Analysis of the robustness of spectral indices during ventricular fibrillation

The spatiotemporal characteristics of cardiac fibrillation are often investigated by using indices extracted from the spectrum of cardiac signals. However different signal acquisition systems may produce signals of different spectra and affect the estimation of some spectral indices. In this study, we investigate the robustness of four spectral indices previously proposed for describing fibrillation, namely the dominant frequency (DF), the peak frequency (PF), the median frequency (MF) and the organization index (OI). The effects of different lead configurations on the values of the spectral indices are statistically quantified and further analyzed in a database consisting of unipolar and bipolar intracardiac electrograms (EGM), recorded by implantable cardioverter-defibrillators during ventricular fibrillation. Our analysis shows that the lead configuration significantly affects the PF, the MF and the OI, whereas the DF remains unaffected. We further explore the nature of cardiac spectrum and show that unipolar EGM concentrate power at lower frequencies than bipolar EGM. We conclude that indices that depend on the envelope of the spectrum of cardiac signals are in general sensitive to the lead configuration.     

Influence of different envelope maskers on signal recognition and neuronal representation in the auditory system of a grasshopper

Background

Animals that communicate by sound face the problem that the signals arriving at the receiver often are degraded and masked by noise. Frequency filters in the receiver''s auditory system may improve the signal-to-noise ratio (SNR) by excluding parts of the spectrum which are not occupied by the species-specific signals. This solution, however, is hardly amenable to species that produce broad band signals or have ears with broad frequency tuning. In mammals auditory filters exist that work in the temporal domain of amplitude modulations (AM). Do insects also use this type of filtering?

Principal Findings

Combining behavioural and neurophysiological experiments we investigated whether AM filters may improve the recognition of masked communication signals in grasshoppers. The AM pattern of the sound, its envelope, is crucial for signal recognition in these animals. We degraded the species-specific song by adding random fluctuations to its envelope. Six noise bands were used that differed in their overlap with the spectral content of the song envelope. If AM filters contribute to reduced masking, signal recognition should depend on the degree of overlap between the song envelope spectrum and the noise spectra. Contrary to this prediction, the resistance against signal degradation was the same for five of six masker bands. Most remarkably, the band with the strongest frequency overlap to the natural song envelope (0–100 Hz) impaired acceptance of degraded signals the least. To assess the noise filter capacities of single auditory neurons, the changes of spike trains as a function of the masking level were assessed. Increasing levels of signal degradation in different frequency bands led to similar changes in the spike trains in most neurones.

Conclusions

There is no indication that auditory neurones of grasshoppers are specialized to improve the SNR with respect to the pattern of amplitude modulations.     

Des sources neuronales aux signaux EEG : modèle et interprétation des activités épileptiques

This work deals with the interpretation of electrophysiological patients recorded in epileptic patients candidate to surgery. This issue is addressed through a physiologically relevant model for the generation of scalp and intracerebral electroencephalographic (EEG) signals. The proposed model is based on a spatiotemporal representation of the sources of brain activity, which combines a distributed dipole source model and a model of coupled neuronal populations. Signals recorded by sensors (scalp and intracerebral) are then computed by solving the forward problem in the head volume conductor. In this paper, the EEG generation model is used to study the influence of some source-related parameters (spatial extent, position, synchronization) on simulated signals, during epileptic transient activity (interictal spikes). Results show that the model allows for studying, on the one hand, the relationship between the spatiotemporal organization of neuronal sources and the properties of the observed signals and, on the other hand, the relationship between surface and depth EEG signals.     

Segmentation of cardiac sound signals by removing murmurs using constrained tunable-Q wavelet transform

The automatic segmentation of cardiac sound signals into heart beat cycles is generally required for the diagnosis of heart valve disorders. In this paper, a new method for segmentation of the cardiac sound signals using tunable-Q wavelet transform (TQWT) has been presented. The murmurs from cardiac sound signals are removed by suitably constraining TQWT based decomposition and reconstruction. The Q-factor, redundancy parameter and number of stages of decomposition of the TQWT are adapted to the desired statistical properties of the murmur-free reconstructed cardiac sound signals. The envelope based on cardiac sound characteristic waveform (CSCW) is extracted after the removal of low energy components from the reconstructed cardiac sound signals. Then the heart beat cycles are derived from the original cardiac sound signals by mapping the required timing information of CSCW which is obtained using established methods. The experimental results are included in order to show the effectiveness of the proposed method for segmentation of cardiac sound signals in comparison with other existing methods for various clinical cases.     

