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文章基本信息

  • 标题:Effects of different intracranial volume correction methods on univariate sex differences in grey matter volume and multivariate sex prediction
  • 本地全文:下载
  • 作者:Carla Sanchis-Segura ; Maria Victoria Ibañez-Gual ; Naiara Aguirre
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2020
  • 卷号:10
  • 期号:1
  • DOI:10.1038/s41598-020-69361-9
  • 出版社:Springer Nature
  • 摘要:Sex differences in 116 local gray matter volumes (GMVOL) were assessed in 444 males and 444 females without correcting for total intracranial volume (TIV) or after adjusting the data with the scaling, proportions, power-corrected proportions (PCP), and residuals methods. The results confirmed that only the residuals and PCP methods completely eliminate TIV-variation and result in sex-differences that are “small” (∣d∣ 80%) when using raw local GMVOL, but also when using scaling or proportions adjusted-data or TIV as a single predictor. Conversely, after properly controlling TIV variation with the PCP and residuals’ methods, prediction accuracy dropped to $$ pprox $$ 60%. It is concluded that gross morphological differences account for most of the univariate and multivariate sex differences in GMVOL
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