Cahart Marie-Stephanie, Dell'Acqua Flavio, Giampietro Vincent, Cabral Joana, Timmers Maarten, Streffer Johannes, Einstein Steven, Zelaya Fernando, Williams Steven C R, O'Daly Owen
Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
NatBrainLab, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
Front Hum Neurosci. 2022 Nov 10;16:980280. doi: 10.3389/fnhum.2022.980280. eCollection 2022.
Leading Eigenvector Dynamics Analysis (LEiDA) is an analytic approach that characterizes brain activity recorded with functional Magnetic Resonance Imaging (fMRI) as a succession of discrete phase-locking patterns, or states, that consistently recur over time across all participants. LEiDA allows for the extraction of three state-related measures which have previously been key to gaining a better understanding of brain dynamics in both healthy and clinical populations: the probability of occurrence of a given state, its lifetime and the probability of switching from one state to another. The degree to which test-retest reliability of the LEiDA measures may be affected by increasing MRI multiband (MB) factors in comparison with single band sequences is yet to be established. In this study, 24 healthy older adults were scanned over three sessions, on weeks 0, 1, and 4. On each visit, they underwent a conventional single band resting-state fMRI (rs-fMRI) scan and three different MB rs-fMRI scans, with MB factors of 4, with and without in-plane acceleration, and 6 without in-plane acceleration. We found test-retest reliability scores to be significantly higher with MB factor 4 with and without in-plane acceleration for most cortical networks. These findings will inform the choice of acquisition parameters for future studies and clinical trials.
主导特征向量动力学分析(LEiDA)是一种分析方法,它将功能磁共振成像(fMRI)记录的大脑活动表征为一系列离散的锁相模式或状态,这些模式或状态在所有参与者中随时间持续反复出现。LEiDA允许提取三种与状态相关的测量指标,这些指标以前是更好地理解健康人群和临床人群大脑动力学的关键:给定状态出现的概率、其持续时间以及从一种状态转换到另一种状态的概率。与单波段序列相比,LEiDA测量指标的重测信度受磁共振成像多波段(MB)因子增加的影响程度尚未确定。在本研究中,24名健康老年人在第0周、第1周和第4周的三个时间段接受扫描。每次就诊时,他们都接受一次传统的单波段静息态fMRI(rs-fMRI)扫描和三次不同的MB rs-fMRI扫描,MB因子分别为4(有无平面内加速)和6(无平面内加速)。我们发现,对于大多数皮质网络,MB因子为4(有无平面内加速)时,重测信度得分显著更高。这些发现将为未来研究和临床试验的采集参数选择提供参考。