An alpha modulation index for electroencephalographic studies using complex demodulation

Complex Modulation Method for Measuring Cross-Frequency Coupling of Neural Oscillations

There is growing evidence from human intracranial electrocorticography (ECoG) studies that interactions between cortical frequencies are important for sensory perception, cognition and inter-regional neuronal communication. Recent studies have focused mainly on the strength of phase-amplitude coupling in cross-frequency interactions. Here, we introduce a complex modulation method based on measures of coherence to investigate cross-frequency coupling in the neural time series. This novel approach uses complex demodulation transform and coherence measures from the transformed signals. We used this method to quantify power coupling between two cortical frequency bands: theta (47 Hz) and high gamma (70-150 Hz) in ECoG signals recorded during an auditory task. We compared complex modulation results with traditional phase-amplitude coupling measures (PAC) derived from the same ECoG dataset. Our results suggest that cross-frequency coupling may involve changes in both phase-amplitude and power relationships between frequencies, reflecting the complexity of neuronal oscillatory interactions.

Effect of mother's voice on neonatal respiratory activity and EEG delta amplitude

While the influence of the mother's voice on neonatal heart-rate response and its relevant activity on cerebral cortex and the autonomic nervous system (ANS) are well known, few studies have assessed its influence on respiratory activity. We investigated the relationship among the respiration rate, the delta wave amplitudes through electroencephalography, and the basal state of ANS through the respiratory variability index while 22 full-term neonates hear their mother's voice and an unknown voice. It was found that when respiratory variability was large, a transient (<5 s) change in respiration rates was observed in response to an unknown voice, while a greater increase in the delta wave amplitude was observed in the frontal lobe than the parietal one in response to the mother's voice. Conversely, when respiratory variability was small, a sustained increase (>10 s) in respiration rates was observed in response to the mother's voice, while a greater increase in the delta wave amplitude was found in both the frontal and parietal lobes. These results suggest that the basal state of ANS influences the latency of increases in respiration rates. Furthermore, induced by the mother's voice, transient increases in respiration rates are reduced in association with frontal lobe activity, and sustained increases in respiration rates are promoted in association with frontal and parietal lobe activities.

Effects of EEG-vigilance regulation patterns on early perceptual processes in human visual cortex

OBJECTIVE

To investigate influences of EEG-vigilance regulation patterns on perceptual processing during sustained visual attention in early visual areas.

METHODS

We compared a subject group with stable vigilance regulation to a group with unstable EEG-vigilance regulation. A rapid serial visual presentation stream (RSVP) elicited a 7.5 Hz steady state visual evoked potential (SSVEP), a continuous sinusoidal brain response as a measure of attentional resource allocation during sustained attention in early visual cortex. Subjects performed a target discrimination task. 150 trials were divided into two parts (75 trials each, trial duration: 11 s).

RESULTS

A significant interaction vigilance group by experimental part provided significantly greater SSVEP amplitudes for the unstable group in the second compared to the first part of the experiment. Both groups showed training effects with increased hit rates and d'-values in the second part of the experiment.

CONCLUSIONS

The unexpected finding of SSVEP amplitude increase for the unstable group might be due to competitive interactions for neural resources between the alpha response and SSVEPs.

SIGNIFICANCE

Individual patterns of EEG-vigilance regulation have a moderate impact on early sensory processing during sustained visual attention that is not paralleled in task performance.

Time perception at different EEG-vigilance levels

BACKGROUND

Human time perception is influenced by various factors such as attention and drowsiness. Nevertheless, the impact of cerebral vigilance fluctuations on temporal perception has not been sufficiently explored. We assumed that the state of vigilance ascertained by electroencephalography (EEG) during the perception of a given auditory rhythm would influence its reproduction. Thus, we hypothesised that the re-tapping interval length and the accuracy of reproduction performance would vary depending on the state of vigilance determined by EEG.

METHODS

12 female and 9 male subjects ranging from 21 to 38 years (M = 25.52, SD = 3.75) participated in a test paradigm comprising a) a resting EEG for the determination of vigilance while an auditory rhythm was presented, b) a short activity of the proband to be sure of sufficient alertness, and c) a tapping task to reproduce the presented rhythm. Vigilance states of three consecutive 1-sec-EEG-segments of the resting EEG before the reproduction phase were classified using the Vigilance Algorithm Leipzig (VIGALL).

RESULTS AND DISCUSSION

Reproduction accuracy was more precise after high EEG-vigilance stages. Thus, the subjects' mean deviation from the given rhythm was lower (t(17) = -2.733, p < 0.05) after high vigilance stage A (MW = 0.046, SD = 0.049) than after low vigilance stage B (MW = 0.065, SD = 0.067). The re-tapping-length was significantly shorter (t(17) = -2.190, p < 0.05) for reproduction phases following high EEG-vigilance stage A compared to the lower EEG-vigilance stage B.

