Blue sky catastrophe in the phenomenological model of neuron-astrocyte interaction.

We study a bifurcation scenario that corresponds to the transition from bursting activity to spiking in a phenomenological model of neuron-astrocyte interaction in neuronal populations. In order to do this, we numerically obtain one-dimensional Poincaré return map and highlight its bifurcation structure using an analytically constructed piecewise smooth model map. This map reveals the existence of a cascade of period-adding bifurcations, leading to a bursting-spiking transition via blue sky catastrophe.

A Method for Assessing Working Memory in Rats Using Controlled Virtual Environment.

Unlabelled: is to develop an experimental method to effectively assess the working memory in rats. The method uses a state-of-the-art controlled virtual environment with a virtual maze. The setup includes a treadmill for rodents, a fixation system, a dome for displaying virtual environment, and a control unit.

Spiral attractors in a reduced mean-field model of neuron-glial interaction.

This paper investigates various bifurcation scenarios of the appearance of bursting activity in the phenomenological mean-field model of neuron-glial interactions. In particular, we show that the homoclinic spiral attractors in this system can be the source of several types of bursting activity with different properties.

Memristive Neural Networks for Predicting Seizure Activity.

Unlabelled: is to assess the possibilities of predicting epileptiform activity using the neuronal activity data recorded from the hippocampus and medial entorhinal cortex of mice with chronic epileptiform activity. To reach this goal, a deep artificial neural network (ANN) has been developed and its implementation based on memristive devices has been demonstrated.

Materials And Methods: Young healthy outbred CD1 mice were used in our study.

Ghost attractors in blinking Lorenz and Hindmarsh-Rose systems.

In this paper, we consider blinking systems, i.e., non-autonomous systems generated by randomly switching between several autonomous continuous time subsystems in each sequential fixed period of time.