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成人神经发生的计算建模

Computational Modeling of Adult Neurogenesis.

作者信息

Aimone James B

机构信息

Data Driven and Neural Computing Group, Center for Computing Research, Sandia National Laboratories, Albuquerque, New Mexico 87185-1327.

出版信息

Cold Spring Harb Perspect Biol. 2016 Apr 1;8(4):a018960. doi: 10.1101/cshperspect.a018960.

DOI:10.1101/cshperspect.a018960
PMID:26933191
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4817800/
Abstract

The restriction of adult neurogenesis to only a handful of regions of the brain is suggestive of some shared requirement for this dramatic form of structural plasticity. However, a common driver across neurogenic regions has not yet been identified. Computational studies have been invaluable in providing insight into the functional role of new neurons; however, researchers have typically focused on specific scales ranging from abstract neural networks to specific neural systems, most commonly the dentate gyrus area of the hippocampus. These studies have yielded a number of diverse potential functions for new neurons, ranging from an impact on pattern separation to the incorporation of time into episodic memories to enabling the forgetting of old information. This review will summarize these past computational efforts and discuss whether these proposed theoretical functions can be unified into a common rationale for why neurogenesis is required in these unique neural circuits.

摘要

成体神经发生仅限于大脑的少数几个区域,这表明这种显著的结构可塑性存在一些共同的需求。然而,尚未确定跨神经发生区域的共同驱动因素。计算研究在深入了解新神经元的功能作用方面具有重要价值;然而,研究人员通常专注于从抽象神经网络到特定神经系统的特定尺度,最常见的是海马体的齿状回区域。这些研究已经产生了许多关于新神经元的不同潜在功能,从对模式分离的影响到将时间纳入情景记忆,再到促进旧信息的遗忘。本综述将总结过去的这些计算研究工作,并讨论这些提出的理论功能是否可以统一为一个关于为何在这些独特神经回路中需要神经发生的共同基本原理。

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本文引用的文献

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