Dr. Jorge Jovicich is currently Co-Director of the Functional Neuroimaging Laboratory (LNiF), from the Center of Mind-Brain Sciences (CIMeC) and Assistant Professor at Department of Cognitive Sciences at the University of Trento, Italy. His research interests include the optimization and development of high-field magnetic resonance imaging methods that maximize the sensitivity, accuracy and reproducibility of MRI-derived neuroimaging results. He is also interested in the integration of functional MRI methods with other functional neuroimaging modalities, like EEG and MEG.
Dr. Jovicich’s background is in physics. He graduated as a Licentiate in Physics at the Faculty of Mathematics, Astronomy and Physics of Cordoba, Argentina (1993), then completed a M.Sc. Medical Imaging course in Aberdeen University, U.K. (1994), followed by a Ph.D. in high-field functional brain MRI at the Max-Planck Institute of Cognitive Neurosciences, Leipzig, Germany (supervised by Prof. David Norris, 1999). He then completed postdoctoral training at Caltech (California Institute of Technology, working with Prof. Christof Koch, 2001), where he studied holistic versus feature processing of faces as well as brain areas specific for attentional load in a motion-tracking task. During this time Dr. Jovicich also conducted clinical research with Prof.s Linda Chang and Thomas Ernst at Harbor UCLA (University of California Los Angeles) to study function and metabolism deficits in HIV patients and patients who take tamoxifen to reduce the risk of breast cancer. In a second postdoctoral fellowship at MIT (Massachusetts Institute of Technology, working with Prof. Nancy Kanwisher, 2002) he applied functional magnetic resonance imaging in object recognition studies.
Before joining CIMeC (2002-2005), Dr. Jovicich was appointed by Massachusetts General Hospital and Harvard Medical School to work as Project Manager and Co-Investigator of the Morphometry Biomedical Informatics Research Network (BIRN, www.nbirn.net). As co-investigator he worked standardizing and calibrating the acquisition of high-resolution structural MRI data to facilitate precise multi-site evaluation of structural imaging data, such as that used to characterize neuropsychiatric illness (Alzheimer's, depression, bipolar disorders).