Lab members
Section of Brain Function Information is part of National Institute for Physiological Sciences. This section is led by Prof. Chikazoe in close collaboration with Prof. Sadato's lab (Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences).
Dr. Pham is employed by research funding given to Section of Brain Function Information. He works on the central project in which deep learning and function MRI is combined. Takaaki and Yutaro are grad students conducting the research projects of our lab while being co-supervised by Prof. Sadato.
Haruki, Yukihiro and Ryunosuke are college students who work as the research assistants of Section of Brain Function Information. They work mainly on deep learning projects.
Though Section of Brain Function Information is a small lab, we tackle ambitious projects while redeeming week points such as unstable research funding and resource by collaborating with Prof. Sadato's lab. It is worth noting that grad students can conduct their research with detailed support of the primary investigator (Prof. Chikazoe).
We are seeking enthusiastic PhD students, so, please feel free to ask us if you are interested.
(Email: chikazoe★nips.ac.jp (please replace ★ by @)).
Associate professor：Junichi Chikazoe (Click the link for CV)
Neural correlates of taste in humans
Combining deep learning and functional MRI
Currency-like nature of emotion
Post-doc：Quang Trung Pham
Combining deep learning and functional MRI
PhD student (D4)：Takaaki Yoshimoto
Value representations in the orbitofrontal cortex (OFC)
Development of biomarkers of mental disorders
PhD student（M1）：Yutaro Koyama
Looking for elementary unit of "mind" by big data analysis on neuroimaging
Development of biomarkers of mental disorders
Research assistant: Haruki Niwa
Neuroimaging data analysis using machine learning technique
Research assistant: Ryunosuke Ishizaki
Building audio-to-value transformer with deep learning
Research assistant: Yukihiro Kato
Anatomical and functional neuroimaging data analysis using machine learning