@article{14979, abstract = {Poxviruses are among the largest double-stranded DNA viruses, with members such as variola virus, monkeypox virus and the vaccination strain vaccinia virus (VACV). Knowledge about the structural proteins that form the viral core has remained sparse. While major core proteins have been annotated via indirect experimental evidence, their structures have remained elusive and they could not be assigned to individual core features. Hence, which proteins constitute which layers of the core, such as the palisade layer and the inner core wall, has remained enigmatic. Here we show, using a multi-modal cryo-electron microscopy (cryo-EM) approach in combination with AlphaFold molecular modeling, that trimers formed by the cleavage product of VACV protein A10 are the key component of the palisade layer. This allows us to place previously obtained descriptions of protein interactions within the core wall into perspective and to provide a detailed model of poxvirus core architecture. Importantly, we show that interactions within A10 trimers are likely generalizable over members of orthopox- and parapoxviruses.}, author = {Datler, Julia and Hansen, Jesse and Thader, Andreas and Schlögl, Alois and Bauer, Lukas W and Hodirnau, Victor-Valentin and Schur, Florian KM}, issn = {1545-9985}, journal = {Nature Structural & Molecular Biology}, keywords = {Molecular Biology, Structural Biology}, publisher = {Springer Nature}, title = {{Multi-modal cryo-EM reveals trimers of protein A10 to form the palisade layer in poxvirus cores}}, doi = {10.1038/s41594-023-01201-6}, year = {2024}, } @inproceedings{13161, author = {Schlögl, Alois and Elefante, Stefano and Hodirnau, Victor-Valentin}, booktitle = {ASHPC23 - Austrian-Slovenian HPC Meeting 2023}, location = {Maribor, Slovenia}, pages = {59--59}, publisher = {EuroCC}, title = {{Running Windows-applications on a Linux HPC cluster using WINE}}, year = {2023}, } @inproceedings{13162, author = {Elefante, Stefano and Stadlbauer, Stephan and Alexander, Michael F and Schlögl, Alois}, booktitle = {ASHPC23 - Austrian-Slovenian HPC Meeting 2023}, location = {Maribor, Slovenia}, pages = {42--42}, publisher = {EuroCC}, title = {{Cryo-EM software packages: A sys-admins point of view}}, year = {2023}, } @inproceedings{12894, author = {Schlögl, Alois and Hornoiu, Andrei and Elefante, Stefano and Stadlbauer, Stephan}, booktitle = {ASHPC22 - Austrian-Slovenian HPC Meeting 2022}, isbn = {978-3-200-08499-5}, location = {Grundlsee, Austria}, pages = {7}, publisher = {EuroCC Austria c/o Universität Wien}, title = {{Where is the sweet spot? A procurement story of general purpose compute nodes}}, doi = {10.25365/phaidra.337}, year = {2022}, } @article{10816, abstract = {Pattern separation is a fundamental brain computation that converts small differences in input patterns into large differences in output patterns. Several synaptic mechanisms of pattern separation have been proposed, including code expansion, inhibition and plasticity; however, which of these mechanisms play a role in the entorhinal cortex (EC)–dentate gyrus (DG)–CA3 circuit, a classical pattern separation circuit, remains unclear. Here we show that a biologically realistic, full-scale EC–DG–CA3 circuit model, including granule cells (GCs) and parvalbumin-positive inhibitory interneurons (PV+-INs) in the DG, is an efficient pattern separator. Both external gamma-modulated inhibition and internal lateral inhibition mediated by PV+-INs substantially contributed to pattern separation. Both local connectivity and fast signaling at GC–PV+-IN synapses were important for maximum effectiveness. Similarly, mossy fiber synapses with conditional detonator properties contributed to pattern separation. By contrast, perforant path synapses with Hebbian synaptic plasticity and direct EC–CA3 connection shifted the network towards pattern completion. Our results demonstrate that the specific properties of cells and synapses optimize higher-order computations in biological networks and might be useful to improve the deep learning capabilities of technical networks.