https://doi.org/10.1140/epjs/s11734-025-01729-2
Regular Article
Adenosine triphosphate-mediated self-repairing astrocyte–neuron network model
1
Guangxi Key Lab of Brain-inspired Computing and Intelligent Chips, School of Electronic and Information Engineering, Guangxi Normal University, Guilin, China
2
Key Laboratory of Nonlinear Circuits and Optical Communications (Guangxi Normal University), Education Department of Guangxi Zhuang Autonomous Region, Guilin, China
Received:
15
April
2025
Accepted:
2
June
2025
Published online:
18
June
2025
Neuronal damage triggers the release of adenosine triphosphate (ATP), which activates nearby astrocytes and thereby induces glutamate release, modulating synaptic transmission and neuronal activity. To address the insufficient recovery of neuronal network activity in the previous self-repair model, this work proposes an adenosine triphosphate-mediated self-repairing astrocyte–neuron network (ATP-S-ANN) model, leveraging ATP and glutamate interactions to facilitate the repair of damaged synapses. The underlying principle of the proposed model is that ATP diffusion in damaged regions stimulates local glutamate release, enhancing the probability of presynaptic release (PR). This subsequently strengthens impaired network activity via glutamate-mediated postsynaptic slow inward currents (SICs), thereby enhancing damaged synaptic strength. The results demonstrate that the ATP-mediated glutamate signaling facilitates local self-repair through three key mechanisms: (1) increasing the PR of damaged synapses enhanced network activity by 12.44
compared to the previous self-repair model, improving network recovery and transmission efficiency; (2) glutamate-mediated postsynaptic SICs increase the activity of damaged networks by 4.28 compared to the original self-repair model, fostering communication and enhancing network recovery; and (3) postsynaptic SICs enhance the strength of damaged synapses, increasing the activity of damaged networks by 9 compared to earlier self-repair model and supporting the continued recovery of synaptic function. These results demonstrate that the proposed ATP-S-ANN effectively overcame the low recovery of neural network activity in the previous self-repair model through three mechanisms, highlighting the potential of ATP-mediated processes in restoring functionality to damaged neural circuits.
Copyright comment Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2025
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
