Decoding of Processing Preferences from Language Paradigms by Means of EEG-ERP Methodology: Risk Markers of Cognitive Vulnerability for Depression and Protective Indicators of Well-Being? Cerebral Correlates and Mechanisms

Author:

Herbert CorneliaORCID

Abstract

Depression is a frequent mental affective disorder. Cognitive vulnerability models propose two major cognitive risk factors that favor the onset and severity of depressive symptoms. These include a pronounced self-focus, as well as a negative emotional processing bias. According to two-process models of cognitive vulnerability, these two risk factors are not independent from each other, but affect information processing already at an early perceptual processing level. Simultaneously, a processing advantage for self-related positive information including better memory for positive than negative information has been associated with mental health and well-being. This perspective paper introduces a research framework that discusses how EEG-ERP methodology can serve as a standardized tool for the decoding of negative and positive processing biases and their potential use as risk markers of cognitive vulnerability for depression, on the one hand, and as protective indicators of well-being, on the other hand. Previous results from EEG-ERP studies investigating the time-course of self-referential emotional processing are introduced, summarized, and discussed with respect to the specificity of depression-related processing and the importance of EEG-ERP-based experimental testing for well-being and the prevention and treatment of depressive disorders.

Funder

German Research Foundation

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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