LRTCs

LRTC
  • 文章类型: Journal Article
    目的:探讨高频振荡(HFO)和长程时间相关性(LRTC)在癫痫术前评估中的实用性。
    方法:对59例耐药癫痫患者进行MEG波纹检测,包括5例患有顶叶癫痫(PLE),21患有额叶癫痫(FLE),14例颞叶外侧癫痫(LTLE),和19伴有颞叶内侧癫痫(MTLE),以确定癫痫发生区(EZ)。将结果与临床MEG报告和切除面积进行比较。随后,通过去趋势波动分析(DFA)和90个大脑皮层区域的5个条带的生活/等待时间,在源水平对LRTC进行了定量。将具有较大DFA指数和标准化的生命等待生物标志物的大脑区域与切除结果进行比较。
    结果:与MEG传感器级数据相比,波纹源更频繁地位于切除区域内。此外,来源水平分析显示,DFA指数和等待生命的生物标志物的比例较高,排名相对较高,主要分布在切除区域内(p<0.01)。此外,这两个LRCT指数在五个不同的频带与EZ相关。
    结论:HFO和来源水平LRTC与EZ相关。整合HFO和LRTC可能是术前评估癫痫的有效方法。
    OBJECTIVE: To explore the utility of high frequency oscillations (HFO) and long-range temporal correlations (LRTCs) in preoperative assessment of epilepsy.
    METHODS: MEG ripples were detected in 59 drug-resistant epilepsy patients, comprising 5 with parietal lobe epilepsy (PLE), 21 with frontal lobe epilepsy (FLE), 14 with lateral temporal lobe epilepsy (LTLE), and 19 with mesial temporal lobe epilepsy (MTLE) to identify the epileptogenic zone (EZ). The results were compared with clinical MEG reports and resection area. Subsequently, LRTCs were quantified at the source-level by detrended fluctuation analysis (DFA) and life/waiting -time at 5 bands for 90 cerebral cortex regions. The brain regions with larger DFA exponents and standardized life-waiting biomarkers were compared with the resection results.
    RESULTS: Compared to MEG sensor-level data, ripple sources were more frequently localized within the resection area. Moreover, source-level analysis revealed a higher proportion of DFA exponents and life-waiting biomarkers with relatively higher rankings, primarily distributed within the resection area (p<0.01). Moreover, these two LRCT indices across five distinct frequency bands correlated with EZ.
    CONCLUSIONS: HFO and source-level LRTCs are correlated with EZ. Integrating HFO and LRTCs may be an effective approach for presurgical evaluation of epilepsy.
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  • 文章类型: Journal Article
    十多年来,神经影像学和脑刺激研究已经调查了第三方惩罚的神经机制,社会规范执行的关键工具。然而,这些机制背后的神经动力学仍不清楚.先前对第三方惩罚的脑电图研究表明,脑间连接与惩罚行为有关。然而,没有明确的证据表明脑间连通性对第三方惩罚的影响是否由局部神经元状态介导.在这项研究中,我们进一步研究了α频率范围内的静息态神经元活动是否可以预测第三方惩罚的个体差异.更具体地说,我们发现右背外侧前额叶和右颞顶叶区域之间的整体静息状态连通性与第三方惩罚水平呈负相关.此外,在右颞顶叶皮质中具有更强的局部静息状态长期时间相关性的个体显示出较低的第三方惩罚水平。因此,我们的结果进一步支持以下观点:全局和局部神经元动力学可能导致第三方惩罚的个体差异.
    For over a decade, neuroimaging and brain stimulation studies have investigated neural mechanisms of third-party punishment, a key instrument for social norms enforcement. However, the neural dynamics underlying these mechanisms are still unclear. Previous electroencephalographic studies on third-party punishment have shown that inter-brain connectivity is linked to punishment behavior. However, no clear evidence was provided regarding whether the effect of inter-brain connectivity on third-party punishment is mediated by local neuronal states. In this study, we further investigate whether resting-state neuronal activity in the alpha frequency range can predict individual differences in third-party punishment. More specifically, we show that the global resting-state connectivity between the right dorsolateral prefrontal and right temporo-parietal regions is negatively correlated with the level of third-party punishment. Additionally, individuals with stronger local resting-state long-range temporal correlations in the right temporo-parietal cortices demonstrated a lower level of third-party punishment. Thus, our results further support the idea that global and local neuronal dynamics can contribute to individual differences in third-party punishment.
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