Jules Schneider1,2, Justus T C Schwabedal3, Stephan Bialonski4,5. 1. Klinik und Poliklinik für Psychiatrie und Psychotherapie, Universitätsklinikum Carl Gustav Carus, Technische Universität Dresden, Dresden, Deutschland. 2. Klinik und Poliklinik für Neurologie, Universitätsklinikum Carl Gustav Carus, Technische Universität Dresden, Dresden, Deutschland. 3. , 53113, Bonn, Deutschland. 4. Fachbereich für Medizintechnik und Technomathematik, FH Aachen, Jülich, Deutschland. bialonski@fh-aachen.de. 5. Institut für datenbasierte Technologien, FH Aachen, Heinrich-Mußmann-Str. 1, 52428, Jülich, Deutschland. bialonski@fh-aachen.de.
Abstract
BACKGROUND: The sleep spindle is a graphoelement of an electroencephalogram (EEG), which can be observed in light and deep sleep. Alterations in spindle activity have been described for a range of psychiatric disorders. Due to their relatively constant properties, sleep spindles may therefore be potential biomarkers in psychiatric diagnostics. METHOD: This article presents an overview of the state of the science on the characteristics and functions of the sleep spindle as well as known alterations of spindle activity in psychiatric disorders. Various methodological approaches and developments of spindle detection are explained with respect to their potential for application in psychiatric diagnostics. RESULTS AND CONCLUSION: Although alterations in spindle activity in psychiatric disorders are known and have been described in detail, their exact potential for psychiatric diagnostics has yet to be fully determined. In this respect, the acquisition of knowledge in research is currently constrained by manual and automated methods for spindle detection, which require high levels of resources and are error prone. Newer approaches to spindle detection based on deep-learning procedures could overcome the difficulties of previous detection methods, and thus open up new possibilities for the practical application of sleep spindles as biomarkers in the psychiatric practice.
BACKGROUND: The sleep spindle is a graphoelement of an electroencephalogram (EEG), which can be observed in light and deep sleep. Alterations in spindle activity have been described for a range of psychiatric disorders. Due to their relatively constant properties, sleep spindles may therefore be potential biomarkers in psychiatric diagnostics. METHOD: This article presents an overview of the state of the science on the characteristics and functions of the sleep spindle as well as known alterations of spindle activity in psychiatric disorders. Various methodological approaches and developments of spindle detection are explained with respect to their potential for application in psychiatric diagnostics. RESULTS AND CONCLUSION: Although alterations in spindle activity in psychiatric disorders are known and have been described in detail, their exact potential for psychiatric diagnostics has yet to be fully determined. In this respect, the acquisition of knowledge in research is currently constrained by manual and automated methods for spindle detection, which require high levels of resources and are error prone. Newer approaches to spindle detection based on deep-learning procedures could overcome the difficulties of previous detection methods, and thus open up new possibilities for the practical application of sleep spindles as biomarkers in the psychiatric practice.
Authors: Fabio Ferrarelli; Reto Huber; Michael J Peterson; Marcello Massimini; Michael Murphy; Brady A Riedner; Adam Watson; Pietro Bria; Giulio Tononi Journal: Am J Psychiatry Date: 2007-03 Impact factor: 18.112
Authors: James W Antony; Luis Piloto; Margaret Wang; Paula Pacheco; Kenneth A Norman; Ken A Paller Journal: Curr Biol Date: 2018-05-24 Impact factor: 10.834