant when accounting for experimental design, in favor of randomized controlled trials (RCTs) in comparison to non RCTs, whereas the type of neurofeedback, trial design, year of publication, number of sessions, age, sex and quality of study did not influence treatment efficacy. In the second group of studies, a small but significant effect between groups was found (Hedges' g = 0.303) in favor of bio- and neurofeedback against control groups. Moderator analyses revealed that treatment efficacy was not moderated by any of the sociodemographic and clinical variables.

CONCLUSIONS

Heart rate variability (HRV) biofeedback and neurofeedback are associated with a reduction in self-reported depression. Despite the fact that the field has still a large room for improvement in terms of research quality, the results presented in this study suggests that both modalities may become relevant complementary strategies for the treatment of MDD and depressive symptomatology in the coming years.

Which exercise and behavioural interventions show most promise for treating fatigue in multiple sclerosis? A network meta-analysis

BACKGROUND

Fatigue is a common, debilitating symptom of multiple sclerosis (MS) without a current standardised treatment.

OBJECTIVE

The aim of this systematic review with network meta-analyses was to estimate the relative effectiveness of both fatigue-targeted and non-targeted exercise, behavioural and combined (behavioural and exercise) interventions.

METHODS

Nine electronic databases up to August 2018 were searched, and 113 trials (n = 6909) were included: 34 were fatigue-targeted and 79 non-fatigue-targeted trials. Intervention characteristics were extracted using the Template for Intervention Description and Replication guidelines. Certainty of evidence was assessed using GRADE.

RESULTS

Pairwise meta-analyses showed that exercise interventions demonstrated moderate to large effects across subtypes regardless of treatment target, with the largest effect for balance exercise (SMD = 0.84). Cognitive behavioural therapies (CBTs) showed moderate to large effects (SMD = 0.60), with fatigue-targeted treatments showing larger effects than those targeting distress. Network meta-analysis showed that balance exercise performed significantly better compared to other exercise and behavioural intervention subtypes, except CBT. CBT was estimated to be superior to energy conservation and other behavioural interventions. Combined exercise also had a moderate to large effect.

CONCLUSION

Treatment recommendations for balance and combined exercise are tentative as the certainty of the evidence was moderate. The certainty of the evidence for CBT was high.

Effects of Transcranial Alternating Current Stimulation and Neurofeedback on Alpha (EEG) Dynamics: A Review

Transcranial alternating current stimulation (tACS) and neurofeedback (NFB) are two different types of non-invasive neuromodulation techniques, which can modulate brain activity and improve brain functioning. In this review, we compared the current state of knowledge related to the mechanisms of tACS and NFB and their effects on electroencephalogram (EEG) activity (online period/stimulation period) and on aftereffects (offline period/post/stimulation period), including the duration of their persistence and potential behavioral benefits. Since alpha bandwidth has been broadly studied in NFB and in tACS research, the studies of NFB and tACS in modulating alpha bandwidth were selected for comparing the online and offline effects of these two neuromodulation techniques. The factors responsible for variability in the responsiveness of the modulated EEG activity by tACS and NFB were analyzed and compared too. Based on the current literature related to tACS and NFB, it can be concluded that tACS and NFB differ a lot in the mechanisms responsible for their effects on an online EEG activity but they possibly share the common universal mechanisms responsible for the induction of aftereffects in the targeted stimulated EEG band, namely Hebbian and homeostatic plasticity. Many studies of both neuromodulation techniques report the aftereffects connected to the behavioral benefits. The duration of persistence of aftereffects for NFB and tACS is comparable. In relation to the factors influencing responsiveness to tACS and NFB, significantly more types of factors were analyzed in the NFB studies compared to the tACS studies. Several common factors for both tACS and NFB have been already investigated. Based on these outcomes, we propose several new research directions regarding tACS and NFB.

