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TU Berlin

Inhalt des Dokuments

Journal Publications

2017

Oschmann, F., Berry, H., Obermayer, K. and Lenk, K. (2017). From in Silico Astrocyte Cell Models to Neuron-astrocyte Network Models: A Review. Brain Research Bulletin


Donner, C., Obermayer, K. and Shimazaki, H. (2017). Approximate Inference for Time-varying Interactions and Macroscopic Dynamics of Neural Populations. PLoS Computational Biology, 13


Meyer, R., Ladenbauer, J. and Obermayer, K. (2017). Influence of Mexican Hat Recurrent Connectivity on Noise Correlations and Stimulus Encoding. Frontiers in Computational Neuroscience


Trowitzsch, I., Mohr, J., Kashef, Y. and Obermayer, K. (2017). Robust Detection of Environmental Sounds in Binaural Auditory Scenes. IEEE Transactions on Audio Speech and Language Processing, 25, 1344-1356.


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.


Oschmann, F., Mergenthaler, K., Jungnickel, E. and Obermayer, K. (2017). Spatial Separation of Two Different Pathways Accounting for the Generation of Calcium Signals in Astrocytes. PLoS Computational Biology, 13


Augustin, M., Ladenbauer, J., Baumann, F. and Obermayer, K. (2017). Low-dimensional spike rate models derived from networks of adaptive integrate-and-fire neurons: Comparison and implementation. PLoS Computational Biology, 13


2016

Guo, R., Böhmer, W., Hebart, M., Chien, S., Sommer, T., Obermayer, K. and Gläscher, J. (2016). Interaction of Instrumental and Goal-directed Learning Modulates Prediction Error Representations in the Ventral Striatum. Journal of Neuroscience, 36, 12650-12660.


Mohr, J., Seyfarth, J., Lueschow, A., Weber, J. E., Wichman, F. A. and Obermayer, K. (2016). BOiS - Berlin Object in Scene Database: Controlled Photographic Images for Visual Search Experiments with Quantified Contextual Priors. Frontiers in Psychology, 7


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


Aspart, F., Ladenbauer, J. and Obermayer, K. (2016). Extending Integrate-and-fire Model Neurons to Account for the Effects of Weak Electric Fields and Input Filtering Mediated by the Dendrite. PLOS Computional Biology, 12, e1005206.


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.


Tobia, M. J., Guo, R., Gläscher, J., Schwarze, U., Brassen, S., Büchel, C., Obermayer, K. and Sommer, T. (2016). Altered behavioral and neural responsiveness to counterfactual gains in the elderly. Cognitive, Affective, & Behavioral Neuroscience, 457-472.


Donner, C., Obermayer, K. and Shimazaki, H. (2016). Approximate Inference for Time-varying Interactions and Macroscopic Dynamics of Neural Populations. PLoS Computional Biology, 13, 1 -27.


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.


Bielivtsov, D., Ladenbauer, J. and Obermayer, K. (2016). Controlling Statistical Moments of Stochastic Dynamical Networks. Physical Review E, 94, 012306.


2015

Seo, S., Mohr, J., Beck, A., Wüstenberg, T., Heinz, A. and Obermayer, K. (2015). Predicting the future relapse of alcohol-dependent patients from structural and functional brain images. Addiction Biology, 20, 1042-1055.


Shelton, J. A., Sheikh, A.-S., Bornschein, J., Sterne, P. and Lücke, J. (2015). Nonlinear Spike-And-Slab Sparse Coding for Interpretable Image Encoding. PLoS ONE, 10, e0124088.


Guggenmos, M., Rothkirch, M., Obermayer, K., Haynes, J. D. and Sterzer, P. (2015). A Hippocampal Signature of Perceptual Learning in Object Recognition. Journal of Cognitive Neuroscience, 27, 787–797.


Hutter, F., Lücke, J. and Schmidt-Thieme, L. (2015). Beyond Manual Tuning of Hyperparameters. KI - Künstliche Intelligenz, 29, 329-337.


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