Epilepsy is a chronic neurological disorder characterized by recurrent and unpredictable seizures. Electrophysiology has remained the gold standard of neural activity detection but its resolution and high susceptibility to noise and motion artifact limit its efficiency. Optical imaging techniques, including fMRI, intrinsic optical imaging, and diffuse optical imaging, have also been used to detect neural activity yet these techniques rely on the indirect measurement of changes in blood flow. A more direct optical imaging technique is optical coherence tomography (OCT), a label-free, high resolution, and minimally invasive imaging technique that can produce depth-resolved cross-sectional and 3D images. In this study, OCT was used to detect non-vascular depth-dependent optical changes in cortical tissue during 4-aminopyridine (4-AP) induced seizure onset. Calculations of localized optical attenuation coefficient (µ) allow for the assessment of depth-resolved volumetric optical changes in seizure induced cortical tissue. By utilizing the depth-dependency of the attenuation coefficient, we demonstrate the ability to locate and remove the optical effects of vasculature within the upper regions of the cortex on the attenuation calculations of cortical tissue in vivo. The results of this study reveal a significant depth-dependent decrease in attenuation coefficient of nonvascular cortical tissue both ex vivo and in vivo. Regions exhibiting decreased attenuation coefficient show significant temporal correlation to regions of increased electrical activity during seizure onset and progression. This study allows for a more thorough and biologically relevant analysis of the optical signature of seizure activity in vivo using OCT.
Danielle Ornelas, Md. Hasan, Oscar Gonzalez, Giri Krishnan, Jenny I. Szu, Timothy Myers, Koji Hirota, Maxim Bazhenov, Devin K. Binder, and Boris H. Park, "Optical changes in cortical tissue during seizure activity using optical coherence tomography (Conference Presentation)," Proc. SPIE 10051, Neural Imaging and Sensing, 1005109 (Presented at SPIE BiOS: January 30, 2017; Published: 19 April 2017); https://doi.org/10.1117/12.2253415.5371358617001.
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