Research Topics
 Hiroyuki NakaharaSummaryAffiliation: RIKEN Brain Science Institute Country: Japan Publications
 Collaborators

Detail Information
Publications
 Multiplexing signals in reinforcement learning with internal models and dopamineHiroyuki Nakahara
Laboratory for Integrated Theoretical Neuroscience, RIKEN Brain Science Institute, 2 1 Hirosawa, Wako, Saitama 351 0198, Japan Electronic address
Curr Opin Neurobiol 25:1239. 2014..Even dopamine, a classic modelfree signal, may work as multiplexed signals using modelbased information and contribute to representational learning of reward structure...  Extended LATER model can account for trialbytrial variability of both pre and postprocessesHiroyuki Nakahara
Laboratory for Integrated Theoretical Neuroscience, RIKEN Brain Science Institute, 2 1 Hirosawa, Wako, Saitama, Japan
Neural Netw 19:102746. 2006..The ELATER model is useful for investigating decision making by taking account of trialbytrial variability of both pre and postprocesses...  Saccaderelated spread of activity across superior colliculus may arise from asymmetry of internal connectionsHiroyuki Nakahara
Laboratory for Mathematical Neuroscience and for Integrated Theoretical Neuroscience, RIKEN Brain Science Institute, Saitama, Japan
J Neurophysiol 96:76574. 2006..Other sensory maps in the brain (e.g., visual cortex) are also nonlinear and our analysis suggests that the consequences of asymmetric connections in those areas should be considered...  Improved parameter estimation for variancestabilizing transformation of geneexpression microarray dataMasato Inoue
Laboratory for Mathematical Neuroscience, RIKEN Brain Science Institute, Saitama 351 0198, Japan
J Bioinform Comput Biol 2:66979. 2004..Validation of this method with experimental data has suggested that it is superior to the conventional method...  A comparison of descriptive models of a single spike train by informationgeometric measureHiroyuki Nakahara
Laboratory for Mathematical Neuroscience, RIKEN Brain Science Institute, Wako, Saitama, 351 0198 Japan
Neural Comput 18:54568. 2006..This provides guidance about what measurements would effectively separate the two models. As newer models are proposed, they also can be compared to these models using information geometry...  Dopamine neurons can represent contextdependent prediction errorHiroyuki Nakahara
Lab for Mathematical Neuroscience, RIKEN Brain Science Institute, Wako, Saitama, Japan
Neuron 41:26980. 2004..This history effect corresponded to the prediction error based on the conditional probability of reward and could be simulated only by implementing the relevant context into the TD model...  Difficulty of singularity in population codingShun Ichi Amari
Laboratory for Mathematical Neuroscience, RIKEN Brain Science Institute, Wako, Saitama, 351 0198 Japan
Neural Comput 17:83958. 2005..Our method integrates a variety of disciplines in population coding, such as nonregular statistics, Bayesian statistics, singularity in algebraic geometry, and synchronous firing, under the theme of Fisher information...  Encoding of social state information by neuronal activities in the macaque caudate nucleusGustavo S Santos
Laboratory for Integrated Theoretical Neuroscience, RIKEN BSI, Wako, Japan
Soc Neurosci 7:4258. 2012..These results indicate that different neuronal activities in the CN encode social state information and rewardrelated information, which may contribute to adjusting competitive behavior in dynamic social contexts...  Hierarchical interaction structure of neural activities in cortical slice culturesGustavo S Santos
Laboratory for Integrated Theoretical Neuroscience, RIKEN Brain Science Institute, Wako, Saitama 351 0198, Japan
J Neurosci 30:872033. 2010..Thus, the identification of appropriate units of interaction may allow for the successful characterization of neuronal activities in largescale networks...  Learning to represent reward structure: a key to adapting to complex environmentsHiroyuki Nakahara
Laboratory for Integrated Theoretical Neuroscience, RIKEN Brain Science Institute, Wako, Saitama 351 0198, Japan
Neurosci Res 74:17783. 2012....  Correlation and independence in the neural codeShun Ichi Amari
Neural Comput 18:125967. 2006..We elucidate the NirenbergLatham loss from the point of view of information geometry...  Informationgeometric measure for neural spikesHiroyuki Nakahara
Laboratory for Mathematical Neuroscience, RIKEN Brain Science Institute, Wako, Saitama, 351 0198, Japan
Neural Comput 14:2269316. 2002..As a result, purely pairwise, triplewise, and higherorder interactions are singled out. We also demonstrate the benefits of our proposal by using several examples...  Synchronous firing and higherorder interactions in neuron poolShun Ichi Amari
