Diego is a post-doctoral researcher at the Oxford Centre for Human Brain Activity (OHBA).
He is interested in the development and application of machine learning techniques for understanding functional connectivity in the brain. In particular, he aims to combine data from different sources (MEG, EEG, anatomical data) using novel modelling techniques. This will eventually permit to get new insight into disease mechanism, as well as exploring ageing and developmental processes.
Diego obtained its graduate degree in Computer Engineering in the Rey Juan Carlos University, in Madrid, obtaining the National Award in that year. After some years working on (non-academic) engineering, he obtained his PhD in the Polytechnic University of Madrid. His thesis explored the use of regularisation techniques in regression and supervised classification. During his doctorate, he has been involved for over 3 years in the Blue Brain Project, where he has worked on theoretical and practical applications of statistics and machine learning for neuroscience.
A list of his publications can be found here.
Guiding functional connectivity estimation by structural connectivity in MEG: An application to discrimination of conditions of mild cognitive impairment
Pineda-Pardo JA. et al, (2014), NeuroImage, 101, 765 - 777
Functional connectomics from resting-state fMRI
Smith SM. et al, (2013), Trends in Cognitive Sciences, 17, 666 - 682
Bayesian sparse partial least squares.
Vidaurre D. et al, (2013), Neural Comput, 25, 3318 - 3339
Classification of neural signals from sparse autoregressive features
Vidaurre D. et al, (2013), Neurocomputing
Cognitive performance in healthy older adults relates to spontaneous switching between states of functional connectivity during rest.
Cabral J. et al, (2017), Sci Rep, 7
Image Processing and Quality Control for the first 10,000 Brain Imaging Datasets from UK Biobank
Alfaro Almagro F. et al, (2017), biorxiv
Discovering dynamic brain networks from big data in rest and task
Vidaurre D. et al, (2017), NeuroImage
Spectrally resolved fast transient brain states in electrophysiological data.
Vidaurre D. et al, (2016), Neuroimage, 126, 81 - 95
Multi-level block permutation.
Winkler AM. et al, (2015), Neuroimage, 123, 253 - 268