Professor recognised for role in revolutionising neuroimaging

A Glasgow academic has received a top accolade in recognition of his role in helping to revolutionise neuroimaging technology.

Professor Mark Girolami, of the Department of Computing Science and the Department of Statistics, was presented with the Unsupervised Learning Pioneer Award by the International Society for Photo-Optical Instrumentation Engineers (SPIE) in Orlando, Florida.

Research carried out 10 years ago by Prof Girolami during his PhD was the catalyst for the development of software tools which helps neuroscientists isolate particular regions of brain activity in electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) scans.

Electrodes attached to a person’s scalp will pick up electric signals from various parts of the brain and body, making it difficult to determine exactly where the signals originate from.

However, algorithms developed by Prof Girolami whilst he was studying at the Salk Institute for Biological Studies in San Diego, California, can be used to isolate signals from particular regions, in the same way the human brain can focus on a single conversation in a room full of other conversations – the so-called ‘cocktail party effect’.

An algorithm is a set of instructions which if followed exactly will produce the same result every time, for example, computer programmes are simply collections of algorithms.

The Salk Institute went on to develop software employing the algorithms he developed which is now used by over 45,000 scientists and engineers throughout the world.

Prof Girolami said: “I’m delighted to have been recognised in this way and that my research laid the groundwork for the development of software to improve neuroimaging. Statistical methodology developed for computational systems biology is an exciting area of work which can hugely develop our understanding of the human body and how it works.”

For more information contact Stuart Forsyth in the University of Glasgow Media Relations Office on 0141 330 4831 or email s.forsyth@admin.gla.ac.uk

First published: 6 May 2009

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