在金表面等离子体共振成像传感器上生长神经网络

2011 Functional Optical Imaging Pub Date : 2011-12-01 DOI:10.1109/FOI.2011.6154846

D. Albutt, M. Alexander, Noah A. Russell

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引用次数: 2

摘要

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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Growing neural networks on gold surface plasmon resonance imaging sensors

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.

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2011 Functional Optical Imaging

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