EEG biomarkers of activation of the lymphatic drainage system of the brain during sleep and opening of the blood-brain barrier.

The lymphatic drainage system of the brain (LDSB) is the removal of metabolites and wastes from its tissues. A dysfunction of LDSB is an important sign of aging, brain oncology, the Alzheimer's and Parkinson's diseases. The development of new strategies for diagnosis of LDSB injuries can improve prevention of age-related cerebral amyloid angiopathy, neurodegenerative and cerebrovascular diseases. There are two conditions, such as deep sleep and opening of the blood-brain-barrier (OBBB) associated with the LDSB activation. A promising candidate for measurement of LDSB could be electroencephalography (EEG). In this pilot study on rats, we tested the hypothesis, whether deep sleep and OBBB can be an informative platform for an effective extracting of information about the LDSB functions. Using the nonlinear analysis of EEG dynamics and machine learning technology, we discovered that the LDSB activation during OBBB and sleep is associated with similar changes in the EEG θ-activity. The OBBB causes the higher LDSB activation vs. sleep that is accompanied by specific changes in the low frequency EEG activity extracted by the power spectra analysis of the EEG dynamics combined with the coherence function. Thus, our findings demonstrate a link between neural activity associated with the LDSB activation during sleep and OBBB that is an important informative platform for extraction of the EEG-biomarkers of the LDSB activity. These results open new perspectives for the development of technology for the LDSB diagnostics that would open a novel era in the prognosis of brain diseases caused by the LDSB disorders, including OBBB.

Noise-sustained patterns in a model of volume-coupled neural tissue.

Computational neuroscience operates on models based on several important paradigms. Among them is the assumption that coupling in neural ensembles is provided by chemical or electrical synapses. This assumption works well under normal conditions. However, there is a growing body of data that show the importance of other communication pathways caused by bi-directional transport of substances between the cells and the intercellular space. This type of interaction is called "volume transmission" and has not been rarely addressed in the model studies. The volume transmission pathway naturally appears in multidimensional quantitative models of cellular processes, but is not sufficiently represented at the level of lumped and computationally effective neural models. In this paper, we propose a simple model that allows one to study the features of volume transmission coupling at various spatial scales and taking into account various inhomogeneities. This model is obtained by the extension of the well-known FitzHugh-Nagumo system by the addition of the nonlinear terms and equations to describe, at a qualitative level, the release of potassium into the intercellular space, its diffusion, and the reverse effect on the neurons. The study of model dynamics in various spatial configurations has revealed a number of characteristic spatio-temporal types of behavior that include self-organizing bursting and phase-locked firing patterns, different scenarios of excitation spreading, noise-sustained target patterns, and long-living slow moving wave segments.

Astrocyte calcium signaling: Interplay between structural and dynamical patterns.

Inspired by calcium activity in astrocytes, which is different in the cell body and thick branches on the one hand and thin branchlets and leaflets on the other hand, we formulate a concept of spatially partitioned oscillators. These are inhomogeneous media with regions having different excitability properties, with a global dynamics governed by spatial configuration of such regions. Due to a high surface-to-volume ratio, calcium dynamics in astrocytic leaflets is dominated by transmembrane currents, while somatic calcium dynamics relies on exchange with intracellular stores, mediated by IP 3 , which is in turn synthesized in the space nearby the plasma membrane. Reciprocal coupling via diffusion of calcium and IP 3 between the two regions makes the spatial configuration an essential contributor to overall dynamics. Due to these features, the mechanisms governing the pattern formation of calcium dynamics differ from classical excitable systems with noise or from networks of clustered oscillators. We show how geometrical inhomogeneity can play an ordering role allowing for stable scenarios for calcium wave initiation and propagation.

Turing-like structures in a functional model of cortical spreading depression.

Cortical spreading depression (CSD) along with migraine waves and spreading depolarization events with stroke or injures are the front-line examples of extreme physiological behaviors of the brain cortex which manifest themselves via the onset and spreading of localized areas of neuronal hyperactivity followed by their depression. While much is known about the physiological pathways involved, the dynamical mechanisms of the formation and evolution of complex spatiotemporal patterns during CSD are still poorly understood, in spite of the number of modeling studies that have been already performed. Recently we have proposed a relatively simple mathematical model of cortical spreading depression which counts the effects of neurovascular coupling and cerebral blood flow redistribution during CSD. In the present study, we address the main dynamical consequences of newly included pathways, namely, the changes in the formation and propagation speed of the CSD front and the pattern formation features in two dimensions. Our most notable finding is that the combination of vascular-mediated spatial coupling with local regulatory mechanisms results in the formation of stationary Turing-like patterns during a CSD event.

Conducted vasoreactivity: the dynamical point of view.

