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Related Experiment Video

Updated: Jun 6, 2025

Using the Threat Probability Task to Assess Anxiety and Fear During Uncertain and Certain Threat

Using the Threat Probability Task to Assess Anxiety and Fear During Uncertain and Certain Threat

Published on: September 12, 2014

Stimulus processing bias in anxiety-related fear generalisation: drift-diffusion modelling and subgroups differences.

Donghuan Zhang^1,2, Min Fan^1,2, Biyao Zhang^1,2

¹Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, South China Normal University, Guangzhou, People's Republic of China.

Cognition & Emotion

|November 22, 2024

Summary

Anxiety influences threat judgments in fear generalization by affecting how people gather evidence. This effect varies across individuals, highlighting the role of strategy preference in processing stimuli.

Keywords:

Fear generalisation anxiety drift-diffusion model gradient

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Last Updated: Jun 6, 2025

Using the Threat Probability Task to Assess Anxiety and Fear During Uncertain and Certain Threat

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Published on: September 12, 2014

Stress-Enhanced Fear Learning, a Robust Rodent Model of Post-Traumatic Stress Disorder

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Published on: October 13, 2018

Measuring Attentional Biases for Threat in Children and Adults

Measuring Attentional Biases for Threat in Children and Adults

Published on: October 19, 2014

Area of Science:

Cognitive Neuroscience
Psychology

Background:

Fear generalization involves overgeneralizing fear responses to similar stimuli.
Anxiety is linked to excessive fear responses and altered threat perception.
Understanding the computational mechanisms of threat judgment in fear generalization is crucial.

Purpose of the Study:

To investigate how anxiety biases threat judgments in a fear generalization paradigm.
To explore differences in generalization gradients across participant subgroups.
To apply computational modeling (drift-diffusion model) to interpret these differences.

Main Methods:

A binary fear generalization judgment task was used to collect behavioral data.
Participants were clustered based on their response patterns.
Hierarchical drift-diffusion modeling analyzed reaction time distributions and individual scores.

Main Results:

State anxiety and stimulus similarity both facilitated threat judgments.
State anxiety weakened the influence of stimulus similarity on evidence gathering.
These anxiety effects were specific to certain participant subgroups.

Conclusions:

Anxiety significantly interacts with stimulus similarity in shaping threat judgments.
Individual differences in strategy preference play a key role in fear generalization.
Computational modeling provides insights into the cognitive processes underlying anxiety and fear generalization.