Spatiotemporal nonlinearity in resting-state fMRI of the human brain

NeuroImage

Volumn 40, Issue 4, 2008, Pages 1672-1685

  Xie, Xiaoping ^a   Cao, Zhitong ^a   Weng, Xuchu ^b  

^a ZHEJIANG UNIVERSITY   (China)

^b INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

Author keywords

Correlation dimension; fMRI; Human brain; Intrinsic dimensionality; Principal Component Analysis; Resting state; Spatiotemporal Lyapunov Exponents; Spatiotemporal nonlinearity

Indexed keywords

ADULT; ALGORITHM; ARTICLE; COMPUTED TOMOGRAPHY SCANNER; CORRELATION ANALYSIS; DATA ANALYSIS; ECHO PLANAR IMAGING; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; HUMAN EXPERIMENT; NEUROIMAGING; NOISE; NONLINEAR SYSTEM; NORMAL HUMAN; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL;

ALGORITHMS; BRAIN; DATA INTERPRETATION, STATISTICAL; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MOTOR CORTEX; MULTIVARIATE ANALYSIS; NONLINEAR DYNAMICS; PRINCIPAL COMPONENT ANALYSIS; REST; VISUAL CORTEX;

EID: 41649100650     PISSN: 10538119     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2008.01.007     Document Type: Article

References (57)

