Affective Neurofeedback Under Naturalistic Conditions: A Mini-Review of Current Achievements and Open Challenges

Abstract

Affective neurofeedback training allows for the self-regulation of the putative circuits of emotion regulation. This approach has recently been studied as a possible additional treatment for psychiatric disorders, presenting positive effects in symptoms and behaviors. After neurofeedback training, a critical aspect is the transference of the learned self-regulation strategies to outside the laboratory and how to continue reinforcing these strategies in non-controlled environments. In this mini-review, we discuss the current achievements of affective neurofeedback under naturalistic setups. For this, we first provide a brief overview of the state-of-the-art for affective neurofeedback protocols. We then discuss virtual reality as a transitional step toward the final goal of “in-the-wild” protocols and current advances using mobile neurotechnology. Finally, we provide a discussion of open challenges for affective neurofeedback protocols in-the-wild, including topics such as convenience and reliability, environmental effects in attention and workload, among others.

Multimodal resting-state connectivity predicts affective neurofeedback performance

“…Importantly, new EEG and fNIRS equipment are portable and allow quick setup when using dry and active electrodes ( Lopez-Gordo et al, 2014 ) or modular multimodal sensors ( von Lühmann et al, 2016 ). Thus, these imaging modalities are ideal for naturalistic neurofeedback implementations ( Trambaiolli et al, 2021b ). Moreover, the proposed pipeline is simple and has low computational cost.…”

“…In this study, we combined EEG and fNIRS data with a task-related connectivity modeling ( Finn et al, 2015 ; Shen et al, 2017 ) to predict participants’ performance in an fNIRS-based affective neurofeedback task ( Trambaiolli et al, 2018 ). The interest in this particular task is due to the potential of fNIRS-based protocols to be used as an intervention outside the overcontrolled environment of laboratories ( Trambaiolli et al, 2021b ). We achieved a satisfactory performance prediction using these modalities as inputs for a support vector regressor.…”

Frontostriatal circuitry as a target for fMRI-based neurofeedback interventions: A systematic review

“…However, repeating sessions have been suggested for different NF modalities (Fede et al, 2020 ; Domingos et al, 2021 ). Indeed, NF studies indicate that there is a correlation between the number of NF training sessions and the overall clinical effects in the treatment group (Trambaiolli et al, 2021 ).…”