Increasing Veno-Arterial Extracorporeal Membrane Oxygenation Flow Reduces Electrical Impedance of the Lung Regions in Porcine Acute Heart Failure.

Veno-arterial extracorporeal membrane oxygenation (VA ECMO) is a technique used in patients with severe heart failure. The aim of this study was to evaluate its effects on left ventricular afterload and fluid accumulation in lungs with electrical impedance tomography (EIT). In eight swine, incremental increases of extracorporeal blood flow (EBF) were applied before and after the induction of ischemic heart failure. Hemodynamic parameters were continuously recorded and computational analysis of EIT was used to determine lung fluid accumulation. With an increase in EBF from 1 to 4 l/min in acute heart failure the associated increase of arterial pressure (raised by 44%) was accompanied with significant decrease of electrical impedance of lung regions. Increasing EBF in healthy circulation did not cause lung impedance changes. Our findings indicate that in severe heart failure EIT may reflect fluid accumulation in lungs due to increasing EBF.

Time precision of hippocampal CA3 neurons.

Time precision of generation of action potentials (AP) is limited by the electrical properties of neuronal membrane, by the probabilistic nature of synaptic transmission and by the membrane noise. In the software environment GENESIS 2.2, we constructed a multicompartmental model of a rat hippocampal neuron, made up of soma, dendritic tree and axonal initial segment (IS). In the model were implemented channel and thermal noise, corrupting the propagation of postsynaptic signal at the soma-dendritic (SD) membrane and the AP initiation at the IS. Various levels of synaptic redundancy, connecting the presynaptic neurons with the SD membrane by various numbers N of unreliable synapses of varying probability P of vesicle release, were modelled. During simulations, random spatio-temporal patterns of synaptic activity were presented to the neuron repeatedly, eliciting sequences of APs, which were further statistically processed. The influence of P, N, channel and thermal noise on the time precision of AP generation was tested by repeated stimulation of identical input. The precision was mostly influenced by the synaptic unreliability and substantially dependent upon values N and P. The channel noise was about an order less corruptive than the synaptic unreliability, causing the time precision of neuronal responses to vary from submilliseconds to tens of microseconds, depending on the values P and N.

Model of neural circuit comparing static and adaptive synapses.

Replacing static synapses with the adaptive ones can affect the behaviour of neuronal network. Several network setups containing synapses modelled by alpha-functions, called here static synapses, are compared with corresponding setups containing more complex, dynamic synapses. The dynamic synapses have four state variables and the time constants are of different orders of magnitude. Response of the network to modelled stimulations was studied together with effects of neuronal interconnectivity, the axonal delays and the proportion of excitatory and inhibitory neurons on the network output. Dependency of synaptic strength on synaptic activity was also studied. We found that dynamic synapses enable network to exhibit broader spectrum of responses to given input and they make the network more sensitive to changes of network parameters. As a step towards memory modelling, retention of input sequences in the network with static and dynamic synapses was studied. The network with dynamic synapses was found to be more flexible in reducing the interference between adjacent inputs in comparison to the network containing static synapses.

Model of spike propagation reliability along the myelinated axon corrupted by axonal intrinsic noise sources.

We investigated how selected electromorphological parameters of myelinated axons influence the preservation of interspike intervals when the propagation of action potentials is corrupted by axonal intrinsic noise. Hereby we tried to determine how the intrinsic axonal noise influences the performance of axons serving as carriers for temporal coding. The strategy of this coding supposes that interspike intervals presented to higher order neurons would minimally be deprived of information included in interspike intervals at the axonal initial segment. Our experiments were conducted using a computer model of the myelinated axon constructed in a software environment GENESIS (GEneral NEural SImulation System). We varied the axonal diameter, myelin sheath thickness, axonal length, stimulation current and channel distribution to determine how these parameters influence the role of noise in spike propagation and hence in preserving the interspike intervals. Our results, expressed as the standard deviation of spike travel times, showed that by stimulating the axons with regular rectangular pulses the interspike intervals were preserved with a microsecond accuracy. Stimulating the axons with pulses imitating postsynaptic currents, greater changes of interspike intervals were found, but the influence of implemented noise on the jitter of interspike intervals was approximately the same.

Model of spike propagation reliability along the myelinated axon corrupted by axonal intrinsic noise sources.

We investigated how selected electromorphological parameters of myelinated axons influence the preservation of interspike intervals when the propagation of action potentials is corrupted by axonal intrinsic noise. Hereby we tried to determine how the intrinsic axonal noise influences the performance of axons serving as carriers for temporal coding. The strategy of this coding supposes that interspike intervals presented to higher order neurons would minimally be deprived of information included in interspike intervals at the axonal initial segment. Our experiments were conducted using a computer model of the myelinated axon constructed in a software environment GENESIS (GEneral NEural SImulation System). We varied the axonal diameter, myelin sheath thickness, axonal length, stimulation current and channel distribution to determine how these parameters influence the role of noise in spike propagation and hence in preserving the interspike intervals. Our results, expressed as the standard deviation of spike travel times, showed that by stimulating the axons with regular rectangular pulses the interspike intervals were preserved with a microsecond accuracy. Stimulation with pulses imitating postsynaptic currents, greater changes of interspike intervals were found, but the influence of implemented noise on the jitter of interspike intervals was approximately the same.