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Electrical Engineering and Computer ScienceSensory Computation in Neural Systems
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Sonnenschein, B., Zaks, M.A., Neiman, A.B., and Schimansky-Geier, L. (2013). How noise and coupling patterns aect collective dynamics of excitable elements. Conference Abstract at the Bernstein Conference, Tubingen, Germany
Sonnenschein, B., Zaks, M.A., Neiman, A.B., and Schimansky-Geier, L. (2013). Excitable elements controlled by noise and network structure. , 2517-2529.
Sonnenschein, B., and Schimansky-Geier, L. (2012). Onset of synchronization in complex networks of noisy oscillators. Phys. Rev. E
Sonnenschein, B., and Schimansky-Geier, L. (2013). Approximate solution to the stochastic Kuramoto model. Phys. Rev. E. American Physical Society, 052111.
Sonnenschein, B., Sagués, F., and Schimansky-Geier, L. (2013). Networks of noisy oscillators with correlated degree and frequency dispersion. European Physical Journal B, 12.
Sonnenschein, B., and Schimansky-Geier, L. (2013). An approximate solution to the stochastic Kuramoto model.
Spitzer, B., Wacker, E., and Blankenburg, F. (2010). Oscillatory correlates of vibrotactile frequency processing in human working memory. Journal of Neuroscience, 4496-502.
Spitzer, B., Goltz, D., Wacker, E., Auksztulewicz, R., and Blankenburg, F. (2013). Maintenance and manipulation of somatosensory information in ventrolateral prefrontal cortex. Human Brain Mapping, Epub: August 2
Spitzer, B., Wacker, E., and Blankenburg, F. (2010). Oscillatory Correlates of Vibrotactile Frequency Processing in Human Working Memory. J Neurosci., 4496-502.
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
Srinivasan, S.D. (2011). Representation, Inference, and Learning on Structured Data. TU Berlin
Susemihl, A.K.,Meir, R., and Opper, M. (2011). Analytical results for the error in filtering of Gaussian processes. Advances in Neural Information Processing Systems 24, 2303-2311.
Susemihl, A.K., and Opper, M. (2011). An analytical study of population coding of dynamic stimuli. Front. Comput. Neurosci. Conference Abstract: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011
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
van Kemenade, B.M., Seymour, K., Wacker, E., Spitzer, B., Blankenburg, F., and Sterzer, P. (2013). Tactile and visual motion direction processing in hMT+/V5. Neuroimage, Epub: Sep 2012
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