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

NCT ID: NCT04876170

Last Updated: 2021-05-06

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Clinical Phase

NA

Total Enrollment

40 participants

Study Classification

INTERVENTIONAL

Study Start Date

2020-07-10

Study Completion Date

2021-09-10

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.

Conditions

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Healthy

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

BASIC_SCIENCE

Blinding Strategy

TRIPLE

Participants Investigators Outcome Assessors

Study Groups

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VS-EFP Neurofeedback

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

Group Type ACTIVE_COMPARATOR

Brain-computer-interface: EEG-based musical Neurofeedback task

Intervention Type OTHER

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'.

Yoked sham Neurofeedback

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).

Group Type SHAM_COMPARATOR

Brain-computer-interface: EEG-based musical Neurofeedback task

Intervention Type OTHER

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'.

Interventions

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Brain-computer-interface: EEG-based musical Neurofeedback task

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'.

Intervention Type OTHER

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
Minimum Eligible Age

18 Years

Maximum Eligible Age

65 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Tel Aviv University

OTHER

Sponsor Role collaborator

McGill University

OTHER

Sponsor Role collaborator

Tel-Aviv Sourasky Medical Center

OTHER_GOV

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Sagol Brain Institute, Tel Aviv Sourasky Medical Center

Tel Aviv, , Israel

Site Status RECRUITING

Countries

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Israel

Central Contacts

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Talma Hendler, MD, PhD

Role: CONTACT

972-36973953

Neomi Singer, PhD

Role: CONTACT

Facility Contacts

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Talma Hendler, MD, PhD

Role: primary

972-36973953

References

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Meir-Hasson Y, Kinreich S, Podlipsky I, Hendler T, Intrator N. An EEG Finger-Print of fMRI deep regional activation. Neuroimage. 2014 Nov 15;102 Pt 1:128-41. doi: 10.1016/j.neuroimage.2013.11.004. Epub 2013 Nov 15.

Reference Type BACKGROUND
PMID: 24246494 (View on PubMed)

Salimpoor VN, Benovoy M, Larcher K, Dagher A, Zatorre RJ. Anatomically distinct dopamine release during anticipation and experience of peak emotion to music. Nat Neurosci. 2011 Feb;14(2):257-62. doi: 10.1038/nn.2726. Epub 2011 Jan 9.

Reference Type BACKGROUND
PMID: 21217764 (View on PubMed)

Mas-Herrero E, Maini L, Sescousse G, Zatorre RJ. Common and distinct neural correlates of music and food-induced pleasure: A coordinate-based meta-analysis of neuroimaging studies. Neurosci Biobehav Rev. 2021 Apr;123:61-71. doi: 10.1016/j.neubiorev.2020.12.008. Epub 2021 Jan 10.

Reference Type BACKGROUND
PMID: 33440196 (View on PubMed)

Frank MJ, Seeberger LC, O'reilly RC. By carrot or by stick: cognitive reinforcement learning in parkinsonism. Science. 2004 Dec 10;306(5703):1940-3. doi: 10.1126/science.1102941. Epub 2004 Nov 4.

Reference Type BACKGROUND
PMID: 15528409 (View on PubMed)

Treadway MT, Buckholtz JW, Schwartzman AN, Lambert WE, Zald DH. Worth the 'EEfRT'? The effort expenditure for rewards task as an objective measure of motivation and anhedonia. PLoS One. 2009 Aug 12;4(8):e6598. doi: 10.1371/journal.pone.0006598.

Reference Type BACKGROUND
PMID: 19672310 (View on PubMed)

Snaith RP, Hamilton M, Morley S, Humayan A, Hargreaves D, Trigwell P. A scale for the assessment of hedonic tone the Snaith-Hamilton Pleasure Scale. Br J Psychiatry. 1995 Jul;167(1):99-103. doi: 10.1192/bjp.167.1.99.

Reference Type BACKGROUND
PMID: 7551619 (View on PubMed)

Mas-Herrero E, Marco-Pallares J, Lorenzo-Seva U, Zatorre RJ, & Rodriguez-Fornells A 2012. Individual differences in music reward experiences. Music Perception, 31(2), 118-138.

Reference Type BACKGROUND

Other Identifiers

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00040030000

Identifier Type: OTHER_GRANT

Identifier Source: secondary_id

0401-17-TLV

Identifier Type: -

Identifier Source: org_study_id

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