Agnes Norbury

Fellow
Max Planck UCL Centre for Computational Psychiatry and Ageing Research

Curriculum Vitae

  • BA (Hons) in Natural Sciences, 2009, University of Cambridge
  • PhD in Neuroscience, 2015, University College London

Research interests

  • Computational approaches to understanding mechanisms of successful psychological treatment of depression, anxiety, and post-traumatic stress disorders
  • Causal structure learning and the role of maladaptive causal beliefs in psychological disorders
  • Formal modelling (e.g., reinforcement learning) and passive sensing approaches to understanding cognitive-behavioural patterns involved in symptom maintenance

Selected publications

Norbury, A., Brinkman, H., Kowalchyk, M., Monti, E., Pietrzak, R. H., Schiller, D., & Feder, A. (2021, Mar 8). Latent cause inference during extinction learning in trauma-exposed individuals with and without PTSD. Psychol Med, 1-12. https://doi.org/10.1017/s0033291721000647

Norbury, A., Liu, S. H., Campaña-Montes, J. J., Romero-Medrano, L., Barrigón, M. L., Smith, E., Artés-Rodríguez, A., Baca-García, E., & Perez-Rodriguez, M. M. (2021, Aug). Social media and smartphone app use predicts maintenance of physical activity during Covid-19 enforced isolation in psychiatric outpatients. Mol Psychiatry, 26(8), 3920-3930. https://doi.org/10.1038/s41380-020-00963-5

Norbury, A., Robbins, T. W., & Seymour, B. (2018, May 8). Value generalization in human avoidance learning. elife, 7. https://doi.org/10.7554/eLife.34779

Sükei, E., Norbury, A., Perez-Rodriguez, M. M., Olmos, P. M., & Artés, A. (2021, Mar 22). Predicting Emotional States Using Behavioral Markers Derived From Passively Sensed Data: Data-Driven Machine Learning Approach. JMIR Mhealth Uhealth, 9(3), e24465. https://doi.org/10.2196/24465

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