Photoreceptor processing speed and input resistance changes during light adaptation correlate with spectral class in the bumblebee, Bombus impatiens

Colour vision depends on comparison of signals from photoreceptors with different spectral sensitivities. However, response properties of photoreceptor cells may differ in ways other than spectral tuning. In insects, for example, broadband photoreceptors, with a major sensitivity peak in the green region of the spectrum (>500 nm), drive fast visual processes, which are largely blind to chromatic signals from more narrowly-tuned photoreceptors with peak sensitivities in the blue and UV regions of the spectrum. In addition, electrophysiological properties of the photoreceptor membrane may result in differences in response dynamics of photoreceptors of similar spectral class between species, and different spectral classes within a species. We used intracellular electrophysiological techniques to investigate response dynamics of the three spectral classes of photoreceptor underlying trichromatic colour vision in the bumblebee, Bombus impatiens, and we compare these with previously published data from a related species, Bombus terrestris. In both species, we found significantly faster responses in green, compared with blue- or UV-sensitive photoreceptors, although all 3 photoreceptor types are slower in B. impatiens than in B. terrestris. Integration times for light-adapted B. impatiens photoreceptors (estimated from impulse response half-width) were 11.3 ± 1.6 ms for green photoreceptors compared with 18.6 ± 4.4 ms and 15.6 ± 4.4 for blue and UV, respectively. We also measured photoreceptor input resistance in dark- and light-adapted conditions. All photoreceptors showed a decrease in input resistance during light adaptation, but this decrease was considerably larger (declining to about 22% of the dark value) in green photoreceptors, compared to blue and UV (41% and 49%, respectively). Our results suggest that the conductances associated with light adaptation are largest in green photoreceptors, contributing to their greater temporal processing speed. We suggest that the faster temporal processing of green photoreceptors is related to their role in driving fast achromatic visual processes.     

Measuring collective behaviour of multicellular ensembles: role of space-time scales

Living systems are spectacular examples of spatiotemporally organized structures. During the development of complex organization there is dynamic equilibrium between the local and global processes acting at the intra-and intercellular levels in multiple space and time scales. Although in modelling studies such spatiotemporal systems can be described by different space-time scales and at many organizational levels, the experimental quantities measured and predictions useful for practical applications are at a macroscopic (coarser or averaged) level/scale; these are limited by the resolution of the measuring method and experimental protocol. In this work, we address whether the spatiotemporal collective dynamics exhibited by a multiscale system can discriminate between, or be borne out by, the coarse-grained and averaged measurements done at different spatial and temporal scales. Using a simple model of a ring of cells, we show that measurements of both spatial and spatiotemporal average behaviour in this multicellular ensemble can mask the variety of collective dynamics observed at other space-time scales, and exhibit completely different behaviours. Such outcomes of measurements can lead to incomplete and incorrect understanding of physiological functions and pathogenesis in multicell ensembles.     

Mitochondrial Oscillations and Waves in Cardiac Myocytes: Insights from Computational Models

Periodic cellwide depolarizations of mitochondrial membrane potential (Ψ_M) which are triggered by reactive oxygen species (ROS) and propagated by ROS-induced ROS release (RIRR) have been postulated to contribute to cardiac arrhythmogenesis and injury during ischemia/reperfusion. Two different modes of RIRR have been described: Ψ_M oscillations involving ROS-sensitive mitochondrial inner membrane anion channels (IMAC), and slow depolarization waves related to mitochondrial permeability transition pore (MPTP) opening. In this study, we developed a computational model of mitochondria exhibiting both IMAC-mediated RIRR and MPTP-mediated RIRR, diffusively coupled in a spatially extended network, to study the spatiotemporal dynamics of RIRR on Ψ_M. Our major findings are: 1), as the rate of ROS production increases, mitochondria can exhibit either oscillatory dynamics facilitated by IMAC opening, or bistable dynamics facilitated by MPTP opening; 2), in a diffusively-coupled mitochondrial network, the oscillatory dynamics of IMAC-mediated RIRR results in rapidly propagating (∼25 μm/s) cellwide Ψ_M oscillations, whereas the bistable dynamics of MPTP-mediated RIRR results in slow (0.1-2 μm/s) Ψ_M depolarization waves; and 3), the slow velocity of the MPTP-mediated depolarization wave is related to competition between ROS scavenging systems and ROS diffusion. Our observations provide mechanistic insights into the spatiotemporal dynamics underlying RIRR-induced Ψ_M oscillations and waves observed experimentally in cardiac myocytes.     

