Spatiotemporal dynamics of the human effective connectome in Neurological disorders
18th International Conference on Neurology and Neurological Disorders
August 23-24, 2018 | Paris, France
University of Bucharest, Romania
Keynote : J Neurol Neurorehabil Res
Connectivity studies using resting-state functional magnetic resonance imaging (rsfMRI), diffusion tensor imaging (DTI), and, more recently, diffusion spectroscopic imaging (DSI) have enhanced our knowledge on the organization of large-scale structural and functional brain networks, which consist of spatially distributed, but functionally linked regions that continuously share information with each other. Brain’s energy is largely consumed at rest during spontaneous neuronal activity (~20%), while task-related increases in metabolism energy are minor (<5%). Spontaneous ultralowfrequency 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). Some RSNs are functionally organized as dynamically competing systems both at rest and during tasks. The default mode network (DMN), the most important RSN, is even more active during rest and involved in realization of tasks like memory retrieval, emotional process, and social cognition. Cortical connectivity at rest is reportedly altered in several neurological and psychiatric disorders. Most recently, human brain function has been imaged in fMRI, and thereby accessing both sides of the mind-brain interface (subjective experience and objective observations) have simultaneously been performed. As such, functional neuroimaging moves onto new potential applications like reading the brain states, brain-computer interfaces, lie detection, and so forth. The presentation aims to review and evaluate the most current approaches and findings on early detection and classification of cognitive impairments and dementia, particularly among syndromes with relatively similar behavioral effects, on the basis of alterations in brain connectivity at rest explored by fused rsfMRI, DTI, and DSI.
Radu Mutihac is Chair of Medical Physics Section, University of Bucharest, and works in Neuroscience, Signal Processing, Microelectronics, and Artificial Intelligence. As postdoc/research associate/visiting professor/full professor he has run his 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.
E-mail: [email protected]