EEG neurofeedback research: A fertile ground for psychiatry?

Abstract

The clinical efficacy of neurofeedback is still a matter of debate. This paper analyzes the factors that should be taken into account in a transdisciplinary approach to evaluate the use of EEG NFB as a therapeutic tool in psychiatry. Neurofeedback is a neurocognitive therapy based on human-computer interaction that enables subjects to train voluntarily and modify functional biomarkers that are related to a defined mental disorder. We investigate three kinds of factors related to this definition of neurofeedback. We focus this article on EEG NFB. The first part of the paper investigates neurophysiological factors underlying the brain mechanisms driving NFB training and learning to modify a functional biomarker voluntarily. Two kinds of neuroplasticity involved in neurofeedback are analyzed: Hebbian neuroplasticity, i.e. long-term modification of neural membrane excitability and/or synaptic potentiation, and homeostatic neuroplasticity, i.e. homeostasis attempts to stabilize network activity. The second part investigates psychophysiological factors related to the targeted biomarker. It is demonstrated that neurofeedback involves clearly defining which kind of relationship between EEG biomarkers and clinical dimensions (symptoms or cognitive processes) is to be targeted. A nomenclature of accurate EEG biomarkers is proposed in the form of a short EEG encyclopedia (EEGcopia). The third part investigates human-computer interaction factors for optimizing NFB training and learning during the closed loop interaction. A model is proposed to summarize the different features that should be controlled to optimize learning. The need for accurate and reliable metrics of training and learning in line with human-computer interaction is also emphasized, including targeted biomarkers and neuroplasticity. All these factors related to neurofeedback show that it can be considered as a fertile ground for innovative research in psychiatry.

Alpha activity neuromodulation induced by individual alpha-based neurofeedback learning in ecological context: A double-blind randomized study

“…This was confirmed by the analysis of the NF index and of the NF learning score, which both demonstrated a specific effect of training sessions in the NF relative to the control group. This finding demonstrates a specific neuromodulation induced by the closed loop between the individual alpha activity and the FB, which could suggest an Hebbian neuroplasticity associated with NFT [19]. The use of a randomized double-blind protocol together with the very strict sham-FB control condition allowed us to control for the many potential confounding factors which may contribute to NFT effects.…”

“…NF learning refers to the capacity to self-regulate a targeted activity in the desired direction across training sessions [19]. Here, the NF group was expected to increase individual alpha activity across the training sessions, reflecting lasting effects [44].…”

“…This modulation is usually learnt through a cognitive strategy enforced by task instruction and related to the cognitivo-motor ability to be improved or restored. The ensuing cognitive or motor improvements are typically used as the primary outcome measures to assess NFT efficiency, in particular in clinical applications [14], [18], [19]. Control conditions are quite variable, not only aiming at the closed loop between brain activity and feedback but also varying the task or the procedure [20].…”

Why we should systematically assess, control and report somatosensory impairments in BCI-based motor rehabilitation after stroke studies

“…For example, BCIs enable paralyzed patients to drive a wheelchair by imagining right or left hand movements ( Carlson and Millan, 2013 ). BCIs share multiple characteristics with neurofeedback (NF), which protocol aims to train people to self-regulate specific functional biomarkers, often associated with mental disorders ( Batail et al, 2019 , Sitaram et al, 2017 ). Actually, when used to provide feedback on sensorimotor activity for motor-rehabilitation, some authors even argue that BCIs and NF are two different names for the same concept ( Perronnet et al, 2016 ).…”

Neurofeedback: A challenge for integrative clinical neurophysiological studies

“…These findings also form the basis of developments focussing on the reduction of functional limitations through rehabilitative procedures based on Brain-Computer Interface (BCI) technologies (for a review see [4]). Neurofeedback has thus attracted the attention of the clinical neurophysiological community [1,2], Nonetheless, a debate regarding the mechanisms through which neurofeedback may benefit therapeutic procedures was initiated in the Lancet Psychiatry [17,21,27,28,34,36] and spread to Brain [6, 23-25, 31, 32, 38], the Journal of Attention Disorders [20,37], and American Psychologist [16,33,35]. In summary, the question is the following: does neurofeedback operate through a specific neurophysiological effect on the modulation of the targeted brain activity [16]?…”