Axonal growth model in PDMS microstructures for in vitro neuro science applications.
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1
ETH Zürich, Institute for Biomedical Engineering, Switzerland
In vitro cell cultures could help us understand how neural networks can store information and do simple computations. In order to do so, one must be able to manipulate the behavior of these networks and observe their response. Microelectrode arrays help us achieve this goal, since they can stimulate and record neuron cultures in an arbitrary fashion with a spatial resolution of tens of micrometers while at the same time having a reasonable temporal resolution.
The drawback of artificially cultured neurons is the lack of reproducibility, which makes it difficult to make reliable statements regarding the interplay of neurons. We believe a more predictable response can be achieved, when the network interconectivity is restrained. Microstructures made out of Polydimethyilsiloxane (PDMS) can be used to confine the soma location to certain areas, while at the same time biasing the growth of axons in a preferred direction. The shape of the microchannel plays a commanding role on the success rate of such directional growth.
To help simply the search for potential microstructure candidates, which can generate directionality, we propose here a novel computational model that predicts the strength of a microstructure by simulating axonal growth in silico.
For a microstructure candidate, the growth of 2048 axons was simulated in an iterative manner. The growth direction of a subsequent iterative step was randomly distributed with a mean value which was dependent on the actual direction and an artifical force field. The force field modeled different axonal affinity towards the border walls of the PDMS micro channels. The directionality of a micro channel was estimated by observing how far the axons grew in the positive direction versus the negative direction.
The model was fitted to data which has been gathered from in vitro neural networks equipped with 10 different PDMS microstructures. Each microstructure has been used independently to predict the model parameters. The fitted parameters do not significantly differ from each other. Using the mean values for each parameter, the microstructures introduced by Renault et al. (1) have been used to validate the model. The predictions made by our model are similar to the results of Renault et al.
References
1) Renault, R., Durand, J. B., Viovy, J. L., & Villard, C. (2016). Asymmetric axonal edge guidance: a new paradigm for building oriented neuronal networks. Lab on a Chip, 16(12), 2188-2191
Keywords:
Axonal pathfinding,
Guidance,
PDMS,
Directionality,
random walk
Conference:
MEA Meeting 2018 | 11th International Meeting on Substrate Integrated Microelectrode Arrays, Reutlingen, Germany, 4 Jul - 6 Jul, 2018.
Presentation Type:
Poster Presentation
Topic:
Microphysiological systems
Citation:
Ihle
SJ,
Forro
C,
Weydert
S,
Weaver
S,
Thompson-Steckel
G and
Vörös
J
(2019). Axonal growth model in PDMS microstructures for in vitro neuro science applications..
Conference Abstract:
MEA Meeting 2018 | 11th International Meeting on Substrate Integrated Microelectrode Arrays.
doi: 10.3389/conf.fncel.2018.38.00006
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Received:
18 Mar 2018;
Published Online:
17 Jan 2019.
*
Correspondence:
Mr. Stephan J Ihle, ETH Zürich, Institute for Biomedical Engineering, Zurich, Zurich, 8092, Switzerland, ihle@biomed.ee.ethz.ch