Archives of Neuroscience

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Hemodynamic Response Function Modeling to Determine the Areas with High Blood Supply in Block-Design fMRI Experiments

Seyedeh Mahboobe Seyed Abbasi 1 , Mohammad Ali Oghabian 2 , Seyed Salman Zakariaee 3 , * and Abbas Rahimiforoushani 1 , **
Authors Information
1 Department of Epidemiology and Biostatistics, Faculty of Public Health, Tehran University of Medical Sciences, Tehran, Iran
2 Department of Medical Physics and Biomedical Engineering, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
3 Department of Medical Physics, Faculty of Paramedical Sciences, Ilam University of Medical Sciences, Ilam, Iran
Corresponding Authors:
Article information
  • Archives of Neuroscience: 6 (Special Issue); e82585
  • Published Online: March 18, 2019
  • Article Type: Research Article
  • Received: July 24, 2018
  • Revised: December 2, 2018
  • Accepted: February 27, 2019
  • DOI: 10.5812/ans.82585

To Cite: Seyed Abbasi S M , Oghabian M A, Zakariaee S S, Rahimiforoushani A . Hemodynamic Response Function Modeling to Determine the Areas with High Blood Supply in Block-Design fMRI Experiments, Arch Neurosci. Online ahead of Print ; 6(Special Issue):e82585. doi: 10.5812/ans.82585.

Copyright © 2019, Archives of Neuroscience. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License ( which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.
1. Background
2. Objectives
3. Methods
4. Results
5. Discussion
  • 1. Aguirre GK, Zarahn E, D'Esposito M. The variability of human, BOLD hemodynamic responses. Neuroimage. 1998;8(4):360-9. doi: 10.1006/nimg.1998.0369. [PubMed: 9811554].
  • 2. Logothetis NK, Pauls J, Augath M, Trinath T, Oeltermann A. Neurophysiological investigation of the basis of the fMRI signal. Nature. 2001;412(6843):150-7. doi: 10.1038/35084005. [PubMed: 11449264].
  • 3. Bellgowan PS, Saad ZS, Bandettini PA. Understanding neural system dynamics through task modulation and measurement of functional MRI amplitude, latency, and width. Proc Natl Acad Sci U S A. 2003;100(3):1415-9. doi: 10.1073/pnas.0337747100. [PubMed: 12552093]. [PubMed Central: PMC298787].
  • 4. Handwerker DA, Gonzalez-Castillo J, D'Esposito M, Bandettini PA. The continuing challenge of understanding and modeling hemodynamic variation in fMRI. Neuroimage. 2012;62(2):1017-23. doi: 10.1016/j.neuroimage.2012.02.015. [PubMed: 22366081]. [PubMed Central: PMC4180210].
  • 5. Lindquist MA, Meng Loh J, Atlas LY, Wager TD. Modeling the hemodynamic response function in fMRI: efficiency, bias and mis-modeling. Neuroimage. 2009;45(1 Suppl):S187-98. doi: 10.1016/j.neuroimage.2008.10.065. [PubMed: 19084070]. [PubMed Central: PMC3318970].
  • 6. Muthukumaraswamy SD, Edden RA, Jones DK, Swettenham JB, Singh KD. Resting GABA concentration predicts peak gamma frequency and fMRI amplitude in response to visual stimulation in humans. Proc Natl Acad Sci U S A. 2009;106(20):8356-61. doi: 10.1073/pnas.0900728106. [PubMed: 19416820]. [PubMed Central: PMC2688873].
  • 7. D'Esposito M, Deouell LY, Gazzaley A. Alterations in the BOLD fMRI signal with ageing and disease: A challenge for neuroimaging. Nat Rev Neurosci. 2003;4(11):863-72. doi: 10.1038/nrn1246. [PubMed: 14595398].
  • 8. Iadecola C. Neurovascular regulation in the normal brain and in Alzheimer's disease. Nat Rev Neurosci. 2004;5(5):347-60. doi: 10.1038/nrn1387. [PubMed: 15100718].
  • 9. Maus B, van Breukelen GJ, Goebel R, Berger MP. Optimal design for nonlinear estimation of the hemodynamic response function. Hum Brain Mapp. 2012;33(6):1253-67. doi: 10.1002/hbm.21289. [PubMed: 21567658].
  • 10. Worsley KJ, Friston KJ. Analysis of fMRI time-series revisited--again. Neuroimage. 1995;2(3):173-81. doi: 10.1006/nimg.1995.1023. [PubMed: 9343600].
  • 11. Lindquist MA, Waugh C, Wager TD. Modeling state-related fMRI activity using change-point theory. Neuroimage. 2007;35(3):1125-41. doi: 10.1016/j.neuroimage.2007.01.004. [PubMed: 17360198].
  • 12. Friston KJ. Imaging neuroscience: Principles or maps? Proc Natl Acad Sci U S A. 1998;95(3):796-802. doi: 10.1073/pnas.95.3.796. [PubMed: 9448243]. [PubMed Central: PMC33800].
  • 13. Friston KJ, Glaser DE, Henson RN, Kiebel S, Phillips C, Ashburner J. Classical and Bayesian inference in neuroimaging: Applications. Neuroimage. 2002;16(2):484-512. doi: 10.1006/nimg.2002.1091. [PubMed: 12030833].
  • 14. Glover GH. Deconvolution of impulse response in event-related BOLD fMRI. Neuroimage. 1999;9(4):416-29. doi: 10.1006/nimg.1998.0419. [PubMed: 10191170].
  • 15. Goutte C, Nielsen FA, Hansen LK. Modeling the haemodynamic response in fMRI using smooth FIR filters. IEEE Trans Med Imaging. 2000;19(12):1188-201. doi: 10.1109/42.897811. [PubMed: 11212367].
  • 16. Shan ZY, Wright MJ, Thompson PM, McMahon KL, Blokland GG, de Zubicaray GI, et al. Modeling of the hemodynamic responses in block design fMRI studies. J Cereb Blood Flow Metab. 2014;34(2):316-24. doi: 10.1038/jcbfm.2013.200. [PubMed: 24252847]. [PubMed Central: PMC3915209].

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