高振幅网络协同波动与月经周期内激素浓度的变化有关。

IF 3.6 3区 医学 Q2 NEUROSCIENCES Network Neuroscience Pub Date : 2023-10-01 eCollection Date: 2023-01-01 DOI:10.1162/netn_a_00307
Sarah Greenwell, Joshua Faskowitz, Laura Pritschet, Tyler Santander, Emily G Jacobs, Richard F Betzel
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引用次数: 2

摘要

许多研究表明,人类内分泌系统调节大脑功能,报告了激素浓度波动与大脑连接之间的联系。然而,激素波动如何在短时间内影响大脑网络组织的快速变化仍然未知。在这里,我们利用最近提出的一个框架,在逐帧的时间尺度上对成对大脑区域的活动之间的共同波动进行建模。在之前的研究中,我们表明,与高振幅共同波动相对应的时间点对时间平均函数连接模式的贡献不成比例,并且这些共同波动模式可以聚集成一组低维的重复“状态”,我们评估了这些网络状态与激素浓度日常变化之间的关系。具体来说,我们感兴趣的是网络状态发生的频率是否与激素浓度有关。我们使用密集采样数据集(N=1大脑)解决了这个问题。在该数据集中,在两种内分泌状态下对单个个体进行采样:自然月经周期和受试者通过口服激素避孕药进行选择性孕酮抑制。在每个周期中,受试者每天接受30次静息状态fMRI扫描和抽血。我们对成像数据的分析揭示了两种重复的网络状态。我们发现,扫描过程中出现状态1的频率与卵泡刺激素和黄体生成素浓度显著相关。我们还仅使用“事件帧”(确定事件发生的时间点)为每个扫描会话构建了具有代表性的网络。我们发现,功能连接的特定亚群的权重不仅与黄体生成素和卵泡刺激激素的浓度波动密切相关,还与孕酮和雌二醇的浓度波动紧密相关。
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High-amplitude network co-fluctuations linked to variation in hormone concentrations over the menstrual cycle.

Many studies have shown that the human endocrine system modulates brain function, reporting associations between fluctuations in hormone concentrations and brain connectivity. However, how hormonal fluctuations impact fast changes in brain network organization over short timescales remains unknown. Here, we leverage a recently proposed framework for modeling co-fluctuations between the activity of pairs of brain regions at a framewise timescale. In previous studies we showed that time points corresponding to high-amplitude co-fluctuations disproportionately contributed to the time-averaged functional connectivity pattern and that these co-fluctuation patterns could be clustered into a low-dimensional set of recurring "states." Here, we assessed the relationship between these network states and quotidian variation in hormone concentrations. Specifically, we were interested in whether the frequency with which network states occurred was related to hormone concentration. We addressed this question using a dense-sampling dataset (N = 1 brain). In this dataset, a single individual was sampled over the course of two endocrine states: a natural menstrual cycle and while the subject underwent selective progesterone suppression via oral hormonal contraceptives. During each cycle, the subject underwent 30 daily resting-state fMRI scans and blood draws. Our analysis of the imaging data revealed two repeating network states. We found that the frequency with which state 1 occurred in scan sessions was significantly correlated with follicle-stimulating and luteinizing hormone concentrations. We also constructed representative networks for each scan session using only "event frames"-those time points when an event was determined to have occurred. We found that the weights of specific subsets of functional connections were robustly correlated with fluctuations in the concentration of not only luteinizing and follicle-stimulating hormones, but also progesterone and estradiol.

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来源期刊
Network Neuroscience
Network Neuroscience NEUROSCIENCES-
CiteScore
6.40
自引率
6.40%
发文量
68
审稿时长
16 weeks
期刊最新文献
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