3 March 2006 Combine temporal clustering analysis with least square estimation to determine the dynamic pattern of cortical spreading depression
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Abstract
A series of images are acquired by optical intrinsic signal imaging (OISI) at 550 nm during cortical spreading depression (CSD) in rats. Temporal clustering analysis (TCA), which is an exploratory data-driven technique that has been proposed for the analysis of fMRI data and laser speckle contrast images, is applied to tract the extreme response during CSD. The minimum of optical intrinsic signals (OIS) during CSD in each pixel, corresponding to the maximum change of regional cerebral blood volume (CBV), is determined by TCA. Interestingly, the spatial pattern of the maximum activation shows the ongoing expanding circle. In order to describe the circular pattern quantitatively, we present the least square estimation (LSE) to detect the three parameters of the expanding circles (radius R, center coordinates (a, b)) at each time point (i.e. in each frame). The evaluated mean centers of the circles (1.50±0.06 mm, 2.62±0.03 mm) were tightly correlated with the pinprick site (1.4±0.2 mm, 2.5±0.2 mm). According to the varying values of the radiuses at different time point, we calculate the propagated speed of the CSD at 3.96 mm/min. The results substantiate the CSD spreads like a wave from the induced site to the periphery at 2~5 mm/min over the cortex. So, the combination of TCA and LSE enables the image analysis of OISI more automatic and effective.
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Shangbin Chen, Shangbin Chen, Pengcheng Li, Pengcheng Li, Hui Gong, Hui Gong, Shaoqun Zeng, Shaoqun Zeng, Qingming Luo, Qingming Luo, } "Combine temporal clustering analysis with least square estimation to determine the dynamic pattern of cortical spreading depression", Proc. SPIE 6085, Complex Dynamics and Fluctuations in Biomedical Photonics III, 60850D (3 March 2006); doi: 10.1117/12.644125; https://doi.org/10.1117/12.644125
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