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| Hauptseite > Publikationsdatenbank > Dynamical and statistical structure of spatially organized neuronal networks > print |
| Hauptseite > Publikationsdatenbank > Dynamical and statistical structure of spatially organized neuronal networks > print |
| 001 | 911032 | ||
| 005 | 20240313103131.0 | ||
| 020 | _ | _ | |a 978-3-95806-651-9 |
| 024 | 7 | _ | |2 Handle |a 2128/32732 |
| 024 | 7 | _ | |2 URN |a urn:nbn:de:0001-2022112310 |
| 037 | _ | _ | |a FZJ-2022-04358 |
| 100 | 1 | _ | |0 P:(DE-Juel1)174497 |a Layer, Moritz |b 0 |e Corresponding author |u fzj |
| 245 | _ | _ | |a Dynamical and statistical structure of spatially organized neuronal networks |
| 260 | _ | _ | |a Jülich |b Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag |c 2022 |
| 300 | _ | _ | |a xiii, 165 |
| 336 | 7 | _ | |2 DataCite |a Output Types/Dissertation |
| 336 | 7 | _ | |0 PUB:(DE-HGF)3 |2 PUB:(DE-HGF) |a Book |m book |
| 336 | 7 | _ | |2 ORCID |a DISSERTATION |
| 336 | 7 | _ | |2 BibTeX |a PHDTHESIS |
| 336 | 7 | _ | |0 2 |2 EndNote |a Thesis |
| 336 | 7 | _ | |0 PUB:(DE-HGF)11 |2 PUB:(DE-HGF) |a Dissertation / PhD Thesis |b phd |m phd |s 1667806627_14947 |
| 336 | 7 | _ | |2 DRIVER |a doctoralThesis |
| 490 | 0 | _ | |a Schriften des Forschungszentrums Jülich Reihe Information / Information |v 85 |
| 502 | _ | _ | |a Dissertation, RWTH Aachen University, 2022 |b Dissertation |c RWTH Aachen University |d 2022 |
| 520 | _ | _ | |a The cerebral cortex, the outer layer of mammalian brains, comprises a vast number of neurons arranged and connected in a highly organized fashion. The likelihood of neurons to be connected and how fast they may exchange signals depends, among other properties, on their spatial distance. Cortical networks may be well described as completely random networks on microscopic scales because cortical neurons have essentially uniform connection probabilities within a few tens of micrometers. However, the distance-dependence of neuronal connections certainly is important on mesoscopic scales spanning several millimeters, where many neurons are most likely unconnected. While the theory of random networks is already well-established, how such a spatial organization affects a network’s activity is not yet fully understood. The objectiveof this thesis is to provide an overview of the current analytical understanding of spatially organized networks on a mesoscopic scale, as well as to advance this understanding with three studies covering complementary aspects of spatially organized network theory. |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/911032/files/Information_85.pdf |y OpenAccess |
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| 910 | 1 | _ | |0 I:(DE-588b)5008462-8 |6 P:(DE-Juel1)174497 |a Forschungszentrum Jülich |b 0 |k FZJ |
| 914 | 1 | _ | |y 2022 |
| 915 | _ | _ | |0 StatID:(DE-HGF)0510 |2 StatID |a OpenAccess |
| 915 | _ | _ | |0 LIC:(DE-HGF)CCBY4 |2 HGFVOC |a Creative Commons Attribution CC BY 4.0 |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-6-20090406 |k INM-6 |l Computational and Systems Neuroscience |x 0 |
| 920 | 1 | _ | |0 I:(DE-Juel1)IAS-6-20130828 |k IAS-6 |l Theoretical Neuroscience |x 1 |
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| 980 | _ | _ | |a book |
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| 980 | _ | _ | |a I:(DE-Juel1)IAS-6-20130828 |
| 980 | _ | _ | |a UNRESTRICTED |
| 981 | _ | _ | |a I:(DE-Juel1)IAS-6-20130828 |
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