Neuroscience continually strives to unravel the intricate relationship between neural network morphology, spiking dynamics, and their resulting functional ...

A new computational model of the brain based closely on its biology and physiology has not only learned a simple visual ...

A biologically grounded computational model built to mimic real neural circuits, not trained on animal data, learned a visual categorization task just as actual lab animals do, matching their accuracy ...

A new ‘biomimetic’ model of brain circuits and function at multiple scales produced naturalistic dynamics and learning, and ...

Abstract: Detection and localization of early internal short circuits (ISCs) in battery packs are critical for mitigating safety risks, including thermal runaway (TR). To address this issue, this ...

Depression arises not only from direct stress exposure but also from complex disruptions in emotional processing, internal state regulation, and socially ...

Learn a step-by-step system to solve almost any circuit question, from basic resistor networks to multi-loop and node-voltage ...

A research team at Duke University has developed a new AI framework that can uncover simple, understandable rules that govern some of the most complex dynamics found in nature and technology.

This codebase implements LearnSPN, a structure learning algorithm for Sum-Product Networks (SPNs), better known as Probabilistic Circuits (PCs). The project was initially created and licensed by ...

Understand Thevenin’s Theorem the easy way with a clear, step-by-step circuit example. Learn how to simplify complex electrical networks into an equivalent circuit, making analysis faster and ...

New research in mice from scientists at New York University Langone Health (NYU Langone Health) and their colleagues elsewhere identifies brain circuits that make memories more stable during learning.