INFER

INFORMATIVE FEATURES OF DEPRESSION


Relevant for Research Area

B - Core Technologies

C - Applications


Summary

Main project goals
INFER: Informative features of depression aims at the patient-specific, data-driven identification of informative features of major depression disorder (MDD), in patients who are candidates for ---or recipients of--- treatment with deep brain stimulation (DBS). The project develops tools to prepare the development of an adaptive DBS approach for MDD. Specifically, in INFER the relation between MDD symptoms, behavioral correlates thereof, DBS-strategy, and neural markers is sought.

Milestones and results achieved
We have designed and gamified behavioral paradigm to establish levels of anhedonia, one of the major symptoms of MDD. The paradigm has been implemented as an app for Android-based tablets and has undergone an iterative improvement process, which allowed us to include it in the standard clinical routine at the Department of Psychiatry and Psychotherapy, University Medical Center, in the group of PI Schläpfer.


With the developed paradigm, we have executed a pilot study with 12 MDD patients, totaling 22 behavioral-assessment sessions, in which we identified paradigm-specific behavioral features that are candidates to describe the affected hedonic behavior of patients. The behavioral features in addition were correlated with standard clinical ratings such as the Montgomery–Åsberg depression rating scale (MADRS) and the Hamilton rating scale for depression (HAMD).


Publications and Achievements

Hannah Kilian, Sebastian Castaño-Candamil, A. Zhelo, Michael Tangermann, Volker Coenen, Thomas Schläpfer: Informative Features of Depression (INFER) - Measuring Symptoms reliably and precisely - the prerequisite for building closed loop stimulation systems. Talk given at the BrainLinks-BrainTools Annual Workshop 2018, Otto Krayer Haus, Freiburg.

S. Castaño-Candamil, H. Kilian, A. Zhelo, V. A. Coenen, T. Schläpfer, M. Tangermann: INFER - Measuring depression symptoms reliably and precisely: Towards closed-loop aDBS. Poster presented at the BrainLinks-BrainTools Annual Workshop 2018, Otto Krayer Haus, Freiburg.