Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Adrian A. Wanner"'
Autor:
Zhihao Zheng, Christopher S. Own, Adrian A. Wanner, Randal A. Koene, Eric W. Hammerschmith, William M. Silversmith, Nico Kemnitz, Ran Lu, David W. Tank, H. Sebastian Seung
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-11 (2024)
Abstract Serial section transmission electron microscopy (TEM) has proven to be one of the leading methods for millimeter-scale 3D imaging of brain tissues at nanoscale resolution. It is important to further improve imaging efficiency to acquire larg
Externí odkaz:
https://doaj.org/article/cd50b5dc025f445b9fa3853971c5a1c2
Autor:
Adrian A. Wanner, Ashwin Vishwanathan
Publikováno v:
Frontiers in Neural Circuits, Vol 12 (2018)
For a mechanistic understanding of neuronal circuits in the brain, a detailed description of information flow is necessary. Thereby it is crucial to link neuron function to the underlying circuit structure. Multiphoton calcium imaging is the standard
Externí odkaz:
https://doaj.org/article/78abf94c21224fbd846da95edb257418
Autor:
Sebastian Ströh, Eric W Hammerschmith, David W Tank, H Sebastian Seung, Adrian Andreas Wanner
Publikováno v:
eLife, Vol 11 (2022)
Electron microscopy of biological tissue has recently seen an unprecedented increase in imaging throughput moving the ultrastructural analysis of large tissue blocks such as whole brains into the realm of the feasible. However, homogeneous, high-qual
Externí odkaz:
https://doaj.org/article/fff3a7819e294d4badc95eca7958c24c
Autor:
Fabian Svara, Dominique Förster, Fumi Kubo, Michał Januszewski, Marco dal Maschio, Philipp J. Schubert, Jörgen Kornfeld, Adrian A. Wanner, Eva Laurell, Winfried Denk, Herwig Baier
Publikováno v:
Nature Methods
This Resource presents a serial block-face EM dataset of the whole larval zebrafish brain, including automated segmentation of neurons, detection of synapses and reconstruction of circuitry for visual motion processing. Dense reconstruction of synapt
Autor:
Zhihao Zheng, Christopher S. Own, Adrian A. Wanner, Randal A. Koene, Eric W. Hammerschmith, William M. Silversmith, Nico Kemnitz, David W. Tank, H. Sebastian Seung
We have achieved a three fold increase in the speed of transmission electron microscopy by using a beam deflecting mechanism to enable highly efficient acquisition of multiple image tiles for each motion of the mechanical stage. For millimeter-scale
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e2b527b8bde62b14a1cd913c3d2ede18
https://doi.org/10.1101/2022.11.23.517701
https://doi.org/10.1101/2022.11.23.517701
Autor:
Rainer W. Friedrich, Adrian A. Wanner
Publikováno v:
Nature neuroscience
Neuronal computations underlying higher brain functions depend on synaptic interactions among specific neurons. A mechanistic understanding of such computations requires wiring diagrams of neuronal networks. In this study, we examined how the olfacto
Electron microscopy of biological tissue has recently seen an unprecedented increase in imaging throughput moving the ultrastructural analysis of large tissue blocks such as whole brains into the realm of the feasible. However, homogeneous, high qual
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1933a1bfc3e95b63ee33df449b7c500
https://doi.org/10.1101/2021.06.19.448808
https://doi.org/10.1101/2021.06.19.448808
Autor:
Rainer W. Friedrich, Adrian A. Wanner
Publikováno v:
Annual review of neuroscience. 44
The dense reconstruction of neuronal wiring diagrams from volumetric electron microscopy data has the potential to generate fundamentally new insights into mechanisms of information processing and storage in neuronal circuits. Zebrafish provide uniqu
Publikováno v:
Frontiers in Neural Circuits, Vol 7 (2013)
The clever choice of animal models has been instrumental for many breakthrough discoveries in life sciences. One of the outstanding challenges in neuroscience is the in-depth analysis of neuronal circuits to understand how interactions between large
Externí odkaz:
https://doaj.org/article/869463694b25406e9ae28064de656af4