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Journal Article

Citation

Balci F, Simen P. Acta Psychol. 2014; 149: 157-168.

Affiliation

Department of Neuroscience, Oberlin College, United States. Electronic address: psimen@oberlin.edu.

Copyright

(Copyright © 2014, Elsevier Publishing)

DOI

10.1016/j.actpsy.2014.03.005

PMID

24726447

Abstract

The processing dynamics underlying temporal decisions and the response times they generate have received little attention in the study of interval timing. In contrast, models of other simple forms of decision making have been extensively investigated using response times, leading to a substantial disconnect between temporal and non-temporal decision theories. An overarching decision-theoretic framework that encompasses existing, non-temporal decision models may, however, account both for interval timing itself and for time-based decision-making. We sought evidence for this framework in the temporal discrimination performance of humans tested on the temporal bisection task. In this task, participants retrospectively categorized experienced stimulus durations as short or long based on their perceived similarity to two, remembered reference durations and were rewarded only for correct categorization of these references. Our analysis of choice proportions and response times suggests that a two-stage, sequential diffusion process, parameterized to maximize earned rewards, can account for salient patterns of bisection performance. The first diffusion stage times intervals by accumulating an endogenously noisy clock signal; the second stage makes decisions about the first-stage temporal representation by accumulating first-stage evidence corrupted by endogenous noise. Reward-maximization requires that the second-stage accumulation rate and starting point be based on the state of the first-stage timer at the end of the stimulus duration, and that estimates of non-decision-related delays should decrease as a function of stimulus duration.

RESULTS are in accord with these predictions and thus support an extension of the drift-diffusion model of static decision making to the domain of interval timing and temporal decisions.


Language: en

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