Recruitment

Recruitment Status
Recruiting
Estimated Enrollment
Same as current

Summary

Conditions
Healthy
Type
Interventional
Phase
Not Applicable
Design
Allocation: RandomizedIntervention Model: Parallel AssignmentMasking: Triple (Participant, Investigator, Outcomes Assessor)Primary Purpose: Basic Science

Participation Requirements

Age
Between 18 years and 65 years
Gender
Both males and females

Description

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...

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.

Tracking Information

NCT #
NCT04876170
Collaborators
  • Tel Aviv University
  • McGill University
Investigators
Not Provided