Conducted vasodilation is part of the physiological response to increasing metabolic demand of the tissue. Similar responses can be elicited by focal electrical or chemical stimulation. Some evidence suggests an endothelial pathway for nondecremental transmission of hyperpolarizing pulses. However, the underlying mechanisms are debated. Here, we focus on dynamical aspects of the problem hypothesizing the existence of a bistability-powered mechanism for regenerative pulse transmission along the endothelium. Bistability implies that the cell can have two different stable resting potentials and can switch between those states following an appropriate stimulus. Bistability is possible if the current-voltage curve is N shaped instead of monotonically increasing. Specifically, the presence of an inwardly rectifying potassium current may provide the endothelial cell with such properties. We provide a theoretical analysis as well as numerical simulations of both single- and multiunit bistable systems mimicking endothelial cells to investigate the self-consistence and stability of the proposed mechanism. We find that the individual cell may switch readily between two stable potentials. An array of coupled cells, however, as found in the vascular wall, requires a certain adaptation of the membrane currents after a switch, in order to switch back. Although the formulation is generic, we suggest a combination of specific membrane currents that could underlie the phenomenon.

Dynamics of nephron-vascular network.

The paper presents a modeling study of the spatial dynamics of a nephro-vascular network consisting of individual nephrons connected via a tree-like vascular branching structure. We focus on the effects of nonlinear mechanisms that are responsible for the formation of synchronous patterns in order to learn about processes not directly amenable to experimentation. We demonstrate that: (i) the nearest nephrons are synchronized in-phase due to a vascular propagated electrical coupling, (ii) the next few branching levels display a formation of phase-shifted patterns due to hemodynamic coupling and mode elimination, and (iii) distantly located areas show asynchronous behavior or, if all nephrons and branches are perfectly identical, an infinitely long transient behavior. These results contribute to the understanding of mechanisms responsible for the highly dynamic and limited synchronization observed among groups of nephrons despite of the fairly strong interaction between the individual units.

Self-terminating wave patterns and self-organized pacemakers in a phenomenological model of spreading depression.

A simple reaction-diffusion model of spreading depression (SD) is presented. Its local dynamics are governed by two activator and two inhibitor variables that provide an extremely simplified description of the mutual interaction between the neurons and extracellular space. This interaction is realized by the substances in the extracellular space that are increasing excitability of the neurons that have released them and are diffusing to the neighboring neurons, thereby spreading this excitation. Typical dynamic patterns of simulated activity are presented. The focus is laid on the case where response of the extracellular medium is relatively fast, and retracting waves, spiral-shaped waves, and autonomous pacemakers are observed, which is in good agreement with experimental observations. The underlying mechanisms are found to be related to switching between the local bi-stable, excitable, and self-sustained dynamics in the simulated medium. This article is part of a Special Issue entitled: Neural Coding.

Functional modeling of the shift in cellular calcium dynamics at the onset of synchronization in smooth muscle cells.

In the present paper we address the nature of synchronization properties found in populations of mesenteric artery smooth muscle cells. We present a minimal model of the onset of synchronization in the individual smooth muscle cell that is manifested as a transition from calcium waves to whole-cell calcium oscillations. We discuss how different types of ion currents may influence both amplitude and frequency in the regime of whole-cell oscillations. The model may also explain the occurrence of mixed-mode oscillations and chaotic oscillations frequently observed in the experimental system.

Dynamical structures in binary media of potassium-driven neurons.

According to the conventional approach neural ensembles are modeled with fixed ionic concentrations in the extracellular environment. However, in some cases the extracellular concentration of potassium ions cannot be regarded as constant. Such cases represent specific chemical pathway for neurons to interact and can influence strongly the behavior of single neurons and of large ensembles. The released chemical agent diffuses in the external medium and lowers thresholds of individual excitable units. We address this problem by studying simplified excitable units given by a modified FitzHugh-Nagumo dynamics. In our model the neurons interact only chemically via the released and diffusing potassium in the surrounding nonactive medium and are permanently affected by noise. First, we study the dynamics of a single excitable unit embedded in the extracellular matter. That leads to a number of noise-induced effects such as self-modulation of firing rate in an individual neuron. After the consideration of two coupled neurons we consider the spatially extended situation. By holding parameters of the neuron fixed, various patterns appear ranging from spirals and traveling waves to oscillons and inverted structures depending on the parameters of the medium.

Dynamical patterns of calcium signaling in a functional model of neuron-astrocyte networks.

We propose a functional mathematical model for neuron-astrocyte networks. The model incorporates elements of the tripartite synapse and the spatial branching structure of coupled astrocytes. We consider glutamate-induced calcium signaling as a specific mode of excitability and transmission in astrocytic-neuronal networks. We reproduce local and global dynamical patterns observed experimentally.

Multimode dynamics in a network with resource mediated coupling.

The purpose of this paper is to study the special forms of multimode dynamics that one can observe in systems with resource-mediated coupling, i.e., systems of self-sustained oscillators in which the coupling takes place via the distribution of primary resources that controls the oscillatory state of the individual unit. With this coupling, a spatially inhomogenous state with mixed high and low-amplitude oscillations in the individual units can arise. To examine generic phenomena associated with this type of interaction we consider a chain of resistively coupled electronic oscillators connected to a common power supply. The two-oscillator system displays antiphase synchronization, and it is interesting to note that two-mode oscillations continue to exist outside of the parameter range in which oscillations occur for the individual unit. At low coupling strengths, the multi-oscillator system shows high dimensional quasiperiodicity with little tendency for synchronization. At higher coupling strengths, one typically observes spatial clustering involving a few oscillating units. We describe three different scenarios according to which the cluster can slide along the chain as the bias voltage changes.

