Engineered self-organization of neural networks using carbon nanotube clusters

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

188 Scopus citations

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.

Original languageEnglish
Pages (from-to)611-621
Number of pages11
JournalPhysica A: Statistical Mechanics and its Applications
Volume350
Issue number2-4
DOIs
StatePublished - 15 May 2005

Funding

FundersFunder number
Iowa Science Foundation

    Keywords

    • Carbon nanotubes
    • Cell patterning
    • Nano-topography
    • Neural networks
    • Neurons
    • Self-organization

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