Nonstationary time-series analysis applied to investigation of brainstem system dynamics

Directional Couplings Between Electroencephalogram and Interbeat Intervals Signals in Awake State and Different Stages of Sleep

Purpose of the work is to identify the directional coupling between the structures of the brain and the autonomic control of the heart rate variability, to analyze the changes in these coupling in sleep and in wakefulness. Infra-slow oscillations of the electroencephalograms potential and low-frequency components (0.04-0.15 Hz) of the interbeat intervals signal where analyzed using a sensitive method for identifying the directional coupling. The technique, based on modeling the dynamics of instantaneous phases of oscillations, made it possible to reveal the presence and quantify the directional couplings between the structures of the brain and the autonomic control of the heart rate variability. It was shown that the coupling coefficients in the frequency band of 0.04-0.15 Hz (associated mainly with sympathetic control of blood circulation), on average, decrease with falling asleep. We have also shown the asymmetry of coupling. At the same time, stronger connections were revealed in the direction from the autonomic control of the heart rate variability to the brain structures than in the opposite direction. It has been shown that the strength of such couplings decreases with increasing of sleep depth.

Synchronization of infra-slow oscillations of brain potentials with respiration

We study the synchronization of infra-slow oscillations in human scalp electroencephalogram signal with the respiratory signal. For the cases of paced respiration with a fixed frequency and linearly increasing frequency, we reveal the phase and frequency locking of infra-slow oscillations of brain potentials by respiration. It is shown that for different brain areas, the infra-slow oscillations and respiration can exhibit synchronous regimes of different orders.

Investigating neuromagnetic brain responses against chromatic flickering stimuli by wavelet entropies

BACKGROUND

Photosensitive epilepsy is a type of reflexive epilepsy triggered by various visual stimuli including colourful ones. Despite the ubiquitous presence of colorful displays, brain responses against different colour combinations are not properly studied.

METHODOLOGY/PRINCIPAL FINDINGS

Here, we studied the photosensitivity of the human brain against three types of chromatic flickering stimuli by recording neuromagnetic brain responses (magnetoencephalogram, MEG) from nine adult controls, an unmedicated patient, a medicated patient, and two controls age-matched with patients. Dynamical complexities of MEG signals were investigated by a family of wavelet entropies. Wavelet entropy is a newly proposed measure to characterize large scale brain responses, which quantifies the degree of order/disorder associated with a multi-frequency signal response. In particular, we found that as compared to the unmedicated patient, controls showed significantly larger wavelet entropy values. We also found that Renyi entropy is the most powerful feature for the participant classification. Finally, we also demonstrated the effect of combinational chromatic sensitivity on the underlying order/disorder in MEG signals.

CONCLUSIONS/SIGNIFICANCE

Our results suggest that when perturbed by potentially epileptic-triggering stimulus, healthy human brain manages to maintain a non-deterministic, possibly nonlinear state, with high degree of disorder, but an epileptic brain represents a highly ordered state which making it prone to hyper-excitation. Further, certain colour combination was found to be more threatening than other combinations.

Nonlinear properties of vagal and sympathetic modulations of heart rate variability in ovine fetus near term

Fetal heart rate (FHR) monitoring is commonly used although clinical studies questioned its diagnostic value. Sophisticated FHR variability (fHRV) measures such as fHRV complexity may improve the sensitivity and specificity of FHR monitoring. A more detailed understanding of the physiology underlying fHRV complexity is essential to harness its use for monitoring fetal health. To examine the specific effects of vagal and sympathetic modulations on fHRV complexity, we blocked vagal activity with atropine and sympathetic activity with propranolol in near-term fetal sheep ( n = 7, 0.85 gestation). Under these conditions, we analyzed the linear and nonlinear parts of fHRV complexity from autonomic information flow. Overall fHRV complexity decreased with both drugs compared with nonrapid eye movement sleep baseline ( P < 0.05). With atropine, this was because of a decrease of the linear part of fHRV complexity on the long-term time scale ( P < 0.05), suggesting that vagal modulation of fHRV is adequately described by linear fHRV measures. With propranolol, the nonlinear part of fHRV complexity decreased on the short-term time scale ( P < 0.05), suggesting that sympathetic influences on fHRV can be detected by the nonlinear part of fHRV complexity. Thus the complex interplay of vagal and sympathetic modulations of fHRV is reflected differently and specifically in the linear and nonlinear properties of fHRV complexity, and on different time scales. Analysis of linear and nonlinear properties of fHRV may improve sensitivity and specificity of FHR monitoring.

