Araya’s google scholar page

2025

Baltieri, M., Torresan, F., & Nakai, T. (2025) , A coalgebraic perspective on predictive processing , arXiv
Nobe, S., & Sasai, S. (2025) , Direct Generation of Images from EEG using Schrödinger Bridge , bioRxiv
Hamada, H. T., & Harada, Y. (2025) , Alignment for Psychological Concept Network , ICONIP 2025
Torresan, F., Suzuki, K., Kanai, R., Baltieri, M. (2025) , Active inference for action-unaware agents , arXiv
Supke, M., Schäfer, S. K., Meier, J., Hamada, H. T., Yamada, M., Wessa, M., Lieb, K. (2025) , Positive mental states and their relation to psychosocial resources: protocol of a systematic review focusing on cultural moderators , BMJ Journals
Virgo, N., Biehl, M., Baltieri, M., & Capucci, M. (2025) , A "good regulator theorem" for embodied agents , arXiv
Constant-Varlet, C., Nakai, T., Longo, L., & Prado, J. (2025) , Familial transmission of neural representations for mental arithmetic across two generations , PNAS , 122 (33) , e2421528122
Aguilera, M., Morales, P. A., Rosas, F. E., & Shimazaki, H. (2025) , Explosive neural networks via higher-order interactions in curved statistical manifolds , Nature Communications , 16 (6511)
Oizumi, M., Lim, C., & Kanai, R. (2025) , Principal Bundle Geometry of Qualia: Understanding the Quality of Consciousness from Symmetry , PsyArXiv
Hamada, H. T., Fujisawa, I., Kawakita, G., & Yamada, Y. (2025) , Measuring How LLMs Internalize Human Psychological Concepts: A preliminary analysis , arXiv
Inoue, M., Sato, M., Tomeoka, K., Nah, N., Hatakeyama, E., Arulkumaran, K., Horiguchi, I., & Sasai, S. (2025) , A Silent Speech Decoding System from EEG and EMG with Heterogenous Electrode Configurations , INTERSPEECH 2025
Hamada, H. T. (2025) , なぜ神経科学者は脳ではなく言語モデルで研究を行うのか？ , The Japanese Journal of Psychonomic Science , 43 (2) , 135-141
Kubo, R., Nishimoto, S., & Nakai, T. (2025) , Second Language Proficiency Modulates Hierarchical Alignment between Brain Activity and Large Language Models , bioRxiv
Okuno, A., Yamaguchi, H. Q., Nishimoto, S., & Nakai, T. (2025) , Modulation of decodable semantic features of brain activity via selection attention , bioRxiv
Taniguchi, T., Takagi, S., Otsuka, J., Hayashi, Y., & Hamada, H. T. (2025) , Collective predictive coding as model of science: formalizing scientific activities towards generative science , ROYAL SOCIETY OPEN SCIENCE
Yamane, Y., Li, Y., Matsumoto, K., Kanai, R., Desforges, M., Gutierrez, C. E., et al. (2025) , Optical Neuroimage Studio (OptiNiSt): Intuitive, scalable, extendable framework for optical neuroimage data analysis , PLOS Computational Biology
Nakai, T., Kubo, R., & Nishimoto, S. (2025) , Cortical representational geometry of diverse tasks reveals subject-specific and subject-invariant cognitive structures , Communications Biology
Iizuka, H., Suzuki, K., Suzuki, R., Izquierdo, E. J., & Baltieri, M. (2025) , Editorial Introduction to the 2023 Conference on Artificial Life Special Issue , Artificial Life
Nedergaard, A., & Morales, P., A. (2025) , An Information-Geometric Approach to Artificial Curiosity , ICML 2025
Rosas, F., Boyd, A., & Baltieri, M. (2025) , AI in a vat: Fundamental limits of efficient world modelling for agent sandboxing and interpretability , RLC
Sun, Y., Fujisawa, I., Juliani, A., Sakuma, J., & Kanai, R. (2025) , Remembering Transformer for Continual Learning , IJCNN 2025
Takatsuki, R., Joseph, S., Fujisawa, I., Kanai, R. (2025) , Decoding Vision Transformers: the Diffusion Steering Lens , Mechanistic Interpretability for Vision (MIV) Workshop at CVPR 2025
Cosentino, S. (2025) , Gender inequality in Japanese academia , Nature Reviews Electrical Engineering
Baltieri, M., Biehl, M., Capucci, M., & Virgo, N. (2025) , A Bayesian Interpretation of the Internal Model Principle , arXiv
Sun, Y., Ochiai, H., Wu, Z., Lin, S., & Kanai, R. (2025) , Associative transformer is a sparse representation learner , CVPR 2025
Sun, Y., Mi, L., Fujisawa, I., & Kanai, R. (2025) , MCM: Multi-layer Concept Map for Efficient Concept Learning from Masked Images , ICLR Workshop on Deep Generative Model in Machine Learning
Shivakanth, S., Nunziante, L., Ogawa Lillrank, D., Dossa, R. F. J., & Arulkumaran, K. (2025) , Improving Low-Cost Teleoperation: Augmenting GELLO with Force , 2025 IEEE/SICE International Symposium on System Integration
Yoshida, A., Dossa, R. F. J., Di Vincenzo, M., Sujit, S., Douglas, H., & Arulkumaran, K. (2025) , A Multi-User Multi-Robot Multi-Goal Multi-Device Human-Robot Interaction Manipulation Benchmark , Frontiers in Robotics and AI , 12
Kanai, R., Sun, Y., & Baltieri, M. (2025) , The Stream of Computation: Temporal Continuity as aMissing Ingredient for Artificial Consciousness , OSF
Baltieri, M., & Kanai, R. (2025) , Steam-engine naturalism , OSF
Kanai, R., Takatsuki, R., & Fujisawa, I. (2025) , Meta-representations as representations of processes , Neuroscience of Consciousness