MRI correlates of cognitive improvement after home-based EEG neurofeedback training in patients with multiple sclerosis: a pilot study

OBJECTIVE

Neurofeedback training may improve cognitive function in patients with neurological disorders. However, the underlying cerebral mechanisms of such improvements are poorly understood. Therefore, we aimed to investigate MRI correlates of cognitive improvement after EEG-based neurofeedback training in patients with MS (pwMS).

METHODS

Fourteen pwMS underwent ten neurofeedback training sessions within 3-4 weeks at home using a tele-rehabilitation system. Half of the pwMS (N = 7, responders) learned to self-regulate sensorimotor rhythm (SMR, 12-15 Hz) by visual feedback and improved cognitively after training, whereas the remainder (non-responders, n = 7) did not. Diffusion-tensor imaging and resting-state fMRI of the brain was performed before and after training. We analyzed fractional anisotropy (FA) and functional connectivity (FC) of the default-mode, sensorimotor (SMN) and salience network (SAL).

RESULTS

At baseline, responders and non-responders were comparable regarding sex, age, education, disease duration, physical and cognitive impairment, and MRI parameters. After training, compared to non-responders, responders showed increased FA and FC within the SAL and SMN. Cognitive improvement correlated with increased FC in SAL and a correlation trend with increased FA was observed.

CONCLUSIONS

This exploratory study suggests that successful neurofeedback training may not only lead to cognitive improvement, but also to increases in brain microstructure and functional connectivity.

The Current Evidence Levels for Biofeedback and Neurofeedback Interventions in Treating Depression: A Narrative Review

This article is aimed at showing the current level of evidence for the usage of biofeedback and neurofeedback to treat depression along with a detailed review of the studies in the field and a discussion of rationale for utilizing each protocol. La Vaque et al. criteria endorsed by the Association for Applied Psychophysiology and Biofeedback and International Society for Neuroregulation & Research were accepted as a means of study evaluation. Heart rate variability (HRV) biofeedback was found to be moderately supportable as a treatment of MDD while outcome measure was a subjective questionnaire like Beck Depression Inventory (level 3/5, “probably efficacious”). Electroencephalographic (EEG) neurofeedback protocols, namely, alpha-theta, alpha, and sensorimotor rhythm upregulation, all qualify for level 2/5, “possibly efficacious.” Frontal alpha asymmetry protocol also received limited evidence of effect in depression (level 2/5, “possibly efficacious”). Finally, the two most influential real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback protocols targeting the amygdala and the frontal cortices both demonstrate some effectiveness, though lack replications (level 2/5, “possibly efficacious”). Thus, neurofeedback specifically targeting depression is moderately supported by existing studies (all fit level 2/5, “possibly efficacious”). The greatest complication preventing certain protocols from reaching higher evidence levels is a relatively high number of uncontrolled studies and an absence of accurate replications arising from the heterogeneity in protocol details, course lengths, measures of improvement, control conditions, and sample characteristics.

Predictors of neurofeedback training outcome: A systematic review

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Best available evidence exists for neurophysiological baseline parameters.

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No substantial effect of age and intelligence on training outcome in most cases.

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Neurofeedback learning success predicts treatment outcome.

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To date, a reliable selection of participants based on predictors is not possible.

Neurofeedback (NF), a training tool aimed at enhancing neural self-regulation, has been suggested as a complementary treatment option for neuropsychiatric disorders. Despite its potential as a neurobiological intervention directly targeting neural alterations underlying clinical symptoms, the efficacy of NF for the treatment of mental disorders has been questioned recently by negative findings obtained in randomized controlled trials (e.g., Cortese et al., 2016). A possible reason for insufficient group effects of NF trainings vs. placebo could be related to the high rate of participants who fail to self-regulate brain activity by NF (“non-learners”). Another reason could be the application of standardized NF protocols not adjusted to individual differences in pathophysiology. Against this background, we have summarized information on factors determining training and treatment success to provide a basis for the development of individualized training protocols and/or clinical indications.

