Department of Psychiatry, University of California San Diego, 9500 Gilman Drive #0603V, La Jolla, CA, 92093, USA.
San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA.
Brain Imaging Behav. 2019 Aug;13(4):945-952. doi: 10.1007/s11682-018-9912-2.
Academic performance in adolescence strongly influences adult prospects. Intelligence quotient (IQ) has historically been considered a strong predictor of academic performance. Less objectively explored have been morphometric features. We analyzed brain MRI morphometry metrics in early adolescence (age 12-14 years) as quantitative predictors of academic performance over high school using a naïve Bayesian classifier approach with n = 170 subjects. Based on the mean GPA, subjects were divided into high (GPA ≥3.54; n = 87) and low (GPA <3.54; n = 83) academic performers. Covariance analysis was performed to look at the influence of subject demographics. We examined predictive features from the 343 available regions (surface areas, cortical thickness, and subcortical volumes) and applied 4 algorithms for selection and reduction of attributes using Weka. Cortical thickness measures performed better than surface areas or subcortical volumes as predictors of academic performance. We identified 15 cortical thickness regions most predictive of academic performance, three of which have not been described in the literature predictive of academic performance. These were in the left hemisphere fusiform, bilateral insula, and left hemisphere paracentral regions. Prediction had a sensitivity of 0.65 and specificity of 0.73 with independent validation. Follow-up independent t-test analyses between high and low academic achievers on 10 of 15 regions showed between-group significance at the p < 0.05 level. High achievers demonstrated thicker cortices than low achievers. These newly identified regions may help pinpoint new targets for further study in understanding the developing adolescent brain in the classroom setting.
青少年时期的学业成绩对成年后的前景影响很大。智商（IQ）一直被认为是学业成绩的强有力预测指标。而形态特征则较少被客观地探讨。我们使用朴素贝叶斯分类器方法，对 170 名年龄在 12-14 岁的青少年进行了大脑 MRI 形态计量学测量，以研究这些测量值是否可以作为高中阶段学业成绩的预测指标。根据平均 GPA，我们将受试者分为高（GPA≥3.54；n=87）和低（GPA<3.54；n=83）学业成绩者。协方差分析用于观察受试者人口统计学特征的影响。我们从 343 个可用区域（表面积、皮质厚度和皮质下体积）中检查了预测特征，并使用 Weka 应用了 4 种选择和减少属性的算法。皮质厚度测量值作为学业成绩的预测指标比表面积或皮质下体积更有效。我们确定了 15 个最能预测学业成绩的皮质厚度区域，其中 3 个区域在预测学业成绩方面尚未在文献中描述过。这些区域位于左侧梭状回、双侧脑岛和左侧旁中央区域。独立验证的预测结果具有 0.65 的敏感性和 0.73 的特异性。对 15 个区域中的 10 个区域，对高学术成就者和低学术成就者进行的后续独立 t 检验分析显示，在 p<0.05 水平上存在组间差异。高成就者的皮质厚度比低成就者厚。这些新发现的区域可能有助于确定新的目标，以便进一步研究在课堂环境中了解发育中青少年大脑的情况。
