Context and trade-offs characterize real-world threat detection systems: A review and comprehensive framework to improve research practice and resolve the translational crisis

Markus Fendt; Michael H Parsons; Raimund Apfelbach; Alexandra J R Carthey; Chris R Dickman; Thomas Endres; Anke S K Frank; Daniel E Heinz; Menna E Jones; Yasushi Kiyokawa; Judith C Kreutzmann; Karin Roelofs; Miriam Schneider; Julia Sulger; Carsten T Wotjak; Daniel T Blumstein

doi:10.1016/j.neubiorev.2020.05.002

Context and trade-offs characterize real-world threat detection systems: A review and comprehensive framework to improve research practice and resolve the translational crisis

Neurosci Biobehav Rev. 2020 Aug:115:25-33. doi: 10.1016/j.neubiorev.2020.05.002. Epub 2020 May 19.

Authors

Markus Fendt¹, Michael H Parsons², Raimund Apfelbach³, Alexandra J R Carthey⁴, Chris R Dickman⁵, Thomas Endres⁶, Anke S K Frank⁷, Daniel E Heinz⁸, Menna E Jones⁹, Yasushi Kiyokawa¹⁰, Judith C Kreutzmann¹¹, Karin Roelofs¹², Miriam Schneider¹³, Julia Sulger¹⁴, Carsten T Wotjak¹⁵, Daniel T Blumstein¹⁶

Affiliations

¹ Institute for Pharmacology and Toxicology, Otto-von-Guericke University Magdeburg, Magdeburg, Germany; Center of Behavioral Brain Sciences (CBBS), Otto-von-Guericke University Magdeburg, Magdeburg, Germany. Electronic address: markus.fendt@med.ovgu.de.
² Department of Biological Sciences, Fordham University, Bronx, NY, USA.
³ University of Tübingen, Zoological Institute, Neurobiology, Tübingen, Germany.
⁴ Department of Biological Sciences, Macquarie University, North Ryde, NSW, Australia.
⁵ University of Sydney, School of Life and Environmental Sciences, Sydney, NSW, Australia.
⁶ Institute for Physiology, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
⁷ University of Sydney, School of Life and Environmental Sciences, Sydney, NSW, Australia; University of Tasmania, School of Natural Sciences, Australia; University of Cologne, Institute of Botany, Cologne, Germany.
⁸ Max Planck School of Cognition, Leipzig, Germany; Max Planck Institute of Psychiatry, Max Planck Institute of Psychiatry, RG Neuronal Plasticity, Munich, Germany.
⁹ University of Tasmania, School of Natural Sciences, Australia.
¹⁰ Laboratory of Veterinary Ethology, The University of Tokyo, Tokyo, Japan.
¹¹ Institute for Pharmacology and Toxicology, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
¹² Donders Institute for Brain Cognition and Behaviour and Behavioural Science Institute, Radboud University, Nijmegen, the Netherlands.
¹³ APOPO, Sokoine University of Agriculture, Morogoro, Tanzania.
¹⁴ Max Planck Institute of Psychiatry, Max Planck Institute of Psychiatry, RG Neuronal Plasticity, Munich, Germany; International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany.
¹⁵ Max Planck Institute of Psychiatry, Max Planck Institute of Psychiatry, RG Neuronal Plasticity, Munich, Germany.
¹⁶ University of California Los Angeles, Department of Ecology and Evolutionary Biology, Los Angeles, CA, USA. Electronic address: marmots@ucla.edu.

PMID: 32439371
DOI: 10.1016/j.neubiorev.2020.05.002

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.

Keywords: Animal models; Anxiety; Bench-to-bedside gap; Fear; Predator-prey models; Translational neuroscience.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Review

MeSH terms

Animals
Anxiety
Anxiety Disorders
Fear*
Humans
Predatory Behavior*