AI analyses drug users' trip reports to better understand psychedelics

Artificial intelligence has been used to analyse thousands of written reports of personal experiences with psychoactive drugs to gain a better understanding of their subjective effects and how they work in the brain. Psychedelic drugs such as LSD, ketamine and psilocybin – the active compound in magic mushrooms – are being investigated as treatments for a range of conditions, including depression, addiction and post-traumatic stress disorder. The experiences they induce, which may be important for their therapeutic effects, are highly variable, and can include visual and auditory hallucinations, an altered sense of self and a distorted perception of time. Danilo Bzdok at McGill University in Montreal, Canada, and his colleagues used a pattern-recognition algorithm to scour 6850 accounts of experiences submitted on the website Erowid, involving 27 different drugs. They linked words used in the accounts for each drug, such as "euphoria", "nausea" or "visuals", with any of 40 receptors in the brain that the drug is known to interact with, and mapped drug effects onto areas of the brain where these receptors are most active.