Katsumi Tateno

Automatic detection of atrial fibrillation using the coefficient of variation and density histograms of RR and ΔRR intervals

The paper describes a method for the automatic detection of atrial fibrillation, an abnormal heart rhythm, based on the sequence of intervals between heartbeats. The RR interval is the interbeat interval, and ΔRR is the difference between two successive RR intervals. Standard density histograms of the RR and ΔRR intervals were prepared as templates for atrial fibrillation detection. As the coefficients of variation of the RR and ΔRR intervals were approximately constant during atrial fibrillation, the coefficients of variation in the test data could be compared with the standard coefficients of variation (CV test). Further, the similarities between the density histograms of the test data and the standard density histograms were estimated using the Kolmogorov-Smirnov test. The CV test based on the RR intervals showed a sensitivity of 86.6% and a specificity of 84.3%. The CV test based on the ΔRR intervals showed that the sensitivity and the specificity are both approximately 84%. The Kolmogorov-Smirnov test based on the RR intervals did not improve on the result of the CV test. In contrast, the Kolmogorov-Smirnov test based on the ΔRR intervals showed a sensitivity of 94.4% and a specificity of 97.2%.

Complexity of spatiotemporal activity of a neural network model which depends on the degree of synchronization

Spatiotemporal activity of a hippocampal CA3 model and its dynamic features were investigated. The CA3 model consists of 256 pyramidal cells and 25 inhibitory interneurons. Each pyramidal cell is a single-compartment model which was reduced from the 19-compartment cable model of the CA3 pyramidal cell developed by [Traub et al. (1991)]. Each interneuron is a model which causes tonic responses to constant depolarizing currents. The hippocampal model spontaneously causes four kinds of rhythms, A-D, which depend on the degree of synchronization of neuronal activity. The rhythm A (about 2Hz) which occurs in a range of strong mutual excitation is spatially coherent, though epileptiform bursts of pyramidal cells propagate from one end of the network to the other in a short period of time. The rhythm B (about 3Hz) occurs in an intermediate range of the strength of mutual excitation; synchronization of bursts is incomplete and the spatiotemporal pattern is complex. When the mutual excitation is relatively weak, the rhythm C (about 6Hz) occurs. Burst propagation is not uniform in direction, and the spatiotemporal activity is irregular. The rhythm D (10-35Hz) occurs in a range of weak mutual excitation when the recurrent inhibition is relatively strong. In this parameter region, pyramidal cells do not cause bursting discharges but irregular beating discharges. The hippocampal model causes phase-lockings and irregular responses to periodic synaptic stimulation depending on its own rhythmic activity and stimulus parameters. Bursting discharges of pyramidal cells are well synchronized in phase-locked responses. Several irregular responses of the rhythms A and B are evidently chaotic; each one-dimensional strobomap of chaotic responses is a non-invertible function with an unstable fixed point. Attractors reconstructed from chaotic responses demonstrate the stretching and folding mechanism.

Spontaneous Initiation and Termination of Complex Rhythms in Cardiac Cell Culture

Introduction: Complex cardiac arrhythmias often start and stop spontaneously. These poorly understood behaviors frequently are associated with pathologic modification of the structural heterogeneity and functional connectivity of the myocardium. To evaluate underlying mechanisms, we modify heterogeneity by varying the confluence of embryonic chick monolayer cultures that display complex bursting behaviors. A simple mathematical model was developed that reproduces the experimental behaviors and reveals possible generic mechanisms for bursting dynamics in heterogeneous excitable systems.

Stochastic resonance in the Hippocampal CA3-CA1 model: a possible memory recall mechanism

Stochastic resonance (SR) in a hippocampal network model was investigated. The hippocampal model consists of two layers, CA3 and CA1. Pyramidal cells in CA3 are connected to pyramidal cells in CA1 through Schaffer collateral synapses. The CA3 network causes spontaneous irregular activity (broadband spectrum peaking at around 3 Hz), while the CA1 network does not. The activity of CA3 causes membrane potential fluctuations in CA1 pyramidal cells. The CA1 network also receives a subthreshold signal (2.5 or 50 Hz) through the perforant path (PP). The subthreshold PP signals can fire CA1 pyramidal cells in cooperation with the membrane potential fluctuations that work as noise. The firing of the CA1 network shows typical features of SR. When the frequency of the PP signal is in the gamma range (50 Hz), SR that takes place in the present model shows distinctive features. 50 Hz firing of CA1 pyramidal cells is modulated by the membrane potential fluctuations, resulting in bursts. Such burst firing in the CA1 network, which resembles the firing patterns observed in the real hippocampal CA1, improves performance of subthreshold signal detection in CA1. Moreover, memory embedded at Schaffer collateral synapses can be recalled by means of SR. When Schaffer collateral synapses in subregions of CA1 are augmented three-fold as a memory pattern. pyramidal cells in the subregions respond to the subthreshold PP signal due to SR, while pyramidal cells in the rest of CA1 do not fire.