Hilbert-Huang transform for analysis of heart rate variability in cardiac health

This paper introduces a modified technique based on Hilbert-Huang transform (HHT) to improve the spectrum estimates of heart rate variability (HRV). In order to make the beat-to-beat (RR) interval be a function of time and produce an evenly sampled time series, we first adopt a preprocessing method to interpolate and resample the original RR interval. Then, the HHT, which is based on the empirical mode decomposition (EMD) approach to decompose the HRV signal into several monocomponent signals that become analytic signals by means of Hilbert transform, is proposed to extract the features of preprocessed time series and to characterize the dynamic behaviors of parasympathetic and sympathetic nervous system of heart. At last, the frequency behaviors of the Hilbert spectrum and Hilbert marginal spectrum (HMS) are studied to estimate the spectral traits of HRV signals. In this paper, two kinds of experiment data are used to compare our method with the conventional power spectral density (PSD) estimation. The analysis results of the simulated HRV series show that interpolation and resampling are basic requirements for HRV data processing, and HMS is superior to PSD estimation. On the other hand, in order to further prove the superiority of our approach, real HRV signals are collected from seven young health subjects under the condition that autonomic nervous system (ANS) is blocked by certain acute selective blocking drugs: atropine and metoprolol. The high-frequency power/total power ratio and low-frequency power/high-frequency power ratio indicate that compared with the Fourier spectrum based on principal dynamic mode, our method is more sensitive and effective to identify the low-frequency and high-frequency bands of HRV.     

Dynamic origin of spatially discordant alternans in cardiac tissue

Alternans, a condition in which there is a beat-to-beat alternation in the electromechanical response of a periodically stimulated cardiac cell, has been linked to the genesis of life-threatening ventricular arrhythmias. Optical mapping of membrane voltage (V_m) and intracellular calcium (Ca_i) on the surface of animal hearts reveals complex spatial patterns of alternans. In particular, spatially discordant alternans has been observed in which regions with a large-small-large action potential duration (APD) alternate out-of-phase adjacent to regions of small-large-small APD. However, the underlying mechanisms that lead to the initiation of discordant alternans and govern its spatiotemporal properties are not well understood. Using mathematical modeling, we show that dynamic changes in the spatial distribution of discordant alternans can be used to pinpoint the underlying mechanisms. Optical mapping of V_m and Ca_i in paced rabbit hearts revealed that spatially discordant alternans induced by rapid pacing exhibits properties consistent with a purely dynamical mechanism as shown in theoretical studies. Our results support the viewpoint that spatially discordant alternans in the heart can be formed via a dynamical pattern formation process which does not require tissue heterogeneity.     

Bench and mathematical modeling of the effects of breathing a helium/oxygen mixture on expiratory time constants in the presence of heterogeneous airway obstructions

Background

Vectorcardiogram (VCG) signals monitor both spatial and temporal cardiac electrical activities along three orthogonal planes of the body. However, the absence of spatiotemporal resolution in conventional VCG representations is a major impediment for medical interpretation and clinical usage of VCG. This is especially so because time-domain features of 12-lead ECG, instead of both spatial and temporal characteristics of VCG, are widely used for the automatic assessment of cardiac pathological patterns.

Materials and methods

We present a novel representation approach that captures critical spatiotemporal heart dynamics by displaying the real time motion of VCG cardiac vectors in a 3D space. Such a dynamic display can also be realized with only one lead ECG signal (e.g., ambulatory ECG) through an alternative lag-reconstructed ECG representation from nonlinear dynamics principles. Furthermore, the trajectories are color coded with additional dynamical properties of space-time VCG signals, e.g., the curvature, speed, octant and phase angles to enhance the information visibility.

Results

In this investigation, spatiotemporal VCG signal representation is used to characterize various spatiotemporal pathological patterns for healthy control (HC), myocardial infarction (MI), atrial fibrillation (AF) and bundle branch block (BBB). The proposed color coding scheme revealed that the spatial locations of the peak of T waves are in the Octant 6 for the majority (i.e., 74 out of 80) of healthy recordings in the PhysioNet PTB database. In contrast, the peak of T waves from 31.79% (117/368) of MI subjects are found to remain in Octant 6 and the rest (68.21%) spread over all other octants. The spatiotemporal VCG signal representation is shown to capture the same important heart characteristics as the 12-lead ECG plots and more.

