3 years ago

Nanostructured Materials for Neural Electrical Interfaces

Nanostructured Materials for Neural Electrical Interfaces
Jessamyn A. Fairfield
Neural electrical interfaces that accurately detect signals from active neurons with minimal signal loss or biological damage are critical to advancing our understanding of neurophysiology and neural coding. Significant physics and engineering issues exist in creating low-impedance interfaces that can efficiently and reliably inject charge from tissue to sensor, as well as biological issues in minimizing immune response, unwanted chemical reactions, and cell damage. The incorporation of nanostructured materials in neural electrodes provides a structural solution by matching the feature size and mechanical properties of neural tissue while improving electrical contact and charge transfer parameters. Indeed, nature contains many examples of nanoscale and layered structures, suggesting engineering approaches that can be mimicked to better interface with the brain. The potential toxicity of nanoscale objects can be controlled by selecting appropriate materials, and the nanomaterials can either be used as coatings for traditional neural electrodes or as electrode materials themselves, for incorporation into electrode arrays with multiplexed readouts as brain–machine interfaces. This review provides an overview of the scientific challenges in neural electrodes, and explores recent advances and future directions in the application of metallic, semiconducting, carbon-based, and polymer nanomaterials to electrodes designed to interface with the brain. Nanostructured materials are uniquely capable of addressing persistent challenges in state-of-the-art neural electrical interfaces. This review explores how nanomaterials based on metals, semiconductors, carbon, and polymers are ideal for creating low-impedance, low-noise, biocompatible electrodes for sensing and control of neural function.

Publisher URL: http://onlinelibrary.wiley.com/resolve/doi

DOI: 10.1002/adfm.201701145

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