高能耗标志着叶中异常的大脑状态过渡的特征
Sam S Javidi1, Qirui Zhang1, Ankeeta Ankeeta1
1Farber Institute for Neuroscience, Department of Neurology, Thomas Jefferson University; Philadelphia, PA, USA.
Neurobiology of disease
|September 10, 2025
概括
叶 (TLE) 扰乱了大脑网络的过渡,需要更多的能量,并且涉及更少的区域. 这些低效的脑网络变化可能解释了TLE患者的认知缺陷.
科学领域:
- 神经科学是一个神经科学.
- 网络科学 网络科学
- 医疗成像医学成像
背景情况:
- 叶 (TLE) 涉及非发作和发作大脑状态之间的动态转变.
- 在TLE中控制这些状态过渡的结构性大脑网络尚未得到充分理解.
研究的目的:
- 调查TLE中大脑状态转换背后的结构网络机制.
- 为了比较TLE患者和健康参与者 (HPs) 之间的大脑过渡能量和网络特征.
主要方法:
- 利用休息状态功能性MRI (fMRI) 来检测动态大脑状态.
- 从多扩散权重的MRI数据构建连接的结构性大脑网络.
- 应用网络控制理论来分析TLE和HPs中的大脑状态过渡能量.
主要成果:
- 确定了三个特定的大脑状态过渡,在TLE患者中,与HP患者相比,需要显著更高的能量.
- 在TLE患者中没有观察到异常低能过渡.
- 与HP不同的是,TLE过渡涉及一组有限的源/目标区域,通常在叶外,与HP不同.
结论:
- TLE与异常和低效的结构性大脑网络过渡有关.
- 这些网络低效率可能是活动的结果,并导致在TLE中观察到的认知缺陷.
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