CONCLUSION

These findings support the hypothesis of a varying time perception and of speed alterations of the internal clock after different states of EEG-vigilance, which were automatically classified by VIGALL. Thus, alterations of cognitive processing may be assessable by specific EEG-patterns.

Hyperstable regulation of vigilance in patients with major depressive disorder

OBJECTIVES

This study tested the hypothesis that patients with depression show less and later declines into lower EEG vigilance stages (different global functional brain states) under resting conditions than healthy controls, as proposed by the vigilance theory of affective disorders.

METHODS

Thirty patients with Major Depressive Disorder (19 female; mean age: 37.2 years, SD: 12.6) without psychotropic medication and 30 carefully age- and sex-matched controls (19 female; mean age: 37.3 years, SD: 12.8) without past or present mental disorders underwent a 15-min resting EEG. EEG-vigilance regulation was determined with a computer-based vigilance classification algorithm (VIGALL, Vigilance Algorithm Leipzig), allowing a classification of vigilance stages A (with substages A1, A2 and A3), B (with substages B1 and B2/3) and C.

RESULTS

Depressive patients spent significantly more time in the highest EEG vigilance substage A1, and less time in substages A2, A3 and B2/3 than controls. In depressive patients, a significantly longer latency until the occurrence of substages A2, A3 and B2/3 was observed. No significant group differences in the percentage of B1 segments or the latency until occurrence of B1 were found.

CONCLUSIONS

The results confirm the hypothesis that patients with depression show less (and later) declines into lower EEG vigilance stages under resting conditions than healthy controls, and support the vigilance theory of affective disorders linking a hyperstable vigilance regulation to depression.

Unstable EEG-vigilance in patients with cancer-related fatigue (CRF) in comparison to healthy controls

OBJECTIVES

Cancer-related fatigue (CRF) is associated with tiredness and sleepiness. It remains unclear, whether such complaints are associated with neurophysiological signs of sleep proneness or a state of neurophysiological hyperarousal in which the patient finds it difficult to relax and to initiate sleep. Therefore the goal of this study is to compare the electroencephalographic (EEG)-vigilance regulation of patients with CRF and healthy controls.

METHODS

A 15-min resting EEG with eyes closed was recorded in 22 patients with CRF and 22 matched healthy controls. Consecutive 1-s segments were classified into seven different vigilance stages ranging from high alertness to relaxed wakefulness (stage 0, A1, A2, A3) and further on to drowsiness (B1, B2/3) and sleep onset (stage C).

RESULTS

Results showed that patients with CRF revealed a higher number of vigilance stages A3 (mean 15.26 vs. 6.67%, P = 0.004) dropped significantly earlier to vigilance levels A3 (drop after 130.8 vs. 533.3 s, P = 0.000) and B2/3&C (407.8 vs. 604.1 s, P = 0.035) and showed significantly more transitions between vigilance stages (46.0 vs. 31.1%, P = 0.003) in comparison to healthy controls.

CONCLUSIONS

These findings suggest an unstable vigilance regulation in patients with CRF and provide a neurophysiological framework for the reported efficacy of psychostimulants in CRF.

Prestimulus vigilance predicts response speed in an easy visual discrimination task

Background

Healthy adults show considerable within-subject variation of reaction time (RT) when performing cognitive tests. So far, the neurophysiological correlates of these inconsistencies have not yet been investigated sufficiently. In particular, studies rarely have focused on alterations of prestimulus EEG-vigilance as a factor which possibly influences the outcome of cognitive tests. We hypothesised that a low EEG-vigilance state immediately before a reaction task would entail a longer RT. Shorter RTs were expected for a high EEG-vigilance state.

Methods

24 female students performed an easy visual discrimination task while an electroencephalogram (EEG) was recorded. The vigilance stages of 1-sec-EEG-segments before stimulus presentation were classified automatically using the computer-based Vigilance Algorithm Leipzig (VIGALL). The mean RTs of each EEG-vigilance stage were calculated for each subject. A paired t-test for the EEG-vigilance main stage analysis (A vs. B) and a variance analysis for repeated measures for the EEG-vigilance sub-stage analysis (A1, A2, A3, B1, B2/3) were calculated.

Results

Individual mean RT was significantly shorter for events following the high EEG-vigilance stage A compared to the lower EEG-vigilance stage B. The main effect of the sub-stage analysis was marginal significant. A trend of gradually increasing RT was observable within the EEG-vigilance stage A.