The present systematic review included 25 reports investigating predictors for the outcome of NF trainings in healthy individuals as well as patients affected by mental disorders or epilepsy. We selected these studies based on searches in EBSCOhost using combinations of the keywords “neurofeedback” and “predictor/predictors”. As “NF training” we defined all NF applications with at least two sessions.

The best available evidence exists for neurophysiological baseline parameters. Among them, the target parameters of the respective training seem to be of particular importance. However, particularities of the different experimental designs and outcome criteria restrict the interpretability of some of the information we extracted. Therefore, further research is needed to gain more profound knowledge about predictors of NF outcome.

Efficacy of Neurofeedback Interventions for Cognitive Rehabilitation Following Brain Injury: Systematic Review and Recommendations for Future Research

OBJECTIVES

Interest in neurofeedback therapies (NFTs) has grown exponentially in recent years, encouraged both by escalating public interest and the financial support of health care funding agencies. Given NFTs' growing prevalence and anecdotally reported success in treating common effects of acquired brain injury (ABI), a systematic review of the efficacy of NFTs for the rehabilitation of ABI-related cognitive impairment is warranted.

METHODS

Eligible studies included adult samples (18+ years) with ABI, the use of neurofeedback technology for therapeutic purposes (as opposed to assessment), the inclusion of a meaningful control group/condition, and clear cognitive-neuropsychological outcomes. Initial automated search identified n = 86 candidate articles, however, only n = 4 studies met the stated eligibility criteria.

RESULTS

Results were inconsistent across studies and cognitive domains. Methodological and theoretical limitations precluded robust and coherent conclusions with respect to the cognitive rehabilitative properties of NFTs. We take the results of these systematic analyses as a reflection of the state of the literature at this time. These results offer a constructive platform to further discuss a number of methodological, theoretical, and ethical considerations relating to current and future NFT-ABI research and clinical intervention.

CONCLUSIONS

Given the limited quantity and quality of the available research, there appears to be insufficient evidence to comment on the efficacy of NFTs within an ABI rehabilitation context at this time. It is imperative that future work increase the level of theoretical and methodological rigour if meaningful advancements are to be made understanding and evaluating NFT-ABI applications.

Self-regulation of brain activity and its effect on cognitive function in patients with multiple sclerosis - First insights from an interventional study using neurofeedback

OBJECTIVE

To investigate the effects of EEG-based neurofeedback training, in which one can learn to self-regulate one's own brain activity, on cognitive function in patients with multiple sclerosis (pwMS).

METHODS

Fourteen pwMS performed ten neurofeedback training sessions within 3-4 weeks at home using a tele-rehabilitation system. The aim of the neurofeedback training was to increase voluntarily the sensorimotor rhythm (SMR, 12-15 Hz) in the EEG over central brain areas by receiving visual real-time feedback thereof. Cognitive function was assessed before and after all neurofeedback training sessions using a comprehensive standardized neuropsychological test battery.

RESULTS

Half of the pwMS (N = 7) showed cognitive improvements in long-term memory and executive functions after neurofeedback training. These patients successfully learned to self-regulate their own brain activity by means of neurofeedback training. The other half of pwMS (N = 7) did neither show any cognitive changes when comparing the pre- and post-assessment nor were they able to modulate their own brain activity in the desired direction during neurofeedback training.

CONCLUSIONS

Data from this interventional study provide first preliminary evidence that successful self-regulation of one's own brain activity may be associated with cognitive improvements in pwMS.

SIGNIFICANCE

These promising results should stimulate further studies. Neurofeedback might be a promising and alternative tool for future cognitive rehabilitation.

