Speaker Biography

Radu Mutihac

University of Bucharest, ROMANIA

Title: Functional Neuroimaging for Prognostics and Diagnostics in Brain Disorders

Radu Mutihac
Biography:

Professor Emeritus Radu Mutihac is Chair of Medical Physics, University of Bucharest, and works in Neuroscience, Neural Networks, Signal Processing, Microelectronics, and Artificial Intelligence. As postdoc/research associate/visiting professor/full professor he has conducted research at the University of Bucharest, International Centre for Theoretical Physics (Italy), Ecole Polytechnique (France), Institut Henri Poincaré (France), KU Leuven (Belgium). Data mining and exploratory analysis of neuroimaging time series were addressed during two Fulbright Grants in Neuroscience (Yale University, CT, and University of New Mexico, NM, USA). His research in fused biomedical imaging modalities was carried out at the Johns Hopkins University, National Institutes of Health, and Walter Reed Army Institute of Research, MD, USA.

Since 2008, Prof. Mutihac has been nominated PhD student supervisor in the field of Biophysics and Medical Physics at the University of Bucharest, Romania.
Prof. Mutihac is member of the ISMRM, ESMRMB, OHBM, Romanian US Alumni Association, and fellow of Signal Processing and Neural Networks Society IEEE, as well as referee for several journals of the Institute of Physics (London, UK), Neural Networks (Elsevier), IEEE Transactions on Image Processing, and evaluator/expert for the ISMRM, OHBM, ARACIS, CNCSIS, UEFISCDI, The Romanian – U.S. Fulbright Commission, and the European Commission (FP7, H2020).
Prof. Mutihac published over 120 scientific papers in reputed peer-reviewed journals, 12 monographs, and contributed with chapters in other 11 textbooks published by renowned scientific publishing houses. He participated in more than 150 scientific meetings with posters and oral presentations, seminars, invited, plenary, and keynote lectures, as well as acting as member of the organizing committees, special session organizer, and chairperson.
Following his scientific activity, Prof. Mutihac has been nominated scientific referee for 12 journals, such as IOP, IEEE journals and alike, as well as Member of the Editorial Board of 9 journals in the field of Neuroscience: J. Romanian College of Medical Physicists, J. Childhood & Developmental Disorders, J. Neurology and Clinical Neuroscience, Medical and Clinical Reviews, J. of Translational Neurosciences, Epilepsy J., The Neurologist - Clinical and Therapeutics J., Advances in Neurology and Neuroscience, and J. of Brain Imaging.

Abstract:

The human brain is a large-scale complex network whose function relies on the interaction between its various regions. Recent studies of the human brain connectivity using resting-state/sleep functional magnetic resonance imaging (rsfMRI), diffusion tensor imaging (DTI), and, more recently, diffusion tensor spectroscopic imaging (DSI) data have provided deeper insight on the organization of structural and functional brain networks that continuously share information. Brain's energy is largely consumed at rest during spontaneous neuronal activity (~20%), while task-related increases in metabolism energy are minor (<5%). Spontaneous ultralow-frequency fluctuations in BOLD-based rsfMRI signals (<0.01Hz) at the level of large-scale neural systems are not noise, but orderly and organized in a series of functional networks that permanently maintain a high level of temporal coherence among brain areas that are structurally segregated and functionally linked in resting state networks (RSNs). There is evidence suggesting that such signals permit to extract information about the connectivity and functionality of specific networks. It is also documented that functional connectivity reflects the underlying structural connectivity, which, at rest undergoes specific alterations in several neurological and psychiatric disorders. Human brain function imaged by rsfMRI allows accessing both sides of human mind-brain interface (subjective experience and objective observations). As such, functional neuroimaging moves onto new potential applications like reading the brain states, discriminate neurological dysfunctions (if any), artificial intelligence (AI), brain-computer interfaces (BCI), lie detection, and alike. The presentation aims to review and evaluate the most current approaches for early detection and classification of various forms of dementia, particularly among syndromes with relatively similar behavioral effects, as well as stages in a given syndrome, based on modifications of the brain connectivity at rest explored by rsfMRI, DTI, and DSI.