Neurogenetic profiles delineate large-scale connectivity dynamics of the human brain.
Neurogenetic profiles delineate large-scale connectivity dynamics of the human brain.
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DOI：
10.1038/s41467-018-06346-3
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发表时间：
2018-09-24
影响因子：
16.6
通讯作者：
Sepulcre J
中科院分区：
文献类型：
--
作者：
Diez I;Sepulcre J
神经活动的实验和建模工作描述了大脑微电路中的循环和吸引子动态模式。然而，人们对是否存在类似的动力学原理或是否可以推广到大规模水平仍然知之甚少。在这里，我们应用基于动态图论的分析来评估跨认知状态的全脑功能连接随时间的动态流。本地网络中的动态连接位于任务期间的注意力区域和休息状态期间的主要感觉区域，分布式网络中的动态连接在任务和休息状态下都汇聚在默认模式网络（DMN）中。重要的是，我们发现独特的动态连接模式在空间上与突触长期增强和长期抑郁相关基因的艾伦人脑图谱遗传转录水平相关。我们的研究结果支持 DMN 内异模态皮层大规模吸引子样动力学的神经生物学基础，无论认知状态如何。吸引子动力学已在神经回路中被发现，但尚不清楚它们是否存在于全脑活动水平。在这里，作者表明，无论大脑状态如何，某些大脑区域都充当许多活动“流”汇聚的节点。这些区域显示出独特的基因表达。
Experimental and modeling work of neural activity has described recurrent and attractor dynamic patterns in cerebral microcircuits. However, it is still poorly understood whether similar dynamic principles exist or can be generalizable to the large-scale level. Here, we applied dynamic graph theory-based analyses to evaluate the dynamic streams of whole-brain functional connectivity over time across cognitive states. Dynamic connectivity in local networks is located in attentional areas during tasks and primary sensory areas during rest states, and dynamic connectivity in distributed networks converges in the default mode network (DMN) in both task and rest states. Importantly, we find that distinctive dynamic connectivity patterns are spatially associated with Allen Human Brain Atlas genetic transcription levels of synaptic long-term potentiation and long-term depression-related genes. Our findings support the neurobiological basis of large-scale attractor-like dynamics in the heteromodal cortex within the DMN, irrespective of cognitive state. Attractor dynamics have been discovered in neural circuits, but it is not clear if they exist at the level of whole-brain activity. Here, the authors show that certain brain regions act as nodes in which many activity ‘streams’ converge, regardless of brain state. These regions show distinctive gene expression.
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影响因子：
4.3
作者：
Bressler SL;Kelso JA
通讯作者：
Kelso JA
影响因子：
3.7
作者：
Breakspear, M.;Roberts, J. A.;Robinson, P. A.
通讯作者：
Robinson, P. A.
影响因子：
5.7
作者：
Cabral, Joana;Hugues, Etienne;Deco, Gustavo
通讯作者：
Deco, Gustavo
影响因子：
4.3
作者：
Deco, Gustavo;Jirsa, Viktor K.;Robinson, Peter A.;Breakspear, Michael;Friston, Karl J.
通讯作者：
Friston, Karl J.
影响因子：
16.2
作者：
de Pasquale F;Della Penna S;Snyder AZ;Marzetti L;Pizzella V;Romani GL;Corbetta M
通讯作者：
Corbetta M