大脑表现型模型对于挑战样本刻板印象的人来说是失败的
Abigail S Greene1,2, Xilin Shen3, Stephanie Noble3
1Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA. abigail.greene@yale.edu.
Nature
|August 24, 2022
概括
当个体偏离刻板印象时, 大脑表型模型会失败. 这项研究揭示了社会人口和临床因素如何影响这些模型, 阻碍基于大脑的准确预测和个性化干预.
科学领域:
- 神经科学
- 认知科学
- 数据科学
背景情况:
- 个体大脑功能组织的差异与各种特征和行为有关.
- 当前的线性大脑表型模型通常假定具有普遍适用性,但在个体之间表现出可变的性能.
- 了解模型失败对于发展强大而公正的脑表型关系至关重要.
研究的目的:
- 调查为什么以及在谁中大脑表型关系的预测模型失败.
- 识别导致一般化大脑表型模型失败的因素.
- 为提高脑表型模型的准确性和实用性提出框架.
主要方法:
- 使用独立数据集的预测建模,培训和测试,以确保可通用性.
- 在异质数据集中应用数据驱动方法来进行神经认知测量,并在两个外部数据集中进行复制.
- 分析了与社会人口统计学和临床共变量相关的模型失败模式.
主要成果:
- 大脑表型模型反映了刻板印象的形状,而不是统一的认知构造.
- 模型失败与神经认知得分偏离预期的社会人口和临床特征的个体有关.
- 模型失败是可靠的,表型特定的,并且可以在不同的数据集中概括.
结论:
- 一种适合所有人的大脑表型建模的方法受到偏见的表型措施的限制.
- 在模型中嵌入的刻板印象形状,当应用到不同个体时会导致失败.
- 提出了一个新的框架来提高模型的可解释性,并确定临床干预的个性化神经点.
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