Conclusion

We conclude that an automatically classified low EEG-vigilance level is associated with an increased RT. Thus, intra-individual variances in cognitive test might be explainable in parts by the individual state of EEG-vigilance. Therefore, the accuracy of neuro-cognitive investigations might be improvable by simultaneously controlling for vigilance shifts using the EEG and VIGALL.

Brain and Body

The temporal dynamics of electroencephalogram (EEG)-vigilance as a measure of tonic cortical arousal are discussed as pathogenetic factors in neuropsychiatric disorders. Although there is broad knowledge about the interaction of cortical arousal and activity of the autonomous nervous system (ANS) during different sleep stages, the association and temporal interaction between fine-graded EEG-vigilance stages and markers of sympathetic and parasympathetic activity during the transition from wakefulness to sleep onset warrants more detailed exploration and was focus of the presented study. A 15-min resting-EEG, electrocardiogram (ECG), and skin conductance level (SCL) were recorded from 54 healthy subjects. Using an EEG-algorithm (VIGALL), 1-s segments were classified into seven different vigilance stages. Associations and temporal interactions between EEG-vigilance stages and heart rate variability (HRV), heart rate (HR), and SCL were computed using correlation analysis, regression analysis, and cross-correlations of EEG-vigilance and ANS time series. EEG-vigilance stages and ANS activity showed a significant association between increased HRV parameters including total and (normalized) very low frequency power and low vigilance stages. Regression analysis revealed significantly increased values of SCL and HR for high vigilance stages in comparison to lower ones. In these relationships, for SCL but not HR most of the covariance was explained by the effect of time. Phasic increases in EEG-vigilance were paralleled by significant increases of HR but not of SCL. Cross-correlations between EEG-vigilance and ANS time series yielded highest correlations when there was no or only a minimal temporal lag. ANS activity during the transition from wakefulness to sleep onset gradually changes along with different fine-graded EEG-vigilance stages. Associations between cortical and autonomic activity are better reflected by HR than by SCL.

Identifying robust and sensitive frequency bands for interrogating neural oscillations

Recent years have seen an explosion of interest in using neural oscillations to characterize the mechanisms supporting cognition and emotion. Oftentimes, oscillatory activity is indexed by mean power density in predefined frequency bands. Some investigators use broad bands originally defined by prominent surface features of the spectrum. Others rely on narrower bands originally defined by spectral factor analysis (SFA). Presently, the robustness and sensitivity of these competing band definitions remains unclear. Here, a Monte Carlo-based SFA strategy was used to decompose the tonic ("resting" or "spontaneous") electroencephalogram (EEG) into five bands: delta (1-5Hz), alpha-low (6-9Hz), alpha-high (10-11Hz), beta (12-19Hz), and gamma (>21Hz). This pattern was consistent across SFA methods, artifact correction/rejection procedures, scalp regions, and samples. Subsequent analyses revealed that SFA failed to deliver enhanced sensitivity; narrow alpha sub-bands proved no more sensitive than the classical broadband to individual differences in temperament or mean differences in task-induced activation. Other analyses suggested that residual ocular and muscular artifact was the dominant source of activity during quiescence in the delta and gamma bands. This was observed following threshold-based artifact rejection or independent component analysis (ICA)-based artifact correction, indicating that such procedures do not necessarily confer adequate protection. Collectively, these findings highlight the limitations of several commonly used EEG procedures and underscore the necessity of routinely performing exploratory data analyses, particularly data visualization, prior to hypothesis testing. They also suggest the potential benefits of using techniques other than SFA for interrogating high-dimensional EEG datasets in the frequency or time-frequency (event-related spectral perturbation, event-related synchronization/desynchronization) domains.

Quantitative analysis of the electroencephalogram during cranial electrotherapy stimulation

OBJECTIVE

Normal individuals were used to quantitate electroencephalographic (EEG) changes during concurrent administration of 0.5 and 100 Hz cranial electrotherapy stimulation (CES).

METHODS

Twelve normal, right-handed males were used in a randomized, double-blind crossover design study. A 3 amplifier system incorporating noise-cancellation was used to collect one channel of EEG (O1-Cz configuration) for 30 min. Either 0.5, 100 Hz, or sham CES treatment was administered for 20 min of each session. Statistical analyses were applied to time- and frequency-domain EEG variables.

RESULTS

Relative to sham control, 0.5 and 100 Hz CES caused the alpha band mean frequency to shift downward. Additionally, 100 Hz CES also caused a decrease of the alpha band median frequency and beta band power fraction.

CONCLUSIONS

Both 0.5 and 100 Hz CES provide frequency distribution shifts that suggest beneficial changes in mental state. However, compared to 0.5 Hz CES, 100 Hz CES effected a greater overall change. It is suggested that similar tests be performed on individuals with various behavioral and neurological disorders to determine if comparable EEG changes can be realized and correlated with beneficial effects of CES therapy.