Neurocognition and Mental Health
Research focus
Our research focuses on uncovering the neurophysiological mechanisms underlying cognitive biases and their modification, to translate cognitive science into clinically meaningful applications. We adopt a multi-method approach that integrates cognitive psychology paradigms, fMRI, EEG/ERP, autonomic measures, personality assessments, and advanced analytical techniques, including machine learning. In collaboration with psychiatrists, data scientists, and computer scientists, we strive to develop diagnostic support systems and personalized cognitive training interventions to alleviate symptoms of anxiety and depression across diverse populations.
Research projects
Neurocognitive-physiological markers of anxiety and depression
Given the high prevalence, comorbidity, and limited treatment success for anxiety and depression, there is a pressing need for more precise diagnostic approaches. Current methods, based mostly on self-reported symptoms, often yield imprecise results. Our study introduces a transdiagnostic framework that examines emotion and cognition by integrating cognitive biases, physiological responses, and neural signatures to better characterize these disorders. Using fMRI, ECG, blood pressure, and cognitive tasks, we aim to identify diagnostic markers and underlying subtypes across the disorders. Machine learning will be used to predict symptom severity and cluster subgroups based on neurophysiological patterns. This integrative approach may advance diagnostic accuracy and support the development of more personalized interventions. The project is led by Dr. Thalia Richter.
We are currently looking for volunteers to take part in the EmoCog-study. For further information, please visit our study participant recruitment pages. Please note that these webpages are only in German.
High-resolution fMRI to reveal subcortical dynamics in emotional processing
Evidence highlights the important role of subcortical regions in early emotion-attention interactions. We will use high-resolution fMRI to examine neural dynamics during emotional processing. We combine behavioral and physiological measures to assess emotional responses and explore how individual differences in anxiety and depression relate to neural activation.
Collaborations
Our research is carried out in collaboration with the Cognition-Emotion Interactions (CEI) lab at the University of Haifa.
