论文标题
LIF电导模型中随机输入和短期突触可塑性的影响
Effects of random inputs and short-term synaptic plasticity in a LIF conductance model for working memory applications
论文作者
论文摘要
工作记忆（WM）已被强烈使用来启用用于处理目的的信息的临时存储，在执行各种认知任务中发挥重要作用。最近的研究表明，WM中的信息不仅是通过持续的复发活动来维持的，而且可以存储在活动中的状态中，例如短期突触可塑性（STSP）。由STSP机制在WM中的重要应用激发，本工作的主要重点是分析随机输入对STSP下泄漏的集成和火的影响（LIF）突触电导神经元。此外，尖峰列车的不规则性可以带有有关神经元中先前刺激的信息。具有多个输入和尖峰间间隔（ISI）变异系数（CV）的LIF电导神经元可以带来输出解码神经元。我们的数值结果表明，随机输入电流中标准偏差和随机耐火周期的增加会导致输出神经元的尖峰列车的不规则性增加。
Working memory (WM) has been intensively used to enable the temporary storing of information for processing purposes, playing an important role in the execution of various cognitive tasks. Recent studies have shown that information in WM is not only maintained through persistent recurrent activity but also can be stored in activity-silent states such as in short-term synaptic plasticity (STSP). Motivated by important applications of the STSP mechanisms in WM, the main focus of the present work is on the analysis of the effects of random inputs on a leaky integrate-and-fire (LIF) synaptic conductance neuron under STSP. Furthermore, the irregularity of spike trains can carry the information about previous stimulation in a neuron. A LIF conductance neuron with multiple inputs and coefficient of variation (CV) of the inter-spike-interval (ISI) can bring an output decoded neuron. Our numerical results show that an increase in the standard deviations in the random input current and the random refractory period can lead to an increased irregularity of spike trains of the output neuron.
