A multivariate analysis of electroencephalography activity reveals super-additive enhancements to the neural encoding of audiovisual stimuli, providing new insights into how the brain integrates ...
In a recent study, a research team led by Assistant Professor Kazuya Sawada from the Department of Information and Computer Technology, Faculty of Engineering at Tokyo University of Science (TUS), ...
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Mapping causality in neuronal activity: New method uses spike train data to identify connections
It proved effective even in the presence of weak coupling with internal noise, a common feature of biological systems. By providing a new tool for inferring neural connectivity from spike train data, ...
A new method of CCM using which connections between neurons can be inferred based on the causal relationships between spike train data. Understanding the brain’s functional architecture is a ...
Computational models predict neural activity for re-establishing connectivity after stroke or injury
Researchers at The Hong Kong University of Science and Technology (HKUST) School of Engineering have developed a novel reinforcement learning–based generative model to predict neural signals, creating ...
(Nanowerk Spotlight) Effectively mimicking the unmatched visual capacities of the human brain while operating within stringent energy constraints poses a formidable challenge for artificial ...
Group photo of the HKUST research team, including Prof. WANG Yiwen, Associate Professor (first row, right); Dr. WU Shenghui (first row, center), Research Assistant Professor, from the Department of ...
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