TY - JOUR A1 - Oberlaender, Marcel A1 - de Kock, Christiaan P. J. A1 - Bruno, Randy M. A1 - Ramirez, Alejandro A1 - Meyer, Hanno A1 - Dercksen, Vincent J. A1 - Helmstaedter, Moritz A1 - Sakmann, Bert T1 - Cell Type-Specific Three-Dimensional Structure of Thalamocortical Circuits in a Column of Rat Vibrissal Cortex JF - Cerebral Cortex Y1 - 2012 U6 - https://doi.org/doi:10.1093/cercor/bhr317 VL - 22 IS - 10 SP - 2375 EP - 2391 ER - TY - JOUR A1 - Dercksen, Vincent J. A1 - Hege, Hans-Christian A1 - Oberlaender, Marcel T1 - The Filament Editor: An Interactive Software Environment for Visualization, Proof-Editing and Analysis of 3D Neuron Morphology JF - NeuroInformatics Y1 - 2014 U6 - https://doi.org/10.1007/s12021-013-9213-2 VL - 12 IS - 2 SP - 325 EP - 339 PB - Springer US ER - TY - JOUR A1 - Ozel, Mehmet Neset A1 - Kulkarni, Abhishek A1 - Hasan, Amr A1 - Brummer, Josephine A1 - Moldenhauer, Marian A1 - Daumann, Ilsa-Maria A1 - Wolfenberg, Heike A1 - Dercksen, Vincent J. A1 - Kiral, Ferdi Ridvan A1 - Weiser, Martin A1 - Prohaska, Steffen A1 - von Kleist, Max A1 - Hiesinger, Peter Robin T1 - Serial synapse formation through filopodial competition for synaptic seeding factors JF - Developmental Cell N2 - Following axon pathfinding, growth cones transition from stochastic filopodial exploration to the formation of a limited number of synapses. How the interplay of filopodia and synapse assembly ensures robust connectivity in the brain has remained a challenging problem. Here, we developed a new 4D analysis method for filopodial dynamics and a data-driven computational model of synapse formation for R7 photoreceptor axons in developing Drosophila brains. Our live data support a 'serial synapse formation' model, where at any time point only a single 'synaptogenic' filopodium suppresses the synaptic competence of other filopodia through competition for synaptic seeding factors. Loss of the synaptic seeding factors Syd-1 and Liprin-α leads to a loss of this suppression, filopodial destabilization and reduced synapse formation, which is sufficient to cause the destabilization of entire axon terminals. Our model provides a filopodial 'winner-takes-all' mechanism that ensures the formation of an appropriate number of synapses. Y1 - 2019 U6 - https://doi.org/10.1016/j.devcel.2019.06.014 VL - 50 IS - 4 SP - 447 EP - 461 ER - TY - JOUR A1 - Landau, Itamar D. A1 - Egger, Robert A1 - Dercksen, Vincent J. A1 - Oberlaender, Marcel A1 - Sompolinsky, Haim T1 - The Impact of Structural Heterogeneity on Excitation-Inhibition Balance in Cortical Networks JF - Neuron N2 - Models of cortical dynamics often assume a homogeneous connectivity structure. However, we show that heterogeneous input connectivity can prevent the dynamic balance between excitation and inhibition, a hallmark of cortical dynamics, and yield unrealistically sparse and temporally regular firing. Anatomically based estimates of the connectivity of layer 4 (L4) rat barrel cortex and numerical simulations of this circuit indicate that the local network possesses substantial heterogeneity in input connectivity, sufficient to disrupt excitation-inhibition balance. We show that homeostatic plasticity in inhibitory synapses can align the functional connectivity to compensate for structural heterogeneity. Alternatively, spike-frequency adaptation can give rise to a novel state in which local firing rates adjust dynamically so that adaptation currents and synaptic inputs are balanced. This theory is supported by simulations of L4 barrel cortex during spontaneous and stimulus-evoked conditions. Our study shows how synaptic and cellular mechanisms yield fluctuation-driven dynamics despite structural heterogeneity in cortical circuits. Y1 - 2016 U6 - https://doi.org/10.1016/j.neuron.2016.10.027 VL - 92 IS - 5 SP - 1106 EP - 1121 ER - TY - JOUR A1 - Lindow, Norbert A1 - Brünig, Florian A1 - Dercksen, Vincent