人間とマウスの推論の基礎となる神経計算
Helen C Barron1, Hayley M Reeve2, Renée S Koolschijn3
1Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford OX1 3TH, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, FMRIB, John Radcliffe Hospital, Oxford OX3 9DU, UK.
Cell
|September 18, 2020
まとめ
科学者は 脳が出来事を関連付けることで 推論的な決定をする方法を発見しました ヒポカンプスは予測コードを使って 柔軟な行動を予測します
科学分野:
- 神経科学
- 認知科学
- 計算神経科学
背景:
- 意思決定は生存と適応に不可欠です
- 新しい選択や関連した出来事に 基づく推論的な決定は 複数の脳領域を巻き込みます
- これらの推論的な決定の背後にある ニューロンの計算は ほとんど未知のままです
研究 の 目的:
- 推論的な意思決定の機能的解剖学とニューロンの計算を調査する.
- 新しい選択に関する予測を可能にする 脳のメカニズムを解明する
主な方法:
- ヒトとマウスの両方を用いた多日間の種間アプローチです
- 成功した推論と休息時の運動の分析
主要な成果:
- 哺乳類の脳は ヒポカンプスのプロスペクティブ・コードを使って 結論を導き出します
- このコードは,時間的に構造化された学問的関連を予測します.
- 休息中に,海馬の鋭い波/波紋は,推論された報酬関係を表す細胞を同活性化し,観察されていないが有益なイベントを効果的に結びつける.
結論:
- ヒッポキャンプスは 予測関連によって 推論的な意思決定に 重要な役割を果たします
- 鋭い波 / リップルの間における海馬細胞の同活性化は,直接体験されていない場合でも,イベント間の"接点"を容易にします.
- このメカニズムは 直接的な経験を超えた 認知マップの形成をサポートし 柔軟な行動を可能にします
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