# Network Synchrony Neurofeedback for Opioid Dependence

> **NIH NIH R43** · NEUROBEHAVIORAL RESEARCH, INC. · 2021 · $269,320

## Abstract

Project Summary/Abstract
Over the last two decades, our laboratory has characterized adaptive changes in resting state
brain network synchrony in substance dependent individuals with long-term (multi-year)
abstinence (LTA) from alcohol and drugs. These adaptive changes more than reverse network
resting-state synchrony (RSS) differences that are associated with active substance dependence
(i.e., increased appetitive drive network RSS and decreased inhibitory control and emotion-
regulation network RSS). We have also shown that EEG coherence based indices reflect these
same networks in the same individuals. We have recently implemented real-time 64-channel
EEG coherence-based network synchrony neurofeedback (NFB) to train the brain to mimic the
changes that occur with LTA. This Phase I SBIR effort will provide 12 such NFB sessions over a
8 week period to opioid dependent individuals receiving Sublocade injection Medication Assisted
Treatment (MAT). Matched pairs of subjects will be studied with a cross-over design, with half of
subjects receiving NFB followed by a 8 week follow-up, and their counterparts being on a 8 week
waiting list followed by NFB. The non-NFB intervals allows us to estimate normal RSS changes
without NFB and measure the persistence of NFB effects.

## Key facts

- **NIH application ID:** 10382736
- **Project number:** 1R43DA052945-01A1
- **Recipient organization:** NEUROBEHAVIORAL RESEARCH, INC.
- **Principal Investigator:** George Fein
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $269,320
- **Award type:** 1
- **Project period:** 2021-09-30 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10382736

## Citation

> US National Institutes of Health, RePORTER application 10382736, Network Synchrony Neurofeedback for Opioid Dependence (1R43DA052945-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10382736. Licensed CC0.

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