Nanofabricating neural networks: Strategies, advances, and challenges

  • Luttge R
2Citations
Citations of this article
13Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Nanofabrication can help us to emulate natural intelligence. Forward-engineering brain gained enormous momentum but still falls short in human neurodegenerative disease modeling. Here, organ-on-chip (OoC) implementation of tissue culture concepts in microfluidic formats already progressed with the identification of our knowledge gap in toxicology and drug metabolism studies. We believe that the self-organization of stem cells and chip technology is a key to advance such complex in vitro tissue models, including models of the human nervous system as envisaged in this review. However, current cultured networks of neurons show limited resemblance with the biological functions in the real nervous system or brain tissues. To take full advantage of scaling in the engineering domain of electron-, ion-, and photon beam technology and nanofabrication methods, more research is needed to meet the requirements of this specific field of chip technology applications. So far, surface topographies, microfluidics, and sensor and actuator integration concepts have all contributed to the patterning and control of neural network formation processes in vitro. However, when probing the state of the art for this type of miniaturized three-dimensional tissue models in PubMed, it was realized that there is very little systematic cross-disciplinary research with biomaterials originally formed for tissue engineering purposes translated to on-chip solutions for in vitro modeling. Therefore, this review contributes to the formulation of a sound design concept based on the understanding of the existing knowledge and the technical challenges toward finding better treatments and potential cures for devastating neurodegenerative diseases, like Parkinson's disease. Subsequently, an integration strategy based on a modular approach is proposed for nervous system-on-chip (NoC) models that can yield efficient and informative optical and electronic NoC readouts in validating and optimizing these conceptual choices in the innovative process of a fast growing and exciting new OoC industry.

Cite

CITATION STYLE

APA

Luttge, R. (2022). Nanofabricating neural networks: Strategies, advances, and challenges. Journal of Vacuum Science & Technology B, 40(2). https://doi.org/10.1116/6.0001649

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free