Validating MEG estimated resting-state connectome with intracranial EEG.

IF 3.6 3区 医学 Q2 NEUROSCIENCES
Network Neuroscience Pub Date : 2025-03-20 eCollection Date: 2025-01-01 DOI:10.1162/netn_a_00441
Jawata Afnan, Zhengchen Cai, Jean-Marc Lina, Chifaou Abdallah, Giovanni Pellegrino, Giorgio Arcara, Hassan Khajehpour, Birgit Frauscher, Jean Gotman, Christophe Grova
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引用次数: 0

Abstract

Magnetoencephalography (MEG) is widely used for studying resting-state brain connectivity. However, MEG source imaging is ill posed and has limited spatial resolution. This introduces source-leakage issues, making it challenging to interpret MEG-derived connectivity in resting states. To address this, we validated MEG-derived connectivity from 45 healthy participants using a normative intracranial EEG (iEEG) atlas. The MEG inverse problem was solved using the wavelet-maximum entropy on the mean method. We computed four connectivity metrics: amplitude envelope correlation (AEC), orthogonalized AEC (OAEC), phase locking value (PLV), and weighted-phase lag index (wPLI). We compared spatial correlation between MEG and iEEG connectomes across standard canonical frequency bands. We found moderate spatial correlations between MEG and iEEG connectomes for AEC and PLV. However, when considering metrics that correct/remove zero-lag connectivity (OAEC/wPLI), the spatial correlation between MEG and iEEG connectomes decreased. MEG exhibited higher zero-lag connectivity compared with iEEG. The correlations between MEG and iEEG connectomes suggest that relevant connectivity patterns can be recovered from MEG. However, since these correlations are moderate/low, MEG connectivity results should be interpreted with caution. Metrics that correct for zero-lag connectivity show decreased correlations, highlighting a trade-off; while MEG may capture more connectivity due to source-leakage, removing zero-lag connectivity can eliminate true connections.

脑电对脑磁图估计静息状态连接体的验证。
脑磁图(MEG)被广泛用于研究静息状态下大脑的连通性。然而,MEG源成像是病态的,空间分辨率有限。这就引入了源泄漏问题,使得在静息状态下解释meg衍生的连接变得具有挑战性。为了解决这个问题,我们使用规范的颅内脑电图(iEEG)图谱验证了45名健康参与者的meg衍生连通性。采用小波最大熵均值法求解脑磁图逆问题。我们计算了四个连通性指标:幅度包络相关性(AEC)、正交化AEC (OAEC)、相位锁定值(PLV)和加权相位滞后指数(wPLI)。我们比较了MEG和ieeeg连接体在标准规范频带上的空间相关性。我们发现脑电图和脑电图连接体在AEC和PLV之间存在适度的空间相关性。然而,当考虑纠正/消除零滞后连接(OAEC/wPLI)的指标时,MEG和iEEG连接体之间的空间相关性下降。与iEEG相比,MEG表现出更高的零滞后连通性。脑磁图和脑电图连接体之间的相关性表明,脑磁图可以恢复相关的连接模式。然而,由于这些相关性是中等/低的,因此应该谨慎地解释MEG连接结果。校正零延迟连接的指标显示相关性降低,突出了一种权衡;虽然由于源泄漏,MEG可能捕获更多的连接,但去除零滞后连接可以消除真正的连接。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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
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