An in silico learning model with pathological intrinsic synaptic dynamics

• Project Area: Constructive understanding of multi-scale dynamism of neuropsychiatric disorders
• Project/Area Number: 18H05432
• Research Category: Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)
• Allocation Type: Single-year Grants
• Review Section: Biological Sciences
• Research Institution: Institute of Physical and Chemical Research
• Principal Investigator: Toyoizumi Taro 国立研究開発法人理化学研究所, 脳神経科学研究センター, チームリーダー (50547461)
• Project Period (FY): 2018-06-29 – 2023-03-31
• Project Status: Completed (Fiscal Year 2022)
• Budget Amount: ¥49,140,000 (Direct Cost: ¥37,800,000、Indirect Cost: ¥11,340,000); Fiscal Year 2022: ¥9,620,000 (Direct Cost: ¥7,400,000、Indirect Cost: ¥2,220,000); Fiscal Year 2021: ¥9,620,000 (Direct Cost: ¥7,400,000、Indirect Cost: ¥2,220,000); Fiscal Year 2020: ¥9,620,000 (Direct Cost: ¥7,400,000、Indirect Cost: ¥2,220,000); Fiscal Year 2019: ¥9,620,000 (Direct Cost: ¥7,400,000、Indirect Cost: ¥2,220,000); Fiscal Year 2018: ¥10,660,000 (Direct Cost: ¥8,200,000、Indirect Cost: ¥2,460,000)
• Keywords: シナプスゆらぎ / スパイン / セルアセンブリ / 記憶 / 主体感 / インテンショナルバインディング / 報酬予測誤差 / プロスペクト理論 / 意思決定モデル / 脳内シミュレーション / 意思決定 / 順次的予期 / 行動経済学 / 順列的神経活動パターン / 非合理的行動 / リスク / ストレス / 予測誤差 / 行動変容 / 学習 / 自閉症 / シナプス動態 / 数理モデル / モデリング / 神経回路 / シナプス可塑性 / スパイン揺らぎ / スパイン体積分布

Outline of Final Research Achievements

Synapses in the brain undergo constant remodeling even in the absence of activity-dependent changes. We moded intrinsic synaptic dynamics in wild-type mice as well as in a mouse model of fragile X syndrome (FXS). Intrinsic dynamics suppressed the expansion of cell assemblies, thereby maintaining memories stably in the wild-type model. In contrast, too strong intrinsic dynamics in the FXS model prevented the formation of cell assemblies, causing delayed learning.

Academic Significance and Societal Importance of the Research Achievements

脳のシナプスの学習則としてはヘッブ型の可塑性がよく知られている。しかし、共に活動するニューロン間のシナプスが強化されるヘッブ型可塑性の帰結として、大きなセルアセンブリが新しいニューロンを取り込んでより大きく拡大し、過度な神経活動の同期を生じる問題点が指摘されていた。本モデル研究によって正常なシナプスゆらぎがその拡大を抑えて記憶の安定に寄与し得ること、自閉症様のシナプスゆらぎが学習遅滞を説明することが分かった。本研究は正常脳と病態脳の学習の理解に貢献すると考えられる。

