Alpha-synuclein effect on neuronal networks in cell culture

Author(s):  
Kristian Leite
2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Martin Bartels ◽  
Daniel Weckbecker ◽  
Peer-Hendrik Kuhn ◽  
Sergey Ryazanov ◽  
Andrei Leonov ◽  
...  

2013 ◽  
Vol 9 ◽  
pp. P721-P721
Author(s):  
Feng Liu ◽  
Justin Hole ◽  
Michael Hutton ◽  
Ronald DeMattos

2019 ◽  
Vol 3 (5) ◽  
pp. 1970054
Author(s):  
Cornelius Fendler ◽  
Christian Denker ◽  
Jann Harberts ◽  
Parisa Bayat ◽  
Robert Zierold ◽  
...  

2015 ◽  
Author(s):  
Robert Samhaber ◽  
Manuel Schottdorf ◽  
Ahmed El Hady ◽  
Kai Broeking ◽  
Andreas Daus ◽  
...  

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. In this paper, we present a novel approach utilizing micro-contact printing (μCP) combined with a custom-made device to accurately position patterns on MEAs with high precision. We call this technique AP-μCP (accurate positioning micro-contact printing). Other approaches presented in the literature using μCP 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. 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.


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