Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist)

Ros, Tomas; Enriquez‐Geppert, Stefanie; Zotev, Vadim; Young, Kymberly; Wood, Guilherme; Whitfield-Gabrieli, Susan; Wan, Feng; Vuilleumier, Patrik; Vialatte, François; Ville, Dimitri Van De; Todder, Doron; Surmeli, Tanju; Sulzer, James; Strehl, Ute; Sterman, M. B.; Steiner, Naomi J.; Sorger, Bettina; Soekadar, Surjo R.; Sitaram, Ranganatha; Sherlin, Leslie; Schönenberg, Michael; Scharnowski, Frank; Schabus, Manuel; Rubia, Katya; Rosa, Agostinho; Reiner, Miriam; Pineda, Jaime A.; Paret, Christian; Ossadtchi, Alexei; Nicholson, Andrew A.; Nan, Wenya; Mínguez, Javier; Micoulaud‐Franchi, Jean‐Arthur; Mehler, David M. A.; Lührs, Michael; Lubar, Joel F.; Lotte, Fabien; Linden, David; Lewis-Peacock, Jarrod A.; Lebedev, Mikhail; Lanius, Ruth A.; Kübler, Andrea; Kranczioch, Cornelia; Koush, Yury; Konicar, Lilian; Kohl, Simon H.; Kober, Silivia E; Klados, Manousos A.; Jeunet, Camille; Janssen, Tieme W. P.; Huster, René J.; Hoedlmoser, Kerstin; Hirshberg, Laurence M.; Heunis, Stephan; Hendler, Talma; Hampson, Michelle; Guggisberg, Adrian G.; Guggenberger, Robert; Gruzelier, John; R, Göbel; Gninenko, Nicolas; Gharabaghi, Alireza; Frewen, Paul A.; Fovet, Thomas; Fernández, Thalı́a; Escolano, Carlos; Ehlis, Ann‐Christine; Drechsler, Renate; deCharms, R. Christopher; Debener, Stefan; Ridder, Dirk De; Davelaar, Eddy J.; Congedo, Marco; Cavazza, Marc; Breteler, M.H.M.; Brandeis, Daniel; Bodurka, Jerzy; Birbaumer, Niels; Bazanova, Olga; Barth, Beatrix; Bamidis, Panagiotis D.; Auer, Tibor; Arns, Martijn; Thibault, Robert T.

doi:10.1093/brain/awaa009

Cited by 257 publications

(279 citation statements)

References 64 publications

Supporting

Mentioning

254

Contrasting

Unclassified

Order By: Relevance

“…The consensus on the reporting and experimental design of clinical and cognitive‐behavioral neurofeedback studies (CRED‐nf checklist) (Ros et al, ) was included in the supplementary section.…”

Section: Methodsmentioning

confidence: 99%

Self‐regulation of ventromedial prefrontal cortex activation using real‐time fMRI neurofeedback—Influence of default mode network

Mayeli

Misaki

Zotev

et al. 2019

Human Brain Mapping

Self Cite

View full text Add to dashboard Cite

The ventromedial prefrontal cortex (vmPFC) is involved in regulation of negative emotion and decision-making, emotional and behavioral control, and active resilient coping. This pilot study examined the feasibility of training healthy subjects (n = 27) to self-regulate the vmPFC activity using a real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf). Participants in the experimental group (EG, n = 18) were provided with an ongoing vmPFC hemodynamic activity (rtfMRI-nf signal represented as variable-height bar). Individuals were instructed to raise the bar by self-relevant value-based thinking. Participants in the control group (CG, n = 9) performed the same task; however, they were provided with computer-generated sham neurofeedback signal. Results demonstrate that (a) both the CG and the EG show a higher vmPFC fMRI signal at the baseline than during neurofeedback training; (b) no significant positive training effect was seen in the vmPFC across neurofeedback runs; however, the medial prefrontal cortex, middle temporal gyri, inferior frontal gyri, and precuneus showed significant decreasing trends across the training runs only for the EG; (c) the vmPFC rtfMRI-nf signal associated with the fMRI signal across the default mode network (DMN). These findings suggest that it may be difficult to modulate a single DMN region without affecting other DMN regions. Observed decreased vmPFC activity during the neurofeedback task could be due to interference from the fMRI signal within other DMN network regions, as well as interaction with taskpositive networks. Even though participants in the EG did not show significant positive increase in the vmPFC activity among neurofeedback runs, they were able to learn to accommodate the demand of self-regulation task to maintain the vmPFC activity with the help of a neurofeedback signal.K E Y W O R D S brain, default mode network, emotion, fMRI Neurofeedback, functional connectivity, selfregulation, vmPFC

show abstract

Section: Methodsmentioning

confidence: 99%

Self‐regulation of ventromedial prefrontal cortex activation using real‐time fMRI neurofeedback—Influence of default mode network

