A mean-field model of glutamate and GABA synaptic dynamics for functional MRS.
A mean-field model of glutamate and GABA synaptic dynamics for functional MRS.
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DOI：
10.1016/j.neuroimage.2022.119813
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发表时间：
2023-02-01
期刊：
影响因子：
5.7
通讯作者：
Trujillo-Barreto NJ
中科院分区：
文献类型：
--
作者：
Lea-Carnall CA;El-Deredy W;Stagg CJ;Williams SR;Trujillo-Barreto NJ
功能磁共振波谱（fMRS）的进展，使体内神经递质浓度的活性依赖性变化的量化。然而，在小于1分钟的短时间尺度内通过fMRS观察到的GABA和谷氨酸的大变化（>10%）的生理基础仍然不清楚，因为这种变化不能通过已知的合成或降解代谢途径来解释。相反，已经假设fMRS检测神经递质浓度的变化，因为它们从突触前囊泡（在那里它们基本上是不可见的）循环到细胞外和细胞溶质池（在那里它们是可检测的）。本文件使用的计算建模方法来证明这一假设的可行性。一个新的平均场模型的神经机制产生的fMRS信号在皮层体素。建议的宏观平均场模型是基于神经递质动力学的突触水平的微观描述。具体而言，GABA和谷氨酸被假定为在三个代谢池之间循环：包装在囊泡中;在突触间隙中活跃;以及在星形胶质细胞或神经元胞质溶胶中进行再循环和重新包装。来自该模型的计算模拟用于生成响应于不同类型的刺激（包括疼痛、视觉和电流刺激）的GABA和谷氨酸浓度的预测变化。细胞外和胞浆池的预测变化对应于经验fMRS数据中报告的变化。此外，该模型预测的GABA/谷氨酸的关系，从而抑制性刺激减少两种神经递质的选择性控制机制，而兴奋性刺激增加谷氨酸和减少GABA。所提出的模型之间的桥梁神经动力学和fMRS和谷氨酸和GABA fMRS信号的活动依赖性的变化提供了一个机械帐户。最后，这些结果表明，回波时间可能是一个重要的定时参数，可以利用最大限度地提高fMRS实验结果。
Advances in functional magnetic resonance spectroscopy (fMRS) have enabled the quantification of activity-dependent changes in neurotransmitter concentrations in vivo. However, the physiological basis of the large changes in GABA and glutamate observed by fMRS (>10%) over short time scales of less than a minute remain unclear as such changes cannot be accounted for by known synthesis or degradation metabolic pathways. Instead, it has been hypothesized that fMRS detects shifts in neurotransmitter concentrations as they cycle from presynaptic vesicles, where they are largely invisible, to extracellular and cytosolic pools, where they are detectable. The present paper uses a computational modelling approach to demonstrate the viability of this hypothesis. A new mean-field model of the neural mechanisms generating the fMRS signal in a cortical voxel is derived. The proposed macroscopic mean-field model is based on a microscopic description of the neurotransmitter dynamics at the level of the synapse. Specifically, GABA and glutamate are assumed to cycle between three metabolic pools: packaged in the vesicles; active in the synaptic cleft; and undergoing recycling and repackaging in the astrocytic or neuronal cytosol. Computational simulations from the model are used to generate predicted changes in GABA and glutamate concentrations in response to different types of stimuli including pain, vision, and electric current stimulation. The predicted changes in the extracellular and cytosolic pools corresponded to those reported in empirical fMRS data. Furthermore, the model predicts a selective control mechanism of the GABA/glutamate relationship, whereby inhibitory stimulation reduces both neurotransmitters, whereas excitatory stimulation increases glutamate and decreases GABA. The proposed model bridges between neural dynamics and fMRS and provides a mechanistic account for the activity-dependent changes in the glutamate and GABA fMRS signals. Lastly, these results indicate that echo-time may be an important timing parameter that can be leveraged to maximise fMRS experimental outcomes.
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