Computational Modeling of Decision Making Enhances the Adversity Researcher's Toolbox

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Authors: Stefan Vermeent, Anna‐Lena Schubert, Willem E. Frankenhuis
Cited by: 0
References: 131

Abstract

Over the past decades, there has been major progress in our understanding of how adversity influences cognitive abilities and strategies. However, most of this research is based on raw performance, such as response times and accuracy. These measures are informative about decision-making outcomes but tell us little about cognitive processes. In this paper, we argue that adversity researchers should draw more on computational modeling of decision making. We focus on the drift diffusion model, a well-established model of decision making that quantifies the efficiency of information processing, response caution, response bias, and speed of stimulus encoding and response execution. This model allows adversity researchers to gain insights into the cognitive processes associated with adversity exposure. We focus on two areas of decision making: executive functioning and explore-exploit tradeoffs. We conclude with future directions for the field.

Fields of Study & Subjects

Artificial Intelligence in Healthcare Disaster Response and Management Diabetic Foot Ulcer Assessment and Management

Publication details

Journal / source
Topics in Cognitive Science
Publisher
Wiley
Pages
e70057–e70057
Publication date
26 May 2026
Language
EN