The potential of functional near-infrared spectroscopy-based neurofeedback – a systematic review and recommendations for best practice

Abstract

<p>Background: The effects of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI)-neurofeedback on brain activation and behaviors have been studied extensively in the past. More recently, researchers have begun to investigate the effects of functional near-infrared spectroscopy-based neurofeedback (fNIRS-neurofeedback). FNIRS is a functional neuroimaging technique based on brain hemodynamics, which is easy to use, portable, inexpensive, and has reduced sensitivity to movement artifacts.Method: We provide the first systematic review and database of fNIRS-neurofeedback studies, synthesizing findings from 22 peer-reviewed studies (including a total of N=441 participants; 337 healthy, 104 patients). We (1) give a comprehensive overview of how fNIRS-neurofeedback training protocols were implemented, (2) review the online signal-processing methods used, (3) evaluate the quality of studies using pre-set methodological and reporting quality criteria and also present statistical sensitivity/power analyses, (4) investigate the effectiveness of fNIRS-neurofeedback in modulating brain activation, and (5) review its effectiveness in changing behavior in healthy and pathological populations. Results and discussion: (1-2) Published studies are heterogeneous (e.g., neurofeedback targets, investigated populations, applied training protocols, and methods). (3) Large randomized controlled trials are still lacking. In view of the novelty of the field, the quality of the published studies is moderate. We identified room for improvement in reporting important information and statistical power to detect realistic effects. (4) Several studies show that people can regulate hemodynamic signals from cortical brain regions with fNIRS-neurofeedback and (5) these studies indicate the feasibility of modulating motor control and prefrontal brain functioning in healthy participants and ameliorating symptoms in clinical populations (stroke, ADHD, autism, and social anxiety). However, valid conclusions about specificity or potential clinical utility are premature. Conclusion: Due to the advantages of practicability and relatively low cost, fNIRS-neurofeedback might provide a suitable and powerful alternative to EEG and fMRI neurofeedback and has great potential for clinical translation of neurofeedback. Together with more rigorous research and reporting practices, further methodological improvements may lead to a more solid understanding of fNIRS-neurofeedback. Future research will benefit from exploiting the advantages of fNIRS, which offers unique opportunities for neurofeedback research.</p>

Neurofeedback training in major depressive disorder: a systematic review of clinical efficacy, study quality and reporting practices

“…Further, we note that the CRED-nf guidelines were published only very recently and hence the authors of the investigated studies could not use neurofeedback specific guidelines as orientation for design and reporting practices. Comparing JBI ratings reported here with other fields, the present sample featured an average rating of 6.17, which is similar to those reported in systematic reviews (that included a similar number of studies) conducted about fMRI neurofeedback training in stroke patients (mean 6.24) and non-clinical/clinical fNIRS neurofeedback (mean 5.55) [28,135]. Also, with regard to essential, encouraged and total CRED-NF ratings, we found similar results (with 65% vs. 63%, 13% vs 10% and 47% vs. 45%, respectively) compared to the fNIRS field [28].…”

“…Comparing JBI ratings reported here with other fields, the present sample featured an average rating of 6.17, which is similar to those reported in systematic reviews (that included a similar number of studies) conducted about fMRI neurofeedback training in stroke patients (mean 6.24) and non-clinical/clinical fNIRS neurofeedback (mean 5.55) [28,135]. Also, with regard to essential, encouraged and total CRED-NF ratings, we found similar results (with 65% vs. 63%, 13% vs 10% and 47% vs. 45%, respectively) compared to the fNIRS field [28]. Lastly, we note that one main limitation of this review was the relatively small number of studies that could be included, and which precluded employing other established meta-research techniques such as p-curve analysis [136] or funnel plots to test for small study effects (e.g.…”

“…fMRI hence provides an indirect measure of neural activity. More recently, fNIRS has gained the attention of the neurofeedback community [28]. fNIRS uses near-infrared light to infer local changes in oxygen concentrations in cortical gyri [29][30][31], a measure that strongly correlates with fMRI BOLD depending on the brain localization and employed task [30,32,33].…”

Graded fMRI Neurofeedback Training of Motor Imagery in Middle Cerebral Artery Stroke Patients: A Preregistered Proof-of-Concept Study

“…Multicenter studies with standardized protocols and less rigorous inclusion/exclusion criteria will likely accelerate recruitment. Alternatively, technologies that are more portable and comfortable such as functional near-infrared spectroscopy (fNIRS) (Kohl et al, 2019 ) and electroencephalography, which have been successfully tested in stroke (Mihara et al, 2013 ; Lioi et al, 2020 ), may yield higher recruitment rates and attainment compared to fMRI. Furthermore, researchers may benefit from preregistering (Bayesian) sequential sampling plans, such as introduced here.…”

“…Preferably, future work should make use of more recently developed real-time correction procedures and quality control tools to reduce head motion (Maclaren et al, 2013 ; Dosenbach et al, 2017 ; Heunis et al, 2019 ; Krause et al, 2019 ). Lastly, neurofeedback technologies such as fNIRS, where the signal acquisition is more resilient toward head motion, may provide a useful alternative (Kohl et al, 2019 ).…”