Unifying Prospective and Retrospective Interval-time Estimation: A Fading-gaussian Activation-based Model of Interval-timing

French, Robert M.; Addyman, Caspar; Mareschal, Denis and Thomas, Elizabeth. 2014. Unifying Prospective and Retrospective Interval-time Estimation: A Fading-gaussian Activation-based Model of Interval-timing. Procedia - Social and Behavioral Sciences, 126, pp. 141-150. ISSN 1877-0428 [Article]

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Abstract or Description

Hass and Hermann (2012) have shown that only variance-based processes will lead to the scalar growth of error that is characteristic of human time judgments. Secondly, a major meta-review of over one hundred studies (Block et al., 2010) reveals a striking interaction between the way in which temporal judgments are queried and cognitive load on participants� judgments of interval duration. For retrospective time judgments, estimates under high cognitive load are longer than under low cognitive load. For prospective judgments, the reverse pattern holds, with increased cognitive load leading to shorter estimates. We describe GAMIT, a Gaussian spreading-activation model, in which the sampling rate of an activation trace is differentially affected by cognitive load. The model unifies prospective and retrospective time estimation, normally considered separately, by relating them to the same underlying process. The scalar property of time estimation arises naturally from the model dynamics and the model shows the appropriate interaction between mode of query and cognitive load.

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This work was supported in part by a joint grant from the French ANR (ANR-10-056 GETPIMA), and the UK ESRC (RES-062-23-0819) within the France-UK ORA framework.


Activation-based model,Interval-timing,Retrospective and prospective timing,Time perception

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Date Deposited:

08 Jan 2016 12:41

Last Modified:

29 Apr 2020 16:13

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Yes, this version has been peer-reviewed.



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