Lectures and seminars Guest seminar - Dr. Akihiro Funamizu, The University of Tokyo
Title: “Bayesian neural representation in mouse cerebral cortex”. August 26th at 11:00 in D1012, Biomedicum.
Welcome to guest seminar by by Dr. Akihiro Funamizu from the Institute for Quantitative Biosciences, The University of Tokyo
Our lab is interested in how animals integrate sensory inputs and prediction of sensory inputs or outcomes to optimize behavior. The signal detection theory based on Bayesian inference provides the optimal way to integrate the sensory and prediction. Based on the theory, we recently updated a tone-frequency discrimination task in head-fixed mice in previous studies by introducing a long or short sound, and biasing the amount of reward in each option. The tone durations and reward amounts affected the stimulus sensitivity and choice bias of mice, respectively. During the task, we performed a brain wide electrophysiology with Neuropixels 1.0 from the medial prefrontal cortex (mPFC), the secondary motor cortex (M2), and the auditory cortex (AC). We found that the choices and sounds were mainly locally represented in the M2 and AC, respectively, while the expected reward of each option (i.e., prior value) was globally represented in all the three recorded areas. These results propose a local and global representation of Bayesian inference in the cerebral cortex.
In the latter half of my talk, I am also going to talk about our recent study in modeling mice choice behaviors with a recurrent neural network (RNN) combining artificial units and real neurons recorded from mice.
Select Publications
- Localized and global representation of prior value, sensory evidence, and choice in male mouse cerebral cortex.
Ishizu K, Nishimoto S, Ueoka Y, Funamizu A
Nat Commun 2024 May;15(1):4071 - Real-cyber hybrid neural network for predicting neural circuits in mouse decision-making.
Ueoka Y, Maeda H, Wang S, Funamizu A.
bioRxiv (2024)