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Progress Towards Detecting Neural Activity in Optical Coherence Tomography Using Phase

Abstract

Optical Coherence Tomography (OCT) is non-invasive, real time optical imaging method based on low coherence interferometry with high resolution. It is capable of imaging microstructure by measuring the light backscattered from the sample. Under the AGI grant, I have built a Swept Source OCT (SS-OCT) / phase resolved OCT to detect the nanometer(nm) scale changes in the cell membrane that occur during membrane depolarization and Ion influx. This type of small changes can be seen using phase. Intensity is robust but is less sensitive to the small-scale changes whereas phase is highly sensitive. The noise level for phase difference quantification depends on the lateral motion, triggering of the wavelength mismatch and signal to noise ratio (SNR). To detect the nm scale changes phase noise should be minimum. The phase noise is inversely proportional to SNR. The SNR of the system should be maximum. The SS-OCT has swept source with sweep rate 100 kHz and it is not phase stable. It needs post processing algorithm to match the triggering wavelength to stabilize the phase. I wrote the code in GPU to reduce the computation time for post processing algorithm. Due to a few setbacks related to moving the system to a collaborating lab, the biological portion of my thesis work, trying to find the neural activity in the walking leg nerve of the Lobster using phase, was done with a spectral domain OCT (SD-OCT). To see any action potential change in the nerve I realigned the SD-OCT system with center wavelength to increase the SNR of the system and the sample arm with the nerve chamber (3D printed) to stimulate the nerve at one end and take the OCT image at the other end to see the action potential.

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