The Hopfield neural network (HNN) method has shown great advantages in SPM and various extended versions have been developed recently. However, a long-standing issue in the HNN, especially in the ...

Uncommon Courses is an occasional series from The Conversation U.S. highlighting unconventional approaches to teaching.

The fully connected topology, which coordinates the connection of each neuron with all other neurons, remains the most commonly used structure in Hopfield-type neural networks. However, fully ...

Deep neural networks are at the heart of artificial intelligence, ranging from pattern recognition to large language and ...

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

In the decade since the discovery of Rowhammer, GPUhammer is the first variant to flip bits inside discrete GPUs and the ...

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 ...

"It's literally going to feel like a sci-fi movie," Figure AI founder Brett Adcock says.

Geoffrey Hinton warns that machine self-preservation may soon pose an existential threat without urgent regulation.

Neuroscientists want to understand how individual neurons encode information that allows us to distinguish objects, like telling a leaf apart from a rock. But they have struggled to build ...

Neural decoding articles from across Nature Portfolio Neural decoding is the study of what information is available in the electrical activity (action potentials) of individual cells or networks ...

Thanks to the neural network, the researchers now suspect that the black hole at the center of the Milky Way is spinning at almost top speed. Its rotation axis points to the Earth.