大脑在认知控制下选择性地将能量分配给功能性大脑网络.
Majid Saberi1,2, Jenny R Rieck3, Shamim Golafshan4
1Neurosciences & Mental Health Program, The Hospital for Sick Children Research Institute, Toronto, Canada. majidsa@umich.edu.
Scientific reports
|December 31, 2024
概括
在认知控制任务期间,大脑网络的能量增加. 这种增加的能量被选择性地分配给感官网络,提高了处理灵活性,并改善了认知任务和年龄的预测模型.
科学领域:
- 神经科学是一个神经科学.
- 复杂系统科学 复杂系统科学
- 认知科学 认知科学
背景情况:
- 网络能量源于复杂网络中的结构平衡理论,为分析大脑功能提供了一个新的框架.
- 了解大脑在认知任务期间如何在功能网络中分配能量,对于阐明神经机制至关重要.
研究的目的:
- 通过使用网络能量框架,在认知控制下评估功能性大脑网络的能量.
- 在各种认知控制任务期间,研究网络能量在规范功能网络的分配.
- 为了评估网络能源的实用性,作为全球网络测量用于预测建模.
主要方法:
- 功能磁共振成像 (fMRI) 数据是从从事认知任务 (工作记忆,抑制控制,认知灵活性) 和在无任务休息状态期间进行认知任务的受试者获得的.
- 从fMRI数据中获得的功能连接模式中提取了网络能量.
- 网络能源被用作全球网络测量,以提高预测建模性能.
主要成果:
- 整个大脑网络的能量在认知控制任务期间显著增加,与无任务的休息状态相比.
- 提高网络能量被选择性地分配;感官网络获得了更多的能量来处理灵活性,而高效的认知网络需要更少的能量.
- 网络能量提高了用于分类认知控制任务和预测时间年龄的预测模型的性能.
结论:
- 网络能量框架提供了一种强大的方法来量化认知控制期间的大脑网络动态.
- 网络能源作为一个有价值的全球网络测量,增强预测建模能力.
- 网络能量显示出作为理解大脑机制和神经疾病的生物标志物的巨大潜力.
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