J. A1 - Fabig, Gunar A1 - Kiewisz, Robert A1 - Redemann, Stefanie A1 - Müller-Reichert, Thomas A1 - Prohaska, Steffen A1 - Baum, Daniel T1 - Semi-automatic stitching of filamentous structures in image stacks from serial-section electron tomography JF - bioRxiv N2 - We present a software-assisted workflow for the alignment and matching of filamentous structures across a 3D stack of serial images. This is achieved by combining automatic methods, visual validation, and interactive correction. After an initial alignment, the user can continuously improve the result by interactively correcting landmarks or matches of filaments. Supported by a visual quality assessment of regions that have been already inspected, this allows a trade-off between quality and manual labor. The software tool was developed to investigate cell division by quantitative 3D analysis of microtubules (MTs) in both mitotic and meiotic spindles. For this, each spindle is cut into a series of semi-thick physical sections, of which electron tomograms are acquired. The serial tomograms are then stitched and non-rigidly aligned to allow tracing and connecting of MTs across tomogram boundaries. In practice, automatic stitching alone provides only an incomplete solution, because large physical distortions and a low signal-to-noise ratio often cause experimental difficulties. To derive 3D models of spindles despite the problems related to sample preparation and subsequent data collection, semi-automatic validation and correction is required to remove stitching mistakes. However, due to the large number of MTs in spindles (up to 30k) and their resulting dense spatial arrangement, a naive inspection of each MT is too time consuming. Furthermore, an interactive visualization of the full image stack is hampered by the size of the data (up to 100 GB). Here, we present a specialized, interactive, semi-automatic solution that considers all requirements for large-scale stitching of filamentous structures in serial-section image stacks. The key to our solution is a careful design of the visualization and interaction tools for each processing step to guarantee real-time response, and an optimized workflow that efficiently guides the user through datasets. Y1 - 2020 U6 - https://doi.org/10.1101/2020.05.28.120899 ER - TY - JOUR A1 - Lang, Stefan A1 - Dercksen, Vincent J. A1 - Sakmann, Bert A1 - Oberlaender, Marcel T1 - Simulation of signal flow in 3D reconstructions of an anatomically realistic neural network in rat vibrissal cortex JF - Neural Networks Y1 - 2011 U6 - https://doi.org/doi:10.1016/j.neunet.2011.06.013 VL - 24 IS - 9 SP - 998 EP - 1011 ER - TY - JOUR A1 - Kuß, Anja A1 - Gensel, Maria A1 - Meyer, Björn A1 - Dercksen, Vincent J. A1 - Prohaska, Steffen T1 - Effective Techniques to Visualize Filament-Surface Relationships JF - Comput. Graph. Forum Y1 - 2010 VL - 29 SP - 1003 EP - 1012 ER - TY - JOUR A1 - Oberlaender, Marcel A1 - Dercksen, Vincent J. A1 - Egger, Robert A1 - Gensel, Maria A1 - Sakmann, Bert A1 - Hege, Hans-Christian T1 - Automated three-dimensional detection and counting of neuron somata JF - Journal of Neuroscience Methods Y1 - 2009 U6 - https://doi.org/10.1016/j.jneumeth.2009.03.008 VL - 180 IS - 1 SP - 147 EP - 160 ER - TY - JOUR A1 - Gubatz, Sabine A1 - Dercksen, Vincent J. A1 - Brüß, Cornelia A1 - Weschke, Winfriede A1 - Wobus, Ulrich T1 - Analysis of barley (hordeum vulgare) grain development using three-dimensional digital models JF - The Plant Journal Y1 - 2007 U6 - https://doi.org/10.1111/j.1365-313X.2007.03260.x VL - 52 IS - 4 SP - 779 EP - 790 ER - TY - JOUR A1 - Egger, Robert A1 - Dercksen, Vincent J. A1 - Udvary, Daniel A1 - Hege, Hans-Christian A1 - Oberlaender, Marcel T1 - Generation of dense statistical connectomes from sparse morphological data JF - Frontiers in Neuroanatomy Y1 - 2014 U6 - https://doi.org/10.3389/fnana.2014.00129 VL - 8 IS - 129 ER -