2024

Juliani, A., Safron, A., & Kanai, R. (2024) , Deep CANALs: A Deep Learning Approach to Refining the Canalization Theory of Psychopathology , Neuroscience of Consciousness
Morales, P. A., & Castro-Villarreal, P. (2024) , Graphene shapes from quantum elasticity , Physical Review B , 110 (19) , 195430
Nakai, T., Constant-Varlet, C., & Prado, J. (2024) , Encoding models for developmental cognitive computational neuroscience: Promise, challenges, and potential , Developmental Cognitive Neuroscience , 70 , 101470
Torresan, F., & Baltieri, M. (2024) , Disentangled representations for causal cognition , Physics of Life Reviews , 51 , 343-381
Nakamura, D., Kaji, S., Kanai, R., & Hayashi, R. (2024) , Unsupervised method for representation transfer from one brain to another , Frontiers in Neuroinformatics , 18 , 1470845
Hagita, N., Kanai, R., Ishiguro, H., Minamizawa, K., Arai, F., Shimpo, F. Matsumura, T., & Yamanishi, Y. (2024) , Cybernetic Avatars: Teleoperation Technologies Applicable from In-body Monitoring to Social Interaction , Science Robotics
García-Marín, L. M., Campos, A. I., Diaz-Torres, S., Rabinowitz, J. A., Ceja, Z., Mitchell, B. L., Grasby, K. L., Thorp, J. G., Agartz, I., Alhusaini, S., Ames, D., Amouyel, P., Andreassen, O. A., Arfanakis, K., Arias-Vasquez, A., Armstrong, N. J., Athanasiu, L., Bastin, M. E., Beiser, A. S., Bennett, D. A., Bis, J. C., Boks, M. P. M., Boomsma, D. I., Brodaty, H., Brouwer, R. M., Buitelaar, J. K., Burkhardt, R., Cahn, W., Calhoun, V. D., Carmichael, O. T., Chakravarty, M., Chen, Q., Ching, C. R. K., Cichon, S., Crespo-Facorro, B., Crivello, F., Dale, A. M., Davey Smith, G., de Geus, E. J. C., De Jager, P. L., de Zubicaray, G. I., Debette, S., DeCarli, C., Depondt, C., Desrivières, S., Djurovic, S., Ehrlich, S., Erk, S., Espeseth, T., Fernández, G., Filippi, I., Fisher, S. E., Fleischman, D. A., Fletcher, E., Fornage, M., Forstner, A. J., Francks, C., Franke, B., Ge, T., Goldman, A. L., Grabe, H. J., Green, R. C., Grimm, O., Groenewold, N. A., Gruber, O., Gudnason, V., Håberg, A. K., Haukvik, U. K., Heinz, A., Hibar, D. P., Hilal, S., Himali, J. J., Ho, B. C., Hoehn, D. F., Hoekstra, P. J., Hofer, E., Hoffmann, W., Holmes, A. J., Homuth, G., Hosten, N., Ikram, M. K., Ipser, J. C., Jack, C. R., Jr., Jahanshad, N., Jönsson, E. G., Kahn, R. S., Kanai, R., Klein, M., Knol, M. J., Launer, L. J., Lawrie, S. M., Le Hellard, S., Lee, P. H., Lemaître, H., Li, S., Liewald, D. C. M., Lin, H., Longstreth, W. T., Jr., Lopez, O. L., Luciano, M., Maillard, P., Marquand, A. F., Martin, N. G., Martinot, J.-L., Mather, K. A., Mattay, V. S., McMahon, K. L., Mecocci, P., Melle, I., Meyer-Lindenberg, A., Mirza-Schreiber, N., Milaneschi, Y., Mosley, T. H., Mühleisen, T. W., Müller-Myhsok, B., Muñoz Maniega, S., Nauck, M., Nho, K., Niessen, W. J., Nöthen, M. M., Nyquist, P. A., Oosterlaan, J., Pandolfo, M., Paus, T., Pausova, Z., Penninx, B. W. J. H., Pike, G. B., Psaty, B. M., Pütz, B., Reppermund, S., Rietschel, M. D., Risacher, S. L., Romanczuk-Seiferth, N., Romero-Garcia, R., Roshchupkin, G. V., Rotter, J. I., Sachdev, P. S., Sämann, P. G., Saremi, A., Sargurupremraj, M., Saykin, A. J., Schmaal, L., Schmidt, H., Schmidt, R., Schofield, P. R., Scholz, M., Schumann, G., Schwarz, E., Shen, L., Shin, J., Sisodiya, S. M., Smith, A. V., Smoller, J. W., Soininen, H. S., Steen, V. M., Stein, D. J., Stein, J. L., Thomopoulos, S. I., Toga, A. W., Tordesillas-Gutiérrez, D., Trollor, J. N., Valdes-Hernandez, M. C., van ′t Ent, D., van Bokhoven, H., van der Meer, D., van der Wee, N. J. A., Vázquez-Bourgon, J., Veltman, D. J., Vernooij, M. W., Villringer, A., Vinke, L. N., Völzke, H., Walter, H., Wardlaw, J. M., Weinberger, D. R., Weiner, M. W., Wen, W., Westlye, L. T., Westman, E., White, T., Witte, A. V., Wolf, C., Yang, J., Zwiers, M. P., Ikram, M. A., Seshadri, S., Thompson, P. M., Satizabal, C. L., Medland, S. E., & Rentería, M. E. (2024) , Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries , Nature Genetics
Fujisawa, I., Nobe, S., Seto, H., Onda, R., Uchida, Y., Ikoma, H., Chien, P., & Kanai R. (2024) , ProcBench: Benchmark for Multi-Step Reasoning and Following Procedure , arXiv
