Drift-diffusion explains response variability and capacity for tracking objects
Asieh DaneshiiD, Hamed AzarnoushiD, Farzad TowhidkhahiD, Amin GohariiD, Ali GhazizadehiD
Abstract
1.Being able to track objects that surround us is key for planning actions in dynamic environments. However, rigorous cognitive models for tracking of one or more objects are currently lacking. In this study, we asked human subjects to judge the time to contact (TTC) a finish line for one or two objects that became invisible shortly after moving. We showed that the pattern of subject responses had an error variance best explained by an inverse Gaussian distribution and consistent with the output of a biased drift-diffusion model. Furthermore, we demonstrated that the pattern of errors made when tracking two objects showed a level of dependence that was consistent with subjects using a single decision variable for reporting the TTC for two objects. This finding reveals a serious limitation in the capacity for tracking multiple objects resulting in error propagation between objects. Apart from explaining our own data, our approach helps interpret previous findings such as asymmetric interference when tracking multiple objects.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 4
- FWCI
- 0.29
- Field percentile
- top 43%
- Organism
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Different forms of variability could explain a difference between human and rat decision making
Quynh Nhu Nguyen, Pamela Reinagel·Frontiers in NeurosciencePeer-reviewed·Feb 22, 2022
- Expressions for Bayesian confidence of drift diffusion observers in dynamic stimuli tasks
J. Calder-Travis, R. Bogacz, N. Yeung·bioRxiv·Feb 25, 2020
- The interaction between elapsed time and decision accuracy differs between humans and rats
C. A. Shevinsky, P. Reinagel·bioRxiv·Oct 18, 2019
- Measuring the double-drift illusion and its resets with hand trajectories
Bernard Marius ’t Hart, Denise Y. P. Henriques, Patrick Cavanagh·Journal of VisionPeer-reviewed·Feb 23, 2022
- Isolating objective and subjective filling-in using the Drift Diffusion Model
Ron Dekel, Dov Sagi, … Uri Polat A·Journal of VisionPeer-reviewed·Dec 18, 2023
- Object speed and distractor number do not affect attentional allocation in multiple object tracking
Nika Adamian, Feride Akalan, Andersen Sk·bioRxiv·Dec 28, 2025