Klaas Enno Stephan

Professor Translational Neuromodeling
Honorary Principal, Wellcome Trust Centre for Neuroimaging, University College London

Klaas Enno Stephan is Professor for Translational Neuromodeling at the University of Zurich and the Swiss Federal Institute of Technology (ETH Zurich) where he directs the Translational Neuromodeling Unit (TNU) at the Institute for Biomedical Engineering. Additionally, he is Honorary Principal at the Wellcome Trust Centre for Neuroimaging, University College London.

Following a doctoral degree in medicine and a Ph.D. in neuroinformatics, he has been working on mathematical models for inferring subject-specific mechanisms of brain disease from non-invasive measures of behaviour and neuronal activity. These models aim to quantify both physiological (synaptic) and computational (information processing) principles that underlie maladaptive cognition, such as aberrant learning and decision-making, in individual subjects. The long-term goal is to use these models for a mechanistic re-definition of psychiatric and neurological diseases, leading to pathophysiologically interpretable diagnostic classifications and individual treatment predictions.

Key past achievements include
(i) the development of the anatomical connecitivity database CoCoMac and underlying neuroinformatics tools such as Objective Relational Transformation (ORT),
(ii) development and validation of computational methods for fMRI and electrophysiological data, e.g. contributions to Dynamic Causal Modeling (DCM) and Baysian Model Selection (BMS),
(iii) a wide range of studies on anatomical, functional and effective brain connectivity in health and in brain disease, and
(iv) development and validation of models for inferring synaptic physiology from fMRI and electrophysiological data.

So far, he has published more than 110 peer-reviewed articles, which have been cited more than 4,600 times. He has an h-factor of 37 and is ranked amongst the top 0.1% most cited neuroscientists over the past 10 years worldwide by the Essential Science Indicators.