Neuropsychological Assessment of the Relationship of Working Memory with K-BIT Matrices and Vocabulary in Normal Development and ADHD Children and Adolescents.

BACKGROUND: The present report tries to understand the possible relationship between working memory (WM) and intelligence measurements, using the direct scores of the Working Memory Test Battery for Children (WMTBC) and Kaufman's Brief Intelligence Test (K-BIT), in normal development (ND) and diagnosed attention deficit hyperactivity disorder (ADHD) children and adolescents. RESULTS: Partial correlations, discounting the effect of age, showed a significant correlation in ND subjects between the central executive (CE) component of WM and the WM visuospatial sketchpad (VSS) component and the WM phonological loop (PL); also, significant correlations were obtained for the WM VSS with the K-BIT Matrices scores, the WM PL with the K-BIT Vocabulary, and the K-BIT Matrices scores with the K-BIT Vocabulary. For ADHD subjects, there were significant correlations between WM VSS and WM CE, and WM VSS and K-BIT Matrices. We tested the robustness of these correlations by selecting a small number of subjects through permutations; a robust correlation between WM CE and WM PL in ND, and between WM VSS and WM CE and WM VSS and K-BIT Matrices scores was obtained. These results were also supported by mediation analysis. CONCLUSIONS: There is a relationship during development between WM as measured with WMTBC and general intelligence as measured with K-BIT in ND and ADHD subjects. The dysexecutive character of ADHD has been shown, given that by controlling for intelligence, the differences in WM performance between ND and ADHD disappear, except for WM CE. The results suggest that in ADHD subjects, the WM VSS component presents a more pivotal role during cognitive processing compared to ND subjects.

Neurovascular coupling during auditory stimulation: event-related potentials and fNIRS hemodynamic.

Intensity-dependent amplitude changes (IDAP) have been extensively studied using event-related potentials (ERPs) and have been linked to several psychiatric disorders. This study aims to explore the application of functional near-infrared spectroscopy (fNIRS) in IDAP paradigms, which related to ERPs could indicate the existence of neurovascular coupling. Thirty-three and thirty-one subjects participated in two experiments, respectively. The first experiment consisted of the presentation of three-tone intensities (77.9 dB, 84.5 dB, and 89.5 dB) lasting 500 ms, each type randomly presented 54 times, while the second experiment consisted of the presentation of five-tone intensities (70.9 dB, 77.9 dB, 84.5 dB, 89.5 dB, and 94.5 dB) in trains of 8 tones lasting 70 ms each tone, the trains were presented 20 times. EEG was used to measure ERP components: N1, P2, and N1-P2 peak-to-peak amplitude. fNIRS allowed the analysis of the hemodynamic activity in the auditory, visual, and prefrontal cortices. The results showed an increase in N1, P2, and N1-P2 peak-to-peak amplitude with auditory intensity. Similarly, oxyhemoglobin and deoxyhemoglobin concentrations showed amplitude increases and decreases, respectively, with auditory intensity in the auditory and prefrontal cortices. Spearman correlation analysis showed a relationship between the left auditory cortex with N1 amplitude, and the right dorsolateral cortex with P2 amplitude, specifically for deoxyhemoglobin concentrations. These findings suggest that there is a brain response to auditory intensity changes that can be obtained by EEG and fNIRS, supporting the neurovascular coupling process. Overall, this study enhances our understanding of fNIRS application in auditory paradigms and highlights its potential as a complementary technique to ERPs.

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.

Linear and Non-linear Analyses of EEG in a Group of ASD Children During Resting State Condition.

This study analyses the spontaneous electroencephalogram (EEG) brain activity of 14 children diagnosed with Autism Spectrum Disorder (ASD) compared to 18 children with normal development, aged 5-11 years. (i) Power Spectral Density (PSD), (ii) variability across trials (coefficient of variation: CV), and (iii) complexity (multiscale entropy: MSE) of the brain signal analysis were computed on the resting state EEG. PSD (0.5-45 Hz) and CV were averaged over different frequency bands (low-delta, delta, theta, alpha, low-beta, high-beta and gamma). MSE were calculated with a coarse-grained procedure on 67 time scales and divided into fine, medium and coarse scales. In addition, significant neurophysiological variables were correlated with behavioral performance data (Kaufman Brief Intelligence Test (KBIT) and Autism Spectrum Quotient (AQ)). Results show increased PSD fast frequency bands (high-beta and gamma), higher variability (CV) and lower complexity (MSE) in children with ASD when compared to typically developed children. These results suggest a more variable, less complex and, probably, less adaptive neural networks with less capacity to generate optimal responses in ASD children.

