{"title":"Hemodynamic response function (HRF) as a novel brain marker: Applications in subjective cognitive decline (SCD)","authors":"Liang Lu, Guangfei Li, Zeyu Song, Zhao Zhang, Xiaoying Tang","doi":"10.1016/j.neuri.2022.100093","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><p>Subjective cognitive decline (SCD) is the first clinical manifestation of the Alzheimer's disease (AD) continuum. Hemodynamic response function (HRF) carries information related to brain pathology and function. The shape of the HRF can be described by three parameters: response height (RH), time-to-peak (TTP), and full-width at half-max (FWHM). We proposed and explored our two hypotheses. Hypothesis 1: HRF was pathologically related to SCD: compared with healthy controls (HC), patients with SCD show HRF aberrations. Hypothesis 2: HRF could be employed as a novel marker of brain imaging for the classification of SCD.</p></div><div><h3>Methods</h3><p>We used resting-state functional magnetic resonance imaging (fMRI) data and performed deconvolution to investigate the HRF parameters in 54 individuals with SCD and 64 HC. Statistical two-sample t tests were performed to investigate between-group differences in HRF parameters. Finally, we used logistic regression to construct a binary classification of SCD and HC.</p></div><div><h3>Results</h3><p>We found altered HRF parameters in the SCD group compared to HC. In the brain regions with altered HRF, we found that RH and FWHM decreased in the SCD group compared to HC, while TTP increased in the SCD group. From the binary logistic regression, we found that the classification accuracy of SCD and HC was 94.07%.</p></div><div><h3>Conclusion</h3><p>The study demonstrated altered HRF parameters in patients with SCD, which could be used as a novel marker of brain function for the classification of SCD.</p></div>","PeriodicalId":74295,"journal":{"name":"Neuroscience informatics","volume":"2 3","pages":"Article 100093"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772528622000553/pdfft?md5=a8e4efc380e399a3b99488a9e888cedd&pid=1-s2.0-S2772528622000553-main.pdf","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuroscience informatics","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772528622000553","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Objective
Subjective cognitive decline (SCD) is the first clinical manifestation of the Alzheimer's disease (AD) continuum. Hemodynamic response function (HRF) carries information related to brain pathology and function. The shape of the HRF can be described by three parameters: response height (RH), time-to-peak (TTP), and full-width at half-max (FWHM). We proposed and explored our two hypotheses. Hypothesis 1: HRF was pathologically related to SCD: compared with healthy controls (HC), patients with SCD show HRF aberrations. Hypothesis 2: HRF could be employed as a novel marker of brain imaging for the classification of SCD.
Methods
We used resting-state functional magnetic resonance imaging (fMRI) data and performed deconvolution to investigate the HRF parameters in 54 individuals with SCD and 64 HC. Statistical two-sample t tests were performed to investigate between-group differences in HRF parameters. Finally, we used logistic regression to construct a binary classification of SCD and HC.
Results
We found altered HRF parameters in the SCD group compared to HC. In the brain regions with altered HRF, we found that RH and FWHM decreased in the SCD group compared to HC, while TTP increased in the SCD group. From the binary logistic regression, we found that the classification accuracy of SCD and HC was 94.07%.
Conclusion
The study demonstrated altered HRF parameters in patients with SCD, which could be used as a novel marker of brain function for the classification of SCD.
Neuroscience informaticsSurgery, Radiology and Imaging, Information Systems, Neurology, Artificial Intelligence, Computer Science Applications, Signal Processing, Critical Care and Intensive Care Medicine, Health Informatics, Clinical Neurology, Pathology and Medical Technology