Nonparametric inference of the hemodynamic response using multi-subject fMRI data

NeuroImage

Volumn 63, Issue 3, 2012, Pages 1754-1765

  Zhang, Tingting ^a   Li, Fan ^b   Beckes, Lane ^a   Brown, Casey ^a   Coan, James A ^a  

^a UNIVERSITY OF VIRGINIA   (United States)

^b Duke University   (United States)

Author keywords

Bias correction; General linear model; Hemodynamic response function; Kernel smoothing; Regularization

Indexed keywords

ANTICIPATION; ARTICLE; CAUDATE NUCLEUS; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HYPOTHESIS; INFORMATION PROCESSING; KERNEL METHOD; MATHEMATICAL MODEL; MOTIVATION; NONPARAMETRIC TEST; PRIORITY JOURNAL; PUTAMEN; REWARD; STATISTICAL MODEL; STIMULUS RESPONSE;

ADULT; ALGORITHMS; BRAIN; CEREBROVASCULAR CIRCULATION; FEMALE; HEMODYNAMICS; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; STATISTICS, NONPARAMETRIC; YOUNG ADULT;

EID: 84867370695     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2012.08.014     Document Type: Article

References (54)

1. Aguirre G.K., Zarahn E., D'Esposito M. The variability of human, BOLD hemodynamic responses. NeuroImage 1998, 8:360-369.
2. Allen J.P., Porter M., McFarland F.C., McElhaney K.B., Marsh P. The relation of attachment security to adolescents' paternal and peer relationships, depression, and externalizing behavior. Child Dev. 2007, 78:1222-1239.
3. Bai P., Truong Y., Huang X. Nonparametric estimation of hemodynamic response function: a frequency domain approach. Optimality: The Third Erich L. Lehmann Symposium 2009, 57:190-215.
4. Benjamini Y., Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B Methodol. 1995, 289-300.
5. Bjork J.M., Knutson B., Fong G.W., Caggiano D.M., Bennett S.M., Hommer D. Incentive-elicited brain activation in adolescents: similarities and differences from young adults. J. Neurosci. 2004, 24:1793-1802.
6. Brosch J., Talavage T., Ulmer J., Nyenhuis J. Simulation of human respiration in fMRI with a mechanical model. IEEE Trans. Biomed. Eng. 2002, 49:700-707.
7. Buxton R.B., Uludag K., Dubowitz D.J., Liu T.T. Modeling the hemodynamic response to brain activation. NeuroImage 2004, 23:220-233.
8. Calhoun V.D., Stevens M.C., Pearlson G.D., Kiehl K.A. fMRI analysis with the general linear model: removal of latency-induced amplitude bias by incorporation of hemodynamic derivative terms. NeuroImage 2004, 22:252-257.
9. Casanova R., Ryali S., Serences J., Yang L., Kraft R., Laurienti P.J., Maldjian J.A. The impact of temporal regularization on estimates of the BOLD hemodynamic response function: a comparative analysis. NeuroImage 2008, 40(4):1606-1618.
10. Casanova R., Yang L., Hairston W.D., Laurienti P.J., Maldjian J.A. Evaluating the impact of spatio-temporal smoothness constraints on the BOLD hemodynamic response function estimation: an analysis based on Tikhonov regularization. Physiol. Meas. 2009, 30(5):37-51.
11. Ciuciu P., Poline J.B., Marrelec G., Idier J., Pallier C., Benali H. Unsupervised robust nonparametric estimation of the hemodynamic response function for any fMRI experiment. IEEE Trans. Med. Imaging 2003, 22:1235-1251.
12. Dale A. Optimal experimental design for event-related fMRI. Hum. Brain Mapp. 1999, 8:109-114.
13. Efron B. False discovery rates and the James-Stein estimator. Stat. Sin. 2008, 18:805-816.
14. Eubank R.L. Nonparametric Regression and Spline Smoothing 1988, Marcel Dekker, New York.
15. Friston K.J., Jezzard P.J., Turner R. Analysis of functional MRI time-series. Hum. Brain Mapp. 1994, 1:153-171.
16. Friston K.J., Holmes A.P., Poline J.B., Grasby P.J., Williams S.C., Frackowiak R.S., Turner R. Analysis of fMRI time-series revisited. NeuroImage 1995, 2:45-53.
17. Friston K.J., Holmes A.P., Worsley K., Poline P.J., Frith C., Frackowiak R. Statistical parametric maps in functional imaging: a general linear approach. Hum. Brain Mapp. 1995, 2:189-210.
18. Friston K.J., Fletcher P., Josephs O., Holmes A., Rugg M.D., Turner R. Event-related fMRI: characterizing differential responses. NeuroImage 1998, 7:30-40.
19. Genovese C.R. A Bayesian time-course model for functional magnetic resonance imaging data (with comments). J. Am. Stat. Assoc. 2000, 95:691-719.
20. Glover G.H. Deconvolution of impulse response in event-related BOLD fMRI. NeuroImage 1999, 9:416-429.
21. Goutte C., Nielsen F.A., Hansen L.K. Modeling the haemodynamic response in fMRI using smooth FIR filters. IEEE Trans. Med. Imaging 2000, 19:1188-1201.
22. Handwerker D.A., Ollinger J.M., D'Esposito M. Variation of BOLD hemodynamic responses across subjects and brain regions and their effects on statistical analyses. NeuroImage 2004, 21:1639-1651.
23. Härdle W. Applied Nonparametric Regression 1990, Cambridge University Press.
