基于抑制性突触可塑性的神经元放电率自稳态机制

神经元放电率自稳态是指大脑神经网络的放电率维持在相对稳定的状态.大量实验研究发现神经元放电率自稳态是神经电活动的重要特征,并且放电率自稳态是实现神经信息处理及维持正常脑功能的基础,因此放电率自稳态的研究是神经科学领域的重要科学问题.脑神经网络是一个高度复杂的动态系统,存在大量输入扰动信号及由于动态链接导致的参数摄动,因此如何建立并维持神经元放电率自稳态及其鲁棒性仍有待深入研究.反馈神经回路是皮层神经网络的典型连接模式,抑制性突触可塑性对神经元放电率自稳态具有重要的调控作用.本文通过构建包含抑制性突触可塑性的反馈神经回路模型对神经元放电率自稳态及其鲁棒性进行计算研究.结果表明:在抑制性突触可塑性的作用下,神经元放电率可自适应地跟踪目标放电率,从而取得放电率自稳态;在有外部输入干扰和参数摄动的情况下,神经元放电率具有良好的抗扰动性能,表明放电率自稳态具有很强的鲁棒性;理论分析揭示了抑制性突触可塑性学习规则是神经元放电率自稳态的神经机制;仿真分析进一步揭示了学习率及目标放电率对放电率自稳态建立过程具有重要影响.

Neural firing rate homeostasis via inhibitory synaptic plasticity

Neural firing rate homeostasis, as an important feature of neural electrical activity, means that the firing rate in brain is maintained in a relatively stable state, and fluctuates around a constant value. Extensive experimental studies have revealed that the firing rate homeostasis is ubiquitous in brain, and provides a base for neural information processing and maintaining normal neurological functions, so that the research on neural firing rate homeostasis is a central problem in the field of neuroscience. Cortical neural network is a highly complex dynamic system with a large number of input disturbance signals and parameter perturbations due to dynamic connection. However, it remains to be further investigated how firing rate homeostasis is established in cortical neural network, furthermore, maintains robustness to these disturbances and perturbations. The feedback neural circuit with recurrent excitatory and inhibitory connection is a typical connective pattern in cortical cortex, and inhibitory synaptic plasticity plays a crucial role in achieving neural firing rate homeostasis. Here, by constructing a feedback neural network with inhibitory spike timing-dependent plasticity (STDP), we conduct a computational research to elucidate the mechanism of neural firing rate homeostasis. The results indicate that the neuronal firing rate can track the target firing rate accurately under the regulation of inhibitory synaptic plasticity, thus achieve firing rate homeostasis. In the face of external disturbances and parameter perturbations, the neuron firing rate deviates transiently from the target firing rate value, and converges to the target firing rate value at a steady state, which demonstrates that the firing rate homeostasis established by the inhibitory synaptic plasticity can maintain strong robustness. Furthermore, the analytical research qualitatively explains the firing rate homeostasis mechanism underlined by inhibitory synaptic plasticity. Finally, the simulations further demonstrate that the learning rate value and the firing rate set point value also exert a quantitative influence on the firing rate homeostasis. Overall, these findings not only gain an insight into the firing rate homeostasis mechanism underlined by inhibitory synaptic plasticity, but also inspire testable hypotheses for future experimental studies.