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This project aims to collect a densely sampled neuroimaging dataset among individuals receiving medications for opioid use disorder (MOUD). MOUD is multiphasic, comprised of medication induction, stabilization, ongoing treatment, and eventual dis-continuation phases. However, with a few small exceptions, existing neuroimaging efforts are almost exclusively single time-point assessments which, by definition, fail to capture these clinically relevant transitions and thus also do not capture individual risk and resilience trajectories. The investigators innovation, the characterization of neurocomputational trajectories during clinically relevant phases of MOUD treatment, will provide unprecedented mechanistic insight into the neurobiological basis of recovery. Once characterized, such trajectories may be used in the identification of specific therapeutic windows for additional intervention (e.g., times of increased neural plasticity) and in the design of novel tailored interventions based on known brain mechanisms (e.g., behavioral therapy, neurostimulation, neurofeedback).
Full description
MOUD individuals between the ages of 18 and 50 who recently enrolled in methadone treatment at APT Foundation clinics in the greater New Haven area. Investigators will aim to recruit individuals as early as possible in treatment, but individuals may be within the first 6 months of treatment at the time of screening, as this may be necessary to ensure that they are on a stable dose of methadone.
AIM 1 - Longitudinal neural fingerprinting of MOUD to repeatedly characterize neural trajectories of individuals in early methadone treatment.
AIM 2 - Complementary, longitudinal computational phenotyping of MOUD to repeatedly characterize behavioral, computational trajectories of individuals in early methadone treatment.
After participation in the main study, participants will be asked to complete a 15-minute follow up every month for an additional three months.
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10 participants in 1 patient group
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Central trial contact
Sarah Yip, PhD, MSc
Data sourced from clinicaltrials.gov
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