Our research currently focuses on Cognitive Control, Numerical Cognition, Methods Development, and Causal Learning and Reasoning. You can learn more about each line of research below.
To behave adaptively we must be able to bring our ongoing thoughts and actions into alignment with our current goals and context. This capacity, known as cognitive control, has been linked to a host of important outcomes, including early math and reading ability, emotion regulation, levels of mental and physical health, and success in the workplace. This line of our research explores how different processes related to cognitive control unfold over the course of a response (within-trial dynamics), are modulated by recent experience (cross-trial dynamics), and change across the life span (developmental dynamics).
Inhibitory control refers to one’s ability to suppress habitual or prepotent responses selectively. For instance, a child might use inhibitory control to suppress their desire to speak when it is not their turn. We study how different processes underlying inhibitory control function across development by having participants complete tasks like the one illustrated above. In this task, participants must focus their attention on the arrow in the middle of the screen and override the tendency to respond according to the surrounding arrows.
We live in a noisy world and so we must be able to focus our attention on information that is relevant to our current task and ignore irrelevant or misleading information. However, sometimes we need to switch from one task to another and this can result in information that was previously irrelevant becoming relevant. Switching between different tasks can therefore be challenging, particularly for young children. We study this capacity in children and adults with tasks that, for example, require participants to switch from sorting images by one dimension (e.g., SHAPE) to sorting by another dimension (e.g., COLOUR).
Attention and Distraction
It can be very difficult to ignore distractions in certain circumstances. Although many distractions are just a nuisance, lapses of attention can result in impaired classroom learning and accidents on the job. We study how well children and adults can (a) avoid having their attention captured by distracting information and (b) re-focus their attention when it is captured by distracting information. For instance, in the task illustrated above, participants must attempt to ignore a salient distractor (the green circle) and search for a particular shape (a diamond) regardless of its colour.
Our understanding of numerical quantities is intricately tied to our experience of space. For example, English speakers tend to associate small numbers (e.g., 2) with the left and larger numbers (e.g., 8) with the right. In this line of work, we explore how this link between spatial and numerical information functions across development by measuring participants’ hand movements as they perform tasks that involve numerical information.
In this task, participants are presented with a number between 1 and 9 in the center rectangle and are instructed to touch the left rectangle for numbers under 5, the right rectangle for numbers over 5, and the center rectangle for 5. Building on previous research with adults, we found that children as young as 5 years of age exhibit a link between numerical and spatial information in their hand movements. For instance, movements to the left target were more curved toward the center rectangle for the number 4 than the number 1. Similarly, hand movements were more curved toward the center rectangle for the number 6 than the number 9.
Learning about fractions is notoriously difficult. For instance, children often exhibit a “whole number bias” by extending strategies that work with whole numbers to fractions (e.g., concluding that 1/2 + 1/2 = 2/4). An additional reason that fractions may be difficult to master is that they can generate competing spatial associations. For instance, 2/3 is made up of a small numerator and denominator but is mapped to the same value as 6/9. In this line of work, we have participants identify whether a fraction’s value is smaller or larger than 1/2 so we can assess how the value of the fraction and the size of the numerator and denominator impact movement trajectories.
An influential perspective in psychology and cognitive science views the mind as an information processing system akin to a modern computer. On this view, information comes into the system through various inputs (perception), the information is processed according to a series of rules until a decision is reached (cognition), and then an output is generated (action). On this view, behaviour is seen as reflecting perceptual and cognitive processes that have already concluded. In contrast to this perspective, a growing body of research supports a more dynamic view of the mind in which processes across perception, cognition, and action are unfolding in a parallel, interactive, and continuous manner. Importantly, this alternative view highlights the possibility that unfolding actions (e.g., reaching towards one of two response options) might reflect how cognitive processes unfold over time. In our lab, we use motion tracking systems to record behavioural responses as they unfold. We are particularly interested in connecting these motion capture systems with measures of eye movements and measures of neural activity.
Our lab uses a number of different techniques to record participant’s hand movements as they complete computerised tasks, including an electromagnetic position and orientation recording system made by Polhemus and an optical tracking system produced by OptiTrack. We have also developed response boxes with buttons that provide a portable and affordable solution for measuring when a movement is initiated and when a response is completed.
EEG and Hand Tracking
We are currently working to combine our hand tracking techniques with electroencephalography (EEG) to investigate how behavioural and neural dynamics are linked. Our hope is that pairing these techniques will enable us to identify what neural mechanisms support different aspects of behaviour (e.g., how we catch ourselves from making errors).
Virtual reality headsets present exciting new opportunities for designing and conducting psychological studies. In addition to providing a highly controlled, immersive experience, commercially available headsets support the tracking of hand and eye movements. Consequently, we are working to develop VR versions of common psychological tasks to evaluate how effective the technology might be for research with different age groups.
Causal Learning and Reasoning
As we learn more about the causal structure of the world around us, we are better able to appreciate why certain actions help us to reach our goals whereas others do not. Similarly, we are better able to identify the range of future actions available to us and then predict what the outcomes of those actions might be. In this line of research, our lab explores how children and adults use their existing causal knowledge to form rich explanations about past events and predictions about future or hypothetical events.
We encounter a wide variety of causal mechanisms in our daily lives. Often, these encounters are restricted to observations of cause (e.g., a button is pressed) and effect (e.g., the elevator arrives) with limited exposure to the mechanism mediating the two events. The nature of the observed cause and effect do give us some hint about the underlying mechanism at work, however. For example, each time that you press the button for a doorbell, the doorbell will ring after a fixed period of time. The elevator, on the other hand, arrives after a variable period of time. This variability leads us to expect that the mechanism at work in the elevator is more complex than that of the doorbell. In this line of work, we explore how children and adults might use cues like an effect’s variability to guide their inferences about causal mechanisms.
Diagnostic Reasoning Under Uncertainty
In order to make effective decisions and form reliable inferences, we must be able to manage uncertainty. In this line of research, we investigate how children manage differing levels of uncertainty when performing a diagnostic reasoning task that requires them to determine which of a set of candidate causes brought about an effect. This research indicates that children under six years of age struggle to reason about what causes were likely to have brought about an effect when uncertainty is involved (e.g., when the efficacy of a candidate cause is unknown).