Laboratory for Mathematical Neuroscience, RIKEN Brain Science Institute, Wako Shi, Saitama, Japan
Neural Comput 15:12742. 2003..We analyze a simple model in which neurons receive common overlapping inputs and prove that such a model can have a widespread distribution of activity, generating higherorder stochastic interactions...  Learning to simulate others' decisionsShinsuke Suzuki
Laboratory for Integrated Theoretical Neuroscience, RIKEN Brain Science Institute, Wako, Saitama 351 0198, Japan
Neuron 74:112537. 2012..These findings show that simulation uses a core prefrontal circuit for modeling the other's valuation to generate prediction and an adjunct circuit for tracking behavioral variation to refine prediction...  Selforganization in the basal ganglia with modulation of reinforcement signalsHiroyuki Nakahara
Laboratory for Mathematical Neuroscience, RIKEN Brain Science Institute 2 1 Hirosawa, Wako, Saitama, 351 0198, Japan
Neural Comput 14:81944. 2002..Simulations based on the model are shown to produce various types of neural activity similar to those found in experiments...  Gene interaction in DNA microarray data is decomposed by information geometric measureHiroyuki Nakahara
Lab for Mathematical Neuroscience, RIKEN Brain Science Institute, Saitama 351 0198, Japan
Bioinformatics 19:112431. 2003..Given the vast amount of gene expression data, it is essential to develop a simple and reliable method of investigating the fine structure of gene interaction. We show how an information geometric measure achieves this...  Differential reward coding in the subdivisions of the primate caudate during an oculomotor taskKae Nakamura
Department of Physiology, Kansai Medical University, Fumizono cho, Moriguch City, Osaka 570 8506, Japan
J Neurosci 32:1596382. 2012..g., baseline firing and spike width. These results suggest parallel processing of different reward information by the basal ganglia subdivisions defined by extrinsic connections and intrinsic properties...  Dual reward prediction components yield Pavlovian sign and goaltrackingSivaramakrishnan Kaveri
Lab for Integrated Theoretical Neuroscience, RIKEN BSI, Wako, Japan Dept of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama, Japan
PLoS ONE 9:e108142. 2014..These results suggest two complementary neural correlates, corresponding to the cue and its evoked reward, form the basis for learning reward predictions in the sign and goaltracking rats. ..  Internaltime temporal difference model for neural valuebased decision makingHiroyuki Nakahara
Laboratory for Integrated Theoretical Neuroscience, RIKEN Brain Science Institute, Wako, Saitama, 351 0198 Japan
Neural Comput 22:3062106. 2010..We also relate the internal TD formulation to research on interval timing and subjective time...  Population coding and decoding in a neural field: a computational studySi Wu
RIKEN Brain Science Institute, Wako Shi, Saitama, Japan
Neural Comput 14:9991026. 2002..This implies that the variance is no longer adequate to measure decoding accuracy...  Basal ganglia orient eyes to rewardOkihide Hikosaka
Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
J Neurophysiol 95:56784. 2006..These data support a specific form of reinforcement learning theories, but also suggest further refinement of the theory...  Correlation of primate caudate neural activity and saccade parameters in rewardoriented behaviorHideaki Itoh
Department of Mathematical Engineering and Information Physics, The University of Tokyo, Tokyo 113 8656, Japan
J Neurophysiol 89:177483. 2003..These results suggest that, while a majority of CD neurons receive rewardrelated signals, only some of them can make a significant contribution to change saccadic outputs based on expected reward...  Modulation of saccadic eye movements by predicted reward outcomeYoriko Takikawa
Department of Physiology, Juntendo University, School of Medicine, 2 1 1 Hongo, Bunkyo ku, Tokyo 113 8421, Japan
Exp Brain Res 142:28491. 2002..These results provide important constraints to the neuronal mechanism underlying rewardoriented behavior because it must satisfy these rules...  Information processing in a neuron ensemble with the multiplicative correlation structureSi Wu
Department of Informatics, Sussex University, Brighton, BN1 9QH UK
Neural Netw 17:20514. 2004....  Structurestabilityfunction relationships of dendritic spinesHaruo Kasai
Department of Cell Physiology, National Institute for Physiological Sciences and The Graduate University for Advanced Studies SOKENDAI, Okazaki 444 8585, Japan
Trends Neurosci 26:3608. 2003..Characterization of supramolecular complexes responsible for synaptic memory and learning is key to the understanding of brain function and disease...