EEG for personalized treatment in psychiatry

Despite the call for new treatment options in psychiatry, the biomarker-informed choice of already available therapy approaches might yield important improvements in the management of several disorders such as major depression or obsessive compulsive disorder. With the outstanding ability of assessing neuronal activity with a high temporal resolution at relatively low costs, the EEG seems a perfect tool for personalized treatment. Source localization algorithms such as low resolution brain electromagnetic tomography (LORETA) in combination with hypothesis driven frameworks such as the vigilance framework (VIGALL) that links electrophysiological arousal patterns with clinical syndromes, might help to guide treatment decisions in the future.

The symposium will give insights into the latest developments of EEG based analysis in major depression and obsessive compulsive disorder. The talks will focus on markers that not only differentiate between pathological conditions and healthy controls but also enable prediction of treatment outcome or the relapse after discontinuation of treatment (Quentin Huys, TNU Zurich). Besides markers that reflect brain arousal (EEG-vigilance framework as presented by Ulrich Hegerl, Leipzig), also findings on EEG-based connectivity analysis (Sebastian Olbrich, PUK Zurich) and emotional reactivity measures will be presented. Since the clinical value of a set of predictive markers increases with the number of alternatives for treatment, several treatment approaches will be covered, ranging from psychopharmacological treatment over electroconvulsive therapy to psychotherapeutic interventions and novel treatment approaches such as ketamine (Martin Brunovsky, Prague).

The human brain takes on different arousal levels which can be separated based on the temporal-spatial pattern of scalp recorded EEG activity. The regulation of brain arousal has been found to be intraindividually stable with considerable interindividual differences. The arousal regulation model of affective disorders describes the pathogenetic impact of disturbed brain arousal regulation in psychiatric disorders.

The Vigilance Algorithm Leipzig (VIGALL), an EEG-based algorithm for the classification of vigilance stages, will be introduced. VIGALL takes into account different frequency bands and the cortical distribution of EEG activity using EEG source localization approaches (Low Resolution Electromagnetic Tomography, LORETA) and has adaptive features concerning individual alpha peaks and amplitude levels. Furthermore, an overview on recent findings on arousal regulation as a diagnostic and predictive biomarker in affective disorders will be given.

Not only the topographic or temporal changes of neuronal activity yield important information on the functional principles of the human brain. A main part of the mode of operation is reflected in the interaction of distinct cortical areas. Thus EEG-based connectivity profiles might serve as biomarkers with a clinical prognostic value.

The talk will give an overview on connectivity measures before presenting recent findings of altered connectivity patterns in disorders like obsessive compulsive disorder and major depression and their association with treatment outcome. The presentation will include results from the large randomized clinical trial “International Study to Predict Optimized Treatment for Depression (iSPOT-D)”.

Novel glutamatergic antidepressant, ketamine, does not improve symptoms in all depressive patients, and it is therefore important to identify neurobiological predictors of treatment response. We pooled data from two double-blind, cross-over, placebo-controlled studies, assessing the effect of single infusion of ketamine (0.54 mg/kg within 30min) in 50 depressive patients to evaluate potential QEEG predictors of treatment response. EEG data were analyzed at baseline, during the infusion and 24hours after ketamine administration using spectral and exact low-resolution electromagnetic tomography (eLORETA) analyses. Responders to ketamine were characterized by higher baseline absolute and relative alpha power and lower relative theta power. At baseline, the responders showed also an increase of alpha-2 current density sources in medial parieto-occipital areas and a decrease of theta sources in subgenual and anterior cingulate as well as in left mediofrontal region. There was no baseline difference between the responders and non-responders in eLORETA-assessed cortical connectivity.

<p>Supported by the grant AZV MZCR 15-33250A and by the project Progres Q35.</p>

Relapses are a major determinant of the long-term outcomes of depression. The relapse risk should therefore feature prominently in decisions about treatment and treatment discontinuation. Although it is known that antidepressant continuation reduced the risk of relapse, there are no known biomarkers to guide individual choices about when to discontinue. AIDA (“Antidepressiva Absetzstudie”) is an ongoing observational study that examines the predictive potential of EEG biomarkers after antidepressant discontinuation. Patients who had a clear response to antidepressants and wish to discontinue their medication are being included. EEG data is acquired during a standardized vigilance paradigm (VIGALL) and a paradigm of emotional reactivity to sad movies. Recruitment is ongoing at both study sites in Berlin and Zurich and we will present the first preliminary results focusing on emotional reactivity measures.