Bayesian fMRI data analysis with sparse spatial basis function priors

NeuroImage

Volumn 34, Issue 3, 2007, Pages 1108-1125

  Flandin, Guillaume ^a   Penny, William D ^a  

^a WELLCOME TRUST CENTRE FOR NEUROIMAGING   (United Kingdom)

Author keywords

fMRI; General linear model; Hierarchical model; Sparse spatial prior; Variational Bayes; Wavelet denoising

Indexed keywords

ANALYTIC METHOD; ARTICLE; BAYES THEOREM; BRAIN FUNCTION; BRAIN MAPPING; BRAIN REGION; DATA ANALYSIS; EVALUATION; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; INTERMETHOD COMPARISON; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; METHODOLOGY; NONLINEAR SYSTEM; PRIORITY JOURNAL; PROBABILITY; PROCESS DEVELOPMENT; PROCESS MONITORING; REGRESSION ANALYSIS; SPARSE SPATIAL BASIS FUNCTION; SPATIAL ORIENTATION; TECHNIQUE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; BRAIN; BRAIN MAPPING; COMPUTER SIMULATION; EVOKED POTENTIALS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED;

EID: 33947179549     PISSN: 10538119     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2006.10.005     Document Type: Article

References (52)

1. Andrade A., Kherif F., Mangin J.-F., Worsley K., Paradis A.-L., Simon O., Dehaene S., and Poline J.-B. Detection of fMRI activation using cortical surface mapping. Hum. Brain Mapp. 12 (2001) 79-93
2. Antoniadis A., Bigot J., and Sapatinas T. Wavelet estimators in nonparametric regression: a comparative simulation study. J. Stat. Softw. 6 6 (2001) 1-83
3. Ashburner J., and Friston K. Unified segmentation. NeuroImage 26 (2005) 839-851
4. Aston J., Gunn R., Hinz R., and Turkheimer F. Wavelet variance components in image space for spatiotemporal neuroimaging data. NeuroImage 25 (2005) 159-168
5. Aston J., Turkheimer F., and Brett M. HBM functional imaging analysis contest data analysis in wavelet space. Hum. Brain Mapp. 27 (2006) 372-379
6. Attias H. A variational Bayesian framework for graphical models. Advances in Neural Information Processing Systems 12 (2000), MIT Press 209-215
7. Beal, M., 2003. Variational algorithms for approximate Bayesian inference. PhD thesis, University College London.
8. Bullmore E., Fadili M., Maxim V., Sendur L., Whitcher B., Suckling J., Brammer M., and Breakspear M. Wavelets and functional magnetic resonance imaging of the human brain. NeuroImage 23 (2004) 234-249
9. Chipman H., McCulloch R., and Kolaczyk E. Adaptive Bayesian wavelet shrinkage. J. Am. Stat. Assoc. 92 (1997) 1413-1421
10. Clyde M., Parmigiani G., and Vidakovic B. Multiple shrinkage and subset selection in Wavelets. Biometrika 85 2 (1998) 391-401
11. Descombes X., Kruggel F., and von Cramon D.Y. fMRI signal restoration using a spatio-temporal Markov random field preserving transitions. NeuroImage 8 (1998) 340-349
12. Donoho D., and Johnstone I. Ideal spatial adaptation by wavelet shrinkage. Biometrika 81 3 (1994) 425-455
13. Donoho D., and Johnstone I. Adapting to unknown smoothness via wavelet shrinkage. J. Am. Stat. Assoc. 90 432 (1995) 1200-1224
14. Everitt B., and Bullmore E. Mixture model mapping of brain activation in functional magnetic resonance images. Hum. Brain Mapp. 8 (1999) 340-349
15. Fadili M., and Bullmore E. A comparative evaluation of wavelet-based methods for hypothesis testing of brain activation maps. NeuroImage 23 3 (2004) 1112-1128
16. Frackowiak R., Friston K., Frith C., Dolan R., Price C., Zeki S., Ashburner J., and Penny W. Human Brain Function. 2nd ed. (2003), Academic Press
17. Friman O., Borga M., Lundberg P., and Knutsson H. Adaptive analysis of fMRI data. NeuroImage 19 3 (2003) 837-845
18. Friston K., and Penny W. Posterior probability maps and SPMs. NeuroImage 19 3 (2003) 1240-1249
19. Friston K., Ashburner J., Frith C., Poline J., Heather J.D., and Frackowiak R. Spatial registration and normalization of images. Hum. Brain Mapp. 2 (1995) 165-189
20. Friston K., Holmes A., Worsley K., Poline J.-B., Frith C., and Frackowiak R. Statistical parametric maps in functional imaging: a general linear approach. Hum. Brain Mapp. 2 (1995) 189-210
21. Friston K., Fletcher P., Josephs O., Holmes A., Rugg M., and Turner R. Event-related fMRI: characterizing differential responses. NeuroImage 7 (1998) 30-40
22. Friston, K., Mattout, J., Trujillo-Barreto, N., Ashburner, J., Penny, W., in press. Variational free energy and the Laplace approximation. NeuroImage.
23. Godtliebsen F., Marron J., and Chaudhuri P. Statistical significance of features in digital images. Image Vis. Comput. 22 13 (2004) 1093-1104