}, author = {Guzmán, José and Schlögl, Alois and Espinoza Martinez, Claudia and Zhang, Xiaomin and Suter, Benjamin and Jonas, Peter M}, issn = {2662-8457}, journal = {Nature Computational Science}, keywords = {general medicine}, number = {12}, pages = {830--842}, publisher = {Springer Nature}, title = {{How connectivity rules and synaptic properties shape the efficacy of pattern separation in the entorhinal cortex–dentate gyrus–CA3 network}}, doi = {10.1038/s43588-021-00157-1}, volume = {1}, year = {2021}, } @article{9329, abstract = {Background: To understand information coding in single neurons, it is necessary to analyze subthreshold synaptic events, action potentials (APs), and their interrelation in different behavioral states. However, detecting excitatory postsynaptic potentials (EPSPs) or currents (EPSCs) in behaving animals remains challenging, because of unfavorable signal-to-noise ratio, high frequency, fluctuating amplitude, and variable time course of synaptic events. New method: We developed a method for synaptic event detection, termed MOD (Machine-learning Optimal-filtering Detection-procedure), which combines concepts of supervised machine learning and optimal Wiener filtering. Experts were asked to manually score short epochs of data. The algorithm was trained to obtain the optimal filter coefficients of a Wiener filter and the optimal detection threshold. Scored and unscored data were then processed with the optimal filter, and events were detected as peaks above threshold. Results: We challenged MOD with EPSP traces in vivo in mice during spatial navigation and EPSC traces in vitro in slices under conditions of enhanced transmitter release. The area under the curve (AUC) of the receiver operating characteristics (ROC) curve was, on average, 0.894 for in vivo and 0.969 for in vitro data sets, indicating high detection accuracy and efficiency. Comparison with existing methods: When benchmarked using a (1 − AUC)−1 metric, MOD outperformed previous methods (template-fit, deconvolution, and Bayesian methods) by an average factor of 3.13 for in vivo data sets, but showed comparable (template-fit, deconvolution) or higher (Bayesian) computational efficacy. Conclusions: MOD may become an important new tool for large-scale, real-time analysis of synaptic activity.}, author = {Zhang, Xiaomin and Schlögl, Alois and Vandael, David H and Jonas, Peter M}, issn = {1872-678X}, journal = {Journal of Neuroscience Methods}, number = {6}, publisher = {Elsevier}, title = {{MOD: A novel machine-learning optimal-filtering method for accurate and efficient detection of subthreshold synaptic events in vivo}}, doi = {10.1016/j.jneumeth.2021.109125}, volume = {357}, year = {2021}, } @misc{10110, abstract = {Pattern separation is a fundamental brain computation that converts small differences in input patterns into large differences in output patterns. Several synaptic mechanisms of pattern separation have been proposed, including code expansion, inhibition and plasticity; however, which of these mechanisms play a role in the entorhinal cortex (EC)–dentate gyrus (DG)–CA3 circuit, a classical pattern separation circuit, remains unclear. Here we show that a biologically realistic, full-scale EC–DG–CA3 circuit model, including granule cells (GCs) and parvalbumin-positive inhibitory interneurons (PV+-INs) in the DG, is an efficient pattern separator. Both external gamma-modulated inhibition and internal lateral inhibition mediated by PV+-INs substantially contributed to pattern separation. Both local connectivity and fast signaling at GC–PV+-IN synapses were important for maximum effectiveness. Similarly, mossy fiber synapses with conditional detonator properties contributed to pattern separation. By contrast, perforant path synapses with Hebbian synaptic plasticity and direct EC–CA3 connection shifted the network towards pattern completion. Our results demonstrate that the specific properties of cells and synapses optimize higher-order computations in biological networks and might be useful to improve the deep learning capabilities of technical networks.