Yamane, Y., Li, Y., Matsumoto, K., Kanai, R., Desforges, M., Gutierrez, C. E., & Doya K. (2024) , Optical Neuroimage Studio (OptiNiSt): intuitive, scalable, extendable framework for optical neuroimage data analysis , bioRxiv
Taniguchi, T., Takagi, S., Otsuka, J., Hayashi, Y., & Hamada, H. T. (2024) , Collective Predictive Coding as Model of Science: Formalizing Scientific Activities Towards Generative Science , arXiv
Aguilera, M., Morales, P. A., Rosas, F. E., & Shimazaki, H. (2024) , Explosive neural networks via higher-order interactions in curved statistical manifolds , arXiv
Sato, M., Tomeoka, K., Horiguchi, I., Arulkumaran, K., Kanai, R., & Sasai S. (2024) , Scaling Law in Neural Data: Non-Invasive Speech Decoding with 175 Hours of EEG Data , arXiv
Nishida, S., Hamada, H. T., Niikawa, T., & Miyahara, K. (2024) , Neural correlates of phenomenological attitude toward perceptual experience , bioRxiv
Nakai, T., Tirou, C., & Prado, J. (2024) , From brain to education through machine learning: Predicting literacy and numeracy skills from neuroimaging data , Imaging Neuroscience , 2 , 1-24
Pham, T. Q., Tran, H. X., Ly, H. H., Ishizuka, H., & Chikazoe, J. (2024) , Decoding passive tactile shape from functional MRI signals , zenodo
Torresan, F., & Baltieri, M. (2024) , Disentangled Representations for Causal Cognition , arXiv
Kanai, R., & Fujisawa, I. (2024) , Toward a universal theory of consciousness , Neuroscience of Consciousness , 2024 (1)
Dossa, R. F. J., Arulkumaran,K., Juliani, A., Sasai, S., & Kanai, R. (2024) , Design and Evaluation of a Global Workspace Agent Embodied in a Realistic Multimodal Environment , Frontiers in Computational Neuroscience , 18
Hamada, H. T., Abe, Y., Tanaka, N., Taira, M., Tanaka, K. F., & Doya, K. (2024) , Optogenetic activation of dorsal raphe serotonin neurons induces brain-wide activation , nature communications
Taguchi, T., Kitazono, J., Sasai, S., & Oizumi, M. (2024) , Association of bidirectional network cores in the brain with conscious perception and cognition , bioRxiv
Constant-Vararlet, C., Nakai, T., & Prado, J. (2024) , Intergenerational transmission of brain structure and function in humans: a narrative review of designs, methods, and findings , Brain Structure and Function
Sato, M., Kabe, Y., Nobe, S., Yoshida, A., Inoue, M., Shimizu, M., Tomeoka., K., & Sasai, S. (2024) , Delineating neural contributions to electroencephalogram-based speech decoding , bioRxiv
Yoshida, A., Dossa, R. F. J., Sujit, S., Arulkumaran, K., Vincenzo, M. D., & Kuwabara, M. (2024) , The Extensible Multi-Robot Multi-Goal Manipulation Benchmark for Human-Robot Interfaces , Supervised Autonomy Workshop
Arulkumaran, K., Vincenzo, M. D., Dossa R. F. J., Akiyama, S., Lillrank, D. O., Sato, M., Tomeoka, K., & Sasai, S. (2024) , A Comparison of Visual and Auditory EEG Interfaces for Robot Multi-stage Task Control , Frontiers in Robotics and AI , 11
Sun, Y., Fujisawa, I., Juliani, A., Sakuma, J., & Kanai, R. (2024) , Remembering Transformer for Continual Learning , arXiv
Akiyama, S., Dossa, R. F. J., Arulkumaran, K., Sujit, S., & Johns, E. (2024) , Open-loop VLM Robot Planning: An Investigation of Fine-tuning and Prompt Engineering Strategies , Navigation and Manipulation Workshop
Morales, P. A., & Castro-Villarreal, P. (2024) , Emergent Elastic Surfaces from Two-Dimensional Dirac Materials , arXiv
Nakai, T., Kubo, R., & Nishimoto, S. (2024) , Cortical representational geometry of diverse tasks reveals subject-specific and subject-invariant cognitive structures , bioRxiv
Kanai, R., Takatsuki, R., & Fujisawa, I. (2024) , Meta-Representations as Representations of Processes , PsyArXiv
Kuwabara, M., & Kanai, R. (2024) , Stimulation technology for brain and nerves, now and future , arXiv
Hamada, H. T. (2024) , 分散型科学が拓く新たなエコシステム：DeSci.Tokyoが果たす役割 , 情報の科学と技術 , 74 (3) , 86-91
Arulkumaran, K., & Lillrank, D. O. (2024) , A Pragmatic Look at Deep Imitation Learning , Asian Conference on Machine Learning , 58-73
Juliani, A., Safron, A., & Kanai, R. (2024) , Deep CANALs: A Deep Learning Approach to Refining the Canalization Theory of Psychopathology , Neuroscience of Consciousness

