@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{OberlaenderDercksenLangetal.2009, author = {Oberlaender, Marcel and Dercksen, Vincent J. and Lang, Stefan and Sakmann, Bert}, title = {3D mapping of synaptic connections within "in silico" microcircuits of full compartmental neurons in extended networks on the example of VPM axons projecting into S1 of rats.}, journal = {Conference Abstract, Neuroinformatics}, doi = {10.3389/conf.neuro.11.2009.08.092}, year = {2009}, 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} } @inproceedings{DercksenWeberGuentheretal.2009, author = {Dercksen, Vincent J. and Weber, Britta and G{\"u}nther, David and Oberlaender, Marcel and Prohaska, Steffen and Hege, Hans-Christian}, title = {Automatic alignment of stacks of filament data}, booktitle = {Proc. IEEE International Symposium on Biomedical Imaging}, publisher = {IEEE press}, address = {Boston, USA}, pages = {971 -- 974}, year = {2009}, language = {en} } @article{OberlaenderDercksenEggeretal.2009, author = {Oberlaender, Marcel and Dercksen, Vincent J. and Egger, Robert and Gensel, Maria and Sakmann, Bert and Hege, Hans-Christian}, title = {Automated three-dimensional detection and counting of neuron somata}, volume = {180}, journal = {Journal of Neuroscience Methods}, number = {1}, doi = {10.1016/j.jneumeth.2009.03.008}, pages = {147 -- 160}, year = {2009}, language = {en} } @article{EggerDercksenUdvaryetal.2014, author = {Egger, Robert and Dercksen, Vincent J. and Udvary, Daniel and Hege, Hans-Christian and Oberlaender, Marcel}, title = {Generation of dense statistical connectomes from sparse morphological data}, volume = {8}, journal = {Frontiers in Neuroanatomy}, number = {129}, doi = {10.3389/fnana.2014.00129}, year = {2014}, language = {en} } @misc{EggerDercksenUdvaryetal.2014, author = {Egger, Robert and Dercksen, Vincent J. and Udvary, Daniel and Hege, Hans-Christian and Oberlaender, Marcel}, title = {Generation of dense statistical connectomes from sparse morphological data}, issn = {1438-0064}, doi = {10.3389/fnana.2014.00129}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-53075}, year = {2014}, abstract = {Sensory-evoked signal flow, at cellular and network levels, is primarily determined by the synaptic wiring of the underlying neuronal circuitry. Measurements of synaptic innervation, connection probabilities and sub-cellular organization of synaptic inputs are thus among the most active fields of research in contemporary neuroscience. Methods to measure these quantities range from electrophysiological recordings over reconstructions of dendrite-axon overlap at light-microscopic levels to dense circuit reconstructions of small volumes at electron-microscopic resolution. However, quantitative and complete measurements at subcellular resolution and mesoscopic scales to obtain all local and long-range synaptic in/outputs for any neuron within an entire brain region are beyond present methodological limits. Here, we present a novel concept, implemented within an interactive software environment called NeuroNet, which allows (i) integration of sparsely sampled (sub)cellular morphological data into an accurate anatomical reference frame of the brain region(s) of interest, (ii) up-scaling to generate an average dense model of the neuronal circuitry within the respective brain region(s) and (iii) statistical measurements of synaptic innervation between all neurons within the model. We illustrate our approach by generating a dense average model of the entire rat vibrissal cortex, providing the required anatomical data, and illustrate how to measure synaptic innervation statistically. Comparing our results with data from paired recordings in vitro and in vivo, as well as with reconstructions of synaptic contact sites at light- and electron-microscopic levels, we find that our in silico measurements are in line with previous results.}, language = {en} } @inproceedings{HarthBastTroidletal.2023, author = {Harth, Philipp and Bast, Arco and Troidl, Jakob and Meulemeester, Bjorge and Pfister, Hanspeter and Beyer, Johanna and Oberlaender, Marcel and Hege, Hans-Christian and Baum, Daniel}, title = {Rapid Prototyping for Coordinated Views of Multi-scale Spatial and Abstract Data: A Grammar-based Approach}, booktitle = {Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM)}, doi = {10.2312/vcbm.20231218}, year = {2023}, abstract = {Visualization grammars are gaining popularity as they allow visualization specialists and experienced users to quickly create static and interactive views. Existing grammars, however, mostly focus on abstract views, ignoring three-dimensional (3D) views, which are very important in fields such as natural sciences. We propose a generalized interaction grammar for the problem of coordinating heterogeneous view types, such as standard charts (e.g., based on Vega-Lite) and 3D anatomical views. An important aspect of our web-based framework is that user interactions with data items at various levels of detail can be systematically integrated and used to control the overall layout of the application workspace. With the help of a concise JSON-based specification of the intended workflow, we can handle complex interactive visual analysis scenarios. This enables rapid prototyping and iterative refinement of the visual analysis tool in collaboration with domain experts. We illustrate the usefulness of our framework in two real-world case studies from the field of neuroscience. Since the logic of the presented grammar-based approach for handling interactions between heterogeneous web-based views is free of any application specifics, it can also serve as a template for applications beyond biological research.}, language = {en} } @article{HarthUdvaryBoeltsetal.2024, author = {Harth, Philipp and Udvary, Daniel and Boelts, Jan and Baum, Daniel and Macke, Jakob H. and Hege, Hans-Christian and Oberlaender, Marcel}, title = {Dissecting origins of wiring specificity in dense cortical connectomes}, journal = {bioRxiv}, doi = {10.1101/2024.12.14.628490}, year = {2024}, abstract = {Wiring specificity in the cortex is observed across scales from the subcellular to the network level. It describes the deviations of connectivity patterns from those expected in randomly connected networks. Understanding the origins of wiring specificity in neural networks remains difficult as a variety of generative mechanisms could have contributed to the observed connectome. To take a step forward, we propose a generative modeling framework that operates directly on dense connectome data as provided by saturated reconstructions of neural tissue. The computational framework allows testing different assumptions of synaptic specificity while accounting for anatomical constraints posed by neuron morphology, which is a known confounding source of wiring specificity. We evaluated the framework on dense reconstructions of the mouse visual and the human temporal cortex. Our template model incorporates assumptions of synaptic specificity based on cell type, single-cell identity, and subcellular compartment. Combinations of these assumptions were sufficient to model various connectivity patterns that are indicative of wiring specificity. Moreover, the identified synaptic specificity parameters showed interesting similarities between both datasets, motivating further analysis of wiring specificity across species.}, language = {en} }