}, author = {Guzmán, José and Schlögl, Alois and Espinoza Martinez, Claudia and Zhang, Xiaomin and Suter, Benjamin and Jonas, Peter M}, publisher = {IST Austria}, title = {{How connectivity rules and synaptic properties shape the efficacy of pattern separation in the entorhinal cortex–dentate gyrus–CA3 network}}, doi = {10.15479/AT:ISTA:10110}, year = {2021}, } @inproceedings{12909, author = {Schlögl, Alois and Elefante, Stefano and Hornoiu, Andrei and Stadlbauer, Stephan}, booktitle = {ASHPC21 – Austrian-Slovenian HPC Meeting 2021}, isbn = {978-961-6980-77-7}, location = {Virtual}, pages = {5}, publisher = {University of Ljubljana}, title = {{Managing software on a heterogenous HPC cluster}}, doi = {10.3359/2021hpc}, year = {2021}, } @article{8261, abstract = {Dentate gyrus granule cells (GCs) connect the entorhinal cortex to the hippocampal CA3 region, but how they process spatial information remains enigmatic. To examine the role of GCs in spatial coding, we measured excitatory postsynaptic potentials (EPSPs) and action potentials (APs) in head-fixed mice running on a linear belt. Intracellular recording from morphologically identified GCs revealed that most cells were active, but activity level varied over a wide range. Whereas only ∼5% of GCs showed spatially tuned spiking, ∼50% received spatially tuned input. Thus, the GC population broadly encodes spatial information, but only a subset relays this information to the CA3 network. Fourier analysis indicated that GCs received conjunctive place-grid-like synaptic input, suggesting code conversion in single neurons. GC firing was correlated with dendritic complexity and intrinsic excitability, but not extrinsic excitatory input or dendritic cable properties. Thus, functional maturation may control input-output transformation and spatial code conversion.}, author = {Zhang, Xiaomin and Schlögl, Alois and Jonas, Peter M}, issn = {0896-6273}, journal = {Neuron}, number = {6}, pages = {1212--1225}, publisher = {Elsevier}, title = {{Selective routing of spatial information flow from input to output in hippocampal granule cells}}, doi = {10.1016/j.neuron.2020.07.006}, volume = {107}, year = {2020}, } @book{7474, abstract = {This booklet is a collection of abstracts presented at the AHPC conference.}, editor = {Schlögl, Alois and Kiss, Janos and Elefante, Stefano}, isbn = {978-3-99078-004-6}, location = {Klosterneuburg, Austria}, pages = {72}, publisher = {IST Austria}, title = {{Austrian High-Performance-Computing meeting (AHPC2020)}}, doi = {10.15479/AT:ISTA:7474}, year = {2020}, } @inproceedings{12901, author = {Schlögl, Alois and Kiss, Janos and Elefante, Stefano}, booktitle = {AHPC19 - Austrian HPC Meeting 2019 }, location = {Grundlsee, Austria}, pages = {25}, publisher = {Institut für Mathematik und wissenschaftliches Rechnen der Universität Graz}, title = {{Is Debian suitable for running an HPC Cluster?}}, year = {2019}, } @inproceedings{630, abstract = {Background: Standards have become available to share semantically encoded vital parameters from medical devices, as required for example by personal healthcare records. Standardised sharing of biosignal data largely remains open. Objectives: The goal of this work is to explore available biosignal file format and data exchange standards and profiles, and to conceptualise end-To-end solutions. Methods: The authors reviewed and discussed available biosignal file format standards with other members of international standards development organisations (SDOs). Results: A raw concept for standards based acquisition, storage, archiving and sharing of biosignals was developed. The GDF format may serve for storing biosignals. Signals can then be shared using FHIR resources and may be stored on FHIR servers or in DICOM archives, with DICOM waveforms as one possible format. Conclusion: Currently a group of international SDOs (e.g. HL7, IHE, DICOM, IEEE) is engaged in intensive discussions. This discussion extends existing work that already was adopted by large implementer communities. The concept presented here only reports the current status of the discussion in Austria. The discussion will continue internationally, with results to be expected over the coming years.}, author = {Sauermann, Stefan and David, Veronika and Schlögl, Alois and Egelkraut, Reinhard and Frohner, Matthias and Pohn, Birgit and Urbauer, Philipp and Mense, Alexander}, isbn = {978-161499758-0}, location = {Vienna, Austria}, pages = {356 -- 362}, publisher = {IOS Press}, title = {{Biosignals standards and FHIR: The way to go}}, doi = {10.3233/978-1-61499-759-7-356}, volume = {236}, year = {2017}, } @inproceedings{12905, author = {Schlögl, Alois and Kiss, Janos}, booktitle = {AHPC17 – Austrian HPC Meeting 2017}, location = {Grundlsee, Austria}, pages = {28}, publisher = {FSP Scientific Computing}, title = {{Scientific Computing at IST Austria}}, year = {2017}, } @inproceedings{10810, abstract = {The main goal of the SCP-ECG standard is to address ECG data and related metadata structuring, semantics