Dr. Natalia Petridou

N.PetridouImaging Division, UMC Utrecht

Dr. Petridou pursued her doctoral research at the National Institutes of Health, Bethesda, MD, under the collaborative education program with the George Washington University, Washington DC, USA. After receiving her Doctor of Science (2006) she spent about three years as a Mansfield fellow at the Sir Peter Mansfield Magnetic Resonance Center, University of Nottingham, UK. In 2009 she joined the UMC Utrecht (Rudolf Magnus Institute and Radiology department), and is presently an Associate Professor with Radiology Dept. Dr. Petridou received a VIDI (STW) in 2013, for her research program on measuring neuronal activity in humans with high field fMRI.

From Blood to Neuron: High resolution functional imaging at 7 Tesla

Functional magnetic resonance imaging (fMRI) measures brain activity via the accompanying changes in blood flow, volume, and oxygenation. As an indirect measure, the accuracy of fMRI is contingent on how closely the measured hemodynamic signals map onto the underlying neuronal activation patterns. The most specific hemodynamic signals arise from the capillary bed, the smallest vessels within gray matter (<20um) that directly serve active neuronal sites. At clinical field strengths, signals from larger veins at the surface of gray matter typically hinder the accuracy of fMRI. 7T allows for improved accuracy in two ways; first, signals from capillaries are enhanced while those from larger veins are reduced. Second, the high signal-to-noise allows for high spatial resolutions that can be exploited to pinpoint the vascular origin of signals measured according to physical location. This talk will give a view into how these advantages translate to increased fMRI specificity to neuronal activation patterns, in light of the correspondence of 7T BOLD fMRI to neuronal activity measured with intracranial electrophysiology (ECoG), in humans. An overview of how the improvements in specificity are being used to measure activity in small neuronal populations, at the spatial scale of columns and layers, will be presented.