Park Jihoon, Kawai Yuji, Asada Minoru
Center for Information and Neural Networks, National Institute of Information and Communications Technology, Suita, Japan.
Symbiotic Intelligent Systems Research Center, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan.
Front Comput Neurosci. 2023 Apr 12;17:1169288. doi: 10.3389/fncom.2023.1169288. eCollection 2023.
Excitatory and inhibitory neurons are fundamental components of the brain, and healthy neural circuits are well balanced between excitation and inhibition (E/I balance). However, it is not clear how an E/I imbalance affects the self-organization of the network structure and function in general. In this study, we examined how locally altered E/I balance affects neural dynamics such as the connectivity by activity-dependent formation, the complexity (multiscale entropy) of neural activity, and information transmission. In our simulation, a spiking neural network model was used with the spike-timing dependent plasticity rule to explore the above neural dynamics. We controlled the number of inhibitory neurons and the inhibitory synaptic weights in a single neuron group out of multiple neuron groups. The results showed that a locally increased E/I ratio strengthens excitatory connections, reduces the complexity of neural activity, and decreases information transmission between neuron groups in response to an external input. Finally, we argued the relationship between our results and excessive connections and low complexity of brain activity in the neuropsychiatric brain disorders.
兴奋性神经元和抑制性神经元是大脑的基本组成部分，健康的神经回路在兴奋和抑制之间保持良好的平衡（E/I平衡）。然而，目前尚不清楚E/I失衡总体上是如何影响网络结构和功能的自组织的。在本研究中，我们研究了局部改变的E/I平衡如何影响神经动力学，如通过活动依赖形成的连通性、神经活动的复杂性（多尺度熵）和信息传递。在我们的模拟中，使用了具有尖峰时间依赖可塑性规则的脉冲神经网络模型来探索上述神经动力学。我们在多个神经元组中的单个神经元组中控制抑制性神经元的数量和抑制性突触权重。结果表明，局部增加的E/I比率会增强兴奋性连接，降低神经活动的复杂性，并减少神经元组之间对外部输入的信息传递。最后，我们讨论了我们的结果与神经精神性脑部疾病中大脑活动的过度连接和低复杂性之间的关系。
