# Gray-Matter Expansion of Social Brain Networks in Individuals High in Public Self-Consciousness
## 2 Materials and Methods
### VBM Analysis  
We performed a voxel-based morphometry (VBM) analysis. This was done to explore possible expansion in GM volume in individuals who score high on public and/or private SCS. We first visually inspected the anatomical images of all participants and confirmed the absence of observable structural abnormalities and motion artefacts. The data were then processed using Statistical Parametric Mapping (SPM12, Wellcome Centre for Human Neuroimaging, University College London, London, UK). All steps were carried out as recommended by [PERSON] (2010) [33]. First, the anatomical image obtained from each participant was segmented into GM, white matter (WM), cerebrospinal fluid (CSF), and nonbrain parts. The default settings in SPM12 were used for all parameters. Next, using diffeomorphic anatomical registration through exponentiated lie algebra (DARTEL), we generated GM and WM DARTEL templates on the basis of anatomical images obtained from all participants. We used DARTEL in the default settings implemented in SPM12. We then applied an affine transformation to the GM and WM DARTEL templates to align them with their tissue probability maps in Montreal Neurological Institute (MNI) standard space. A segmented GM image from each participant was then nonlinearly warped to the GM DARTEL template in MNI space (spatial normalization). The warped image was modulated by Jacobian determinants of the deformation field to preserve relative GM volume even after spatial normalization. The modulated image of each participant was then smoothed with an 8 mm full-width-at-half-maximum (FWHM) Gaussian kernel and resampled to a resolution of 1.5 \(\times\) 1.5 \(\times\) 1.5 mm\({}^{3}\) voxel size. In the group-level analysis, to identify brain regions in which GM volume was positively correlated with public and private SCS scores respectively, we performed multiple regression analysis in the whole brain using the individual GM images. We included individual public and private SCS scores as independent variables, as well as sex, age, handedness score, and intracerebral volume (sum of GM, WM, and CSF volumes) as nuisance covariates (i.e., effects of no interest), since these factors may have a significant effect on the results of a VBM analysis [19]. To exclusively select truly positive GM voxels by eliminating possible noise outside the brain and to increase statistical power by reducing search volumes, we generated a mask on the basis of our present data using the SPM Masking Toolbox [34] ([[http://www0.cs.ucl.ac.uk/staff/g.ridgway/masking/](http://www0.cs.ucl.ac.uk/staff/g.ridgway/masking/)]([http://www0.cs.ucl.ac.uk/staff/g.ridgway/masking/](http://www0.cs.ucl.ac.uk/staff/g.ridgway/masking/)); accessed on 18 March 2019). Thus, voxels outside of this mask were excluded from the analysis. We reported active voxels using a statistical height threshold of \(p<0.005\) and a statistical extent threshold of \(p<0.05\), corrected for multiple comparisons with the family-wise error rate (FWE) across the entire brain. For anatomical identification, we referenced the anatomical automatic labeling (AAL) atlas [35] and the cytoarchitectonic probability maps derived from the MNI standard brain in the SPM Anatomy Toolbox v2.2b [36]. Since the whole-brain analysis showed GM expansions in the emotion-related areas and the default mode networks in relation to the public SCS scores, we further examined the possibility of the existence of subfactors of the public self-consciousness that are particularly associated with these expansions. In this analysis, multiple regression analysis was performed with the same procedure as in the first multiple regression analysis except for independent variables. Within the five factors identified in the present factor analysis, we used individual factor scores of the three factors that were correlated with the public SCS score (correlation coefficient higher than 0.4) as independent variables.