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.

Worming out the molecular secrets behind collective behavior

Studying social behavior is crucial for understanding how certain neuromodulatory pathways—like the serotonin pathway, which influences mood and social interactions—are regulated. Kavita Babu, Professor at the Centre for ...

2D memristors could help solve AI's energy problem

New generations of memristors could reliably store information directly within the molecular structures of graphene-like materials. In a new review published in Nanoenergy Advances, Gennady Panin of the Russian Academy of ...

Courtship is complicated, even in fruit flies

Love is in the air for the vinegar fly. Drosophila melanogaster has long been a model for understanding how brains translate sensory information into courtship behavior. Male flies perform a multitude of romantic actions—orienting, ...

The making of doting dads may involve a specific gene

Male caregiving is rare. Of the nearly 6,000 mammalian species, fewer than 5% of fathers stick around to raise their own young. Most are even instinctively hostile. Even among the mammals that pitch in with caregiving duties, ...

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