Schottdorf, Manuel

[["dc.bibliographiccitation.firstpage","194"],["dc.bibliographiccitation.journal","Journal of Neuroscience Methods"],["dc.bibliographiccitation.lastpage","203"],["dc.bibliographiccitation.volume","257"],["dc.contributor.author","Samhaber, Robert"],["dc.contributor.author","Schottdorf, Manuel"],["dc.contributor.author","El Hady, Ahmed"],["dc.contributor.author","Broeking, Kai"],["dc.contributor.author","Daus, Andreas"],["dc.contributor.author","Thielemann, Christiane"],["dc.contributor.author","Stühmer, Walter"],["dc.contributor.author","Wolf, Fred"],["dc.date.accessioned","2018-11-07T10:19:24Z"],["dc.date.available","2018-11-07T10:19:24Z"],["dc.date.issued","2016"],["dc.description.abstract","Background: Multi-electrode arrays (MEAs) allow non-invasive multi-unit recording in-vitro from cultured neuronal networks. For sufficient neuronal growth and adhesion on such MEAs, substrate preparation is required. Plating of dissociated neurons on a uniformly prepared MEA's surface results in the formation of spatially extended random networks with substantial inter-sample variability. Such cultures are not optimally suited to study the relationship between defined structure and dynamics in neuronal networks. To overcome these shortcomings, neurons can be cultured with pre-defined topology by spatially structured surface modification. Spatially structuring a MEA surface accurately and reproducibly with the equipment of a typical cell-culture laboratory is challenging. New method: In this paper, we present a novel approach utilizing micro-contact printing (mu CP) combined with a custom-made device to accurately position patterns on MEAs with high precision. We call this technique AP-mu CP (accurate positioning micro-contact printing). Comparison with existing methods: Other approaches presented in the literature using mu CP for patterning either relied on facilities or techniques not readily available in a standard cell culture laboratory, or they did not specify means of precise pattern positioning. Conclusion: Here we present a relatively simple device for reproducible and precise patterning in a standard cell-culture laboratory setting. The patterned neuronal islands on MEAs provide a basis for high throughput electrophysiology to study the dynamics of single neurons and neuronal networks. (C) 2015 Elsevier B.V. All rights reserved."],["dc.identifier.doi","10.1016/j.jneumeth.2015.09.022"],["dc.identifier.isi","000366224100020"],["dc.identifier.pmid","26432934"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/41649"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.issn","1872-678X"],["dc.relation.issn","0165-0270"],["dc.title","Growing neuronal islands on multi-electrode arrays using an accurate positioning-mu CP device"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e1004602"],["dc.bibliographiccitation.issue","11"],["dc.bibliographiccitation.journal","PLOS Computational Biology"],["dc.bibliographiccitation.volume","11"],["dc.contributor.author","Schottdorf, Manuel"],["dc.contributor.author","Keil, Wolfgang"],["dc.contributor.author","Coppola, David"],["dc.contributor.author","White, Leonard E."],["dc.contributor.author","Wolf, Fred"],["dc.date.accessioned","2017-09-07T11:45:38Z"],["dc.date.available","2017-09-07T11:45:38Z"],["dc.date.issued","2015"],["dc.description.abstract","The architecture of iso-orientation domains in the primary visual cortex (V1) of placental carnivores and primates apparently follows species invariant quantitative laws. Dynamical optimization models assuming that neurons coordinate their stimulus preferences throughout cortical circuits linking millions of cells specifically predict these invariants. This might indicate that V1’s intrinsic connectome and its functional architecture adhere to a single optimization principle with high precision and robustness. To validate this hypothesis, it is critical to closely examine the quantitative predictions of alternative candidate theories. Random feedforward wiring within the retino-cortical pathway represents a conceptually appealing alternative to dynamical circuit optimization because random dimension-expanding projections are believed to generically exhibit computationally favorable properties for stimulus representations. Here, we ask whether the quantitative invariants of V1 architecture can be explained as a generic emergent property of random wiring. We generalize and examine the stochastic wiring model proposed by Ringach and coworkers, in which iso-orientation domains in the visual cortex arise through random feedforward connections between semi-regular mosaics of retinal ganglion cells (RGCs) and visual cortical neurons. We derive closed-form expressions for cortical receptive fields and domain layouts predicted by the model for perfectly hexagonal RGC mosaics. Including spatial disorder in the RGC positions considerably changes the domain layout properties as a function of disorder parameters