Guzmán J, Schlögl A, Espinoza Martinez C, Zhang X, Suter B, Jonas PM. How connectivity rules and synaptic properties shape the efficacy of pattern separation in the entorhinal cortex–dentate gyrus–C network. 2021. doi:10.15479/AT:ISTA:10110
LibreCat: https://research-explorer.ista.ac.at/record/10110
DOI: 10.15479/AT:ISTA:10110

Schlögl A, Kiss J, Elefante S, eds. Austrian High-Performance-Computing Meeting (AH). Klosterneuburg, Austria: IST Austria; 2020. doi:10.15479/AT:ISTA:7474
LibreCat: https://research-explorer.ista.ac.at/record/7474
DOI: 10.15479/AT:ISTA:7474

Zhang X, Schlögl A, Jonas PM. Selective routing of spatial information flow from input to output in hippocampal granule cells. Neuron. 2020;107(6):1212-1225. doi:10.1016/j.neuron.2020.07.006
LibreCat: https://research-explorer.ista.ac.at/record/8261
DOI: 10.1016/j.neuron.2020.07.006
WoS: 000579698700009
PMID: 32763145

Schlögl A, Kiss J, Elefante S. Is Debian suitable for running an HPC Cluster? In: AHP - Austrian HPC Meeting 2019 . Institut für Mathematik und wissenschaftliches Rechnen der Universität Graz; 2019:25.
LibreCat: https://research-explorer.ista.ac.at/record/12901

Sauermann S, David V, Schlögl A, et al. Biosignals standards and FHIR: The way to go. In: Vol 236. IOS Press; 2017:356-362. doi:10.3233/978-1-61499-759-7-356
LibreCat: https://research-explorer.ista.ac.at/record/630
DOI: 10.3233/978-1-61499-759-7-356

Schlögl A, Kiss J. Scientific Computing at IST Austria. In: AHP – Austrian HPC Meeting 2017. FSP Scientific Computing; 2017:28.
LibreCat: https://research-explorer.ista.ac.at/record/12905

Guzmán J, Schlögl A, Frotscher M, Jonas PM. Synaptic mechanisms of pattern completion in the hippocampal C network. Science. 2016;353(6304):1117-1123. doi:10.1126/science.aaf1836
LibreCat: https://research-explorer.ista.ac.at/record/1350
DOI: 10.1126/science.aaf1836

Schlögl A, Stadlbauer S. High performance computing at IST Austria: Modelling the human hippocampus. In: AHP - Austrian HPC Meeting 2016. VSC - Vienna Scientific Cluster; 2016:37.
LibreCat: https://research-explorer.ista.ac.at/record/12903

Körner C, Braunstein V, Stangl M, Schlögl A, Neuper C, Ischebeck A. Sequential effects in continued visual search: Using fixation-related potentials to compare distractor processing before and after target detection. Psychophysiology. 2014;51(4):385-395. doi:10.1111/psyp.12062
LibreCat: https://research-explorer.ista.ac.at/record/1890
DOI: 10.1111/psyp.12062

Guzmán J, Schlögl A, Schmidt Hieber C. Stimfit: Quantifying electrophysiological data with Python. Frontiers in Neuroinformatics. 2014;8(FEB). doi:10.3389/fninf.2014.00016
LibreCat: https://research-explorer.ista.ac.at/record/2230
DOI: 10.3389/fninf.2014.00016

Pernia-Andrade A, Goswami S, Stickler Y, Fröbe U, Schlögl A, Jonas PM. A deconvolution based method with high sensitivity and temporal resolution for detection of spontaneous synaptic currents in vitro and in vivo. Biophysical Journal. 2012;103(7):1429-1439. doi:10.1016/j.bpj.2012.08.039
LibreCat: https://research-explorer.ista.ac.at/record/2954
DOI: 10.1016/j.bpj.2012.08.039
PMID: 23062335

Tangermann M, Müller K, Aertsen A, et al. Review of the BCI competition IV. Frontiers in Neuroscience. 2012;6. doi:10.3389/fnins.2012.00055
LibreCat: https://research-explorer.ista.ac.at/record/493
DOI: 10.3389/fnins.2012.00055

Schlögl A, Vidaurre C, Sander T. BioSig: The free and open source software library for biomedical signal processing. Computational Intelligence and Neuroscience. 2011;2011. doi:10.1155/2011/935364
LibreCat: https://research-explorer.ista.ac.at/record/490
DOI: 10.1155/2011/935364

Schlögl A, Vidaurre C, Müller K-R. Adaptive Methods in BCI Research - An Introductory Tutorial. In: Graimann B, Pfurtscheller G, Allison B, eds. Brain-Computer Interfaces. 1st ed. FRONTCOLL. Berlin, Heidelberg: Springer; 2010:331-355. doi:10.1007/978-3-642-02091-9_18
LibreCat: https://research-explorer.ista.ac.at/record/14983
DOI: 10.1007/978-3-642-02091-9_18