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Inhalt des Dokuments

Modelle neuronaler Systeme



Cakan, C., Dimulescu, C., Khakimova, L., Obst, D., Flöel, A. and Obermayer, K. (2022). Spatiotemporal patterns of adaptation-induced slow oscillations in a whole-brain model of slow-wave sleep. Frontiers in Computational Neuroscience, 15, 800101.

Cakan, C. and Obermayer, K. (2020). Biophysically grounded mean-field models of neural populations under electrical stimulation. PLOS Computational Biology, 2020

Cakan, C., Jajcay, N. and Obermayer, K. (2021). neurolib: A Simulation Framework for Wholebrain Neural Mass Modeling. Cognit. Comput., 2021

Chouzouris, T., Roth, N., Cakan, C. and K., O. (2021). Applications of Optimal Nonlinear Control to a Whole-brain Network of FitzHugh-Nagumo Oscillators. Phys. Rev. E, 2021


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

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.


Erwin, E., Obermayer, K. and Schulten, K. (1995). Models of Orientation and Ocular Dominance Columns in the Visual Cortex: A Critical Comparison. Neural Computation, 7, 425 – 468.


Gallinat, J., Obermayer, K. and Heinz, A. (2007). Systems Biology of the Dysfunctional Brain: Schizophrenia. Pharmacopsychiatry, 40, 40 – 44.

Garg, A., Bhaumik, B. and Obermayer, K. (2005). Variable Discharge Pattern and Contrast Invariant Orientation Tuning of a Simple Cell: A Modeling Study. Neural Information Processing - Letters and Reviews, 6, 59 – 68.

Garg, A., Obermayer, K. and Bhaumik, B. (2005). Development of Feedforward Receptive Field Structure of a Simple Cell and its Contribution to the Orientation Selectivity: A Modeling Study. International Journal of Neural Systems, 15, 55 – 70.

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.

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.


Heinz, A., Beck, A., Wrase, J., Mohr, J., Obermayer, K., Gallinat, J. and Puls, I. (2009). Neurotransmitter Systems in Alcohol Dependence. Pharmacopsychiatry, 42, 95 – 101.

Hoch, T., Volgushev, S., Malyshev, A., Obermayer, K. and Volgushev, M. (2011). Modulation of the Amplitude of γ-Band Activity by Stimulus Phase Enhances Signal Encoding. European Journal of Neuroscience, 33, 1223-1239.

Hoch, T., Wenning, G. and Obermayer, K. (2005). The Effect of Correlations in the Background Activity on the Information Transmission Properties of Neural Populations. Journal of Neurocomputing, 65-66, 365 – 370.

Hoch, T., Wenning, G. and Obermayer, K. (2003). Adaptation using Local Information for Maximizing the Global Cost. Neurocomputing, 52 – 54, 467-472.

Hoch, T., Wenning, G. and Obermayer, K. (2003). Optimal Noise-Aided Signal Transmission through Populations of Neurons. Physical Review E, 68, 11911.

Holca-Lamarre, R., Luecke, J. and Obermayer, K. (2017). Acetylcholine and Dopamine Signals Differentially Improve Sensory Representations in a Neural Network Model. Front. Comput. Neurosci., 11

Houillon, A., Lorenz, R. C., Boehmer, W., Rapp, M. A., Heinz, A., Gallinat, J. and Obermayer, K. (2013). The effect of novelty on reinforcement learning. Progress in brain research, 202, 415–439.


Jajcay, N., Cakan, C. and Obermayer, K. (2022). Cross-frequency slow oscillation-spindle coupling in a biophysically realistic thalamocortical neural mass model. Frontiers in Computational Neuroscience, 16, 769860.

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