Comparison of domain specific connectivity metrics for estimation brain network indices in boys with ADHD-C

The goal of the present study is to propose use global connectivity measures as quantitative indicators long-term medication in pediatric patients with Attention-Deficit-Hyperactivity Disorder, combined type (ADHD-C). For this purpose, graph theoretical brain indices are computed from estimations across eyes-opened resting-state EEG recordings measured before and after treatment osmotic release oral system-methylphenidate for a month 18 boys (aged between 7–12 years). In order reliable results, neurofunctional correlations firstly estimated time (Pearson Correlation (PC), Spearman Correlation), frequency (Directed Transfer Function, Partial Directed Coherence) phase (Phase Locking Value, Phase Lag Index) domains short segments 2sec over single trials 1min. Later, transitivity, clustering coefficients, assortativity, efficiency modularity based matrices produced by each approach. Since highest classification accuracy 83.79% provided PC, statistical tests (one-way Anova, pair-wise multiple comparison) step-wise logistic regression modelling all examined detect significant differences pre- post- relevant measures. Statistical boxplots also shown, well. Overall results reveal that can be increased ADHD-C terms segregation & resilience. This first demonstrate normalize functional ADHD, which characterized decreased compared controls.