Quantitatively interpreting fMRI signal

Nanyin Zhang, Xiao Hong Zhu, Zhongming Liu, Bin He, Wei Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Quantitative relationships among the neurophysiologic processes that link neuronal activity to hemodynamic change is extremely important to interpret the functional magnetic resonance imaging (fMRI) signals. In this article the neurovascular coupling relationship was noninvasively studied in the human visual cortex. Graded neuronal/hemodynamic suppression conditions were generated using a paired-stimulus paradigm. Visual evoked potential (VEP) was measured to quantify neuronal activity. Hemodynamic activities were measured and quantified by perfusion changes. All quantification was normalized to the same activation condition using a single-stimulus paradigm within each experimental session. The results reveal: (i) there is a tight neurovascular coupling at graded neuronal suppression conditions; (ii) the neurovascular coupling relationship contains a subtle, but significant, nonlinear component; (iii) the linear model, nevertheless, is still a good approximation reflecting the neurovascular coupling relationship.

Original languageEnglish (US)
Title of host publicationProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
PublisherIEEE Computer Society
Pages4415-4418
Number of pages4
ISBN (Print)9781424418152
StatePublished - 2008
Event30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - Vancouver, BC, Canada
Duration: Aug 20 2008Aug 25 2008

Other

Other30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
CountryCanada
CityVancouver, BC
Period8/20/088/25/08

Fingerprint

Hemodynamics
Magnetic Resonance Imaging
Bioelectric potentials
Visual Evoked Potentials
Visual Cortex
Chemical activation
Linear Models
Perfusion
Neurovascular Coupling

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

Zhang, N., Zhu, X. H., Liu, Z., He, B., & Chen, W. (2008). Quantitatively interpreting fMRI signal. In Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 (pp. 4415-4418). [4650190] IEEE Computer Society.
Zhang, Nanyin ; Zhu, Xiao Hong ; Liu, Zhongming ; He, Bin ; Chen, Wei. / Quantitatively interpreting fMRI signal. Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. IEEE Computer Society, 2008. pp. 4415-4418
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Zhang, N, Zhu, XH, Liu, Z, He, B & Chen, W 2008, Quantitatively interpreting fMRI signal. in Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08., 4650190, IEEE Computer Society, pp. 4415-4418, 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08, Vancouver, BC, Canada, 8/20/08.

Quantitatively interpreting fMRI signal. / Zhang, Nanyin; Zhu, Xiao Hong; Liu, Zhongming; He, Bin; Chen, Wei.

Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. IEEE Computer Society, 2008. p. 4415-4418 4650190.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - Quantitative relationships among the neurophysiologic processes that link neuronal activity to hemodynamic change is extremely important to interpret the functional magnetic resonance imaging (fMRI) signals. In this article the neurovascular coupling relationship was noninvasively studied in the human visual cortex. Graded neuronal/hemodynamic suppression conditions were generated using a paired-stimulus paradigm. Visual evoked potential (VEP) was measured to quantify neuronal activity. Hemodynamic activities were measured and quantified by perfusion changes. All quantification was normalized to the same activation condition using a single-stimulus paradigm within each experimental session. The results reveal: (i) there is a tight neurovascular coupling at graded neuronal suppression conditions; (ii) the neurovascular coupling relationship contains a subtle, but significant, nonlinear component; (iii) the linear model, nevertheless, is still a good approximation reflecting the neurovascular coupling relationship.

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Zhang N, Zhu XH, Liu Z, He B, Chen W. Quantitatively interpreting fMRI signal. In Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. IEEE Computer Society. 2008. p. 4415-4418. 4650190