EEG Frequency and Phase Coupling during Human Information Processing

Neuronal activity during information processing is represented by oscillations within local or widespread neuronal networks. These oscillations may be recorded by the EEG (electroencephalogram). The oscillatory interaction between neuronal ensembles may be at one single frequency or at different frequencies due to non-linear coupling. The investigation of momentary coherence and phase enables the examination of synchronized oscillatory network activity during fast-changing cognitive processes. On this basis information transfer from occipital areas towards frontal areas could be described during processing of visual presented words. Non-linear phase coupling between oscillations with different frequencies during memory processing was detected by means of cross-bicoherence.

Phase synchronization between theta and upper alpha oscillations in a working memory task

Motivated by findings that theta and upper alpha oscillations respond selectively to different types of memory demands, we investigated the role of phase synchronization in a memory scanning task. During retention, we found a load dependent increase in upper alpha power at O2 and P4 and a significant upper alpha:theta phase synchronization between right posterior, central and left anterior sites. During retrieval, a load dependent increase in upper alpha phase locking was observed at O2 and an increase in upper alpha:theta phase synchronization between right posterior and left anterior sites. We suggest that theta reflects central executive functions whereas upper alpha may be important for the reactivation of long-term memory codes in short-term memory. The interplay between theta and upper alpha may be reflected by phase synchronization between these frequencies.

[Time variant bispectral analysis based on adaptive recursive Fourier transformation]

An appropriate investigation of quadratic phase couplings (QPC) in non-stationary signals requires time-variant methods of bispectral analysis. A new approach for time-variant estimation of power spectrum and bispectrum based on an adaptively, recursively estimated Fourier transform (ADFT) is presented in this paper. A reduced calculation effort and the possibility of the calculation of the bispectrum for selected frequency triples are important advantages of this method. Because of the recursive calculation, the ADFT is convenient for analysing ongoing signals. This will be demonstrated for simulated and real biomedical signals.

[Brief causal relations in EEG based on adaptive Granger causality]

Commonly, coherence and correlation are used to describe interrelations between EEG signals. But, on this basis, the investigation of causality or direction of interrelations is not possible. The general idea of causality between two signals may be expressed in terms of upgrading the predictability of one signal bye the knowledge of the past of the other signal. The best established approach in this context is the so-called Granger causality. The study present an adaptive estimation of Granger causality, which allows to detect dynamic causal relations within time intervals of less 100 ms. The time-variant Granger causality is applied to EEG data of the Stroop task. It could be shown, that conflict situation generates a dense web of directed interactions from posterior to anterior cortical areas.

Frequency characteristics of evoked and oscillatory electroencephalic activity in a human memory scanning task

Research on memory scanning tasks indicates that oscillatory activity increases with load during retention, whereas evoked power (EP, comprising the P3) decreases during retrieval. We investigate the question, whether both phenomena are primarily related to theta oscillations. However, we found that during retention alpha oscillations increased with load and that exactly this frequency exhibits increased phase locking - measured by a specially developed phase locking index (PLI) - during retrieval. The decreased P3 amplitude was related to decreased delta EP and PLI. The P3 coincides with the last of three evoked alpha peaks. Thus, alpha may be important for the timing of the scanning and the evaluation of the read out process that most likely is manifested by the P3.

Phase-coupling of theta-gamma EEG rhythms during short-term memory processing

Because of the importance of oscillations as a general phenomenon of neuronal activity the use of EEG spectral analysis is among the most important approaches for studying human information processing. Usually, oscillations at different frequencies occur simultaneously during information processing. Thus, the question for synchronisation of different frequencies by phase coupling and its possible functional significance is of primary importance. An answer may be given by bispectral analysis. Estimation of the (cross-) bispectrum allows to identify synchronised frequencies and possibly, the existence of non-linear phase coupling of different oscillators. Previous studies have demonstrated the simultaneous occurrence of slow (4-7 Hz) and fast (20-30 Hz) oscillations at frontal and prefrontal electrode positions during memory processing. However, interrelations between these rhythms have not been investigated up to now. In order to test short-term memory, the Sternberg task with random figures and number words was carried out on 10 female subjects. During the task EEG was recorded. Power and bispectral analyses from frontal, prefrontal and frontopolar regions were performed off-line. Increased power was found in both the theta and the gamma bands. Strong phase-coupling between theta at Fz and gamma at F3 and at Fp1, respectively, was shown for memorising number words by means of cross-bicoherence. A possible reason for this is an amplitude modulation of gamma frequencies by slow oscillations. The correspondent coherence analysis between the envelope of gamma frequencies at Fp1 and the raw EEG at Fz supports this presumption. This finding is interpreted as an EEG aspect of the functional linking between the prefrontal areas and the G.cinguli (as part of the limbic system), which are both extremely important for memory functions.

