Knowledge of Threat Biases Perceptual Decision Making in Anxiety: Evidence From Signal Detection Theory and Drift Diffusion Modeling.

Sekine Ozturk, Xian Zhang, Shannon Glasgow, Ramesh R Karnani, Gabriella Imbriano, Christian Luhmann, Jingwen Jin, Aprajita Mohanty
Author Information
  1. Sekine Ozturk: Department of Psychology, Stony Brook University, Stony Brook, New York.
  2. Xian Zhang: Department of Psychology, Stony Brook University, Stony Brook, New York.
  3. Shannon Glasgow: Department of Psychology, Stony Brook University, Stony Brook, New York.
  4. Ramesh R Karnani: Department of Psychology, The University of Hong Kong, Hong Kong SAR, China.
  5. Gabriella Imbriano: Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California.
  6. Christian Luhmann: Department of Psychology, Stony Brook University, Stony Brook, New York.
  7. Jingwen Jin: Department of Psychology, The University of Hong Kong, Hong Kong SAR, China.
  8. Aprajita Mohanty: Department of Psychology, Stony Brook University, Stony Brook, New York.

Abstract

Background: Threat biases are considered key factors in the development and maintenance of anxiety. However, these biases are poorly operationalized and remain unquantified. Furthermore, it is unclear whether and how prior knowledge of threat and its uncertainty induce these biases and how they manifest in anxiety.
Method: Participants ( = 55) used prestimulus cues to decide whether the subsequently presented stimuli were threatening or neutral. The cues either provided no information about the probability (high uncertainty) or indicated high probability (low uncertainty) of encountering threatening or neutral targets. We used signal detection theory and hierarchical drift diffusion modeling to quantify bias.
Results: High-uncertainty threat cues improved discrimination of subsequent threatening and neutral stimuli more than neutral cues. However, anxiety was associated with worse discrimination of threatening versus neutral stimuli following high-uncertainty threat cues. Using hierarchical drift diffusion modeling, we found that threat cues biased decision making not only by shifting the starting point of evidence accumulation toward the threat decision but also by increasing the efficiency with which sensory evidence was accumulated for both threat-related and neutral decisions. However, higher anxiety was associated with a greater shift of starting point toward the threat decision but not with the efficiency of evidence accumulation.
Conclusions: Using computational modeling, these results highlight the biases by which knowledge regarding uncertain threat improves perceptual decision making but impairs it in case of anxiety.

Keywords

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Grants

  1. R21 MH111999/NIMH NIH HHS

Word Cloud

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