For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light ...

Recent research has employed chemical reaction networks (CRNs), which harness biochemical processes for computations that translate interactions involving biochemical species into graphical form.

Radial basis function neural networks (RBFs) are prime candidates for pattern classification and regression and have been used extensively in classical machine learning applications. However, RBFs ...

A new study reveals that inhibitory neurons born later in development mature more quickly than earlier ones, allowing them to catch up and integrate evenly into neural networks.

The strength of certain neural connections can predict how well someone can learn math, and mildly electrically stimulating ...

This useful study presents a biologically realistic, large-scale cortical model of the rat's non-barrel somatosensory cortex, investigating synaptic plasticity of excitatory connections under varying ...

A biphasic structural plasticity rule interacts with homeostatic synaptic scaling to maintain firing rate homeostasis in neural networks.

This article focuses on the research regarding the impact of different activation functions on neural network models for predicting vibration responses. Activation functions are designed for three ...

Objective Long-term azithromycin treatment effectively prevents acute exacerbations of chronic obstructive pulmonary disease ...