Jedynak Maciej, Troisi Lopez Emahnuel, Romano Antonella, Jirsa Viktor, David Olivier, Sorrentino Pierpaolo
Aix Marseille University, INSERM, INS, Institut de Neurosciences des Systèmes, Marseille, France.
Institute of Applied Sciences and Intelligent Systems of National Research Council, Pozzuoli, Italy.
Hum Brain Mapp. 2025 Feb 1;46(2):e70093. doi: 10.1002/hbm.70093.
Measuring propagation of perturbations across the human brain and their transmission delays is critical for network neuroscience, but it is a challenging problem that still requires advancement. Here, we compare results from a recently introduced, noninvasive technique of functional delays estimation from source-reconstructed electro/magnetoencephalography, to the corresponding findings from a large dataset of cortico-cortical evoked potentials estimated from intracerebral stimulations of patients suffering from pharmaco-resistant epilepsies. The two methods yield significantly similar probabilistic connectivity maps and signal propagation delays, in both cases characterized with Pearson correlations greater than 0.5 (when grouping by stimulated parcel is applied for delays). This similarity suggests a correspondence between the mechanisms underpinning the propagation of spontaneously generated scale-free perturbations (i.e., neuronal avalanches observed in resting state activity studied using magnetoencephalography) and the spreading of cortico-cortical evoked potentials. This manuscript provides evidence for the accuracy of the estimate of functional delays obtained noninvasively from reconstructed sources. Conversely, our findings show that estimates obtained from externally induced perturbations in patients capture physiological activities in healthy subjects. In conclusion, this manuscript constitutes a mutual validation between two modalities, broadening their scope of applicability and interpretation. Importantly, the capability to measure delays noninvasively (as per MEG) paves the way for the inclusion of functional delays in personalized large-scale brain models as well as in diagnostic and prognostic algorithms.
测量扰动在人脑中的传播及其传输延迟对于网络神经科学至关重要，但这是一个仍需改进的具有挑战性的问题。在这里，我们将一种最近引入的、从源重建的脑电图/脑磁图进行功能延迟估计的非侵入性技术的结果，与来自一组大型数据集的相应结果进行比较，该数据集是通过对药物难治性癫痫患者进行脑内刺激估计得到的皮质-皮质诱发电位。这两种方法产生了显著相似的概率连接图和信号传播延迟，在两种情况下，以大于0.5的皮尔逊相关性为特征（当按受刺激的脑区分组用于延迟时）。这种相似性表明，支撑自发产生的无标度扰动传播的机制（即使用脑磁图研究的静息状态活动中观察到的神经元雪崩）与皮质-皮质诱发电位的传播之间存在对应关系。本手稿为从重建源无创获得的功能延迟估计的准确性提供了证据。相反，我们的研究结果表明，从患者外部诱发的扰动获得的估计捕获了健康受试者的生理活动。总之，本手稿构成了两种方法之间的相互验证，拓宽了它们的适用范围和解释范围。重要的是，无创测量延迟的能力（如通过脑磁图）为在个性化大规模脑模型以及诊断和预后算法中纳入功能延迟铺平了道路。