2023

Baltieri, M., Iizuka, H., Witkowski, O., Sinapayen, L., & Suzuki, K. (2023) , Hybrid Life: Integrating Biological, Artificial, and Cognitive Systems , WIREs Cognitive Science
Kamiya, S., Kawakita, D., Sasai, S., Kitazono, J., & Oizumi, M. (2023) , Optimal Control Costs of Brain State Transitions in Linear Stochastic Systems , Journal of Neuroscience , 43 , 270-281
Marshall, W., Grasso, M., Mayner, W. G. P., Zaeemzadeh, A., Barbosa, S. L., Chastain, E., Findlay, G., Sasai, S., Albantakis, L., & Tononi, G. (2023) , System Integrated Information , Entropy , 25 (2) , 335
Albantakis, L., Barbosa, L., Findlay, D., Grasso, M., Haun, M. A., Marshall, W., Mayner, W. G. P., Zaeemzadeh, A., Boly, M., Juel, E. B., Sasai, S., Fujii, K., David, I., Hendren, J., Lang, P. J., & Tononi, G. (2023) , Integrated information theory (IIT) 4.0: Formulating the properties of phenomenal existence in physical terms , PLoS Computational Biology
Morales, P. A., & Copinger, P. (2023) , Curvature-induced pseudogauge fields from time-dependent geometries in graphene , PHYSICAL REVIEW B , 107 (7) , 75432
Oka, T., Takashima, K., Ueda, K., Mori, Y., Sasaki, K., Hamada, H. T., Yamagata, M., & Yamada, Y. (2023) , Autonomous, bidding, credible, decentralized, ethical, and funded (ABCDEF) publishing , F1000Research
Murakami, S., Dan, K., Seo, T., Yamazaki, T., Cho, M., Higuchi, M., Matsuyoshi, D., Kanai, R., Aizawa, Y., & Yamada, M. (2023) , A human machine interface suggested from neuroscientific analysis of human factor , 27th International Technical Conference on the Enhanced Safety of Vehicles (ESV) , 122 (33) , e2421528122
Morales, P. A., Korbel, J., & Rosas, F. E. (2023) , Geometric Structures Induced by Deformations of the Legendre Transform , Entropy , 25 (4) , 678
Hata, J., Nakae, K., Tsukada, H., Woodward, A., Haga, Y., Iida, M., Uematsu, A., Seki, F., Ichinohe, N., Gong, R., Kaneko, T., Yoshimaru, D., Watakabe, A., Abe, H., Tani, T., Hamada, H.T., Gutierrez, C.E., Skibbe, H., Maeda, M., Papazian, F., Hagiya, K., Kishi, N., Ishii, S., Doya, K., Shimogori, T., Yamamori, T., Tanaka, K., Okano H.J., & Okano, H. (2023) , Multi-modal brain magnetic resonance imaging database covering marmosets with a wide age range , Scientific Data , 10 , 1-8
Morales, P. A., Korbel, J., & Rosas, F. E. (2023) , Thermodynamics of exponential Kolmogorov-Nagumo averages , New Journal of Physics - IOPscience
Koyama, Y., Yamamoto, T., Hirayama, J., Jimura, K., Sadato, N., & Chikazoe, J. (2023) , Cognitive Dynamics Estimation: A whole-brain spatial regression paradigm for extracting the temporal dynamics of cognitive processes , bioRxiv
Denk, I. T., Takagi, Y., Matsuyama, T., Agostinelli, A., Nakai, T., Frank, C., & Nishimoto, S. (2023) , Brain2music: Reconstructing music from human brain activity , arXiv
