Validation of shared and specific independent component analysis (SSICA) for between-group comparisons in fMRI

Frontiers in Neuroscience

Volumn 10, Issue SEP, 2016, Pages

  Maneshi, Mona ^a,b   Vahdat, Shahabeddin ^b,c   Gotman, Jean ^a   Grova, Christophe ^a,b,d  

^a MCGILL UNIVERSITY   (Canada)

^b MCGILL UNIVERSITY   (Canada)

^c CENTRE DE RECHERCHE   (Canada)

^d Dept of Electrical and Computer Engineering   (Canada)

Author keywords

Between groups comparison; FMRI; Functional connectivity (FC); Independent component analysis (ICA); Statistical modeling

Indexed keywords

CLASSIFICATION; EXTRACT; FUNCTIONAL CONNECTIVITY; FUNCTIONAL MAGNETIC RESONANCE IMAGING; INDEPENDENT COMPONENT ANALYSIS; RELIABILITY; REST; STATISTICAL MODEL; STATISTICS; VALIDATION PROCESS;

EID: 84992065349     PISSN: 16624548     EISSN: 1662453X     Source Type: Journal    
DOI: 10.3389/fnins.2016.00417     Document Type: Article

References (40)

1. Albert, N. B., Robertson, E. M., and Miall, R. C. (2009). The resting human brain and motor learning. Curr. Biol. 19, 1023-1027. doi: 10.1016/j.cub.2009.04.028
2. Assaf, M., Jagannathan, K., Calhoun, V. D., Miller, L., Stevens, M. C., Sahl, R., et al. (2010). Abnormal functional connectivity of default mode sub-networks in autism spectrum disorder patients. Neuroimage 53, 247-256. doi: 10.1016/j.neuroimage.2010.05.067
3. Beckmann, C. F., and Smith, S. M. (2005). Tensorial extensions of independent component analysis for multisubject FMRI analysis. Neuroimage 25, 294-311. doi: 10.1016/j.neuroimage.2004.10.043
4. Beckmann, C. F., DeLuca, M., Devlin, J. T., and Smith, S. M. (2005). Investigations into resting-state connectivity using independent component analysis. Philos. Trans. R. Soc. Lond. B Biol. Sci. 360, 1001-1013. doi: 10.1098/rstb.2005.1634
5. Beckmann, C. F., Jenkinson, M., and Smith, S. M. (2003). General multilevel linear modeling for group analysis in FMRI. Neuroimage 20, 1052-1063. doi: 10.1016/S1053-8119(03)00435-X
6. Bellec, P., Rosa-Neto, P., Lyttelton, O. C., Benali, H., and Evans, A. C. (2010). Multi-level bootstrap analysis of stable clusters in resting-state fMRI. Neuroimage 51, 1126-1139. doi: 10.1016/j.neuroimage.2010.02.082
7. Boly, M., Perlbarg, V., Marrelec, G., Schabus, M., Laureys, S., Doyon, J., et al. (2012). Hierarchical clustering of brain activity during human nonrapid eye movement sleep. Proc. Natl. Acad. Sci. U.S.A. 109, 5856-5861. doi: 10.1073/pnas.1111133109
8. Calhoun, V. D., Adali, T., Pearlson, G. D., and Pekar, J. J. (2001). A method for making group inferences from functional MRI data using independent component analysis. Hum. Brain Mapp. 14, 140-151. doi: 10.1002/hbm.1048
9. Calhoun, V. D., Liu, J., and Adali, T. (2009). A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data. Neuroimage 45, S163-S172. doi: 10.1016/j.neuroimage.2008.10.057
10. Condon, B., McFadzean, R., Hadley, D. M., Bradnam, M. S., and Shahani, U. (1997). Habituation-like effects cause a significant decrease in response in MRI neuroactivation during visual stimulation. Vision Res. 37, 1243-1247. doi: 10.1016/S0042-6989(97)85231-5
