Although neuromorphic hardware is key to mimicking brain-like information processing, existing systems have much higher energy consumption than biological systems. A molybdenum disulfide-based neuron ...

The development of algorithms to accurately decode neural information has long been a research focus in the field of neuroscience. Brain decoding typically involves training machine learning models to ...

Spiking neural networks (SNNs) are artificial intelligence (AI) models inspired by how biological neurons communicate with ...

Combining microscopy, scanning, and deep learning enables more precise imaging of functional dynamics in neural networks of human cortical organoids.

Artificial intelligence systems designed to physically emulate natural brains can simulate human brain activity before being trained, according to new research from Johns Hopkins University. “The work ...

In 1943, a pair of neuroscientists were trying to describe how the human nervous system works when they accidentally laid the foundation for artificial intelligence. In their mathematical framework ...

Researchers identified two brain networks involved in word retrieval -- the cognitive process of accessing words we need to speak. A semantic network processes meaning in middle/inferior frontal gyri, ...

A sweeping new analysis of more than 4,000 brain scans reveals that our brains’ neural networks don’t simply mature and then decline; they reorganize through a series of distinct life-stage “epochs,” ...

A positive face-to-face conversation between a mother and her child can temporarily align their neural activity even after ...