Publications of Stefan J. Kiebel

Rahmati, V., Kirmse, K., Markovic, D., Holthoff, K., & Kiebel, S. J. (2016). Inferring neuronal dynamics from calcium imaging data using biophysical models and bayesian inference. PLoS Computational Biology, 12. doi:10.1371/journal.pcbi.1004736

Park, H., Lueckmann, J.-M., von Kriegstein, K., Bitzer, S., & Kiebel, S. J. (2016). Spatiotemporal dynamics of random stimuli account for trial-to-trial variability in perceptual decision making. Scientific Reports, 6. doi:10.1038/srep18832

Markovic, D., Gläscher, J., Bossaerts, P., O'Doherty, J., & Kiebel, S. J. (2015). Modeling the evolution of beliefs using an attentional focus mechanism. PLoS Computational Biology, 11. doi:10.1371/journal.pcbi.1004558

Cuevas Rivera, D., Bitzer, S., & Kiebel, S. J. (2015). Modelling odor decoding in the antennal lobe by combining sequential firing rate models with bayesian inference. PLoS Computational Biology, 11. doi:10.1371/journal.pcbi.1004528

Bitzer, S., Bruineberg, J., & Kiebel, S. J. (2015). A bayesian attractor model for perceptual decision making. PLoS Computational Biology, 11. doi:10.1371/journal.pcbi.1004442

Riedel, P., Ragert, P., Schelinski, S., Kiebel, S. J., & von Kriegstein, K. (2015). Visual face-movement sensitive cortex is relevant for auditory-only speech recognition. Cortex, 68, 86–99.

Taubert, M., Wenzel, U., Draganski, B., Kiebel, S. J., Ragert, P., Krug, J., & Villringer, A. (2015). Investigating neuroanatomical features in top athletes at the single subject level. PLoS One, 10. doi:10.1371/journal.pone.0129508

Schall, S., Kiebel, S. J., Maess, B., & von Kriegstein, K. (2015). Voice identity recognition: Functional division of the right STS and its behavioral relevance. Journal of Cognitive Neuroscience, 27, 280–291.

Blank, H., Kiebel, S. J., & von Kriegstein, K. (2015). How the human brain exchanges information across sensory modalities to recognize other people. Human Brain Mapping, 36, 324–339.

Schäfer, A., Margulies, D. S., Lohmann, G., Gorgolewski, K. J., Smallwood, J., Kiebel, S. J., & Villringer, A. (2014). Dynamic network participation of functional connectivity hubs assessed by resting-state fMRI. Frontiers in Human Neuroscience, 8. doi:10.3389/fnhum.2014.00195

Bitzer, S., Park, H., Blankenburg, F., & Kiebel, S. J. (2014). Perceptual decision making: Drift-diffusion model is equivalent to a Bayesian model. Frontiers in Human Neuroscience, 8. doi:10.3389/fnhum.2014.00102

Yildiz, B., von Kriegstein, K., & Kiebel, S. J. (2013). From birdsong to human speech recognition: Bayesian inference on a hierarchy of nonlinear dynamical systems. PLoS Computational Biology, 9. doi:10.1371/journal.pcbi.1003219

Schall, S., Kiebel, S., Maess, B., & von Kriegstein, K. (2013). Early auditory sensory processing of voices is facilitated by visual mechanisms. NeuroImage, 77, 237–245.

Meyer, L., Obleser, J., Kiebel, S. J., & Friederici, A. D. (2012). Spatiotemporal dynamics of argument retrieval and reordering: An fMRI and EEG study on sentence processing. Frontiers in Psychology, 3. doi:10.3389/fpsyg.2012.00523

Yildiz, I. B., Jaeger, H., & Kiebel, S. J. (2012). Re-visiting the echo state property. Neural Networks, 35, 1–9.

Díaz, B., Hintz, F., Kiebel, S. J., & von Kriegstein, K. (2012). Dysfunction of the auditory thalamus in developmental dyslexia. Proceedings of the National Academy of Sciences of the United States of America, 109, 13841–13846.

Ostwald, D., Spitzer, B., Guggenmos, M., Schmidt, T. T., Kiebel, S. J., & Blankenburg, F. (2012). Evidence for neural encoding of Bayesian surprise in human somatosensation. NeuroImage, 62, 177–188.

Bitzer, S., & Kiebel, S. (2012). Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks. Biological Cybernetics, 106, 201–217.

Chen, C.-C., Kiebel, S. J., Kilner, J. M., Ward, N. S., Stephan, K. E., Wang, W.-J., & Friston, K. J. (2012). A dynamic causal model for evoked and induced responses. NeuroImage, 59, 340–348.

Yildiz, I. B., & Kiebel, S. J. (2011). A hierarchical neuronal model for generation and online recognition of birdsongs. PLoS Computational Biology, 7. doi:10.1371/journal.pcbi.1002303