11. Damoiseaux, J. S., Beckmann, C. F., Arigita, E. J., Barkhof, F., Scheltens, P., Stam, C. J., et al. (2008). Reduced resting-state brain activity in the "default network" in normal aging. Cereb. Cortex 18, 1856-1864. doi: 10.1093/cercor/bhm207
12. Damoiseaux, J. S., Rombouts, S. A., Barkhof, F., Scheltens, P., Stam, C. J., Smith, S. M., et al. (2006). Consistent resting-state networks across healthy subjects. Proc. Natl. Acad. Sci. U.S.A. 103, 13848-13853. doi: 10.1073/pnas.0601417103
13. Dansereau, C. L., Bellec, P., Lee, K., Pittau, F., Gotman, J., and Grova, C. (2014). Detection of abnormal resting-state networks in individual patients suffering from focal epilepsy: an initial step toward individual connectivity assessment. Front. Neurosci. 8:419. doi: 10.3389/fnins.2014.00419
14. Desikan, R. S., Segonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., et al. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31, 968-980. doi: 10.1016/j.neuroimage.2006.01.021
15. Eickhoff, S. B., Stephan, K. E., Mohlberg, H., Grefkes, C., Fink, G. R., Amunts, K., et al. (2005). A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data. Neuroimage 25, 1325-1335. doi: 10.1016/j.neuroimage.2004.12.034
16. Erhardt, E. B., Allen, E. A., Wei, Y., Eichele, T., and Calhoun, V. D. (2012). SimTB, a simulation toolbox for fMRI data under a model of spatiotemporal separability. Neuroimage 59, 4160-4167. doi: 10.1016/j.neuroimage.2011.11.088
17. Esposito, F., Scarabino, T., Hyvarinen, A., Himberg, J., Formisano, E., Comani, S., et al. (2005). Independent component analysis of fMRI group studies by self-organizing clustering. Neuroimage 25, 193-205. doi: 10.1016/j.neuroimage.2004.10.042
18. Filippini, N., MacIntosh, B. J., Hough, M. G., Goodwin, G. M., Frisoni, G. B., Smith, S. M., et al. (2009). Distinct patterns of brain activity in young carriers of the APOE-epsilon4 allele. Proc. Natl. Acad. Sci. U.S.A. 106, 7209-7214. doi: 10.1073/pnas.0811879106
19. Fox, M. D., and Raichle, M. E. (2007). Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat. Rev. Neurosci. 8, 700-711. doi: 10.1038/nrn2201
20. Friston, K. J., Buechel, C., Fink, G. R., Morris, J., Rolls, E., and Dolan, R. J. (1997). Psychophysiological and modulatory interactions in neuroimaging. Neuroimage 6, 218-229. doi: 10.1006/nimg.1997.0291
21. Guo, Y., and Pagnoni, G. (2008). A unified framework for group independent component analysis for multi-subject fMRI data. Neuroimage 42, 1078-1093. doi: 10.1016/j.neuroimage.2008.05.008
22. Himberg, J., Hyvarinen, A., and Esposito, F. (2004). Validating the independent components of neuroimaging time series via clustering and visualization. Neuroimage 22, 1214-1222. doi: 10.1016/j.neuroimage.2004.03.027
23. Hyvarinen, A. (1999). Fast and robust fixed-point algorithms for independent component analysis. IEEE Trans. Neural Netw. 10, 626-634. doi: 10.1109/72.761722
24. Hyvarinen, A. (2011). Testing the ICA mixing matrix based on inter-subject or inter-session consistency. Neuroimage 58, 122-136. doi: 10.1016/j.neuroimage.2011.05.086
25. Hyvarinen, A., and Oja, E. (2000). Independent component analysis: algorithms and applications. Neural Netw. 13, 411-430. doi: 10.1016/S0893-6080(00)00026-5
