The Limbic System in Co-Occurring Substance Use and Anxiety Disorders: A Narrative Review Using the RDoC Framework.

Substance use disorders (SUDs) and anxiety disorders (ADs) are highly comorbid, a co-occurrence linked to worse clinical outcomes than either condition alone. While the neurobiological mechanisms involved in SUDs and anxiety disorders are intensively studied separately, the mechanisms underlying their comorbidity remain an emerging area of interest. This narrative review explores the neurobiological processes underlying this comorbidity, using the Research Domain Criteria (RDoC) framework to map disruptions in positive valence, negative valence, and cognitive systems across the three stages of the addiction cycle: binge/intoxication, withdrawal/negative affect, and preoccupation/anticipation.

Brain connectivity changes to fast versus slow dopamine increases.

The rewarding effects of stimulant drugs such as methylphenidate (MP) depend crucially on how fast they raise dopamine in the brain. Yet how the rate of drug-induced dopamine increases impacts brain network communication remains unresolved. We manipulated route of MP administration to generate fast versus slow dopamine increases.

Neural circuit selective for fast but not slow dopamine increases in drug reward.

The faster a drug enters the brain, the greater its addictive potential, yet the brain circuits underlying the rate dependency to drug reward remain unresolved. With simultaneous PET-fMRI we linked dynamics of dopamine signaling, brain activity/connectivity, and self-reported 'high' in 20 adults receiving methylphenidate orally (results in slow delivery) and intravenously (results in fast delivery) (trial NCT03326245). We estimated speed of striatal dopamine increases to oral and IV methylphenidate and then tested where brain activity was associated with slow and fast dopamine dynamics (primary endpoint).

Accelerated Aging of the Amygdala in Alcohol Use Disorders: Relevance to the Dark Side of Addiction.

Here we assessed changes in subcortical volumes in alcohol use disorder (AUD). A simple morphometry-based classifier (MC) was developed to identify subcortical volumes that distinguished 32 healthy controls (HCs) from 33 AUD patients, who were scanned twice, during early and later withdrawal, to assess the effect of abstinence on MC-features (Discovery cohort). We validated the novel classifier in an independent Validation cohort (19 AUD patients and 20 HCs).