当前位置: X-MOL 学术Commun. Nonlinear Sci. Numer. Simul. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Short-term and spike-timing-dependent plasticity facilitate the formation of modular neural networks
Communications in Nonlinear Science and Numerical Simulation ( IF 3.4 ) Pub Date : 2020-12-29 , DOI: 10.1016/j.cnsns.2020.105689
Ewandson L. Lameu , Fernando S. Borges , Kelly C. Iarosz , Paulo R. Protachevicz , Chris G. Antonopoulos , Elbert E.N. Macau , Antonio M. Batista

The brain has the phenomenal ability to reorganise itself by forming new connections among neurons and by pruning others. The so-called neural or brain plasticity facilitates the modification of brain structure and function over different time scales. Plasticity might occur due to external stimuli received from the environment, during recovery from brain injury, or due to modifications within the body and brain itself. In this paper, we study the combined effect of short-term (STP) and spike-timing-dependent plasticity (STDP) on the synaptic strength of excitatory coupled Hodgkin-Huxley neurons and show that plasticity can facilitate the formation of modular neural networks with complex topologies that resemble those of networks with preferential attachment properties. In particular, we use an STDP rule that alters the synaptic coupling intensity based on time intervals between spikes of postsynaptic and presynaptic neurons. Previous work has shown that STDP may induce the emergence of directed connections from high to low frequency spiking neurons. On the other hand, STP is attributed to the release of neurotransmitters in the synaptic cleft of neurons that alter its synaptic efficiency. Our results suggest that the combined effect of STP and STDP with long recovery times facilitates the formation of connections among neurons with similar spike frequencies only, a kind of preferential attachment. We then pursue this further and show that, when starting with all-to-all neural configurations, depending on the STP recovery time and distribution of neural frequencies, modular neural networks can emerge as a direct result of the combined effect of STP and STDP.



中文翻译:

短期和依赖于尖峰时间的可塑性促进了模块化神经网络的形成

大脑具有通过在神经元之间形成新连接并修剪其他神经元来重组自身的惊人能力。所谓的神经或大脑可塑性促进了在不同时间尺度上大脑结构和功能的改变。可塑性可能是由于从环境中接收到的外部刺激,在脑损伤恢复期间或由于身体和大脑本身的修饰而发生的。在本文中,我们研究了短期(STP)和依赖于尖峰时序的可塑性(STDP)对兴奋性耦合霍奇金-赫克斯利神经元突触强度的联合作用,并显示可塑性可以促进具有以下特征的模块化神经网络的形成:类似于具有优先附件属性的网络的复杂拓扑。特别是,我们使用STDP规则,根据突触后神经元和突触前神经元的尖峰之间的时间间隔来更改突触耦合强度。先前的工作表明,STDP可能会诱导从高频尖峰神经元到低频尖峰神经元的定向连接的出现。另一方面,STP归因于神经元突触间隙中神经递质的释放,从而改变了其突触效率。我们的研究结果表明,STP和STDP具有较长恢复时间的组合效应,仅在具有相似尖峰频率的神经元之间就形成了连接,这是一种优先附着。然后,我们进一步进行研究,并表明,当从所有神经配置开始时,取决于STP恢复时间和神经频率的分布,

更新日期:2021-01-04
down
wechat
bug