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


Creative Commons License

Aydin S., Çetin F. H., Çikili Uytun M., Babadag̃í Z., Güven A. S., Işık Y.

Biomedical Signal Processing and Control, vol.76, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 76
  • Publication Date: 2022
  • Doi Number: 10.1016/j.bspc.2022.103626
  • Journal Name: Biomedical Signal Processing and Control
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED)
  • Keywords: Pearson correlation, Br a i n connectivity, Graph theory, EEG, ADHD, PHASE-LAG INDEX, FUNCTIONAL CONNECTIVITY, DEFAULT-MODE, NAIVE BOYS, EEG, CHILDREN, METHYLPHENIDATE, DISORDERS, UNDERACTIVATION, METAANALYSIS
  • Hacettepe University Affiliated: Yes

Abstract

https://www.sciencedirect.com/science/article/pii/S1746809422001483 

© 2022 Elsevier LtdThe goal of the present study is to propose the use of global connectivity measures as quantitative indicators of long-term medication in pediatric patients with Attention-Deficit-Hyperactivity Disorder, combined type (ADHD-C). For this purpose, graph theoretical brain connectivity indices are computed from connectivity estimations across eyes-opened resting-state EEG recordings measured before and after the treatment with osmotic release oral system-methylphenidate for a month in 18 boys (aged between 7–12 years). In order to present the reliable results, neurofunctional correlations are firstly estimated in time (Pearson Correlation (PC), Spearman Correlation), frequency (Directed Transfer Function, Partial Directed Coherence) and phase (Phase Locking Value, Phase Lag Index) domains in between short segments of 2sec over single trials of 1min. Later, transitivity, clustering coefficients, assortativity, global efficiency and modularity are computed from EEG based connectivity matrices produced by each approach. Since the highest classification accuracy of 83.79% is provided by PC, statistical tests (one-way Anova, pair-wise multiple comparison) and step-wise logistic regression modelling are all examined to detect significant differences between pre- and post- treatment relevant connectivity measures. Statistical boxplots are also shown, as well. Overall results reveal that global brain connectivity can be increased by long-term medication in pediatric ADHD-C in terms of increased segregation & resilience. This is the first study to demonstrate that long-term medication can normalize the functional brain connectivity in ADHD, which is characterized by decreased connectivity compared to controls.