Göttingen Campus Institut für
Dynamik biologischer Netzwerke (CIDBN)

Wibral, Michael, Prof. Dr.

Professor for Data-Driven Analysis of Biological Networks


  • since 8/2018 Professor for Data-driven Analysis of Biological Networks, Campus Institute for Dynamics of Biological Networks, Georg-August-University.
  • 2012–2014 Speaker, Research Consortium LOEWE NeFF
  • 2012–2018 Professor for Magnetoencephalography, MEG Unit, Brain Imaging Center, Johann Wolfgang Goethe-Universität Frankfurt, Germany
  • since 2010 Project leader of the open source software projects TRENTOOL and IDT
  • 2006–2012 Laboratory Head, Johann Wolfgang Goethe-Universität Frankfurt, Germany
  • 2002–2007 Dr. rer. nat. in Neurobiology, Technische Universität Darmstadt, Germany



Major Research Interests

I am interested in the information-theoretic analysis of neural data, both in the development of novel methods for specific neuroscience problems (like testing predictive coding theories), and in the application of information theoretical methods to empirical data in non-human, humans and in patients with Autism Spectrum Disorder.


Homepage


Selected Recent Publications

  • Nascimento Costa, G., Schaum, M., Duarte, J. V., Martins R., Duarte I. C., Castelhano J., Wibral, M., Castelo-Branco M. (2024) Distinct oscillatory patterns differentiate between segregation and integration processes in perceptual grouping. Human Brain Mapping. https://doi.org/10.1002/hbm.26779

    • Barnes-Scheufler, C.V., Rösler, L., Schaum, M., Schiweck, C., Peters, B., Mayer, J.S., Reif, A., Wibral, M., Bittner, R.A. (2024) External cues improve visual working memory encoding in the presence of salient distractors in schizophrenia. Psychological Medicine. Vol. 54, Issue 9, pp. 1965 - 1974. https://doi.org/10.1017/S0033291724000059

      • Ehrlich, D., Schneider, A.C., Priesemann, V., Wibral, M., Makkeh, A. (2023) A Measure of the Complexity of Neural Representations based on Partial Information Decomposition. Transaction on Machine Learning Research

        • Hagemann, A., Kehl, M. S., Dehning, J., Spitzner, F. P., Niediek, J., Wibral, M., Mormann, F. & Priesemann, V. (2022) Intrinsic timescales of spiking activity in humans during wakefulness and sleep. arXiv preprint arXiv:2205.10308.

        • Mikulasch, F. A., Rudelt, L., Wibral, M., & Priesemann, V. (2022) Dendritic predictive coding: A theory of cortical computation with spiking neurons. arXiv preprint arXiv:2205.05303.

        • Gutknecht A. J., Wibral M. & Makkeh A. (2021) Bits and pieces: understanding information decomposition from part-whole relationships and formal logic. Proc. R. Soc. A.4772021011020210110. http://doi.org/10.1098/rspa.2021.0110.

        • Brodski-Guerniero, A., Naumer, M. J., Moliadze, V., Chan, J., Althen, H., Ferreira-Santos, F., Lizier, J. T., Schlitt, S., Kitzerow, J., Schütz, M., Langer, A., Kaiser, J., Freitag, C. M., Wibral M. (2018) Predictable information in neural signals during resting state is reduced in autism spectrum disorder. Hum Brain Mapp 39(8), 3227-3240. doi: 10.1002/hbm.24072.

        • Brodski-Guerniero, A., Paasch, G. F., Wollstadt, P., Özdemir, I., Lizier, J. T. and Wibral, M. (2017) Information-Theoretic Evidence for Predictive Coding in the Face-Processing System. J Neurosci 37(34), 8273-8283. doi: 10.1523/JNEUROSCI.0614-17.2017.

        • Wollstadt, P., Sellers, K. K., Rudelt, L., Priesemann, V., Hutt, A., Fröhlich, F. and Wibral, M. (2017) Breakdown of local information processing may underlie isoflurane anesthesia effects. PLoS Comput Biol. 13(6), e1005511. doi: 10.1371/journal.pcbi.1005511.

        • Brodski, A., Paasch, G. F., Helbling, S. and Wibral, M. (2015) The Faces of Predictive Coding. J Neurosci. 35(24), 8997-9006. doi: 10.1523/JNEUROSCI.1529-14.2015.

        • Priesemann, V., Wibral, M., Valderrama, M., Pröpper, R., Le Van Quyen, M., Geisel, T., Triesch, J., Nikolić, D. and Munk, M. H. (2014) Spike avalanches in vivo suggest a driven, slightly subcritical brain state. Front Syst Neurosci. 8, 108. doi: 10.3389/fnsys.2014.00108.

        • Gómez, C., Lizier, J. T., Schaum, M., Wollstadt, P., Grützner, C., Uhlhaas, P., Freitag, C. M., Schlitt, S., Bölte, S., Hornero, R. and Wibral, M. (2014) Reduced predictable information in brain signals in autism spectrum disorder. Front Neuroinform. 8, 9. doi: 10.3389/fninf.2014.00009.

        • Wibral, M., Lizier, J. T., Vögler, S., Priesemann, V. and Galuske, R. (2014) Local active information storage as a tool to understand distributed neural information processing. Front Neuroinform. 8, 1. doi: 10.3389/fninf.2014.00001.

        • Vicente, R.*, Wibral, M.*, Lindner, M. and Pipa, G. (*equal contrib.). (2011) Transfer entropy--a model-free measure of effective connectivity for the neurosciences. J Comput Neurosci. 30(1), 45-67. doi: 0.1007/s10827-010-0262-3.

        • Grützner, C., Uhlhaas, P. J., Genc, E., Kohler, A., Singer, W. and Wibral, M. (2010) Neuroelectromagnetic correlates of perceptual closure processes. J Neurosci. 30(24), 8342-52. doi: 10.1523/JNEUROSCI.5434-09.2010.

        • Wibral, M., Bledowski, C., Kohler, A., Singer, W. and Muckli, L. (2009) The timing of feedback to early visual cortex in the perception of long-range apparent motion. Cereb Cortex. 19(7), 1567-82. doi: 10.1093/cercor/bhn192.



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