@article{2950, abstract = {Contractile actomyosin rings drive various fundamental morphogenetic processes ranging from cytokinesis to wound healing. Actomyosin rings are generally thought to function by circumferential contraction. Here, we show that the spreading of the enveloping cell layer (EVL) over the yolk cell during zebrafish gastrulation is driven by a contractile actomyosin ring. In contrast to previous suggestions, we find that this ring functions not only by circumferential contraction but also by a flow-friction mechanism. This generates a pulling force through resistance against retrograde actomyosin flow. EVL spreading proceeds normally in situations where circumferential contraction is unproductive, indicating that the flow-friction mechanism is sufficient. Thus, actomyosin rings can function in epithelial morphogenesis through a combination of cable-constriction and flow-friction mechanisms.}, author = {Behrndt, Martin and Salbreux, Guillaume and Campinho, Pedro and Hauschild, Robert and Oswald, Felix and Roensch, Julia and Grill, Stephan and Heisenberg, Carl-Philipp J}, journal = {Science}, number = {6104}, pages = {257 -- 260}, publisher = {American Association for the Advancement of Science}, title = {{Forces driving epithelial spreading in zebrafish gastrulation}}, doi = {10.1126/science.1224143}, volume = {338}, year = {2012}, } @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}, } @article{2965, abstract = {Dieser Artikel soll die sechs verschiedenen Creative Commons Lizenzen erläutern und ihre Bedeutung im Rahmen des wissenschaftlichen Publizierens und des Open Access erklären (CC-BY, CC-BY-SA, CC-BY-NC, CC-BY-ND, CC-BYNC-SA, CC-BY-NC-ND).}, author = {Danowski, Patrick}, journal = {Mitteilungen der Vereinigung Österreichischer Bibliothekarinnen & Bibliothekare}, number = {2}, pages = {200 -- 212}, publisher = {VÖB}, title = {{Kontext Open Access: Creative Commons}}, volume = {65}, year = {2012}, } @article{3243, abstract = {Wie wandelt sich das Berufsbild in Wissenschaftlichen Bibliotheken? Patrick Danowski gibt seine Einschätzung ab. }, author = {Danowski, Patrick}, issn = {1607-7172}, journal = {Büchereiperspektiven}, number = {1}, pages = {11}, publisher = {Büchereiverband Österreichs}, title = {{Zwischen Technologie und Information}}, volume = {2012}, year = {2012}, } @article{3244, abstract = {Bibliothekare haben die Aufgabe, sich mit neuen Medienformen auseinanderzusetzen. }, author = {Danowski, Patrick}, issn = {1869-1137}, journal = {BuB - Forum Bibliothek und Information}, number = {4}, pages = {284}, publisher = {Fachzeitschrift des BIB – Berufsverband Information Bibliothek}, title = {{Die Zeit des Abwartens ist vorbei!}}, volume = {64}, year = {2012}, } @article{493, abstract = {The BCI competition IV stands in the tradition of prior BCI competitions that aim to provide high quality neuroscientific data for open access to the scientific community. As experienced already in prior competitions not only scientists from the narrow field of BCI compete, but scholars with a broad variety of backgrounds and nationalities. They include high specialists as well as students.The goals of all BCI competitions have always been to challenge with respect to novel paradigms and complex data. We report on the following challenges: (1) asynchronous data, (2) synthetic, (3) multi-class continuous data, (4) sessionto-session transfer, (5) directionally modulated MEG, (6) finger movements recorded by ECoG. As after past competitions, our hope is that winning entries may enhance the analysis methods of future BCIs.}, author = {Tangermann, Michael and Müller, Klaus and Aertsen, Ad and Birbaumer, Niels and Braun, Christoph and Brunner, Clemens and Leeb, Robert and Mehring, Carsten and Miller, Kai and Müller Putz, Gernot and Nolte, Guido and Pfurtscheller, Gert and Preissl, Hubert and Schalk, Gerwin and Schlögl, Alois and Vidaurre, Carmen and Waldert, Stephan and Blankertz, Benjamin}, journal = {Frontiers in Neuroscience}, publisher = {Frontiers Research Foundation}, title = {{Review of the BCI competition IV}}, doi = {10.3389/fnins.2012.00055}, volume = {6}, year = {2012}, } @techreport{5398, abstract = {This document is created as a part of the project “Repository for Research Data on IST Austria”. It summarises the actual state of research data at IST Austria, based on survey results. It supports the choice of appropriate software, which would best fit the requirements of their users, the researchers.