Time-variant non-linear phase-coupling analysis of EEG burst patterns in sedated patients during electroencephalic burst suppression period

OBJECTIVES

The quadratic phase-coupling (QPC) within burst patterns during electroencephalic burst suppression has been quantified.

METHODS

It can be shown that a QPC exists between the frequency ranges 0-2.5 and 3-7.5 Hz and between the frequency ranges 0-2.5 and 8-12 Hz. By means of time-variant bicoherence analysis, a strong phase-locking between the modulating and the modulated component can be identified. The phase-locking is demonstrable within the first 250 ms after the burst onset and comes up to the maximum between 750 and 1250 ms.

RESULTS

The effect is maintained over the whole first part of the burst (2 s) with a decreasing tendency after 1250 ms. All these effects cannot be found in the EEG before entering the burst suppression period (BSP). The transient coupling phenomena in the EEG bursts during BSP can be regarded as indicators for short-term interrelations between the underlying electrophysiologic processes.

CONCLUSIONS

It can be suggested that the method introduced for the quantification of the sedation depth should be used.

Multiplicity in the high-frequency signals during the short-latency somatosensory evoked cortical activity in humans

OBJECTIVE

Recent studies using electroencephalography or magnetoencephalography have shown that peripheral nerve stimulations produce short-latency high-frequency signals in the human somatosensory cortex. The present study tested whether they consist of more than one distinct type of signal.

METHODS

Somatic evoked magnetic fields (SEFs) elicited by electrical stimulation of the median nerve were measured in 12 healthy volunteers. They were analyzed using a time-frequency analysis method based on Gabor filters and another based on autoregressive moving average, and also with bispectrum and bicoherence techniques and a new dispersion curve method.

RESULTS

Signals in two separate high-frequency bands (200 and 600 Hz) were distinguished from the main signal in the low frequency (LF) range during the time period of N20m and P25m. The novel 200 Hz-band signal was seen reliably in those channels where the LF band signal was weak, so that the former was not masked by the latter. The 600 Hz signal consisted of two distinct components or parts (p1 and p2) in 10 out of 12 subjects, one peaking during ascending slope and the second during the descending slope of the N20m. The latency of the p1 was shorter than the latencies of the 200 Hz and LF signals according to the dispersion curve analysis. The inter-peak interval of p1 became shorter for later peaks in all 12 subjects. Bicoherence analysis revealed a significant phase coupling between the 200 and 600 Hz bands.

CONCLUSIONS

There are three distinct types of signal during the time period of the short-latency cortical components of the SEF -- LF which gives rise to the commonly seen waveform of the SEF, the newly found 200 Hz signal and the 600 Hz signal which consists of two components. The possible origins of the high frequency signals are discussed in light of the new set of evidence found in the present study.

EEG frequency and phase coupling during human information processing

Neuronal activity during information processing is represented by oscillations within local or widespread neuronal networks. These oscillations may be recorded by the EEG (electroencephalogram). The oscillatory interaction between neuronal ensembles may be at one single frequency or at different frequencies due to non-linear coupling. The investigation of momentary coherence and phase enables the examination of synchronized oscillatory network activity during fast-changing cognitive processes. On this basis information transfer from occipital areas towards frontal areas could be described during processing of visual presented words. Non-linear phase coupling between oscillations with different frequencies during memory processing was detected by means of cross-bicoherence.