24. Henson R., Price C.J., Rugg M.D., Turner R., Friston K.J. Detecting latency differences in event-related BOLD responses: application to words versus nonwords and initial versus repeated face presentations. NeuroImage 2002, 15:83-97.
25. Hotelling H. The generalization of Student's ratio. Ann. Math. Stat. 1931, 2:360-378.
26. Jenkinson M., Bannister P., Brady M., Smith S. Improved optimization for the robust and accurate linear registration and motion correction of brain images. NeuroImage 2002, 17:825-841.
27. Josephs O., Turner R., Friston K.J. Event-related fMRI. Hum. Brain Mapp. 1997, 5:243-248.
28. Knutson B., Westdorp A., Kaiser E., Hommer D. FMRI visualization of brain activity during a monetary incentive delay task. NeuroImage 2000, 12:20-27.
29. Knutson B., Fong G.W., Adams C.M., Varner J.L., Hommer D. Dissociation of reward anticipation and outcome with event-related fMRI. Neuroreport 2001, 12(17):3683-3687.
30. Lange N., Strother S.C., Anderson J.R., Nielsen F.A., Holmes A.P., Kolenda T., Savoy R., Hansen L.K. Plurality and resemblance in fMRI data analysis. NeuroImage 1999, 10:282-303.
31. Liao C.H., Worsley K.J., Poline J.-B., Aston J.A.D., Duncan G.H., Evans A.C. Estimating the delay of the fMRI response. NeuroImage 2002, 16:593-606.
32. Lindquist M.A. The statistical analysis of fMRI data. Stat. Sci. 2008, 23:439-464.
33. Lindquist M.A., Wager T.D. Validity and power in hemodynamic response modelling: a comparison study and a new approach. Hum. Brain Mapp. 2007, 28:764-784.
34. Lindquist M.A., Loh J.M., Atlas L., Wager T.D. Modeling the hemodynamic response function in fMRI: efficiency, bias and mis-modeling. NeuroImage 2009, 45:S187-S198.
35. Luo H., Puthusserypady S. Analysis of fMRI data with drift: modified general linear model and Bayesian estimator. IEEE Trans. Biomed. Eng. 2008, 55:1504-1511.
36. Marrelec G., Benali H., Ciuciu P., Poline J.B. Bayesian estimation of the hemodynamic of the hemodynamic response function in functional MRI. AIP Conf. Proc. 2001, 617:229-247.
37. Marrelec G., Benali H., Ciuciu P., Pelegrini-Issac M., Poline J.B. Robust estimation of the hemodynamic response function in event-related BOLD fMRI using basic physiological information. Hum. Brain Mapp. 2003, 19:1-17.
38. Mattay V.S., Frank J.A., Santha A.K.S., Pekar J.J., Duyn J.H., McLaughlin A.C., Weinberger D.R. Whole brain functional mapping with isotropic MR imaging. Radiology 1996, 201:399-404.
39. Ollinger J.M., Corbetta M., Shulman G.L. Separating processes within a trial in event-related functional MRI. NeuroImage 2001, 13:218-229.
40. Riera J.J., Watanabe J., Kazuki I., Naoki M., Aubert E., Ozaki T., Kawashima R. A state-space model of the hemodynamic approach: nonlinear filtering of bold signals. NeuroImage 2004, 21:547-567.
41. Smith S.M. Fast robust automated brain extraction. Hum. Brain Mapp. 2002, 17:143-155.
42. Smith A., Lewis B., Ruttinmann U., et al. Investigation of low frequency drift in fMRI signal. NeuroImage 1999, 9:526-533.
43. Smith S.M., Jenkinson M., Woolrich M.W., Beckmann C.F., Behrens T.E.J., Johansen-Berg H., Bannister P.R., De Luca M., Drobnjak I., Flitney D.E., Niazy R., Saunders J., Vickers J., Zhang Y., De Stefano N., Brady J.M., Matthews P.M. Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage 2004, 23(S1):208-219.
44. Spielberger C.D., Vagg P.R. Psychometric properties of the STAI: a reply to Ramanaiah, Franzen, and Schill. J. Personal. Assess. 1984, 48:95-97.
45. Tikhonov A.N., Arsenin V.Y. Solution of Ill-posed Problems 1977, Winston & Sons, Washington.
46. Vakorin V.A., Borowsky R., Sarty G.E. Characterizing the functional MRI response using Tikhonov regularization. Stat. Med. 2007, 26(21):3830-3844.
47. Wahba G. Spline Models for Observational Data 1990, SIAM, Philadelphia.
48. Wang J., Zhu H., Fan J.Q., Giovanello K., Lin W.L. Multiscale adaptive smoothing model for the hemodynamic response function in fMRI. MICCAI, LNCS 2011, 6892:269-276.
49. Woolrich M.W., Behrens T.E., Smith S.M. Constrained linear basis sets for HRF modelling using variational Bayes. NeuroImage 2004, 21:1748-1761.
50. Woolrich M.W., Jbabdi S., Patenaude B., Chappell M., Makni S., Behrens T., Beckmann C., Jenkinson M., Smith S.M. Bayesian analysis of neuroimaging data in FSL. NeuroImage 2009, 45:S173-S186.
51. Worsley K.J., Friston K.J. Analysis of fMRI time-series revisited again. NeuroImage 1995, 2:173-181.
52. Worsley K.J., Liao C.H., Aston J., Petre V., Duncan G.H., Morales F., Evans A. A general statistical analysis for fMRI Data. NeuroImage 2002, 15:1-15.
53. Zarahn E. Using larger dimensional signal subspaces to increase sensitivity in fMRI time series analyses. Hum. Brain Mapp. 2002, 17:13-16.
54. Zhang C.M., Jiang Y., Yu T. A comparative study of one-level and two-level semiparametric estimation of hemodynamic response function for fMRI data. Stat. Med. 2007, 26:3845-3861.