Estimation of the hemodynamic response of fMRI data using RBF neural network

IEEE Transactions on Biomedical Engineering

Volumn 54, Issue 8, 2007, Pages 1371-1381

  Luo, Huaien ^a   Puthusserypady, Sadasivan ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Event related design; Functional magnetic resonance imaging (fMRI); Hemodynamic response (HDR); Neural network; Radial basis functions (RBF); Volterra kernels

Indexed keywords

EVENT-RELATED DESIGN; FUNCTIONAL MAGNETIC RESONANCE IMAGING (FMRI); HEMODYNAMIC RESPONSE (HDR); VOLTERRA KERNELS;

BRAIN; DATA REDUCTION; HEMODYNAMICS; MAGNETIC RESONANCE IMAGING; OXYGENATION; RADIAL BASIS FUNCTION NETWORKS;

MEDICAL IMAGING;

ARTICLE; BLOOD OXYGENATION; BRAIN FUNCTION; BRAIN REGION; DATA ANALYSIS; EVENT RELATED POTENTIAL; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HEMODYNAMICS; HUMAN; IMAGING SYSTEM; MATHEMATICAL MODEL; NERVE CELL NETWORK; NEUROIMAGING; RADIAL BASED FUNCTION; SIMULATION;

ARTIFICIAL INTELLIGENCE; BLOOD FLOW VELOCITY; BRAIN; BRAIN MAPPING; CEREBROVASCULAR CIRCULATION; COMPUTER SIMULATION; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MODELS, NEUROLOGICAL; NEURAL NETWORKS (COMPUTER); OXYGEN;

EID: 34447500344     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/TBME.2007.900795     Document Type: Article

References (23)

1. S. Ogawa, T. Lee, A. Nayak, and P. Glynn, "Oxygenation-sensitive contrast in magnetic resonance image of rodent brain of high magnetic fields," Magn. Reson, Med., vol. 14, pp. 68-78, 1990.
2. P. Jezzard, P. Matthews, and S. Smith, Eds., Functional Magnetic Resonance Imaging: An Introduction to Methods. Oxford, U.K.: Oxford Univ. Press, 2001.
3. S. A. Huettel, A. W. Song, and G. McCarthy, Functional Magnetic Resonance Imaging. Sunderland, MA: Sinauer, 2004.
4. R. B. Buxton, Introduction to Functional Magnetic Resonance Imaging: Principles and Techniques. Cambridge, MA: Cambridge Univ. Press, 2002.
5. K. J. Friston, A. P. Holmes, K. J. Worsley, J. P. Poline, C. D. Frith, and R. S. J. Frackowiak, "Statistical parametric maps in functional imaging: A general linear approach," Hum. Brain Mapp., vol. 2, pp. 189-210, 1995.
6. G. M. Boynton, S. A. Engel, G. H. Glover, and D. J. Heeger, "Linear systems analysis of functional magnetic resonance imaging in human V1," J. Neurosci., vol. 16, pp. 4207-4221, 1996.
7. D. A. Handwerker, J. M. Ollinger, and M. D'Esposito, "Variation of BOLD hemodynamic responses across subjects and brain regions and their effects on statistical analyses," NeuroImage, vol. 21, pp. 1639-1651, 2004.
8. R. Frackowiak, K. J. Friston, C. Frith, R. Dolan, C. Price, S. Zeki, J. Ashburner, and W. Penny, Eds., Human Brain Function, 2nd ed. New York: Academic, 2003.
9. R. M. Birn, Z. S. Saad, and P. A. Bandettini, "Spatial heterogeneity of the nonlinear dynamics in the fMRI BOLD response," NeuroImage, vol. 14, pp. 817-826, 2001.
10. A. Laird, B. Rogers, and M. Meyerand, "Investigating the nonlinearity of fMRI activation data," in Proc. 2nd Joint EMBS/BMES Conf., 2002, pp. 23-26.
11. K. L. Miller, W. M. Luh, T. T. Liu, A. Martinez, T. Obata, E. C. Wong, L. R. Frank, and R. B. Buxton, "Nonlinear temporal dynamics of the cerebral blood flow response," Hum. Brain Mapp., vol. 13, pp. 1-12, 2001.
12. T. D. Wager, A. Vazquez, L. Hernandez, and D. C. Noll, "Accounting for nonlinear BOLD effects in fMRI: Parameter estimates and a model for prediction in rapid event-related studies," NeuroImage, vol. 25, pp. 206-218, 2005.
13. K. J. Friston, O. Josephs, G. Rees, and R. Turner, "Nonlinear event-related responses in fMRI," Magn. Reson, Med., vol. 39, pp. 41-52, 1998.
14. R. Buxton, E. Wong, and L. Frank, "Dynamics of blood flow and oxygenation changes during brain activation: The Balloon model," Magn. Reson. Med., vol. 39, pp. 855-864, 1998.
15. K. J. Friston, A. Mechelli, R. Turner, and C. J. Price, "Nonlinear responses in fMRI: The Balloon model, Volterra kernels, and other hemodynamics," NeuroImage, vol. 12, pp. 466-477, 2000.
16. R. Buxton, K. Uludag, D. J. Dubowitz, and T. T. Liu, "Modeling the hemodynamic response to brain activation," NeuroImage, vol. 23, pp. S220-S233, 2004.
17. S. Haykin, Neural Networks: A Comprehensive Foundation, 2nd ed. Upper Saddle River, NJ: Prentice-Hall, 1999.
18. M. Misaki and S. Miyauchi, "Application of artificial neural network to fMRI regression analysis," NeuroImage, vol. 29, pp. 396-408, 2006.
19. H. Luo and S. Puthusserypady, "NARX neural networks for dynamical modelling of fMRI data," presented at the IEEE World Congr. Computational Intelligence, Vancouver, BC, Canada, Jul. 16-21, 2006.
20. E. Rank, "Application of Bayesian trained RBF networks to nonlinear time-series modeling," Signal Process., vol. 83, pp. 1393-1410, 2003.
21. P. L. Purdon and R.Weisskoff, "Effect of temporal autocorrelation due to physiological noise and stimulus paradigm on voxel-level false-positive rates in fMRI," Hum. Brain Mapp., vol. 6, pp. 239-249, 1998.
22. J. Tanabe, D. Miller, J. Tregellas, R. Freedman, and F. G. Meyer, "Comparison of detrending methods for optimal fMRI preprocessing," NeuroImage, vol. 15, pp. 902-907, 2002.
23. I. Klein, A. Paradis, J. Poline, S. Kosslyn, and D. Bihan, "Transient activity in the human calcarine cortex during visual-mental imagery: An event-related fMRI study," J. Cogn.Neurosci., vol. 12, no. 2, pp. 15-23, 2000.