Giant glial cell: new insight through mechanism-based modeling.

The paper describes a detailed mechanism-based model of a tripartite synapse consisting of P- and R-neurons together with a giant glial cell in the ganglia of the medical leech (Hirudo medicinalis), which is a useful object for experimental studies in situ. We describe the two main pathways of the glial cell activation: (1) via IP(3) production and Ca(2 +) release from the endoplasmic reticulum and (2) via increase of the extracellular potassium concentration, glia depolarization, and opening of voltage-dependent Ca(2 +) channels. We suggest that the second pathway is the more significant for establishing the positive feedback in glutamate release that is critical for the self-sustained activity of the postsynaptic neuron. This mechanism differs from the mechanisms of the astrocyte-neuron signaling previously reported.

Functional modeling of neural-glial interaction.

We propose a generalized mathematical model for a small neural-glial ensemble. The model incorporates subunits of the tripartite synapse that includes a presynaptic neuron, the synaptic terminal itself, a postsynaptic neuron, and a glial cell. The glial cell is assumed to be activated via two different pathways: (i) the fast increase of intercellular [K(+)] produced by the spiking activity of the postsynaptic neuron, and (ii) the slow production of a mediator triggered by the synaptic activity. Our model predicts the long-term potentiation of the postsynaptic neuron as well as various [Ca(2+)] transients in response to the activation of different pathways.

Two-mode chaos and its synchronization properties.

Using a simple model with bimodal dynamics, we investigate the intra- and inter-system entrainment of the two different time scales involved in the chaotic oscillations. The transition between mode-locked and mode-unlocked chaos is analyzed for a single system. For coupled oscillators, we demonstrate full and partial synchronization patterns depending on the adjustment between the fast and slow time scales and reveal the embedded structure of the corresponding synchronization regions.

Chaotic bursting as chaotic itinerancy in coupled neural oscillators.

We show that chaotic bursting activity observed in coupled neural oscillators is a kind of chaotic itinerancy. In neuronal systems with phase deformation along the trajectory, diffusive coupling induces a dephasing effect. Because of this effect, an antiphase synchronized solution is stable for weak coupling, while an in-phase solution is stable for very strong coupling. For intermediate coupling, a chaotic bursting activity is generated. It is a mixture of three different states: an antiphase firing state, an in-phase firing state, and a nonfiring resting state. As we construct numerically the deformed torus manifold underlying the chaotic bursting state, it is shown that the three unstable states are connected to give rise to a global chaotic itinerancy structure. Thus we claim that chaotic itinerancy provides an alternative route to chaos via torus breakdown.

Complex phase dynamics in coupled bursters.

The phenomenon of phase multistability in the synchronization of two coupled oscillatory systems typically arises when the systems individually display complex wave forms associated, for instance, with the presence of subharmonic components. Alternatively, phase multistability can be caused by variations of the phase velocity along the orbit of the individual oscillator. Focusing on the mechanisms underlying the appearance of phase multistability, the paper examines a variety of phase-locked patterns in the bursting behavior of a model of coupled pancreatic cells. In particular, we show how the number of spikes per train and the proximity of a neighboring equilibrium point can influence the formation of coexisting regimes.

Phase multistability of self-modulated oscillations.

The paper examines the type of multistability that one can observe in the synchronization of two oscillators when the systems individually display self-modulation or other types of multicrest wave forms. The investigation is based on a phase reduction method and on the calculation of phase maps for vanishing and finite coupling strengths, respectively. Various phase-locked patterns are observed. In the presence of a frequency mismatch, the two-parameter bifurcation analysis reveals a set of synchronization regions inserted one into the other. Numerical examples using a generator with inertial nonlinearity and a biologically motivated model of nephron autoregulation are presented.

Noise-induced multimode behavior in excitable systems.

Based on experiments with electronic circuits, we show how a system of coupled excitable units can possess several noise-induced oscillatory modes. We characterize the multimode organization in terms of the coherence resonance effect. Multiple gain of regularity is found to be related to different frequency entrainments and to the appearance of additional time scales.

Coherence resonance versus synchronization in a periodically forced self-sustained system.

A fundamental relationship between coherence resonance (CR) and phase synchronization in a self-sustained system in the presence of noise is addressed. A Van der Pol system synchronized by external forcing is taken as an example. It is shown that, in breaking down synchronization, applied noise creates a new ordered motion whose coherence depends resonantly on its intensity, i.e., CR occurs. The same is true for both types of synchronization, via phase locking and via suppression: only the mechanisms of CR differ. The result is valid for any order n:m of synchronization.

Clustering of noise-induced oscillations.

The subject of our study is clustering in a population of excitable systems driven by Gaussian white noise and with randomly distributed coupling strength. The cluster state is frequency-locked state in which all functional units run at the same noise-induced frequency. Cooperative dynamics of this regime is described in terms of effective synchronization and noise-induced coherence.