Topographic analysis of engagement and disengagement of neural oscillators in photic driving: a combined electroencephalogram/magnetoencephalogram study.

OBJECTIVE: A coupled system of nonlinear neural oscillators with an individual resonance frequency is assumed to form the neuronal substrate for the photic driving phenomenon. The aim was to investigate the spatiotemporal stability of these oscillators and quantify the spatiotemporal process of engagement and disengagement of the neuronal oscillators in both multitrial and single-trial data. METHODS: White light-emitting diode flicker stimulation was used at 15 frequencies, which were set relative to the individual α frequency of each of the 10 healthy participants. Simultaneously, the electroencephalogram (EEG) and the magnetoencephalogram (MEG) were recorded. Subsequently, spatiotemporal matching pursuit (MP) algorithms were used to analyze the EEG and MEG topographies. RESULTS: Intraindividually similar topographies were found at stimulation frequencies close to (1) the individual α frequency and (2) half the individual α frequency in the multitrial and the single-trial cases. In both stimulation frequency ranges, the authors observed stable topographies 5 to 10 stimuli after the beginning of the stimulation and lasting three nonexisting periods after the end of the stimulation. This was interpreted as the engaging/disengaging effect of the observed oscillations, because especially the frequency parameter adopted before and after stable topographies were observed. Topographic entrainment was slightly more pronounced in MEG as compared with that in EEG. CONCLUSIONS: The results support the hypothesis of nonlinear information processing in human visual system, which can be described by nonlinear neural oscillators.

Quantification of compensatory processes of postnatal hypoxia in newborn piglets applying short-term nonlinear dynamics analysis.

BACKGROUND: Newborn mammals suffering from moderate hypoxia during or after birth are able to compensate a transitory lack of oxygen by adapting their vital functions. Exposure to hypoxia leads to an increase in the sympathetic tone causing cardio-respiratory response, peripheral vasoconstriction and vasodilatation in privileged organs like the heart and brain. However, there is only limited information available about the time and intensity changes of the underlying complex processes controlled by the autonomic nervous system. METHODS: In this study an animal model involving seven piglets was used to examine an induced state of circulatory redistribution caused by moderate oxygen deficit. In addition to the main focus on the complex dynamics occurring during sustained normocapnic hypoxia, the development of autonomic regulation after induced reoxygenation had been analysed. For this purpose, we first introduced a new algorithm to prove stationary conditions in short-term time series. Then we investigated a multitude of indices from heart rate and blood pressure variability and from bivariate interactions, also analysing respiration signals, to quantify the complexity of vegetative oscillations influenced by hypoxia. RESULTS: The results demonstrated that normocapnic hypoxia causes an initial increase in cardiovascular complexity and variability, which decreases during moderate hypoxia lasting one hour (p < 0.004). After reoxygenation, cardiovascular complexity parameters returned to pre-hypoxic values (p < 0.003), however not respiratory-related complexity parameters. CONCLUSIONS: In conclusion, indices from linear and nonlinear dynamics reflect considerable temporal changes of complexity in autonomous cardio-respiratory regulation due to normocapnic hypoxia shortly after birth. These findings might be suitable for non-invasive clinical monitoring of hypoxia-induced changes of autonomic regulation in newborn humans.

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.

Modeling brain resonance phenomena using a neural mass model.

Stimulation with rhythmic light flicker (photic driving) plays an important role in the diagnosis of schizophrenia, mood disorder, migraine, and epilepsy. In particular, the adjustment of spontaneous brain rhythms to the stimulus frequency (entrainment) is used to assess the functional flexibility of the brain. We aim to gain deeper understanding of the mechanisms underlying this technique and to predict the effects of stimulus frequency and intensity. For this purpose, a modified Jansen and Rit neural mass model (NMM) of a cortical circuit is used. This mean field model has been designed to strike a balance between mathematical simplicity and biological plausibility. We reproduced the entrainment phenomenon observed in EEG during a photic driving experiment. More generally, we demonstrate that such a single area model can already yield very complex dynamics, including chaos, for biologically plausible parameter ranges. We chart the entire parameter space by means of characteristic Lyapunov spectra and Kaplan-Yorke dimension as well as time series and power spectra. Rhythmic and chaotic brain states were found virtually next to each other, such that small parameter changes can give rise to switching from one to another. Strikingly, this characteristic pattern of unpredictability generated by the model was matched to the experimental data with reasonable accuracy. These findings confirm that the NMM is a useful model of brain dynamics during photic driving. In this context, it can be used to study the mechanisms of, for example, perception and epileptic seizure generation. In particular, it enabled us to make predictions regarding the stimulus amplitude in further experiments for improving the entrainment effect.

Nonlinear analysis and modeling of cortical activation and deactivation patterns in the immature fetal electrocorticogram.

