Brain & Cognition Lab
Wellcome Centre for Integrative Neuroimaging
I am a postdoctoral fellow supervised by Kia Nobre and I am funded by the James S McDonnell Foundation.
My main research interest is the question of how the brain can integrate previous experience with current task demands. This includes the anticipation of sensory events and pro-active processes that make us humans interact with our environment as smoothly and efficiently as we do. More specifically, this means studying how expectations about what and when events will happen are implemented, how such expectations influence sensory processing, and how they facilitate behaviour. In addition, we can look at what happens when expectations are not met, how these violations are detected, and how they update internal models to improve predictions for the next time we encounter such situations. As a Biophysicist by training, I also have a secondary interest in the sources of the electrophysiological signals we measure in our experiments, what kind of information they carry, and how these signals relate across different methodologies (e.g. intracranial vs EEG vs MEG). The methods I use most often are ECoG and intracranial depth recordings in epilepsy patients, and EEG and MEG in healthy subjects. I may explore simultaneous recordings of EEG and MEG or EEG and fMRI in the future. I also employ varying computational and machine learning methods to extract information from data that is not accessible with univariate methods.
The questions I am trying to answer in my current research projects are: 1) How does the hippocampus contribute to setting up temporal expectations? I will study this in two parallel experiments, using MEG and intracranial recordings. 2) What role do low-frequency oscillations in the auditory cortex play in temporal expectations? I will investigate this in already acquired intracranial datasets.
Learning how the brain uses prior information to inform behaviour is important for a number of reasons. First, by understanding this fundamental principle, we can next investigate how this may be affected in disease. For example, impaired expectation processing may underlie disorders such as Schizophrenia. The hippocampus itself is a fascinating brain region. With vast connections to the rest of the brain, it is in a unique position to perform complex computations. We know quite a lot about how hippocampus implements two specific cognitive functions: spatial navigation and memory. However, the hippocampus may be involved in a lot of other functions as well. I research how the hippocampus is involved in the processing of time, and how this helps us to anticipate important events, and to time our actions. The hippocampus recently has become a target for deep brain stimulation preventing seizures. Investigation of the extent of hippocampal involvement in an array of cognitive functions is important, as it will help us to understand the potential effects of this novel treatment. It may also help us in treating patients with damage in this region. Finally, learning how the brain solves complex problems related to how we interact with our environment can inspire technological advances in patient intervention, brain machine interfaces, and beyond.
My academic background includes undergraduate degrees in Natural Sciences and Philosophy, and a Masters degree in Biophysics at the Radboud University Nijmegen. Before joining the Brain & Cognition lab here at Oxford, I obtained my PhD in Neuroscience from UC Berkeley supported by Fulbright and HHMI fellowships. Here I worked on the electrophysiology of motor inhibition and auditory prediction in human cortex with my PhD advisor Bob Knight.
I like to be active in motivating future generations of scientists, through one-on-one mentorship of students, or through outreach programs in secondary schools that create opportunities for all students to engage with science.
The Neural Mechanisms of Prediction in Visual Search.
Spaak E. et al, (2016), Cereb Cortex, 26, 4327 - 4336
Frontal and motor cortex contributions to response inhibition: evidence from electrocorticography.
Fonken YM. et al, (2016), J Neurophysiol, 115, 2224 - 2236