Image processing within a locally complete retinal ganglion cell population (D02 (ehem. 12))

• Subject Area: Cognitive, Systems and Behavioural Neurobiology
• Term: since 2017
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 276693517

The goal of this project continues to be the development of a convolutional neural network (CNN) model that is able to accurately describe how image information is nonlinearly transformed in the retinal network and, hence, can predict the responses of the approx. 40 different retinal output channels to new stimuli. A key challenge of such models is that they require large amounts of training data. Therefore, the project will maintain its dual focus to (1) improve experimental aspects related to maximising data yield, and (2) to develop analysis and modelling frameworks that can discount heterogeneities both between neurons of the same type and between different experimental sessions.

• DFG Programme: Collaborative Research Centres
• Subproject of: SFB 1233: Robust Vision - Inference Principles and Neural Mechanisms
• Applicant Institution: Eberhard Karls Universität Tübingen
• Project Heads: Professor Dr. Matthias Bethge; Professor Dr. Thomas Euler