Page 14: 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.

Brighter fluorescent markers allow for finer imaging

Researchers at the McKelvey School of Engineering at Washington University in St. Louis have pioneered a new technique that will enable higher-resolution imaging of very small objects like neurons. The technique, which improves ...

Developing nanoprobes to detect neurotransmitters in the brain

The animal brain consists of tens of billions of neurons or nerve cells that perform complex tasks like processing emotions, learning, and making judgments by communicating with each other via neurotransmitters. These small ...

Neuromorphic camera and machine learning aid nanoscopic imaging

In a new study, researchers at the Indian Institute of Science (IISc) show how a brain-inspired image sensor can go beyond the diffraction limit of light to detect miniscule objects such as cellular components or nanoparticles ...

New nanosensor gives unprecedented look at dopamine release

Astronomers build new telescopes and peer at the night sky to see what they might find. Janelia Group Leader Abraham Beyene takes a similar approach when looking at the cells that make up the human brain.

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