Technique for the quantification of transient quadratic phase couplings between heart rate components

A technique for the time-variant analysis of quadratic phase coupling (QPC) in heart rate data is introduced and tested in 6 human neonates during quiet sleep. The set up of the approach is based up on the assumption that QPCs in the heart rate variability (HRV) are related to amplitude modulation effects. The application of the biamplitude deals with the detection of the coupling pattern and the bicoherence is used for the statistical quantification of coupling. By means of the results of bispectral analysis the time-variant processing has been adapted. The frequency-selective complex demodulation of the HRV leads to the envelope of the respiratory sinus arrhythmia (RSA), this has been used as one input for a time-variant coherence analysis. The other input is the low-pass filtered 10-second-rhythm of the HRV. A time-continuous quantification of the QPC, caused by amplitude modulation (10-second-rhythm modulates the RSA), is possible using this approach. According to our observed results in neonatal HRV both a phase co-ordination between the 10-second-rhythm and RSA as well as a non-linear coupling (amplitude modulation) between these HRV components can be seen.

Instantaneous multivariate EEG coherence analysis by means of adaptive high-dimensional autoregressive models

This study presents an efficient algorithm for the fitting of multivariate autoregressive models (MVAR) with time-dependent parameters to multidimensional signals. Thereby, the dimension of the model may be chosen to equal the number of signal channels. The autoregressive (AR) parameter matrices are estimated by an extension of the recursive least squares (RLS) algorithm with forgetting factor. The estimation procedure includes a single trial as well as an ensemble mean approach. The latter approach allows the simultaneous fit of one mean MVAR model to a set of single trials, each of them representing the measurement of the same task. A particular advantage of this ensemble mean approach is that it requires only a low computation effort in comparison to well known procedures applied to single trials. Furthermore, the ensemble mean approach is linked with a high adaptation capability. The properties of the estimator are investigated using simulated time series. It can be demonstrated that the adaptation capability of the estimation (measured by its adaptation speed and variance) does not depend on the model dimension. The mean MVAR fit is applied to 19-dimensional EEG data, recorded during an elementary comparison procedure. The calculation of ordinary and multiple coherence is discussed. The sensitivity of the multiple instantaneous EEG coherence will be demonstrated.

Quantification of transient quadratic phase couplings within EEG burst patterns in sedated patients during electroencephalic burst-suppression period

The time dynamics of the quadratic phase coupling within burst patterns during electroencephalic burst-suppression has been quantified. It can be shown that a transient quadratic phase coupling (QPC) exists between the frequency ranges 0 to 2.5 and 3 to 7.5 Hz and between the frequency ranges 0 to 2.5 and 8 to 12 Hz. The QPC can be explained by an amplitude modulation, where the slow rhythm modulates the rhythmic activities with a higher frequency. By means of time-variant bicoherence analysis, a strong phase-locking between the modulating and the modulated component can be identified. The phase-locking is demonstrable within the first 250 ms after the burst onset and comes up to the maximum between 750 and 1250 ms. The effect is maintained over the whole first part of the burst (2 s) with a decreasing tendency after 1250 ms. All these effects cannot be found in the EEG before entering the burst suppression period (BSP). The transient coupling phenomena in the EEG bursts during BSP can be regarded as indicators for short-term interrelations between the underlying electrophysiologic processes.

Early magnetic field changes preceding the intracortical penicillin induced spikes

Events preceding interictal activity were studied using a combination of magnetoencephalography (MEG), electrocorticography (ECoG), and intracortical field potential recordings in rabbits. We measured MEG signals simultaneously with ECoG before and during interictal discharges induced by penicillin injected in the cortex (group 1: n = 12, medial cortex, regio retrosplenialis granularis; group 2: n = 4, cortical convexity, regio retrosplenialis agranularis; control group: n = 5); in group 3 (n = 12) a 16-channel depth electrode array was used to calculate the current source density in the cortical area exhibiting interictal epileptiform discharges. The modified Z-parameter as a lumped measure of magnetic field pattern changes and the global field power as a lumped measure of changes of field amplitude differences were calculated. In almost all recordings of both group 1 and 2, the Z-parameter of intra-individual MEG data became significantly larger than the control condition before the earliest change of the interictal spike recorded at the penicillin injection site (20-310 ms earlier, median: 91 ms, n = 151). The increase in Z-parameter in averaged MEG data of group 1 was significantly correlated with time as early as 790 ms before the spike (Pearson correlation coefficient, P < 0.05). After the start of the early increase of the Z-parameter, the global field power also began to increase before the ECoG spike. These results suggest a prespike field recruitment nearly 1 s before an interictal spike.

