Cannabidiol is a non-psychoactive compound that is the second most abundant component of cannabis. It has been shown to have a potential therapeutic value for a wide range of disorders, including anxiety, psychosis, and depression. Recently, it was suggested that cannabidiol might be a potential treatment for heroin craving and relapse. Here we investigated the effects of an acute treatment with cannabidiol on cocaine self-administration and cue-induced cocaine seeking in rats. Rats were trained to press a lever to self-administer cocaine (0.5 mg/kg/infusion), first under a fixed interval 20 s (FI-20 s) and then under a progressive ratio (PR) schedule of reinforcement. Cocaine self-administration under a PR schedule of reinforcement was not attenuated by cannabidiol injections (5.0 mg/kg and 10.0 mg/kg; i.p.) when tested 30 min and 24 h after treatment. Cannabidiol treatment (5.0 mg/kg or 10.0 mg/kg) also did not attenuate cue-induced cocaine seeking in rats after a withdrawal period of 14 days. In contrast, treatment with cannabidiol (10.0 mg/kg; i.p.) resulted in a statistically significant anxiolytic effect in the elevated plus-maze. Our findings suggest that, under the conditions described here, an acute cannabidiol treatment has a minimal effect on a rat model of cocaine intake and relapse.

Temporal-difference (TD) learning models afford the neuroscientist a theory-driven roadmap in the quest for the neural mechanisms of reinforcement learning. The application of these models to understanding the role of phasic midbrain dopaminergic responses in reward prediction learning constitutes one of the greatest success stories in behavioural and cognitive neuroscience. Critically, the classic learning paradigms associated with TD are poorly suited to cast light on its neural implementation, thus hampering progress. Here, we present a serial blocking paradigm in rodents that overcomes these limitations and allows for the simultaneous investigation of two cardinal TD tenets; namely, that learning depends on the computation of a prediction error, and that reinforcing value, whether intrinsic or acquired, propagates back to the onset of the earliest reliable predictor. The implications of this paradigm for the neural exploration of TD mechanisms are highlighted.

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Major depressive disorder (MDD) is a chronic and disabling disorder affecting roughly 280 million people worldwide. While multiple brain areas have been implicated, dysfunction of prefrontal cortex (PFC) circuitry has been consistently documented in MDD, as well as in animal models for stress-induced depression-like behavioral states. During brain development, axonal guidance cues organize neuronal wiring by directing axonal pathfinding and arborization, dendritic growth, and synapse formation. Guidance cue systems continue to be expressed in the adult brain and are emerging as important mediators of synaptic plasticity and fine-tuning of mature neural networks. Dysregulation or interference of guidance cues has been linked to depression-like behavioral abnormalities in rodents and MDD in humans. In this review, we focus on the emerging role of guidance cues in stress-induced changes in adult prefrontal cortex circuitry and in precipitating depression-like behaviors. We discuss how modulating axonal guidance cue systems could be a novel approach for precision medicine and the treatment of depression.