Engineered self-organization of neural networks using carbon nanotube clusters

Tamir Gabay, Eyal Jakobs, Eshel Ben-Jacob and Yael Hanein

Physica A: Statistical Mechanics and its Applications, 2005, vol. 350, issue 2, 611-621

Abstract: A novel approach was developed to form engineered, electrically viable, neuronal networks, consisting of ganglion-like clusters of neurons. In the present method, the clusters are formed as the cells migrate on low affinity substrate towards high affinity, lithographically defined carbon nanotube templates on which they adhere and assemble. Subsequently, the gangliated neurons send neurites to form interconnected networks with pre-designed geometry and graph connectivity. This process is distinct from previously reported formation of clusterized neural networks in which a network of linked neurons collapses via neuronal migration along the inter-neuron links. The template preparation method is based on photo-lithography, micro-contact printing and carbon nanotube chemical vapor deposition techniques. The present work provides a new approach to form complex, engineered, interconnected neuronal network with pre-designed geometry via engineering the self-assembly process of neurons.

Keywords: Neurons; Neural networks; Carbon nanotubes; Self-organization; Nano-topography; Cell patterning (search for similar items in EconPapers)
Date: 2005
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:350:y:2005:i:2:p:611-621

DOI: 10.1016/j.physa.2004.11.007

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