Cornelis J. Stam mainly investigates Neuroscience, Electroencephalography, Magnetoencephalography, Resting state fMRI and Small-world network. The Neuroscience study combines topics in areas such as Alzheimer's disease, Alpha and Clustering coefficient. His Electroencephalography research is multidisciplinary, incorporating elements of Schizophrenia, Communication and Nonlinear system.
His research integrates issues of Nerve net, Central nervous system disease, Power graph analysis, Parkinson's disease and Functional connectivity in his study of Magnetoencephalography. The study incorporates disciplines such as Frontal lobe, Average path length, Functional magnetic resonance imaging, Default mode network and Brain activity and meditation in addition to Resting state fMRI. His Small-world network research is multidisciplinary, incorporating perspectives in Graph theory, Temporal lobe, Path length and Scale-free network.
Cornelis J. Stam mainly focuses on Neuroscience, Electroencephalography, Magnetoencephalography, Cognition and Resting state fMRI. Cornelis J. Stam mostly deals with Brain mapping in his studies of Neuroscience. The various areas that he examines in his Electroencephalography study include Functional connectivity, Disease, Audiology and Epilepsy.
His Magnetoencephalography research integrates issues from Magnetic resonance imaging, Brain activity and meditation, Glioma and Cognitive decline. Cornelis J. Stam focuses mostly in the field of Resting state fMRI, narrowing it down to matters related to Artificial intelligence and, in some cases, Machine learning. Cornelis J. Stam has included themes like Graph theory, Graph and Clustering coefficient in his Small-world network study.
His primary scientific interests are in Magnetoencephalography, Neuroscience, Electroencephalography, Cognition and Functional connectivity. The concepts of his Magnetoencephalography study are interwoven with issues in Centrality, Resting state fMRI, Magnetic resonance imaging, Cognitive decline and Default mode network. His Neuroscience research includes elements of Multiple sclerosis and Parkinson's disease.
His Electroencephalography research incorporates themes from Alpha, Audiology, Cardiology and Dementia, Disease. His Cognition study incorporates themes from Biomarker and Alzheimer's disease. In general Functional connectivity, his work in Functional networks is often linked to Network analysis linking many areas of study.
Cornelis J. Stam focuses on Magnetoencephalography, Neuroscience, Functional connectivity, Electroencephalography and Cognition. Cornelis J. Stam interconnects Centrality, Sensitivity, Ictal, Resting state fMRI and Artificial intelligence in the investigation of issues within Magnetoencephalography. His White matter research extends to the thematically linked field of Neuroscience.
His study in the field of Dynamic functional connectivity is also linked to topics like Network analysis. His Electroencephalography research includes themes of Dementia, Disease, Pathology, Graph theory and Clinical psychology. His studies deal with areas such as Alpha, Physical medicine and rehabilitation, Power graph analysis, Cognitive decline and Alzheimer's disease as well as Cognition.
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Consistent resting-state networks across healthy subjects
J. S. Damoiseaux;S. A. R. B. Rombouts;F. Barkhof;P. Scheltens.
Proceedings of the National Academy of Sciences of the United States of America (2006)
Nonlinear dynamical analysis of EEG and MEG: Review of an emerging field
Clinical Neurophysiology (2005)
Phase lag index: assessment of functional connectivity from multi channel EEG and MEG with diminished bias from common sources.
Cornelis J. Stam;Guido Nolte;Andreas Daffertshofer.
Human Brain Mapping (2007)
Small-world networks and functional connectivity in Alzheimer's disease
CJ Stam;BF Jones;G Nolte;M Breakspear;M Breakspear.
Cerebral Cortex (2006)
Reduced resting-state brain activity in the “default network” in normal aging
J.S. Damoiseaux;C.F. Beckmann;E.J. Sanz Arigita;F. Barkhof.
Cerebral Cortex (2008)
Efficiency of Functional Brain Networks and Intellectual Performance
Martijn P. van den Heuvel;Cornelis J. Stam;René S. Kahn;Hilleke E. Hulshoff Pol.
The Journal of Neuroscience (2009)
Graph theoretical analysis of complex networks in the brain
Cornelis J Stam;Jaap C Reijneveld.
Nonlinear Biomedical Physics (2007)
Comparing brain networks of different size and connectivity density using graph theory
Bernadette C. M. van Wijk;Cornelis J. Stam;Andreas Daffertshofer.
PLOS ONE (2010)
Graph theoretical analysis of magnetoencephalographic functional connectivity in Alzheimer's disease.
C. J. Stam;W. de Haan;A. Daffertshofer;B. F. Jones.
Modern network science of neurological disorders
Cornelis J. Stam.
Nature Reviews Neuroscience (2014)
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