@Article{cmes.2020.010796,
AUTHOR = {Lan Yang, Shun Qi, Chen Qiao, Yanmei Kang},
TITLE = {Exploring the Abnormal Brain Regions and Abnormal Functional Connections in SZ by Multiple Hypothesis Testing Techniques},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {125},
YEAR = {2020},
NUMBER = {1},
PAGES = {215--237},
URL = {http://www.techscience.com/CMES/v125n1/40214},
ISSN = {1526-1506},
ABSTRACT = {Schizophrenia (SZ) is one of the most common mental diseases. Its
main characteristics are abnormal social behavior and inability to correctly understand real things. In recent years, the magnetic resonance imaging (MRI) technique has been popularly utilized to study SZ. However, it is still a great challenge
to reveal the essential information contained in the MRI data. In this paper, we
proposed a biomarker selection approach based on the multiple hypothesis testing
techniques to explore the difference between SZ and healthy controls by using
both functional and structural MRI data, in which biomarkers represent both
abnormal brain functional connectivity and abnormal brain regions. By implementing the biomarker selection approach, six abnormal brain regions and
twenty-three abnormal functional connectivity in the brains of SZ are explored.
It is discovered that compared with healthy controls, the significantly reduced
gray matter volumes are mainly distributed in the limbic lobe and the basal
ganglia, and the significantly increased gray matter volumes are distributed in
the frontal gyrus. Meanwhile, it is revealed that the significantly strengthened
connections are those between the middle frontal gyrus and the superior occipital gyrus, the superior occipital gyrus and the middle occipital gyrus as well as
the middle occipital gyrus and the fusiform gyrus, and the rest connections are
significantly weakened.},
DOI = {10.32604/cmes.2020.010796}
}