Blanchard Solenna, Saillet Sandrine, Ivanov Anton, Benquet Pascal, Bénar Christian-George, Pélégrini-Issac Mélanie, Benali Habib, Wendling Fabrice
Université de Rennes 1, INSERM U1099, Laboratoire Traitement du Signal et de l'Image, Rennes, France.
Aix Marseille Université, INSERM UMRS 1106, Institut de Neurosciences des Systèmes, Marseille, France.
PLoS One. 2016 Feb 5;11(2):e0147292. doi: 10.1371/journal.pone.0147292. eCollection 2016.
Developing a clear understanding of the relationship between cerebral blood flow (CBF) response and neuronal activity is of significant importance because CBF increase is essential to the health of neurons, for instance through oxygen supply. This relationship can be investigated by analyzing multimodal (fMRI, PET, laser Doppler…) recordings. However, the important number of intermediate (non-observable) variables involved in the underlying neurovascular coupling makes the discovery of mechanisms all the more difficult from the sole multimodal data. We present a new computational model developed at the population scale (voxel) with physiologically relevant but simple equations to facilitate the interpretation of regional multimodal recordings. This model links neuronal activity to regional CBF dynamics through neuro-glio-vascular coupling. This coupling involves a population of glial cells called astrocytes via their role in neurotransmitter (glutamate and GABA) recycling and their impact on neighboring vessels. In epilepsy, neuronal networks generate epileptiform discharges, leading to variations in astrocytic and CBF dynamics. In this study, we took advantage of these large variations in neuronal activity magnitude to test the capacity of our model to reproduce experimental data. We compared simulations from our model with isolated epileptiform events, which were obtained in vivo by simultaneous local field potential and laser Doppler recordings in rats after local bicuculline injection. We showed a predominant neuronal contribution for low level discharges and a significant astrocytic contribution for higher level discharges. Besides, neuronal contribution to CBF was linear while astrocytic contribution was nonlinear. Results thus indicate that the relationship between neuronal activity and CBF magnitudes can be nonlinear for isolated events and that this nonlinearity is due to astrocytic activity, highlighting the importance of astrocytes in the interpretation of regional recordings.
深入了解脑血流量（CBF）反应与神经元活动之间的关系至关重要，因为脑血流量的增加对神经元的健康至关重要，例如通过提供氧气。这种关系可以通过分析多模态（功能磁共振成像、正电子发射断层扫描、激光多普勒……）记录来研究。然而，潜在的神经血管耦合中涉及的中间（不可观测）变量数量众多，使得仅从多模态数据中发现机制变得更加困难。我们提出了一种在群体尺度（体素）上开发的新计算模型，该模型使用生理相关但简单的方程，以促进对区域多模态记录的解释。该模型通过神经-胶质-血管耦合将神经元活动与区域脑血流量动态联系起来。这种耦合涉及一群称为星形胶质细胞的神经胶质细胞，它们在神经递质（谷氨酸和γ-氨基丁酸）循环中发挥作用，并对邻近血管产生影响。在癫痫中，神经网络会产生癫痫样放电，导致星形胶质细胞和脑血流量动态变化。在这项研究中，我们利用神经元活动幅度的这些巨大变化来测试我们模型再现实验数据的能力。我们将模型的模拟结果与孤立的癫痫样事件进行了比较，这些事件是在大鼠局部注射荷包牡丹碱后通过同步局部场电位和激光多普勒记录在体内获得的。我们发现低水平放电时神经元的贡献占主导，而高水平放电时星形胶质细胞的贡献显著。此外，神经元对脑血流量的贡献是线性的，而星形胶质细胞的贡献是非线性的。因此，结果表明，对于孤立事件，神经元活动与脑血流量幅度之间的关系可能是非线性的，并且这种非线性是由于星形胶质细胞的活动引起的，突出了星形胶质细胞在解释区域记录中的重要性。
