動物における情動の状態・情動障害および動物福祉を検証するための計算モデルの応用に関する入門的総説

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論文概要

動物がどのような感情や気分の状態にあるかを客観的に測定することは、ヒトの情動障害についての基礎的研究や実験動物をはじめとする動物たちの福祉を考える上で極めて重要である。しかし、情動と、それに対応して行動・生理・認知などで外から観察できる指標との関係は複雑でもあり、こうした情動の状態を客観的に測定する手法を開発し検証することは困難である。このような指標は外部から観測できない、基底にあるプロセスによって産み出されるが、ここで我々は、この基底プロセスを計算モデル化することによって情動の状態と指標の関係を明確にできることを提案する。このような計算論的手法による精神医学へのアプローチは、ヒトを対象とした健康・疾病の研究では広く用いられているが、トランスレーショナルな（橋渡し的な）精神医学研究における応用は乏しく、未だ途上にある。そこで我々は、動物で得られたデータから構築する計算論的モデルが、情動障害や関連する情動の状態、その基盤にある認知過程などを理解するうえで重要であることを解説し、計算論的解析の基本的なステップについて概説する。

Vikki Neville, Michael Mendl, Elizabeth S. Paul, Peggy Seriès, Peter Dayan

2023/11/30

A primer on the use of computational modelling to investigate affective states, affective disorders and animal welfare in non-human animals

https://link.springer.com/article/10.3758/s13415-023-01137-w

動物の未来-FACTSへ戻る