Researchers challenge the "efficiency" theory of the brain, showing that neurons become more coordinated and share more information as learning occurs.

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

People's decisions are known to be influenced by past experiences, including the outcomes of earlier choices. For over a ...

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

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...

Astrocytes use the MEGF10 receptor to prune synapses in the striatum, a process essential for dopamine-driven motor learning.

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the tail end ...

Examining brain plasticity and its implications for development, aging, and brain injury recovery.