Adaptive phase estimation and its application in EEG analysis of word processing

Oscillations are a general phenomenon of neuronal activity during information processing. Mostly, widespread networks are involved in brain functioning. In order to investigate network activity coherence analysis turned out to be a useful tool for examining the functional relationship between different cortical areas. This parameter allows the investigation of synchronisation phenomena with regard to defined frequencies or frequency bands. Coherence and cross phase are closely connected spectral parameters. Coherence may be understood as a measure of phase stability. Whereas coherence describes the amount of information transfer, the corresponding phase, from which time delays can be computed, hints at the direction of information transfer. Mental processes can be very brief and coupling between different areas may be highly dynamic. For this reason a two-dimensional approach of adaptive filtering was developed to estimate coherence and phase continuously in time. Statistical and dynamic properties of instantaneous phase are discussed. In order to demonstrate the value of this method for studying higher cognitive processes the method was applied to EEG recorded during word processing. During visual presentation of abstract nouns an information transfer from visual areas to frontal association areas in the Alpha1 frequency band could be verified within the first 400 ms. The Alpha1 band predominately seems to reflect sensory processing and attentional processes. In addition to conventional coherence analyses during word processing phase estimations may yield valuable new insights into the physiological mechanisms during word processing.

Instantaneous EEG coherence analysis during the Stroop task

OBJECTIVE

In the present study the Stroop effect is analyzed by means of EEG coherence analysis in addition to traditional analysis of behavioral data (reaction time) and ERP analysis. Data from 10 normal subjects are examined.

METHODS

In particular, a special dynamic approach for a continuous coherence estimation is applied to investigate the procedural evolution of functional cortical relationships during the Stroop task.

RESULTS

The frequency band of 13-20 Hz is found to be sensitive to the discrimination between the congruent and the incongruent task conditions on the basis of instantaneous coherence analysis. The magnitude of coherence values within the time interval of late potentials and the maximal coherence values are used to assess the strength of interaction between distinct areas of the cortex. Higher coherences are observed within the left frontal and left parietal areas, as well as between them for the incongruent situation in comparison with the congruent situation. Furthermore, the time-points of maximal coherence allows a procedural discrimination between both situations. The peak synchrony described by the time-points of maximal coherence correlates strongly with the reaction times mainly within the frontal area and between fronto-parietal areas in the incongruent case, whereas this correlation is restricted to the right hemisphere in the congruent case.

The sensitivity of instantaneous coherence for considering elementary comparison processing. Part I: The relationship between mental activities and instantaneous EEG coherence

In this study the sensitivity of instantaneous EEG coherence for the description of the processual evolution of thinking processes is investigated. The adaptive estimation approach presented allows the calculation of the coherence function with high time and frequency resolution. On this basis the detection of time intervals with high synchronization phenomena is possible. The strength of coupling between different EEG channels may therefore be measured even for very short mental activities. The inclusion of the time component enables the calculation of very sensitive coherence parameters, such as the maximal coherence value or the length of time intervals with high synchronization during information processing. Based on these dynamic examinations, conceptual and imaginal representations are distinguishable for elementary cognitive processes.

The sensitivity of instantaneous coherence for considering elementary comparison processing. Part II: Similarities and differences between EEG and MEG coherences

The EEG (electroencephalogram) coherence depends on EEG deviation type. A high level of sensitivity of instantaneous coherence for investigating elementary cognitive tasks could be shown in the case of unipolar reference (ear lobe reference). In order to validate of this result the same investigations were performed for MEG (magnetoencephalogram) coherence, where EEG and MEG were measured simultaneously. A strong correlation between time intervals with high EEG and MEG coherence could be shown. The equivalence of the sensitivity of EEG and MEG coherence for the description of the dynamic behaviour of information processing and the distinction between different elementary cognitive tasks is proven statistically.

