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Computational Cognitive Neuroscience (Affiliated Unit) Lab
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A lab that explains decision making and the ability to read other people's minds as computations performed by the brain.

AboutAbout the lab
Brain function is brain computation.
Computational Cognitive Neuroscience (Affiliated Unit) is a unit affiliated with RIKEN, run by Affiliated Professor Hiroyuki Nakahara (Learning Theory and Social Brain Research Team) and Wataru Sato.
The Nakahara Lab studies the brain mechanisms that produce adaptive behavior and the computational principles behind them. It focuses in particular on "decision making and learning" and on "social intelligence," which matters most in everyday life.
The lab pursues experiments and theory in parallel. In experiments, it works with human fMRI; in theory, it works on computational models of the brain, brain-inspired intelligence, and techniques for analyzing brain data.
Key terms
- reinforcement learning
- A mechanism for learning better actions based on rewards obtained through trial and error
- fMRI
- A device that produces images showing which parts of the brain are active, based on changes in blood flow in the brain
- social intelligence
- The brain's ability to infer other people's minds and actions and to behave well in society
ResearchResearch themes
Based on the idea that "brain functions are realized by brain computation, that is, information processing," the lab conducts research that brings experiments and theory together and integrates them.
*Illustrative imageReward-Based Learning and Decision Making
The lab aims to clarify the brain mechanisms and computations behind decision making based on expected rewards and learning from past experience. It combines computational theories of the brain, such as reinforcement learning, with psychological experiments and measurement of brain activity using fMRI.
*Illustrative imageSocial Learning and Decision Making
To establish a computational theory of the brain for social intelligence, in a sense a "brain computation theory of the mind," the lab integrates human fMRI experiments with computational theories of the brain, centering on social decision making.
*Illustrative imageBrain Data Analysis and Brain-Inspired Computation
The lab develops analysis methods that extract information from large-scale brain data, as well as brain decoding techniques, particularly for human fMRI data. It also aims to connect the principles of information processing in the brain to new learning theories and to the development of brain-inspired artificial intelligence.
MembersFaculty
- Affiliated ProfessorHiroyuki Nakahara
- Affiliated ProfessorWataru Sato
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Anatomical model of human brain, Wellcome L0010009” Wellcome Images / CC BY 4.0 (cropped)
- Reward-Based Learning and Decision Making: “A jar of world coins” Billjones94 / CC BY-SA 4.0 (cropped)
- Social Learning and Decision Making: “Players and watchers focus intensely on a makeshift Thai board game - Khlong Toei - Bangkok” Alisdare Hickson / CC BY-SA 4.0 (cropped)
- Brain Data Analysis and Brain-Inspired Computation: “CFS-brain-scan-basal-ganglia-fMRI” Miller AH, Jones JF, Drake DF, Tian H, Unger ER, Pagnoni G (2014) Decreased Basal Ganglia Activation / CC BY 4.0 (cropped)
- Related lab (計算神経科学
(連携ユニット) ): “Nyt-Cajal DRAWING m1673-resized-for-web” Santiago Ramón y Cajal / Public domain (cropped) - Related lab (計算知能システム
(連携ユニット) ): “Visualizing Artificial Neural Networks (ANNs) with python library-ANN Visualizer” Serenechan3 / CC BY-SA 4.0 (cropped) - Related lab (教育情報学 分野): “Future School” Rasica03 / CC BY-SA 4.0 (cropped)
- Related lab (脳情報学 分野): “EEG Recording Cap” Chris Hope / CC BY 2.0 (cropped)
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