Abstract

Abstract: Decades of mathematical psychology research have yielded a powerful set of computational models for explaining how perceptual decisions are forged in the brain. These ‘sequential sampling’ models come in many forms which, thus far, have been evaluated based on their ability to quantitatively account for behavioural data. However, as recent controversies highlight, any two model variants can make highly similar behavioural predictions despite invoking fundamentally different algorithmic elements. This is of particular concern in light of the rapid increase in the adoption of sequential sampling models in psychiatry and in functional neuroimaging research where the choice of model to employ in a given study may have a major bearing on the results. These challenges can be potentially overcome by also considering the ability of a model to capture key observable aspects of the biological implementation of the decision process: where two models may produce the same behavioural trends, they frequently make distinguishable predictions regarding the associated decision-related neural dynamics. It is only very recently that it has become possible to explore these possibilities using human data owing to the discovery of non-invasively recorded brain signals that reflect the key processing levels underpinning decision formation. I will present recent work from our lab demonstrating how these signals can be used to directly inform the construction and validation of mathematical decision models that can account for two important phenomena: speed-accuracy tradeoffs and age-related cognitive decline.

Bio: Redmond O’Connell is Associate Professor at Trinity College Dublin where he is a principal investigator at the Trinity College Institute of Neuroscience and Director of Research at the School of Psychology. Redmond received his PhD from Trinity College in 2007 and completed a postdoctoral fellowship at the Queensland Brain Institute, Brisbane before returning to Trinity where he was appointed to faculty in 2011. His research is directed toward understanding the neural mechanisms underpinning decision making and meta-cognition. This work comprises both basic and translational research and employs a range of psychophysiological techniques (e.g. EEG , fMRI, pupillometry) alongside computational modelling. His laboratory has published extensively on perceptual decision making, performance monitoring, and attention. Redmond is an adjunct senior research fellow at Monash University, Melbourne and currently holds a European Research Council Starting Grant (2015-2020). His laboratory has received funding from the National Science Foundation, Science Foundation Ireland and the Brain and Behavior Research Foundation.