Machine-learning identifies substance-specific behavioral markers for opiate and stimulant dependence.

ABSTRACT:

Background

Recent animal and human studies reveal distinct cognitive and neurobiological differences between opiate and stimulant addictions; however, our understanding of the common and specific effects of these two classes of drugs remains limited due to the high rates of polysubstance-dependence among drug users.

Methods

The goal of the current study was to identify multivariate substance-specific markers classifying heroin dependence (HD) and amphetamine dependence (AD), by using machine-learning approaches. Participants included 39 amphetamine mono-dependent, 44 heroin mono-dependent, 58 polysubstance dependent, and 81 non-substance dependent individuals. The majority of substance dependent participants were in protracted abstinence. We used demographic, personality (tr

SUBMITTER: Ahn WY 

PROVIDER: S-EPMC4955649 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature