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E

Bhattacharyya, A., Bießmann, F., Veit, J., Kretz., R., and Rainer, G. (2012). Functional and laminar dissociations between muscarinic and nicotinic neuromodulation in the tree shrew primary visual cortex. Eur J Neurosci, 1270-80.


Franke, F., Natora, M., Meier, P., Hagen, E., Pettersen, K.H., Linden, H., Einevoll, G., and Obermayer, K. (2010). An Automated Online Positioning System and Simulation Environment for Multi-Electrodes in Extracellular Recordings. 32nd Annual International IEEE EMBS Conference 2010, Buenos Aires, Argentina, 593-597.


D

Häusler, C., and Susemihl, A. (2012). Temporal autoencoding restricted Boltzmann machines. Deep Learning and Unsupervised Feature Learning Workshop at NIPS


C

Einevoll, G.T., Franke, F., Hagen, E., Pouzat, C., and Harris, K.D. (2011). Towards Reliable Spike-Train Recordings from Thousands of Neurons with Multielectrodes. Current Opinion in Neuroiology, 11-17.


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


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. 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. Conference Proceedings IEEE Engineering in Medicine and Biology Society, 3692-5.


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


Wacker, E., Spitzer, B., Driver, J., and Blankenburg, F. (2011). Top-down attentional bias for perception of tactile stimulus attributes. Conference abstract: Frontiers in Compututational Neuroscience BC11: Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting


Sonnenschein, B., Zaks, M.A., Neiman, A.B., and Schimansky-Geier, L. (2013). How noise and coupling patterns a ect collective dynamics of excitable elements. Conference Abstract at the Bernstein Conference, Tubingen, Germany


Roemschied, F., Schleimer, J.-H., Eberhard, M., Ronacher, B., Schreiber, S. (2013). Cellular temperature compensation of sensory receptor neuron responses. Computational Neuroscience Meeting in Paris, France


Clemens, J., Rau, F., Hildebrandt, J., and Hennig, M. (2012). Adaptive sharpening of tuning in the auditory system of the cricket. Computational and Systems Neuroscience 2012


Onken, A., Grünewälder, S., Munk, M.H.J., and Obermayer, K. (2010). A Non-Stationary Copula-Based Spike Count Model. Computational and Systems Neuroscience


Reverberi, C., Görgen, K., and Haynes, J.-D. (2011). Compositionality of Rule Representations in Human Prefrontal Cortex. Cerebral Cortex


Spitzer, B., Gloel, M., Schmidt, T.T., and Blankenburg, F. (2013). Working memory coding of analog stimulus properties in the human prefrontal cortex. Cerebral Cortex


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