Context and trade-offs characterize real-world threat detection systems: A review and comprehensive framework to improve research practice and resolve the translational crisis.
Animal models
Anxiety
Bench-to-bedside gap
Fear
Predator-prey models
Translational neuroscience
Journal
Neuroscience and biobehavioral reviews
ISSN: 1873-7528
Titre abrégé: Neurosci Biobehav Rev
Pays: United States
ID NLM: 7806090
Informations de publication
Date de publication:
08 2020
08 2020
Historique:
received:
12
02
2020
revised:
28
04
2020
accepted:
03
05
2020
pubmed:
23
5
2020
medline:
22
6
2021
entrez:
23
5
2020
Statut:
ppublish
Résumé
A better understanding of context in decision-making-that is, the internal and external conditions that modulate decisions-is required to help bridge the gap between natural behaviors that evolved by natural selection and more arbitrary laboratory models of anxiety and fear. Because anxiety and fear are mechanisms evolved to manage threats from predators and other exigencies, the large behavioral, ecological and evolutionary literature on predation risk is useful for re-framing experimental research on human anxiety-related disorders. We review the trade-offs that are commonly made during antipredator decision-making in wild animals along with the context under which the behavior is performed and measured, and highlight their relevance for focused laboratory models of fear and anxiety. We then develop an integrative mechanistic model of decision-making under risk which, when applied to laboratory and field settings, should improve studies of the biological basis of normal and pathological anxiety and may therefore improve translational outcomes.
Identifiants
pubmed: 32439371
pii: S0149-7634(20)30397-3
doi: 10.1016/j.neubiorev.2020.05.002
pii:
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
25-33Informations de copyright
Copyright © 2020 Elsevier Ltd. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest All authors declare no conflicts of interest.