Post-doctoral researcher (Honorary)
Large-scale probabilistic functional modes from resting state fMRI.
Harrison SJ. et al, (2015), Neuroimage, 109, 217 - 231
The relationship between spatial configuration and functional connectivity of brain regions.
Bijsterbosch JD. et al, (2018), Elife, 7
Investigations into within- and between-subject resting-state amplitude variations.
Bijsterbosch J. et al, (2017), Neuroimage, 159, 57 - 69
The main aim of my research at Oxford is to develop novel techniques that identify brain networks by examining the spontaneous activity of the brain at rest.
To this end, we have developed PROFUMO, a Bayesian framework for inferring resting-state networks from fMRI data. The code is available at https://git.fmrib.ox.ac.uk/samh/profumo. Crucially, we aim to do this in a way that captures for the variability of these networks across subjects. In our model, this variability can either manifest itself as differences in the spatial location or in the temporal dynamics of these networks.
We are using cutting edge data from the Human Connectome Project to investigate how we can relate this variability in spontaneous brain activity to both behavioural and genetic factors.
I graduated from Cambridge with an MEng in Information and Computer Engineering. Upon completion, I began the Life Sciences Interface Doctoral Training Centre at Oxford, where the focus on mathematical and computational techniques for the biomedical sciences naturally led onto a DPhil in neuroimaging analysis techniques at FMRIB.