The neurotransmitter is a chemical substance that transmits information between neurons. Its metabolic process includes four links: synthesis, storage, release and inactivation. As one of the important chemical components of neurotransmitters, acetylcholine is synthesized under the catalysis of acetylcholine coenzyme A and choline acetylase. Inspired by the biological fact that enzymes exist in neurons and that enzymes are involved in neurotransmitter synthesis, we propose spiking neural P systems with enzymes (SNPE). Different from the previous spiking neural P systems and their variants, each neuron of SNPE contains two classes of objects, and each spiking rule has the participation of enzymes. In addition, the number of spikes and enzymes in a neuron can also serve as a consumption condition for controlling whether a reaction (rule execution) occurs. When the number of enzymes meets the requirements of a specific biochemical reaction, the number of occurrences of the reaction can also be controlled. As number generation and acceptance devices, the proposed SNPE systems are proved to be Turing universal. In addition, 61 neurons are used to construct an SNPE system that realizes function computation, which proves the Turing universality in this mode. Finally, we also explore using a uniform SNPE model to solve the subset sum problem and compare it with the standard SN P and its several variants.

中文翻译：

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用酶刺激神经 P 系统

神经递质是一种在神经元之间传递信息的化学物质。其代谢过程包括合成、储存、释放和失活四个环节。乙酰胆碱作为神经递质的重要化学成分之一，是在乙酰胆碱辅酶A和胆碱乙酰化酶的催化下合成的。受神经元中存在酶以及酶参与神经递质合成这一生物学事实的启发，我们提出用酶 (SNPE) 加标神经 P 系统。与以往的脉冲神经P系统及其变体不同，SNPE的每个神经元包含两类对象，每个脉冲规则都有酶的参与。此外，神经元中尖峰和酶的数量也可以作为控制反应（规则执行）是否发生的消耗条件。当酶的数量满足特定生化反应的要求时，也可以控制反应发生的次数。作为数字生成和接受设备，所提出的 SNPE 系统被证明是图灵通用的。此外，利用61个神经元构建了实现函数计算的SNPE系统，证明了该模式的图灵普适性。最后，我们还探索了使用统一的 SNPE 模型来解决子集和问题，并将其与标准 SN P 及其几个变体进行了比较。作为数字生成和接受设备，所提出的 SNPE 系统被证明是图灵通用的。此外，利用61个神经元构建了实现函数计算的SNPE系统，证明了该模式的图灵普适性。最后，我们还探索了使用统一的 SNPE 模型来解决子集和问题，并将其与标准 SN P 及其几个变体进行了比较。作为数字生成和接受设备，所提出的 SNPE 系统被证明是图灵通用的。此外，利用61个神经元构建了实现函数计算的SNPE系统，证明了该模式的图灵普适性。最后，我们还探索了使用统一的 SNPE 模型来解决子集和问题，并将其与标准 SN P 及其几个变体进行了比较。