Neuronal Network

Neuronal networks, encompassing both biological and artificial systems, are studied to understand information processing in the brain and to develop more efficient and powerful computing architectures. Current research focuses on developing novel model architectures, such as spiking neural networks and graph neural networks incorporating temporal attention mechanisms, to better capture the dynamic and complex nature of neuronal activity and connectivity. These advancements aim to improve the accuracy and efficiency of machine learning algorithms for tasks like time-series classification and to provide insights into biological learning mechanisms, potentially leading to breakthroughs in neuroscience and robotics.