Authors
Alexander Schakowski, Dominik Deffner, Marwa M Kavelaars, Lou M Haux, Kiri Kuroda, Félicie Dhellemmes, Ralf H J M Kurvers
Published in
Trends in cognitive sciences. Aug 13, 2026. Epub Aug 13, 2026.
Abstract
Understanding human decision-making processes in everyday life is a central, yet rarely addressed, challenge in psychology. Either real-life complexity is reduced by isolating specific aspects of decision-making in highly constrained experimental settings, yielding insights into specific cognitive mechanisms under idealized conditions, or decision-making is studied in real-life contexts, using high-level descriptions of behavior that do not afford fine-grained, process-level insights. Bridging this gap poses a challenge of both measurement and inference. Recent advances in high-resolution tracking technologies provide novel solutions to many measurement challenges but are rarely integrated with formal psychological theory. In this article, we review tracking technologies and statistical tools, proposing a cognitive-computational framework that uses high-resolution spatiotemporal data to investigate the mechanisms of real-life decision-making in a theory-driven manner.
PMID:
42586903
Bibliographic data and abstract were imported from PubMed on 13 Aug 2026.
Read full publication at:
Please sign in
to see all details.
Advertisement
Stats
- Recommendations n/a n/a positive of 0 vote(s)
- Views 60
- Comments 0