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Updated: Mar 13, 2026
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Measuring Attentional Biases for Threat in Children and Adults
Published on: October 19, 2014
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Context learning for threat detection
Akos Szekely1, Suparna Rajaram1, Aprajita Mohanty1
1a Department of Psychology , Stony Brook University , Stony Brook , NY , USA.
Cognition & Emotion
|October 25, 2016
Summary
Threat detection is improved by learning contextual cues, not just stimulus properties. Context learning for threats can hinder learning for non-threatening stimuli, highlighting top-down influences.
Area of Science:
- Cognitive Psychology
- Neuroscience
- Visual Perception
Background:
- Threat detection is traditionally linked to stimulus salience and physical properties.
- However, stimuli are often embedded in rich contexts, raising questions about context's role.
Purpose of the Study:
- To investigate if learning contextual regularities facilitates threat detection.
- To determine if context learning for threats impacts non-threatening stimuli detection.
Main Methods:
- Participants detected threatening face targets in familiar versus novel spatial configurations of schematic faces.
- The study also examined detection of both threatening and non-threatening faces in learned vs. new configurations.
Main Results:
- Detection of threatening targets was faster in familiar configurations.
- Context learning for threatening stimuli facilitated their detection but impaired non-threatening stimuli detection.
- This suggests context learning for threats can obstruct learning for non-threats.
Conclusions:
- Threat detection is influenced by learned contextual information (top-down factors), not solely by stimulus properties (bottom-up factors).
- Context learning plays a crucial role in identifying salient, threatening stimuli.
- Learned contexts for threat can interfere with the processing of non-threatening information.
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