An observational study in Opioid Use Disorder and Healthy Controls Group - Age and Sex-matched, sponsored by Yale University. Recruiting at 1 site in United States. Open to participants aged 21 Years to 60 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-06-16.
Sponsored by Yale University · Observational
The goal of this observational study is to characterize the brain processes of pain avoidance learning dysfunctions in individuals with opioid use disorder (OUD). The main questions it aims to answer are:
Compared with healthy controls, do those with OUD exhibit impaired avoidance learning in response to pain? What are the brain processes that are associated with this avoidance learning dysfunction? Do these brain processes serve to predict future use or relapse?
Researchers will compare those with OUD and healthy controls to determine avoidance learning dysfunction and its relationship with opioid use.
Participants will be performing a learning task inside an fMRI scanner. Those with OUD will also be followed up for a year to determine future opioid use.
Opioid Use Disorder (OUD) is a chronic condition with exceptionally high relapse rates. Over 80% of patients receiving treatment relapse within a year. To understand the etiological processes of OUD, investigators have focused on reward seeking as a primary drinking motive. However, whereas reward and sensation seeking may be central to the early stages of OUD, it is posited that drinking as an avoidance coping behavior plays a more critical role in the maintenance of OUD. Specifically, as opioid escalates, consumption is increasingly driven by individuals' enhanced sensitivity to the aversive consequences of withdrawal. This indicates a fundamental shift of motivation from positive to negative reinforcement in OUD. Paradoxically, while users seek opioid to avoid painful physical and emotional states, chronic opioid use heightens pain reactivity, which further motivates drug use as an avoidance coping strategy. Over time, this maladaptive behavior becomes progressively less amenable to cognitive control, trapping users in a spiraling cycle of drug use and distress. The investigators thus hypothesize that dysfunctional avoidance learning is a central pathophysiological process of OUD.
Avoidance learning is a product of pain reactivity and cognitive control and their underlying brain circuits. Yet, how avoidance learning and its circuit processes are compromised in individuals with OUD remains unclear. This study aims to fill this important gap in research by investigating avoidance learning deficits as a principal mechanism of OUD.
The current proposal leverages neuroimaging, physiological recordings, and clinical assessments of avoidance learning to identify a set of markers to distinguish those with OUD from healthy controls (HC), evaluate the "diagnostic" accuracy of these markers, and describe how they may predict relapse. The investigators will also examine reward learning as a contrast to differentiate its role in OUD. Avoidance and reward learning will be operationalized via a probabilistic learning go/no-go task in which participants learn to associate cues with outcomes to avoid electric shocks and optimize reward. First, the investigators will identify brain dysfunctions in avoidance and reward learning in OUD patients and establish their inter-relationships with clinical and drug use characteristics. Next, in addition to continuing recruitment, the investigators will follow up with OUD patients for 12 months to identify predictors of relapse. The investigators will also follow up with opioid regular users to determine changes in opioid use over time.
Individuals with OUD and HCs will be recruited from the Greater New Haven, Hartford, Bridgeport areas of CT. Those with OUD will be drawn by self-referral based on seeing flyers and brochures posted at treatment programs such as the Substance Abuse Treatment Unit (SATU) and the Connecticut Mental Health Center (CMHC), by advertisements of the study, or by word of mouth. HCs will be recruited from the community by flyers and advertisements or by word of mouth.
Ninety treatment-seeking individuals with OUD (45 women) between 21 and 60 years of age and meeting the diagnosis of moderate to severe OUD will be recruited to participate in the study.
Forty individuals with regular opioid use (i.e., at least weekly, non-prescription) (20 women) aged between 21-60 who are not seeking treatment will also be recruited.
Ninety HCs (45 women) with matching demographics (including age, sex, race, and education) will be recruited. HCs will undergo the same intake assessments to confirm eligibility.
1,411 studies on the registry are indexed under Opioid-Related Disorders; 290 are open to participants now.
This study's planned enrollment of 180 is above the median of 129 across 174 observational studies indexed under Opioid-Related Disorders.
Browse Opioid-Related Disorders studies →Yale University is the lead sponsor of 1,724 studies on the registry; 298 are open to participants now.
Of its 210 completed or terminated interventional studies of FDA-regulated products, 126 (60%) have results posted.
Counted across the registry records on this site, refreshed daily.
Treatment-seeking OUD patients will be recruited from local clinics. Those with OUD not seeking treatment and healthy controls will be recruited from New Haven and surrounding areas in Connecticut.
Patients with Opioid Use Disorder (OUD)
To be eligible for inclusion in the study, an individual must meet all of the following criteria:
Exclusion Criteria:
Individuals with regular opioid use
To be eligible for inclusion in the study, an individual must meet all of the following criteria:
Exclusion Criteria:
Individuals with regular opioid use
To be eligible for inclusion in the study, an individual must meet all of the following criteria:
Exclusion Criteria:
Individuals with regular opioid use
To be eligible for inclusion in the study, an individual must meet all of the following criteria:
Exclusion Criteria:
Healthy controls (HC) Inclusion Criteria
Exclusion Criteria:
4. Any subjects with foreign ferromagnetic metal objects in their body or other MR contraindications will be excluded.
5. Pregnant or lactating women will not be recruited for the study. 6. Cannot or are not willing to lie comfortably flat on his/her back for up to 2 hours in the MRI scanner (self-report).
7. Body weight > 550 lbs. The MR scanner bed is tested to a weight limit of 550 lbs.
individuals with OUD diagnosis
Behavioral: follow up interviews for 12 months to determine opioid use
Healthy individuals without substance use disorders
Follow-up
Avoidance learning measure
Task performance measure of avoidance learning, quantified by response time and performance accuracy. Those with OUD are expected to have lower performance accuracy, lower learning rates, and higher response time during avoidance learning relative to healthy controls
Time frame: Day 1 (immediately after consent and clinical assessment)
opioid use
Quantity of opioid use following the baseline visit, measured by times use per week. Timeline follow back method will be used to assess the quantity of opioid use during the follow-up period. The investigators will examine this opioid use quantity in relation with avoidance learning deficits. The investigators expect greater avoidance dysfunction at baseline to predict higher weekly use of opioids
Time frame: During the 12-month follow-up period
Brain activity during avoidance learning
The brain activation magnitude associated with avoidance learning and avoidance learning dysfunction during the task performance. Brain activation will be computed by using contrast between avoidance learning vs. neutral conditions. Contrasts between two subject groups (i.e., OUD vs. HC) will also be examined. The investigators expect OUD patients to exhibit greater activations in the pain circuit during avoidance learning relative to healthy controls. Additionally, pain circuit activation will be assessed in association with opioid use severity during follow-up period.
Time frame: Day 1 (immediately after consent and clinical assessment)
Comparison of avoidance learning rate between women and men
Sex differences in avoidance learning dysfunction in those with opioid use disorder. Comparison between women and men will be conducted in relation to their avoidance learning task performance (e.g., performance accuracy, response time)
Time frame: Day 1 (immediately after consent and clinical assessment)
Comparison of brain activity during avoidance learning between women and men
Comparison between women and men will be conducted in relation to their brain activations during avoidance learning to determine whether women or men may have higher brain activity amplitude during learning of avoidance behavior.
Time frame: Day 1 (immediately after consent and clinical assessment)
Relationship between sex differences in avoidance learning and opioid use
Investigators will examine whether opioid use severity has a relationship with differences in avoidance learning performance.
Time frame: Day 1 (immediately after consent and clinical assessment)
Plan to share: No — There is no plan to share IPD at this time
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