College of Physics and Electronic Information, Huaibei Normal University, Huaibei 235000, China.
Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China.
Phys Rev E. 2019 Mar;99(3-1):032419. doi: 10.1103/PhysRevE.99.032419.
In the course of development, sleep, or mental disorders, certain neurons in the brain display spontaneous spike-burst activity. The synaptic plasticity evoked by such activity is here studied in the presence of spike-timing-dependent plasticity (STDP). In two chemically coupled bursting model neurons, the spike-burst activity can translate the STDP related to pre- and postsynaptic spike activity into burst-timing-dependent plasticity (BTDP), based on the timing of bursts of pre- and postsynaptic neurons. The resulting BTDP exhibits exponential decays with the same time scales as those of STDP. In weakly coupled bursting neuron networks, the synaptic modification driven by the spike-burst activity obeys a power-law distribution. The model can also produce a power-law distribution of synaptic weights. Here, the considered bursting behavior is made of stereotypical groups of spikes, and bursting is evenly spaced by long intervals.
在大脑发育、睡眠或精神障碍的过程中,大脑中的某些神经元会表现出自发的爆发活动。本文研究了在存在尖峰时间依赖可塑性(STDP)的情况下,这种活动引起的突触可塑性。在两个化学耦合并具有爆发活动的神经元模型中,爆发活动可以根据前、后神经元爆发的时间,将与前、后神经元尖峰活动相关的 STDP 转化为爆发时间依赖可塑性(BTDP)。由此产生的 BTDP 表现出与 STDP 相同时间尺度的指数衰减。在弱耦合爆发神经元网络中,由尖峰爆发活动驱动的突触修饰遵循幂律分布。该模型还可以产生突触权重的幂律分布。这里,所考虑的爆发行为由典型的尖峰群组成,爆发由长间隔均匀隔开。