Publications of Helmut Schmidt

Sánchez, S. M., Schmidt, H., Gallardo, G., Anwander, A., Brauer, J., Friederici, A. D., & Knösche, T. R. (2023). White matter brain structure predicts language performance and learning success. Human Brain Mapping, 44, 1445–1455.

Hahn, G., Kumar, A., Schmidt, H., Knösche, T. R., & Deco, G. (2022). Rate and oscillatory switching dynamics of a multilayer visual microcircuit model. ELife, 11. doi:10.7554/eLife.77594

Schmidt, H., & Knösche, T. R. (2022). Modelling the effect of ephaptic coupling on spike propagation in peripheral nerve fibres. Biological Cybernetics, 116, 461–473.

Gast, R., Knösche, T. R., & Schmidt, H. (2021). Mean-field approximations of networks of spiking neurons with short-term synaptic plasticity. Physical Review E, 104. doi:10.1103/PhysRevE.104.044310

Gast, R., Gong, R., Schmidt, H., Meijer, H. G. E., & Knösche, T. R. (2021). On the role of arkypallidal and prototypical neurons for phase transitions in the external pallidum. The Journal of Neuroscience, 41, 6673–6683.

Schmidt, H., Hahn, G., Deco, G., & Knösche, T. R. (2021). Ephaptic coupling in white matter fibre bundles modulates axonal transmission delays. PLoS Computational Biology, 17. doi:10.1371/journal.pcbi.1007858

Gast, R., Schmidt, H., & Knösche, T. R. (2020). A mean-field description of bursting dynamics in spiking neural networks with short-term adaptation. Neural Computation, 32, 1615–1634.

Woldman, W., Schmidt, H., Abela, E., Chowdhury, F. A., Pawley, A. D., Jewell, S., … Terry, J. R. (2020). Dynamic network properties of the interictal brain determine whether seizures appear focal or generalised. Scientific Reports, 10. doi:10.1038/s41598-020-63430-9

Schmidt, H., & Avitabile, D. (2020). Bumps and oscillons in networks of spiking neurons. Chaos, 30. doi:10.1063/1.5135579

Schmidt, H., & Knösche, T. R. (2019). Action potential propagation and synchronisation in myelinated axons. PLoS Computational Biology, 15. doi:10.1371/journal.pcbi.1007004

Schmidt, H., Avitabile, D., Montbrió, E., & Roxin, A. (2018). Network mechanisms underlying the role of oscillations in cognitive tasks. PLoS Computational Biology, 14. doi:10.1371/journal.pcbi.1006430

Schmidt, H., Woldman, W., Goodfellow, M., Chowdhury, F., Koutroumanidis, M., Jewell, S., … Terry, J. (2016). A computational biomarker of idiopathic generalized epilepsy from resting state EEG. Epilepsia, 57, e200–e204.

Avitabile, D., & Schmidt, H. (2015). Snakes and ladders in an inhomogeneous neural field model. Physica D: Nonlinear Phenomena, 294, 24–36.

Schmidt, H., Petkov, G., Richardson, M., & Terry, J. (2014). Dynamics on networks: The role of local dynamics and global networks on the emergence of hypersynchronous neural activity. PLoS Computational Biology, 10. doi:10.1371/journal.pcbi.1003947

Coombes, S., Schmidt, H., & Bojak, I. (2012). Interface dynamics in planar neural field models. Journal Mathematical Neuroscience, 2. doi:10.1186/2190-8567-2-9

Coombes, S., Laing, C., Schmidt, H., Svanstedt, N., & Wyller, J. (2012). Waves in random neural media. Discrete and Continuous Dynamical Systems, 32, 2951–2970.

Coombes, S., & Schmidt, H. (2010). Neural fields with sigmoidal firing rates: Approximate solutions. Discrete and Continuous Dynamical Systems. Series S, 28, 1369–1379.

Schmidt, H., Hutt, A., & Schimansky-Geier, L. (2009). Wave fronts in inhomogeneous neural field models. Physica D: Nonlinear Phenomena, 238, 1101–1112.

Coombes, S., Schmidt, H., & Avitabile, D. (2014). Spots: Breathing, drifting and scattering in a neural field model. In S. Coombes (Ed.), P. Beim Graben & R. Potthast, Neural Fields (pp. 187–211). Heidelberg: Springer.

Chien, V. S. C., Röse, C., Wang, P., Schmidt, H., Knösche, T. R., & Weise, K. (2024). A biological model of spinal and peripheral motor pathways for TMS-induced MEPs. In Journal of Computational Neuroscience (Vol. 52, pp. S135–S136). Boston: Kluwer Academic Publishers.