4.8 Article

A Materials Roadmap to Functional Neural Interface Design

期刊

ADVANCED FUNCTIONAL MATERIALS
卷 28, 期 12, 页码 -

出版社

WILEY-V C H VERLAG GMBH
DOI: 10.1002/adfm.201701269

关键词

bioelectronics; electrodes; microelectromechanical systems; photonics; sensors

资金

  1. NIH NINDS [1R01NS094396]
  2. Grainger Foundation
  3. NIH [U01-NS090526-01, R01-NS094404]
  4. NSF [1545858]
  5. NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE [R01NS094396, R01NS089688, U01NS090526, R01NS094404] Funding Source: NIH RePORTER

向作者/读者索取更多资源

Advancements in neurotechnologies for electrophysiology, neurochemical sensing, neuromodulation, and optogenetics are revolutionizing scientific understanding of the brain while enabling treatments and preventative measures for a variety of neurological disorders. The grand challenge in neural interface engineering is to seamlessly integrate the interface between neurobiology and engineered technology to record from and modulate neurons over chronic timescales. However, the biological inflammatory response to implants, neural degeneration, and long-term material stability diminishes the quality of the interface overtime. Recent advances in functional materials are aimed at engineering solutions for chronic neural interfaces, yet, the development and deployment of neural interfaces designed from novel materials have introduced new challenges that have been largely unaddressed. Many engineering efforts that solely focus on optimizing individual probe design parameters, such as softness or flexibility, downplay critical multidimensional interactions between different physical properties of the device that contribute to overall performance and biocompatibility. Moreover, the use of these new materials present substantial new difficulties that must be addressed before regulatory approval for use in human patients is achievable. In this review, the interdependence of different electrode components is highlighted to demonstrate the current material-based challenges facing the field of neural interface engineering.

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