Liljenström, Hans
- Department of Energy and Technology, Swedish University of Agricultural Sciences
Research article2009Peer reviewedOpen access
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
von Rosen, Dietrich
- Department of Energy and Technology, Swedish University of Agricultural Sciences
- Department of Energy and Technology, Swedish University of Agricultural Sciences
SLU Authors
UKÄ Subject classification
Neurosciences
Publication identifier
DOI: https://doi.org/10.1155/2009/989824
Permanent link to this page (URI)
https://res.slu.se/id/publ/28592