Characterizing the dynamics, reactivity and controllability of moods in depression with a Kalman filter

Mood dynamics are richly and profoundly altered in depressed states. The humble Kalman filter is a well-established, rich framework to characterise mood dynamics. Its application to EMA data is valid; straightforward; and likely to result in substantial novel insights both into mechanisms and treatments.

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Publication Details

Journal
PLoS Computational Biology
Published
2024-09-23
DOI
https://doi.org/10.1371/journal.pcbi.1012457
Citations
3
Primary Topic
Mental Health Research Topics
Type
article
Field-Weighted Citation Impact
1.52

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article

Characterizing the dynamics, reactivity and controllability of moods in depression with a Kalman filter

Ruud van Winkel, Bart P. F. Rutten, Nele Jacobs, Marc D. Binder et al.
3 citations
PLoS Computational Biology
Mental Health Research Topics
1.52
article

Characterizing the dynamics, reactivity and controllability of moods in depression with a Kalman filter

Ruud van Winkel, Bart P. F. Rutten, Nele Jacobs, Marc D. Binder, Quentin J. M. Huys, Philippe Delespaul, Jolanda Malamud, Sinan Gülöksüz, Cathérine Derom, Evert Thiery
article en
3 citations

Abstract

Mood dynamics are richly and profoundly altered in depressed states. The humble Kalman filter is a well-established, rich framework to characterise mood dynamics. Its application to EMA data is valid; straightforward; and likely to result in substantial novel insights both into mechanisms and treatments.

PLoS Computational BiologyVol. 20(9)
University of Antwerp (BE), Maastricht University Medical Centre (NL), Ghent University Hospital (BE), Yale University (US), National Hospital for Neurology and Neurosurgery (GB), VIB-KU Leuven Center for Brain & Disease Research (BE), University Psychiatric Hospital (SI), University College London (GB), Open University of the Netherlands (NL), KU Leuven (BE)
Wellcome, Wellcome Trust, International Max Planck Research School for Environmental, Cellular and Molecular Microbiology, National Institute for Health and Care Research, Max-Planck-Gesellschaft, University College London Hospitals NHS Foundation Trust, International Max Planck Research School for Advanced Methods in Process and Systems Engineering, UCLH Biomedical Research Centre
Openalex Percentile: Top 16%
Mental Health Research Topics
1.52
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