@article{OberlaenderdeKockBrunoetal.2012, author = {Oberlaender, Marcel and de Kock, Christiaan P. J. and Bruno, Randy M. and Ramirez, Alejandro and Meyer, Hanno and Dercksen, Vincent J. and Helmstaedter, Moritz and Sakmann, Bert}, title = {Cell Type-Specific Three-Dimensional Structure of Thalamocortical Circuits in a Column of Rat Vibrissal Cortex}, volume = {22}, journal = {Cerebral Cortex}, number = {10}, doi = {doi:10.1093/cercor/bhr317}, pages = {2375 -- 2391}, year = {2012}, language = {en} } @misc{OberlaenderBrunodeKocketal.2009, author = {Oberlaender, Marcel and Bruno, Randy M. and de Kock, Christiaan P. J. and Meyer, Hanno and Dercksen, Vincent J. and Sakmann, Bert}, title = {3D distribution and sub-cellular organization of thalamocortical VPM synapses for individual excitatory neuronal cell types in rat barrel cortex}, journal = {Conference Abstract No. 173.19/Y35, 39th Annual Meeting of the Society for Neuroscience (SfN)}, year = {2009}, language = {en} } @misc{OberlaenderDercksenBroseretal.2008, author = {Oberlaender, Marcel and Dercksen, Vincent J. and Broser, Philip J. and Bruno, Randy M. and Sakmann, Bert}, title = {NeuroMorph and NeuroCount: Automated tools for fast and objective acquisition of neuronal morphology for quantitative structural analysis}, journal = {Frontiers in Neuroinformatics. Conference Abstract: Neuroinformatics}, doi = {10.3389/conf.neuro.11.2008.01.065}, year = {2008}, language = {en} } @misc{EggerDercksenKocketal.2014, author = {Egger, Robert and Dercksen, Vincent J. and Kock, Christiaan P.J. and Oberlaender, Marcel}, title = {Reverse Engineering the 3D Structure and Sensory-Evoked Signal Flow of Rat Vibrissal Cortex}, volume = {11}, journal = {The Computing Dendrite}, editor = {Cuntz, Hermann and Remme, Michiel W.H. and Torben-Nielsen, Benjamin}, publisher = {Springer}, address = {New York}, doi = {10.1007/978-1-4614-8094-5_8}, pages = {127 -- 145}, year = {2014}, language = {en} } @misc{DercksenHegeOberlaender2013, author = {Dercksen, Vincent J. and Hege, Hans-Christian and Oberlaender, Marcel}, title = {The Filament Editor: An Interactive Software Environment for Visualization, Proof-Editing and Analysis of 3D Neuron Morphology}, issn = {1438-0064}, doi = {10.1007/s12021-013-9213-2}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-43157}, year = {2013}, abstract = {Neuroanatomical analysis, such as classification of cell types, depends on reliable reconstruction of large numbers of complete 3D dendrite and axon morphologies. At present, the majority of neuron reconstructions are obtained from preparations in a single tissue slice in vitro, thus suffering from cut off dendrites and, more dramatically, cut off axons. In general, axons can innervate volumes of several cubic millimeters and may reach path lengths of tens of centimeters. Thus, their complete reconstruction requires in vivo labeling, histological sectioning and imaging of large fields of view. Unfortunately, anisotropic background conditions across such large tissue volumes, as well as faintly labeled thin neurites, result in incomplete or erroneous automated tracings and even lead experts to make annotation errors during manual reconstructions. Consequently, tracing reliability renders the major bottleneck for reconstructing complete 3D neuron morphologies. Here, we present a novel set of tools, integrated into a software environment named 'Filament Editor', for creating reliable neuron tracings from sparsely labeled in vivo datasets. The Filament Editor allows for simultaneous visualization of complex neuronal tracings and image data in a 3D viewer, proof-editing of neuronal tracings, alignment and interconnection across sections, and morphometric analysis in relation to 3D anatomical reference structures. We illustrate the functionality of the Filament Editor on the example of in vivo labeled axons and demonstrate that for the exemplary dataset the final tracing results after proof-editing are independent of the expertise of the human operator.}, language = {en} } @article{DercksenHegeOberlaender2014, author = {Dercksen, Vincent J. and Hege, Hans-Christian and Oberlaender, Marcel}, title = {The Filament Editor: An Interactive Software Environment for Visualization, Proof-Editing and Analysis of 3D Neuron Morphology}, volume = {12}, journal = {NeuroInformatics}, number = {2}, publisher = {Springer US}, doi = {10.1007/s12021-013-9213-2}, pages = {325 -- 339}, year = {2014}, language = {en} } @article{OzelKulkarniHasanetal.2019, author = {Ozel, Mehmet Neset and Kulkarni, Abhishek and Hasan, Amr and Brummer, Josephine and Moldenhauer, Marian and Daumann, Ilsa-Maria and Wolfenberg, Heike and Dercksen, Vincent J. and Kiral, Ferdi Ridvan and Weiser, Martin and Prohaska, Steffen and von Kleist, Max and Hiesinger, Peter Robin}, title = {Serial synapse formation through filopodial competition for synaptic seeding factors}, volume = {50}, journal = {Developmental Cell}, number = {4}, doi = {10.1016/j.devcel.2019.06.014}, pages = {447 -- 461}, year = {2019}, abstract = {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.}, language = {en} } @article{LandauEggerDercksenetal.2016, author = {Landau, Itamar D. and Egger, Robert and Dercksen, Vincent J. and Oberlaender, Marcel and Sompolinsky, Haim}, title = {The Impact of Structural Heterogeneity on Excitation-Inhibition Balance in Cortical Networks}, volume = {92}, journal = {Neuron}, number = {5}, doi = {10.1016/j.neuron.2016.10.027}, pages = {1106 -- 1121}, year = {2016}, abstract = {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.}, language = {en} } @article{LindowBruenigDercksenetal.2020, author = {Lindow, Norbert and Br{\"u}nig, Florian and Dercksen, Vincent J. and Fabig, Gunar and Kiewisz, Robert and Redemann, Stefanie and M{\"u}ller-Reichert, Thomas and Prohaska, Steffen and Baum, Daniel}, title = {Semi-automatic stitching of filamentous structures in image stacks from serial-section electron tomography}, journal = {bioRxiv}, doi = {10.1101/2020.05.28.120899}, year = {2020}, abstract = {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.}, language = {en} } @misc{OezelKulkarniHasanetal.2019, author = {{\"O}zel, M. Neset and Kulkarni, Abhishek and Hasan, Amr and Brummer, Josephine and Moldenhauer, Marian and Daumann, Ilsa-Maria and Wolfenberg, Heike and Dercksen, Vincent J. and Kiral, F. Ridvan and Weiser, Martin and Prohaska, Steffen and von Kleist, Max and Hiesinger, Peter Robin}, title = {Serial synapse formation through filopodial competition for synaptic seeding factors}, issn = {1438-0064}, doi = {10.1016/j.devcel.2019.06.014}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-74397}, year = {2019}, abstract = {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.}, language = {en} }