Design and Implementation of a Novel Subject-Specific Neurofeedback Evaluation and Treatment System

Electroencephalography (EEG)-based neurofeedback (NF) is a safe, non-invasive, non-painful method for treating various conditions. Current NF systems enable the selection of only one NF parameter, so that two parameters cannot be feedback simultaneously. Consequently, the ability to individually-tailor the treatment to a patient is limited, and treatment efficiency may therefore be compromised. We aimed to design, implement and test an all-in-one, novel, computerized platform for closed-loop NF treatment, based on principles from learning theories. Our prototype performs numeric evaluation based on quantifying resting EEG and event-related EEG responses to various sensory stimuli. The NF treatment was designed according to principles of efficient learning, and implemented as a gradual, patient-adaptive 1D or 2D computer game, that utilizes automatic EEG feature extraction. Verification was performed as we compared the mean area under curve (AUC) of the theta band of a dozen subjects staring at a wall or performing the NF. Most of the subjects (75%) increased their theta band AUC during the NF session compared with the trial staring at the wall (p = 0.041). Our system enables multiple feature selection and its machine learning capabilities allow an accurate discovery of patient-specific biomarkers and treatment targets. Its novel characteristics may allow for improved evaluation of patients and treatment outcomes.

Frontal brain activity and cognitive processing speed in multiple sclerosis: An exploration of EEG neurofeedback training

BACKGROUND

Cognitive deficits including impaired information processing speed as assessed by the Symbol Digit Modalities Test (SDMT) are common in multiple sclerosis (MS). Oscillatory markers of processing speed may be extracted from magnetoencephalographic (MEG) and electroencephalographic (EEG) resting-state recordings. In this context, an increased proportion of frontal slow-wave (theta, 4-8 Hz) to fast-wave (beta, 13-30 Hz) EEG activity was indicative of impaired SDMT performance. Such an increased theta/beta ratio may reflect oscillatory slowing associated with deficits in attention control. Therapeutic approaches that consider atypical oscillatory activity in MS remain sparse.

OBJECTIVES

In a cross-sectional design, we examined the relation between SDMT performance, the EEG theta/beta ratio and its components. We also explored longitudinally, whether EEG neurofeedback could be used to induce a putatively adaptive alteration in these EEG parameters, toward a pattern indicative of improved processing speed.

METHODS

N = 58 MS patients (RRMS/SPMS/PPMS N: 18/35/3, 2 cases excluded) participated in a neuropsychological examination and a resting-state EEG recording. Subsequently, N = 10 patients received neurofeedback training for two weeks in a hospitalized setting. The purpose was to reduce the frontal theta/beta ratio through operant conditioning.

RESULTS

In the cross-sectional examination, patients with slow SDMT speed displayed an increased theta/beta ratio, relative to those with normal speed. This involved increased frontal theta power, whereas beta power was equal across groups. The theta/beta ratio remained stable during neurofeedback across sessions of the two-week training period. In an exploratory secondary analysis, within sessions a reduction in the theta/beta ratio during active training blocks relative pre/post session resting-states was observed, driven by reduced theta power.

CONCLUSIONS

These findings provide support for utilizing frontal EEG theta activity as an inverse marker of processing speed in MS. Across sessions, there was no support for successful operant conditioning of the theta/beta ratio during the two-week training period. The observed state-specific shift within sessions, involving a transient reduction in theta activity, nevertheless may provide a rationale for a further investigation of neurofeedback as a treatment approach in MS.

Exploring the Use of Neurofeedback by Cancer Survivors: Results of Interviews with Neurofeedback Providers and Clients

Objective

Cancer survivors may experience persistent physical and psychological symptoms following completion of cancer treatment. Neurofeedback is a noninvasive form of brain training reported to help with symptoms including pain, fatigue, depression, anxiety, insomnia, and cognitive decline; however, there is a lack of research exploring its use with cancer survivors. The objective of this study was to describe the experiences of neurofeedback and its impact on the lives of posttreatment cancer survivors as perceived by neurofeedback providers and cancer survivor clients.

Methods

This qualitative descriptive study employed semi-structured interviews and thematic analysis of interview transcripts. A convenience sample of twelve neurofeedback providers and five cancer survivor clients participated in this study.

