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.
Signatures of depression in non-stationary biometric time-series / M., Culic; Gjoneska, Biljana; H., Hinrikus; M., Jändel; W., Klonowski; H., Liljenström; N., Nada Pop Jordanova; D., Psatta; D., Rosen; B., Wahlind. - In: COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE. - ISSN 1687-5265. - STAMPA. - 2009:(2009). [10.1155/2009/989824]
Signatures of depression in non-stationary biometric time-series
GJONESKA, BILJANA;
2009
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
