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Analysis of Neural Data

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Mohr, J., Hess, A., Scholz, M. and Obermayer, K. (2003). Segmentation of 2 1/2 D Brain Image Stacks with Automatic Extraction and Visualization of Functional Information [8]. Proceedings of the IEEE International Conference of Image Processing - ICIP03, 1089 – 1092.,


Mohr, J., Seo, S., Puls, I., Heinz, A. and Obermayer, K. (2008). Target Selection: A New Learning Paradigm and its Application to Genetic Association Studies [9]. Proceedings of the ICMLA '08: The Seventh International Conference on Machine Learning and Applications. IEEE, 182 – 187.,10.1109/ICMLA.2008.58


Onken, A., Grünewälder, S., Munk, M. and Obermayer, K. (2009). Modeling Short-Term Noise Dependence of Spike Counts in Macaque Prefrontal Cortex [10]. Advances in Neural Information Processing Systems 21. MIT Press, 1233 – 1240.,


Onken, A., Grünewälder, S. and Obermayer, K. (2009). Correlation Coefficients are Insufficient for Analyzing Spike Count Dependencies [11]. Advances in Neural Information Processing Systems 22. MIT Press, 1383 – 1391.,


Pielot, R., Scholz, M., Obermayer, K., Gundelfinger, E. and Hess, A. (1999). Optimiertes Warping durch gewichtete Summen von Verschiebungsvektoren - eine neue Methode zur Reduktion von interindividuellen Variabilitäten von Hirndaten [12]. Bildverarbeitung für die Medizin. Springer-Verlag Heidelberg, 417 – 421.,


Pielot, R., Scholz, M., Obermayer, K., Gundelfinger, E. and Hess, A. (2000). A New Approach to Define Landmarks for Point-Based Warping in Brain Imaging [13]. Bildverarbeitung für die Medizin. Springer-Verlag Heidelberg, 28 – 32.,


Pielot, R., Scholz, M., Obermayer, K., Gundelfinger, E. and Hess, A. (2000). Point-Based Warping with Optimized Weighting Factors of Displacement Vectors. [14]. Medical Imaging 2000, 1387 – 1395.,


Pielot, R., Scholz, M., Obermayer, K., Gundelfinger, E. and Hess, A. (2001). 3D Edge Detection to Define Landmarks for Point-based Warping in Brain Imaging [15]. International Conference on Image Processing - ICIP01. IEEE, 343 – 346.,10.1109/ICIP.2001.958498


Pielot, R., Scholz, M., Obermayer, K., Gundelfinger, E. and Hess, A. (2000). Warping with Optimized Weighting Factors of Displacement Vectors - A New Method to Reduce Inter-Individual Variations in Brain Imaging [16]. 4th IEEE Southwest Symposium on Image Analysis and Interpretation. IEEE, 264 – 268.,10.1109/IAI.2000.839612


Schöner, H., Stetter, M., Schießl, I., Mayhew, J., Lund, J., McLoughlin, N. and Obermayer, K. (2000). Application of Blind Separation of Sources to Optical Recording of Brain Activity [17]. Advances in Neural Information Processing Systems 12. MIT Press, 949 – 955.,


Schießl, I., Schöner, H., Stetter, M., Dima, A. and Obermayer, K. (2000). Regularized Second Order Source Separation [18]. Int. Workshop on Independent Component Analysis and Blind Signal Separation, 111 – 116.,


Schießl, I., Stetter, M., Mayhew, J., McLoughlin, N., Lund, J. and Obermayer, K. (2000). Blind Signal Separation from Optical Imaging Data [19]. Mustererkennung 2000, DAGM-Symposium, 91 – 98.,


Schiessl, I., Stetter, M., Mayhew, J., Askew, S., McLoughlin, N., Levitt, J., Lund, J. and Obermayer, K. (1999). Blind Separation of Spatial Signal Patterns from Optical Imaging Records [20]. ICA99 - International workshop on Idependent Component Analysis and Blind Source Separation, 179 – 184.,


Xie, S., Wang, L., Obermayer, K. and Zhu, F. (2016). Design of a Visual Stimulation System with LED in the Study of Spatial Selective Attention [21]. Advances in Cognitive Neurodynamics. Springer, 461-468.,10.1007/978-981-10-0207-6_63


Seo, S., Mohr, J., Heekeren, H., Heinz, A., Eppinger, B., Li, S. and Obermayer, K. (2012). A voxel selection method for the multivariate analysis of imaging genetics data. [22]. IJCNN. IEEE, 2884-2890.,10.1109/IJCNN.2012.6252766


Proepper, R., Munk, M. and Obermayer, K. (2013). Memory load modulates spiking activity in prefrontal cortex [23]. ,10.12751/nncn.bc2013.0180


Vollgraf, R. and Obermayer, K. (2002). Multi Dimensional ICA to Separate Correlated Sources [24]. Advances in Neural Information Processing Systems 14. MIT Press, 993 – 1000.,


Vollgraf, R., Stetter, M. and Obermayer, K. (2000). Convolutive Decorrelation Procedures for Blind Source Separation [25]. Int. Workshop on Independent Component Analysis and Blind Signal Separation, 515 – 520.,


Dima, A., Scholz, M. and Obermayer, K. (2001). From Multiscale Edges to 3D-Graph Representations of Nerve Cells from Confocal Microscope Scans [26]. Proceedings of the International Conference of Computational Harmonic Analysis, 9 – 10.,


Dima, A., Scholz, M. and Obermayer, K. (1999). Semi-Automatic Quality Determination of 3D Confocal Microscope Scans of Neuronal Cells Denoised by 3D-Wavelet Shrinkage [27]. Wavelet Applications VI - Proceedings of the SPIE, 446 – 457.,10.1117/12.342957


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