and syntax, with the objective of facilitating interoperability and thus supporting and promoting the exchange of the relevant information for unary and serial ECG diagnosis. Starting with version V3.0, the standard now also provides support for the storage of continuous, long-term ECG recordings and affords a repository for selected ECG sequences and the related metadata to accommodate stress tests, drug trials and protocol-based ECG recordings. The global and per-lead measurements sections have been extended and three new sections have been introduced for storing beat-by-beat and/or spike-by-spike measurements and annotations. The used terminology and the provided measurements and annotations have been harmonized with the ISO/IEEE 11073-10102 Annotated ECG standard. Emphasis has also been put on harmonizing the Universal Statement Codes with the CDISC and the categorized AHA statement codes and similarly the drug and implanted devices codes with the ATC and NASPE/BPEG codes. }, author = {Rubel, Paul and Pani, Danilo and Schlögl, Alois and Fayn, Jocelyne and Badilini, Fabio and Macfarlane, Peter and Varri, Alpo}, booktitle = {2016 Computing in Cardiology Conference}, issn = {2325-887X}, location = {Vancouver, Canada}, pages = {309--312}, publisher = {Computing in Cardiology}, title = {{SCP-ECG V3.0: An enhanced standard communication protocol for computer-assisted electrocardiography}}, doi = {10.22489/cinc.2016.090-500}, volume = {43}, year = {2016}, } @article{1350, abstract = {The hippocampal CA3 region plays a key role in learning and memory. Recurrent CA3–CA3 synapses are thought to be the subcellular substrate of pattern completion. However, the synaptic mechanisms of this network computation remain enigmatic. To investigate these mechanisms, we combined functional connectivity analysis with network modeling. Simultaneous recording fromup to eight CA3 pyramidal neurons revealed that connectivity was sparse, spatially uniform, and highly enriched in disynaptic motifs (reciprocal, convergence,divergence, and chain motifs). Unitary connections were composed of one or two synaptic contacts, suggesting efficient use of postsynaptic space. Real-size modeling indicated that CA3 networks with sparse connectivity, disynaptic motifs, and single-contact connections robustly generated pattern completion.Thus, macro- and microconnectivity contribute to efficient memory storage and retrieval in hippocampal networks.}, author = {Guzmán, José and Schlögl, Alois and Frotscher, Michael and Jonas, Peter M}, journal = {Science}, number = {6304}, pages = {1117 -- 1123}, publisher = {American Association for the Advancement of Science}, title = {{Synaptic mechanisms of pattern completion in the hippocampal CA3 network}}, doi = {10.1126/science.aaf1836}, volume = {353}, year = {2016}, } @inproceedings{12903, author = {Schlögl, Alois and Stadlbauer, Stephan}, booktitle = {AHPC16 - Austrian HPC Meeting 2016}, location = {Grundlsee, Austria}, pages = {37}, publisher = {VSC - Vienna Scientific Cluster}, title = {{High performance computing at IST Austria: Modelling the human hippocampus}}, year = {2016}, } @article{1890, abstract = {To search for a target in a complex environment is an everyday behavior that ends with finding the target. When we search for two identical targets, however, we must continue the search after finding the first target and memorize its location. We used fixation-related potentials to investigate the neural correlates of different stages of the search, that is, before and after finding the first target. Having found the first target influenced subsequent distractor processing. Compared to distractor fixations before the first target fixation, a negative shift was observed for three subsequent distractor fixations. These results suggest that processing a target in continued search modulates the brain's response, either transiently by reflecting temporary working memory processes or permanently by reflecting working memory retention.