School of Psychology, University of Auckland, Auckland, New Zealand.
Departments of Psychiatry and Neurology, Jena University Hospital, Jena, Germany.
Cogn Neurosci. 2021 Jul-Oct;12(3-4):155-162. doi: 10.1080/17588928.2020.1800617. Epub 2020 Sep 9.
Sex differences in brain anatomy have been described from early childhood through late adulthood, but without any clear consensus among studies. Here, we applied a machine learning approach to estimate 'Brain Sex' using a continuous (rather than binary) classifier in 162 boys and 185 girls aged between 5 and 18 years. Changes in the estimated sex differences over time at different age groups were subsequently calculated using a sliding window approach. We hypothesized that males and females would differ in brain structure already during childhood, but that these differences will become even more pronounced with increasing age, particularly during adolescence. Overall, the classifier achieved a good performance, with an accuracy of 80.4% and an AUC of 0.897 across all age groups. Assessing changes in the estimated sex with age revealed a growing difference between the sexes with increasing age. That is, the very large effect size of d = 1.2 which was already evident during childhood increased even further from age 11 onward, and eventually reached an effect size of d = 1.6 at age 17. Altogether these findings suggest a systematic sex difference in brain structure already during childhood, and a subsequent increase of this difference during adolescence.
大脑解剖结构的性别差异在儿童期到成年后期都有描述，但不同研究之间没有明确的共识。在这里，我们应用机器学习方法，使用连续（而不是二进制）分类器，对 162 名 5 至 18 岁的男孩和 185 名女孩进行“大脑性别”的估计。随后使用滑动窗口方法计算不同年龄组在不同时间点的估计性别差异变化。我们假设男性和女性在儿童时期的大脑结构就存在差异，但随着年龄的增长，这种差异会更加明显，特别是在青春期。总体而言，该分类器在所有年龄组的准确率为 80.4%，AUC 为 0.897，性能良好。评估随着年龄的增长估计性别变化表明，随着年龄的增长，男女之间的差异越来越大。也就是说，在儿童时期已经明显的非常大的效应量 d = 1.2 甚至在 11 岁以后进一步增加，最终在 17 岁时达到效应量 d = 1.6。总的来说，这些发现表明儿童期已经存在大脑结构的系统性性别差异，随后在青春期这种差异会进一步增加。
