Djimbouon Frank, Stoyanov Drozdstoy, Çatal Yasir, Paunova Rossitsa, Northoff Georg
Mind, Brain Imaging and Neuroethics Research Unit, The Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada.
Division of Translational Neuroscience, Research Institute at Medical University of Plovdiv, 4002 Plovdiv, Bulgaria; Strategic Research and Innovation Program for the Development of MU - PLOVDIV - (SRIPD - MUP), Creation of a Network of Research Higher Schools, National Plan for Recovery and Sustainability, European Union - NextGenerationEU, Bulgaria; Department of Psychiatry and Medical Psychology, Medical University of Plovdiv, 4002 Plovdiv, Bulgaria.
J Affect Disord. 2025 Dec 1;390:119775. doi: 10.1016/j.jad.2025.119775. Epub 2025 Jul 1.
Major Depressive Disorder (MDD) is characterized by widespread alterations in brain network organization, but the relationship between temporal dynamics and network connectivity remains poorly understood. We investigated how intrinsic neural timescales (INT), measured through the autocorrelation window (ACW), relate to functional connectivity (FC) in MDD during a disorder-specific task paradigm.
21 MDD patients, 19 schizophrenia patients (clinical comparison), and 21 healthy controls underwent fMRI scanning during a self-evaluation task. We analyzed temporal dynamics using ACW and examined FC using Network-Based Statistics. The relationship between ACW and FC was assessed using Bayesian modeling.
MDD patients showed significantly reduced ACW compared to controls, with the strongest reductions in Control (β = -0.264), Default Mode (β = -0.203), and Somatomotor (β = -0.177) networks. Network-Based Statistics revealed increased FC in MDD (243 unique connections) particularly within Default and Control networks. MDD patients exhibited a disorder-specific inverse relationship between ACW and FC (β = -0.119) that was absent in controls and contrasted with the positive relationship observed in schizophrenia patients (β = 0.189).
Our findings reveal that MDD involves both temporal dysregulation (shortened neural timescales) and spatial disruption (increased connectivity), with a specific alteration in how these properties are coupled. This suggests that MDD might be understood as involving disrupted integration of temporal and spatial brain dynamics, offering novel perspectives for biomarker development and therapeutic interventions targeting temporal processing abnormalities.
重度抑郁症（MDD）的特征是大脑网络组织广泛改变，但时间动态与网络连通性之间的关系仍知之甚少。我们研究了通过自相关窗口（ACW）测量的内在神经时间尺度（INT）在特定疾病任务范式期间如何与MDD中的功能连通性（FC）相关。
21名MDD患者、19名精神分裂症患者（临床对照）和21名健康对照在自我评估任务期间接受功能磁共振成像扫描。我们使用ACW分析时间动态，并使用基于网络的统计方法检查FC。使用贝叶斯模型评估ACW与FC之间的关系。
与对照组相比，MDD患者的ACW显著降低，在控制网络（β = -0.264）、默认模式网络（β = -0.203）和躯体运动网络（β = -0.177）中降低最为明显。基于网络的统计显示MDD中FC增加（243个独特连接），特别是在默认和控制网络内。MDD患者在ACW与FC之间表现出特定于疾病的负相关关系（β = -0.119），而对照组中不存在这种关系，且与精神分裂症患者中观察到的正相关关系（β = 0.189）形成对比。
我们的研究结果表明，MDD涉及时间失调（神经时间尺度缩短）和空间破坏（连通性增加），以及这些特性耦合方式的特定改变。这表明MDD可能被理解为涉及时间和空间大脑动态的整合中断，为生物标志物开发和针对时间处理异常的治疗干预提供了新的视角。
