Multiscale entropy of ADHD children during resting state condition.

This present study aims to investigate neural mechanisms underlying ADHD compared to healthy children through the analysis of the complexity and the variability of the EEG brain signal using multiscale entropy (MSE), EEG signal standard deviation (SDs), as well as the mean, standard deviation (SDp) and coefficient of variation (CV) of absolute spectral power (PSD). For this purpose, a sample of children diagnosed with attention-deficit/hyperactivity disorder (ADHD) between 6 and 17 years old were selected based on the number of trials and diagnostic agreement, 32 for the open-eyes (OE) experimental condition and 25 children for the close-eyes (CE) experimental condition. Healthy control subjects were age- and gender-matched with the ADHD group. The MSE and SDs of resting-state EEG activity were calculated on 34 time scales using a coarse-grained procedure. In addition, the PSD was averaged in delta, theta, alpha, and beta frequency bands, and its mean, SDp, and CV were calculated. The results show that the MSE changes with age during development, increases as the number of scales increases and has a higher amplitude in controls than in ADHD. The absolute PSD results show CV differences between subjects in low and beta frequency bands, with higher variability values in the ADHD group. All these results suggest an increased EEG variability and reduced complexity in ADHD compared to controls. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-022-09869-0.

Time-frequency neural dynamics of ADHD children and adolescents during a Working Memory task.

The present report analyzed the time-frequency changes in Event-Related Spectral perturbations (ERSP) in a sample of ADHD children and adolescents compared to a normodevelopment (ND) sample. A delayed match-to-sample (DMTS) test of working memory (WM) was presented to a group of ADHD subjects (N = 29) and compared with ND group (N = 34) with ages between 6 and 17 years old. Time-frequency decomposition was computed through wavelets. ADHD subjects presented higher Reaction Time (RT), Standard Deviation of RT (Std of RT), and a reduced percentage of correct responses. The results showed a complex pattern of oscillatory bursts during the encoding, maintenance, and recognition phases with similar dynamics in both groups. ADHD children presented a reduced Event-Related Synchronization (ERS) in the Theta range during the encoding phase, and also a reduced Alpha ERS during the late period of the maintenance phase. S1 Early theta ERS was positively correlated with Std of RT. Behavioral data, early Theta, and late Alpha ERS classified correctly above 70 % of ADHD and ND subjects when a linear discriminant analysis was applied. The reduced encoding and maintenance impaired brain dynamics of ADHD subjects would justify the poorer performance of this group of subjects.