J. Guzmán, A. Schlögl, C. Espinoza Martinez, X. Zhang, B. Suter, and P. M. Jonas, “How connectivity rules and synaptic properties shape the efficacy of pattern separation in the entorhinal cortex–dentate gyrus–C network.” IST Austria, 2021.

A. Schlögl, J. Kiss, and S. Elefante, Eds., Austrian High-Performance-Computing meeting (AH). Klosterneuburg, Austria: IST Austria, 2020.

X. Zhang, A. Schlögl, and P. M. Jonas, “Selective routing of spatial information flow from input to output in hippocampal granule cells,” Neuron, vol. 107, no. 6. Elsevier, pp. 1212–1225, 2020.

A. Schlögl, J. Kiss, and S. Elefante, “Is Debian suitable for running an HPC Cluster?,” in AHP - Austrian HPC Meeting 2019 , Grundlsee, Austria, 2019, p. 25.

S. Sauermann et al., “Biosignals standards and FHIR: The way to go,” presented at the eHealth: Health Informatics Meets eHealth, Vienna, Austria, 2017, vol. 236, pp. 356–362.

A. Schlögl and J. Kiss, “Scientific Computing at IST Austria,” in AHP – Austrian HPC Meeting 2017, Grundlsee, Austria, 2017, p. 28.

J. Guzmán, A. Schlögl, M. Frotscher, and P. M. Jonas, “Synaptic mechanisms of pattern completion in the hippocampal C network,” Science, vol. 353, no. 6304. American Association for the Advancement of Science, pp. 1117–1123, 2016.

A. Schlögl and S. Stadlbauer, “High performance computing at IST Austria: Modelling the human hippocampus,” in AHP - Austrian HPC Meeting 2016, Grundlsee, Austria, 2016, p. 37.

C. Körner, V. Braunstein, M. Stangl, A. Schlögl, C. Neuper, and A. Ischebeck, “Sequential effects in continued visual search: Using fixation-related potentials to compare distractor processing before and after target detection,” Psychophysiology, vol. 51, no. 4. Wiley-Blackwell, pp. 385–395, 2014.

J. Guzmán, A. Schlögl, and C. Schmidt Hieber, “Stimfit: Quantifying electrophysiological data with Python,” Frontiers in Neuroinformatics, vol. 8, no. FEB. Frontiers Research Foundation, 2014.

A. Pernia-Andrade, S. Goswami, Y. Stickler, U. Fröbe, A. Schlögl, and P. M. Jonas, “A deconvolution based method with high sensitivity and temporal resolution for detection of spontaneous synaptic currents in vitro and in vivo,” Biophysical Journal, vol. 103, no. 7. Biophysical, pp. 1429–1439, 2012.

M. Tangermann et al., “Review of the BCI competition IV,” Frontiers in Neuroscience, vol. 6. Frontiers Research Foundation, 2012.

A. Schlögl, C. Vidaurre, and T. Sander, “BioSig: The free and open source software library for biomedical signal processing,” Computational Intelligence and Neuroscience, vol. 2011. Hindawi Publishing Corporation, 2011.

A. Schlögl, C. Vidaurre, and K.-R. Müller, “Adaptive Methods in BCI Research - An Introductory Tutorial,” in Brain-Computer Interfaces, 1st ed., B. Graimann, G. Pfurtscheller, and B. Allison, Eds. Berlin, Heidelberg: Springer, 2010, pp. 331–355.