Dynamic profile comparison reveals statistical processing that static tasks cannot.
Evidence
The dependence of performance on change time suggests a dynamical integration mechanism to play a role in the decision process. While the dependence on change time indicates an ongoing estimation of the initial statistics, it does not provide much insight into the estimation of the post-change statistics. We hypothesized that reaction times here could be informative. Reaction times had previously been demonstrated to depend on task difficulty (Kiani et al. 2014 ), and difficulty in the present paradigm correlates inversely with the availability of a greater difference in change size, i.e. statistics (Fig. 2a ). — Dijk, Pim van, Physiology, Psychoacoustics and…, 3333 (
#expands, via linked claim)
Categorization
- XREF: connects to: Task-related fMRI subtraction can erase the very activity it aims to measure.; Dynamic statistical texture perception differs from static spectral profile analysis; Classical d’ analysis fails in dynamic decision tasks where outcomes unfold over time (+2 more)
Related
- Reaction times reveal how listeners estimate post-change statistics in integration tasks. (similarity 0.85)
- Psychophysical methods differ in task type and time-to-result (similarity 0.84)
- Dynamic spectral-comparison tasks reveal integration processes static tests miss (similarity 0.84)
- Profile analysis compares static spectra while texture change detection needs dynamic statistics (similarity 0.84)
- Detection of statistical change requires temporal integration of the marginal distribution (similarity 0.83)
- Human change detection follows a statistical-integration model as estimation precision improves with observation (similarity 0.82)
- Dynamic statistical texture perception differs from static spectral profile analysis (similarity 0.80)
- Classical d’ analysis fails in dynamic decision tasks where outcomes unfold over time (similarity 0.80)
- Auditory change detection integrates statistical evidence accumulated over time (similarity 0.80)
- Statistically driven spectral analysis requires dynamically presented stochastic tone streams (similarity 0.79)
- Listeners detect statistical changes in ongoing sound based on time available for evidence integration (similarity 0.79)
- Temporal integration may sample informative snapshots rather than integrating all energy (similarity 0.78)
Broader Connections
- Reaction times reveal how listeners estimate post-change statistics in integration tasks.
#expands(0.85) — Dijk, Pim van, Physiology, Psychoacoustics and…, 3333 - Statistically-driven change detection may improve when attention is withdrawn.
#expands(0.80)