Network effects of traumatic brain injury: from infra slow to high frequency oscillations

Author:

Marsh BriannaORCID,Huang MingxiongORCID,Bazhenov Maxim

Abstract

AbstractTraumatic brain injury (TBI) can have a multitude of effects on neural functioning. In extreme cases, TBI can lead to seizures both immediately following the injury as well as persistent epilepsy over years to a lifetime. However, mechanisms of neural dysfunctioning after TBI remain poorly understood. To address these questions, we analyzed experimental data and developed a biophysical network model implementing effects of ion concentration dynamics and homeostatic synaptic plasticity to test effects of TBI on the brain network dynamics. We focus on three primary phenomena that have been reportedin vivoafter TBI: an increase in infra slow oscillations (<0.1 Hz), increase in delta (0.1 - 4 Hz) power, and the emergence of high frequency oscillations (HFOs) in the gamma range (30 - 100 Hz). We show that the infra slow oscillations can be directly attributed to extracellular potassium fluctuations, while the existence and characterization of HFOs is related to the increase in strength of synaptic weights from homeostatic synaptic scaling. The experimentally found transient increase in delta power can be attributed to the inter-HFO timings. We then show that buildup of high frequency oscillations in the injured region can lead to seizure-like events that span all neurons in the network; additional seizures can then be initiated in previously healthy regions. This study brings greater understanding of network effects of TBI, and how they can give rise to epileptic activity. This lays the foundation to begin investigating how injured networks can be healed and seizures prevented.Significance StatementThis project delineates and attempts to explain abnormalities seen in human brain following traumatic brain injury (TBI). TBI can lead to the development of seizures, which may last a lifetime and often become resistant to pharmaceutical treatments. The study identified key mechanisms responsible for occurrence of three characteristic changes in spatio-temporal network dynamics following TBI. This model provides predictions that can serve as a testing ground for potential therapeutic approaches.

Publisher

Cold Spring Harbor Laboratory

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3