One hundred years of EEG for brain and behaviour research

On the centenary of the first human EEG recording, more than 500 experts reflect on the impact that this discovery has had on our understanding of the brain and behaviour. We document their priorities and call for collective action focusing on validity, democratization and responsibility to realize the potential of EEG in science and society over the next 100 years

Resting-state EEG oscillatory dynamics in fragile X syndrome: abnormal functional connectivity and brain network organization.

Disruptions in functional connectivity and dysfunctional brain networks are considered to be a neurological hallmark of neurodevelopmental disorders. Despite the vast literature on functional brain connectivity in typical brain development, surprisingly few attempts have been made to characterize brain network integrity in neurodevelopmental disorders. Here we used resting-state EEG to characterize functional brain connectivity and brain network organization in eight males with fragile X syndrome (FXS) and 12 healthy male controls. Functional connectivity was calculated based on the phase lag index (PLI), a non-linear synchronization index that is less sensitive to the effects of volume conduction. Brain network organization was assessed with graph theoretical analysis. A decrease in global functional connectivity was observed in FXS males for upper alpha and beta frequency bands. For theta oscillations, we found increased connectivity in long-range (fronto-posterior) and short-range (frontal-frontal and posterior-posterior) clusters. Graph theoretical analysis yielded evidence of increased path length in the theta band, suggesting that information transfer between brain regions is particularly impaired for theta oscillations in FXS. These findings are discussed in terms of aberrant maturation of neuronal oscillatory dynamics, resulting in an imbalance in excitatory and inhibitory neuronal circuit activity

Mean normalized path length over all epochs for FXS and controls participants in the delta (0.05–4 Hz), theta (4–8 Hz), lower alpha (8–10 Hz), upper alpha (10–13 Hz), beta (13–30 Hz), and gamma (30–45 Hz) frequency range.

<p>Path length in the theta band is significant longer in FXS males as compared to controls. Asterisks represent significant differences at <i>p</i><.05. Error bars represent standard error of the mean.</p

Results of the small-world index “<i>S</i>” in FXS and controls in the six EEG frequency bands.

<p>Note: Values represent mean small-world index ‘<i>S</i>’. Standard error of the mean is presented between brackets.</p

Mean normalized clustering coefficients over all epochs for FXS and controls participants in the delta (0.05–4), theta (4–8 Hz), lower alpha (8–10 Hz), upper alpha (10–13 Hz), beta (13–30 Hz), and gamma (30–45 Hz) frequency range.

<p>Error bars represent standard error of the mean.</p

An overview of the method used to calculate weighted graphs.

<p>(A) EEG time-series from the 26 scalp electrodes were separately filtered for the delta, theta, alpha low, alpha high, beta, and gamma frequency bands. Higher alpha (10–13 Hz) is shown here as largest group differences were found for this frequency band. (B) Functional connectivity between all 26×26 electrode pairs was calculated based on the phase lag index, yielding connectivity values between 0 and 1 (higher values reflect more synchronization between electrodes). (C) When using graph theoretical analysis on EEG time series, electrodes represent “nodes” and the distance between these nodes represent the “edges” in the graph. PLI scores were used to calculate the path length (distance between the nodes) and the clustering coefficients (the degree in which nodes cluster together). In addition, a randomization procedure is employed to obtain measures independent of network size. From each original graph, random networks were derived by randomly shuffling the edge weights. Mean values of weighted graphs are then determined by dividing the original graph measures by these ‘surrogate’ measures.</p

Corrigendum: Graph Analysis of EEG Functional Connectivity Networks During a Letter-Speech Sound Binding Task in Adult Dyslexics

[This corrects the article DOI: 10.3389/fpsyg.2021.767839.]

EEG Resting State Functional Connectivity in Adult Dyslexics Using Phase Lag Index and Graph Analysis

Developmental dyslexia may involve deficits in functional connectivity across widespread brain networks that enable fluent reading. We investigated the large-scale organization of electroencephalography (EEG) functional networks at rest in 28 dyslexics and 36 typically reading adults. For each frequency band (delta, theta alpha and beta), we assessed functional connectivity strength with the phase lag index (PLI). Network topology was examined using minimum spanning tree (MST) graphs derived from the functional connectivity matrices. We found significant group differences in the alpha band (8–13 Hz). The graph analysis indicated more interconnected nodes, in dyslexics compared to typical readers. The graph metrics were significantly correlated with age in dyslexics but not in typical readers, which may indicate more heterogeneity in maturation of brain networks in dyslexics. The present findings support the involvement of alpha oscillations in higher cognition and the sensitivity of graph metrics to characterize functional networks in adult dyslexia. Finally, the current results extend our previous findings on children

Cardiac and electro-cortical concomitants of social feedback processing in women

This study provides a joint analysis of the cardiac and electro-cortical-early and late P3 and feedback-related negativity (FRN)-responses to social acceptance and rejection feedback. Twenty-five female participants performed on a social- and age-judgment control task, in which they received feedback with respect to their liking and age judgments, respectively. Consistent with previous reports, results revealed transient cardiac slowing to be selectively prolonged to unexpected social rejection feedback. Late P3 amplitude was more pronounced to unexpected relative to expected feedback. Both early and late P3 amplitudes were shown to be context dependent, in that they were more pronounced to social as compared with non-social feedback. FRN amplitudes were more pronounced to unexpected relative to expected feedback, irrespective of context and feedback valence. This pattern of findings indicates that social acceptance and rejection feedback have widespread effects on bodily state and brain function, which are modulated by prior expectancies