网络签名定义了焦点发作期间的意识状态
Derek J Doss1,2,3, Graham W Johnson1,2,3, Ghassan S Makhoul1,2,3
1Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA.
Epilepsia
|July 26, 2024
概括
焦点受损意识发作 (FIAS) 和深度睡眠有类似的大脑网络变化,与其他类型的发作不同. 这一发现可能会导致在发作期间保持意识的新方法.
科学领域:
- 神经科学是一个神经科学.
- 发病学 (Epileptology) 是一个专业的学科.
- 计算神经科学是一种神经科学.
背景情况:
- 影响全球人口的1%,在焦点受损意识发作 (FIASs) 和焦点对双边强力-克隆发作 (FBTCSs) 中,失去意识是特别令人虚弱的.
- 导致发作期间失去意识的潜在网络机制尚未完全理解.
- 之前的研究指出,活动和间连接的变化,但网络状态在不同的类型仍然未评估.
研究的目的:
- 通过使用先进的网络措施,研究和比较焦点意识发作 (FAS),FIAS和FBTCS的ictal网络状态.
- 探索期间大脑网络动态与意识状态之间的关系.
- 开发一种深度学习模型来分类影响意识的发作.
主要方法:
- 分析了74名患者的立体电脑图 (SEEG) 数据.
- 滑动窗带功率,功能连接和隔离被计算为 preictal, ictal 和 postictal 期间.
- 使用SEEG和fMRI评估皮下与新皮层的连接性,并使用卷积神经网络进行类型分类.
主要成果:
- 影响意识的发作 (FIAS,FBTCS) 和深度睡眠显示,前对面皮质的三角带功率增加.
- FIAS和深度睡眠独特地表现出增加的三角形和减少的马分离.
- 与对照组相比,患有FIAS的患者表现出皮下皮层与新皮层功能连接性降低.
- 一个深度学习网络在检测影响意识的发作时实现了0.75的AUC.
结论:
- 这项研究揭示了不同焦点发作类型的不同点网络动态.
- 在FIAS中Ictal网络的变化与在自然深度睡眠中观察到的变化非常相似,使其与FBTCS区别开来.
- 这些发现为开发新的神经调节策略提供了潜力,以保持患者的意识.
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