成年海马神经发生对模式分离的影响及其应用

IF 3.1 3区 工程技术 Q2 NEUROSCIENCES Cognitive Neurodynamics Pub Date : 2024-04-16 DOI:10.1007/s11571-024-10110-3
Zengbin Wang, Kai Yang, Xiaojuan Sun
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引用次数: 0

摘要

成人海马神经发生(AHN)被认为是记忆形成的关键。在神经生理学和行为学实验中,包含关键期(4-6 周)新生齿状回颗粒细胞的齿状回神经网络已被广泛讨论。然而,这一关键期的新生齿状回颗粒细胞如何影响齿状回的模式分离仍不清楚。为了解决这个问题,我们提出了一个与 AHN 生物学相关的齿状回神经网络模型。通过利用该模型,我们发现在中等神经发生水平(5% 的成熟颗粒细胞)时,模式分离会增强。这是因为成熟颗粒细胞的稀疏发射增加了。我们可以从以下两个方面来理解这种变化。一方面,新生颗粒细胞与成熟颗粒细胞竞争来自内皮层的输入,从而削弱了成熟颗粒细胞的发射。另一方面,新生颗粒细胞通过促进中间神经元(苔藓细胞和篮状细胞)的发射,进而间接调节成熟颗粒细胞的稀疏发射,从而有效提高网络的反馈抑制水平。为了验证该模型在模式分离方面的有效性,我们将所提出的模型应用于类似的概念分离任务,结果表明我们的模型在该任务中的表现优于原始模型。
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Effect of adult hippocampal neurogenesis on pattern separation and its applications

Adult hippocampal neurogenesis (AHN) is considered essential in memory formation. The dentate gyrus neural network containing newborn dentate gyrus granule cells at the critical period (4–6 weeks) have been widely discussed in neurophysiological and behavioral experiments. However, how newborn dentate gyrus granule cells at this critical period influence pattern separation of dentate gyrus remains unclear. To address this issue, we propose a biologically related dentate gyrus neural network model with AHN. By Leveraging this model, we find pattern separation is enhanced at the medium level of neurogenesis (5% of mature granule cells). This is because the sparse firing of mature granule cells is increased. We can understand this change from the following two aspects. On one hand, newborn granule cells compete with mature granule cells for inputs from the entorhinal cortex, thereby weakening the firing of mature granule cells. On the other hand, newborn granule cells effectively enhance the feedback inhibition level of the network by promoting the firing of interneurons (Mossy cells and Basket cells) and then indirectly regulating the sparse firing of mature granule cells. To verify the validity of the model for pattern separation, we apply the proposed model to a similar concept separation task and reveal that our model outperforms the original model counterparts in this task.

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来源期刊
Cognitive Neurodynamics
Cognitive Neurodynamics 医学-神经科学
CiteScore
6.90
自引率
18.90%
发文量
140
审稿时长
12 months
期刊介绍: Cognitive Neurodynamics provides a unique forum of communication and cooperation for scientists and engineers working in the field of cognitive neurodynamics, intelligent science and applications, bridging the gap between theory and application, without any preference for pure theoretical, experimental or computational models. The emphasis is to publish original models of cognitive neurodynamics, novel computational theories and experimental results. In particular, intelligent science inspired by cognitive neuroscience and neurodynamics is also very welcome. The scope of Cognitive Neurodynamics covers cognitive neuroscience, neural computation based on dynamics, computer science, intelligent science as well as their interdisciplinary applications in the natural and engineering sciences. Papers that are appropriate for non-specialist readers are encouraged. 1. There is no page limit for manuscripts submitted to Cognitive Neurodynamics. Research papers should clearly represent an important advance of especially broad interest to researchers and technologists in neuroscience, biophysics, BCI, neural computer and intelligent robotics. 2. Cognitive Neurodynamics also welcomes brief communications: short papers reporting results that are of genuinely broad interest but that for one reason and another do not make a sufficiently complete story to justify a full article publication. Brief Communications should consist of approximately four manuscript pages. 3. Cognitive Neurodynamics publishes review articles in which a specific field is reviewed through an exhaustive literature survey. There are no restrictions on the number of pages. Review articles are usually invited, but submitted reviews will also be considered.
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