Nakai, T., & Prado, J. (2023) , From brain to education through machine learning: Predicting literacy and numeracy skills from neuroimaging data , PsyArXiv
Lillrank, D. O., Akiyama, S., & Arulkumaran, K. (2023) , Zero-Shot Object Manipulation with Semantic 3D Image Augmentation for Perceiver-Actor ,
Akiyama, S., Lillrank, D. O., & Arulkumaran, K. (2023) , Fine-Grained Object Detection and Manipulation with Segmentation-Conditioned Perceiver-Actor , ICRA2023 Workshop on Pretraining for Robotics (PT4R)
Kawamoto, M., Takagishi, H., Ishihara, T., Takagi, S., Kanai, R., Sugihara, G., Takahashi, H., & Matsuda, T. (2023) , Hippocampal volume mediates the relationship of parental rejection in childhood with social cognition in healthy adults , Scientific Reports , 13
Sun, Y., Ochiai, H., Wu, Y., Lin, S., & Kanai, R. (2023) , Associative Transformer is a Sparse Representation Learner , arXiv
Pham, T. Q., Matsui, T., & Chikazoe, J. (2023) , Evaluation of the Hierarchical Correspondence between the Human Brain and Artificial Neural Networks , MDPI , 12 (10) , 1330
Kanai, R., & Fujisawa, I. (2023) , Toward a Universal Theory of Consciousness , PsyArXiv
Hamada, H. T. (2023) , 研究開発における新たな科学運営モデル , Jxiv, JST
Matsumoto, D., & Nakai, T. (2023) , Syntactic theory of mathematical expressions , Cognitive Psychology | Journal | ScienceDirect.com by Elsevier , 146
Sato, A., Chikazoe, J., Funai, S., Mochihashi, D., Shikano, Y., Asahara, M., Iso, S., & Kobayashi, I. (2023) , Investigation of Information Processing Mechanisms in the Human Brain During Reading Tanka Poetry , Springer Nature Switzerland , 407-418
Copinger, P. , & Morales, P. A. (2023) , Emergent spacetime from a Berry-inspired dynamical gauge field coupled to electromagnetism , Physical Review D , 108 (6)
Lee, D. H., & Chikazoe, J. (2023) , A clearing in the objectivity of aesthetics? , Frontiers in Neuroimaging
Saito, Y., Kamagata, K., Akashi, T., Wada, A., Shimoji, K., Hori, M., Kuwabara, M., Kanai, R., & Aoki, S. (2023) , Review of Performance Improvement of a Noninvasive Brain-computer Interface in Communication and Motor Control for Clinical Applications , Juntendo Medical Journal , 69 (4) , 319-326
Negi, R., Yoshida, A., Kuwabara, M., & Kanai, R. (2023) , A Deep Learning Approach to Detecting Temporal Characteristics of Cortical Regions , bioRxiv
Butlin, P., Long, R., Elmoznino, E., Bengio, Y., Birch, J., Constan, A., Deane,G., Fleming, S. M., Frith, C., Ji, X., Kanai, R., Klein, C., Lindsay, G., Michel, M., Mudrik, L., Peters, M. A. K., Schwitzgebel, E., Simon, J., & VanRullen, R. (2023) , Consciousness in Artificial Intelligence: Insights from the Science of Consciousness , arXiv
Gallotta, R., Arulkumaran, K., & Soros, L. B. (2023) , Preference-Learning Emitters for Mixed-Initiative Quality-Diversity Algorithms , IEEE Transactions on Games , 16 (2) , 303 - 316