Conclusions

Spatiotemporal VCG signal representation is shown to facilitate the characterization of space-time cardiac pathological patterns and enhance the automatic assessment of cardiovascular diseases.     

A Bayesian spatiotemporal statistical analysis of out-of-hospital cardiac arrests

We propose a Bayesian spatiotemporal statistical model for predicting out-of-hospital cardiac arrests (OHCAs). Risk maps for Ticino, adjusted for demographic covariates, are built for explaining and forecasting the spatial distribution of OHCAs and their temporal dynamics. The occurrence intensity of the OHCA event in each area of interest, and the cardiac risk-based clustering of municipalities are efficiently estimated, through a statistical model that decomposes OHCA intensity into overall intensity, demographic fixed effects, spatially structured and unstructured random effects, time polynomial dependence, and spatiotemporal random effect. In the studied geography, time evolution and dependence on demographic features are robust over different categories of OHCAs, but with variability in their spatial and spatiotemporal structure. Two main OHCA incidence-based clusters of municipalities are identified.     

Excitation transport and trapping on spectrally disordered lattices

It is widely assumed that the decay of fluorescence in photosynthetic systems can be described as a sum of exponential components and that the amplitude of each component is directly related to the absorption cross-section of the antenna pigments coupled to the fluorescing species. We present exact calculations of excited state decay in two-dimensional regular lattices of different geometries containing multiple spectral forms of antenna pigments. We illustrate by these calculations that there is no simple relation between the decay amplitudes (and resulting time-resolved excitation spectra) and the steady-state absorption spectra. Only in the limit that the electronic excitations reach a rapid equilibrium among all antenna spectral forms does the excitation spectrum depend uniquely on the spectral features of the array. Using the simulations in conjunction with our recent fluorescence studies, we examine excitation transport and trapping dynamics in photosystem I and the limitations imposed by the finite time resolution in single photon counting experiments. In particular, we show that rising components, associated with excitation transfer among different spectral forms, with lifetimes <20 ps would be undetected in a typical photon counting experiment.     

Patterning the heart's left-right axis: From zebrafish to man

Normal left-right asymmetry is highly conserved among vertebrates. Errors in the proper patterning of this axis are believed to lead to congenital anomalies of the heart and abdominal viscera, often with profound clinical consequences. We review briefly the nature of potential signals and signaling sources that lead to the break in left-right symmetry. The evidence suggests that left-right reversal, or homogenization, of these signals may lead to different consequences, and we explain some malpositions and malalignments of the atria, ventricles, and/or outflow tract that are seen in a variety of congenital cardiac diseases. We speculate that there are units of organ assembly responsive to laterality signals, and these units may be driven independently. One crucial source of signals appears to be the notochord and floorplate. In order to examine the clinical relationship of these midline structures to putative disorders of laterality, we review all patients with disturbances of normal laterality seen at the Massachusetts General Hospital over the past 20 years. We find a significant association between laterality defects and anomalies of the spine and other midline structures. Dev. Genet. 22:278–287, 1998. © 1998 Wiley-Liss, Inc.     

Mapping cardiac surface mechanics with structured light imaging

Cardiovascular disease often manifests as a combination of pathological electrical and structural heart remodeling. The relationship between mechanics and electrophysiology is crucial to our understanding of mechanisms of cardiac arrhythmias and the treatment of cardiac disease. While several technologies exist for describing whole heart electrophysiology, studies of cardiac mechanics are often limited to rhythmic patterns or small sections of tissue. Here, we present a comprehensive system based on ultrafast three-dimensional (3-D) structured light imaging to map surface dynamics of whole heart cardiac motion. Additionally, we introduce a novel nonrigid motion-tracking algorithm based on an isometry-maximizing optimization framework that forms correspondences between consecutive 3-D frames without the use of any fiducial markers. By combining our 3-D imaging system with nonrigid surface registration, we are able to measure cardiac surface mechanics at unprecedented spatial and temporal resolution. In conclusion, we demonstrate accurate cardiac deformation at over 200,000 surface points of a rabbit heart recorded at 200 frames/s and validate our results on highly contrasting heart motions during normal sinus rhythm, ventricular pacing, and ventricular fibrillation.     

