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Page 2 of 10 Zarei. Neuroimmunol Neuroinflammation 2018;5:13 I http://dx.doi.org/10.20517/2347-8659.2018.02

INTRODUCTION
Schizophrenia is a severe mental disorder, affecting ~1% of the population . Recent studies have shown
[1,2]
dysfunction of the precentral gyrus (PreCG) has long been thought to play a role in the impairments of
voluntary movement associated with Schizophrenia and it has significantly reduced functional activity
(FC) in patients with schizophrenia . Also, schizophrenia is associated with volume deficits in PreCG .
[3,4]
[5]
Another research indicates the patients with schizophrenia showed lower activation in left PreCG than right
PreCG and a regional homogeneity (ReHo) study showed decreased ReHo in right precentral gyrus . In
[6]
[7]
this research, we examined the PreCG functional connectivity impairment in patients with schizophrenia
using ROI based analysis . We used the Center for Biomedical Research Excellence data set (COBRE)
[8]
[9]
to demonstrate how the functional connectivity of the PreCG with the rest of the brain regions changes
in schizophrenia. In conjunction with previous studies [10-13] , our results indicate the PreCG has abnormal
connectivity with brain regions like Thalamus and Hippocampus, but these impairments are not similar
in two hemispheres. We also analyzed the functional connectivity differences between male and female
patients with schizophrenia and showed the regions like Thalamus are more affected in the female patients
with schizophrenia.

METHODS
Data
Two groups of subjects from the COBRE data set are used to examine the aberrant functional brain
connectome in schizophrenia. COBRE data set contains raw anatomical and functional MRI data from
patients with schizophrenia and healthy controls. Some papers that by the COBRE group published on this
data [14-16] . This data set is available on and contains raw anatomical and functional MR data from patients
with Schizophrenia and healthy controls, ranging in age from 18 to 65 years old. Resting fMRI, anatomical
MRI, phenotype data for every participant including gender, age, handedness and diagnostic information
are released . More details about the COBRE data set can be found in the Table 1.
[17]
Analysis
Different preprocessing methods like realignment , coregistering, normalization are applied to the
[18]
structural and functional data. The functional volumes are coregistered with the region of interest and
structural volumes [19,20] . Regions of interest and all the Brodmann areas defined by the Talairach daemon
assigned to all subjects. By segmentation of structural image for each subject, grey matter, white matter
and cerebrospinal fluid (CSF) mask generated. Here, the time series of interest are numbers of PCA
components.

First and second level of covariates
In this step, the realignment parameters in Blood-Oxygen-Level-Dependent (BOLD) model is defined (the
first level covariate), then in the second level covariate, the group level regressor is performed. We categorized
the data input data into 4 groups: females and males healthy control, females and males patients with
schizophrenia. After defining the experimental data, the functional data is imported, then the structural data
segmented to define the grey matter, white matter, the cerebrospinal fluid region of interest. By performing
principal component analysis (PCA) on within region of interests the ROIs time series is extracted.

Data preprocessing
Before analyzing the data, we need to explore and remove the confound. The different source of possible
confounds like cerebrospinal fluid and white matter signal and within-subject covariate (realignment
parameters) are considered. We chose the 5-dimension numbers of temporal components are being used.
Similarly, numbers of dimension for the white matter was 5 and the derivative order was 0 and the histogram