EEG Spectral Amplitudes Research Articles

Brain electrical microstate features as biomarkers of a stable motor output

Objective. The aim of the present study was to elucidate the brain dynamics underlying the maintenance of a constant force level exerted during a visually guided isometric contraction task by optimizing a predictive multivariate model based on global and spectral brain dynamics features. Approach. Electroencephalography (EEG) was acquired in 18 subjects who were asked to press a bulb and maintain a constant force level, indicated by a bar on a screen. For intervals of 500 ms, we calculated an index of force stability as well as indices of brain dynamics: microstate metrics (duration, occurrence, global explained variance, directional predominance) and EEG spectral amplitudes in the theta, low alpha, high alpha and beta bands. We optimized a multivariate regression model (partial least square (PLS)) where the microstate features and the spectral amplitudes were the input variables and the indexes of force stability were the output variables. The issues related to the collinearity among the input variables and to the generalizability of the model were addressed using PLS in a nested cross-validation approach. Main results. The optimized PLS regression model reached a good generalizability and succeeded to show the predictive value of microstates and spectral features in inferring the stability of the exerted force. Longer duration and higher occurrence of microstates, associated with visual and executive control networks, corresponded to better contraction performances, in agreement with the role played by the visual system and executive control network for visuo-motor integration. Significance. A combination of microstate metrics and brain rhythm amplitudes could be considered as biomarkers of a stable visually guided motor output not only at a group level, but also at an individual level. Our results may play an important role for a better understanding of the motor control in single trials or in real-time applications as well as in the study of motor control.

Electrophysiological correlates of the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism

The brain-derived neurotrophic factor (BDNF) protein is essential for neuronal development. Val66Met (rs6265) is a functional polymorphism at codon 66 of the BDNF gene that affects neuroplasticity and has been associated with cognition, brain structure and function. The aim of this study was to clarify the relationship between BDNF Val66Met polymorphism and neuronal oscillatory activity, using the electroencephalogram (EEG), in a normative cohort. Neurotypical (N = 92) young adults were genotyped for the BDNF Val66Met polymorphism and had eyes open resting-state EEG recorded for four minutes. Focal increases in right fronto-parietal delta, and decreases in alpha-1 and right hemispheric alpha-2 amplitudes were observed for the Met/Met genotype group compared to Val/Val and Val/Met groups. Stronger frontal topographies were demonstrated for beta-1 and beta-2 in the Val/Met group versus the Val/Val group. Findings highlight BDNF Val66Met genotypic differences in EEG spectral amplitudes, with increased cortical excitability implications for Met allele carriers.

Topographic Electrophysiological Signatures of fMRI Resting State Networks

BackgroundfMRI Resting State Networks (RSNs) have gained importance in the present fMRI literature. Although their functional role is unquestioned and their physiological origin is nowadays widely accepted, little is known about their relationship to neuronal activity. The combined recording of EEG and fMRI allows the temporal correlation between fluctuations of the RSNs and the dynamics of EEG spectral amplitudes. So far, only relationships between several EEG frequency bands and some RSNs could be demonstrated, but no study accounted for the spatial distribution of frequency domain EEG.Methodology/Principal FindingsIn the present study we report on the topographic association of EEG spectral fluctuations and RSN dynamics using EEG covariance mapping. All RSNs displayed significant covariance maps across a broad EEG frequency range. Cluster analysis of the found covariance maps revealed the common standard EEG frequency bands. We found significant differences between covariance maps of the different RSNs and these differences depended on the frequency band.Conclusions/SignificanceOur data supports the physiological and neuronal origin of the RSNs and substantiates the assumption that the standard EEG frequency bands and their topographies can be seen as electrophysiological signatures of underlying distributed neuronal networks.

