Page 3: Research news on Neuroscience, neural computation & artificial intelligence

Neuroscience, neural computation, and artificial intelligence constitute an integrative research area that investigates the principles of information processing in nervous systems and applies them to computational models and algorithms. It encompasses the study of neural coding, synaptic plasticity, network dynamics, and cognitive architectures, with the dual goals of explaining brain function and developing biologically inspired machine learning methods. Neural computation formalizes neuronal and circuit-level processes using mathematical models and simulations, while artificial intelligence leverages these insights to design architectures such as neural networks and reinforcement learning systems, enabling tasks like perception, decision-making, and control in both biological and artificial agents.

AI generates first complete models of proteins in motion

Many drug and antibody discovery pathways focus on intricately folded cell membrane proteins. When molecules of a drug candidate bind to these proteins, like a key going into a lock, they trigger chemical cascades that alter ...

Nature might have a universal rhythm

Animal communication can look wildly different—flashing lights, chirping calls, croaking songs and elaborate dances. But new research from Northwestern University suggests many of these signals share a surprising feature: ...

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