such as position scatter and its correlations across the retina. However, independent of parameter choice, we find that the model predictions substantially deviate from the layout laws of iso-orientation domains observed experimentally. Considering random wiring with the currently most realistic model of RGC mosaic layouts, a pairwise interacting point process, the predicted layouts remain distinct from experimental observations and resemble Gaussian random fields. We conclude that V1 layout invariants are specific quantitative signatures of visual cortical optimization, which cannot be explained by generic random feedforward-wiring models."],["dc.identifier.doi","10.1371/journal.pcbi.1004602"],["dc.identifier.gro","3151833"],["dc.identifier.pmid","26575467"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/12731"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8659"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.relation.issn","1553-7358"],["dc.relation.orgunit","Fakultät für Physik"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Random Wiring, Ganglion Cell Mosaics, and the Functional Architecture of the Visual Cortex"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","no"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e86139"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","PLoS ONE"],["dc.bibliographiccitation.volume","9"],["dc.contributor.author","Schottdorf, Manuel"],["dc.contributor.author","Eglen, Stephen J."],["dc.contributor.author","Wolf, Fred"],["dc.contributor.author","Keil, Wolfgang"],["dc.date.accessioned","2017-09-07T11:45:42Z"],["dc.date.available","2017-09-07T11:45:42Z"],["dc.date.issued","2014"],["dc.description.abstract","It has been argued that the emergence of roughly periodic orientation preference maps (OPMs) in the primary visual cortex (V1) of carnivores and primates can be explained by a so-called statistical connectivity model. This model assumes that input to V1 neurons is dominated by feed-forward projections originating from a small set of retinal ganglion cells (RGCs). The typical spacing between adjacent cortical orientation columns preferring the same orientation then arises via Moiré-Interference between hexagonal ON/OFF RGC mosaics. While this Moiré-Interference critically depends on long-range hexagonal order within the RGC mosaics, a recent statistical analysis of RGC receptive field positions found no evidence for such long-range positional order. Hexagonal order may be only one of several ways to obtain spatially repetitive OPMs in the statistical connectivity model. Here, we investigate a more general requirement on the spatial structure of RGC mosaics that can seed the emergence of spatially repetitive cortical OPMs, namely that angular correlations between so-called RGC dipoles exhibit a spatial structure similar to that of OPM autocorrelation functions. Both in cat beta cell mosaics as well as primate parasol receptive field mosaics we find that RGC dipole angles are spatially uncorrelated. To help assess the level of these correlations, we introduce a novel point process that generates mosaics with realistic nearest neighbor statistics and a tunable degree of spatial correlations of dipole angles. Using this process, we show that given the size of available data sets, the presence of even weak angular correlations in the data is very unlikely. We conclude that the layout of ON/OFF ganglion cell mosaics lacks the spatial structure necessary to seed iso-orientation domains in the primary visual cortex."],["dc.identifier.doi","10.1371/journal.pone.0086139"],["dc.identifier.gro","3151837"],["dc.identifier.pmid","24475081"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/9901"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8664"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.relation.issn","1932-6203"],["dc.relation.orgunit","Fakultät für Physik"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Can Retinal Ganglion Cell Dipoles Seed Iso-Orientation Domains in the Visual Cortex?"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","no"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.contributor.author","Samhaber, Robert"],["dc.contributor.author","Schottdorf, Manuel"],["dc.contributor.author","Hady, Ahmed El"],["dc.contributor.author","Broeking, Kai"],["dc.contributor.author","Daus, Andreas"],["dc.contributor.author","Thielemann, Christiane"],["dc.contributor.author","Stühmer, Walter"],["dc.contributor.author","Wolf, Fred"],["dc.date.accessioned","2017-09-07T11:45:41Z"],["dc.date.available","2017-09-07T11:45:41Z"],["dc.date.issued","2015"],["dc.identifier.gro","3151836"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/8663"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.publisher","Cold Spring Harbor Laboratory"],["dc.title","Growing neuronal islands on multi-electrode arrays using an Accurate Positioning-μCP device"],["dc.type","preprint"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]