Intracortical Dynamics Underlying Repetitive Stimulation Predicts Changes in Network Connectivity

作者
Yuhao Huang,Boglárka Hajnal,László Entz,Dániel Fabó,Jose L. Herrero,Ashesh D. Mehta,Corey J. Keller
出处
期刊:The Journal of Neuroscience [Society for Neuroscience]
卷期号:39 (31): 6122-6135 被引量:53
标识
DOI:10.1523/jneurosci.0535-19.2019
摘要

Abstract Targeted stimulation can be used to modulate the activity of brain networks. Previously we demonstrated that direct electrical stimulation produces predictable post-stimulation changes in brain excitability. However, understanding the neural dynamics during stimulation and its relationship to post-stimulation effects is limited but critical for treatment optimization. Here, we applied 10Hz direct electrical stimulation across several cortical regions in 14 patients implanted with intracranial electrodes for seizure monitoring. The stimulation train was characterized by a consistent increase in high gamma (70-170Hz) power. Immediately post-train, low-frequency (1-8Hz) power increased, resulting in an evoked response that was highly correlated with the neural response during stimulation. Using two measures of network connectivity, cortico-cortical evoked potentials (indexing effective connectivity) and theta coherence (indexing functional connectivity), we found a stronger response to stimulation in regions that were highly connected to the stimulation site. In these regions, repeated cycles of stimulation trains and rest progressively altered the stimulation response. Finally, after just 2 minutes (10%) of repetitive stimulation, we were able to predict post-stimulation connectivity changes with high discriminability. Taken together, this work reveals a relationship between stimulation dynamics and post-stimulation connectivity changes in humans. Thus, measuring neural activity during stimulation can inform future plasticity-inducing protocols.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Sonder发布了新的文献求助10
刚刚
刚刚
1秒前
3秒前
鹤轸发布了新的文献求助10
3秒前
盛小铃发布了新的文献求助10
3秒前
4秒前
Maestro_S的应助被qixu123采纳,获得10
4秒前
jjj完成签到,获得积分10
5秒前
Lucas的应助被我是学霸采纳,获得10
5秒前
5秒前
6秒前
甄晓溪发布了新的文献求助10
6秒前
7秒前
橙汁完成签到,获得积分0
7秒前
舒心傲丝发布了新的文献求助10
7秒前
乐乐的应助被dongqiangqiang采纳,获得10
8秒前
指南针指北完成签到 ,获得积分10
9秒前
追寻的觅双完成签到 ,获得积分10
9秒前
10秒前
10秒前
lbw发布了新的文献求助10
10秒前
Wissenheimer的应助被Prof.Z采纳,获得30
11秒前
秋风的应助被科研牛马采纳,获得20
12秒前
枣核发布了新的文献求助10
12秒前
mmy发布了新的文献求助30
13秒前
冷静的豪完成签到 ,获得积分10
14秒前
机智一斩发布了新的文献求助10
14秒前
14秒前
Wulihc完成签到,获得积分10
14秒前
我开花了发布了新的文献求助20
16秒前
弹指一挥关注了科研通微信公众号
17秒前
17秒前
Rongxing发布了新的文献求助10
18秒前
19秒前
Wangguanbo发布了新的文献求助10
19秒前
orixero的应助被盛小铃采纳,获得10
19秒前
刘海青发布了新的文献求助10
19秒前
畅快乐菱完成签到,获得积分10
20秒前
我是学霸发布了新的文献求助10
23秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Encyclopedia of Modern Artificial Intelligence 1000
Особенности технологий и методов информационно-психологических войн СССР с Великобританией и США в период 1939-1953 гг 1000
Das Matthäusevangelium: Kapitel 1:1–17 1000
IRTSD: Open-Source Data and Toolset for Electromagnetic Transient Analysis of Disturbances and IBR Control Malfunctions in Transmission Systems 1000
Analyses de reconnaissances de dettes passées devant les échevins d'Ypres (1249-1291) 600
拉伸高分子熔体中缠结行为的模拟和小角中子散射研究 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 8135708
求助须知:如何正确求助?哪些是违规求助? 9536963
关于积分的说明 21620460
捐赠科研通 7718420
什么是DOI,文献DOI怎么找? 3419585
关于科研通互助平台的介绍 2544892
邀请新用户注册赠送积分活动 2461273