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All Publications by GRK Members

2013

Höhne, J., Krenzlin, K., Dähne, S., and Tangermann, M. (2013). Natural stimuli improve auditory BCIs with respect to ergonomics and performance. 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. 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. PLoS ONE


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


Haenicke, J., Pamir, E., and Nawrot, M.P. (2013). A computational model of fast associative learning in the honeybee. 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. Conference paper, 6th International IEEE EMBS Conference on Neural Engineering



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





Susemihl, A.K., Meir R., and Opper, M. (2013). Dynamic state estimation based on Poisson spike trains: Towards a theory of optimal encoding. Journal of Statistical Mechanics: Theory and Experiments


Pangalos, M., Donoso, J.R., Winterer, J., Zivkovic, A.R., Kempter, R., Maier, N., and Schmitz, D. (2013). Recruitment of oriens-lacunosum-moleculare interneurons during hippocampal ripples. Proc. Natl. Acad. Sci. USA, 4398-4403.


Samek, W., Blythe, D., Müller, K.-R., and Kawanabe, M. (2013). Robust spatial filtering with beta divergence. Advances in Neural Information Processing Systems


Kawanabe, M., Samek, W., Müller, K.-R., Vidaurre, C. (2013). Robust common spatial filters with a maxmin approach. Neural Computation


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