24. Gössl C., Auer D., and Fahrmeir L. Bayesian spatio-temporal inference in functional magnetic resonance imaging. Biometrics (2001) 554-562
25. Hartvig N., and Jensen J. Spatial mixture modelling of fMRI data. Hum. Brain Mapp. 11 (2000) 233-248
26. Henson R., Shallice T., Gorno-Tempini M.-L., and Dolan R. Face repetition effects in implicit and explicit memory tests as measured by fMRI. Cereb. Cortex 12 (2002) 178-186
27. Kiebel S., Goebel R., and Friston K. Anatomically informed basis functions. NeuroImage 11 6 (2000) 656-667
28. Kim H., Giacomantone J., and Cho Z. Robust anisotropic diffusion to produce enhanced statistical parametric map from noisy fMRI. Comput. Vis. Image Underst. 99 3 (2005) 435-452
29. Lappalainen H., and Miskin J. Ensemble learning. Advances in Independent Component Analysis (2000), Springer Verlag 75-92
30. Mallat S. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans. Pattern Anal. Mach. Intell. 11 7 (1989) 674-693
31. Mallat S. A Wavelet Tour of Signal Processing (1999), Academic Press
32. Penny W. Variational Bayes for d-Dimensional Gaussian Mixture Models. Tech. rep. (2001), University College London
33. Penny W., and Flandin G. Bayesian analysis of fMRI data with spatial priors. Proceedings of the Joint Statistical Meeting (JSM), Section on Statistical Graphics (2005), American Statistical Association, Alexandria, VA
34. Penny W., and Friston K. Mixtures of general linear models for functional neuroimaging. IEEE Trans. Med. Imag. 22 4 (2003) 504-514
35. Penny W., Kiebel S., and Friston K. Variational Bayesian inference for fMRI time series. NeuroImage 19 3 (2003) 727-741
36. Penny W., Trujillo-Bareto N., and Friston K. Bayesian fMRI time series analysis with spatial priors. NeuroImage 24 2 (2005) 350-362
37. Penny, W., Flandin, G., Trujillo-Barreto, N., in press. Bayesian comparison of spatially regularised general linear models. Hum. Brain Mapp.
38. Poline J.-B., and Mazoyer B. Analysis of individual brain activation maps using hierarchical description and multiscale detection. IEEE Trans. Med. Imag. 13 (1994) 702-710
39. Ruttimann U., Unser M., Rawlings R., Rio D., Ramsey N., Mattay V., Hommer D., Frank J., and Weinberger D. Searching scale space for activation in PET images. IEEE Trans. Med. Imag. 17 (1998) 142-154
40. Sendur L., Maxim V., Whitcher B., and Bullmore E. Multiple hypothesis mapping of functional MRI data in orthogonal and complex wavelet domains. IEEE Trans. Signal Process. 53 9 (2005) 3413-3426
41. Solé A., Ngan S., Sapiro G., Hu X., and López A. Anisotropic 2D and 3D averaging of fMRI signals. IEEE Trans. Med. Imag. 20 2 (2001) 86-93
42. SPM, 2005. Wellcome Department of Imaging Neuroscience. Available from http://www.fil.ion.ucl.ac.uk/spm/.
43. Thirion B., Flandin G., Pinel P., Roche A., Ciuciu P., and Poline J.-B. Dealing with the shortcomings of spatial normalization: multi-subject parcellation of fMRI datasets. Hum. Brain Mapp. 27 8 (2006) 678-693
44. Turkheimer F., Aston J., Asselin M., and Hinz R. Multi-resolution Bayesian regression in PET dynamic studies using wavelets. NeuroImage 32 1 (2006) 111-121
45. Van De Ville D., Blu T., and Unser M. Wavelets versus resels in the context of fMRI: establishing the link with SPM. Proceedings of the SPIE Conference on Mathematical Imaging: Wavelet Applications in Signal and Image Processing X (2003), San Diego, USA 417-425
46. Van De Ville D., Blu T., and Unser M. Integrated wavelet processing and spatial statistical testing of fMRI data. NeuroImage 23 (2004) 1472-1485
47. Van De Ville D., Blu T., and Unser M. WSPM or how to obtain statistical parametric maps using shift-invariant wavelet processing. IEEE International Conference on Acoustics, Speech, and Signal Processing vol. V (2006), Toulouse, France 1101-1104
48. WaveLab, 1999. D. Donoho, M. Duncan, X. Huo, and O. Levi. Available from http://www-stat.stanford.edu/~wavelab/.
49. Wink A., and Roerdink J. Denoising functional MR images: a comparison of wavelet denoising and Gaussian smoothing. IEEE Trans. Med. Imag. 23 (2004) 375-387
50. Woolrich M., Jenkinson M., Brady J., and Smith S. Fully Bayesian spatio-temporal modeling of fMRI data. IEEE Trans. Med. Imag. 23 (2004) 213-231
51. Woolrich M., Behrens T., Beckmann C., and Smith S. Mixture models with adaptive spatial regularization for segmentation with an application to fMRI data. IEEE Trans. Med. Imag. 24 1 (2005) 1-11
52. Worsley K., Marret S., Neelin P., and Evans A. Searching scale space for activation in PET images. Hum. Brain Mapp. 4 (1996) 74-90