A psychoengineering paradigm for the neurocognitive mechanisms of biofeedback and neurofeedback

Gaume, Antoine; Vialatte, Audrey; Mora-Sánchez, Aldo; Ramdani, Céline; Vialatte, François

doi:10.1016/j.neubiorev.2016.06.012

Cited by 103 publications

(117 citation statements)

References 169 publications

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“…If the brain activation becomes closer to the predetermined target, a larger feedback score is provided to participants. In this case, feedback scores may work as a reinforcement signal, which provides (1) cues to making activations closer to targeted activation measure as a supervising signal and also gives (2) an internal sense of achievement or internal reward [45]. …”

Section: Four Significant Aspects Of Progress Of Fmri Neurofeedbackmentioning

confidence: 99%

Advances in fMRI Real-Time Neurofeedback

Watanabe

Sasaki

Shibata

et al. 2017

Trends in Cognitive Sciences

230

211

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Functional magnetic resonance imaging (fMRI) neurofeedback is a type of biofeedback in which real-time online fMRI signals are used to self-regulate brain function. Since its advent in 2003, significant progress has been made in fMRI neurofeedback techniques. Specifically, the use of implicit protocols, external rewards, multivariate analysis, and connectivity analysis have allowed neuroscientists to explore a possible causal involvement of modified brain activity in modified behavior. These techniques have also been integrated into groundbreaking new neurofeedback technologies, specifically decoded neurofeedback (DecNef) and functional-connectivity-based neurofeedback (FCNef). By modulating neural activity and behavior, DecNef and FCNef have substantially advanced both basic and clinical research.

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Section: Four Significant Aspects Of Progress Of Fmri Neurofeedbackmentioning

confidence: 99%

Advances in fMRI Real-Time Neurofeedback

Watanabe

Sasaki

Shibata

et al. 2017

Trends in Cognitive Sciences

230

211

View full text Add to dashboard Cite

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“…Interestingly, this decrease of performance on NF features was also observed in related works (Zotev et al, 2014) though both on EEG and fMRI features. This decrease of performance can also be explained as being part of the U-shaped learning curve (Carlucci and Case, 2013; Gaume et al, 2016): by trying new regulation strategies, the cognitive load of the subject suddenly increases and results in a temporary loss of performance. However, it is not yet known how this applies to bimodal NF.…”

Section: Discussionmentioning

confidence: 99%

“…Though we did not compare our integrated metaphor with a non-integrated one, most of our participants reported that it felt like they had one task to do during bimodal NF. Having two separate feedbacks to control and thus two separate targets to achieve could increase the cognitive load, which is an important aspect of the NF process (Gaume et al, 2016). Integrating both NF signals in one single feedback can be a way to relieve the cognitive load of the subject.…”

Section: Discussionmentioning

confidence: 99%

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Unimodal Versus Bimodal EEG-fMRI Neurofeedback of a Motor Imagery Task

Perronnet

Lécuyer

Mano

et al. 2017

Front. Hum. Neurosci.

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Neurofeedback is a promising tool for brain rehabilitation and peak performance training. Neurofeedback approaches usually rely on a single brain imaging modality such as EEG or fMRI. Combining these modalities for neurofeedback training could allow to provide richer information to the subject and could thus enable him/her to achieve faster and more specific self-regulation. Yet unimodal and multimodal neurofeedback have never been compared before. In the present work, we introduce a simultaneous EEG-fMRI experimental protocol in which participants performed a motor-imagery task in unimodal and bimodal NF conditions. With this protocol we were able to compare for the first time the effects of unimodal EEG-neurofeedback and fMRI-neurofeedback versus bimodal EEG-fMRI-neurofeedback by looking both at EEG and fMRI activations. We also propose a new feedback metaphor for bimodal EEG-fMRI-neurofeedback that integrates both EEG and fMRI signal in a single bi-dimensional feedback (a ball moving in 2D). Such a feedback is intended to relieve the cognitive load of the subject by presenting the bimodal neurofeedback task as a single regulation task instead of two. Additionally, this integrated feedback metaphor gives flexibility on defining a bimodal neurofeedback target. Participants were able to regulate activity in their motor regions in all NF conditions. Moreover, motor activations as revealed by offline fMRI analysis were stronger during EEG-fMRI-neurofeedback than during EEG-neurofeedback. This result suggests that EEG-fMRI-neurofeedback could be more specific or more engaging than EEG-neurofeedback. Our results also suggest that during EEG-fMRI-neurofeedback, participants tended to regulate more the modality that was harder to control. Taken together our results shed first light on the specific mechanisms of bimodal EEG-fMRI-neurofeedback and on its added-value as compared to unimodal EEG-neurofeedback and fMRI-neurofeedback.

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“…The purpose is to teach the participant to modify this parameter. Neurofeedback can be used to improve cognitive performance, such as memory, attention or emotions (Gruzelier 2014;Gaume et al 2016). It can be used in healthy people (e.g.…”

Section: Introductionmentioning

confidence: 99%

An artistic approach to neurofeedback for emotion regulation

Gabriel

Chabin

Joucla

et al. 2019

Preprint

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Declarations of interest : none.Abstract Neurofeedback has been shown to be a promising tool for learning to regulate one's own emotions in healthy populations and in neuropsychiatric disorders. While it has been suggested that neurofeedback performance improves when sensory feedback is related to the pathology under consideration, it is still difficult to represent in real time a proper feedback representative of our emotional state. Since emotion is a central part of people's dealings with artworks, we have initiated a collaboration between neuroscientists and artists to develop a visual representation of emotions that can be used in neurofeedback experiences. As a result of this collaboration, emotions were represented as particles, moving in a white sphere according to valence and arousal levels. In this study, several possibilities for particle control were explored: direction of particles, their concentration in a specific place, or their gravity. 107 participants evaluated these performances, either in laboratory condition or at various scientific and artistic events. At the end of the

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A psychoengineering paradigm for the neurocognitive mechanisms of biofeedback and neurofeedback

Cited by 103 publications

References 169 publications

Advances in fMRI Real-Time Neurofeedback

Advances in fMRI Real-Time Neurofeedback

Unimodal Versus Bimodal EEG-fMRI Neurofeedback of a Motor Imagery Task

An artistic approach to neurofeedback for emotion regulation

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