Peng Hu, Bochao Niu, Hang Yang, Yang Xia, Donna Chen, Chun Meng, Ke Chen, Bharat Biswal
{"title":"利用激光散斑对比成像检测功能激活的分析和可视化方法","authors":"Peng Hu, Bochao Niu, Hang Yang, Yang Xia, Donna Chen, Chun Meng, Ke Chen, Bharat Biswal","doi":"10.1111/micc.12783","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Previous studies have used regional cerebral blood flow (CBF) hemodynamic response to measure brain activities. In this work, we use a laser speckle contrast imaging (LSCI) apparatus to sample the CBF activation in somatosensory cortex (S1BF) with repetitive whisker stimulation. Traditionally, the CBF activations were processed by depicting the change percentage above baseline; however, it is not clear how different methods influence the detection of activations.</p>\n </section>\n \n <section>\n \n <h3> Aims</h3>\n \n <p>Thus, in this work we investigate the influence of different methods to detect activations in LSCI.</p>\n </section>\n \n <section>\n \n <h3> Materials & Methods</h3>\n \n <p>First, principal component analysis (PCA) was performed to denoise the CBF signal. As the signal of the first principal component (PC1) showed the highest correlation with the S1BF CBF response curve, PC1 was used in the subsequent analyses. Then, we used fast Fourier transform (FFT) to evaluate the frequency properties of the LSCI images and the activation map was generated based on the amplitude of the central frequency. Furthermore, Pearson's correlation coefficient (C–C) analysis and a general linear model (GLM) were performed to estimate the S1BF activation based on the time series of PC1.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>We found that GLM performed better in identifying activation than C–C. Additionally, the activation maps generated by FFT were similar to those obtained by GLM. Particularly, the superficial vein and arterial vessels separated the activation region as segmented activated areas, and the regions with unresolved vessels showed a common activation for whisker stimulation.</p>\n </section>\n \n <section>\n \n <h3> Discussion and Conclusion</h3>\n \n <p>Our research analyzed the extent to which PCA can extract meaningful information from the signal and we compared the performance for detecting brain functional activation between different methods that rely on LSCI. This can be used as a reference for LSCI researchers on choosing the best method to estimate brain activation.</p>\n </section>\n </div>","PeriodicalId":18459,"journal":{"name":"Microcirculation","volume":"29 6-7","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Analysis and visualization methods for detecting functional activation using laser speckle contrast imaging\",\"authors\":\"Peng Hu, Bochao Niu, Hang Yang, Yang Xia, Donna Chen, Chun Meng, Ke Chen, Bharat Biswal\",\"doi\":\"10.1111/micc.12783\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Previous studies have used regional cerebral blood flow (CBF) hemodynamic response to measure brain activities. In this work, we use a laser speckle contrast imaging (LSCI) apparatus to sample the CBF activation in somatosensory cortex (S1BF) with repetitive whisker stimulation. Traditionally, the CBF activations were processed by depicting the change percentage above baseline; however, it is not clear how different methods influence the detection of activations.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Aims</h3>\\n \\n <p>Thus, in this work we investigate the influence of different methods to detect activations in LSCI.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Materials & Methods</h3>\\n \\n <p>First, principal component analysis (PCA) was performed to denoise the CBF signal. As the signal of the first principal component (PC1) showed the highest correlation with the S1BF CBF response curve, PC1 was used in the subsequent analyses. Then, we used fast Fourier transform (FFT) to evaluate the frequency properties of the LSCI images and the activation map was generated based on the amplitude of the central frequency. Furthermore, Pearson's correlation coefficient (C–C) analysis and a general linear model (GLM) were performed to estimate the S1BF activation based on the time series of PC1.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>We found that GLM performed better in identifying activation than C–C. Additionally, the activation maps generated by FFT were similar to those obtained by GLM. Particularly, the superficial vein and arterial vessels separated the activation region as segmented activated areas, and the regions with unresolved vessels showed a common activation for whisker stimulation.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Discussion and Conclusion</h3>\\n \\n <p>Our research analyzed the extent to which PCA can extract meaningful information from the signal and we compared the performance for detecting brain functional activation between different methods that rely on LSCI. This can be used as a reference for LSCI researchers on choosing the best method to estimate brain activation.</p>\\n </section>\\n </div>\",\"PeriodicalId\":18459,\"journal\":{\"name\":\"Microcirculation\",\"volume\":\"29 6-7\",\"pages\":\"\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2022-09-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Microcirculation\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/micc.12783\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"HEMATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Microcirculation","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/micc.12783","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEMATOLOGY","Score":null,"Total":0}
Analysis and visualization methods for detecting functional activation using laser speckle contrast imaging
Background
Previous studies have used regional cerebral blood flow (CBF) hemodynamic response to measure brain activities. In this work, we use a laser speckle contrast imaging (LSCI) apparatus to sample the CBF activation in somatosensory cortex (S1BF) with repetitive whisker stimulation. Traditionally, the CBF activations were processed by depicting the change percentage above baseline; however, it is not clear how different methods influence the detection of activations.
Aims
Thus, in this work we investigate the influence of different methods to detect activations in LSCI.
Materials & Methods
First, principal component analysis (PCA) was performed to denoise the CBF signal. As the signal of the first principal component (PC1) showed the highest correlation with the S1BF CBF response curve, PC1 was used in the subsequent analyses. Then, we used fast Fourier transform (FFT) to evaluate the frequency properties of the LSCI images and the activation map was generated based on the amplitude of the central frequency. Furthermore, Pearson's correlation coefficient (C–C) analysis and a general linear model (GLM) were performed to estimate the S1BF activation based on the time series of PC1.
Results
We found that GLM performed better in identifying activation than C–C. Additionally, the activation maps generated by FFT were similar to those obtained by GLM. Particularly, the superficial vein and arterial vessels separated the activation region as segmented activated areas, and the regions with unresolved vessels showed a common activation for whisker stimulation.
Discussion and Conclusion
Our research analyzed the extent to which PCA can extract meaningful information from the signal and we compared the performance for detecting brain functional activation between different methods that rely on LSCI. This can be used as a reference for LSCI researchers on choosing the best method to estimate brain activation.
期刊介绍：
The journal features original contributions that are the result of investigations contributing significant new information relating to the vascular and lymphatic microcirculation addressed at the intact animal, organ, cellular, or molecular level. Papers describe applications of the methods of physiology, biophysics, bioengineering, genetics, cell biology, biochemistry, and molecular biology to problems in microcirculation.
Microcirculation also publishes state-of-the-art reviews that address frontier areas or new advances in technology in the fields of microcirculatory disease and function. Specific areas of interest include: Angiogenesis, growth and remodeling; Transport and exchange of gasses and solutes; Rheology and biorheology; Endothelial cell biology and metabolism; Interactions between endothelium, smooth muscle, parenchymal cells, leukocytes and platelets; Regulation of vasomotor tone; and Microvascular structures, imaging and morphometry. Papers also describe innovations in experimental techniques and instrumentation for studying all aspects of microcirculatory structure and function.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
