Page 2: 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.

Physics-trained digital 'super-brain' speeds nanophotonic design

Studying physics can be very useful—even when it comes to machine learning. A digital "super-brain" with built-in knowledge of the fundamental laws of nature can speed up the development of optical components for everything ...

The impact of nanoplastics on neurons may depend on their size

Smaller plastic particles have more effects on neurons, the key information processing cells of the brain, new research from the University of Eastern Finland shows. In the study, neuronal cells were exposed to polystyrene ...

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