Concept activation and coordination of activation procedure require two different networks

In the present study, we used EEG-coherence analysis to assess general regional changes in neuronal activity related to semantic retrieval, testing the hypothesis that concept activation and coordination procedures are neurobiologically distinguishable. Four subjects had to decide whether or not a capital letter and a lower case letter have the identical name (e.g. Aa). This task requires two mental procedures: (i) the activation of concepts and (ii) their coordination, particularly when the interstimulus interval is shorter than the duration of concept activation. This memory retrieval of a concept appears to be subserved by two distinct networks: the left parietotemporal region for concept activation and the prefrontal region for coordination.

Analysis of the interrelations between a low-frequency and a high-frequency signal component in human neonatal EEG during quiet sleep

It can be shown that dominant rhythmic signal components of neonatal EEG burst patterns (discontinuous EEG in quiet sleep) are characterised by a quadratic phase coupling (bispectral analysis). A so-called 'initial wave' (narrow band rhythm within a frequency range of 3-12 Hz) can be demonstrated within the first part of the burst pattern. The detection of this signal component and of the phase coupling is more successful in the frontal region. By means of amplitude demodulation of the 'initial wave' and a subsequent coherence analysis the phase coupling can be attributed to an amplitude modulation, i.e. the envelope curve of the 'initial wave' shows for a distinct period of time the same qualitative course as the signal trace of a 'lower' frequency component (0.75-3 Hz). The results were derived from six neonates (20 burst patterns for each neonate; 8 channel recordings).

Dynamic power and coherence analysis of ultra short-term cognitive processes--a methodical study

This EEG mapping study was designed to explore ultra short-term cognitive processes in human thinking. The EEG was recorded while the subjects performed two tasks randomly mixed in time: category concept activation and pattern comparison. A novel approach is introduced to examine these tasks by means of band powers and coherence with high time and frequency resolution. This approach is based on general adaptive principles and the adaptive fit of a bivariate linear model (ARMA model) with time varying parameters, and allows the estimation of band powers and coherences continuously in time. The application of mapping to these spectral parameter functions results in map sequences of band powers, and local band coherences. It was proved that these map sequences of the frequency band 13-20Hz reflect the dynamic behaviour of information processing in a characteristic topographical manner. Based on these dynamic topographical examinations, conceptual and imaginal representations are distinguishable.

[Adaptive procedures for measuring arterial blood flow velocity in retinal vessels using indicator technique]

There are highly significant differences in the measuring results of arterial blood velocity between the indicator and laser-Doppler techniques (up to 800%). A new measuring procedure for the analysis of indicator dilution curves was developed based on indicator model and experimental results. The use of this new measuring procedure results in reduced mean systematic error between the indicator and laser-Doppler techniques to values around 10%. With the introduction of adaptive measuring arrays for the creation of indicator dilution curves and the application of adaptive algorithms for centering and spectral normalizing of the dilution curves, improved reproducibility can be expected.

Methods of dynamic spectral analysis by self-exciting autoregressive moving average models and their application to analysing biosignals

Dynamic methods in the spectral domain are necessary to analyse biological signals because of the frequently nonstationary character of the signals. The paper presents an adaptive procedure of fitting time-dependent ARMA models to nonstationary signals, which is suitable for on-line calculations. The properties of the model parameter estimations are examined, and in the stationary case are compared with the results of convergent estimation methods. On this basis time-varying spectral parameters with high temporal and spectral resolution are calculated, and the possibility of their application is shown in EEG analysis and laser-Doppler-flowmetry.

Dynamic description of stochastic signal by adaptive momentary power and momentary frequency estimation and its application in analysis of biological signals

The importance of dynamic spectral analysis of time-varying signals in medicine, biology and technology is increasing rapidly. The basic spectral parameters are momentary power and momentary frequency. The paper presents adaptive recursive estimation methods for these spectral parameters. Their specific properties are investigated, and the possibilities of applications in computer-assisted analysis of biological and technical signals are demonstrated, even satisfying real-time requirements.

[Adaptative procedures for pre-processing of evoked potentials]

The investigation of evoked potentials requires suitable consideration of physiological and pathophysiological characteristics of spontaneous and evoked electrical activity of the brain. For this purpose a preprocessing strategy based on adaptive recursive estimation of statistical parameters was developed. In this way, artifact handling, classification, filtering and further preprocessing of spontaneous EEG and evoked potentials can be improved.