• 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

相似文献

1
A Causal Network Analysis of Neuromodulation in the Mood Processing Network.情绪处理网络中神经调节的因果网络分析。
Neuron. 2020 Sep 9;107(5):972-985.e6. doi: 10.1016/j.neuron.2020.06.012. Epub 2020 Jul 8.
2
Modelling and prediction of the dynamic responses of large-scale brain networks during direct electrical stimulation.直接电刺激下大规模脑网络动态响应的建模与预测。
Nat Biomed Eng. 2021 Apr;5(4):324-345. doi: 10.1038/s41551-020-00666-w. Epub 2021 Feb 1.
3
Multiregional communication and the channel modulation hypothesis.多区域通讯与信道调制假说。
Curr Opin Neurobiol. 2021 Feb;66:250-257. doi: 10.1016/j.conb.2020.11.016. Epub 2020 Dec 24.
4
Dissecting neural circuits for multisensory integration and crossmodal processing.剖析用于多感官整合和跨模态处理的神经回路。
Philos Trans R Soc Lond B Biol Sci. 2015 Sep 19;370(1677):20140203. doi: 10.1098/rstb.2014.0203.
5
Synthesis of high-complexity rhythmic signals for closed-loop electrical neuromodulation.闭环电神经调节的高复杂度节奏信号合成。
Neural Netw. 2013 Jun;42:62-73. doi: 10.1016/j.neunet.2013.01.005. Epub 2013 Jan 21.
6
Causal Inference and Explaining Away in a Spiking Network.脉冲神经网络中的因果推理与解释消除
Sci Rep. 2015 Dec 1;5:17531. doi: 10.1038/srep17531.
7
Advancing neuromodulation using a dynamic control framework.使用动态控制框架推进神经调节
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:671-4. doi: 10.1109/IEMBS.2011.6090150.
8
NeuroDots: From Single-Target to Brain-Network Modulation: Why and What Is Needed?NeuroDots:从单靶点到脑网络调控:为什么以及需要什么?
Neuromodulation. 2024 Jun;27(4):711-729. doi: 10.1016/j.neurom.2024.01.003. Epub 2024 Apr 16.
9
Multi-Connection Pattern Analysis: Decoding the representational content of neural communication.多连接模式分析:解码神经通讯的表象内容。
Neuroimage. 2017 Nov 15;162:32-44. doi: 10.1016/j.neuroimage.2017.08.033. Epub 2017 Aug 13.
10
Intracortical Dynamics Underlying Repetitive Stimulation Predicts Changes in Network Connectivity.皮层内动力学预测重复刺激下网络连接的变化。
J Neurosci. 2019 Jul 31;39(31):6122-6135. doi: 10.1523/JNEUROSCI.0535-19.2019. Epub 2019 Jun 10.

引用本文的文献

1
Closed-loop control of theta oscillations enhances human hippocampal network connectivity.θ振荡的闭环控制增强人类海马体网络连通性。
Nat Commun. 2025 Apr 30;16(1):4061. doi: 10.1038/s41467-025-59417-7.
2
The Neurostimulationist will see you now: prescribing direct electrical stimulation therapies for the human brain in epilepsy and beyond.神经刺激专家现在将为您诊治:为癫痫及其他病症的人脑开具直接电刺激疗法的处方。
Front Hum Neurosci. 2024 Sep 4;18:1439541. doi: 10.3389/fnhum.2024.1439541. eCollection 2024.
3
Modulation of hippocampal theta oscillations via deep brain stimulation of the parietal cortex depends on cognitive state.通过对顶叶皮层的深部脑刺激来调节海马体θ振荡取决于认知状态。
Cortex. 2024 Jun;175:28-40. doi: 10.1016/j.cortex.2024.03.010. Epub 2024 Apr 25.
4
Microstimulation of visual area V4 improves visual stimulus detection.视区 V4 的微刺激可改善视觉刺激检测。
Cell Rep. 2022 Sep 20;40(12):111392. doi: 10.1016/j.celrep.2022.111392.
5
State-dependent effects of neural stimulation on brain function and cognition.神经刺激对大脑功能和认知的状态依赖性影响。
Nat Rev Neurosci. 2022 Aug;23(8):459-475. doi: 10.1038/s41583-022-00598-1. Epub 2022 May 16.
6
Landscape Perception Identification and Classification Based on Electroencephalogram (EEG) Features.基于脑电(EEG)特征的景观感知识别与分类。
Int J Environ Res Public Health. 2022 Jan 6;19(2):629. doi: 10.3390/ijerph19020629.
7
Stoney vs. Histed: Quantifying the spatial effects of intracortical microstimulation.史东尼诉希斯特:量化皮质内微刺激的空间效应。
Brain Stimul. 2022 Jan-Feb;15(1):141-151. doi: 10.1016/j.brs.2021.11.015. Epub 2021 Nov 30.
8
Improving scalability in systems neuroscience.提高系统神经科学的可扩展性。
Neuron. 2021 Jun 2;109(11):1776-1790. doi: 10.1016/j.neuron.2021.03.025. Epub 2021 Apr 7.
9
Multiregional communication and the channel modulation hypothesis.多区域通讯与信道调制假说。
Curr Opin Neurobiol. 2021 Feb;66:250-257. doi: 10.1016/j.conb.2020.11.016. Epub 2020 Dec 24.
10
Theory of neuronal perturbome in cortical networks.皮质网络中神经元扰动组理论。
Proc Natl Acad Sci U S A. 2020 Oct 27;117(43):26966-26976. doi: 10.1073/pnas.2004568117. Epub 2020 Oct 14.

