Phenotyping Ex-Combatants From EEG Scalp Connectivity
Phenotyping Ex-Combatants From EEG Scalp Connectivity
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DOI：
10.1109/access.2018.2872765
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发表时间：
2018-09
期刊：
影响因子：
3.9
通讯作者：
Andrés Quintero-Zea;J. López;Keith M. Smith;N. Trujillo;M. Parra;J. Escudero
中科院分区：
文献类型：
--
作者：
Andrés Quintero-Zea;J. López;Keith M. Smith;N. Trujillo;M. Parra;J. Escudero
参与战争经历可能会对心理健康产生严重后果。这种接触与哥伦比亚前战斗人员的主动攻击调节情绪处理的风险有关。然而，攻击行为背后的认知过程的程度仍然是一个悬而未决的问题。在本文中，我们提出了一种基于支持向量机的处理管道，以识别与非典型情绪处理相关的不同认知表型，基于EEG网络特征的典型相关分析，以及认知和行为评估。结果表明，存在的认知表型与叶分数的平均值和直径的EEG网络跨组的差异。在这些原本健康的受试者中识别表型的能力开辟了帮助制定旨在减少前战斗人员主动攻击性表达的具体干预措施并评估此类干预措施的功效的可能性。
Being involved in war experiences may have severe consequences in mental health. This exposure has been associated in Colombian ex-combatants with risk of proactive aggression modulating emotional processing. However, the extent of the cognitive processes underlying aggressive behavior is still an open issue. In this paper, we propose a support vector machine-based processing pipeline to identify different cognitive phenotypes associated with atypical emotional processing, based on canonical correlation analysis of EEG network features, and cognitive and behavioral evaluations. Results show the existence of cognitive phenotypes associated with differences in the mean value of leaf fraction and diameter of EEG networks across groups. The ability of identifying phenotypes in these otherwise healthy subjects opens up the possibility to aid in the development of specific interventions aimed to reduce expression of proactive aggression in ex-combatants and assessing the efficacy of such interventions.