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在通过机器学习进行视网膜脱落的患者中,主要视觉皮层的异常动态功能和有效连接性变化

Yu Ji¹, Yuan-Yuan Wang², Qi Cheng¹

¹Departments of Ophthalmology.

|October 18, 2024

概括

视网膜脱落 (RD) 患者表现出大脑连接的改变,特别是在视觉皮层. 动态功能连接 (dFC) 的这些变化可能有助于诊断RD,并影响视觉处理.

科学领域:

神经科学是一个神经科学.
医疗成像医学成像
眼科医生眼科眼科

背景情况:

以前的研究表明,视网膜脱落 (RD) 患者的大脑活动发生变化,重点关注局部变化.
在RD患者中,初级视觉皮层 (V1) 内的定向功能连接性尚不清楚.

研究的目的:

研究RD患者在V1区域内动态功能连接 (dFC) 的方向变化.
通过机器学习探索这些连接变化的诊断潜力.

主要方法:

基于种子的功能连接性和格兰杰因果分析被用来评估dFC和动态有效连接性 (dEC).
一个支持向量机算法分类了RD患者和健康对照 (HCs).

主要成果:

在视觉网络 (VN) 和默认模式网络 (DMN) 之间以及在VN内,RD患者的dFC/dEC呈现较高.
观察到VN与听觉网络 (AN) 之间的dFC降低,VN与感觉运动网络 (SMN) 之间的dEC降低.
从左侧V1区域的dFC变化实现了0.786的诊断AUC.

结论:

在RD患者中存在VN-DMN连接的显著变化,可能会影响视觉处理和认知.
改变的左V1连接和全脑dFC显示了RD的诊断前景.
研究结果提供了对 RD 中视觉和认知障碍的神经机制的见解.

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