■演題
Synergistic development of brain models and brain-like computing algorithms for applications
■ 要旨
Brain modelling has become one of important approaches in neuroscience as it facilitates an integrative framework for a wide range of experimental data reflecting multilevel organisation of the nervous system and thus provides theoretical foundations for biological phenomena. In our research the focus has been on studying perceptual and cognitive aspects of brain functionality with the ambition to provide a hypothetical mechanistic explanation at the level of synaptic learning and network effects. This work has at the same time offered valuable insights into generic computational principles of neural information processing in cortical networks. In consequence, it has helped the development of brain-like neural network algorithms for extracting neural-like representations of data and addressing unsupervised as well as semi-supervised learning paradigms. Although the proposed brain-like algorithms have been shown to offer competitive performance in standard machine learning benchmarks, further exploitation of the lessons learnt from brain modelling and simulations holds a promise for the future efforts towards brain-like AI systems.
■日時
2022年11月18日（金） 13:00～14:00
Zoom URL：本フォームにご入力いただいた方に，メールでお知らせいたします．
■ 共催
■お問い合わせ
佐藤茂雄 (東北大学電気通信研究所) shigeo@tohoku.ac.jp
