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Updated: Nov 9, 2025

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI
Published on: November 27, 2019
Asymmetrical alterations of grey matter among psychiatric disorders: A systematic analysis by voxel-based activation
Kexin Huang1, Yafei Kang1, Zhongcheng Wu1
1School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China.
Abstract:
Schizophrenia (SZ), bipolar disorder (BD) and major depression disorder (MDD) have been regarded as highly diverged independent entities in current psychiatric diagnosis. However, ample new evidence suggests that they may have common biological traits. Neuroimaging studies showed that psychiatric disorders might associated with altered grey matter (GM) asymmetry compared to controls; however, the degree to which SZ, BD and MDD have common and/or distinct asymmetrical alterations in GM is still ambiguous. In this study, we analysed 169 voxel-based studies (including 3517 SZ patients, 1575 BD patients, 3280 MDD patients and 9733 controls) using activation likelihood estimation (ALE) meta-analysis to systematically review the existence of similar GM atrophy and asymmetrical alteration patterns among these psychiatric disorders, and the functional association between behaviour domains and topological alterations. We found that the right parahippocampal gyrus and left superior frontal gyrus showed commonly altered GM volume across all three illnesses, but did not identify common asymmetrical alteration. The asymmetrical alteration with leftward bias appeared in SZ and bipolar disorder at different locations, but more asymmetrical alteration with rightward bias appeared in MDD. Moreover, these changes have been confirmed to be associate with several symptoms and may have roles in functional networks. Our findings support the existence of common neurobiological damnification in these psychiatric disorders and provides valuable insights for the neural commonalties among different psychiatric disorders based on a large sample size.
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