Understanding the operation of neurons and synapses is essential to reproducing biological computation. Building artificial neuromorphic networks opens the door to a new generation of faster and low-energy-consuming electronic circuits for computatio...
Computational intelligence and neuroscience
Aug 25, 2021
The nonlinear spiking neural P systems (NSNP systems) are new types of computation models, in which the state of neurons is represented by real numbers, and nonlinear spiking rules handle the neuron's firing. In this work, in order to improve computi...
Advanced materials (Deerfield Beach, Fla.)
Aug 22, 2021
Optogenetics refers to a technique that uses light to modulate neuronal activity with a high spatiotemporal resolution, which enables the manipulation of learning and memory functions in the human brain. This strategy of controlling neuronal activity...
Small (Weinheim an der Bergstrasse, Germany)
Aug 21, 2021
The computing based on artificial neuron network is expected to break through the von Neumann bottleneck of traditional computer, and to greatly improve the computing efficiency, displaying a broad prospect in the application of artificial visual sys...
Neural networks : the official journal of the International Neural Network Society
Aug 16, 2021
We use a recently developed synchronous Spiking Neural Network (SNN) model to study the problem of learning hierarchically-structured concepts. We introduce an abstract data model that describes simple hierarchical concepts. We define a feed-forward ...
A fundamental challenge for the theoretical study of neuronal networks is to make the link between complex biophysical models based directly on experimental data, to progressively simpler mathematical models that allow the derivation of general opera...
IEEE transactions on neural networks and learning systems
Aug 3, 2021
This article presents concurrent associative memories with synaptic delays useful for processing sequences of real vectors. Associative memories with synaptic delays were introduced by the authors for symbolic sequential inputs and demonstrated sever...
IEEE transactions on neural networks and learning systems
Aug 3, 2021
Studies of structural connectivity at the synaptic level show that in synaptic connections of the cerebral cortex, the excitatory postsynaptic potential (EPSP) in most synapses exhibits sub-mV values, while a small number of synapses exhibit large EP...
Artificial synaptic platforms are promising for next-generation semiconductor computing devices; however, state-of-the-art optoelectronic approaches remain challenging, owing to their unstable charge trap states and limited integration. We demonstrat...
In classical computational neuroscience, analytical model descriptions are derived from neuronal recordings to mimic the underlying biological system. These neuronal models are typically slow to compute and cannot be integrated within large-scale neu...