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    • Data for Brain Reference Architecture of YS24 Longitudinally Segmented Distal CA1 and Periphery

      Yudai Suzuki, Yoshiko Honda, Shinya Ohara, Ayako Fukawa, Hiroshi Yamakawa

      1st. Int. Whole Brain Architecture Workshop, vol.1, num.1, WBA-WS-001-01, July 2024.

    • BRAES: Developing a Brain Reference Architecture Editorial System for Accumulating Hypotheses on Neural Functionality

      Yoshimasa Tawatsuji, Yuta Ashihara, Naoya Arakawa, Hiroshi Yamakawa

      INCF Neuroinformatics Assembly, 517. September 2023

    • Proposing a Database Extracting Anatomical Structures from Neuroscience Literature and Evaluating Its Information Credibility

      Yuta Ashihara, Hiroshi Yamakawa, Iriya Horiguchi

      INCF Neuroinformatics Assembly, 518.

    • BDBRA: Database for extracting descriptions of neural projections and brain regions from neuroscience literature with dialogue prompts

      Yuta Ashihara, Hiroshi Yamakawa, Iriya Horiguchi, Yutaka Matsuo

      Computational Neuroscience, P128. 2023.

    • Proposal of a function-oriented SCID method for reverse engineering a wide range of brain regions

      Hiroshi Yamakawa, Ayako Fukawa, Naoya Arakawa, Yoshimasa Tawatsuji, Yuta Ashihara , Yutaka Matsuo

      Computational Neuroscience, P127. 2023

    • Whole Brain Architecture Approach for AGI development

      Hiroshi Yamakawa

      Japan AI Alignment Conference

    • Investigating the anatomy and computational models of the cerebral cortex

      Yoshimasa Tawatsuji, Yudai Suzuki, Hiroshi Yamakawa

      The 1st International Symposium of “Biology of Behavior Change”

    • Design Methodology for Information Processing Architecture Learned from the Brain

      Hiroshi Yamakawa

      3rd International Symposium & Young Investigator Symposium on Brain Information Dynamics

    • 全脳アーキテクチャ ─ 機能を理解しながら脳型AIを設計・開発する ─. in 認知科学講座4 心をとらえるフレームワークの展開 (編集 横澤一彦) 209–249

      山川 宏

      東京大学出版会

    • Hippocampal formation-inspired probabilistic generative model

      Taniguchi, A., Fukawa, A., & Yamakawa,H

      Neural Networks: The Official Journal of the International Neural Network Society.(2022)