Summary

In order to make sense of our noisy and ambiguous environment, the human brain is constantly generating predictions to facilitate the processing of incoming sensory information. We are using theory of Bayesian inference and predictive processing to develop computational models for understanding the mechanistic underpinnings of cognitive processing in healthy brains, studying inter-individual differences using personality traits, and of potential cognitive alterations in psychiatric disorders, such as psychosis. The aim of the modelling is to build unifying approaches that allow translation between different cognitive domains such as decision making, language or memory processing. In our research, we therefore develop and apply computational models to novel behavioural paradigms, which combine different cognitive domains (e.g., language processing and episodic memory), and brain data (i.e., f/MRI, EEG, spectroscopy, PET).

Please, visit my webpage for current projects and open positions: https://franziskaknolle.com

Fig: Levels of glutamate in the left DLPFC predict how much individuals with increase psychotic-like experiences rely on prior knowledge during language comprehension.

Leitung

Mitarbeiter

Elisabeth F. Sterner (PhD Candidate);
Pritha Sen (PhD Candidate);
Verena F. Demler (MD science Candidate);
Zachary Tefertiller (PhD Candidate);
Julia Kohler (MD science Candidate)

Kooperation

• Dr Lucy MacGregor (University of Cambridge);
• Dr James Kesby (University of Queensland);
• Dr Helen Blank (UKE Hamburg);
• Dr Kelly Diederen (King’s College London);
• Prof Chris Mathys (Aarhus University);
• Prof Graham Murray (University of Cambridge)