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Sundai, A.

Publications and source records attributed to Sundai, A..

2 recordsLinked to original sources

Dopamine signatures of excessive and compulsive cocaine and fentanyl use

Excessive and compulsive drug use despite adverse consequences is a hallmark of substance use disorder, yet individuals differ markedly in their vulnerability to develop these behaviors. Drugs of abuse are long known to alter endogenous dopamine (DA) signaling, but shared principles for how DA dynamics impact compulsive use among individuals and across drug classes are lacking. Here, we monitored DA release in the medial shell of nucleus accumbens (NAc) during cocaine and fentanyl self-administration, with or without coincident punishment, in large cohorts of mice. Contingent cocaine and fentanyl self-administration evoked complex and individually distinct DA dynamics; nevertheless, a robust negative correlation held across both drugs, such that high takers exhibited lower drug-evoked DA signals. During punished drug taking, cocaine and fentanyl cases were associated with distinct DA signatures of compulsivity. For cocaine, punishment-resistant mice showed lower sustained DA responses during the post-shock, drug-associated cue period, whereas for fentanyl, punishment-resistant mice displayed larger phasic DA at the co-occurrence of footshock and drug infusion. To identify common principles underlying these observations, we developed a computational model grounded in an Actor-Critic temporal-difference (TD) learning framework that incorporates internal states, agents uncertainty, and drug-specific effects. Remarkably, this model captures the observed diversity in DA dynamics across drug classes and among mice with variable drug taking propensities, hereby providing a unified interpretation of NAc DA signals as encoding TD reward prediction errors.

neuroscience↗

Reverse engineering placebo analgesia

Placebo analgesia is a widely observed clinical phenomenon. Establishing a robust mouse model of placebo analgesia is needed for careful dissection of the underpinning circuit mechanisms. However, previous studies failed to observe consistent placebo effects in rodent models of chronic pain. We wondered whether strong placebo analgesia can be reverse engineered using general anesthesia-activated neurons in the central amygdala (CeAGA) that can potently suppress pain. Indeed, in both acute and chronic pain models, pairing a context with CeAGA-mediated pain relief produced robust context-dependent analgesia, exceeding that induced by morphine in the same paradigm. We reasoned that if the analgesic effect was dependent on reactivation of CeAGA neurons by conditioned contextual cues, the analgesia would still be an active treatment, rather than a placebo effect. CeAGA neurons indeed receive monosynaptic inputs from temporal lobe areas that could potentially relay contextual cues directly to CeAGA. However, in vivo imaging showed that CeAGA neurons were not re-activated in the conditioned context, despite mice displaying a strong analgesic phenotype, supporting the notion that the cue-induced pain relief is true placebo analgesia. Our results show that conditioning with activation of a central pain-suppressing circuit is sufficient to engineer placebo analgesia, and that purposefully linking a context with an active treatment could be a means to harness the power of placebo for pain relief.

neuroscience↗