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Analysis of Neural Data

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Balta Beylergila, S., Beck, A., Deserno, L., Lorenz, R., Rapp, M., Schlagenhauf, F., Heinz, A. and Obermayer, K. (2017). Dorsolateral prefrontal cortex contributes to the impaired behavioral adaptation in alcohol dependence. Neuroimage: Clinical, 15, 80–94.


Bucher, D., Scholz, M., Stetter, M., Obermayer, K. and Pflüger, H.-J. (2000). Corrections Methods for Three-dimensional Reconstructions from Confocal Images: I. Tissue Shrinking and Axial Scaling. Journal of Neuroscience Methods, 100, 135 – 143.


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Dima, A., Scholz, M. and Obermayer, K. (2003). Automatic Segmentation and Skeletonization of Neurons from Confocal Microscopy Images Based on the 3-D Wavelet Transform. IEEE TRANSACTIONS ON IMAGE PROCESSING, 11, 790-801.


Dima, A., Scholz, M. and Obermayer, K. (2001). From Multiscale Edges to 3D-Graph Representations of Nerve Cells from Confocal Microscope Scans. 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. Wavelet Applications VI - Proceedings of the SPIE, 446 – 457.,10.1117/12.342957


Dima, A., Scholz, M. and Obermayer, K. (2003). Automatic 3D-Graph Construction of Nerve Cells from Confocal Microscopy Scans. Journal of Electronic Imaging, 12, 134 – 150.


Dima, A., Scholz, M. and Obermayer, K. (2002). Automatic Segmentation and Skeletonization of Neurons from Confocal Microscopy Images based on the 3D Wavelet Transform. IEEE Trans. on Image Proc., 11, 790 – 801.


Dimulescu, C., Gareayaghi, S., Kamp, F., Fromm, S., K., O. and Metzner, C. (2021). Structural Differences between Healthy Subjects and Patients with Schizophrenia and Schizoaffective Disorder: A Graph and Control Theoretical Perspective. Front. Psychiatry, 2021


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Franke, F., Natora, M., Boucsein, C., Munk, M. and Obermayer, K. (2010). An Online Spike Detection and Spike Classification Algorithm Capable of Instantaneous Resolution of Overlapping Spikes. Journal of Computional Neuroscience, 127 – 148.


Franke, F., Natora, M., Meier, P., Hagen, E., Pettersen, K., Linden, H., Einevoll, G. and Obermayer, K. (2010). An Automated Online Positioning System and Simulation Environment for Multi-Electrodes in Extracellular Recordings. Proceedings of 32nd Annual International Conference of the IEEE EMBS, 593 – 597.,10.1109/IEMBS.2010.5626631


Franke, F., Natora, M., Munk, M. and Obermayer, K. (2009). Blind Source Separation of Sparse Overcomplete Mixtures and Application to Neural Recordings. Independent Component Analysis and Signal Separation. Springer Berlin Heidelberg, 459 – 466.,10.1007/978-3-642-00599-2_58


Franke, F., Pröpper, R., Alle, H., Meier, P., Geiger, J. R. P., Obermayer, K. and Munk, M. H. J. (2015). Spike sorting of synchronous spikes from local neuron ensembles. Journal of Neurophysiology, 114, 2535–2549.


Franke, F., Quiroga, R. Q., Hierlemann, A. and Obermayer, K. (2015). Bayes optimal template matching for spike sorting – combining fisher discriminant analysis with optimal filtering. Journal of Computational Neuroscience, 38, 439-459.


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Gaudnek, M., Hess, A., Obermayer, K., Budinsky, L., Brune, K. and Sibila, M. (2005). Geometric Reconstruction of the Rat Vascular System Imaged by MRA. IEEE International Conference on Image Processing 2005. IEEE, 1278-1281.,10.1109/ICIP.2005.1530296


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Hiesinger, P., Scholz, M., Meinertzhagen, I., Fischbach, K.-F. and Obermayer, K. (2001). Visualization of Synaptic Markers in the Optic Neuropils of Drosophila Using a New Constrained Deconvolution Method. Journal of Comparative Neurology, 429, 277 – 288.


Huys, Q., Deserno, L., Obermayer, K., Schlagenhauf, F. and Heinz, A. (2016). Model-free temporal-difference learning and dopamine in alcohol dependence: examining concepts from theory and animals in human imaging. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 1, 401 - 410.


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Kanev, J., Koutsou, A., Christodoulou, C. and Obermayer, K. (2016). Integrator or Coincidence Detector - a Novel Measure Based on the Discrete Reverse Correlation to Determine a Neuron's Operational Mode. Neural Computation, 28, 1-38.


Koren, V., Andrei, A., Hu, M., Dragoi, V. and Obermayer, K. (2019). Reading-out task variables as a low-dimensional reconstruction of parallel spike trains in single trials. PLoS ONE, 14(10), 24.


Koren, V., Andrei, A., Hu, M., Dragol, V. and Obermayer, K. (2020). Pair-wise Synchrony and Correlations Depend on the Structure of the Population Code in Visual Cortex. Cell Reports, 2020


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Meyer, R. and Obermayer, K. (2016). pypet: A Python Toolkit for Data Management of Parameter Explorations. Frontiers Neuroinformatics, 10


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