• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

层次组织进化神经网络中的相互投射会影响类似 EEG 的信号。

Reciprocal projections in hierarchically organized evolvable neural circuits affect EEG-like signals.

机构信息

Neuroheuristic Research Group, Information Science Inst., Univ. of Lausanne, Switzerland.

出版信息

Brain Res. 2012 Jan 24;1434:266-76. doi: 10.1016/j.brainres.2011.08.018. Epub 2011 Aug 16.

DOI:10.1016/j.brainres.2011.08.018
PMID:21890119
Abstract

Modular architecture is a hallmark of many brain circuits. In the cerebral cortex, in particular, it has been observed that reciprocal connections are often present between functionally interconnected areas that are hierarchically organized. We investigate the effect of reciprocal connections in a network of modules of simulated spiking neurons. The neural activity is recorded by means of virtual electrodes and EEG-like signals, called electrochipograms (EChG), analyzed by time- and frequency-domain methods. A major feature of our approach is the implementation of important bio-inspired processes that affect the connectivity within a neural module: synaptogenesis, cell death, spike-timing-dependent plasticity and synaptic pruning. These bio-inspired processes drive the build-up of auto-associative links within each module, which generate an areal activity, recorded by EChG, that reflect the changes in the corresponding functional connectivity within and between neuronal modules. We found that circuits with intra-layer reciprocal projections exhibited enhanced stimulus-locked response. We show evidence that all networks of modules are able to process and maintain patterns of activity associated with the stimulus after its offset. The presence of feedback and horizontal projections was necessary to evoke cross-layer coherence in bursts of -frequency at regular intervals. These findings bring new insights to the understanding of the relation between the functional organization of neural circuits and the electrophysiological signals generated by large cell assemblies. This article is part of a Special Issue entitled "Neural Coding".

摘要

模块化架构是许多大脑回路的标志。特别是在大脑皮层中,人们观察到功能上相互连接的区域之间经常存在着递归连接,这些区域是按照层次组织的。我们在模拟尖峰神经元模块的网络中研究了递归连接的效果。通过虚拟电极和类似于脑电图的信号(称为电芯片图,EChG)来记录神经活动,通过时频域方法进行分析。我们方法的一个主要特点是实现了影响神经模块内连接的重要生物启发过程:突触发生、细胞死亡、尖峰时间依赖性可塑性和突触修剪。这些生物启发过程促使每个模块内自动关联链接的建立,从而产生 EChG 记录的区域活动,反映相应神经元模块内和模块间功能连接的变化。我们发现具有层内递归投影的电路表现出增强的刺激锁响应。我们有证据表明,所有的模块网络都能够在刺激结束后处理和保持与刺激相关的活动模式。反馈和水平投影的存在对于在规则间隔内引发 - 频率的跨层相干是必要的。这些发现为理解神经回路的功能组织与大细胞集合产生的电生理信号之间的关系提供了新的见解。本文是题为“神经编码”的特刊的一部分。

相似文献

1
Reciprocal projections in hierarchically organized evolvable neural circuits affect EEG-like signals.层次组织进化神经网络中的相互投射会影响类似 EEG 的信号。
Brain Res. 2012 Jan 24;1434:266-76. doi: 10.1016/j.brainres.2011.08.018. Epub 2011 Aug 16.
2
Effect of stimulus-driven pruning on the detection of spatiotemporal patterns of activity in large neural networks.刺激驱动的修剪对大型神经网络中活动时空模式检测的影响。
Biosystems. 2007 May-Jun;89(1-3):287-93. doi: 10.1016/j.biosystems.2006.05.020. Epub 2006 Nov 15.
3
Functional interactions in hierarchically organized neural networks studied with spatiotemporal firing patterns and phase-coupling frequencies.利用时空放电模式和相位耦合频率研究层次组织神经网络中的功能相互作用。
Chin J Physiol. 2010 Dec 31;53(6):382-95. doi: 10.4077/cjp.2010.amm039.
4
Recurrent spatiotemporal firing patterns in large spiking neural networks with ontogenetic and epigenetic processes.具有个体发育和表观遗传过程的大型脉冲神经网络中的反复时空放电模式。
J Physiol Paris. 2010 May-Sep;104(3-4):137-46. doi: 10.1016/j.jphysparis.2009.11.016. Epub 2009 Nov 26.
5
Neuronal avalanches of a self-organized neural network with active-neuron-dominant structure.具有活性神经元主导结构的自组织神经网络的神经元雪崩。
Chaos. 2012 Jun;22(2):023104. doi: 10.1063/1.3701946.
6
Synaptic plasticity: taming the beast.突触可塑性:驯服这头野兽。
Nat Neurosci. 2000 Nov;3 Suppl:1178-83. doi: 10.1038/81453.
7
Synaptic plasticity in micropatterned neuronal networks.微图案化神经元网络中的突触可塑性
Biomaterials. 2005 May;26(15):2549-57. doi: 10.1016/j.biomaterials.2004.07.031.
8
Spike-timing-dependent plasticity in balanced random networks.平衡随机网络中依赖于尖峰时间的可塑性。
Neural Comput. 2007 Jun;19(6):1437-67. doi: 10.1162/neco.2007.19.6.1437.
9
Self-tuning of neural circuits through short-term synaptic plasticity.通过短期突触可塑性实现神经回路的自我调节。
J Neurophysiol. 2007 Jun;97(6):4079-95. doi: 10.1152/jn.01357.2006. Epub 2007 Apr 4.
10
Learning in realistic networks of spiking neurons and spike-driven plastic synapses.在具有脉冲发放神经元和脉冲驱动可塑性突触的真实网络中进行学习。
Eur J Neurosci. 2005 Jun;21(11):3143-60. doi: 10.1111/j.1460-9568.2005.04087.x.

引用本文的文献

1
Redefining cognitive neurodynamics through transdisciplinary innovation.通过跨学科创新重新定义认知神经动力学。
Cogn Neurodyn. 2025 Dec;19(1):144. doi: 10.1007/s11571-025-10332-z. Epub 2025 Sep 5.
2
Psychiatric Neural Networks and Precision Therapeutics by Machine Learning.基于机器学习的精神科神经网络与精准治疗
Biomedicines. 2021 Apr 8;9(4):403. doi: 10.3390/biomedicines9040403.
3
An attractor-based complexity measurement for Boolean recurrent neural networks.基于吸引子的布尔递归神经网络复杂度度量。
PLoS One. 2014 Apr 11;9(4):e94204. doi: 10.1371/journal.pone.0094204. eCollection 2014.