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Pedro Antonio Valdes-Sosa | |
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Born | Chicago, Illinois, USA | March 12, 1950
Nationality | Cuban |
Awards | Friendship Award |
Pedro Antonio Valdes-Sosa (born March 12, 1950) is a Cuban neuroscientist who currently serves as the General Vice-Director for Research of the Cuban Neurosciences Center, which he cofounded in 1990. Valdes-Sosa is also member of the editorial boards of journals Neuroimage, [1] Medicc, [2] Audiology and Neurotology, [3] PLosOne [4] and Frontiers, Neuroimage and Brain Connectivity. His work includes statistical analysis of electrophysiological measurements, neuroimaging (fMRI, EEG and MEG tomography), nonlinear dynamical modeling of brain functions and Software and electrophysiological equipment development.
Valdes-Sosa studied medicine at the University of Havana, [5] and graduated in 1972. He also studied Mathematics in 1973. He obtained his Ph.D. in 1978.[ citation needed ] In 1979 he undertook postdoc training on "Neurometrics and Computational Techniques" and "Biophysical Modeling of brain electrical activity" with E. Roy John at the Brain Research Lab of New York University USA. In 2011 obtained his Doctor in Science degree.[ citation needed ]
Valdes-Sosa initiated work with quantitative electrophysiology in 1969 with the first Cuban microcomputer, co-founding CNEURO in 1990, an institution which has changed health indicators in his country as well as in others. His research includes (computational) theory, methodology, and both fMRI and electromagnetic brain imaging, with contributions to multichannel EEG/MEG (1969–1989), Distributed ESI (Electrophysiological Source Imaging, 1989), SPM for ESI (2000), Granger Causality (1998). Neural mass modeling (1997), and EEG/fMRI fusion (2001). He has been active in promoting Brain Mapping, setting up international collaborations and societies, the Cuban and Latin-American Brain Mapping projects, participating actively in OHBM since 1998, having served on its Program Committee.
He is a senior professor of the Higher Institute for Medical Sciences, full member of the Cuban Academy of Sciences, [6] full member of the Latin American Academy of Sciences, associate member of the International Center for Theoretical Physics. He has also been invited professor of the Institute of Statistical Mathematics of Japan, [7] invited researcher of the Brain Science Institute of RIKEN, Japan and Honorary Professor of UCL. 2010 Head of Overseas Team of Talent Introducing Base for Neuroinformation (111 Project) China. 2011 Visiting Professor for Senior International Scientific of the Chinese Academy of Sciences.
Vales-Sosa is Distinguished Professor of Neuroinformatics of the Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, [8] and Program Chair of the Organization for Human Brain Mapping. [9]
In 1997, Valdes-Sosa received the Cuban Academy of Science Award. Statistic Tridimensional Mapping of the EEG Generator's Spectra. In 1995 he received the "Carlos J. Finlay" Award for Scientific Achievements. In 2006 he was got the "José Tey" Award for his dedication to the Education of other professionals. In 2007, he received a Ministry of Science, Technology and Environment Special Award and the Cuban Academy of Science Award both in recognition of the scientific research work: Determination of functional networks in the brain through Granger's causality. In 2013 he received the Award to the best Doctorate Thesis in 2012 of the Academy of Sciences and Ministry of Higher Education of Cuba "Granger causality on the determination of brain functional networks".[ citation needed ]
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Functional neuroimaging is the use of neuroimaging technology to measure an aspect of brain function, often with a view to understanding the relationship between activity in certain brain areas and specific mental functions. It is primarily used as a research tool in cognitive neuroscience, cognitive psychology, neuropsychology, and social neuroscience.
Functional integration is the study of how brain regions work together to process information and effect responses. Though functional integration frequently relies on anatomic knowledge of the connections between brain areas, the emphasis is on how large clusters of neurons – numbering in the thousands or millions – fire together under various stimuli. The large datasets required for such a whole-scale picture of brain function have motivated the development of several novel and general methods for the statistical analysis of interdependence, such as dynamic causal modelling and statistical linear parametric mapping. These datasets are typically gathered in human subjects by non-invasive methods such as EEG/MEG, fMRI, or PET. The results can be of clinical value by helping to identify the regions responsible for psychiatric disorders, as well as to assess how different activities or lifestyles affect the functioning of the brain.
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Neuroimaging is the use of quantitative (computational) techniques to study the structure and function of the central nervous system, developed as an objective way of scientifically studying the healthy human brain in a non-invasive manner. Increasingly it is also being used for quantitative research studies of brain disease and psychiatric illness. Neuroimaging is highly multidisciplinary involving neuroscience, computer science, psychology and statistics, and is not a medical specialty. Neuroimaging is sometimes confused with neuroradiology.
Developmental cognitive neuroscience is an interdisciplinary scientific field devoted to understanding psychological processes and their neurological bases in the developing organism. It examines how the mind changes as children grow up, interrelations between that and how the brain is changing, and environmental and biological influences on the developing mind and brain.
EEG-fMRI is a multimodal neuroimaging technique whereby EEG and fMRI data are recorded synchronously for the study of electrical brain activity in correlation with haemodynamic changes in brain during the electrical activity, be it normal function or associated with disorders.
The Wellcome Centre for Human Neuroimaging at University College London is a world-leading interdisciplinary centre for neuroimaging research based in London, United Kingdom. Researchers at the Centre use expertise to investigate how the human brain generates behaviour, thoughts and feelings and how to use this knowledge to help patients with neurological and psychiatric disorders. Human neuroimaging allows scientists to non-invasively investigate the brain structure and functions including Action, Decision Making, Emotion, Hearing, Language, Memory, Navigation, Seeing, Self awareness, Social Behaviour and the Bayesian Brain
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The following outline is provided as an overview of and topical guide to brain mapping:
Dynamic functional connectivity (DFC) refers to the observed phenomenon that functional connectivity changes over a short time. Dynamic functional connectivity is a recent expansion on traditional functional connectivity analysis which typically assumes that functional networks are static in time. DFC is related to a variety of different neurological disorders, and has been suggested to be a more accurate representation of functional brain networks. The primary tool for analyzing DFC is fMRI, but DFC has also been observed with several other mediums. DFC is a recent development within the field of functional neuroimaging whose discovery was motivated by the observation of temporal variability in the rising field of steady state connectivity research.
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