Machine learning of brain gray matter differentiates sex in a large forensic sample
Machine learning of brain gray matter differentiates sex in a large forensic sample
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DOI：
10.1002/hbm.24462
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发表时间：
2019-04-01
影响因子：
4.8
通讯作者：
Kiehl, Kent A.
中科院分区：
文献类型：
--
作者：
Anderson, Nathaniel E.;Harenski, Keith A.;Kiehl, Kent A.
男性和女性之间的差异已经在生物，心理和行为领域得到了广泛的记录。其中，反社会行为的比率和类型的性别差异仍然是人类最显著和最持久的模式之一。然而，反社会人群大脑中性别二态性的性质和程度仍然没有得到探索。在这里，我们试图使用机器学习来了解大样本（n= 1，300）中被监禁男性和女性之间大脑结构的性别差异。我们应用基于源的形态学，一种当代的多变量方法来量化用磁共振成像测量的灰质，并使用机器学习来分类性别。使用脑灰质体积和浓度的组成部分的模型能够区分男性和女性，具有大于93%的可推广的准确性。高度分化的成分包括眶额和额极区，女性比例较大，男性前内侧颞区比例较大。我们还提供了一个非法医健康对照样本的免费分析，并复制了我们93%的性别歧视。这些发现表明，男性和女性的大脑是高度可区分的。了解大脑中的性别差异对于阐明疾病的发病率和进展，精神病理学以及心理特征和行为差异的差异具有重要意义。这些差异的可靠性证实了性别作为大脑结构个体差异调节剂的重要性，并建议未来的研究应考虑性别特异性模型。
Differences between males and females have been extensively documented in biological, psychological, and behavioral domains. Among these, sex differences in the rate and typology of antisocial behavior remains one of the most conspicuous and enduring patterns among humans. However, the nature and extent of sexual dimorphism in the brain among antisocial populations remains mostly unexplored. Here, we seek to understand sex differences in brain structure between incarcerated males and females in a large sample (n=1,300) using machine learning. We apply source-based morphometry, a contemporary multivariate approach for quantifying gray matter measured with magnetic resonance imaging, and carry these parcellations forward using machine learning to classify sex. Models using components of brain gray matter volume and concentration were able to differentiate between males and females with greater than 93% generalizable accuracy. Highly differentiated components include orbitofrontal and frontopolar regions, proportionally larger in females, and anterior medial temporal regions proportionally larger in males. We also provide a complimentary analysis of a nonforensic healthy control sample and replicate our 93% sex discrimination. These findings demonstrate that the brains of males and females are highly distinguishable. Understanding sex differences in the brain has implications for elucidating variability in the incidence and progression of disease, psychopathology, and differences in psychological traits and behavior. The reliability of these differences confirms the importance of sex as a moderator of individual differences in brain structure and suggests future research should consider sex specific models.