Value-based decision-making network functional connectivity correlates with substance use and delay discounting...

Area of Science:

• Neuroscience
• Psychiatry
• Genetics

Background:

• Substance use disorders (SUDs) involve impaired control over substance use, leading to social and occupational deficits.
• High relapse rates and poor treatment compliance are common in SUDs.
• Identifying neural biomarkers for SUD risk can enable earlier detection and intervention.

Purpose of the Study:

• To identify neurobiological correlates of substance use frequency and severity.
• To explore the underlying structure of polysubstance use behavior.
• To investigate potential neural susceptibility biomarkers for SUDs.

Main Methods:

• Utilized data from 1,200 Human Connectome Project participants (aged 22-37).
• Assessed substance use across eight classes using the Semi-Structured Assessment for the Genetics of Alcoholism.
• Employed exploratory structural equation modeling, latent class analysis, and factor mixture modeling to define a substance use severity spectrum.
• Analyzed functional connectivity in 650 participants using Network-based Statistic, comparing it with delay discounting and substance use severity.

Main Results:

• A unidimensional continuum of substance use severity was identified, allowing participants to be ranked.
• Functional connectivity in the medial orbitofrontal, lateral prefrontal, and posterior parietal cortices correlated with impulsive decision-making and polysubstance use.
• Specific brain networks were identified as potentially serving as susceptibility biomarkers.

Conclusions:

• Substance use behavior can be represented as a unitary severity spectrum.
• Key brain regions and their functional connectivity are associated with impulsive decision-making and polysubstance use.
• These identified neural networks show promise as susceptibility biomarkers for earlier identification and treatment of substance use disorders.