Growing neural networks on gold surface plasmon resonance imaging sensors

D. Albutt, M. Alexander, Noah A. Russell
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引用次数: 2

Abstract

Surface plasmon resonance (SPR) is sensitive to changes of refractive index at a metal-dielectric interface. This technique has been applied to image networks of neurons non-invasively. The long term survival of active neural networks on SPR sensors requires optimisation of both the cell culture and the surface chemistry to ensure neurons adhere and grow uniformly.
在金表面等离子体共振成像传感器上生长神经网络
表面等离子体共振(SPR)对金属-介质界面折射率的变化非常敏感。该技术已被应用于非侵入性神经元图像网络。主动神经网络在SPR传感器上的长期存活需要优化细胞培养和表面化学,以确保神经元粘附和均匀生长。
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