Sundqvist Nicolas, Podéus Henrik, Sten Sebastian, Engström Maria, Dura-Bernal Salvador, Cedersund Gunnar
Department of Biomedical Engineering, Linköping University, Linköping, Sweden.
Drug Metabolism and Pharmacokinetics, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden.
bioRxiv. 2024 Oct 17:2024.10.15.618416. doi: 10.1101/2024.10.15.618416.
Functional magnetic resonance imaging (fMRI) is a pivotal tool for mapping neuronal activity in the brain. Traditionally, the observed hemodynamic changes are assumed to reflect the activity of the most common neuronal type: excitatory neurons. In contrast, recent experiments, using optogenetic techniques, suggest that the fMRI-signal instead reflects the activity of inhibitory interneurons. However, these data paint a complex picture, with numerous regulatory interactions, and where the different experiments display many qualitative differences. It is therefore not trivial how to quantify the relative contributions of the different cell types and to combine all observations into a unified theory. To address this, we present a new model-driven meta-analysis, which provides a unified and quantitative explanation for all data. This model-driven analysis allows for quantification of the relative contribution of different cell types: the contribution to the BOLD-signal from the excitatory cells is <20 % and 50-80 % comes from the interneurons. Our analysis also provides a mechanistic explanation for the observed experiment-to-experiment differences, e.g. a biphasic vascular response dependent on different stimulation intensities and an emerging secondary post-stimulation peak during longer stimulations. In summary, our study provides a new, emerging consensus-view supporting the larger role of interneurons in fMRI.
功能磁共振成像(fMRI)是绘制大脑神经元活动图谱的关键工具。传统上,观察到的血液动力学变化被认为反映了最常见的神经元类型——兴奋性神经元的活动。相比之下,最近使用光遗传学技术进行的实验表明,fMRI信号反而反映了抑制性中间神经元的活动。然而,这些数据呈现出一幅复杂的图景,存在众多调节相互作用,而且不同实验显示出许多定性差异。因此,如何量化不同细胞类型的相对贡献并将所有观察结果整合为一个统一的理论并非易事。为了解决这个问题,我们提出了一种新的模型驱动的荟萃分析,它为所有数据提供了统一的定量解释。这种模型驱动的分析能够量化不同细胞类型的相对贡献:兴奋性细胞对血氧水平依赖(BOLD)信号的贡献小于20%,而50 - 80%来自中间神经元。我们的分析还为观察到的实验间差异提供了一种机制解释,例如,取决于不同刺激强度的双相血管反应以及在较长刺激期间出现的继发性刺激后峰值。总之,我们的研究提供了一种新的、正在形成的共识观点,支持中间神经元在fMRI中发挥更大作用。