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创伤性脑损伤恢复过程中神经网络成本效率的演变

The evolution of cost-efficiency in neural networks during recovery from traumatic brain injury.

作者信息

Roy Arnab, Bernier Rachel A, Wang Jianli, Benson Monica, French Jerry J, Good David C, Hillary Frank G

机构信息

Department of Psychology, The Pennsylvania State University, University Park, Pennsylvania, United States of America.

Department of Radiology, Hershey Medical Center, Hershey, Pennsylvania, United States of America.

出版信息

PLoS One. 2017 Apr 19;12(4):e0170541. doi: 10.1371/journal.pone.0170541. eCollection 2017.

Abstract

A somewhat perplexing finding in the systems neuroscience has been the observation that physical injury to neural systems may result in enhanced functional connectivity (i.e., hyperconnectivity) relative to the typical network response. The consequences of local or global enhancement of functional connectivity remain uncertain and this is particularly true for the overall metabolic cost of the network. We examine the hyperconnectivity hypothesis in a sample of 14 individuals with TBI with data collected at approximately 3, 6, and 12 months following moderate and severe TBI. As anticipated, individuals with TBI showed increased network strength and cost early after injury, but by one-year post injury hyperconnectivity was more circumscribed to frontal DMN and temporal-parietal attentional control regions. Cost in these subregions was a significant predictor of cognitive performance. Cost-efficiency analysis in the Power 264 data parcellation suggested that at 6 months post injury the network requires higher cost connections to achieve high efficiency as compared to the network 12 months post injury. These results demonstrate that networks self-organize to re-establish connectivity while balancing cost-efficiency trade-offs.

摘要

系统神经科学中一个有点令人困惑的发现是,观察到相对于典型的网络反应,神经系统的物理损伤可能会导致功能连接增强(即超连接)。功能连接局部或全局增强的后果仍不确定,对于网络的整体代谢成本而言尤其如此。我们在14名创伤性脑损伤(TBI)患者的样本中检验了超连接假说,数据收集于中度和重度TBI后约3个月、6个月和12个月。正如预期的那样,TBI患者在受伤后早期表现出网络强度和成本增加,但到受伤后一年,超连接更多地局限于额叶默认模式网络(DMN)和颞顶叶注意力控制区域。这些子区域的成本是认知表现的一个重要预测指标。在Power 264数据分割中的成本效益分析表明,与受伤后12个月的网络相比,受伤后6个月的网络需要更高成本的连接来实现高效率。这些结果表明,网络会自我组织以重新建立连接,同时平衡成本效益的权衡。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7719/5396850/7c755e26e42d/pone.0170541.g001.jpg

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