Purchase this article with an account.
Tiffany Ho, Edward Ester, Newton Abuyo, Shaheen Modir, John Serences; Individual differences in working memory capacity predict the speed of perceptual decision making. Journal of Vision 2012;12(9):161. https://doi.org/10.1167/12.9.161.
Download citation file:
© ARVO (1962-2015); The Authors (2016-present)
The ability to make rapid and accurate decisions regarding the importance of incoming visual information is a fundamental component of visual cognition. Perceptual decision making (PDM) is typically characterized as a process where information about a stimulus is accumulated until a decision threshold is reached and a response is produced. The integration of sensory evidence over time requires some form of temporary storage buffer, presumably working memory (WM). However, it is unclear whether mechanisms of PDM draw on the same mnemonic resources that determine individual differences in visual WM ability. To examine this possibility, we asked subjects to report the direction of a variable-coherence random dot kinetogram as quickly and as accurately as possible. We fit behavioral performance to the Linear Ballistic Accumulator model (LBA; Brown & Heathcote, 2008). The use of a formal quantitative model is critical because typical behavioral measures (e.g., response latency and accuracy) only capture the final output of the decision process. Quantiative models such as the LBA, however, allow one to quantify latent aspects of PDM, including the speed at which sensory information is integrated (i.e., drift rate), and the total amount of information needed before a decision is made (i.e., response threshold). Our results indicate that individual differences in WM capacity (quantified via performance in separate change detection task and recall tasks) are positively correlated with individual differences in drift rates (r = 0.44; N = 41). Supplemental analyses show that this relationship cannot be explained by individual differences in subjects’ response thresholds or mean response latencies. Thus, our findings suggest that individual differences in visual WM capacity predict which subjects are most efficient at integrating incoming sensory information.
Meeting abstract presented at VSS 2012
This PDF is available to Subscribers Only