}, author = {Körner, Christof and Braunstein, Verena and Stangl, Matthias and Schlögl, Alois and Neuper, Christa and Ischebeck, Anja}, journal = {Psychophysiology}, number = {4}, pages = {385 -- 395}, publisher = {Wiley-Blackwell}, title = {{Sequential effects in continued visual search: Using fixation-related potentials to compare distractor processing before and after target detection}}, doi = {10.1111/psyp.12062}, volume = {51}, year = {2014}, } @article{2230, abstract = {Intracellular electrophysiological recordings provide crucial insights into elementary neuronal signals such as action potentials and synaptic currents. Analyzing and interpreting these signals is essential for a quantitative understanding of neuronal information processing, and requires both fast data visualization and ready access to complex analysis routines. To achieve this goal, we have developed Stimfit, a free software package for cellular neurophysiology with a Python scripting interface and a built-in Python shell. The program supports most standard file formats for cellular neurophysiology and other biomedical signals through the Biosig library. To quantify and interpret the activity of single neurons and communication between neurons, the program includes algorithms to characterize the kinetics of presynaptic action potentials and postsynaptic currents, estimate latencies between pre- and postsynaptic events, and detect spontaneously occurring events. We validate and benchmark these algorithms, give estimation errors, and provide sample use cases, showing that Stimfit represents an efficient, accessible and extensible way to accurately analyze and interpret neuronal signals.}, author = {Guzmán, José and Schlögl, Alois and Schmidt Hieber, Christoph}, issn = {16625196}, journal = {Frontiers in Neuroinformatics}, number = {FEB}, publisher = {Frontiers Research Foundation}, title = {{Stimfit: Quantifying electrophysiological data with Python}}, doi = {10.3389/fninf.2014.00016}, volume = {8}, year = {2014}, } @article{10396, abstract = {Stimfit is a free cross-platform software package for viewing and analyzing electrophysiological data. It supports most standard file types for cellular neurophysiology and other biomedical formats. Its analysis algorithms have been used and validated in several experimental laboratories. Its embedded Python scripting interface makes Stimfit highly extensible and customizable.}, author = {Schlögl, Alois and Jonas, Peter M and Schmidt-Hieber, C. and Guzman, S. J.}, issn = {1862-278X}, journal = {Biomedical Engineering / Biomedizinische Technik}, keywords = {biomedical engineering, data analysis, free software}, location = {Graz, Austria}, number = {SI-1-Track-G}, publisher = {De Gruyter}, title = {{Stimfit: A fast visualization and analysis environment for cellular neurophysiology}}, doi = {10.1515/bmt-2013-4181}, volume = {58}, year = {2013}, } @article{2954, abstract = {Spontaneous postsynaptic currents (PSCs) provide key information about the mechanisms of synaptic transmission and the activity modes of neuronal networks. However, detecting spontaneous PSCs in vitro and in vivo has been challenging, because of the small amplitude, the variable kinetics, and the undefined time of generation of these events. Here, we describe a, to our knowledge, new method for detecting spontaneous synaptic events by deconvolution, using a template that approximates the average time course of spontaneous PSCs. A recorded PSC trace is deconvolved from the template, resulting in a series of delta-like functions. The maxima of these delta-like events are reliably detected, revealing the precise onset times of the spontaneous PSCs. Among all detection methods, the deconvolution-based method has a unique temporal resolution, allowing the detection of individual events in high-frequency bursts. Furthermore, the deconvolution-based method has a high amplitude resolution, because deconvolution can substantially increase the signal/noise ratio. When tested against previously published methods using experimental data, the deconvolution-based method was superior for spontaneous PSCs recorded in vivo. Using the high-resolution deconvolution-based detection algorithm, we show that the frequency of spontaneous excitatory postsynaptic currents in dentate gyrus granule cells is 4.5 times higher in vivo than in vitro.}, author = {Pernia-Andrade, Alejandro and Goswami, Sarit and Stickler, Yvonne and Fröbe, Ulrich and Schlögl, Alois and Jonas, Peter M}, journal = {Biophysical Journal}, number = {7}, pages = {1429 -- 1439}, publisher = {Biophysical}, title = {{A deconvolution based method with high sensitivity and temporal resolution for detection of spontaneous synaptic currents in vitro and in vivo}}, doi = {10.1016/j.bpj.2012.08.039}, volume = {103}, year = {2012}, }