Neural Coding and Brain Computing Unit (Tomoki Fukai)
Overview
Research interests
- Network mechanisms of statistical modeling (e.g., predicitve coding, hierarchical Bayesian inference)
- Computations in idling brain states for memory, reasoning, and beyond
- Dendritic computation for network-level computing and learning
- Deciphering neural code in large-scale neural activity data
- Spike-based learning and computing theories (for neuro-AI)
Latest Unit News
- Tomoki Fukai received JNNS Research Award from the Japanese Neural Network Society.
- A collaboration with Tom George (an internship student from UCL) "A generative model of the hippocampal formation trained with theta driven local learning rules" was accepted by NeurIPs2023.
- Congratulations to Thomas Burns' for his work "Simplicial Hopfield networks" accepted by ICLR2023! (January 2023)
More Unit News
Postdoc opportunities
We are interested in hiring postdocs with strong background in computational neuroscience, physics, and applied mathematics. Interested candidates are requested to send their resumes to tomoki.fukai[at]oist.jp.
For details of the job posting, please refer to the OIST Careers page.