Abstract
It is now well established that the time course of perceptual processing influences the first second or so of performance in a wide variety of cognitive tasks. Over the last 20 years, there has been a shift from modeling the speed at which a display is processed, to modeling the speed at which different features of the display are perceived and formalizing how this perceptual information is used in decision making. The first of these models (Lamberts, 1995) was implemented to fit the time course of performance in a speeded perceptual categorization task and assumed a simple stochastic accumulation of feature information. Subsequently, similar approaches have been used to model performance in a range of cognitive tasks including identification, absolute identification, perceptual matching, recognition, visual search, and word processing, again assuming a simple stochastic accumulation of feature information from both the stimulus and representations held in memory. These models are typically fit to data from signal-to-respond experiments whereby the effects of stimulus exposure duration on performance are examined, but response times (RTs) and RT distributions have also been modeled. In this article, we review this approach and explore the insights it has provided about the interplay between perceptual processing, memory retrieval, and decision making in a variety of tasks. In so doing, we highlight how such approaches can continue to usefully contribute to our understanding of cognition.
Highlights
A growing body of evidence, using detailed mathematical models of the time course of perception and memory, clearly demonstrates that information about a stimulus in the environment and about memory representations becomes gradually available over time (e.g., Purcell et al, 2010)
It is important to understand how stimulus information is accumulated from both perception and memory, integrated and utilized in cognitive tasks, and the extent to which errors in such tasks can be attributable to making decisions based on incomplete perceptual and memorial representations
In this article we argue that stochastic sampling of feature information is a process common to both perception and memory and that it underlies early performance in a number of tasks including categorization and identification, recognition and matching, visual search, and word identification
Summary
A growing body of evidence, using detailed mathematical models of the time course of perception and memory, clearly demonstrates that information about a stimulus in the environment and about memory representations becomes gradually available over time (e.g., Purcell et al, 2010).
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