Results

Thematic analysis revealed seven overarching themes as follows: (1) paying it forward; (2) transforming lives; (3) regaining control; (4) brain healing itself; (5) comforting experience, (6) accessibility, and (7) failure to respond. The first five themes related to benefits of neurofeedback, and the final two related to challenges of using neurofeedback with cancer survivors.

Conclusions

Results support the use of neurofeedback to improve quality of life for cancer survivors; however, more research is needed to determine which neurofeedback systems and protocols are most effective for this population with persistent symptoms.

Depression in Multiple Sclerosis: Epidemiology, Aetiology, Diagnosis and Treatment

Depressive disorders are common in patients with multiple sclerosis, influencing their quality of life and adherence to treatments, as well as becoming more frequent with the progression of the disease and in the secondary progressive form of multiple sclerosis. Patients with multiple sclerosis often experience a typical cluster of symptoms in association with depression, such as fatigue, pain and cognitive impairment. However, the pathogenesis of multiple sclerosis-related depression remains partially unclear, even though genetic, immune-inflammatory and psychosocial factors might be seen to play a role, in addition to the brain structural alterations documented by magnetic resonance imaging studies. The high incidence and burden of depression in people affected with multiple sclerosis are matters of crucial importance. Despite such importance, the efficacy of pharmacologic treatments has been poorly studied and, for the most part, the access to non-pharmacological treatments is partially dependent on the local health system availability. It has been determined that interferon-beta and glatiramer acetate do not cause depressive symptoms; however, no definitive data in this regard are avaible for the newer disease-modifyng medications. In this review, we discuss the diagnosis, prevalence, pathogenesis, clinical aspects, magnetic resonance imaging findings and treatments available in patients experiencing multiple sclerosis-related depression.

Assessing the Effectiveness of Neurofeedback Training in the Context of Clinical and Social Neuroscience

Social neuroscience benefits from the experimental manipulation of neuronal activity. One possible manipulation, neurofeedback, is an operant conditioning-based technique in which individuals sense, interact with, and manage their own physiological and mental states. Neurofeedback has been applied to a wide variety of psychiatric illnesses, as well as to treat sub-clinical symptoms, and even to enhance performance in healthy populations. Despite growing interest, there persists a level of distrust and/or bias in the medical and research communities in the USA toward neurofeedback and other functional interventions. As a result, neurofeedback has been largely ignored, or disregarded within social neuroscience. We propose a systematic, empirically-based approach for assessing the effectiveness, and utility of neurofeedback. To that end, we use the term perturbative physiologic plasticity to suggest that biological systems function as an integrated whole that can be perturbed and guided, either directly or indirectly, into different physiological states. When the intention is to normalize the system, e.g., via neurofeedback, we describe it as self-directed neuroplasticity, whose outcome is persistent functional, structural, and behavioral changes. We argue that changes in physiological, neuropsychological, behavioral, interpersonal, and societal functioning following neurofeedback can serve as objective indices and as the metrics necessary for assessing levels of efficacy. In this chapter, we examine the effects of neurofeedback on functional connectivity in a few clinical disorders as case studies for this approach. We believe this broader perspective will open new avenues of investigation, especially within social neuroscience, to further elucidate the mechanisms and effectiveness of these types of interventions, and their relevance to basic research.

Biofeedback

Although evidence supports the efficacy of biofeedback for treating a number of disorders and for enhancing performance, significant barriers block both needed research and payer support for this method. Biofeedback has demonstrated effects in changing psychophysiological substrates of various emotional, physical, and psychosomatic problems, but payers are reluctant to reimburse for biofeedback services. A considerable amount of biofeedback research is in the form of relatively small well-controlled trials (Phase II trials). This article argues for greater payer support and research support for larger trials in the “real life” clinical environment (Phase III trials) and meta-analytic reviews.