The results include a comparison between two different basis functions for temporal selectivity and how these generate different predictions for the dynamics of neural populations. The conclusions are ...

A two-chip photonic neuromorphic system performs real time spiking reinforcement learning using only light, achieving ...

The field of systems neuroscience increasingly seeks to understand how distributed neural populations interact to support complex cognitive functions such ...

Figure 1. Diagram showing an electrically active cell in a neuronal culture and the process of recording its transmembrane potential for further analysis Neurons are cells that enable the brain to ...

In order for large-scale artificial neural network hardware to become practical in the future, it is essential to integrate artificial neuron and synaptic devices, and it is necessary to reduce mass ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

A new study reveals that astrocytes—star-shaped support cells traditionally viewed as passive partners of neurons—play a ...

(A) A traditional fully connected neural network. The layers are connected by black lines corresponding to weights. The neurons separately realize the summation and nonlinear activation functions ...

Researchers have developed photonic computing chips that overcome key limitations for a type of neural network known as a ...

Researchers applied the mathematical theory of synchronization to clarify how recurrent neural networks (RNNs) generate predictions, revealing a certain map, based on the generalized synchronization, ...