Category Archives: Conferences

Cognitive Interference and Category Learning: A Tale of Two Systems

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 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.

People Are More Likely to Use Classification Rules When Features Are Easy to Describe Verbally

Bailey Brashears, a PhD in the Minda Cognitive Science lab, is presenting some research from her Master’s thesis as a poster at the 2019 Psychonomics Meeting in Montreal. The poster presentation is scheduled for the Friday Nov 15 poster session at noon. You can get a copy of the poster here

The Experiment

Bailey investigated the effects of feature verbalizablity on the acquisition of novel concepts. Participants in the experiment learned a category set that could be acquired by either a perfectly predictive criterial attribute rule or an overall family-resemblance strategy. Half of the participants learned this set with features that were easy to name and describe verbally and the other half learned this set with features that were not easy to name and describe verbally. In this case, easy to name meant features that corresponded to focal colours, nameable shapes, or countable shapes. Features that were not easy to name were equally diagnostic of category membership, but did not correspond to focal colours or nameable shapes.  

Some examples of the stimuli we used. Each pair shown are opposite prototypes


After learning, participants were transferred to a set of new exemplars that included stimuli designed to distinguish between rule strategies and family-resemblance strategies. We found that it took participants about the same number of trials to learn the category sets regardless of the feature type learned. However, participants’ accuracy on previous items in the testing phase was higher for participants who learned the stimulus with easy to verbalize features; while participants were able to learn the categories in either condition, they retained these categories with better accuracy when the features were easy to verbalize. 

The majority of the subjects in the easily verbalizable condition were fit best by the criterial attribute (CA) rule model.

We also analyzed each learner’s performance with a set of computational models. Each model in the set assumed that performance was driven by one (and only one) of the available strategies (a rule, family resemblance, guessing, etc) and we examined which of the model best fit the observed performances. We found that people who learned the categories with easier to name features were more likely to classify new stimuli in accordance with a rule-based strategy. People who learned the categories with difficult to name features showed evidence of both rule use and family resemblance responding and no clear preference for either strategy. The figure above shows the models’ fit (essentially how close the model is to the observed data) for each subject by condition.


What do these results mean? For one thing, these results suggest that when people can rely on language to label features and to name things, they do. The more available the names are, the more likely people are to use rules that correspond to those features. This points to the primacy of language as a means to consolidate information. This language-based rule system might be a default way to acquire new concepts. It also means that there are other ways to learn concepts beyond using language, however. People who learned the categories that had features that were hard to describe verbally often learned the overall family resemblance, suggesting a tendency to learn exemplars. 

Bailey is working on a second study to replicate these results and plans to develop other ways to explore the role of language in acquiring new concepts. As well, she’s working on designing gaming environments that can explore the incidental acquisition of concepts. Stay tuned for more!

This work was supported by NSERC, Western University, and BrainsCAN.

Category Learning in Older Adulthood: The Role of Age and Executive Functioning

If you are at the Psychonomics meeting in Boston in November, stop by the Cognitive Aging session (Back Bay C & D, Saturday Morning, 8:00-10:00). Dr. Minda will be giving a talk entitled “Category Learning in Older Adulthood: The Role of Age and Executive Functioning” based on some of Rachel Rabi’s doctoral work.

We asked older and younger adults to learn category sets of varying rule complexity. Older adults performed comparable to younger adults when learning single-dimensional rule-based categories, but struggled greatly with learning complex rule-based categories, which taxed their working memory resources. A second experiment examined whether complex rule-based categorization performance could be improved in older adults by reducing task demands. Following familiarization with the category set, older adults demonstrated marked improvements in performance. The reduction of the working memory demands allowed the older adults to formulate the complex rule and to perform comparably to younger adults. Our findings suggest that age-related declines in executive functioning may be associated with difficulty learning more complex rule-based categories.

Slides from the talk are available HERE

SOBDR conference at Brock University

Members of the Categorization Lab will be presenting three posters at the Southern Ontario Behavioral Decision Research Conference (SOBDR) at Brock University this Thursday (May 7th). Sarah Devantier will be presenting her research on goal-oriented categories in clinical thinking, Ruby Nadler will be presenting her research on Mood and category learning and Sarah Miles will be presenting her research on the visual-spatial aspects of category learning. If you happen to be at the conference, please stop by to see our posters.