BRAIN and NERVE－神経研究の進歩71巻7号

2019年07月発行

増大特集 人工知能と神経科学

人工知能と小脳運動学習

著者： 永雄総一¹ 本多武尊²

所属機関： ¹希望病院・のぞみ高次脳機能研究所 ²東京都医学総合研究所・運動障害プロジェクト

ページ範囲：P.665 - P.680

文献概要

半世紀前パーセプトロンを基にMarr-Albus-Ito小脳学習仮説が提案され，その検証過程で小脳学習と記憶の原因となるシナプス可塑性の長期抑圧（LTD）が発見された。小脳学習仮説は脳における深層学習の原型である液状態機械モデルへと発展し，運動のタイミングと効率の学習，運動記憶の形成や内部モデルに基づく認知機能まで拡張されつつある。パーセプトロンから発展した人工知能が今後小脳の神経科学に与える影響について論じる。

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