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Porbadnigk, A.K., Görnitz, N., Kloft, M., and Müller, K.-R. (2013). Decoding brain states by supervising unsupervised learning [23]. Journal of Computing Science and Engineering (accepted)

Dähne, S., Bießmann, F., Meinecke, F.C., Mehnert, J., Fazli, S., and Müller, K.-R. (2013). Integration of multivariate data streams with bandpower signals [24]. IEEE Transactions on Multimedia, 1001-1013.

Daähne, S., Meinecke, F.C., Haufe, S., Höhne, J., Tangermann, M., Müller, K.-R., and Nikulin, V. (2013). SPoC: a novel framework for relating the amplitude of neuronal oscillations to behaviorally relevant parameters [25]. NeuroImage (in press)

Schreuder, M., Riccio, A., Risetti, M., Dähne, S., Ramsey, A., Williamson, J., Mattia, D., and Tangermann, M. (2013). User-centered design in BCI - a case study [26]. Artificial Intelligence in Medicine (accepted)

Höhne, J., Krenzlin, K., Dähne, S., and Tangermann, M. (2013). Natural stimuli improve auditory BCIs with respect to ergonomics and performance [27]. Journal of Neural Engineering, 045003.

Schönfelder, V.H., and Wichmann, F.A. (2013). Identi cation of stimulus cues in narrow-band tone-in-noise detection using sparse observer models [28]. Journal of the Acoustical Society of America, 447-463.

Meckenhäuser, G., Hennig, R.M., and Nawrot, M.P. (2013). Critical song features for auditory pattern recognition in crickets [29]. PLoS ONE

Samek, W., Meinecke, F.C., and Müller, K.-R. (2013). Transferring subspaces between subjects in brain-computer interfacing [30]. IEEE Transactions on Biomedical Engineering

Haenicke, J., Pamir, E., and Nawrot, M.P. (2013). A computational model of fast associative learning in the honeybee [31]. Conference talk, symposium 13, 10th Meeting of the German Neuroscience Society Gottingen

Helgadottir, L.I., Haenicke, J., Landgraf, T., Rojas, R., and Nawrot, M.P. (2013). Conditioned behavior in a robot controlled by a spiking neural network [32]. Conference paper, 6th International IEEE EMBS Conference on Neural Engineering

Schoenfelder, V. (2013). Identification of Stimulus Cues in Tone-in-Noise Detection with Sparse Logistic Regression [33]. Technische Universität Berlin

Sonnenschein, B., Sagués, F., and Schimansky-Geier, L. (2013). Networks of noisy oscillators with correlated degree and frequency dispersion [34]. European Physical Journal B, 12.

Dold, H. (2013). On modelling data from visual psychophysics: A Bayesian graphical model approach [35]. Technische Universität Berlin

Pamir, E. (2013). From behavioral plasticity to neuronal computation: An investigation of associative learning in the honeybee brain [36]. Freie Universität Berlin

Schleimer, J.H. (2013). Spike statistics and coding properies of phase models – From ion channels to neural coding [37]. Humboldt-Universität zu Berlin

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