Dynamical properties of the two-process model for sleep-wake cycles in infantile autism

The two-process model is a scheme for the timing of sleep that consists of homeostatic (Process S) and circadian (Process C) variables. The two-process model exhibits abnormal sleep patterns such as internal desynchronization or sleep fragmentation. Early infants with autism often experience sleep difficulties. Large day-by-day changes are found in the sleep onset and waking times in autistic children. Frequent night waking is a prominent property of their sleep. Further, the sleep duration of autistic children is often fragmented. These sleep patterns in infants with autism are not fully understood yet. In the present study, the sleep patterns in autistic children were reproduced by a modified two-process model using nonlinear analysis. A nap term was introduced into the original two-process model to reproduce the sleep patterns in early infants. The nap term and the time course of Process S are mentioned in the present study. Those parameters led to bifurcation of the sleep-wake cycle in the modified two-process model. In a certain range of these parameter sets, a small external noise was amplified, and an irregular sleep-wake cycle appeared. The short duration of sleep led to another irregular sleep onset or waking. Consequently, an irregular sleep-wake cycle appeared in early infantile autism.

Cell-type-dependent action potentials and voltage-gated currents in mouse fungiform taste buds.

Taste receptor cells fire action potentials in response to taste substances to trigger non‐exocytotic neurotransmitter release in type II cells and exocytotic release in type III cells. We investigated possible differences between these action potentials fired by mouse taste receptor cells using in situ whole‐cell recordings, and subsequently we identified their cell types immunologically with cell‐type markers, an IP3 receptor (IP3R3) for type II cells and a SNARE protein (SNAP‐25) for type III cells. Cells not immunoreactive to these antibodies were examined as non‐IRCs. Here, we show that type II cells and type III cells fire action potentials using different ionic mechanisms, and that non‐IRCs also fire action potentials with either of the ionic mechanisms. The width of action potentials was significantly narrower and their afterhyperpolarization was deeper in type III cells than in type II cells. Na+ current density was similar in type II cells and type III cells, but it was significantly smaller in non‐IRCs than in the others. Although outwardly rectifying current density was similar between type II cells and type III cells, tetraethylammonium (TEA) preferentially suppressed the density in type III cells and the majority of non‐IRCs. Our mathematical model revealed that the shape of action potentials depended on the ratio of TEA‐sensitive current density and TEA‐insensitive current one. The action potentials of type II cells and type III cells under physiological conditions are discussed.

Development of Frequency Based Taste Receptors Using Bioinspired Glucose Nanobiosensor

A method to fabricate a bioinspired nanobiosensor using electronic-based artificial taste receptors for glucose diagnosis is presented. Fabricated bioinspired glucose nanobiosensor designated based on an artificial taste bud including an amperometric glucose biosensor and taste bud-inspired circuits. In fact, the design of the taste bud-inspired circuits was inspired by the signal-processing mechanism of taste nerves which involves two layers. The first, known as a type II cell, detects the glucose by glucose oxidase and transduces the current signal obtained for the pulse pattern is conducted to the second layer, called type III cell, to induce synchronisation of the neural spiking activity. The oscillation results of fabricated bioinspired glucose nanobiosensor confirmed an increase in the frequency of the output pulse as a function of the glucose concentration. At high glucose concentrations, the bioinspired glucose nanobiosensor showed a pulse train of alternating short and long interpulse intervals. A computational analysis performed to validate the hypothesis, which was successfully reproduced the alternating behaviour of bioinspired glucose our nanobiosensor by increasing the output frequency and alternation of pulse intervals according to the reduction in the resistivity of the biosensor.

Theta rhythm selection of a dentate gyrus network model

The dentate gyrus selectively transmits the theta rhythm to the hippocampal CA3 region. The random synaptic input to mossy cells determines frequency responses of the dentate gyrus network model. We show preliminary experimental results of this filtering property in vitro, and propose a neural network model which may account for the theta rhythm selection.

Network model of chemical-sensing system inspired by mouse taste buds

Taste buds endure extreme changes in temperature, pH, osmolarity, so on. Even though taste bud cells are replaced in a short span, they contribute to consistent taste reception. Each taste bud consists of about 50 cells whose networks are assumed to process taste information, at least preliminarily. In this article, we describe a neural network model inspired by the taste bud cells of mice. It consists of two layers. In the first layer, the chemical stimulus is transduced into an irregular spike train. The synchronization of the output impulses is induced by the irregular spike train at the second layer. These results show that the intensity of the chemical stimulus is encoded as the degree of the synchronization of output impulses. The present algorithms for signal processing result in a robust chemical-sensing system.

Functional Properties of Resonate-and-Fire Neuron Circuits for Bio-Inspired Chemical Sensor Array

The purpose of our project is to develop brain-inspired chemical sensor arrays from physiological, theoretical, and engineering points of view. In the previous work, a computational model for chemical sensor arrays has been proposed based on physiological properties of mouse taste bud cells (TBCs). The model consists of three functional parts: the chemical sensor, the random pulse generator, and the stochastic synchronizer. The chemical sensor array based on the computational model detects the concentration of chemical substances as the degree of stochastic synchronization. For practical implementation, we compare the probabilistic firing properties of an array of resonate-and-fire neuron (RFN) models and those of an array of leaky integrate-and-fire neuron models in order to consider their feasibility as the second part of a chemical sensor array. We further investigate stochastic synchronization in uncoupled integrated circuits implementing the RFN model in order to confirm if they act as the third part of a chemical sensor array on a practical hardware platform.