Abstract

Emotion and motivation are evolutionary highly preserved drivers of behaviour and dysregulations in these

processes represent a transdiagnostic feature across the most common mental disorders. The prevailing

neuroimaging approaches are limited with respect to establishing process-specific and comprehensive brain

models of the highly subjective conscious emotional and motivational experiences in humans. This in turn

critically hampers the development and evaluation of novel interventions for mental disorders. In the present

talk I will outline (1) how machine learning-based advanced decoding of fMRI-based neural activity can

precisely determine the momentary emotional and motivational state in humans, (2) how these neural

signatures can be translated into ecologically valid neurocomputational signatures that track conscious

experiences in dynamic situations, and (3) how these neurocomputational signatures can be employed to

rapidly test the therapeutic potential of neuropeptides (oxytocin, angiotensin II) as innovative treatments to

enhance emotion and motivation regulation in humans.