An electroencephalography connectome predictive model of craving for methamphetamine

Area of Science:

• Neuroscience
• Addiction Research
• Psychiatry

Background:

• Methamphetamine use disorder (MUD) is marked by intense craving and relapse.
• Neural underpinnings of cue-induced craving and its relation to impulsivity and abstinence duration in MUD are not fully understood.

Purpose of the Study:

• To identify the neural substrates of methamphetamine craving.
• To develop a predictive model for craving in MUD using brain activity.
• To explore the relationship between craving, abstinence duration, and trait impulsivity.

Main Methods:

• High-density resting-state electroencephalography (EEG) was recorded after participants viewed methamphetamine use cues.
• Source imaging and connectome predictive modeling (CPM) were used to build a craving-specific network in beta band activity.
• The model was developed and validated on two independent MUD cohorts.

Main Results:

• A unified neural signature for craving was identified, involving medial prefrontal, frontal parietal, and subcortical networks.
• The craving connectome profile mediated the link between abstinence duration and craving intensity.
• Trait impulsivity mediated the relationship between the EEG-derived craving connectome and cue-induced craving.

Conclusions:

• A novel predictive model using EEG-derived sourced connectivity accurately predicts methamphetamine craving in individuals with MUD.
• Findings illuminate the cognitive processes in craving, including cognitive control, attention, and reward reactivity.
• EEG data offers insights into craving dynamics, aiding in understanding and treating substance use disorders.