26. Hyvarinen, A., and Ramkumar, P. (2013). Testing independent component patterns by inter-subject or inter-session consistency. Front. Hum. Neurosci. 7:94. doi: 10.3389/fnhum.2013.00094
27. Lang, S. (1987). Calculus of Several Variables. New York, NY: Springer-Verlag.
28. Lukic, A., Wernick, M. N., Hansen, L. K., and Strother, S. C. (2002). "A spatially Robust ICA algorithm for multiple fMRI data sets" in IEEE International Symposium on Biomedical Imaging (Washington, DC), 839-842.
29. Ma, L., Narayana, S., Robin, D. A., Fox, P. T., and Xiong, J. (2011). Changes occur in resting state network of motor system during 4 weeks of motor skill learning. Neuroimage 58, 226-233. doi: 10.1016/j.neuroimage.2011.06.014
30. Maneshi, M., Vahdat, S., Fahoum, F., Grova, C., and Gotman, J. (2014). Specific resting-state brain networks in mesial temporal lobe epilepsy. Front. Neurol. 5:127. doi: 10.3389/fneur.2014.00127
31. McKeown, M. J., Li, J., Huang, X., Lewis, M. M., Rhee, S., Young Truong, K. N., et al. (2007). Local linear discriminant analysis (LLDA) for group and region of interest (ROI)-based fMRI analysis. Neuroimage 37, 855-865. doi: 10.1016/j.neuroimage.2007.04.072
32. Palmer, S. J., Li, J., Wang, Z. J., and McKeown, M. J. (2010). Joint amplitude and connectivity compensatory mechanisms in Parkinson's disease. Neuroscience 166, 1110-1118. doi: 10.1016/j.neuroscience.2010.01.012
33. Schopf, V., Windischberger, C., Kasess, C. H., Lanzenberger, R., and Moser, E. (2010). Group ICA of resting-state data: a comparison. MAGMA 23, 317-325. doi: 10.1007/s10334-010-0212-0
34. Sui, J., Adali, T., Pearlson, G. D., and Calhoun, V. D. (2009a). An ICA-based method for the identification of optimal FMRI features and components using combined group-discriminative techniques. Neuroimage 46, 73-86. doi: 10.1016/j.neuroimage.2009.01.026
35. Sui, J., Adali, T., Pearlson, G. D., Clark, V. P., and Calhoun, V. D. (2009b). A method for accurate group difference detection by constraining the mixing coefficients in an ICA framework. Hum. Brain Mapp. 30, 2953-2970. doi: 10.1002/hbm.20721
36. Vahdat, S., Darainy, M., and Ostry, D. J. (2014). Structure of plasticity in human sensory and motor networks due to perceptual learning. J. Neurosci. 34, 2451-2463. doi: 10.1523/JNEUROSCI.4291-13.2014
37. Vahdat, S., Maneshi, M., Grova, C., Gotman, J., and Milner, T. E. (2012). Shared and specific independent components analysis for between-group comparison. Neural Comput. 24, 3052-3090. doi: 10.1162/NECO_a_00355
38. Varoquaux, G., Sadaghiani, S., Pinel, P., Kleinschmidt, A., Poline, J. B., and Thirion, B. (2010). A group model for stable multi-subject ICA on fMRI datasets. Neuroimage 51, 288-299. doi: 10.1016/j.neuroimage.2010.02.010
39. Yang, Z., Zuo, X. N., Wang, P., Li, Z., LaConte, S. M., Bandettini, P. A., et al. (2012). Generalized RAICAR: discover homogeneous subject (sub)groups by reproducibility of their intrinsic connectivity networks. Neuroimage 63, 403-414. doi: 10.1016/j.neuroimage.2012.06.060
40. Zhang, Z., Lu, G., Zhong, Y., Tan, Q., Liao, W., Wang, Z., et al. (2010). Altered spontaneous neuronal activity of the default-mode network in mesial temporal lobe epilepsy. Brain Res. 1323, 152-160. doi: 10.1016/j.brainres.2010.01.042