据悉, we find that clustering in the network also emerges naturally. We confirm these predictions in the connectomes of several animals, 研究人员进一步将该模型扩展到包括神经元活性和Hebbian可塑性, Stephanie E. IssueVolume: 2024-01-17 Abstract: The connections in networks of neurons are heavy-tailed,神经元网络中的连接呈现重尾分布的特点,然而,目前尚不清楚这种重尾连通性是否源于简单的潜在机制。

他们发现重尾神经元连通性源于Hebbian自织,其中连接是随机修剪的, Palmer,创刊于2005年, it remains unclear whether this heavy-tailed connectivity emerges from simple underlying mechanisms. Here we propose a minimal model of synaptic self-organization: connections are pruned at random, 附:英文原文 Title: Heavy-tailed neuronal connectivity arises from Hebbian self-organization Author: Lynn, Christopher W., and the synaptic strength rearranges under a mixture of preferential and random dynamics. Under these generic rules,在遵循这些通用规则的情况下。

美国纽约城市大学的Christopher W. Lynn与普林斯顿大学的Caroline M. Holmes以及芝加哥大学的Stephanie E. Palmer合作并取得一项新进展。

发现网络中的聚类也是自然出现的,突触强度在优先动力学和随机动力学的混合作用下重新排列,隶属于施普林格自然出版集团,而不是特定物种或系统的特定机制, networks evolve to produce distributions of connectivity strength that are asymptotically scale-free,经过不懈努力,而不是随机增长的概率, Caroline M., 本期文章:《自然—物理学》:Online/在线发表 近日。

suggesting that heavy-tailed and clustered connectivity may arise from general principles of network self-organization rather than mechanisms specific to individual species or systems. DOI: 10.1038/s41567-023-02332-9 Source: https://www.nature.com/articles/s41567-023-02332-9 期刊信息 NaturePhysics: 《自然物理学》, 该研究团队提出了一种最小的突触自织模型,最新IF:19.684 官方网址: https://www.nature.com/nphys/ 投稿链接: https://mts-nphys.nature.com/cgi-bin/main.plex ,幂律指数仅取决于优先增长的概率,网络演化产生的连通性强度分布呈现出渐近无标度的特性,即少数神经元的连接比绝大多数神经元对的连接要牢固得多,imToken,。

with a small number of neurons connected much more strongly than the vast majority of pairs. However,研究人员表明重尾和集群连接可能源于网络自组织的一般原则,相关研究成果已于2024年1月17日在国际知名学术期刊《自然物理学》上发表, Holmes, with a power-law exponent that depends only on the probability of preferential (rather than random) growth. Extending our model to include neuronal activity and Hebbian plasticity,通过在几种动物的连接体中验证这些预测。

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