Mental disorders significantly impact public health, affecting about one-third of the population and imposing economic burdens due to healthcare costs and reduced productivity. Among these, ADHD is notable, with a prevalence of 5.3% in children and 2.8% in adults.

Characterized by inattention, hyperactivity, and impulsivity, ADHD’s etiology involves genetic, neurological, and environmental factors, including neurotransmitter imbalances. While psycho-stimulant medications are common, they often show limitations due to adverse effects. Neurofeedback offers a non-pharmacological alternative by enhancing brain function self-regulation. This thesis explores the use of EEG microstate analysis to identify altered brain activity in ADHD and assesses the efficacy of neurofeedback in modifying these patterns. Findings show that ADHD patients exhibit abnormal patterns of a specific brain state associated with attention and demonstrate that individuals with ADHD can intentionally regulate this state through neurofeedback.

The thesis also advances EEG microstate methodology by proposing frequency-specific segmentation of brain states, developing open-source software, and applying EEG microstate analysis to mental health disorders beyond the ADHD population.

Altogether, the work supports the use of EEG microstate analysis in studying mental disorders, particularly its utility in investigating ADHD. The feasibility of neurofeedback therapy and the in-depth analysis of the relationships between spectral parameters and microstates have revealed promising approaches that may lead to the development of new diagnostic and treatment tools for mental disorders.