Research areas

• – Computational psychiatry
• – Cognitive neuroscience

Short biography

I hold a PhD in computational neuroscience from the Bernstein Center for Computational Neuroscience and the Charité Berlin. My academic background is in psychology and I am currently a postdoctoral researcher with the TAM cluster in Marburg. My research focuses on applying Bayesian models to decision-making processes in the context of both health and disease, with active projects exploring depression, chronic pain, autism and psychosis.

Relevant publications

• Eckert, A. L., Pabst, K., & Endres, D. M. (2022). A Bayesian model for chronic pain. Frontiers in Pain Research, 3:966034.
• Kirchner, L., Eckert, A. L., & Berg, M. (2022). From broken models to treatment selection: Active inference as a tool to guide clinical research and practice. Clinical Psychology in Europe, 4(2).
• Eckert, A. L., Gounitski, Y., Guggenmos, M., & Sterzer, P. (2023). Cross-Modality Evidence for Reduced Choice History Biases in Psychosis-Prone Individuals. Schizophrenia Bulletin, 49(2), 397-406.
• Kirchner, L., Eckert, A. L., Berg, M., Endres, D., Straube, B., & Rief, W. (2024). An active inference approach to interpersonal differences in depression. New Ideas in Psychology, 74, 101092.
• Eckert, A. L., Pawlowski, J., Rief, W., Endres, D., & Kirchner, L. (2023). Simulating Active Inference of Interpersonal Context Within and Across Mental Disorders.
• Eckert, A. L., Blume, J. S., Knopp, B., Schuetz, A., & Endres, D. (2024). Distinct Biases Shape Perceptual Inference Dynamics Along the Autism-Psychosis Spectra (pre-print).