Autonomic organization of respirocardial function in healthy human neonates in quiet and active sleep

BACKGROUND AND AIM

It is not known on which time scales the nonlinear respirocardial interactions occur. This work's aim is to quantitatively assess functional respirocardial organization during quiet and active sleep of healthy full-term neonates by autonomic information flow (AIF) without limitation on specific time scales. Representing respirocardial interactions on a global time scale AIF carries information on a wider scope of interdependencies than known linear and nonlinear measures described. It assesses the complexity of heart rate fluctuations (HRF) and respiratory movements (RM) and their interaction comprising both linear and nonlinear properties. Thus, we hypothesized AIF to characterize novel aspects of sleep state-dependent respirocardial interaction.

METHODS

RM and ECG-derived HRF of six healthy full-term neonates were studied. We analyzed their power spectra, coherence, auto- and cross-correlation and complexity estimated on local ("next sample" prediction) and global time scales (an integral over AIF predicting for all time lags in HRF and RM).

RESULTS

We found the global AIF of HRF and RM to differ significantly between active and quiet sleep in all neonates, whereas on a local time scale this applied to the HRF AIF only. HRF complexity was larger in quiet than in active sleep. Respirocardial interaction was less complex in quiet versus active sleep in the high frequency band only.

CONCLUSION

Complex sleep state-related changes of respirocardial interdependencies cannot be identified completely on the local time scale. Considering the global time scale of respirocardial interactions allows a more complete physiological interpretation with regard to the underlying autonomic dynamics.

Cardiorespiratory effects induced by vagus nerve stimulation in epileptic children

Vagus nerve stimulation (VNS) is used in pharmaco-resistant epilepsy to decrease the number of seizures. Although it is well known that VNS affects respiration, there are only a few reports concerning an effect of VNS on heart rate or heart rate variability (HRV). We investigated the relationship between respiratory frequency and the high frequency (HF) domain of the discrete Fourier transform (DFT) of the RR interval function during night sleep recordings of ten subjects treated with VNS. Our results show that VNS shifts the frequency of maximal power spectrum density (PSD) in the HF-band, decreases the related PSD and induces a partial cardiorespiratory decoupling.

Cardiovascular rhythms in the 0.15-Hz band: common origin of identical phenomena in man and dog in the reticular formation of the brain stem?

Selected examples from experiments in humans and dogs with time series of reticular neurons, respiration, arterial blood pressure and cutaneous forehead blood content fluctuations were analysed using multiscaled time-frequency distribution, post-event-scan and pointwise transinformation. We found in both experiments a "0.15-Hz rhythm" exhibiting periods of spindle waves (increasing and decreasing amplitudes), phase synchronized with respiration at 1:2 and 1:1 integer number ratios. At times of wave-epochs and n:m phase synchronization, the 0.15-Hz rhythm appeared in heart rate and arterial blood pressure. As phase synchronization of the 0.15-Hz rhythm with respiration was established at a 1:1 integer number ratio, all cardiovascular-respiratory oscillations were synchronized at 0.15 Hz. Analysis of a canine experiment supplied evidence that the emergence of the 0.15-Hz rhythm and n:m phase synchronization appears to result from a decline in the level of the general activity of the organism associated with a decline in the level of activity of reticular neurons in the lower brainstem network. These findings corroborate the notion of the 0.15-Hz rhythm as a marker of the "trophotropic mode of operation" first introduced by W.R. Hess.

The control of seizure-like activity in the rat hippocampal slice

The sudden and transient hypersynchrony of neuronal firing that characterizes epileptic seizures can be considered as the transitory stabilization of metastable states present within the dynamical repertoire of a neuronal network. Using an in vitro model of recurrent spontaneous seizures in the rat horizontal hippocampal slice preparation, we present an approach to characterize the dynamics of the transition to seizure, and to use this information to control the activity and avoid the occurrence of seizure-like events. The transition from the interictal activity (between seizures) to the seizure-like event is aborted by brief (20-50 s) low-frequency (0.5 Hz) periodic forcing perturbations, applied via an extracellular stimulating electrode to the mossy fibers, the axons of the dentate neurons that synapse onto the CA3 pyramidal cells. This perturbation results in the stabilization of an interictal-like low-frequency firing pattern in the hippocampal slice. The results derived from this work shed light on the dynamics of the transition to seizure and will further the development of algorithms that can be used in automated devices to stop seizure occurrence.

Short and long term non-linear analysis of RR variability series

The complexity of RR variability is approached in the short and in the long term by means of black-box data analysis. Short term series of a few hundred beats are explored by means of informational entropy and predictability indexes. A correction to biases toward false determinism is performed assuming maximum uncertainty, whenever data do not furnish sufficient recurrences. Non-randomness and non-linearity are tested by means of surrogate data provided by random shuffling and phase randomization respectively. In the long term of the 24-h or of several hours, similar tests based on mutual information are applied and validated by means of surrogate series. In addition the state space reconstruction is carried out by means of state space non-linear filtering addressing directly the reconstructed trajectories. In this condition, parameters characterizing the hypothetical attractor, mainly the maximum Lyapunov exponent, can be reliably identified.