Coding of communication calls in the subcortical and cortical structures of the auditory system

The processing of species-specific communication signals in the auditory system represents an important aspect of animal behavior and is crucial for its social interactions, reproduction, and survival. In this article the neuronal mechanisms underlying the processing of communication signals in the higher centers of the auditory system--inferior colliculus (IC), medial geniculate body (MGB) and auditory cortex (AC)--are reviewed, with particular attention to the guinea pig. The selectivity of neuronal responses for individual calls in these auditory centers in the guinea pig is usually low--most neurons respond to calls as well as to artificial sounds; the coding of complex sounds in the central auditory nuclei is apparently based on the representation of temporal and spectral features of acoustical stimuli in neural networks. Neuronal response patterns in the IC reliably match the sound envelope for calls characterized by one or more short impulses, but do not exactly fit the envelope for long calls. Also, the main spectral peaks are represented by neuronal firing rates in the IC. In comparison to the IC, response patterns in the MGB and AC demonstrate a less precise representation of the sound envelope, especially in the case of longer calls. The spectral representation is worse in the case of low-frequency calls, but not in the case of broad-band calls. The emotional content of the call may influence neuronal responses in the auditory pathway, which can be demonstrated by stimulation with time-reversed calls or by measurements performed under different levels of anesthesia. The investigation of the principles of the neural coding of species-specific vocalizations offers some keys for understanding the neural mechanisms underlying human speech perception.     

Macroscopic optical mapping of excitation in cardiac cell networks with ultra-high spatiotemporal resolution

Optical mapping of cardiac excitation using voltage- and calcium-sensitive dyes has allowed a unique view into excitation wave dynamics, and facilitated scientific discovery in the cardiovascular field. At the same time, the structural complexity of the native heart has prompted the design of simplified experimental models of cardiac tissue using cultured cell networks. Such reduced experimental models form a natural bridge between single cells and tissue/organ level experimental systems to validate and advance theoretical concepts of cardiac propagation and arrhythmias. Macroscopic mapping (over >1cm(2) areas) of transmembrane potentials and intracellular calcium in these cultured cardiomyocyte networks is a relatively new development and lags behind whole heart imaging due to technical challenges. In this paper, we review the state-of-the-art technology in the field, examine specific aspects of such measurements and outline a rational system design approach. Particular attention is given to recent developments of sensitive detectors allowing mapping with ultra-high spatiotemporal resolution (>5 megapixels/s). Their interfacing with computer platforms to match the high data throughput, unique for this new generation of detectors, is discussed here. This critical review is intended to guide basic science researchers in assembling optical mapping systems for optimized macroscopic imaging with high resolution in a cultured cell setting. The tools and analysis are not limited to cardiac preparations, but are applicable for dynamic fluorescence imaging in networks of any excitable media.     

Dynamical analysis of the calcium signaling pathway in cardiac myocytes based on logarithmic sensitivity analysis

Many cellular functions are regulated by the Ca(2+) signal which contains specific information in the form of frequency, amplitude, and duration of the oscillatory dynamics. Any alterations or dysfunctions of components in the calcium signaling pathway of cardiac myocytes may lead to a diverse range of cardiac diseases including hypertrophy and heart failure. In this study, we have investigated the hidden dynamics of the intracellular Ca(2+) signaling and the functional roles of its regulatory mechanism through in silico simulations and parameter sensitivity analysis based on an experimentally verified mathematical model. It was revealed that the Ca(2+) dynamics of cardiac myocytes are determined by the balance among various system parameters. Moreover, it was found through the parameter sensitivity analysis that the self-oscillatory Ca(2+) dynamics are most sensitive to the Ca(2+) leakage rate of the sarcolemmal membrane and the maximum rate of NCX, suggesting that these two components have dominant effects on circulating the cytosolic Ca(2+).     

Categorization of environmental sounds

Sounds in the natural environment are non-stationary, in that their spectral dynamics is time-dependent. We develop measures to analyze the spectral dynamics of environmental sound signals and find that they fall into two categories—simple sounds with slowly varying spectral dynamics and complex sounds with rapidly varying spectral dynamics. Based on our results and those from auditory processing we suggest rate of spectral dynamics as a possible scheme to categorize sound signals in the environment.