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突触前囊泡循环中的幂律适应性。

Power-law adaptation in the presynaptic vesicle cycle.

作者信息

Mikulasch Fabian A, Georgiev Svilen V, Rudelt Lucas, Rizzoli Silvio O, Priesemann Viola

机构信息

Max-Planck-Institute for Dynamics and Self-Organization, Göttingen, Germany.

University Medical Center Göttingen, Institute for Neuro- and Sensory Physiology, Göttingen, Germany.

出版信息

Commun Biol. 2025 Apr 2;8(1):542. doi: 10.1038/s42003-025-07956-6.

Abstract

After synaptic transmission, fused synaptic vesicles are recycled, enabling the synapse to recover its capacity for renewed release. The recovery steps, which range from endocytosis to vesicle docking and priming, have been studied individually, but it is not clear what their impact on the overall dynamics of synaptic recycling is, and how they influence signal transmission. Here we model the dynamics of vesicle recycling and find that the multiple timescales of the recycling steps are reflected in synaptic recovery. This leads to multi-timescale synapse dynamics, which can be described by a simplified synaptic model with 'power-law' adaptation. Using cultured hippocampal neurons, we test this model experimentally, and show that the duration of synaptic exhaustion changes the effective synaptic recovery timescale, as predicted by the model. Finally, we show that this adaptation could implement a specific function in the hippocampus, namely enabling efficient communication between neurons through the temporal whitening of hippocampal spike trains.

摘要

突触传递后,融合的突触小泡会被循环利用,使突触恢复再次释放神经递质的能力。从内吞作用到小泡对接和启动的恢复步骤已被分别研究,但它们对突触循环的整体动力学有何影响,以及如何影响信号传递尚不清楚。在这里,我们对小泡循环的动力学进行建模,发现循环步骤的多个时间尺度反映在突触恢复中。这导致了多时间尺度的突触动力学,可用具有“幂律”适应的简化突触模型来描述。我们使用培养的海马神经元对该模型进行了实验测试,并表明突触耗尽的持续时间会改变有效的突触恢复时间尺度,正如模型所预测的那样。最后,我们表明这种适应可能在海马体中实现特定功能,即通过海马体尖峰序列的时间白化实现神经元之间的高效通信。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/538e/11965563/e0f455dc951c/42003_2025_7956_Fig1_HTML.jpg

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