Reward Circuit Modulation Via fMRI-informed-EEG-based Musical Neurofeedback

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    Tel-Aviv Sourasky Medical Center
Updated on 15 October 2021


The goal of this study is to test whether voluntary up-regulation of mesolimbic reward system activation is possible, and to examine the neurobehavioral effects of specific neuromodulation of this circuit on reward processing. This goal will be achieved by testing the effects of a novel non-invasive experimental framework for neuromodulation that relies on neurofeedback (NF), which is guided by neuronal activation in the ventral striatum (VS) and interfaced with personalized pleasurable music as feedback. We Hypothesize that it is possible to learn to volitionally regulate the VS using this musical NF approach. We further predict that successful NF training for up-regulating the VS-EFP signal will result in marked changes in neural and behavioral outcomes associated with upregulation of dopaminergic signaling.


Neurofeedback is a training approach in which people learn to regulate their brain activity by using a feedback signal that reflects real-time brain signals. An effective utilization of this approach requires that the represented brain activity be measured with high specificity, yet in an accessible manner, enabling repeated sessions. Evidence suggests that individuals are capable to volitionally regulate their own regional neural activation, including in deep brain regions such as the VS via real-time functional Magnetic Resonance Imaging (rt-fMRI). Yet, the utility of rt-fMRI-NF for repeated training is limited due to immobility, high-cost and extensive physical requirements. Electroencephalography (EEG), on the other hand, is low-cost and accessible. However, the behavioral and clinical benefits of EEG-NF, especially within the context of depression and other affective disorders are still debated. Previous work from Hendler's lab has established a novel framework for an accessible probing of specific brain networks termed electrical fingerprinting [1]. The fingerprinting relies on the statistical modeling of an fMRI-inspired EEG pattern based on a simultaneous recording of EEG/fMRI in combination with learning algorithms. This approach has been successfully applied and validated for the amygdala, revealing successful modulation of the EFP-amygdala signal during NF training, as well as lingering neuronal and behavioral effects among trainees, relative to sham-NF training. In the current study, the NF training procedure utilizes a newly developed fMRI-inspired EEG model of mesolimbic activity, centered on the VS; VS-electrical fingerprint (VS-EFP). Furthermore, to improve accessibility to the mesolimbic system, the feedback interface is based on pleasurable music, which has been repeatedly shown to engage the reward circuit and lead to dopaminergic release within the striatum [e.g, 2; cf. 3]. The basic principle behind the musical interface is that during training, participants are presented with their self-selected music, which becomes more or less acoustically distorted so as to reliably alter its level of pleasantness in real-time. A feasibility study with twenty participants (N=10 test group, N=10 control group), which was conducted at McGill, demonstrated the feasibility of this approach. In the current study, we wish to replicate and extend these findings in a larger sample (N=~40; N=20 test group and N=20 sham-control group) and to test the hypotheses arisen in this study with regards to its possible neurobehavioral outcomes.

Condition healthy
Treatment Brain-computer-interface: EEG-based musical Neurofeedback task
Clinical Study IdentifierNCT04876170
SponsorTel-Aviv Sourasky Medical Center
Last Modified on15 October 2021

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