Extended Spiking Neural P systems with Excitatory and Inhibitory Astrocytes

Small Universal Spiking Neural P Systems with Astrocytes

Spiking neural P systems with astrocytes (SNPA systems, for short) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes, where also astrocytes are considered, having an excitatory or an inhibitory influence on synapses. Looking for small universal computing devices is a classical research topic in computer science. In this work, we i...

Asynchronous Extended Spiking Neural P Systems with Astrocytes

A neural mass model of CA1-CA3 neural network and studying sharp wave ripples

We spend one third of our life in sleep. The interesting point about the sleep is that the neurons are not quiescent during sleeping and they show synchronous oscillations at different regions. Especially sharp wave ripples are observed in the hippocampus. Here, we propose a simple phenomenological neural mass model for the CA1-CA3 network of the hippocampus considering the spike frequency adap...

Supervised Associative Learning in Spiking Neural Network

In this paper, we propose a simple supervised associative learning approach for spiking neural networks. In an excitatory-inhibitory network paradigm with Izhikevich spiking neurons, synaptic plasticity is implemented on excitatory to excitatory synapses dependent on both spike emission rates and spike timings. As results of learning, the network is able to associate not just familiar stimuli b...

Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks.

Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by incorporating the well-documented dependence of connection probability on distance. Spatially extended spiking networks exhibit symmetry-breaking bifurcations and gener...