We investigate neural computations and brain mechanisms for learning and decision-making along with motivation/emotion/social functions.
Hiroyuki Nakahara, Ph.D.
Team Leader, Integrated Theoretical Neuroscience
hiroyuki.nakahara [at] riken.jp
- Research Overview
- Selected Publications
- News & Media
- Curriculum Vitae
- Laboratory Website
- Postdoctoral research scientist position (Human fMRI) (W889)
- Postdoctoral research scientist position (Computational neuroscience) (W890)
The long-term goal of our laboratory is to understand the computational principles that underlie the way neural systems realize adaptive behavior, decision-making, and associated learning. In particular, we focus on (1) reward-based learning and decision-making and (2) social learning and decision-making. Toward this goal, we address computational questions by building computational and mathematical models. We also use human fMRI in combination with quantitative approaches such as model-based analysis and neural decoding techniques. We further develop quantitative techniques and methods for realizing innovative data analysis in neuroscience, and also theories and models for brain-based artificial intelligence. In collaborative work with experimental investigators, we investigate the topics of our interest, using various types of experimental data.
Main Research Field
Related Research Fields
- Terada S, Sakurai Y, Nakahara H, Fujisawa S.:
"Temporal and rate coding for discrete event sequences in the hippocampus."
Neuron, 94, 1248-1262 (2017)
- Nakahara, H.:
"Multiplexing signals in reinforcement learning with internal models and dopamine."
Curr Opin Neurobiol, 25, 123-129 (2014)
- Suzuki, S., Harasawa, N., Ueno, K., Gardner, JL., Ichinohe, N., Haruno, M., Cheng, K., and Nakahara, H.:
"Learning to simulate others' decisions."
Neuron, 74(6), 1125-1137 (2012)
- Bromberg-Martin, ES., Matsumoto, M., Nakahara, H., and Hikosaka, O.:
"Multiple timescales of memory in lateral habenula and dopamine neurons."
Neuron, 67(3), 499-510 (2010)
- Nakahara, H., and Kaveri, S.:
"Internal-Time Temporal Difference Model for Neural Value-based Decision Making.", Neural Comput, 22(12), 3062-3106 (2010)
- Santos, GS., Gireesh, ED., Plenz, D., and Nakahara, H.:
"Hierarchical interaction structre of neural activities in cortical slice cultures."
J Neurosci, 30(26), 8720-8733 (2010)
- Nakahara, H., Amari, S., and Richmond, BJ.:
"A comparison of descriptive models of a single spike train by information-geometric measure."
Neural Comput, 18(3), 545-568 (2006)
- Nakahara, H., Itoh, H., Kawagoe, R., Takikawa, Y., Hikosaka, O.:
"Dopamine neurons can represent context-dependent prediction error."
Neuron, 41(2), 269-280 (2004)
- Nakahara, H., and Amari, S.:
"Information geometric measure for neural spikes."
Neural Comput, 14(10), 2269-2316 (2002)
- Nakahara, H., Doya, K., and Hikosaka, O.:
"Parallel cortico-basal ganglia mechanisms for acquisition and execution of visuomotor sequences: A computational approach."
J Cognitive Neurosci, 13(5), 626-647 (2001)
News & Media
Jun. 21, 2012（Press Release）