Mechanisms Underlines Brain Processes in Addiction: A Spiking Neural Network Analysis from the EEG

Research in the field of pathological addiction has shown that craving is one of the factors contributing to continued substance use. Craving can be considered an urgent need to use substances and can be triggered by a prolonged period of abstinence or by external stimuli. Several studies have shown how the use of non-invasive neurostimulation techniques such as tDCS (Transcranial Direct Current Stimulation) can help reduce craving through the use of protocols and repetitive stimulation sessions. The present study aims to analyze the neurological mechanisms underlying the brain processes, stimulated by neurostimulation, through the use of Spiking Neural Network (SNN), which represents a biologically more adherent method compared to traditional neural network models, for learning, classification, and comparative analysis of brain data. EEG traces were recorded on eight subjects with cocaine dependence during a cognitively activating task. Four subjects performed 9 sessions with tDCS and the remaining 4 subjects did not perform tDCS. Anode placed on F3 and cathode on F4 has been used as tDCS protocol. EEG data were collected through a Brain–Computer Interface (BCI). The NeuCube architecture, trained on spatio-temporal EEG data, was used to classify EEG data between the two groups of subjects to facilitate a more in-depth comparative analysis of dynamic processes in the brain. The results showed different brain activity patterns, in particular related to the frontal areas. Through the analysis of the connectivity of the SNN model and its dynamics, new information has been revealed on the effects of tDCS on cognitive functions of the brain and areas involved in cocaine addiction. These results can bring new insights into the brain functions associated with brain activity in subjects with addiction under cognitive activation conditions.