Research

My research focuses on understanding how humans process and learn about the relationships between stimuli in the environment, and how such learning shapes behavior. In particular I am interested in the processes involved in associative learning, how learning interacts with attentional processing, and how we can develop computational models of learning. I am also interested in comparisons between learning under conditions of effortful reflection versus conditions which rely on the rapid processing of stimuli, the importance of intention in learning, and the related question of whether conscious awareness is necessary for learning.

Current and recent major research projects in my lab

Known Unknowns and Unknown Unknowns: Coping with Different States of Uncertainty in a Changing World. This ESRC project grant (with Mark Haselgrove) will explore how different forms of uncertainty in the world shape the cognitive processes of learning and attention. We will explore different types of uncertain situations, differentiating between stable periods of uncertainty (the “known unknowns”) and situations where things change suddenly (the “unknown unknowns”). We aim to explore how these affect stimulus processing and cognitive vigilance, contingency learning, and knowledge integration.

Can psychopathy inform the cognitive mechanics of social learning? This ARC Discovery Project (DP20, Caroline Moul, Tom Beesley, Mark Dadds) is exploring whether specific deficits in associative learning and attention are linked to the development of different personality traits. We are using eye-tracking to tease apart the sub-components of basic learning processes, and exploring whether such processes lead to unusual patterns of attention in people high in traits related to psychopathy.

Automatic and controlled processes in learned biases of attention. This ARC Discovery Project (DP16, Tom Beesley & David Luque) examined the attentional mechanisms involved in human associative learning. In particular, the project explored the development of, and relationship between, automatic and controlled processes leading to learned biases of attention. We examined these sub-components using online measures of attention such as eye-tracking and EEG.

How does uncertainty guide attention in human learning. This ARC Discovery Project (DP14 Tom Beesley, Mike Le Pelley, & Chris Mitchell) examines the way in which uncertainty guides our selection of information from the environment. It appears that under uncertain conditions we increase our attention to stimuli (see Beesley, Nguyen, Pearson, & Le Pelley, 2015; Luque, Vadillo, Le Pelley, & Beesley, in press) for enhanced processing. My two PhD students Lara Easdale and Adrian Walker are currently working on related projects, with forthcoming papers/submissions.

Incidental learning of repeated visual context. How do humans learn to process and activate the repeated visual scenes they experience in their environment? How does experience with the world shape what we attend to and what we ignore? Can such learning occur in the absence of any conscious awareness of what we have experienced? In a number of papers we have set about testing models of learning in visual search (i.e., “contextual cuing”). This work suggests that we form configural representations of visual scenes (see Beesley, Vadillo, Pearson & Shanks, 2015; 2016).

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For recent news from our lab check: https://twitter.com/BeesleyLAB

Collaborators

Mark Haselgrove – University of Nottingham

A/Prof. Mike Le Pelley – UNSW, Australia

Dr David Luque – UNSW, Australia

Prof. David Shanks – UCL, UK

Dr. Miguel A. Vadillo – King’s College, UK

Dr. Steve Most – UNSW, Australia

Dr Caroline Moul – University of Sydney, Australia

A/Prof. Thomas Whitford – UNSW, Australia

Dr Evan Livesey – University of Sydney, Australia

Dr Oren Griffiths – Flinders University, Adelaide

 

Last updated 25th August, 2022.