Research article - Peer-reviewed, 2009
Signatures of Depression in Non-Stationary Biometric Time Series
Culic, Milka; Gjoneska, Biljana; Hiie, Hinrikus; Jändel, Magnus; Klonowski, Wlodzimierz; Liljenström, Hans; Pop-Jordanova, Nada; Psatta, Dan; von, Rosen Dietrich; Wahlund, BjörnAbstract
This paper is based on a discussion that was held during a special session on models of mental disorders, at the NeuroMath meeting in Stockholm, Sweden, in September 2008. At this occasion, scientists from different countries and different fields of research presented their research and discussed open questions with regard to analyses and models of mental disorders, in particular depression. The content of this paper emerged from these discussions and in the presentation we briefly link biomarkers (hormones), bio-signals (EEG) and biomaps (brain-maps via EEG) to depression and its treatments, via linear statistical models as well as nonlinear dynamic models. Some examples involving EEG-data are presentedPublished in
Computational Intelligence and Neuroscience2009, volume: 2009, article number: 989824
Publisher: Hindawi Publishing Corporation
Authors' information
Culic, Milka
Gjoneska, Biljana
Hiie, Hinrikus
Jändel, Magnus
Klonowski, Wlodzimierz
Swedish University of Agricultural Sciences, Department of Energy and Technology
Pop-Jordanova, Nada
Psatta, Dan
Swedish University of Agricultural Sciences, Department of Energy and Technology
Wahlund, Björn
UKÄ Subject classification
Neurosciences
Publication Identifiers
DOI: https://doi.org/10.1155/2009/989824
URI (permanent link to this page)
https://res.slu.se/id/publ/28592