227-0973-00L  Translational Neuromodeling

SemesterSpring Semester 2015
LecturersK. Stephan
Periodicityyearly course
Language of instructionEnglish


AbstractThis lecture deals with computational modeling of neuronal and cognitive processes for diagnostic applications in psychiatry ("Translational Neuromodeling"). A particular focus is on Bayesian methods and generative models, e.g. dynamic system models for inferring neuronal mechanisms from neuroimaging data, and hierarchical learning models for inference on cognitive mechanisms from behaviour.
ObjectiveTo obtain an understanding of the goals and methods of translational neuromodeling, particularly with regard to Bayesian models of neuroimaging (fMRI, EEG) and behavioural data.
ContentThis lecture deals with computational modeling of neuronal and cognitive processes for diagnostic applications in psychiatry ("translational neuromodeling"). A particular focus is on Bayesian methods and generative models, e.g. dynamic causal models (DCMs) for inferring neuronal mechanisms from neuroimaging data, and hierarchical learning models for inference on cognitive mechanisms from behavioural data. The course illustrates the application of these models to various psychiatric diseases and outlines a general research strategy.
LiteratureSee TNU website:
http://www.biomed.ee.ethz.ch/research/tnu/teaching
Prerequisites / NoticeBasic knowledge of Bayesian statistics, MATLAB programming skills