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.

Activation-Inhibition dynamics of the oscillatory bursts of the human EEG during resting state. The macroscopic temporal range of few seconds.

The ubiquitous brain oscillations occur in bursts of oscillatory activity. The present report tries to define the statistical characteristics of electroencephalographical (EEG) bursts of oscillatory activity during resting state in humans to define (i) the statistical properties of amplitude and duration of oscillatory bursts, (ii) its possible correlation, (iii) its frequency content, and (iv) the presence or not of a fixed threshold to trigger an oscillatory burst. The open eyes EEG recordings of five subjects with no artifacts were selected from a sample of 40 subjects. The recordings were filtered in frequency ranges of 2 Hz wide from 1 to 99 Hz. The analytic Hilbert transform was computed to obtain the amplitude envelopes of oscillatory bursts. The criteria of thresholding and a minimum of three cycles to define an oscillatory burst were imposed. Amplitude and duration parameters were extracted and they showed durations between hundreds of milliseconds and a few seconds, and peak amplitudes showed a unimodal distribution. Both parameters were positively correlated and the oscillatory burst durations were explained by a linear model with the terms peak amplitude and peak amplitude of amplitude envelope time derivative. The frequency content of the amplitude envelope was contained in the 0-2 Hz range. The results suggest the presence of amplitude modulated continuous oscillations in the human EEG during the resting conditions in a broad frequency range, with durations in the range of few seconds and modulated positively by amplitude and negatively by the time derivative of the amplitude envelope suggesting activation-inhibition dynamics. This macroscopic oscillatory network behavior is less pronounced in the low-frequency range (1-3 Hz).

Absolute and relative variability changes of the resting state brain rhythms from childhood and adolescence to young adulthood.

The present report aimed to analyze the possible relationship of spontaneous EEG power variability across epochs in individual subjects (absolute and relative) with age. For this purpose, the resting state EEG of a sample of 258 healthy subjects (6-29 years old) in open and closed eyes experimental conditions were recorded. The power spectral density (PSD) was calculated from 0.5-45 Hz. Three electrodes with the highest PSD in each band were selected, and linear and inverse regression of the mean, standard deviation (SD), and coefficient of variation CV of the PSD vs age were computed. The results showed that the EEG absolute variability (SD) decreases with age, and in contrast, the relative variability (CV) increased, except for high frequencies in which it remains stable during maturation. We conclude that the variability in the EEG PSD when is not influenced by the mean PSD tends to increase from childhood and adolescence to young adulthood. Present results complement the extensive literature on changes of EEG power in different brain rhythms with the changes in EEG power variability during maturation.

Frequency coupling of low and high frequencies in the EEG of ADHD children and adolescents in closed and open eyes conditions.

The present report examines the possible differences in absolute Power Spectral Density (PSD), the topography of brain rhythms, and low frequency (delta and theta) vs. beta PSD when attention deficit disorder (ADHD) children and controls are compared. These results would potentially be useful to test the validity of the developmental lag and differential developmental models for ADHD. The EEG resting state under the experimental conditions of open and closed eyes were recorded in samples of control subjects and children with ADHD (6-17 years old). The PSD from 0 to 46 Hz was calculated and ANOVAs were performed to compare the groups of subjects in the two experimental conditions. To observe differences in the co-maturation of the brain rhythms between the groups of subjects, correlations of the PSD of all frequency ranges were computed. These results showed an increase in delta power in children with ADHD compared to control subjects. The topographies of the different brain rhythms were similar in children with ADHD and controls. The maturational power-to-power frequency-coupling between low frequencies and beta rhythms was lower in children with ADHD. The increased delta PSD in ADHD and the similar brain rhythms topographies in children with ADHD and controls support the developmental lag model, whereas the decreased co-maturation of low frequencies vs. beta PSD in children with ADHD suggests a differential maturation rate for low and beta frequencies in children with ADHD compared to controls.