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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, Björn

Abstract

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 presented

Published in

Computational Intelligence and Neuroscience
2009, 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