Mayeli

Misaki

Zotev

et al. 2019

Human Brain Mapping

Self Cite

View full text Add to dashboard Cite

show abstract

“…Within non-clinical populations, NFB is a nootropic using operant conditioning to train specific brainwave patterns associated with optimal cognitive functioning [for a review see Hammond et al (2011)]. However, some researchers recently expressed scepticism about the published results supporting the NFB efficacy and emphasized the need for more rigorous studies (Thibault and Raz, 2016a,b, 2017Ros et al, 2019). To date, the main shortcomings of the existing studies include the scarcity of randomized and well-controlled trials (i.e., non-blinded participants and raters), and the absence of objective neuropsychological or electrophysiological data (Schönenberg et al, 2017;Ros et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…However, some researchers recently expressed scepticism about the published results supporting the NFB efficacy and emphasized the need for more rigorous studies (Thibault and Raz, 2016a,b, 2017Ros et al, 2019). To date, the main shortcomings of the existing studies include the scarcity of randomized and well-controlled trials (i.e., non-blinded participants and raters), and the absence of objective neuropsychological or electrophysiological data (Schönenberg et al, 2017;Ros et al, 2019). Indeed, a randomized, double-blind, sham-controlled milestone study from Schabus et al (2017) showed that NFB may work for very different reasons than what the mainstream interpretations describe.…”

Section: Introductionmentioning

confidence: 99%

“…Their results showed that the effect of NFB was only related to placebo effects and only showed in the participants' subjective data (Schabus et al, 2017). Moreover, there is a lack of standard protocols with a well-defined number of sessions within the neurofeedback literature Raz, 2016a,b, 2017;Ros et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…However, the main question pertaining to EEG NFB training remains whether we are capable of perceiving and thus altering our EEG activity. To advance our understanding of the NFB mechanisms on brain function and behavior, a consortium of researchers established a standardized checklist outlining best practices in the experimental design and reporting of neurofeedback studies (Ros et al, 2019). It appears that learning indices, i.e., changes in the power densities of the targeted EEG frequency bands within and across training sessions, are often lacking in NFB studies Raz, 2016a,b, 2017;.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Train Your Brain? Can We Really Selectively Train Specific EEG Frequencies With Neurofeedback Training

Dessy

Maîresse

Puyvelde

et al. 2020

Front. Hum. Neurosci.

View full text Add to dashboard Cite

Neurofeedback for Attention-Deficit/Hyperactivity Disorder

Westwood,

Aggensteiner,

Kaiser

et al. 2024

JAMA Psychiatry

View full text Add to dashboard Cite

ImportanceNeurofeedback has been proposed for the treatment of attention-deficit/hyperactivity disorder (ADHD) but the efficacy of this intervention remains unclear.ObjectiveTo conduct a meta-analysis of randomized clinical trials (RCTs) using probably blinded (ie, rated by individuals probably or certainly unaware of treatment allocation) or neuropsychological outcomes to test the efficacy of neurofeedback as a treatment for ADHD in terms of core symptom reduction and improved neuropsychological outcomes.Data SourcesPubMed (MEDLINE), Ovid (PsycInfo, MEDLINE, Embase + Embase Classic), and Web of Science, as well as the reference lists of eligible records and relevant systematic reviews, were searched until July 25, 2023, with no language limits.Study SelectionParallel-arm RCTs investigating neurofeedback in participants of any age with a clinical ADHD or hyperkinetic syndrome diagnosis were included.Data Extraction and SynthesisStandardized mean differences (SMDs) with Hedges g correction were pooled in random effects meta-analyses for all eligible outcomes.Main Outcomes and MeasuresThe primary outcome was ADHD total symptom severity assessed at the first postintervention time point, focusing on reports by individuals judged probably or certainly unaware of treatment allocation (probably blinded). Secondary outcomes were inattention and/or hyperactivity-impulsivity symptoms and neuropsychological outcomes postintervention and at a longer-term follow-up (ie, after the last follow-up time point). RCTs were assessed with the Cochrane risk of bias tool version 2.0.ResultsA total of 38 RCTs (2472 participants aged 5 to 40 years) were included. Probably blinded reports of ADHD total symptoms showed no significant improvement with neurofeedback (k = 20; n = 1214; SMD, 0.04; 95% CI, −0.10 to 0.18). A small significant improvement was seen when analyses were restricted to RCTs using established standard protocols (k = 9; n = 681; SMD, 0.21; 95% CI, 0.02 to 0.40). Results remained similar with adults excluded or when analyses were restricted to RCTs where cortical learning or self-regulation was established. Of the 5 neuropsychological outcomes analyzed, a significant but small improvement was observed only for processing speed (k = 15; n = 909; SMD, 0.35; 95% CI, 0.01 to 0.69). Heterogeneity was generally low to moderate.Conclusions and RelevanceOverall, neurofeedback did not appear to meaningfully benefit individuals with ADHD, clinically or neuropsychologically, at the group level. Future studies seeking to identify individuals with ADHD who may benefit from neurofeedback could focus on using standard neurofeedback protocols, measuring processing speed, and leveraging advances in precision medicine, including neuroimaging technology.

show abstract

Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist)

Abstract: Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.

Cited by 257 publications

References 64 publications

Self‐regulation of ventromedial prefrontal cortex activation using real‐time fMRI neurofeedback—Influence of default mode network

Self‐regulation of ventromedial prefrontal cortex activation using real‐time fMRI neurofeedback—Influence of default mode network

Train Your Brain? Can We Really Selectively Train Specific EEG Frequencies With Neurofeedback Training

Neurofeedback for Attention-Deficit/Hyperactivity Disorder

Contact Info

Product

Resources

About