モデルベースの階層的行動における人間の脳におけるサブゴールの表現と評価
Cooper D Grossman1, Vincent Man1, John P O'Doherty1
1Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, USA.
Neuron
|February 14, 2026
まとめ
この研究は,機能的磁気共鳴画像 (fMRI) を使用して,脳が連続的な行動のためのサブゴールをどのように表現するかを明らかにしています. それは,決定値のニューラル相関を特定し,階層的およびモデルベースの計画を統合します.
科学分野:
- 神経科学は神経科学である.
- コグニティブ・サイエンス コグニティブ・サイエンス
- 計算神経科学とは
背景:
- セグメントに挙動の階層的な組織化は,複雑な目標指向の行動に不可欠です.
- サブゴールは,行動セグメントの完了をマークし,連続した行動をガイドします.
- サブゴール表現と決定値計算のニューラル基盤を理解することは,認知神経科学における重要なギャップです.
研究 の 目的:
- 連続的な意思決定の過程で,脳がどのようにサブゴールを表現するかを調査する.
- 準目標と環境知識の関数として,決定値がどのように計算されるかを決定する.
- 意思決定における階層的およびモデルベースのプロセスの統合を探求する.
主な方法:
- 新しいシーケンス・サブゴール・意思決定タスクを利用した.
- 機能的磁気共鳴画像 (fMRI) を用いて脳の活動を記録した.
- 神経データを分析するために,モデルベースの階層的な強化学習モデルを開発しました.
主要な成果:
- インスラとベントロメディアル前頭皮質の現在のサブゴール表現を成功裏に解読しました.
- 前頭皮質内の重要な意思決定価値信号を特定しました.
- タスク中の参加者の階層的,モデルベースの行動を示した.
結論:
- インスラとベントロメディアル前頭前皮質のニューラル活動は,連続的な行動のためのサブゴールの表現を支えている.
- 前頭皮質の活動は,環境知識と階層構造を使用して計算された意思決定値を反映します.
- この研究は,意思決定における階層的な制御とモデルベースの計画を統合する神経メカニズムを明らかにします.
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