A coherent neurobiological framework for functional neuroimaging provided by a model integrating compartmentalized energy metabolism
A coherent neurobiological framework for functional neuroimaging provided by a model integrating compartmentalized energy metabolism
复制标题
DOI：
10.1073/pnas.0605864104
复制
发表时间：
2007-03-06
影响因子：
11.1
通讯作者：
Costalat, Robert
中科院分区：
文献类型：
--
作者：
Aubert, Agnes;Pellerin, Luc;Costalat, Robert
近年来，功能性神经影像学经历了惊人的发展。奇怪的是，它的神经生物学基础仍然难以捉摸，导致围绕激活时发生的细胞机制的激烈争论，这可能有助于测量信号。利用建模方法，我们在这里提出了一个连贯的神经生物学框架，不仅解释了几个在体外和体内的观察，但也提供了一个生理基础来解释成像信号。首先，基于区室化能量代谢模型，我们表明体外观察到的NADH变化的复杂动力学可以通过两个细胞群体中不同的代谢反应来解释，这让人想起神经元和星形胶质细胞。第二，扩展应用的模型在体内的情况下，使我们能够重现的演变实质内的氧水平激活后，实验测量，而基本上不改变初始参数值。最后，将相同的模型应用于人类的功能性神经成像，我们能够确定功能性MRI记录的血氧水平依赖性反应的早期负成分，称为初始下降，关键取决于神经元的氧化反应，而信号的晚期方面对应于来自具有两种不同代谢谱的细胞类型的响应的组合，星形胶质细胞总之，我们的结果，获得这样的建模方法，支持的概念，神经元和神经胶质细胞的代谢反应形成的神经影像信号的重要组成部分。
Functional neuroimaging has undergone spectacular developments in recent years. Paradoxically, its neurobiological bases have remained elusive, resulting in an intense debate around the cellular mechanisms taking place upon activation that could contribute to the signals measured. Taking advantage of a modeling approach, we propose here a coherent neurobiological framework that not only explains several in vitro and in vivo observations but also provides a physiological basis to interpret imaging signals. First, based on a model of compartmentalized energy metabolism, we show that complex kinetics of NADH changes observed in vitro can be accounted for by distinct metabolic responses in two cell populations reminiscent of neurons and astrocytes. Second, extended application of the model to an in vivo situation allowed us to reproduce the evolution of intraparenchymal oxygen levels upon activation as measured experimentally without substantially altering the initial parameter values. Finally, applying the same model to functional neuroimaging in humans, we were able to determine that the early negative component of the blood oxygenation level-dependent response recorded with functional MRI, known as the initial dip, critically depends on the oxidative response of neurons, whereas the late aspects of the signal correspond to a combination of responses from cell types with two distinct metabolic profiles that could be neurons and astrocytes. In summary, our results, obtained with such a modeling approach, support the concept that both neuronal and glial metabolic responses form essential components of neuroimaging signals.