不確実性と報酬の歴史は,勝敗後の決定に明確な影響を及ぼします
bioRxiv : the preprint server for biology
|September 2, 2025
まとめ
動物はフィードバックから 適応的に学習しますが 勝利と敗北を どう評価するかは不明です この研究は,不確実性と報酬の歴史が,この学習非対称性に影響を及ぼし,ネズミの性別特異的な効果が観察されたことを明らかにしています.
科学分野:
- 神経科学
- 行動科学
- 計算神経科学
背景:
- インテリジェントな行動は 適応的なフィードバックの統合に依存しています
- 動物はポジティブなフィードバックと ネガティブなフィードバックから 非対称的な学習をします
- 勝敗の差分加算の基礎となる計算は十分に理解されていない.
研究 の 目的:
- ネズミの勝利と敗北の重み付けをどのように変えたかを調査する.
- 不確実性と報酬の歴史を組み込む強化学習モデルを提案し,テストする.
- 変化する環境に適応するために 動物が使う行動戦略を理解する
主な方法:
- 変数報酬の予測可能性を持つダイナミックな確率逆転学習タスクを使用した.
- ネズミの行動データを集めました
- 非サイン平均報酬予測エラーと主観的な報酬履歴を統合した補強学習モデルを開発した.
主要な成果:
- 不確実性の過去と報酬の過去の両方が,勝敗に対するネズミの感受性に大きく影響した.
- 予測可能な低不確実性環境では,ネズミは損失よりも勝利を重んじます (より高い勝利-滞在,より低い損失-シフト).
- 性別別別別の差異が認められた.オスのマウスの転勤決定は報酬の歴史によってより強く影響され,メスのマウスは不確実性の歴史によって影響された.
結論:
- 報酬と不確実性の変化に 適応するための重要な戦略です
- 不確実性の推定と報酬の歴史の推定は,行動適応を調節する上で異なる役割を果たします.
- 性別特有の神経計算は適応学習戦略に寄与する.
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