Standardizing the intrinsic brain: towards robust measurement of inter-individual variation in 1000 functional connectomes - PubMed (original) (raw)

Standardizing the intrinsic brain: towards robust measurement of inter-individual variation in 1000 functional connectomes

Chao-Gan Yan et al. Neuroimage. 2013.

Abstract

As researchers increase their efforts to characterize variations in the functional connectome across studies and individuals, concerns about the many sources of nuisance variation present and their impact on resting state fMRI (R-fMRI) measures continue to grow. Although substantial within-site variation can exist, efforts to aggregate data across multiple sites such as the 1000 Functional Connectomes Project (FCP) and International Neuroimaging Data-sharing Initiative (INDI) datasets amplify these concerns. The present work draws upon standardization approaches commonly used in the microarray gene expression literature, and to a lesser extent recent imaging studies, and compares them with respect to their impact on relationships between common R-fMRI measures and nuisance variables (e.g., imaging site, motion), as well as phenotypic variables of interest (age, sex). Standardization approaches differed with regard to whether they were applied post-hoc vs. during pre-processing, and at the individual vs. group level; additionally they varied in whether they addressed additive effects vs. additive+multiplicative effects, and were parametric vs. non-parametric. While all standardization approaches were effective at reducing undesirable relationships with nuisance variables, post-hoc approaches were generally more effective than global signal regression (GSR). Across approaches, correction for additive effects (global mean) appeared to be more important than for multiplicative effects (global SD) for all R-fMRI measures, with the exception of amplitude of low frequency fluctuations (ALFF). Group-level post-hoc standardizations for mean-centering and variance-standardization were found to be advantageous in their ability to avoid the introduction of artifactual relationships with standardization parameters; though results between individual and group-level post-hoc approaches were highly similar overall. While post-hoc standardization procedures drastically increased test-retest (TRT) reliability for ALFF, modest reductions were observed for other measures after post-hoc standardizations-a phenomena likely attributable to the separation of voxel-wise from global differences among subjects (global mean and SD demonstrated moderate TRT reliability for these measures). Finally, the present work calls into question previous observations of increased anatomical specificity for GSR over mean centering, and draws attention to the near equivalence of global and gray matter signal regression.

Keywords: Data aggregation; Functional connectomics; Resting-state fMRI; Standardization; Test–retest reliability.

Copyright © 2013 Elsevier Inc. All rights reserved.

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Conflict of interest statement

Conflicts of interest

The authors declare that there are no conflicts of interest.

Figures

Fig. 1

Fig. 1

The impact of standardization procedures on site effects for the R-fMRI measures. The distribution of F values across voxels was plotted. Given the large amount of reducing site effects for the standardized measures, different scales were used on the non-standardized and standardized measures for ALFF, fALFF, ReHo and DC.

Fig. 2

Fig. 2

The impact of standardization procedures on motion effects for the R-fMRI measures. (A) The voxel-wise motion effects (estimated from the group analysis model) of the standardization procedures for each R-fMRI measure on surface brain (left hemisphere, with BrainNet Viewer,

http://www.nitrc.org/projects/bnv/

). (B) Box plots of the motion effects across gray matter. To demonstrate the change in motion effects of each standardization procedure from the non-standardized measure, the differences in z value (each standardization procedure minus non-standardized) were plotted.

Fig. 3

Fig. 3

The impact of standardization procedures on age effects for the R-fMRI measures. (A) The voxel-wise age effects (estimated from the group analysis model) of the standardization procedures for each R-fMRI measure on surface brain (left hemisphere). (B) Box plots of age effects across the gray matter voxels. To demonstrate the change in age effects of each standardization procedure from the non-standardized measure, the differences in z value (each standardization procedure minus non-standardized) were plotted.

Fig. 4

Fig. 4

The impact of standardization procedures on sex effects for the R-fMRI measures. (A) The voxel-wise sex effects (estimated from the group analysis model) of the standardization procedures for each R-fMRI measure on surface brain (left hemisphere). (B) Box plots of sex effects across the gray matter voxels. To demonstrate the change in sex effects of each standardization procedure from the non-standardized measure, the differences in z value (each standardization procedure minus non-standardized) were plotted.

Fig. 5

Fig. 5

The statistical differences between different standardization approaches across voxels in clusters exhibiting positive (+) and negative (−) associations with nuisance variable (motion) and signals of interest (age, sex). For each effect examined, we generated composite maps that represent the union of significant findings across the different post-hoc standardization approaches; positive and negative effect relationships were treated separately. Then, for each composite, Wilcoxon signed-rank test was performed across voxels to compare the statistical Z value between standardization approaches. Results were Bonferroni corrected to take into account the number of pairwise comparisons [3 (effects) * 2 (positive/negative) * 8 (number of standardization approaches) * 7 / 2 = 168]. Given differences in the number of voxels that may be included in a given composite map, we plot effect sizes (Wilcoxon's Z/N) which take into account the number of voxels across which the significance was determined.

Fig. 6

Fig. 6

The correlation between the standardized measure and the global mean (A) or global SD (B) within gray matter voxels. For each measure, the global mean (or global SD) of each subject was firstly extracted, and then correlated with all the voxels across subjects. The correlation distribution within the gray matter voxels was plotted for each standardization procedure.

Fig. 7

Fig. 7

The impact of standardization procedures on test–retest (TRT) reliability (indexed by intra-class correlation [ICC] based on NYU TRT dataset) for the R-fMRI measures. (A) The voxel-wise TRT reliability of the standardization procedures for each R-fMRI measure on surface brain (left hemisphere). (B) Box plots of the TRT reliability across the gray matter voxels. The differences in the ICC value (each standardization procedure minus non-standardized) were plotted in order to demonstrate the change in TRT reliability of each standardization procedure from the non-standardized measure.

Fig. 8

Fig. 8

The impact on group mean effects of within-subject standardization procedures for PCC-iFC (A) and MT-iFC (B). The MT seed is centered at [−47, −69, −3] (and converted from Talairach space to MNI space) as defined in Fox et al. (2009). The standardization was performed within the whole brain mask (upper row) or within the gray matter mask (bottom row) (axial slice on z = 27). The right panel demonstrates the voxel-wise distribution in T values (T values were used to avoid the inaccuracy of transforming extreme T values into Z values) within the gray matter mask (upper row), white matter mask (middle row) and whole brain (bottom row). Of note, the gray matter and white matter masks were specifically eroded for one voxel to avoid the partial voluming issue related to the gray matter/white matter boundary.

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