Akihiro Funamizu

Lecturer, Institute for Quantitative Biosciences, The University of Tokyo *Profile is at the time of the award.

2021Inamori Research GrantsBiology & Life sciences

Research topics
Neural mechanism of behavior optimization based on prior knowledge
In order to decide whether to carry an umbrella when going out, the information available to us is limited to uncertain information such as the weather conditions. The brain's mechanism for deciding what to do based on uncertain sensory information is still unknown. My research aims to elucidate such information processing processes in the brain, with the help of computational theory used in the research of artificial intelligence. In particular, this research investigates how the brain integrates the knowledge in the mind, i.e., prior knowledge, with sensory information obtained from the outside world to determine behavior. We use behavioral experiments on mice, state-of-the-art neural activity imaging, and machine learning in an integrated manner.


Thank you very much for selecting me for the Inamori Research Grant. I will devote myself to make my research contribute to the understanding of the brain, the development of AI, and the integration of the brain and AI.

Outline of Research Achievments

Animals and humans make choices based on uncertain sensory inputs. Our study investigated whether the mouse decisions are optimal by integrating the sensory inputs and prior knowledge of reward expectations. We analyzed the choice behavior of mice during a task with signal detection theory and reinforcement learning and found the sub-optimality of choices.

Akihiro Funamizu (2021) Integration of sensory evidence and reward expectation in mouse perceptual decision-making task with various sensory uncertainties. iScience 24(8), 102826. doi: 10.1016/j.isci.2021.102826

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Biology & Life sciences