Spike Timing Dependent Plasticity Enhances Integrated Information at the EEG Level: A Large-scale Brain Simulation Experiment
Spike Timing Dependent Plasticity Enhances Integrated Information at the EEG Level: A Large-scale Brain Simulation Experiment
复制标题
尖峰时间依赖性可塑性增强脑电图水平的综合信息：大规模大脑模拟实验
DOI：
10.1109/devlrn.2019.8850724
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Kuniyoshi Yasuo
中科院分区：
文献类型：
--
作者：
Fujii Keiko;Kanazawa Hoshinori;Kuniyoshi Yasuo
大脑在发育过程中增强了功能分离和功能整合。新生儿脑电图（EEG）实验使用各种测量方法，如复杂性维度或综合信息，支持了这一点。阐明这种同时增强的机制对于理解大脑如何成为一个复杂的认知系统非常重要。这种机制的一个候选是吸引子的出现，因为它们被认为代表神经网络中的差异化信息，同时诱导多变量之间的夹带。事实上，在神经元水平的模拟研究中，通过峰值时间依赖的可塑性（STDP）规则学习导致了吸引子的出现。然而，STDP的突触变化与脑电图等更大空间尺度的脑活动之间的知识差距仍然存在。因此，本研究的主要目的是测试STDP学习是否影响脑电水平上的功能分离和整合。我们构建了由STDP规则介导的脉冲神经元和突触组成的大规模脑模拟。我们通过模拟尖峰神经活动来估计脑电图信号。这些新系统使我们能够检查突触变化对脑电图信号的影响。作为衡量平衡良好的功能分离和集成，我们研究了集成信息φ*的变化。我们发现，在STDP学习后，φ*和吸引子数量的增加呈显著正相关。这些结果支持了我们的假设，即吸引子的出现可能是增强功能分离和整合的潜在机制。
The brain enhances functional segregation and functional integration through the developmental process. This is supported by neonatal electroencephalography (EEG) experiments using various measurements such as complexity dimension or integrated information. Elucidating the mechanisms of this simultaneous enhancement is important to understand how the brain becomes a sophisticated cognitive system. One candidate for this mechanism is the emergence of attractors because they are thought to represent differentiated information in a neural network and at the same time induce entrainment among multivariates. Indeed, in neuron level simulation studies, learning by spike timing dependent plasticity (STDP) rule resulted in the emergence of attractors. However, there is still a gap in knowledge between synaptic changes by STDP and brain activity at a larger spatial scale such as EEG. Thus, the main aim of this study was to test whether STDP learning affects functional segregation and integration at the EEG level. We constructed a large-scale brain simulation composed of spiking neurons and synapses mediated by STDP rule. We estimated EEG signals from simulated spiking neural activities. These novel systems enabled us to examine the effect of synaptic changes on EEG signals. As a measurement of well-balanced functional segregation and integration, we examined changes in integrated information φ*. We found the increases in φ* and the number of attractors after STDP learning, and they showed a significant positive correlation. These results support our hypothesis that the emergence of attractors can be an underlying mechanism of enhanced functional segregation and integration.
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