Context and trade-offs characterize real-world threat detection systems: A review and comprehensive framework to improve research practice and resolve the translational crisis. (August 2020)
- Record Type:
- Journal Article
- Title:
- Context and trade-offs characterize real-world threat detection systems: A review and comprehensive framework to improve research practice and resolve the translational crisis. (August 2020)
- Main Title:
- Context and trade-offs characterize real-world threat detection systems: A review and comprehensive framework to improve research practice and resolve the translational crisis
- Authors:
- Fendt, Markus
Parsons, Michael H.
Apfelbach, Raimund
Carthey, Alexandra J.R.
Dickman, Chris R.
Endres, Thomas
Frank, Anke S.K.
Heinz, Daniel E.
Jones, Menna E.
Kiyokawa, Yasushi
Kreutzmann, Judith C.
Roelofs, Karin
Schneider, Miriam
Sulger, Julia
Wotjak, Carsten T.
Blumstein, Daniel T. - Abstract:
- Highlights: In nature, antipredator decision-making is shaped by context and characterized by trade-offs. In the laboratory, neurobiological models of fear and anxiety control context and limit trade-offs. Translational science is failing because models fail to address real-world conditions. We develop a mechanistic model to show why contextual factors should be experimentally manipulated. Abstract: 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.
- Is Part Of:
- Neuroscience and biobehavioral reviews. Volume 115(2020)
- Journal:
- Neuroscience and biobehavioral reviews
- Issue:
- Volume 115(2020)
- Issue Display:
- Volume 115, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 115
- Issue:
- 2020
- Issue Sort Value:
- 2020-0115-2020-0000
- Page Start:
- 25
- Page End:
- 33
- Publication Date:
- 2020-08
- Subjects:
- Animal models -- Bench-to-bedside gap -- Fear -- Anxiety -- Predator-prey models -- Translational neuroscience
Psychophysiology -- Periodicals
Human behavior -- Periodicals
Animal behavior -- Periodicals
Neurology -- Periodicals
Behavior -- Periodicals
Ethology -- Periodicals
Neurology -- Periodicals
Psychophysiologie -- Périodiques
Comportement humain -- Périodiques
Animaux -- Mœurs et comportement -- Périodiques
Neurologie -- Périodiques
Animal behavior
Human behavior
Neurology
Psychophysiology
Periodicals
Electronic journals
573.8 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01497634 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.neubiorev.2020.05.002 ↗
- Languages:
- English
- ISSNs:
- 0149-7634
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6081.561000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 13940.xml