Wu Jialiang, Qi Zhen, Voit Eberhard O
School of Mathematics, Georgia Institute of Technology, Atlanta, Georgia, USA.
Stud Health Technol Inform. 2011;162:222-35.
Dopamine is a critical neurotransmitter for the normal functioning of the central nervous system. Abnormal dopamine signal transmission in the brain has been implicated in diseases such as Parkinson's disease (PD) and schizophrenia, as well as in various types of drug addition. It is therefore important to understand the dopamine signaling dynamics in the presynaptic neuron of the striatum and the synaptic cleft, where dopamine synthesis, degradation, compartmentalization, release, reuptake, and numerous regulatory processes occur. The biochemical and biological processes governing this dynamics consist of interacting discrete and continuous components, operate at different time scales, and must function effectively in spite of intrinsic stochasticity and external perturbations. Not fitting into the realm of purely deterministic phenomena, the hybrid nature of the system requires special means of mathematical modeling, simulation and analysis. We show here how hybrid functional Petri-nets (HFPNs) and the software Cell Illustrator facilitate computational analyses of systems that simultaneously contain deterministic, stochastic, and delay components. We evaluate the robustness of dopamine signaling in the presence of delays and noise and discuss implications for normal and abnormal states of the system.
多巴胺是中枢神经系统正常运作的关键神经递质。大脑中多巴胺信号传递异常与帕金森病(PD)、精神分裂症等疾病以及各种类型的药物成瘾有关。因此,了解纹状体突触前神经元和突触间隙中的多巴胺信号动态很重要,多巴胺的合成、降解、区室化、释放、再摄取以及众多调节过程都发生在这些部位。控制这种动态的生化和生物学过程由相互作用的离散和连续成分组成,在不同的时间尺度上运作,并且尽管存在内在的随机性和外部干扰,仍必须有效发挥作用。该系统的混合性质不属于纯粹确定性现象的范畴,需要特殊的数学建模、模拟和分析方法。我们在此展示了混合功能Petri网(HFPN)和软件Cell Illustrator如何促进对同时包含确定性、随机性和延迟成分的系统进行计算分析。我们评估了存在延迟和噪声时多巴胺信号的稳健性,并讨论了其对系统正常和异常状态的影响。