2022

Song, C., Sandberg, K., Rutiku, R., & Kanai, R. (2022) , Linking human behaviour to brain structure: further challenges and possible solutions , Nature Reviews Neuroscience
Juliani, A., Kanai, R., & Sasai, S. (2022) , The Perceiver Architecture is a Functional Global Workspace , Proceedings of the Annual Meeting of the Cognitive Science Society , 44
Chikazoe, J. (2022) , Refining the negative into general and specific , Nature Neuroscience , 25 , 678–683
Youssef, M. M. M., Hamada, H. T., Lai, E. S. K., Kiyama, Y., Tabbal, M. E., Kiyonari, H., Nakano, K., Kuhn, B., & Yamamoto, T. (2022) , TOB is an effector of the hippocampus-mediated acute stress response , Translational Psychiatry , 12 (302)
Gallotta, R., Arulkumaran, K., & Soros, L. B. (2022) , Surrogate Infeasible Fitness Acquirement FI-2Pop for Procedural Content Generation , IEEE Conference on Games
Juliani, A., Arulkumaran, K., Sasai, S., & Kanai, R. (2022) , On the link between conscious function and general intelligence in humans and machines , Transactions on Machine Learning Research
Kawakita, G., Kamiya, S., Sasai, S., Kitazono, J., & Oizumi, M. (2022) , Quantifying brain state transition cost via Schrödinger’s bridge , Network Neuroscience , 6 (1) , 118–134
Niikawa, T., Miyahara, K., Hamada, H. T., & Nishida, S. (2022) , Functions of consciousness: conceptual clarification , Neuroscience of Consciousness , 2022 (1)
Arulkumaran, K., Ashley, D. R., Schmidhuber, J., & Srivastava, R. K. (2022) , All You Need Is Supervised Learning: From Imitation Learning to Meta-RL With Upside Down RL , Multi-disciplinary Conference on Reinforcement Learning and Decision Making
Ashley, D. R., Arulkumaran, K., Schmidhuber, J., & Srivastava, R. K. (2022) , Learning Relative Return Policies With Upside-Down Reinforcement Learning , Multi-disciplinary Conference on Reinforcement Learning and Decision Making
Galotta, R., Arulkumaran, K., & Soros, L. B. (2022) , Evolving Spaceships with a Hybrid L-system Constrained Optimisation Evolutionary Algorithm , Genetic and Evolutionary Computation Conference
Arulkumaran, K., & Nguyen-Phuoc, T. (2022) , Minimal Criterion Artist Collective , Genetic and Evolutionary Computation Conference
Morales, P. A., Korbel, J., & Rosas, F. E. (2022) , Ode to Legendre: Geometric and thermodynamic implications on curved statistical manifolds , arXiv
Hamada, H. T., & Kanai, R. (2022) , AI agents for facilitating social interactions and wellbeing , arXiv
Yoshimoto, T., Okazaki, S., Sumiya, M., Takahashi, K. H., Nakagawa, E., Koike, T., Kitada, R., Okamoto, S., Nakata, M., Yada, T., Kosaka, H., Sadato, N., & Chikazoe, J. (2022) , Coexistence of sensory qualities and value representations in human orbitofrontal cortex , Neuroscience Research , 180 , 48-57
Matsui, T., Pham, T. Q., Jimura,K., & Chikazoe, J. (2022) , On co-activation pattern analysis and non-stationarity of resting brain activity , NeuroImage , 249 , 118904
Matsui, T., Taki, M., Pham, T. Q., Chikazoe, J., & Jimura, K. (2022) , Counterfactual Explanation of Brain Activity Classifiers using Image-to-Image Transfer by Generative Adversarial Network , Frontiers in Neuroinformatics , 15
Dai, T., Arulkumaran, K., Gerbert, T., Tukra, S., Behbahani, F., & Bharath, A. A. (2022) , Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation , Neurocomputing , 493 , 143-165
Langdon, A., Botvinick, M., Nakahara, H., Tanaka, K., Matsumoto, M., & Kanai, R. (2022) , Meta-learning, social cognition and consciousness in brains and machines , Neural Networks , 145 , 80-89
Hamada, H. T., Matsuyoshi, D., & Kanai, R. (2022) , Gray matter analysis of MRI images: Introduction to current research practice , Encyclopedia of Behavioral Neuroscience , 2 , 84-96
Terai, A., Yamamura, N., Chikazoe, J., Yoshimoto, T., Sadato, N., & Jimura, K. (2022) , On the role of shape features in metaphor generation for abstract images , 2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS) , 1-5
Fordson H. P., Gardhouse, K., Cicero, N., Chikazoe ,J. Anderson, A., & Derosa, E. (2022) , A Novel Deep Learning Based Emotion Recognition Approach to well Being from Fingertip Blood Volume Pulse , 2022 International Conference on Machine Learning and Cybernetics (ICMLC) , 130-137
Pham, T. Q., Ly H. H., Hiroki, I., & Chikazoe, J. (2022) , Design of an fMRI-compatible pneumatic tactile array for spatiotemporal stimulation , 2022 61st Annual Conference of the Society of Instrument and Control Engineers (SICE) , 1343-1346
Shintaki, R., Tanaka, D., Suzuki, S., Yoshimoto, T., Sadato, N., & Chikazoe, J. (2022) , Subjectivity of time perception alters choice preference for future rewards through fronto-striatal value signal dynamics , bioRxiv
Hamada, H. T., Abe, Y., Takata, N., Taira, M., Tanaka, K. F., & Doya, K. (2022) , Optogenetic activation of dorsal raphe serotonin neurons induces a brain-wide response in reward network , bioRxiv
Morales, P. A., & Copinger, P. (2022) , Curvature induced pseudo-gauge fields from time-dependent geometries in graphene , arXiv
Hamada, H. T. (2022) , Web3テクノロジーによるサイエンスの再設計の動き : 分散型サイエンスの誕生と課題 , Jxiv
Bruineberg, J., Dołęga, K., Dewhurst, J., & Baltieri, M. (2022) , The Emperor Is Naked: Replies to commentaries on the target article , Behavioral and Brain Sciences , 45 , e219
Fermin, A. S. R., Kiyonari, T., Matsumoto, Y., Takagishi, H., Li, Y., Kanai, R., Sakagami, M., Akaishi, R., Ichikawa,N., Takamura, M., Yokoyama, S., Machizawa, M. G., Chan, H., Matani, A., Yamawaki, S., Okada, G., Okamoto, Y., & Yamagishi, T. (2022) , The neuroanatomy of social trust predicts depression vulnerability , Scientific Reports , 12 , 16724
Fujisawa, I., & Kanai, R. (2022) , Logical Tasks for Measuring Extrapolation and Rule Comprehension , arXiv