Research Products

• [Int'l Joint Research] Beloit College(米国)
• [Int'l Joint Research] University of Strathclyde(英国)
• [Journal Article] Information maximization explains state-dependent synaptic plasticity and memory reorganization during non-rapid eye movement sleep (2023)
  • Author(s): Yoshida Kensuke、Toyoizumi Taro
  • Journal Title: PNAS Nexus Volume: 2 Issue: 1 Pages: 1-13
  • DOI: 10.1093/pnasnexus/pgac286
  • Peer Reviewed / Open Access
• [Journal Article] Progressive Interpretation Synthesis: Interpreting Task Solving by Quantifying Previously Used and Unused Information (2023)
  • Author(s): He Zhengqi、Toyoizumi Taro
  • Journal Title: Neural Computation Volume: 35 Issue: 1 Pages: 38-57
  • DOI: 10.1162/neco_a_01542
  • Peer Reviewed / Open Access
• [Journal Article] Ordering in heterogeneous connectome weights for visual information processing (2022)
  • Author(s): Toyoizumi Taro
  • Journal Title: Proceedings of the National Academy of Sciences Volume: 119 Issue: 48
  • DOI: 10.1073/pnas.2216092119
  • Peer Reviewed
• [Journal Article] Decoding silence in free recall (2022)
  • Author(s): Fumarola Francesco、He Zhengqi、Kusmierz Lukasz、Toyoizumi Taro
  • Journal Title: Physical Review Research Volume: 4 Issue: 3 Pages: 033089-033089
  • DOI: 10.1103/physrevresearch.4.033089
  • Peer Reviewed / Open Access / Int'l Joint Research
• [Journal Article] Computational roles of intrinsic synaptic dynamics (2021)
  • Author(s): Shimizu Genki、Yoshida Kensuke、Kasai Haruo、Toyoizumi Taro
  • Journal Title: Current Opinion in Neurobiology Volume: 70 Pages: 34-42
  • DOI: 10.1016/j.conb.2021.06.002
  • Peer Reviewed / Open Access
• [Journal Article] Spine dynamics in the brain, mental disorders and artificial neural networks (2021)
  • Author(s): Kasai Haruo、Ziv Noam E.、Okazaki Hitoshi、Yagishita Sho、Toyoizumi Taro
  • Journal Title: Nature Reviews Neuroscience Volume: 22 Issue: 7 Pages: 407-422
  • DOI: 10.1038/s41583-021-00467-3
  • Peer Reviewed / Open Access
• [Journal Article] Dimensionality reduction to maximize prediction generalization capability (2021)
  • Author(s): Isomura Takuya、Toyoizumi Taro
  • Journal Title: Nature Machine Intelligence Volume: 3 Issue: 5 Pages: 434-446
  • DOI: 10.1038/s42256-021-00306-1
  • Peer Reviewed
• [Journal Article] On the Achievability of Blind Source Separation for High-Dimensional Nonlinear Source Mixtures (2021)
  • Author(s): Isomura Takuya、Toyoizumi Taro
  • Journal Title: Neural Computation Volume: 33 Issue: 6 Pages: 1433-1468
  • DOI: 10.1162/neco_a_01378
  • Peer Reviewed
• [Journal Article] Learning poly-synaptic paths with traveling waves (2021)
  • Author(s): Ito Yoshiki、Toyoizumi Taro
  • Journal Title: PLOS Computational Biology Volume: 17 Issue: 2 Pages: e1008700-e1008700
  • DOI: 10.1371/journal.pcbi.1008700
  • Peer Reviewed / Open Access
• [Journal Article] Edge of Chaos and Avalanches in Neural Networks with Heavy-Tailed Synaptic Weight Distribution (2020)
  • Author(s): Kusmierz Lukasz、Ogawa Shun、Toyoizumi Taro
  • Journal Title: Physical Review Letters Volume: 125 Issue: 2 Pages: 028101-028101
  • DOI: 10.1103/physrevlett.125.028101
  • Peer Reviewed
• [Journal Article] Theta Oscillations Alternate With High Amplitude Neocortical Population Within Synchronized States (2019)
  • Author(s): Munro Krull Erin、Sakata Shuzo、Toyoizumi Taro
  • Journal Title: Frontiers in Neuroscience Volume: 13 Pages: 316-316
  • DOI: 10.3389/fnins.2019.00316
  • Peer Reviewed / Open Access / Int'l Joint Research
• [Journal Article] Synthetic agency: sense of agency in artificial intelligence (2019)
  • Author(s): Legaspi Roberto、He Zhengqi、Toyoizumi Taro
  • Journal Title: Current Opinion in Behavioral Sciences Volume: 29 Pages: 84-90
  • DOI: 10.1016/j.cobeha.2019.04.004
  • Peer Reviewed / Open Access
• [Journal Article] Multi-context blind source separation by error-gated Hebbian rule (2019)
  • Author(s): Isomura Takuya、Toyoizumi Taro
  • Journal Title: Scientific Reports Volume: 9 Issue: 1 Pages: 7127-7127
  • DOI: 10.1038/s41598-019-43423-z
  • Peer Reviewed / Open Access
• [Journal Article] Intrinsic Spine Dynamics Are Critical for Recurrent Network Learning in Models With and Without Autism Spectrum Disorder (2019)
  • Author(s): Humble James、Hiratsuka Kazuhiro、Kasai Haruo、Toyoizumi Taro
  • Journal Title: Frontiers in Computational Neuroscience Volume: 13 Pages: 38-38
  • DOI: 10.3389/fncom.2019.00038
  • Peer Reviewed / Open Access
• [Journal Article] Robust random search with scale-free stochastic resetting (2019)
  • Author(s): Kusmierz Lukasz、Toyoizumi Taro
  • Journal Title: Physical Review E Volume: 100 Issue: 3 Pages: 032110-032110
  • DOI: 10.1103/physreve.100.032110
  • Peer Reviewed
• [Journal Article] A Bayesian psychophysics model of sense of agency (2019)
  • Author(s): Legaspi Roberto、Toyoizumi Taro
  • Journal Title: Nature Communications Volume: 10 Issue: 1 Pages: 4250-4250
  • DOI: 10.1038/s41467-019-12170-0
  • Peer Reviewed / Open Access
• [Remarks] 二つの臨界現象をつなぐ －脳内神経ネットワークの「カオスの縁」と「雪崩現象」－
  • URL: https://www.riken.jp/press/2020/20200708_2/index.html