IQB Handbook

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17ACHIEVEMENTPUBLICATIONFunamizu A, Kuhn B, Doya K. Neural substrate of dynamic Bayesian inference in the cerebral cortex. Nat Neurosci. 2016 Dec;19(12):1682-1689. DOI:10.1038/nn.4390Funamizu A, Ito M, Doya K, Kanzaki R, Takahashi H. Condition interference in rats performing a choice task with switched variable- and fixed-reward conditions. Front Neurosci. 2015 Feb 13;9:27. DOI:10.3389/fnins.2015.00027Funamizu A, Ito M, Doya K, Kanzaki R, Takahashi H. Uncertainty in action-value estimation affects both action choice and learning rate of the choice behaviors of rats. Eur J Neurosci. 2012 Apr;35(7):1180-9. DOI: 10.1111/j.1460-9568.2012.08025.xOur laboratory combines machine learning and animal experiments to understand the neural substrate of decision making. We succeeded to model mouse behavior with reinforcement learning and Bayesian inference, and decode mouse position from population neuronal activity. We image calcium signals from dorsal cortical neurons and manipulate them with optogenetics.FUNAMIZUAKIHIROPH.D. (2011) THE UNIVERSITY OF TOKYOPOSTDOCTORAL RESEARCH (2011) OKINAWA INSTITUTE OF SCIENCE AND TECHNOLOGYPOSTDOCTORAL RESEARCH (2016) COLD SPRING HARBOR LABORATORYLECTURER (2020)IQB / INSTITUTE FOR QUANTITATIVE BIOSCIENCES, THE UNIVERSITY OF TOKYO●MEMBER■ LECTURER :FUNAMIZU AKIHIRO■ RESEARCH ASSOCIATE :ISHIZU KOTAROPUBLICATIONPUBLICATIONur laboratory studies the circuitry of decision making in the dorsal cortices. Our aim is to understand how the brain generates complex behaviors by combining sensory inputs and prior knowledge. We are particularly interest-ed in how the neuronal processes of decision making are functionally different from machine learning algorithms. Although recent artificial neural networks (or artificial intelli-gence: AI) achieve magnificent performance in visual processing, Shogi, Go, and StarCraft, there are still some tasks which are easy to solve for animals but difficult for AI. We use mice as a model system and combine behav-ioral tasks, calcium imaging, optogenetics, electrophysiology, and computations to address these questions. My bachelor’s degree is in engineering, especially in robotics, from the University of Tokyo. At that time, before the era of deep learning, I got interested in neuroscience to understand how the brain accomplishes the sophisticated sensory processes and action selection. After I got a PhD in information science and technology, I continued my career in neuroscience with Dr. Kenji Doya at Okinawa Institute of Science and Technology (OIST) and learned interdisciplinary approaches of computational theory and experiment. At OIST, I investigated the neural substrate of dynamic Bayesian inference in the cerebral cortex. I then did my second postdoc with Dr. Anthony Zador at Cold Spring Harbor Laboratory (CSHL) and studied the neural substrate of perceptual decision making in the mouse auditory cortex.O