Modeling the hemodynamic response in single-trial functional MRI experiments

Magnetic Resonance in Medicine

Volumn 42, Issue 4, 1999, Pages 787-797

  Kruggel, Frithjof ^a   Von Cramon, D Yves ^a  

^a MAX PLANCK INSTITUTE FOR HUMAN COGNITIVE AND BRAIN SCIENCES   (Germany)

Author keywords

FMRI; Functional data analysis; Hemodynamic response; Nonlinear regression; Ornstein Uhlenbeck process; Single trial design

Indexed keywords

IMAGE SEGMENTATION;

FMRI; FUNCTIONAL DATA ANALYSIS; HEMODYNAMIC RESPONSE; NON-LINEAR REGRESSION; ORNSTEIN-UHLENBECK PROCESS; SINGLE TRIAL;

HEMODYNAMICS;

HEMOGLOBIN;

ARTICLE; BLOOD VESSEL REACTIVITY; COGNITION; DATA ANALYSIS; HEMODYNAMICS; HYPOTHESIS; NUCLEAR MAGNETIC RESONANCE IMAGING; OXYGEN CONSUMPTION; OXYGENATION; REGRESSION ANALYSIS; STATISTICAL MODEL;

EID: 0032869655     PISSN: 07403194     EISSN: None     Source Type: Journal    
DOI: 10.1002/(SICI)1522-2594(199910)42:4<787::AID-MRM22>3.0.CO;2-V     Document Type: Article

References (32)

1. Belliveau JW, Kennedy DN, McKinstry RC, Buchbinder BR, Weisskoff RM, Cohen MS, Vevea JM, Brady TJ, Rosen BR. Functional mapping of the human visual cortex by magnetic resonance imaging. Science 1991;254:716-719.
2. Kwong KK, Belliveau JW, Chesler DA, Goldberg IE, Kennedy DN, Weisskoff RM, Poncelet BP, Hoppel BE, Cohen MS, Turner R, Cheng H, Brady TJ, Rosen BR. Dynamic magnetic resonance imaging of the human brain activity during sensory stimulation. Proc Natl Acad Sci USA 1992;89:5675-5679.
3. Ogawa S, Tank DW, Menon R, Ellermann JM, Kim SG, Merkle H, Ugurbil K. Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc Natl Acad Sci USA 1992;89:5951-5955.
4. Ernst T, Henning J. Observation of fast response in functional MR. Magn Reson Med 1994;32:146-149.
5. Menon RS, Ogawa S, Tank DW, Ugurbil K. 4 Tesla gradient recalled echo characteristics of photic stimulation-induced signal changes in the human primary visual cortex. Magn Reson Med 1993;30:380-386.
6. Vilringer A, Dirnagl U. Coupling of brain activity and cerebral blood flow: basis of functional neuroimaging. Cereb Brain Metab Rev 1995;7: 240-276.
7. Luknowsky DC, Thomas CG, Gati JS, Menon RS. Millisecond sequencing of neural activation in simple tasks determined by the BOLD fMRI neurovascular response. Neuroimage 1998;6:S280.
8. Richter W, Tegeler C, Georgopoulos A, Ugurbil K, Kim SG. Time-resolved fMRI of motor area activity during mental rotation. Neuroimage 1998;6:858.
9. Zarahn E, Aguirre G, D'Esposito M. A trial-based experimental design for fMRI. Neuroimage 1997;6:122-138.
10. Josephs O, Turner R, Friston K. Event-related fMRI. Hum Brain Mapp 1997;5:243-248.
11. Richter W, Ugurbil K, Georgopoulos A, Kim SG. Time-resolved fMRI of mental rotation. Neuroreport 1997;8:3697-3702.
12. Kruggel F, Descombes X, von Cramon DY. Preprocessing of fMRI data sets. In: Workshop on biomedical image analysis (Santa Barbara). Los Alamitos: IEEE Computer Press; 1998.
13. Rosenfeld A, Kak AC. Digital picture processing. San Diego: Academic; 1982.
14. Seber GAF, Wild CJ. Nonlinear regression. New York: Wiley; 1989.
15. Nelder JA, Mead R. The simplex method. Computer Journal 1965;7:308.
16. Friston KJ, Jezzard P, Turner R. Analysis of functional MRI time-series. Hum Brain Mapp 1994;1:153-171.
17. Lange N, Zeger SL. Nonlinear Fourier time series analysis for human brain mapping by functional magnetic resonance imaging. J R Stat Soc Appl Stat 1997;46:1-29.
18. Friston KJ, Josephs O, Rees G, Turner R. Nonlinear event-related responses in fMRI. Magn Reson Med 1998;39:41-52.
19. Rajapakse JC, Kruggel F, von Cramon DY. Modeling hemodynamic response for analysis of functional MRI time-series. Hum Brain Mapp 1998;6:283-300.
20. Bullmore E, Brammer M, Williams SCR, Rabe-Hesketh S, Janolh N, David A, Mellers J, Howard R, Sham P. Statistical methods of estimation and inference for functional MR Image analysis. Magn Reson Med 1996;35:261-277.
21. Benali H, Buvat I, Anton JL, Pelegrini M, Di Paola M, Bittoun J, Burnod Y, Di Paola R. Space-time statistical model for functional MRI image sequences. In: Duncan J, Gindi G, eds. Information processing in medical imaging. Lecture notes in computer science 1230. Berlin: Springer Verlag; 1997.
22. Gardiner CW. Handbook of stochastic methods for physics, chemistry and the natural sciences. Berlin: Springer; 1985.
23. Neumaier A, Schneider T. Multivariate autoregressive and Ornstein-Uhlenbeck processes: estimates for order, parameters, spectral information, and confidence regions. ACM Trans Math Soft 1998 http://www. aos.princeton.edu/WWWPUBLIC/tapio/papers/arfit.html.
24. Walter E, Ponzatto L. Identification of parametric models. Heidelberg: Springer; 1997.
25. Cressie NAC. Statistics for spatial data. New York: Wiley; 1993.
26. Bates D, Watts D. Nonlinear regression analysis and its applications. New York: Wiley; 1988.
27. Cox C, Ma G. Asymptotic confidence bands for generalized nonlinear regression models. Biometrics 1995;51:142-150.
28. Qu RP, Kosorok MR. Improving confidence bands for nonlinear regression. Technical Report 114. Madison, Wisconsin: Department of Biostatistics, University of Wisconsin-Madison; 1997.
29. Descombes X, Kruggel F, von Cramon DY. FMRI signal restoration using a spatio-temporal Markov random field preserving transitions. Neuroimage 1998;8:340-349.
30. Friston KJ, Worsley KJ, Frackowiak RSJ, Mazziotta JC, Evans AC. Assessing the significance of focal activations using their spatial extent. Hum Brain Mapp 1994;1:210-220.
31. Cohen MS. Parametric analysis of fMRI data using linear systems methods. Neuroimage 1997;6:93-103.
32. Venables WN, Ripley BD. Modern applied statistics with S-Plus. Heidelberg: Springer; 1997.