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人間の適応的メンタライゼーションの神経計算メカニズム
Toan Nong1, Jun Feng2, Jean-Claude Dreher1
1Neuroeconomics Lab, Institut des Sciences Cognitives Marc Jeannerod, Centre National de la Recherche Scientifique (CNRS), Lyon, France; University Claude Bernard Lyon, Lyon 1, Villeurbanne, France.
Trends in cognitive sciences
|January 22, 2026
まとめ
この研究は、静的なタスクを超えて、変化する思考や意図を推論する方法を理解するために、メンタライゼーションの適応的な性質を探求する。計算モデリングと神経画像法は、動的な社会的認知に関する洞察を明らかにする。
科学分野:
- 認知神経科学
- 計算精神医学
- 社会的認知
背景:
- 従来の「心の理論」(ToM)研究では、静的な推論タスクが使用されている。
- 静的なタスクでは、現実世界の社会的相互作用の動的な性質を捉えきれない。
- 動的なメンタライゼーションを理解することは、社会的認知にとって重要である。
研究 の 目的:
- メンタライゼーションの適応的な性質を調査すること。
- 他者の変化する思考や意図の連続的な推論を探求すること。
- 静的な心の理論タスクと動的な社会的認知とのギャップを埋めること。
主な方法:
- 計算モデリングと神経画像技術を組み合わせた。
- 動的なメンタライゼーションを評価するタスクを開発・利用した。
- 変化する精神状態の推論中の脳活動を分析した。
主要な成果:
- 動的なメンタライゼーションを計算論的および神経生物学的に研究する可能性を実証した。
- 他者の意図の連続的な変化を推論することに関連する神経相関を特定した。
- 動的な社会的文脈におけるメンタライゼーションの適応的な性質を示した。
結論:
- メンタライゼーションは、社会的相互作用に不可欠な、適応的で動的なプロセスである。
- 計算モデリングと神経画像法は、動的な社会的認知を研究するための強力なツールを提供する。
- 将来の研究では、他者の精神状態を推論する連続的な性質に焦点を当てるべきである。
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