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Onken, A., and Obermayer, K. (2009). A Frank Mixture Copula Family for Modeling Higher-Order Correlations of Neural Spike Counts [23]. J. Phys.: Conf. Ser.. IOP Publishing, 012019.


Clemens, J., Weschke, G., Vogel, A., and Ronacher, B. (2010). Intensity invariance properties of auditory neurons compared to the statistics of relevant natural signals in grasshoppers [24]. Journal of Comparative Physiology A, 285-297.


Clemens, J., and Hennig, R.M. (2013). Computational principles underlying the recognition of acoustic signals in insects [25]. Journal of Computational Neuroscience, 75-85.


Porbadnigk, A.K., Görnitz, N., Kloft, M., and Müller, K.-R. (2013). Decoding brain states by supervising unsupervised learning [26]. Journal of Computing Science and Engineering (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.


Samek, W., Vidaurre, C., Müller, K.-R., and Kawanabe, M. (2012). Stationary common spatial patterns for brain-computer interfacing [28]. Journal of Neural Engineering, 026013.


Blythe, D.A.J., Meinecke, C., von Bünau, P., and Müller, K.-R. (2013). Explorative data analysis for changes in neural activity [29]. Journal of Neural Engineering, 026018.


Hackmack, K., Weygandt, M., Wuerfel, J., Pfueller, C., Bellmann-Strobl, J., Paul, F., and Haynes, J.-D. (2012). can we overcome the clinico-radiological paradox in multiple sclerosis? [30]. Journal of Neurology, 2151-60.


Clemens, J., Wohlgemuth, S., and Ronacher, B. (2012). Nonlinear computations underlying temporal and population sparseness in the auditory system of the grasshopper [31]. Journal of Neuroscience, 10053-10062.


Clemens, J., and Ronacher, B. (2013). Feature extraction and integration underlying perceptual decision making during courtship behavior [32]. Journal of Neuroscience, 12136-12145.


Spitzer, B., Wacker, E., and Blankenburg, F. (2010). Oscillatory correlates of vibrotactile frequency processing in human working memory [33]. Journal of Neuroscience, 4496-502.


Susemihl, A.K., Meir R., and Opper, M. (2013). Dynamic state estimation based on Poisson spike trains: Towards a theory of optimal encoding [34]. Journal of Statistical Mechanics: Theory and Experiments


Schönfelder, V., and Wichmann, F. (2013). Identification of stimulus cues in narrow-band tone-in-noise detection using sparse observer models [35]. Journal of the Acoustic Society of America, 447-463.


Schönfelder, V., and Wichmann, F.A. (2012). Sparse regularized regression identi es behaviorally-relevant stimulus features from psychophysical data [36]. Journal of the Acoustical Society of America, 3953-3969.


Schönfelder, V.H., and Wichmann, F.A. (2013). Identi cation of stimulus cues in narrow-band tone-in-noise detection using sparse observer models [37]. Journal of the Acoustical Society of America, 447-463.


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