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


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Aydin S., Cetin F. H., ÇIKILI UYTUN M., Babadagi Z., Gueven A. S., Isik Y.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL, cilt.76, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 76
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1016/j.bspc.2022.103626
  • Dergi Adı: BIOMEDICAL SIGNAL PROCESSING AND CONTROL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, EMBASE, INSPEC
  • Anahtar Kelimeler: 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
  • Gazi Üniversitesi Adresli: Evet

Özet

The 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 ar e 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 Corre-lation), 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 1m i n . Later, transitivit y , clustering coefficients, assortativity, global efficiency and modularity are computed from EEG based connectivit y 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 a l l examined to detect significant differences between pre-and post-treatment relevant connectivity measures. Statistical boxplots are also shown, as well. Overal l 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.