A posterior-alpha ageing network is differentially associated with antidepressant effects of venlafaxine and rTMS.

Major depressive disorder (MDD) is a highly prevalent psychiatric disorder, but chances for remission largely decrease with each failed treatment attempt. It is therefore desirable to assign a given patient to the most promising individual treatment option as early as possible. We used a polygenic score (PGS) informed electroencephalography (EEG) data-driven approach to identify potential predictors for MDD treatment outcome.

Associations between psychotropic drugs and rsEEG connectivity and network characteristics: a cross-sectional study in hospital-admitted psychiatric patients.

Introduction: Resting-state EEG (rsEEG) characteristics, such as functional connectivity and network topology, are studied as potential biomarkers in psychiatric research. However, the presence of psychopharmacological treatment in study participants poses a potential confounding factor in biomarker research. To address this concern, our study aims to explore the impact of both single and multi-class psychotropic treatments on aforementioned rsEEG characteristics in a psychiatric population.

[Sustainability in Flemish and Dutch mental health care].

Background: The Flemish and Dutch (mental) health sectors cause greenhouse gas emissions and therefore will have to make an effort to reduce their climate impact.

Aim: To assess whether differences can be found in the climate policies of Flemish and Dutch mental health institutions.

Method: Descriptive research based on a sustainability questionnaire, in which concrete actions, objectives and ambitions in the field of sustainability were questioned at Flemish and Dutch mental health institutions.

A polygenic-informed approach to a predictive EEG signature empowers antidepressant treatment prediction: A proof-of-concept study.

The treatment of major depressive disorder (MDD) is hampered by low chances of treatment response in each treatment step, which is partly due to a lack of firmly established outcome-predictive biomarkers. Here, we hypothesize that polygenic-informed EEG signatures may help predict antidepressant treatment response. Using a polygenic-informed electroencephalography (EEG) data-driven, data-reduction approach, we identify a brain network in a large cohort (N=1,123), and discover it is sex-specifically (male patients, N=617) associated with polygenic risk score (PRS) of antidepressant response.

Event-related potentials and use of psychotropic medication in major psychiatric disorders.

Background: Attention deficits measured using event-related potentials (ERPs) have been frequently reported in several major psychiatric disorders, e.g. mood disorder (MD), psychotic disorder (PD) and substance use disorder (SUD).