Growing neuronal islands on multi-electrode arrays using an accurate positioning-μCP device.

J Neurosci Methods

Max Planck Institute for Dynamics and Self-Organization, Dept. Nonlinear Dynamics, Am Faßberg 17, 37077 Göttingen, Germany; Bernstein Center for Computational Neuroscience, Göttingen, Germany; Bernstein Focus Neurotechnology, Göttingen, Germany; SFB-889 Cellular Mechanisms of Sensory Processing, Göttingen, Germany; Faculty of Physics, Georg-August-Universität Göttingen, Göttingen, Germany. Electronic address:

Published: January 2016

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 (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).

Comparison With Existing Methods: 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.

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.

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Source
http://dx.doi.org/10.1016/j.jneumeth.2015.09.022DOI Listing

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