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脳数理情報連携研究室
Showing the original Japanese · View translation
脳の学習と適応のしくみを、数理モデルで解き明かす研究室。

AboutAbout the lab
脳が学習するしくみを、理論で解き明かす。
脳数理情報連携研究室は、
神経回路が
統計力学や
神経回路網が
Key terms
- 計算神経科学
- 脳の
働きを 計算の モデルと して 表し、 数理の 言葉で 理解しようと する 分野 - 神経可塑性
- 神経細胞が
自分の 活動に 応じて 性質を 変える 現象。 学習や 記憶、 発達の もとに なる - 神経回路網
- 神経細胞が
つながって できた、 情報を 処理する ネットワーク
NewsLab news
研究成果
「生体情報処理の 高度化には “跳躍”が ある」を 発表 研究成果
「学習過程を 少数合成データに 圧縮する 仕組みの 理論的解明」を 発表 研究成果
「大切な 情報を 抽出する 神経回路モデル」を 発表 研究成果
「シナプスの 結び つきの 強さが 睡眠の 量と 質を 一定に 保つ 仕組みに 関与する」を 発表 特別研究員が、
時実利彦記念神経科学優秀博士研究賞を 受賞
ResearchResearch themes
数理モデルの
*Illustrative image脳の情報処理と適応の理論
コンピュータの
*Illustrative image神経可塑性の理論
神経細胞が
*Illustrative imageできあがる回路の性能を予測
可塑性に
MembersFaculty
脳数理情報連携研究室の
- Affiliated Professor豊泉 太郎
- Affiliated Associate ProfessorLukas Ian Schmitt
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RelatedLabs similar to 脳数理情報連携研究室
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Synapsin and CamK2 positive neurons” ManuelSchottdorf / CC BY-SA 4.0 (cropped)
- 脳の
情報処理と 適応の 理論: “White Matter Connections Obtained with MRI Tractography” Xavier Gigandet et. al. / CC BY 2.5 (cropped) - 神経可塑性の
理論: “A segment of pyramidal cell dendrite from stratum radiatum (CA1)” Dr. Kristen M. Harris / CC BY 2.0 (cropped) - できあがる
回路の 性能を 予測: “Lorenz-1000” Vogel (К.Б. Циберкин) / Public domain (cropped) - Related lab (システムズ薬理学研究室): “Lab mouse mg 3263” Rama / CC BY-SA 2.0 fr (cropped)
- Related lab (数理生命情報学研究室): “Mouse Embryo Cerebellum ( )” NIH Image Gallery from Bethesda, Maryland, USA / Public domain (cropped)
- Related lab (脳情報計測・
制御研究室(天野・中山研究室)): “Double cone coil” Baburov / CC BY-SA 4.0 (cropped) - Related lab (学習数理情報学研究室(山西研究室)): “CERN Server 03” Florian Hirzinger - www.fh-ap.com / CC BY-SA 3.0 (cropped)
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