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功能性MRI延迟结构的时空特征与神经信号和大脑层次关系

Hyoungshin Choi^1,2, Yeongjun Park^3,4, Jong-Eun Lee^1,2

¹Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, 16419, Republic of Korea.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)

|August 28, 2025

概括

这项研究引入了休息状态功能磁共振成像 (rs-fMRI) 的延迟结构分析,以探索大脑动态. 研究结果揭示了fMRI延迟和神经参数之间的相关性, 提供了对大脑功能和自闭症谱系障碍等疾病的见解.

科学领域:

神经科学
大脑成像
计算生物学

背景情况:

休息状态功能磁共振成像 (rs-fMRI) 显示了内在的大脑活动.
传统的延迟分析仅限于宏观动态,使fMRI衍生的延迟结构未被探索.
了解fMRI信号的时空特征对于研究大脑过程至关重要.

研究的目的:

通过延迟结构分析研究fMRI信号的时空特征.
探索fMRI衍生的延迟结构的物理意义.
关联这些结构与神经参数和功能大脑组织.

主要方法:

对469名健康成年人的fMRI数据进行了延迟结构分析.
计算滞后交叉共变率和主要组件分析以生成延迟自向量.
用生物物理模型参数,时间/空间特征和功能梯度进行关联分析.

主要成果:

延迟特征与神经参数显著相关 (突触门,反复连接,激发/抑制平衡).
与内在神经时间尺度和主要功能性大脑轴 (感觉转移,视觉运动,多重需求任务负) 相关的自身向量.
延迟模型与皮层层次和内在神经信号模型保持一致.

结论:

延迟结构分析为了解fMRI信号的时空特征提供了一种新方法.
这些发现提供了脑信号延迟背后的生理学见解.
通过验证在自闭症谱系障碍中的临床影响.

关键词:

生物物理模型功能连接性梯度内在神经时间表延迟结构

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