{"title":"The Relationship Between M in \"Calibrated fMRI\" and the Physiologic Modulators of fMRI.","authors":"Hanzhang Lu, Joanna Hutchison, Feng Xu, Bart Rypma","doi":"10.2174/1874440001105010112","DOIUrl":null,"url":null,"abstract":"<p><p>The \"calibrated fMRI\" technique requires a hypercapnia calibration experiment in order to estimate the factor \"M\". It is desirable to be able to obtain the M value without the need of a gas challenge calibration. According to the analytical expression of M, it is a function of several baseline physiologic parameters, such as baseline venous oxygenation and CBF, both of which have recently been shown to be significant modulators of fMRI signal. Here we studied the relationship among hypercapnia-calibrated M, baseline venous oxygenation and CBF, and assessed the possibility of estimating M from the baseline physiologic parameters. It was found that baseline venous oxygenation and CBF are highly correlated (R(2)=0.77, P<0.0001) across subjects. However, the hypercapnia-calibrated M was not correlated with baseline venous oxygenation or CBF. The hypercapnia-calibrated M was not correlated with an estimation of M based on analytical expression either. The lack of correlation may be explained by the counteracting effect of venous oxygenation and CBF on the M factor, such that the actual M value of an individual may be mostly dependent on other parameters such as hematocrit. Potential biases in hypercapnia-based M estimation were also discussed in the context of possible reduction of CMRO(2) during hypercapnia.</p>","PeriodicalId":37431,"journal":{"name":"Open Neuroimaging Journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3263507/pdf/","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Neuroimaging Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1874440001105010112","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2011/11/4 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 6
Abstract
The "calibrated fMRI" technique requires a hypercapnia calibration experiment in order to estimate the factor "M". It is desirable to be able to obtain the M value without the need of a gas challenge calibration. According to the analytical expression of M, it is a function of several baseline physiologic parameters, such as baseline venous oxygenation and CBF, both of which have recently been shown to be significant modulators of fMRI signal. Here we studied the relationship among hypercapnia-calibrated M, baseline venous oxygenation and CBF, and assessed the possibility of estimating M from the baseline physiologic parameters. It was found that baseline venous oxygenation and CBF are highly correlated (R(2)=0.77, P<0.0001) across subjects. However, the hypercapnia-calibrated M was not correlated with baseline venous oxygenation or CBF. The hypercapnia-calibrated M was not correlated with an estimation of M based on analytical expression either. The lack of correlation may be explained by the counteracting effect of venous oxygenation and CBF on the M factor, such that the actual M value of an individual may be mostly dependent on other parameters such as hematocrit. Potential biases in hypercapnia-based M estimation were also discussed in the context of possible reduction of CMRO(2) during hypercapnia.
“校准fMRI”技术需要高碳酸血症校准实验,以估计因子“M”。希望能够在不需要气体挑战校准的情况下获得M值。根据M的解析表达,它是几个基线生理参数的函数,如基线静脉氧合和CBF,这两个参数最近被证明是fMRI信号的重要调节剂。在这里,我们研究了高血氧校准M、基线静脉氧合和CBF之间的关系,并评估了从基线生理参数估计M的可能性。结果发现,基线静脉氧合与CBF高度相关(R(2)=0.77, P
期刊介绍:
The Open Neuroimaging Journal is an Open Access online journal, which publishes research articles, reviews/mini-reviews, and letters in all important areas of brain function, structure and organization including neuroimaging, neuroradiology, analysis methods, functional MRI acquisition and physics, brain mapping, macroscopic level of brain organization, computational modeling and analysis, structure-function and brain-behavior relationships, anatomy and physiology, psychiatric diseases and disorders of the nervous system, use of imaging to the understanding of brain pathology and brain abnormalities, cognition and aging, social neuroscience, sensorimotor processing, communication and learning.