An approach combining time-continuous nonlinear stability analysis and a parametric bispectral method was introduced to better describe cortical activation and deactivation patterns in the immature fetal electroencephalogram (EEG). Signal models and data-driven investigations were performed to find optimal parameters of the nonlinear methods and to confirm the occurrence of nonlinear sections in the fetal EEG. The resulting measures were applied to the in utero electrocorticogram (ECoG) of fetal sheep at 0.7 gestation when organized sleep states were not developed and compared to previous results at 0.9 gestation. Cycling of the nonlinear stability of the fetal ECoG occurred already at this early gestational age, suggesting the presence of premature sleep states. This was accompanied by cycling of the time-variant biamplitude which reflected ECoG synchronization effects during premature sleep states associated with nonrapid eye movement sleep later in gestation. Thus, the combined nonlinear and time-variant approach was able to provide important insights into the properties of the immature fetal ECoG.

Heart rate variability analysis allows early asphyxia detection in ovine fetus.

Fetal heart rate (FHR) monitoring is commonly used to predict asphyxia but clinical and experimental studies have questioned its diagnostic value. We examined the usefulness of fetal heart rate variability (fHRV) measures in detecting early asphyxia using chronically instrumented fetal sheep under normoxic (n = 6) and asphyxic conditions (3 umbilical cord occlusions, n = 6). The occlusions consistently led to pH decreases from 7.35 +/- 0.01 to 7.09 +/- 0.03 ( P < .05). FHR showed biphasic deceleration during each occlusion, associated with increasing arterial blood pressure ( P < .05). RMSSD, an index of vagal modulation of fHRV, increased consistently during repeated occlusion induced FHR decelerations ( P < .05). Under normoxic conditions, RMSSD did not change during FHR decelerations and decreased during FHR accelerations ( P < .05). Our results suggest that an increase of RMSSD in association with FHR decelerations reflects initial vagal activation during fetal asphyxia. RMSSD may accurately identify asphyxic fetuses early. Clinical validation is needed.

Coupled oscillators for modeling and analysis of EEG/MEG oscillations.

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).

Alpha entrainment in human electroencephalogram and magnetoencephalogram recordings.

Visual stimulation by repetitive flashes of light can lead to an entrainment of the alpha rhythm in electroencephalogram recordings (also called photic driving). We report a comparison of simultaneously recorded electric and magnetic data in a photic driving experiment, adapted to the individual alpha rhythm of 10 healthy volunteers. We show that there is a stronger frequency entrainment in magnetoencephalogram than in electroencephalogram recordings in all volunteers, which indicates a possible tangential brain activity underlying the dominant entrainment effect. The entrainment in the magnetoencephalogram lasts over significantly more frequencies and is most effective in the region around the individual alpha and a half alpha. For different channels, we found different degrees of entrainment showing topological and time-varying properties.

Detection of directed information flow in biosignals.

Several analysis techniques have been developed for time series to detect interactions in multidimensional dynamic systems. When analyzing biosignals generated by unknown dynamic systems, awareness of the different concepts upon which these analysis techniques are based, as well as the particular aspects the methods focus on, is a basic requirement for drawing reliable conclusions. For this purpose, we compare four different techniques for linear time series analysis. In general, these techniques detect the presence of interactions, as well as the directions of information flow, in a multidimensional system. We review the different conceptual properties of partial coherence, a Granger causality index, directed transfer function, and partial directed coherence. The performance of these tools is demonstrated by application to linear dynamic systems.

Analysis of time-variant quadratic phase couplings in the tracé alternant EEG by recursive estimation of 3rd-order time-frequency distributions.

The quantification of transient quadratic phase couplings (QPC) by means of time-variant bispectral analysis is a useful approach to explain several interrelations between signal components. A generalized recursive estimation approach for 3rd-order time-frequency distributions (3rd-order TFD) is introduced. Based on 3rd-order TFD, time-variant estimations of biamplitude (BA), bicoherence (BC) and phase bicoherence (PBC) can be derived. Different smoothing windows and local moment functions for an optimization of the estimation properties are investigated and compared. The methods are applied to signal simulations and EEG signals, and it can be shown that the new time-variant bispectral analysis results in a reliable quantification of QPC in the tracé alternant EEG of healthy neonates.

Time-variant analysis of nonlinear stability and bispectral measures to quantify the development of fetal sleep states.

A combined time-variant analysis of nonlinear stability and parametric bispectral measures was applied to the in utero electrocorticogram (ECoG) of fetal sheep between 0.7 and 0.9 gestation to examine the maturation of sleep states and synchronization patterns of the ECoG. Cycling of the nonlinear stability of the fetal ECoG occurred already at 0.7 gestation and suggests the presence of premature sleep states. This was accompanied by cycling of the time-variant biamplitude which reflected ECoG synchronization effects during premature NREM sleep. Maturation of NREM sleep begun at 0.78 gestation and preceded that of REM sleep that begun at 0.85 gestation. Our results suggest that maturation of brain stem and thalamic function precedes that of cortical function.

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.