1. Bandettini P.A., Birn R.M., Kelley D., and Saad Z.S. Dynamics nonlinearities in BOLD contrast: neuronal or hemodynamic. Internation Congress Series 1235 (2002) 73-85
2. Bartels A., and Zeki S. Brain dynamics during natural viewing condition-A new guide for mapping connectivity in vivo. NeuroImage 24 (2005) 339-349
3. Birn R.M., Saad Z.S., and Bandettini P.A. Spatial Heterogenenity of the Nonlinear Dynamics in the FMRI BOLD Response. NeuroImage 14 (2001) 817-826
4. Bianciardi M., Sirabella P., Hagberg G.E., Giuliani A., Zbilut J.P., and Colosimo A. Model-free analysis of brain fMRI data by recurrence quantification. NeuroImage 37 (2007) 489-503
5. Breakspear M., Brammer M., and Robinson P.A. Construction of multivariate surrogate sets from nonlinear data using the wavelet transform. Physica D 182 (2003) 1-22
6. Bullmore E., Fadili J., Maxim V., Sendur L., Whitcher B., Suckling J., Brammer M., and Breakspear M. Wavelets and functional resonance imaging of the human brain. NeuroImage 23 (2004) S234-S249
7. Burden R.L., and Faires J.D. Numerical analysis (2001), Higher Education Press and Thomson Learning, Inc., Beijing
8. Buxton R.B., Wong E.C., and Frank L.R. Dynamics of blood flow and oxygenation changes during brain activation: the balloon model. Magn. Reson. Med. 39 6 (1998) 855-864
9. Cellucci C.J., Albano A.M., and Rapp P.E. Comparative study of embedding method. Phys. Rev. E 67 (2003) 066210-1-13
10. Cordes D., and Nandy R.R. Estimation of the intrinsic dimensionality of fMRI data. NeuroImage 29 (2006) 145-154
11. Cordes D., Haughton V.M., Arfanakis K., Carew J.D., Turski P.A., Moritz C.H., Quigley M.A., and Meyerand M.E. Frequencies Contributing to Functional Connectivity in the Cerebral Cortex in ''Resting-state'' Data. AJNR Am. J. Neuroradiol. 22 (2001) 1326-1333
12. Deshpande G., LaConte S., Peltier S., and Hu X. Spatial Embedding of fMRI for Investigating Local Coupling in Human Brain. Medical Imaging 2005: Physiology, Function, and Structure from Medical Images, Proceeding of SPIE, Vol. 5746 (2005) 119-125 SPIE, Bellingham, WA
13. Deshpande G., LaConte S., Peltier S., and Hu X. Tissue Specificity of Nonlinear Dynamics in Baseline fMRI. Magn. Reson. Med. 55 (2006) 626-632
14. Dhamala M., Pagnoni G., Wiesenfeld K., and Berns G.S. Measurement of brain activity complexity for vary mental loads. Phys. Rev. E 65 (2002) 041917-1-7
15. Freeman W.J. Mescopic neurodynamics: From neuron to brain. J. Physiol. (Paris) 94 (2000) 303-322
16. Friman O., and Westin C.F. Resampling fMRI time series. NeuroImage 25 (2005) 859-867
17. Friston K.J., Mechelli A., Turner R., and Price C.J. Nonlinear Responses in fMRI: The Balloon Model, Volterra Kernels, and Other Hemodynamics. NeuroImage 12 (2000) 466-477
18. Galka A. Topics in nonlinear time series analysis: with implications for EEG analysis (2000), World Scientific, Singppore
19. Gautanma T., Mandic D.P., and Hulle M.M.V. Signal nonlinearity in fMRI: A comparison between BOLD and MION. IEEE Trans. Med. Imag. 22 5 (2003) 636-644
20. Glass L., and Mackey M.C. From clocks to chaos: the rhythms of life (1988), Princeton University Press, Princeton, New Jersey
21. Gusnard D.A., and Raichle M.E. Searching for a baseline: functional imaging and the resting human brain. Nat. Rev., Neurosci. 2 (2001) 685-694
22. Hampson M., Peterson B.S., Skudlarski P., Gatenby J.C., and Gore J.C. Detection of Functional Connectivity Using Temporal Correlations in MR Images. Hum. Brain Mapp. 15 (2002) 247-262
23. Harrison L., Penny W.D., and Friston K. Multivariate autoregressive modeling of fMRI time series. NeuroImage 19 (2003) 1477-1491
24. Hegger R., and Kantz H. Practical implementation of nonlinear time series methods: The TISEAN package. Chaos 9 (1999) 413-435
25. Huettel S.A. Non-linearities in blood-oxygenation-level dependent (BOLD) response measured by functional magnetic resonance imaging (fMRI). Proceeding of the 26th Annual International Conference of the IEEE EMBS, San Francisco, CA (2004) 4413-4416
26. Kantz H., and Schreiber T. Nonlinear time series analysis (1997), Cambridge University Press, Cambridge
27. LaConte S., Peltier S., Kadah Y., Ngan S.C., Deshpande G., and Hu X. Detecting nonlinear dynamics of functional connectivity. Medical Imaging 2004: Physiology, Function, and Structure from Medical Images, Proceeding of SPIE, Vol. 5369 (2004) 227-237 SPIE, Bellingham, WA
28. Lahaye P.J., Poline J.B., Flandin G., Dodel S., and Garnero L. Functional connectivity: studying nonlinear, delayed interactions between BOLD signals. NeuroImage 20 (2003) 962-974
