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

Study Overview
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Brief Summary
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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.

Detailed Description
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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.

Official Title
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Reward Circuit Modulation Via EEG-based Neurofeedback

Conditions
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Healthy

Intervention / Treatment
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* Other: Brain-computer-interface: EEG-based musical Neurofeedback task


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Healthy without known background diseases Without known cognitive decline Have normal hearing Dominance of the right hand No history of psychiatric or neurological illnesses requiring hospitalization. The accepted criteria for inclusion for an MRI examination for medical purposes will apply, in accordance with the procedures established at the MRI Institute at the Sourasky Medical Center in Tel Aviv. Exclusion Criteria: Has a diagnosis of psychiatric or neurological diseases Uses psychiatric or neurological medications Hearing loss The accepted criteria for exclusion for an MRI examination for medical purposes will apply, according to the procedures established at the MRI Institute at the Sourasky Medical Center in Tel Aviv

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 65 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Basic Science
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Triple


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Active Comparator: VS-EFP Neurofeedback<br>Neurofeedback is based on the learned change in a particular neural signal or a combination of neural signals when feedback and reward of these signals are repeatedly presented to the organism. Thus, individuals learn to modulate their neural activity through a closed NF loop; in this condition, participants will receive musical feedback driven by their own VS-EFP | Other: Brain-computer-interface: EEG-based musical Neurofeedback task<br>* Neurofeedback training with EEG, in which participants are presented with self-selected music and requested to make the presented music sound better by applying mental strategies. Six repeated training sessions, each composed of five training cycles. Each cycle is composed of 120 sec of 'local baseline' block and 90 sec of 'regulation' block while listening to self-selected music. Participants are instructed to passively listen to their self-selected music during the 'local baseline' block, and to 'make the music sound better' during the 'regulation' block. Participants are instructed to recruit chosen mental strategies, which they find to be most efficient towards this regulatory task. During 'regulation', the quality of the sound varies in real-time (every 3 sec) in proportion to the difference between the current value of VS-EFP and its average value during 'local baseline'.<br>|
| Sham Comparator: Yoked sham Neurofeedback<br>Neurofeedback is based on the learned change in a particular neural signal or a combination of neural signals when feedback and reward of these signals are repeatedly presented to the organism. Thus, individuals learn to modulate their neural activity through a closed NF loop; in this condition, the musical feedback will be provided based on another participant's VS-EFP signal. Hence, each participant from the sham group is paired with a participant from the test group, thus receiving feedback based on the paired test participant. This way, both groups are exposed to the exact proportion of sound manipulation that indicates their success level. To account for a possible contribution of the temporal order of feedback presentation, in half of the control participants, the feedback pattern will be replayed forward (maintaining the original temporal pattern of VS-EFP that the paired participant has received), and in half - backward (flipping the original temporal pattern right-to-left). | Other: Brain-computer-interface: EEG-based musical Neurofeedback task<br>* Neurofeedback training with EEG, in which participants are presented with self-selected music and requested to make the presented music sound better by applying mental strategies. Six repeated training sessions, each composed of five training cycles. Each cycle is composed of 120 sec of 'local baseline' block and 90 sec of 'regulation' block while listening to self-selected music. Participants are instructed to passively listen to their self-selected music during the 'local baseline' block, and to 'make the music sound better' during the 'regulation' block. Participants are instructed to recruit chosen mental strategies, which they find to be most efficient towards this regulatory task. During 'regulation', the quality of the sound varies in real-time (every 3 sec) in proportion to the difference between the current value of VS-EFP and its average value during 'local baseline'.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| VS-EFP regulation success | Measured by change in VS-EFP power; based on the difference between EFP during 'regulate' and 'local baseline' conditions during the neurofeedback cycles. The investigators predict a greater modulation of VS-EFP power among the neurofeedback group relative to sham controls (test > sham). | 0 to 4 weeks | 
| Transfer of VS-EFP regulation: VS-EFP volitional regulation success under a different context | Measured by change in VS-EFP power; based on the difference between regulate and local baseline conditions during the transfer condition; volitional regulation when no music or feedback is provided. The transfer condition is introduced at the beginning of each training session. The investigators predict a positive change in VS-EFP regulation following successful training among the neurofeedback group, relative to sham controls. | 1 to 5 weeks | 
| Mesolimbic self-regulation under a different context | Measured via fMRI; a transfer task (volitional regulation when no feedback is applied) during an fMRI scan, which will take place before and after the entire training period. Region of interest (ROI) analysis of the ventral striatum (VS) will be defined based on the target region used for developing the VS-EFP. Additional regions of the mesolimbic network will be defined based on a meta-analysis of reward. The outcome will be measured for each group, as the change (post > pre) in the contrast between 'regulate' and 'local-baseline' condition. The investigators predict a positive change in VS upregulation following successful training among the neurofeedback group, relative to sham controls. Exploratory analysis: the investigators intend to further explore whether NF training resulted in a positive change in the upregulation of additional mesolimbic nodes. | 1 to 5 weeks | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Reward-learning behavior | Assessed via the performance in probabilistic selection task (PST), which will be administered before and after the entire training period. This is a task of probabilistic reward learning, in which participants' ability to learn to choose a frequently rewarded symbol (e.g., symbol A which is rewarded 80% of the times) or to avoid a rarely rewarded symbol (B, 20% of the times) is examined [4]. The outcome will be measured for each group, as the change (post > pre) in the accuracy of learning from reward (select A) or from punishments (avoid B). The investigators predict a positive change in learning from rewards following successful training among the neurofeedback group, relative to sham controls. | 1 to 5 weeks | 
| Incentive motivation behavior | Measured via the performance in the Effort Expenditure for Rewards Task (Eefrt task), which will be administered before and after the entire training period. This is an effort-based decision-making task, in which participants choose to perform a 'hard' vs. 'easy' task for gaining varying amounts of monetary rewards under low/medium/high probability of reward receipt [5]. The outcome will be measured for each group, as the change (post >pre) in the proportion of choosing to expend more effort for a high/low monetary gain under high/medium/low probability. The investigators predict a positive change in the proportion of choosing the hard task for high monetary gain under lower probabilities of gaining rewards following successful training among the neurofeedback group, relative to sham controls. | 1 to 5 weeks | 
| Hedonic trait: link between hedonic traits and neurofeedback success | Measured via the Snaith Hemilton Pleasure Scale (SHAPS), a 14 item questionnaire that assesses hedonic capacity; an index of c-anhedonia will be derived as the sum of the responses [6]. The investigators predict that there will be a negative correlation between anhedonia scores following training and the performance in the NF-VS-EFP among the neurofeedback group. | 1 to 5 weeks |