模拟区域异质性和潜在的大脑功能网络的关键动态之间的相互作用
Jijin Zhang1, Kejian Wu1, Jiaqi Dong1
1School of Physical Science and Technology, Lanzhou Center for Theoretical Physics, Key Laboratory of Theoretical Physics of Gansu Province, and Key Laboratory of Quantum Theory and Applications of MoE, Lanzhou University, Lanzhou, Gansu 730000, China.
概括
神经活动同步中的大脑区域差异与基因表达相关. 在大脑网络模型中增加这种异质性可以提高它们复制真实大脑连接模式和个体差异的能力.
科学领域:
- 神经科学是一个神经科学.
- 计算神经科学是一种神经科学.
- 系统神经科学 系统神经科学
背景情况:
- 人类大脑功能依赖于复杂的网络连接,但区域异质性如何影响这一点尚未完全理解.
- 局部神经动力学及其与基因表达和大规模网络功能的关系需要进一步研究.
研究的目的:
- 调查局部大脑动态中的区域异质性如何促进全脑功能连接和认知能力.
- 开发和验证包含区域动态的异质全脑网络模型.
主要方法:
- 分析功能磁共振成像 (fMRI) 数据以测量语音神经活动同步.
- 关联神经同步与激发性和抑制性受体的基因表达数据.
- 构建异构的全脑网络模型,由区域同步措施告知节点刺激性.
- 模拟网络动态,并将新出现的功能连接与实证数据进行比较.
主要成果:
- 大脑区域的神经活动同步与刺激性和抑制性受体基因表达有显著的相关性.
- 运行在临界点附近的异质网络模型产生类似于实证静止状态和任务唤起数据的功能连接模式.
- 这些模型准确地预测了大脑网络中的功能连接和因果影响的个体差异.
结论:
- 局部大脑动态的区域异质性对于产生现实的全脑功能连接至关重要.
- 异质整脑网络模型可以有效地捕捉实证大脑网络特性和个体变异性.
- 这种方法提高了计算模型的预测能力,以了解大脑功能和认知.
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