2021

Bruineberg, J.,Dolega, K., Dewhurst, J., & Baltieri, M. (2021) , The Emperor's New Markov Blankets , Behavioral and Brain Sciences
Shintaki, R., Tanaka, D., Suzuki, S., Yoshimoto, T., Sadato, N., & Chikazoe, J. (2021) , Anticipatory dynamics in the human brain guide foraging for primary rewards , bioRxiv
Tsumura, K., Shintaki, R., Takeda, M., Chikazoe, J., Nakahara, K., & Jimura, K. (2021) , Perceptual uncertainty alternates top-down and bottom-up fronto-temporal network signaling during response inhibition , The Journal of Neuroscience , 42 (22) , 4567-4579
Pham, T. Q., Nishiyama, S., Sadato, N., & Chikazoe, J. (2021) , Distillation of Regional Activity Reveals Hidden Content of Neural Information in Visual Processing , Frontiers in Human Neuroscience
Highnam, K., Arulkumaran, K., Hanif, Z., & Jennings, N. R. (2021) , BETH Dataset: Real Cybersecurity Data for Anomaly Detection Research , Conference on Applied Machine Learning for Information Security
Morales, P. A., & Rosas, F. E. (2021) , Generalization of the maximum entropy principle for curved statistical manifolds , Phys. Rev. Research , 3 (3) , 33216
Dai, T., Liu, H., Arulkumaran, K., Ren, G., & Bharath, A. A. (2021) , Diversity-Based Trajectory and Goal Selection with Hindsight Experience Replay , Pacific Rim International Conference on Artificial Intelligence , 32–45
Matsumoto, K., Tamai, S., & Kanai, R. (2021) , Goal-Directed Planning by Predictive-Coding based Variational Recurrent Neural Network from Small Training Samples , IEEE International Conference on Development and Learning , 1‐6
Massari, F., Biehl, M., Meeden, L. & Kanai, R. (2021) , Experimental Evidence that Empowerment May Drive Exploration in Sparse-Reward Environments , IEEE International Conference on Development and Learning , 1‐6
VanRullen, R., & Kanai, R. (2021) , Deep learning and the Global Workspace Theory , Trends Neurosci , 44 (9) , 692‐704
Morales, P. A., & Rosas, F.E. (2021) , A generalization of the maximum entropy principle for curved statistical manifolds , Physical Review Research , 33 , 33216
Biehl, M., Pollock, F., & Kanai, R. (2021) , A Technical Critique of Some Parts of the Free Energy Principle , Entropy , 23 (3) , 293
Copinger, P., & Morales, P. (2021) , Schwinger pair production in SL(2,C) topologically nontrivial fields via non-Abelian worldline instantons , Physical Review D , 103 , 36004
Arulkumaran, K., & Lillrank, D. O. (2021) , A Pragmatic Look at Deep Imitation Learning , arXiv
Shintaki, R., Tanaka, D., Suzuki, S., Yoshimoto, T., Sadato, N., & Chikazoe, J. (2021) , Human foraging for primary rewards is guided by fronto-hippocampal dynamics of anticipation , bioRxiv
Shintaki, R., Tanaka, D., Suzuki, S., Yoshimoto, T., Sadato, N., & Chikazoe, J. (2021) , Continuous decision to wait for a future reward is guided by fronto-hippocampal anticipatory dynamics , bioRxiv
Virgo N., Biehl M., & McGregor, S. (2021) , Interpreting Dynamical Systems as Bayesian Reasoners , Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML PKDD 2021. Communications in Computer and Information Science , 1524

2020

Rosas, F. E., Mediano, P. A. M., Biehl, M., Chandaria, S., & Polani, D. (2020) , Causal Blankets: Theory and Algorithmic Framework , International Workshop on Active Inference (IWAI) 2020: Active Inference, 187-198 , 187–198
Biehl, M., & Kanai, R. (2020) , Dynamics of a Bayesian Hyperparameter in a Markov Chain , International Workshop on Active Inference (IWAI) 2020: Active Inference, 35-41 , 35–41
Biehl, M., & Kanai, R. (2020) , Non-trivial informational closure of a Bayesian hyperparameter , IEEE Symposium on Artificial Life (IEEE ALIFE)
Yoshimoto, T., Okazaki, S., Sumiya, M., Takahashi, K. H., Nakagawa, E., Koike, T., Kitada, R., Okamoto, S., Nakata, M,. Yada, T., Kosaka, H., Sadato, N., & Chikazoe, J. (2020) , A new experimental phenomenological method to explore the subjective features of psychological phenomena: its application to binocular rivalry , Neuroscience of Consciousness , 2020 (1) , niaa018
Abe, Y., Takata, N., Sakai, Y., Hamada, H. T., Hiraoka Y., Aida, T., Tanaka, K., Le Bihan, D., Doya, K., & Tanaka, K. F. (2020) , Diffusion functional MRI reveals global brain network functional abnormalities driven by targeted local activity in a neuropsychiatric disease mouse model , NeuroImage , 223 , 117318
Kitazono, J., Kanai, R., & Oizumi, M. (2020) , Efficient search for informational cores in complex systems: Application to brain networks , Neural Networks , 132 , 232-244
Chang, A. Y. C., Biehl, M., Yu, Y., & Kanai, R. (2020) , Information Closure Theory of Consciousness , Frontiers in Psychology , 11 , 1504
Miyahara, K., Niikawa, T., Hamada, H. T., & Nishida, S. (2020) , Developing a short-term phenomenological training program: A report of methodological lessons. , New Ideas in Psychology , 58 , 100780
Grasby, K. L., Jahanshad, N., Painter, J. N., Colodro-Conde, L., ., …, Kanai, R., …, Thompson, P. M., & Medland, S. E. (2020) , The genetic architecture of the human cerebral cortex , Science , 367 (6484) , eaay6690
Kumrai, T., Korpela, J., Maekawa, T., Yu, Y., & Kanai, R. (2020) , Human Activity Recognition with Deep Reinforcement Learning using the Camera of a Mobile Robot , 2020 IEEE International Conference on Pervasive Computing and Communications , 125-134
Eguchi, A., Horii, T., Nagai, T., Kanai, R., & Oizumi, M. (2020) , An Information Theoretic Approach to Reveal the Formation of Shared Representation , Frontiers in Computational Neuroscience , 14 (1)
Mao, Y., Kanai, R., Ding, C., Bi, T., & Qiu, J. (2020) , Temporal variability of brain networks predicts individual differences in bistable perception , Neuropsychologia , 142 , 107426

