A multiscale analysis of the temporal characteristics of resting-state fMRI data

Journal of Neuroscience Methods

Volumn 193, Issue 2, 2010, Pages 334-342

  Park, Cheolwoo ^a   Lazar, Nicole A ^a   Ahn, Jeongyoun ^a   Sornborger, Andrew ^b  

^a UNIVERSITY OF GEORGIA   (United States)

^b University of Georgia   (United States)

Author keywords

Hurst parameter; Long range dependence; Principal component analysis; Sizer; Spectrum; Wavelet

Indexed keywords

ANALYTIC METHOD; ARTICLE; BRAIN MAPPING; DATA ANALYSIS; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; IMAGE ANALYSIS; NEUROIMAGING; NULL HYPOTHESIS; PARAMETER; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; SPECTRUM; STATISTICAL ANALYSIS; TIME SERIES ANALYSIS; WHITE NOISE;

ALGORITHMS; BRAIN; BRAIN MAPPING; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MODELS, BIOLOGICAL; OXYGEN; REST; TIME FACTORS;

EID: 78049385156     PISSN: 01650270     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jneumeth.2010.08.021     Document Type: Article

References (29)

1. Abry P., Veitch D. Wavelet analysis of long-range dependent traffic. IEEE Transactions on Information Theory 1998, 44:2-15.
2. Bullmore E., Brammer M., Williams S., Rabe-Hesketh S., Janot N., David A., et al. Statistical methods of estimation and inference for functional MR image analysis. Magnetic Resonance in Medicine 1996, 35:261-277.
3. Bullmore E., Fadili J., Breakspear M., Salvador R., Suckling J., Brammer M. Wavelets and statistical analysis of functional magnetic resonance images of the human brain. Statistical Methods in Medical Research 2003, 12:375-399.
4. Chaudhuri P., Marron J.S. SiZer for exploration of structures in curves. Journal of the American Statistical Association 1999, 94:807-823.
5. Daubechies I. Ten lectures on wavelets 1992, SIAM, Philadelphia.
6. Fadili M., Bullmore E. Wavelet-generalized least squares: a new BLU estimator of linear regression models with 1/f errors. NeuroImage 2002, 15:217-232.
7. Fan J., Gijbels I. Local polynomial modelling and its applications 1996, Chapman & Hall, London.
8. Fox M., Raichle M. Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Neuroscience 2007, 8:700-711.
9. Gautama T., Van Hulle M.M. Estimating the global order of the fMRI noise model. NeuroImage 2005, 26:1211-1217.
10. Hannig J., Marron J.S. Advanced distribution theory for SiZer. Journal of the American Statistical Association 2006, 101:484-499.
11. Huang C.-C., Liou M., Cheng P.E. Baseline correction of functional MR time courses with PCA. Proceedings of the 9th international conference on neural information processing, vol. 1 2002, 433-435.
12. Lindeberg T. Scale space theory in computer vision 1994, Kluwer, Boston.
13. Locascio J., Jennings P., Moore C., Corkin S. Time series analysis in the time domain and resampling methods for studies of functional magnetic resonance brain imaging. Human Brain Mapping 1997, 5:168-193.
14. Long C., Brown E., Triantafyllou C., Aharon I., Wald L., Solo V. Nonstationary noise estimation in functional MRI. NeuroImage 2005, 28:890-903.
15. Lund T., Madsen K., Sidaros K., Luo W., Nichols T. Non-white noise in fMRI: does modelling have an impact?. NeuroImage 2006, 29:54-66.
16. Luo W., Nichols T.E. Diagnosis and exploration of massively univariate neuroimaging models. NeuroImage 2003, 19:1014-1032.
17. Maxim V., Sendur L., Fadili J., Suckling J., Gould R., Howard R., et al. Fractional Gaussian noise, functional MRI and Alzheimer's disease. NeuroImage 2005, 25:141-158.
18. Park C, Hernandez Campos F, Le L, Marron JS, Park J, Pipiras V, et al. Long-range dependence analysis of Internet traffic. Journal of Applied Statistics; in press.
19. Park C, Lazar NA, Ahn J, Sornborger A. Do different parts of the brain have the same dependence structure? A multiscale analysis of the temporal and spatial characteristics of resting fMRI data. Technical report. Department of Statistics, University of Georgia; 2008.
20. Park C., Marron J.S., Rondonotti V. Dependent SiZer: goodness of fit tests for time series models. Journal of Applied Statistics 2004, 31:999-1017.
21. Penny W., Kiebel S., Friston K. Variational Bayes inference for fMRI time series. NeuroImage 2003, 19:727-741.
22. Purdon P.L., Solo V., Weisskoff R.M., Brown E.N. Locally regularized spatiotemporal modeling and model comparison for functional MRI. NeuroImage 2001, 14:912-923.
23. Raichle M., Snyder A. A default mode of brain function: a brief history of an evolving idea. NeuroImage 2007, 37:1083-1090.
24. Rondonotti V., Marron J.S., Park C. SiZer for time series: a new approach to the analysis of trends. Electronic Journal of Statistics 2007, 1:268-289.
25. Stoev S., Taqqu M., Park C., Marron J.S. On the wavelet spectrum diagnostic for hurst parameter estimation in the analysis of Internet traffic. Computer Networks 2005, 48:423-445.
26. Veitch D., Abry P. A wavelet based joint estimator for the parameters of LRD. IEEE Transactions on Information Theory 1999, 45:878-897.
27. Woolrich M.W., Ripley B.D., Brady J.M., Smith S.M. Temporal autocorrelation in univariate linear modeling of fMRI data. NeuroImage 2001, 14:1370-1386.
28. Worsley K.J., Marrett S., Neelin P., Evans A.C. Searching scale space for activation in PET images. Human Brain Mapping 1996, 4:74-90.
29. Worsley KJ, Wolforth M, Evans AC. ICA of functional MRI data: an overviewscale space searches for a periodic signal in fMRI data with spatially varying hemodynamic response. In: Proceedings of BrainMap '95 conference; 1997.