RESUMEN
Evidence of central nervous system (CNS) exogenous opioid effects in humans has been primarily gained through neuroimaging of three participant populations: individuals after acute opioid administration, those with opioid use disorder (OUD), and those with chronic pain receiving opioid therapy. In both the brain and spinal cord, opioids alter processes of pain, cognition, and reward. Opioid-related CNS effects may persist and accumulate with longer opioid use duration. Meanwhile, opioid-induced benefits versus risks to brain health remain unclear. This review article highlights recent accumulating evidence for how exogenous opioids impact the CNS in humans. While investigation of CNS opioid effects has remained largely disparate across contexts of opioid acute administration, OUD, and chronic pain opioid therapy, integration across these contexts may enable advancement toward effective interventions.
Asunto(s)
Analgésicos Opioides , Encéfalo , Dolor Crónico , Neuroimagen , Trastornos Relacionados con Opioides , Humanos , Analgésicos Opioides/administración & dosificación , Dolor Crónico/tratamiento farmacológico , Dolor Crónico/diagnóstico por imagen , Trastornos Relacionados con Opioides/fisiopatología , Neuroimagen/métodos , Encéfalo/efectos de los fármacos , Encéfalo/diagnóstico por imagen , Encéfalo/fisiopatologíaRESUMEN
Reward motivation is essential in shaping human behavior and cognition. Both reward motivation and reward brain circuits are altered in chronic pain conditions, including fibromyalgia. In this study of fibromyalgia patients, we used a data-driven independent component analysis (ICA) approach to investigate how brain networks contribute to altered reward processing. From females with fibromyalgia (N = 24) and female healthy controls (N = 24), we acquired fMRI data while participants performed a monetary incentive delay (MID) reward task. After analyzing the task-based fMRI data using ICA to identify networks, we analyzed 3 networks of interest: motor network (left), value-driven attention network, and basal ganglia network. Then, we evaluated correlation coefficients between each network timecourse versus a task-based timecourse which modeled gain anticipation. Compared to controls, the fibromyalgia cohort demonstrated significantly stronger correlation between the left motor network timecourse and the gain anticipation timecourse, indicating the left motor network was more engaged with gain anticipation in fibromyalgia. In an exploratory analysis, we compared motor network engagement during early versus late phases of gain anticipation. Across cohorts, greater motor network engagement (i.e., stronger correlation between network and gain anticipation) occurred during the late timepoint, which reflected enhanced motor preparation immediately prior to response. Consistent with the main results, patients exhibited greater engagement of the motor network during both early and late phases compared with healthy controls. Visual-attention and basal ganglia networks revealed similar engagement in the task across groups. As indicated by post-hoc analyses, motor network engagement was positively related to anxiety and negatively related to reward responsiveness. In summary, we identified enhanced reward-task related engagement of the motor network in fibromyalgia using a novel data-driven ICA approach. Enhanced motor network engagement in fibromyalgia may relate to impaired reward motivation, heightened anxiety, and possibly to altered motor processing, such as restricted movement or dysregulated motor planning.