}, author = {Porsche, Jana}, publisher = {IST Austria}, title = {{Actual state of research data @ ISTAustria}}, year = {2012}, } @article{490, abstract = {BioSig is an open source software library for biomedical signal processing. The aim of the BioSig project is to foster research in biomedical signal processing by providing free and open source software tools for many different application areas. Some of the areas where BioSig can be employed are neuroinformatics, brain-computer interfaces, neurophysiology, psychology, cardiovascular systems, and sleep research. Moreover, the analysis of biosignals such as the electroencephalogram (EEG), electrocorticogram (ECoG), electrocardiogram (ECG), electrooculogram (EOG), electromyogram (EMG), or respiration signals is a very relevant element of the BioSig project. Specifically, BioSig provides solutions for data acquisition, artifact processing, quality control, feature extraction, classification, modeling, and data visualization, to name a few. In this paper, we highlight several methods to help students and researchers to work more efficiently with biomedical signals. }, author = {Schlögl, Alois and Vidaurre, Carmen and Sander, Tilmann}, journal = {Computational Intelligence and Neuroscience}, publisher = {Hindawi Publishing Corporation}, title = {{BioSig: The free and open source software library for biomedical signal processing}}, doi = {10.1155/2011/935364}, volume = {2011}, year = {2011}, } @inproceedings{9943, abstract = {Segmentation is the process of partitioning digital images into meaningful regions. The analysis of biological high content images often requires segmentation as a first step. We propose ilastik as an easy-to-use tool which allows the user without expertise in image processing to perform segmentation and classification in a unified way. ilastik learns from labels provided by the user through a convenient mouse interface. Based on these labels, ilastik infers a problem specific segmentation. A random forest classifier is used in the learning step, in which each pixel's neighborhood is characterized by a set of generic (nonlinear) features. ilastik supports up to three spatial plus one spectral dimension and makes use of all dimensions in the feature calculation. ilastik provides realtime feedback that enables the user to interactively refine the segmentation result and hence further fine-tune the classifier. An uncertainty measure guides the user to ambiguous regions in the images. Real time performance is achieved by multi-threading which fully exploits the capabilities of modern multi-core machines. Once a classifier has been trained on a set of representative images, it can be exported and used to automatically process a very large number of images (e.g. using the CellProfiler pipeline). ilastik is an open source project and released under the BSD license at www.ilastik.org.}, author = {Sommer, Christoph M and Straehle, Christoph and Köthe, Ullrich and Hamprecht, Fred A.}, booktitle = {2011 IEEE International Symposium on Biomedical Imaging: from Nano to Micro}, isbn = {978-1-4244-4127-3}, issn = {1945-8452}, keywords = {image segmentation, biomedical imaging, three dimensional displays, neurons, retina, observers, image color analysis}, location = {Chicago, Illinois, USA}, publisher = {Institute of Electrical and Electronics Engineers}, title = {{Ilastik: Interactive learning and segmentation toolkit}}, doi = {10.1109/isbi.2011.5872394}, year = {2011}, } @inbook{14983, abstract = {This chapter tackles a difficult challenge: presenting signal processing material to non-experts. This chapter is meant to be comprehensible to people who have some math background, including a course in linear algebra and basic statistics, but do not specialize in mathematics, engineering, or related fields. Some formulas assume the reader is familiar with matrices and basic matrix operations, but not more advanced material. Furthermore, we tried to make the chapter readable even if you skip the formulas. Nevertheless, we include some simple methods to demonstrate the basics of adaptive data processing, then we proceed with some advanced methods that are fundamental in adaptive signal processing, and are likely to be useful in a variety of applications. The advanced algorithms are also online available [30]. In the second part, these techniques are applied to some real-world BCI data.}, author = {Schlögl, Alois and Vidaurre, Carmen and Müller, Klaus-Robert}, booktitle = {Brain-Computer Interfaces}, editor = {Graimann, Bernhard and Pfurtscheller, Gert and Allison, Brendan}, isbn = {9783642020902}, issn = {1612-3018}, pages = {331--355}, publisher = {Springer}, title = {{Adaptive Methods in BCI Research - An Introductory Tutorial}}, doi = {10.1007/978-3-642-02091-9_18}, year = {2010}, } @article{4157, abstract = {Integrin- and cadherin-mediated adhesion is central for cell and tissue morphogenesis, allowing cells and tissues to change shape without loosing integrity. Studies predominantly in cell culture showed that mechanosensation through adhesion structures is achieved by force-mediated modulation of their molecular composition. The specific molecular composition of adhesion sites in turn determines their signalling activity and dynamic reorganization. Here, we will review how adhesion sites respond to mecanical stimuli, and how spatially and temporally regulated signalling from different adhesion sites controls cell migration and tissue morphogenesis.}, author = {Papusheva, Ekaterina and Heisenberg, Carl-Philipp J}, journal = {EMBO Journal}, number = {16}, pages = {2753 -- 2768}, publisher = {Wiley-Blackwell}, title = {{Spatial organization of adhesion: force-dependent regulation and function in tissue morphogenesis}}, doi = {10.1038/emboj.2010.182}, volume = {29}, year = {2010}, }