Human brain connectivity: Clinical applications for clinical neurophysiology. Issue 7 (July 2020)

• Record Type: Journal Article
• Authors: Hallett, Mark; de Haan, Willem; Deco, Gustavo; Dengler, Reinhard; Di Iorio, Riccardo; Gallea, Cecile; Gerloff, Christian; Grefkes, Christian; Helmich, Rick C.; Kringelbach, Morten L.; Miraglia, Francesca; Rektor, Ivan; Strýček, Ondřej; Vecchio, Fabrizio; Volz, Lukas J.; Wu, Tao; Rossini, Paolo M.
• Is Part Of: Clinical neurophysiology. Volume 131:Issue 7(2020:Jul.)
• Page Start: 1621
• Page End: 1651
• Publication Date: 2020-07
• Subjects: Networks, coherence -- Graph theory -- Neurodegeneration -- Dementia -- Amyotrophic lateral sclerosis -- Stroke -- Parkinson disease -- Dystonia -- Essential tremor -- Apraxia -- Epilepsy -- Phantom limb -- Psychiatric disorders -- EEG -- MRI; Neurophysiology -- Periodicals; Electroencephalography -- Periodicals; Electromyography -- Periodicals; Neurology -- Periodicals; 612.8
• DOI: 10.1016/j.clinph.2020.03.031
• Languages: English
• ISSNs: 1388-2457

Abstract

Highlights: The brain operates in networks and clinical neurophysiology can assess these networks. Methods include EEG, MEG, and functional MRI. Neurological and psychiatric disorders cause a breakdown in brain networks. Abstract: This manuscript is the second part of a two-part description of the current status of understanding of the network function of the brain in health and disease. We start with the concept that brain function can be understood only by understanding its networks, how and why information flows in the brain. The first manuscript dealt with methods for network analysis, and the current manuscript focuses on the use of these methods to understand a wide variety of neurological and psychiatric disorders. Disorders considered are neurodegenerative disorders, such as Alzheimer disease and amyotrophic lateral sclerosis, stroke, movement disorders, including essential tremor, Parkinson disease, dystonia and apraxia, epilepsy, psychiatric disorders such as schizophrenia, and phantom limb pain. This state-of-the-art review makes clear the value of networks and brain models for understanding symptoms and signs of disease and can serve as a foundation for further work.