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多时间尺度的动态有效大脑网络揭示了患有严重抑郁症的个体的加速大脑衰老

Shanling Ji¹, Shutang Zhao¹, Yang Tian²

¹School of Mental Health, Jining Medical University, Shandong Province, China.

Journal of psychiatric research

|February 21, 2026

概括

多时间尺度动态有效大脑网络 (MTS-DEBN) 提高了大脑年龄预测的准确性. 这种方法揭示了主要抑郁症 (MDD) 患者的加速大脑衰老,这表明它可以被用作神经精神疾病的生物标志物.

科学领域:

神经成像是一种神经成像.
计算神经科学是一种神经科学.
精神病学是一个精神病学.

背景情况:

大脑年龄估计是大脑健康的关键生物标志物,但面临着准确性挑战.
大型抑郁症 (MDD) 与不典型的大脑衰老模式有关.
休息状态功能磁共振成像 (rs-fMRI) 对于研究大脑功能至关重要.

研究的目的:

调查多时间尺度动态有效大脑网络 (MTS-DEBN) 的潜力,以提高大脑年龄预测.
使用MTS-DEBN识别MDD中的非典型衰老模式.
评估MTS-DEBN在区分健康对照和MDD患者中的实用性.

主要方法:

分析了80名健康对照 (HC) 和80名MDD患者的rs-fMRI数据.
动态有效的大脑网络在四个时间尺度上使用粗粒度算法构建.
在HC数据上训练的支持向量回归模型预测了MDD组中的大脑年龄.

主要成果:

综合特征集 (ALL) 在HC中实现了最高的预测准确性 (MAE = 3.64年).
与HC (1.96年) 相比,当前的MDD (4.56年) 和缓解的MDD (3.16年) 中观察到大脑年龄差距 (BAG) 显著更高.
在当前和缓解的MDD之间没有发现BAG的显著差异,也没有与抑郁症持续时间或严重程度的相关性.

结论:

MTS-DEBN显著提高了大脑年龄预测的准确性.
加速的大脑衰老在当前和缓解的MDD患者中都很明显.
MTS-DEBN 作为一种敏感的生物标志物,用于追踪神经精神疾病中大脑衰老动态和治疗效果.

关键词:

大脑衰老的老化动态有效的大脑网络.大型抑郁症主要是抑郁症.多个时间尺度的时间尺度.

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