Joshua Hatherley, a PhD student in the Minda Cognitive Science lab, is presenting some research from his dissertation as a poster at the 2019 Psychonomics Meeting in Montreal. The poster presentation is scheduled for Friday, November 15, 2019 from 12:00 PM – 1:30 PM in Room 517B. You can get a copy of the poster link here.
The Experiment
Josh investigated the relationship between working memory, procedural memory, and category learning. The COVIS model assumes that category learning is regulated by an explicit system which uses working memory and an implicit system which uses procedural memory. Research by Minda et al. (2008) used a co-articulation task to disrupt disjunctive-rule category learning and Miles and Minda (2011) used a switching task to disrupt rule-based category learning. However, Minda et al. (2008) failed to find a link between performance on single-dimensional category sets and working memory. Miles and Minda (2011) used a demanding task that interfered with verbal working memory, visual working memory, and executive functions but did not specify if one or all of these processes caused the disruption. The present study addressed these limitations by asking people to learn either a rule-defined (RD) or a non-rule-defined (Information Integration) category set (see Figure 1) composed of 80 Gabor patch images, 40 in each category, that varied in either the orientation of the image, or the frequency of the lines in the image.
While completing this primary categorization task, participants were asked to also perform one of three concurrent tasks that interfered with either verbal working memory, procedural memory, or none of the processes (see Figure 2). In the first concurrent task, participants only learned the category set. This was done in order to be able to compare concurrent task performance to some kind of baseline. In the second concurrent task, participants were asked to speak aloud letters as they appear directly underneath the categorization stimuli. As reading and speaking a list of letters as they appear on the screen should have used a verbal working memory system, it was expected that this additional task would divert resources away from working memory and interfere with learning rule-defined category sets. In the third concurrent task, participants were assigned to complete a motor concurrent task. In it, participants were asked to tap the table with their non-dominant hand whenever they see a colon appear on the screen. As motor function is thought to be a process of procedural memory, adding the additional burden of performing a tapping task should slow down participants ability to learn non-rule-defined categories.
Results
Results indicated that both the verbal working memory task and the procedural memory task impaired the learning of rule-defined categories but had no effect on the learning of information integration categories (see Figure 3).
Information integration category learning did not seem to be affected by either the verbal or the tapping concurrent task. Although we did not predict an effect of the verbal concurrent task, we did predict an effect of the tapping task. We also see that rule-defined category learning appears to be slowed by both the verbal concurrent task and the tapping concurrent task. While we did expect to see an impact from the verbal concurrent task on rule-defined category learning, we did not expect to see it from the tapping concurrent task – which was thought to only impact procedural memory.
What do these results mean? For one thing, learning to perform perceptual classifications is difficult. It takes practice. But people can learn to do it fairly well, even for stimuli like these that are hard to describe. But these results also show that some classifications, the rule-defined ones, are made even more difficult when people are asked to do two things at once. We think that the cognitive resources that are needed to speak the letters or to switch between tasks are also being used for learning these categories. Other classification, the information-integration categories, do not seem to suffer from the same kind of interference. Do these results suggest that there are two cognitive systems that learn new categories? Perhaps. The best way to know for sure is to look more closely at some of the cognitive and neural substrates involved in learning. That’s what our lab is planning to do next.
This work was supported by NSERC, Western University, and BrainsCAN.
For full analysis, see our rpubs page.