Haeusler, C. (2014). The brain as Data Source - Model - Inspiration. Freie Universität Berlin

Schoenfelder, V. (2013). Identification of Stimulus Cues in Tone-in-Noise Detection with Sparse Logistic Regression. Technische Universität Berlin

Dold, H. (2013). On modelling data from visual psychophysics: A Bayesian graphical model approach. Technische Universität Berlin

Pamir, E. (2013). From behavioral plasticity to neuronal computation: An investigation of associative learning in the honeybee brain. Freie Universität Berlin

Schleimer, J.H. (2013). Spike statistics and coding properies of phase models – From ion channels to neural coding. Humboldt-Universität zu Berlin

Bießmann, F. (2012). Data-driven analysis for multimodal neuroimaging. Technische Universität Berlin

Clemens, J. (2012). Neural computation in small sensory systems. Lessons on sparse and adaptive coding. Humboldt-Universität zu Berlin

Hackmack, K. (2012). Decoding Multiple Sclerosis and Related Disease Parameters Using Structural Brain MRI and Multivariate Analysis Algorithms. BCCN/ Charité Berlin

Franke, F. (2011). Real-Time Analysis of Extracellular Recordings. Technische Universität Berlin

Wacker, E. (2011). Tactile Feature Processing and Attentional Modulation in the Human Somatosensory System. BCCN / TU Berlin , 108.

Onken, A. (2011). Stochastic Analysis of Neural Spike Count Dependencies. Technische Universität Berlin

Srinivasan, S.D. (2011). Representation, Inference, and Learning on Structured Data. TU Berlin

Biessmann, F. (2011). Data-driven analysis for multimodal neuroimaging. Technische Universität Berlin