Project Summary Prescription opioids, e.g., oxycodone (OXY), are commonly encountered in youth and pose a significant public health problem. In addition, there are significant individual differences in subjective responses to opioids which contribute to vulnerabilities for misuse. However, little is understood about OXY's effects on brain function, or on how individual differences in these effects might relate to variations in subjective responses. Assessment of OXY's effects on brain function is critical to understanding its abuse liability a n d will provide insight into how and why this drug leads to misuse and abuse/dependence in some, but not all, individuals. This proposal will assess the effects of low-dose OXY (10mg) on whole-brain functional connectivity (FC), and explore relationships with subjective responses in healthy young adults (ages 21 to 30 years, N=40) with limited prior opioid exposure. OXY's effects on FC during both reward- processing and resting-state will be assessed using a randomized, double-blind, placebo-controlled, cross-over design incorporating multiband fMRI scanning. Subjective measures of drug response (e.g., `drug liking') will be collected before, during and after neuroimaging using NIDA PhenX measures. Neuroimaging data will be analyzed using data-driven methods to facilitate assessment of OXY's effects on FC both within hypothesized networks (e.g., salience and reward networks) as well as on patterns of between- network connectivity. Specifically, FC changes following OXY versus placebo (Aim 1) and relationships between these changes and subjective drug responses (Aim 2) will be assessed using intrinsic connectivity distribution (ICD). ICD is a data-driven, voxel-to-voxel method of assessing whole-brain connectivity patterns that is not limited by specification of seed regions or connectivity thresholds. In addition, connectome-based machine-learning will be used to build a predictive model of subjective responses to OXY using data acquired during placebo scans (Aim 3). This project will for the first time assess the effects of a prescription opioid on whole-brain FC. Understanding OXY's effects on large-scale network dynamics is crucial for understanding its abuse liability, and will guide future studies of OXY in addicted and at-risk populations. Identification of networks that are predictive of subjective responses to OXY is an essential first step toward finding a reliable biomarker of opioid response that will help to identify individuals at highest risk for misuse.