本文引用的文献

1
Neuromodulation of Brain State and Behavior.脑状态和行为的神经调节。
Annu Rev Neurosci. 2020 Jul 8;43:391-415. doi: 10.1146/annurev-neuro-100219-105424. Epub 2020 Apr 6.
2
Specialized medial prefrontal-amygdala coordination in other-regarding decision preference.特定的内侧前额叶-杏仁核协调与他人决策偏好有关。
Nat Neurosci. 2020 Apr;23(4):565-574. doi: 10.1038/s41593-020-0593-y. Epub 2020 Feb 24.
3
Excitatory/Inhibitory Responses Shape Coherent Neuronal Dynamics Driven by Optogenetic Stimulation in the Primate Brain.光遗传学刺激驱动下的灵长类大脑中兴奋/抑制反应塑造相干神经元动力学。
J Neurosci. 2020 Mar 4;40(10):2056-2068. doi: 10.1523/JNEUROSCI.1949-19.2020. Epub 2020 Jan 21.
4
Brain-machine interfaces from motor to mood.从运动到情绪的脑机接口。
Nat Neurosci. 2019 Oct;22(10):1554-1564. doi: 10.1038/s41593-019-0488-y. Epub 2019 Sep 24.
5
Functional control of electrophysiological network architecture using direct neurostimulation in humans.在人类中使用直接神经刺激对电生理网络结构进行功能控制。
Netw Neurosci. 2019 Jul 1;3(3):848-877. doi: 10.1162/netn_a_00089. eCollection 2019.
6
Theoretical principles of deep brain stimulation induced synaptic suppression.深部脑刺激诱导的突触抑制的理论原理。
Brain Stimul. 2019 Nov-Dec;12(6):1402-1409. doi: 10.1016/j.brs.2019.07.005. Epub 2019 Jul 10.
7
Effective learning is accompanied by high-dimensional and efficient representations of neural activity.有效的学习伴随着神经活动的高维高效表示。
Nat Neurosci. 2019 Jun;22(6):1000-1009. doi: 10.1038/s41593-019-0400-9. Epub 2019 May 20.
8
Dynamic network modeling and dimensionality reduction for human ECoG activity.人类脑电活动的动态网络建模与降维
J Neural Eng. 2019 Aug 14;16(5):056014. doi: 10.1088/1741-2552/ab2214.
9
Deep brain stimulation of the internal capsule enhances human cognitive control and prefrontal cortex function.内囊的深部脑刺激增强了人类的认知控制和前额叶皮层功能。
Nat Commun. 2019 Apr 4;10(1):1536. doi: 10.1038/s41467-019-09557-4.
10
Deep brain stimulation: current challenges and future directions.深部脑刺激:当前的挑战和未来的方向。
Nat Rev Neurol. 2019 Mar;15(3):148-160. doi: 10.1038/s41582-018-0128-2.

情绪处理网络中神经调节的因果网络分析。

A Causal Network Analysis of Neuromodulation in the Mood Processing Network.

机构信息

Center for Neural Science, New York University, New York, NY 10003, USA.

Center for Neural Science, New York University, New York, NY 10003, USA; Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA; Department of Neurology, New York University Langone Health, New York, NY 10016, USA.

出版信息

Neuron. 2020 Sep 9;107(5):972-985.e6. doi: 10.1016/j.neuron.2020.06.012. Epub 2020 Jul 8.

DOI:10.1016/j.neuron.2020.06.012
PMID:32645299
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7486259/
Abstract

Neural decoding and neuromodulation technologies hold great promise for treating mood and other brain disorders in next-generation therapies that manipulate functional brain networks. Here we perform a novel causal network analysis to decode multiregional communication in the primate mood processing network and determine how neuromodulation, short-burst tetanic microstimulation (sbTetMS), alters multiregional network communication. The causal network analysis revealed a mechanism of network excitability that regulates when a sender stimulation site communicates with receiver sites. Decoding network excitability from neural activity at modulator sites predicted sender-receiver communication, whereas sbTetMS neuromodulation temporarily disrupted sender-receiver communication. These results reveal specific network mechanisms of multiregional communication and suggest a new generation of brain therapies that combine neural decoding to predict multiregional communication with neuromodulation to disrupt multiregional communication.

摘要

神经解码和神经调制技术在下一代治疗方法中具有很大的应用前景,这些方法可以操纵功能性大脑网络,从而治疗情绪和其他大脑疾病。在这里,我们进行了一项新颖的因果网络分析,以解码灵长类动物情绪处理网络中的多区域通信,并确定神经调制(短爆发强直微刺激 (sbTetMS))如何改变多区域网络通信。因果网络分析揭示了一种调节发送者刺激部位与接收部位何时进行通信的网络兴奋性机制。从调制器部位的神经活动中解码网络兴奋性可以预测发送者-接收者的通信,而 sbTetMS 神经调制则暂时中断了发送者-接收者的通信。这些结果揭示了多区域通信的特定网络机制,并提出了一种新一代的脑治疗方法,该方法将神经解码与预测多区域通信相结合,同时结合神经调制来干扰多区域通信。