The human visual system demonstrates powerful image processing functionalities. Inspired by the principles from neuroscience, a spiking neural network is proposed to perform the discrete cosine transform for visual images. The structure and the properties of the network are detailed in this paper. Simulation results show that the network is able to perform the discrete cosine transform for visu...

In spiking neural P systems with anti-spikes, integers can be represented as the number of spikes/anti-spikes present in a neuron. Thus it is possible to represent increment, decrement, relational operations and assignment statements using spiking neural P systems. With these basic structures, it is also possible to represent programming language constructs like conditional, iterative and diffe...

Experiments showed that a neuron can fire when its membrane potential (an intrinsic quality related to electrical charge) reaches specific threshold. On theoretical studies, there are two crucial issues in exploring cortical neuronal dynamics: (i) what model describes spiking dynamics of each neuron, and (ii) how the neurons connected [E. M. Izhikevich, IEEE Trans. Neural Networks, 15 (2004)]. ...

In axon-bearing neurons, action potentials conventionally initiate at the axon initial segment (AIS) and are important for neuron excitability and cell-to-cell communication. However in axonless neurons, spike origin has remained unclear. Here we report in the axonless, spiking AII amacrine cell of the mouse retina a dendritic process sharing organizational and functional similarities with the ...

Spiking Neural Networks (SNNs) have been attached great importance due to the distinctive properties of low power consumption, biological plausibility, and adversarial robustness. The most effective way train deep SNNs is through ANN-to-SNN conversion, which yielded best performance in network structure large-scale datasets. However, there a trade-off between accuracy latency. In order achieve ...

We describe an analog Very-Large-Scale Integrated (aVLSI) wide-field direction-selective spiking neuron that responds robustly to both natural and artificial images. The circuitry is based on a model of the wide-field direction-selective neurons in the fly visual system. The architecture of the chip closely follows the anatomical layout of the fly visual system. The circuit has a one-dimensiona...

In the first step toward identifying the neurotransmitter released from spiking interneurons of both local and intersegmental groups in the crayfish terminal abdominal ganglion, the authors examined whether spiking local interneurons and ascending intersegmental interneurons contain the transmitter gamma-aminobutyric acid (GABA). In this paper, 17 identified ascending interneurons and three spi...

We continue here the study of the recently introduced spiking neural P systems, which mimic the way that neurons communicate with each other by means of short electrical impulses, identical in shape (voltage), but emitted at precise moments of time. The sequence of moments when a neuron emits a spike is called the spike train (of this neuron); by designating one neuron as the output neuron of a...

We study a minimal network of two coupled neurons described by the Hindmarsh – Rose model with linear coupling. suppose that individual are identical and whether dynamical regimes single neuron would be stable synchronous in neurons. find among only regular periodic spiking quiescence certain range parameters, while no bursting stable. Moreover, we show there chaotic parameter considered. On ot...

Spiking neural networks are known to be superior over artificial for their computational power efficiency and noise robustness. The benefits of spiking coupled with the high-bandwidth low-latency photonics can enable highly-efficient, noise-robust, high-speed processors. landscape photonic neurons consists an overwhelming majority excitable lasers a few demonstrations on nonlinear optical cavit...