I'm a cognitive scientist and philosopher based at the University of Cambridge in the Department of Psychology. Before coming to Cambridge, I held research positions at the ARC Centre of Excellence in Cognition and Its Disorders at Macquarie University (Sydney, Australia), and the Donders Institute for Brain, Behaviour, and Cognition at Radboud University (Nijmegen, Netherlands). I also held a lectureship in the School of Psychology at the Australian Catholic University (Brisbane, Australia). My work spans neuroscience, experimental psychology, and philosophy and I try to investigate problems at multiple levels and from multiple perspectives.
I completed my PhD, titled Predicting the Actions of Other Agents, in 2012 in the Department of Cognitive Science at Macquarie University, where I was affiliated with the Collective Cognition Research Group, the Perception and Action Research Centre, and the Music, Sound, and Performance Laboratory. Prior to this, I completed by Bachelor and Master of Science degree in the Department of Psychology at the University of Auckland.
About my research
My research falls into several broad areas related to Joint Action, Music Cognition, MEG Methodology, and Philosophy of Cognitive Science, and Statistics.
Philosophy of Statistics
In this work I explore debates surrounding statistical reform in psychology and neuroscience, with a particular interest in how these debates play into notions of evidence. I'm also interested in the role of machine learning in the analysis of social, behavioural, and neuroscientific, and how these analytic startergies align with the explanatory goals in these sciences. (Recent collaborators: Dénes Szűcs)
Replication and Statistics in Psychology and Neuroscience
This is a new area of research for me, so more will be coming soon... (Recent collaborators: Dénes Szűcs, and many others... see a recent article in Science about how some of this work was done!)
Philosophy of Cognitive Science
This work is primarily concerned with the nature of explanation in Cognitive Science. In particular, I am interested in the role of mechanistic explanation in Cognitive Science and the relationship between mechanistic explanation and dynamical systems theory (DST) approaches. (Recent collaborators: David Kaplan, Kellie Williamson, Dan Williams)
This is a new area of research for me, so more will be coming soon... (Recent collaborators: Dénes Szűcs, Tim Myers)
In this work I investigate the mechanisms that allow people to generate predictions about the actions of other people. For example, when engaged in certain joint tasks, such as playing a piano duet, it is necessary for the two actors to synchronise the execution of their actions. To do this, it is necessary for actors to be able to anticipate the actions of their co-actors. I have used behavioural experiments to investigate the possibility that during joint action actors use their action systems “off-line” in order to run simulations of their co-actor's actions, and then use these simulations as the basis for anticipatory action planning. (Recent collaborators: John Sutton, Bill Thompson, Natalie Sebanz, Günther Knoblich)
Auditory Processing and Music Cognition
I am primarily interested in how musical pitch is represented in the brain. Several well developed psychological and music theoretic models of musical pitch perception exist. In this work I am interested in testing these models against brain imaging data. For example, it has been claimed that musical notes that differ by a perfect fifth or an octave sound more similar to notes separated by some other interval. Using brain imagining techniques such as representational similarity analysis it may be possible to examine whether the brain activity mirrors these relationships. In past work I have examined questions relating to auditory scene analysis and the basis of musical evoked emotion. (Recent collaborators: Bill Thompson, Thomas Carlson)
In this work, I have sought to apply multivariate pattern analysis techniques, commonly used for fMRI data, to MEG data. I am currently using these methods to study how musical pitch is represented in the brain and how neural representations for musical pitch change in response to different harmonic contexts. (Collaborators: Thomas Carlson)