2019

Satizabal, C. L., Adams, H. H. H., Hibar, D. P., White, C. C., …, Kanai, R., …, & Ikram, M. A. (2019) , Genetic architecture of subcortical brain structures in 38,851 individuals , Nature Genetics , 51 , 1624-1636
Kanai, R., Chang, A., Yu, Y., Magrans de Abril, I., Biehl, M., & Guttenberg, N. (2019) , Information generation as a functional basis of consciousness , Neuroscience of Consciousness , 5 (1) , niz016
Protopapa, F., Hayashi, M. J., van der Zwaag, D., Battistella, G., Murray, M. M., Kanai, R., & Bueti, D. (2019) , Chronotopic maps in human supplementary motor area , PLoS Biology , 17 (3) , e3000026

2018

Magrans de Abril, I., & Kanai, R. (2018) , A unified strategy for implementing curiosity and empowerment driven reinforcement learning , arXiv
Guttenberg, N., & Kanai, R. (2018) , Learning to generate classifiers , arXiv
Yu, Y., Chang, A., & Kanai, R. (2018) , Boredom-Driven Curious Learning by Homeo-Heterostatic Value Gradient , Frontiers in Neurorobotics , 12 , 88
Hayashi, M., van der Zwaag, W., Bueti, D., & Kanai, R. (2018) , Representations of time in human frontoparietal cortex , Communications Biology , 1 (1) , 233
Hidaka, S., & Oizumi, M. (2018) , Fast and exact search for the partition with minimal information loss , PLoS One , 13 (9) , e0201126
Magrans de Abril, I., & Kanai, R. (2018) , Curiosity-Driven Reinforcement Learning with Homeostatic Regulation , 2018 International Joint Conference on Neural Networks (IJCNN) , 1-6
Amari, S., Karakida, R., & Oizumi, M. (2018) , Information geometry connecting Wasserstein distance and Kullback–Leibler divergence via the entropy-relaxed transportation problem , Information Geometry , 1 , 13-37
Guttenberg, N., Biehl, M., Virgo, N., & Kanai, R. (2018) , Being curious about the answers to questions: novelty search with learned attention , Artificial Life Conference Proceedings , 30 , 518-525
Biehl, M. (2018) , Geometry of Friston’s active inference , arXiv
Biehl, M., Guckelsberger, C., Salge, C., Smith, S. C., & Polani, D. (2018) , Expanding the Active Inference Landscape: More Intrinsic Motivations in the Perception-Action Loop , Frontiers in Neurorobotics , 12 , 45
Mori, H., & Oizumi, M. (2018) , Information integration in a globally coupled chaotic system , Entropy , 384-385
Kitazono, J., Kanai, R., & Oizumi, M. (2018) , Efficient Algorithms for Searching the Minimum Information Partition in Integrated Information Theory , Entropy , 20 (3) , 173

2017

Mizutani, H., & Kanai, R. (2017) , A description length approach to determining the number of k-means clusters , arXiv
Guttenberg, N., Yu, Y., & Kanai, R. (2017) , Counterfactual Control for Free with Generative Models , arXiv
Guttenberg, N., Biehl, M., & Kanai, R. (2017) , Learning body-affordances to simplify action spaces , arXiv
Haun, A. M., Oizumi, M., Kovach, C. K., Kawasaki, H., Oya, H., Howard, M. A., Adolphs, R., & Tsuchiya, N. (2017) , Conscious Perception as Integrated Information Patterns in Human Electrocorticography , eNeuro , 4 (5) , 0085-17
Magrans de Abril, I., & Kanai, R. (2017) , Intrinsically-motivated reinforcement learning for control with continuous actions , 2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) , 212-214
Tajima, S., & Kanai, R. (2017) , Integrated information and dimensionality in continuous attractor dynamics , Neuroscience of Consciousness , 2017 (1) , nix011
Biehl, M., & Polani, D. (2017) , Action and perception for spatiotemporal patterns , Proceedings of ECAL 2017 the 14th European Conference on Artificial Life , 14 , 68–75
Biehl, M., Ikegami, T., & Polani, D. (2017) , Specific and Complete Local Integration of Patterns in Bayesian Networks , Entropy , 19 (5) , 230
Otten, M., Pinto, Y., Paffen, C. L. E., Seth, A. K., & Kanai, R. (2017) , The Uniformity Illusion: Central Stimuli Can Determine Peripheral Perception , Psychological Science , 28 (1) , 56–68

2016

Guttenberg, N., Virgo, N., Witkowski, O., Aoki, H., & Kanai, R. (2016) , Permutation-equivariant neural networks applied to dynamics prediction , arXiv
Guttenberg, N., Biehl, M., & Kanai, R. (2016) , Neural Coarse-Graining: Extracting slowly-varying latent degrees of freedom with neural networks , arXiv
Wiener, M., & Kanai, R. (2016) , Frequency tuning for temporal perception and prediction , Current Opinion in Behavioral Sciences , 8 , 1-6
Oizumi, M., Yanagawa, T., Amari, S., Fujii, N., & Tsuchiya, N. (2016) , Measuring Integrated Information from the Decoding Perspective , PLoS Computational Biology , 12 (11) , e1004654
Sherman, M. T., Seth, A. K., & Kanai, R. (2016) , Predictions Shape Confidence in Right Inferior Frontal Gyrus , Journal of Neuroscience , 36 , 10323-10336

2015

Kanai, R. (2015) , Neuroprofile: a web-based service for personalized neuroprediction from anatomical brain scans , UbiComp '15: The 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing , 915–918