Life-span changes in EEG spectral amplitude, amplitude variability and mean frequency

Objectives: The objectives were to assess life-span alterations in intrasubject variability of EEG spectral amplitudes and in amplitude and mean frequency computed from spectral amplitude profiles.Methods: EEG was recorded from the central and occipital scalp of 222 healthy males aged 4 to 90 years. Amplitude spectral profiles derived from FFT procedures provided data for the computation of amplitude variability (ampCV), absolute and relative amplitude and mean frequency for each of five spectral bands. Analysis of variance, coefficient of correlation and t test were employed in data analyses.Results: The ampCV measure did not provide direct evidence of age-related intrasubject changes in EEG frequency but was useful for indexing the presence of rhythmic EEG activity. Marked decreases in absolute amplitude occurred during childhood with little change thereafter. Age changes in relative amplitude were more complex and differed for slow and fast EEG activity. We also report that an algorithm frequently used to estimate mean frequency can introduce consistent bias into mean frequency computations under some conditions.Conclusions: Life-span changes in measured EEG characteristics were generally consistent with those from earlier studies. It is important that investigators validate and describe procedures used to determine mean frequency of EEG spectral data.

EEG asymmetry and heart rate during experience of hypnotic analgesia in high and low hypnotizables

This study evaluates the effects of hypnotic analgesia and hypnosis on bilateral EEG activity recorded from frontal, central and posterior areas during three painful electrical stimulation conditions: waking, hypnosis/no-analgesia, hypnosis/analgesia. Eight high-hypnotizable and eight low-hypnotizable (right handed) subjects participated in the experiment. The following measures were obtained: pain and distress tolerance ratings; EEG spectral amplitudes for the frequency bands: δ (0.5–3.75 Hz), θ1 (4–5.75 Hz), θ2 (6–7.75 Hz), α1 (8–9.75 Hz), α2 (10–12.75 Hz), β1 (13–15.75 Hz), β2 (16–31.75 Hz), total band (0.5–31.75 Hz), ‘40-Hz’ (36–44 Hz); cardiac interbeat interval (ms); mid-frequency and high-frequency peaks from power spectral analysis of heart period variability. During hypnosis/analgesia, high hypnotizable subjects displayed significant reductions in pain and distress scores compared to hypnosis/no-analgesia and waking conditions. In each experimental condition these subjects displayed significant lower total and β1 amplitudes compared to low hypnotizables. High hypnotizables, on central and posterior recording sites, during both hypnosis/analgesia and hypnosis/no-analgesia conditions also showed total and delta EEG amplitude reductions in both hemispheres and a θ1 amplitude reduction in the left hemisphere. However, for total, delta and β1 bands in the hypnosis/analgesia condition the amplitude reduction was more pronounced in the right hemisphere as shown by hemispheric asymmetry in favor of the left hemisphere. Low hypnotizables, on posterior recording sites, displayed a delta amplitude reduction during hypnosis/no-analgesia and hypnosis/analgesia conditions. These subjects also showed, for all recording sites, a reduction in θ1 amplitude during hypnosis/no-analgesia compared to the waking condition. Lows, however, failed in evidencing amplitude differences between hypnosis/no-analgesia and hypnosis/analgesia conditions. During hypnotic analgesia the hemispheric asymmetry found in high hypnotizables was parallel to a significant reduction in the spectral mid-frequency peak of heart period variability which indicated a decrease in the level of sympathetic activity. In contrast, during hypnosis/no-analgesia the EEG amplitude reduction was not paralleled by a decrease in sympathetic activity.

An analysis of the intercorrelations among spectral amplitudes in the EEG: a generator study.

The objective of this study is to explore the physiological sources of covariation between multiple narrow-band EEG spectral amplitudes with an aim toward parsimonious modeling of the observed intercorrelations. Specifically, a factor-analytic model describing the intercorrelations among 25 spectral amplitudes, at 1-Hz increments from 1 to 25 Hz, is presented. This method is applied to the EEGs obtained from a group of five subjects controlled for age, sex, state of consciousness, and recording dipole. The subjects were studied in waking and sleeping states in order to examine how this model would represent such physiological changes.