29. Laird A.R., Rogers B.P., and Meyerand M.E. Investigating the Nonlinearity of fMRI Activation Data. Proceeding of the Second Joint EMBS/BMES Conference (2002), IEEE, Houston, TX 11-12
30. Lee U., and Kim S. Classification of epilepsy types through global network analysis of scalp electroencephalograms. Phys. Rev. E 73 (2006) 041920-1-9
31. Lee Y.J., Zhu Y.S., Xu Y.H., Shen M.F., Zhang H.X., and Thakor N.V. Detection of non-linearity in the EEG of schizophrenic patients. Clin. Neurophysiol. 112 (2001) 1288-1294
32. Lehnertz K., and Elger C.E. Can epileptic seizures be predicted? Evidence from nonlinear time series analysis of brain electrical activity. Phys. Rev. Lett. 80 22 (1998) 5019-5022
33. Lowe M.J., Mock B.J., and Sorenson J.A. Functional Connectivity in Single and Mutislice Echoplanar Imageing Using Resting-State Fluctuation. NeuroImage 7 (1998) 119-132
34. Luca D.M., Beckmann C.F., Stefano D.N., Matthews P.M., and Smith S.M. fMRI resting state networks define distinct modes of long-distance interactions in the human brain. NeuroImage 29 (2006) 1359-1367
35. Maxim V., Sendur L., Fadili J., Suxkling J., Gould R., Howard R., and Bullmore E. Fractional Gaussian noise, functional MRI and Alzheimer's diease. NeuroImage 25 (2005) 141-158
36. McIntosh A.R., Chan W.K., and Protzner A.B. Spatiotemporal analysis of event-related fMRI data using partial least squares. NeuroImage 23 (2004) 764-775
37. Müller M., and Baier G. Detection and characterization of changes of the correlation structure in multivariate time series. Phys. Rev. E 71 (2005) 046116-1-16
38. Pezard L., Martinerie J., Müller-Gerking J., Varela F.J., and Renault B. Entropy quantification of human brain spatio-temporal dynamics. Physica D 96 (1996) 344-354
39. Pfeuffer J., McCullough J.C., Moortele V.P.F., Ugurbil K., and Hu X. Spatial dependence of the nonlinear BOLD response at short stimulus duration. NeuroImage 18 (2003) 990-1000
40. Perc M. Nonlinear time series analysis of the human electrocardiogram. Eur. J. Phys. 26 (2005) 757-768
41. Reidl J., Strrke J., Omer D.B., Grinvald A., and Spors H. Independent component analysis of high-resolution imaging data identifies distinct functional domains. NeuroImaging 34 (2007) 94-108
42. Raichle M.E. The brain's dark energy. Science 314 (2006) 1249-1250
43. Ricard V.S., and Jordi B. Measuing Chaos from Spatial Information. J. Theor. Biol. 175 (1995) 139-147
44. Raab C., and Kurths J. Estimation of large-scale dimension densities. Phys. Rev. E 64 (2001) 016216-1-5
45. Raab C., Wessel N., Schirdewan A., and Kurths J. Large-scale dimension densities for heart rate variability analysis. Phys. Rev. E 73 (2006) 041907-1-7
46. Schreiber T., and Schmitz A. Surrogated time series. Physica D 142 (2000) 346-382
47. Sendur L., Suckling J., Whitcher B., and Bullmore E. Resampling methods for improved wavelet-based multiple hypothesis testing of parametric maps in functional MRI. NeuroImage 37 (2007) 1186-1194
48. Small M. Applied nonlinear time series analysis: applications in physics, physiology and finance (2005), World Scientific Publishing Co. Pet. Ltd., Singapore
49. Stam C.J. Nonlinear dynamical analysis of EEG and MEG: Review of an emerging field. Clin. Neurophysiol. 116 (2005) 2266-2301
50. Stam C.J., Jelles B., Achtereekte H.A.M., Rombouts S.A.R.B., Slaets J.P.J., and Keunen R.W.M. Investigation of EEG non-linearity in dementia and Parkinson's disease. Electroencephalogr. Neurophysiol. 95 (1995) 309-317
51. Thirion B., Dodel S., and Poline J.B. Detection of signal synchronizations in resting-state fMRI data. NeuroImage 29 (2006) 321-327
52. Uhl C., Kruggel F., Opitz B., and Cramon D.Y. A New Concept for EEG/MEG Signal Analysis: Detection of Interacting Spatial Modes. Hum. Brain Mapp. 6 (1998) 137-149
53. Vazquez A.L., and Noll D.C. Nonlinear Aspects of the BOLD Response in Functional MRI. NeuroImage 7 (1998) 108-118
54. Wager T.D., Vazquez A., Hernandez L., and Noll D.C. Accounting for nonlinear BOLD effects in fMRI: parameter estimates and a model for prediction in rapid event-related studies. NeuroImage 25 (2005) 206-218
55. Wicker B., Ruby P., Royet J.P., and Fonlupt P. A relation between rest and self in the brain?. Brain Res. Rev. 43 (2003) 224-230
56. Worsley K.J., Chen J.I., Lerch J., and Evans A.E. Comparing functional connectivity via thresholding correlations and singular value decomposition. Phil. Trans. R. Soc. B 360 (2005) 913-920
57. Zuendorf G., Kerrouche N., Herholz K., and Baron J.C. Efficient Principal Component Analysis for Multivariate 3D Voxel-Based Mapping of Brain Functional Imaging Data Sets as Applied to FDG-PET and Normal Aging. Hum. Brain Mapp. 18 (2003) 13-21