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Onken, A., Grünewälder, S., and Obermayer, K. (2009). Extensions to copula based modeling of spike counts [23]. Front. in Comput. Neurosci.

Onken, A., and Obermayer, K. (2008). Stimulus-Independence of Noise Correlations is Beneficial for Short-Term Population Coding in MT [24]. Neuron, 4.

Onken, A., and Obermayer, K. (2009). A Frank Mixture Copula Family for Modeling Higher-Order Correlations of Neural Spike Counts [25]. J. Phys.: Conf. Ser.. IOP Publishing, 012019.

Onken, A. (2011). Stochastic Analysis of Neural Spike Count Dependencies [26]. Technische Universität Berlin

Onken, A., Dragoi, V., and Obermayer, K. (2012). A maximum entropy test for evaluating higher-order correlations in spike counts [27]. PLoS Comput. Biol., e1002539.

Ostwald, D., Spitzer, B., Guggenmos, M., Schmidt, T., Kiebel, S., and Blankenburg, F. (2012). Evidence for neural encoding of Bayesian surprise in human somatosensation [28]. NeuroImage, 177-188.


Pamir, E., Schleyer, M., Saumweber, T., Gerber, B., and Nawrot, M.P. (2011). Reverse engineering in Drosophila larvae - Modeling neural control of learned versus innate behavior [29]. Front. Comput. Neurosci. Conference Abstract: Computational Neuroscience and Neurotechnology Bernstein Conference & Neurex Annual Meeting.

Pamir, E., Eisenhardt, D., Stollhoff, N., Menzel, R., Nawrot, M.P. (). Evidence for one-shot learning in the honeybee [30]. 9th Göttingen Meeting of the German Neuroscience Society, March 23-27

Pamir, E. (2013). From behavioral plasticity to neuronal computation: An investigation of associative learning in the honeybee brain [31]. Freie Universität Berlin

Pamir, E. et al. (2011). Average group behavior does not represent individual behavior in classical conditioning of the honeybee [32]. Learning and Memory

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 [33]. Proc. Natl. Acad. Sci. USA, 4398-4403.

Porbadnigk, A., Antons, J.N., Blankertz, B., Tredes, M.S., Schleicher, R., Möller, S., and Curio, G. (2010). Using ERPs for assessing the (sub)conscious perception of noise [34]. Conference Proceedings IEEE Engineering in Medicine and Biology Society, 2690-2693.

Porbadnigk, A.K., Scholler, S., Blankertz, B., Ritz, A., Born, M., Scholl, R., Müller, K.-R., Curio, G., and Treder, M.S. (2011). Revealing the neural response to imperceptible peripheral flicker with machine learning [35]. Conference Proceedings IEEE Engineering in Medicine and Biology Society, 3692-5.

Porbadnigk, A.K., Görnitz, N., Kloft, M., and Müller, K.-R. (2013). Decoding brain states by supervising unsupervised learning [36]. Journal of Computing Science and Engineering (accepted)

Porbadnigk, A.K., Antons, J.N., Treder, M.S., Blankertz, B., Schleicher, R., Möller, S., and Curio, G. (2011). ERP assessment of word processing under broadcast bit rate limitations [37]. Neuroscience Letters, e49.

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