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人类视觉皮层中的行波:一种基于脑磁图-脑电图模型的方法。

Traveling waves in the human visual cortex: An MEG-EEG model-based approach.

作者信息

Grabot Laetitia, Merholz Garance, Winawer Jonathan, Heeger David J, Dugué Laura

机构信息

Université Paris Cité, CNRS, Integrative Neuroscience and Cognition Center, Paris, France.

Laboratoire des Systèmes Perceptifs, Département d'études Cognitives, École normale supérieure, PSL University, CNRS, Paris, France.

出版信息

PLoS Comput Biol. 2025 Apr 17;21(4):e1013007. doi: 10.1371/journal.pcbi.1013007. eCollection 2025 Apr.

Abstract

Brain oscillations might be traveling waves propagating in cortex. Studying their propagation within single cortical areas has mostly been restricted to invasive measurements. Their investigation in healthy humans, however, requires non-invasive recordings, such as MEG or EEG. Identifying traveling waves with these techniques is challenging because source summation, volume conduction, and low signal-to-noise ratios make it difficult to localize cortical activity from sensor responses. The difficulty is compounded by the lack of a known ground truth in traveling wave experiments. Rather than source-localizing cortical responses from sensor activity, we developed a two-part model-based neuroimaging approach: (1) The putative neural sources of a propagating oscillation were modeled within primary visual cortex (V1) via retinotopic mapping from functional MRI recordings (encoding model); and (2) the modeled sources were projected onto MEG and EEG sensors to predict the resulting signal using a biophysical head model. We tested our model by comparing its predictions against the MEG-EEG signal obtained when participants viewed visual stimuli designed to elicit either fovea-to-periphery or periphery-to-fovea traveling waves or standing waves in V1, in which ground truth cortical waves could be reasonably assumed. Correlations on within-sensor phase and amplitude relations between predicted and measured data revealed good model performance. Crucially, the model predicted sensor data more accurately when the input to the model was a traveling wave going in the stimulus direction compared to when the input was a standing wave, or a traveling wave in a different direction. Furthermore, model accuracy peaked at the spatial and temporal frequency parameters of the visual stimulation. Together, our model successfully recovers traveling wave properties in cortex when they are induced by traveling waves in stimuli. This provides a sound basis for using MEG-EEG to study endogenous traveling waves in cortex and test hypotheses related with their role in cognition.

摘要

脑振荡可能是在皮层中传播的行波。对其在单个皮层区域内传播的研究大多局限于侵入性测量。然而,在健康人类中进行此类研究需要非侵入性记录,如脑磁图(MEG)或脑电图(EEG)。用这些技术识别行波具有挑战性,因为源总和、容积传导以及低信噪比使得从传感器响应中定位皮层活动变得困难。行波实验中缺乏已知的真实情况使这一困难更加复杂。我们没有从传感器活动中对皮层响应进行源定位,而是开发了一种基于模型的两部分神经成像方法:(1)通过功能磁共振成像记录的视网膜拓扑映射(编码模型),在初级视觉皮层(V1)内对传播振荡的假定神经源进行建模;(2)使用生物物理头部模型将建模的源投影到MEG和EEG传感器上,以预测产生的信号。我们通过将模型预测结果与参与者观看旨在在V1中引发从中央凹到周边或从周边到中央凹的行波或驻波的视觉刺激时获得的MEG - EEG信号进行比较,来测试我们的模型,在这种情况下可以合理假定真实的皮层波。预测数据与实测数据在传感器内相位和幅度关系上的相关性显示出良好的模型性能。至关重要的是,与输入为驻波或不同方向的行波相比,当模型的输入是沿刺激方向传播的行波时,模型对传感器数据的预测更准确。此外,模型准确性在视觉刺激的空间和时间频率参数处达到峰值。总之,当刺激中的行波诱发皮层中的行波特性时,我们的模型成功地恢复了这些特性。这为使用MEG - EEG研究皮层中的内源性行波以及测试与其在认知中的作用相关的假设提供了坚实的基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b093/12037073/c841cab25adc/pcbi.1013007.g001.jpg

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