Peter Putsche

New Approaches for the Detection and Analysis of Electroencephalographic Burst-Suppression Patterns in Patients under Sedation

An automatic EEG pattern detection unit was developed and tested for the recognition of burst-suppression periods and for the separation of burst from suppression patterns. The median, standard deviation and the 95% edge frequency were computed from single channels of the EEG within a moving window and completed by the continuous computation of frequency band power via an adapted Hilbert resonance filter. These parameters were given to the inputs of two hierarchically arranged artificial neural networks (NNs). The output signals of NNs indicate the suppression and burst phases. The burst recognition was focused on the precise recognition of the burst onset. In subsequent processing steps the time course of percentages of burst patterns within their corresponding burst-suppression-phases was calculated and the time locations of burst onsets can be used to trigger an averaging for a burst-related analysis. The data for our investigations were derived from the routine EEG derivations of 12 patients with various neurosurgical diseases. A group-related training of the NNs was realized. For the group-related trained NNs EEG data for 6 patients were used for training and the data of 6 other patients for testing the classification performance of the pattern recognition units. Additionally, the reliability of the detection algorithm was tested with data of two patients with convulsive state, resistant to treatment, and burst-suppression like pattern EEG.

Interrelations between EEG frequency components in sedated intensive care patients during burst-suppression period

The EEG during basic sedation and burst patterns during electroencephalic burst-suppression patterns (BSP) were analyzed. The aim of EEG analysis was the characterization and quantification of the interrelations between distinct frequency components in both states of sedation. The data for the investigations were derived from the routine EEG derivations of 12 patients with various neurosurgical diseases. It can be demonstrated that the degree of interrelation (amplitude modulation) between a low-frequency component (0-2.5 Hz) and oscillations with higher frequency (3-7.5 and 8-12 Hz) is increased in burst patterns during BSP compared with the EEG during basic sedation. It can be concluded that the degree of interrelations depends on the sedation depth induced by hypnotic drugs.

On the rhythmicity of quadratic phase coupling in the tracé alternant EEG in healthy neonates

The time-variant quadratic phase coupling (QPC) in trace alternant (TA) EEG patterns in healthy full-term neonates (quiet sleep) was investigated by means of time-variant bispectral analysis. The frequency plain 1-1.5 Hz <=> 3.5-4.5 Hz was used as the region-of-interest. QPC rhythms with a frequency of approximately 0.1 Hz were found in all neonates (n = 6). It can be demonstrated that the QPC rhythm of the TA is generated by a pattern-spanning time-variant phase-locking process characterising early functional interactions in the immature brain.

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.

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.

Coupled oscillators for modeling and analysis of EEG/MEG oscillations

Abstract This study presents three EEG/MEG applications in which the modeling of oscillatory signal components offers complementary analysis and an improved explanation of the underlying generator structures. Coupled oscillator networks were used for modeling. Parameters of the corresponding ordinary coupled differential equation (ODE) system are identified using EEG/MEG data and the resulting solution yields the modeled signals. This model-related analysis strategy provides information about the coupling quantity and quality between signal components (example 1, neonatal EEG during quiet sleep), allows identification of the possible contribution of hidden generator structures (example 2, 600-Hz MEG oscillations in somatosensory evoked magnetic fields), and can explain complex signal characteristics such as amplitude-frequency coupling and frequency entrainment (example 3, EEG burst patterns in sedated patients).

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 realtime requirements.

Dynamics of directed interactions between brain regions during interburst-burst EEG patterns in quiet sleep of full-term neonates

The study investigates time-variant directed interactions between brain regions during the interburst-burst EEG pattern (tracé alternant) characteristic of quiet sleep in healthy neonates. The transition from interburst to burst is of particular interest as the generation of the EEG characteristics at burst onset reflects timing and time-variant interplay between the cortical and the thalamo-cortical brain structures. To study the dynamics of the interactions, time-variant partial directed coherence (PDC), a measure of effective connectivity, was used which allows analysis in the time-frequency range. The main results of the grand mean PDC analysis are: (1) PDC time-frequency patterns are frequently associated with phase-locked oscillations. (2) Interhemispheric interactions are dominant between frontal, central and occipital electrodes and intrahemispheric interactions are much less substantial. (3) An interaction breakdown for the frequency ranges 1-4 Hz (Fp(1) ⇒ Fp(2)) and 0.5-3 Hz (Fp(2) ⇒ Fp(1)) exists which lasts about 2.5s and which is located at about burst onset. (4) Strong interactions in the high-frequency range 3.5-4.5 Hz between the frontal electrodes can be observed for both directions at the burst onset. It can be concluded that the evolution of strong interactions in the high-frequency range, which starts shortly before or at the burst onset from frontal regions to anteroposterior directions as well as the frontal interhemispheric interactions, are associated with the burst onset generation. Additionally, the collapsing of the interactions before burst onset and after the burst are indicative of neuronal reorganisation processes.

A Time-Variant Processing Approach for the Analysis of Alpha and Gamma MEG Oscillations During Flicker Stimulus Generated Entrainment

Repetitive flicker stimulation (photic driving) offers the possibility to study the properties and coupling characteristics of stimulation-sensitive neuronal oscillators by means of the MEG/EEG analysis. With flicker frequencies in the region of the individual alpha band frequency, the dynamics of the entrainment process of the alpha oscillation, as well as the dynamics of the accompanying gamma oscillations and the coupling between the oscillations, are investigated by means of an appropriate combination of time-variant analysis methods. The Hilbert and the Gabor transformation reveal time-variant properties (frequency entrainment, phase locking, and n:m synchronization) of the entrainment process in the whole frequency range. Additionally, time-variant partial directed coherence is applied to identify ocular saccadic interferences and to study the directed information transfer between the recording sites of the simultaneously derived MEG/EEG data during the entrainment. The MEG data is the focus of this methodological study as the entrainment effects of the alpha oscillation are stronger in MEG than in the EEG. The occipital brain region (visual cortex) was mainly investigated and the dynamics of the alpha entrainment quantified. It can be shown that at the beginning of this entrainment, a transient, strongly phase-locked “40-Hz” gamma oscillation occurs.

A processing scheme for time-variant phase analysis in EEG burst activity of premature and full-term newborns in quiet sleep: a methodological study.

Abstract A processing scheme for the investigation of neonatal electroencephalographic burst oscillations that is composed of time-variant methods for linear and nonlinear phase analysis is introduced. Starting from a time-frequency analysis of oscillations’ amplitudes, time-variant approaches for quantification of phase locking, n:m phase synchronization, and quadratic phase coupling are applied. Tracé discontinue patterns from premature newborns and tracé alternant patterns from full-term newborns were investigated using bipolar EEG recordings. Maturation-related differences between the burst generation mechanisms can be shown, which are reflected in group-specific patterns of augmentation, timing, and grouping of time-varying phase characteristics of the EEG burst oscillations. We demonstrate for both groups (premature and full-term newborns) that phase-locked low-frequency oscillations are pronounced in the frequency range of 0.5–1.5 Hz. Phase-locked oscillations also occur in a frequency range of >3 Hz. The amplitude of a phase-locked 2-Hz oscillation is higher in full-term than in premature newborns. After onset, n:m synchronization and an increase in bicoherence occur earlier in the premature group (between 0.5–1.5 Hz and 3.0–6.0 Hz). It can be suggested that during the maturation process, the driving force of thalamic structures decreases and that cortical activity plays an increasingly important role in the process of burst generation.