ArticleiScience2023
Functional sophistication in human escape.
Article in iScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed.
- Human approach-avoidance conflict behaviour relates to transdiagnostic psychiatric symptom dimensions.Translational psychiatry · 2026Article
- Bridging human and animal personality: A behavioral test to assess reward sensitivity.iScience · 2025Article
- Article
- An intracranial dissection of human escape circuits.Nature communications · 2025Article
- The CogLearn Toolkit for Unity: Validating a virtual reality paradigm for human avoidance learning.Behavior research methods · 2025Article
- Social threat avoidance depends on action-outcome predictability.Communications psychology · 2024Article
- No cardiac phase bias for threat-related distance perception under naturalistic conditions in immersive virtual reality.Royal Society open science · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Animals including humans must cope with immediate threat and make rapid decisions to survive. Without much leeway for cognitive or motor errors, this poses a formidable computational problem. Utilizing fully immersive virtual reality with 13 natural threats, we examined escape decisions in N = 59 humans. We show that escape goals are dynamically updated according to environmental changes. The decision whether and when to escape depends on time-to-impact, threat identity and predicted trajectory, and stable personal characteristics. Its implementation appears to integrate secondary goals such as behavioral affordances. Perturbance experiments show that the underlying decision algorithm exhibits planning properties and can integrate novel actions. In contrast, rapid information-seeking and foraging-suppression are only partly devaluation-sensitive. Instead of being instinctive or hardwired stimulus-response patterns, human escape decisions integrate multiple variables in a flexible computational architecture. Taken together, we provide steps toward a computational model of how the human brain rapidly solves survival challenges.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.