在不同成年年龄段对准开放性特征的特定人格网络特征的稳定性:机器学习分析
Shengwen Zhi1, Wentao Zhao1, Ruiping Wang2
1Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, Shanxi, China; Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
Biochemical and biophysical research communications
|June 23, 2023
概括
与开放性人格特征相关的休息状态大脑连接模式是稳定的,可以在成年期区分个人. 然而,这些网络特征显示了一些与年龄相关的变化,突出显示了大脑动态.
科学领域:
- 神经科学是一个神经科学.
- 心理学 心理学 心理学
- 认知科学 认知科学
背景情况:
- 休息状态功能连接 (rs-fC) 反映了与认知和行为相关的大脑动态.
- rs-fC提供了一个客观的人格评估方法,可能取代传统问卷.
- 在成年期 rs-fC 人格映射的稳定性仍未得到充分研究.
研究的目的:
- 为了确定与个性特征相关的大脑网络特征是否可以区分个体.
- 检查这些与人格相关的网络特征在早期和中期成年期的稳定性.
- 研究与人格相关的大脑功能连接模式的与年龄相关的变化.
主要方法:
- 利用了343名健康成年人的休息状态功能磁共振成像 (fMRI) 数据.
- 使用五大调查问卷评估人格.
- 员工支持向量机器 (SVM) 用于分类和基于网络的统计 (NBS) 用于网络分析.
主要成果:
- 与"开放"人格特征相关的网络特征表现出稳定性,并在早期和中期成年人群中有效区分个人.
- 分析显示,在不同成年时期,这些与人格相关的网络特征的年龄相关变化.
- 通过交叉验证,SVM成功地区分了具有高和低开放度分数的受试者.
结论:
- 大脑的功能连接模式,特别是开放性,在整个成年期提供了稳定而客观的个性衡量标准.
- 这些发现强调了大脑网络的动态性质以及它们与整个生命周期的人格的关系.
- 这项研究支持rs-fC在理解人格和大脑功能方面的应用.
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