Longitudinal Neural Fingerprinting of Opioid-use Trajectories

Study Summary

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).

Primary Outcome

Relationship between functional connectivity within canonical neural networks and within the 'opioid abstinence network' and opioid use over 6 biweekly sessions. Functional connectivity is computed as the Pearson's correlation between two brain regions, or 'nodes'. This will be done in a pairwise manner to obtain connectivity values for all possible node pairs in the Shen atlas, a 268-node atlas covering the cortex, subcortex and cerebellum. Correlation coefficients are transformed to Z-scores u

Conditions Studied

Interventions

• DIAGNOSTIC_TEST fMRI

Study Locations (1)