Modeling functional brain connections in methamphetamine and opioid abusers

Abstract

Substance abuse has become a significant problem worldwide. The primary purpose of this study was to model the functional brain connectivity in methamphetamines (Meth) and opioids (Op) groups in comparison with the healthy control (HC) group. EEG data were recorded in Meth (n ​= ​8), Op (n ​= ​12), and HC groups (n ​= ​12) in a closed-eye resting state. The NeuCube model based on a spiking neural network was used for EEG data's functional brain connectivity modeling. The NeuCube model was evaluated quantitatively and qualitatively with model descriptive parameters. The results showed the average value of the neuron's activation level, spikes emitted from neurons, and clustering coefficient as a communication parameter in the HC group decreased from 1154, 1103, 0.026 to 1036, 981, 0.020 in the Op group and to 511, 468, 0.009 in the Meth group, respectively. The changes in indices were significant according to the ANOVA test with p ≪0.001. The decrease in indices was more significant in the Meth group than in the Op group. The research findings showed that the abuse of Meth and Op causes damage to the brain's functional connections. The damage included shortening and limiting communication routes and decreased neurons' ability to generate membrane potential and emit inhibitory and excitatory spikes. Injuries were reported to be more severe in the Meth group than in the Op group.

Keywords

• Electroencephalogram
• Methamphetamines
• NeuCube model
• Opioids
• Spiking neural networks