Abstract
In this paper, it is reported that the method and primary application of a novel noninvasive technique, resting functional magnetic resonance imaging (fMRI) with unified statistical parameter mapping (SPM) independent component analysis (ICA), and principal component analysis( PCA), for localizing interictal epileptic activities of glioma foci. SPM is based on the general linear model (GLM). ICA combined PCA was firstly applied to fMRI datasets to disclose independent components, which is specified as the equivalent stimulus response patterns in the design matrix of a GLM. Then, parameters were estimated and regionally-specific statistical inferences were made about activations in the usual way. The validity is tested by simulation experiment. Finally, the fMRI data of two glioma patients is analyzed, whose results are consisting with the clinical estimate.
Supported by NSFC#90208003, #30200059, 30470510, TRAPOYT, the 973 Project No. 2003CB716100, Doctor training Fund of MOE, PRC, Fok Ying Tong Education Foundation (91041).
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References
Friston, K.J., Frith, C.D., Turner, R., Frackowiak, R.S.: Characterizing evoked hemodynamics with fMRI. NeuroImage 2, 157–165 (1995)
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 2, 45–53 (1995)
Adler, R.J.: The geometry of random fields. John Wiley & Sons, Inc., New York (1981)
Dewen, H., Lirong, Y., Yadong, L., Zongtan, Z., Friston, K.J., Changlian, T., Daxing, W.: Unified SPM-ICA for fMRI analysis. Neuroimage 25, 746–755 (2005)
Della-Maggiore, V., Chau, W., Peres-Neto, P.R., McIntosh, A.R.: An empirical comparison of SPM preprocessing parameters to the analysis of fMRI data. NeuroImage 17, 19–28 (2002)
Friston, K.J., Fletcher, P., Josephs, O., Holmes, A., Rugg, M.D., Turner, R.: Event-related fMRI: characterizing differential responses. NeuroImage 7, 30–40 (1998)
Fadili, M.J., Ruan, S., Bloyet, D., Mazoyer, B.: A multistep unsupervised fuzzy clustering analysis of fMRI time series. Hum. Brain Mapp. 10, 160–178 (2000)
Backfrieder, W.: Quantification of intensity variations in functional MR images using rotated principal components. Phys. Med. Biol. 41, 1425–1438 (1996)
Stone, J.V.: Blind source separation using temporal predictability. Neural Compute. 13, 1559–1574 (2001)
Calhoun, V.D., Adali, T., Pearlson, G.D., Pekar, J.J.: Spatial and temporal independent component analysis of functional MRI data containing a pair of task-related waveforms. Hum. Brain Mapp. 13, 43–53 (2001)
McKeown, M.J., Makeig, S., Brown, G.G., Jung, T.P., Kindermann, S.S., Bell, A.J., Sejnowski, T.J.: Analysis of fMRI data by blind separation into independent spatial components. Hum. Brain Mapp. 6, 160–188 (1998)
Fransson, P.: Spontaneous Low-frequency BOLD Signal Fluctuations: An fMRI Investigation of the Resting-state Default Mode of Brain Function Hypothesis. Human Brain Mapping 26, 15–29 (2005)
Friston, K.J., Jezzard, P., Turner, R.: Analysis of functional MRI time series. Hum. Brain Mapp. 1, 153–171 (1994)
Quyang, X., Pike, G.B., Evance, A.C.: FMRI of human visual cortex using temporal correlation and spatial coherence analysis. In: Proc., SMR, 2nd Annual Meeting, San Franciseco, p. 633 (1994)
Turner, R., Grinvald, A.: Direct visualization of patterns of deoxygenating and deoxygenating in monkey cortical vas-culture during functional brain activation. In: Proc., SMR, 2nd Annual Meeting, San Franciseco, p. 430 (1994)
Zhang, Y., Ye, M., Lv, J.C., Tan, K.K.: Convergence analysis of a deterministic discrete time system of Oja’s PCA learning algorithm. IEEE Trans. on Neural Networks 16(6), 1318–1328 (2005)
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Song, Q., Yin, F., Chen, H., Zhang, Y., Hu, Q., Yao, D. (2006). A Novel Unified SPM-ICA-PCA Method for Detecting Epileptic Activities in Resting-State fMRI. In: Jiao, L., Wang, L., Gao, X., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4222. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881223_77
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DOI: https://doi.org/10.1007/11881223_77
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