Researchers have unveiled a new generation of photonic computing chips capable of performing real‑time learning and decision‑making using only light-based processes. Photonic chips deliver real‑time ...

A team of neuroscientists at the Champalimaud Centre for the Unknown, in Lisbon, has been able to map single neural connections over long distances in the brain. "These are the first measurements of ...

Complex-valued neural networks represent an evolving frontier where the intrinsic properties of complex numbers—magnitude and phase—are harnessed to develop richer and more robust representations of ...

In order to uncover the relationship between structure and function, researchers used microfluidic devices to study neuronal networks. Uncovering the relationship between structure (connectivity) and ...

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 ...

Researchers have mapped the long-range synaptic connections involved in vocal learning in zebra finches, uncovering new details about how the brain organises learned vocalisations such as birdsong.

New research suggests that the brains of people with Long COVID and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) struggle to communicate effectively during mentally tiring tasks. While ...

Using an algorithm they call the Krakencoder, researchers at Weill Cornell Medicine are a step closer to unraveling how the brain's wiring supports the way we think and act. The study, published June ...

According to the Parkinson’s Foundation, an estimated 10 million people around the world live with Parkinson’s disease — a neurological condition that affects a person’s ability to move. Parkinson’s ...

Uncovering the relationship between structure (connectivity) and function (neuronal activity) is a fundamental question across many areas of biology. However, investigating this directly in animal ...

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