Page 6: 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.

What honey bee brain chemistry tells us about human learning

A multi-institutional team of researchers led by Virginia Tech's Fralin Biomedical Research Institute at VTC has for the first time identified specific patterns of brain chemical activity that predict how quickly individual ...

Teaching machines to design molecular switches

In biology, many RNA molecules act as sophisticated microscopic machines. Among them, riboswitches function as tiny biological sensors, changing their 3D shape upon binding to a specific metabolite. This shape-change acts ...

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