Department of Psychological Sciences (BMA), Centre for Brain and Cognitive Development, Birkbeck College, University of London, Malet Street, London, WC1E 7HX, UK.
Department of Experimental Psychology, Helmholtz Institute, Utrecht University, Heidelberglaan 1, 3584 CS, Utrecht, The Netherlands.
Sci Rep. 2020 Jul 29;10(1):12703. doi: 10.1038/s41598-020-68981-5.
Atypicalities in connectivity between brain regions have been implicated in a range of neurocognitive disorders. We require metrics to assess stable individual differences in connectivity in the developing brain, while facing the challenge of limited data quality and quantity. Here, we examine how varying core processing parameters can optimise the test-retest reliability of EEG connectivity measures in infants. EEG was recorded twice with a 1-week interval between sessions in 10-month-olds. EEG alpha connectivity was measured across different epoch lengths and numbers, with the phase lag index (PLI) and debiased weighted PLI (dbWPLI), for both whole-head connectivity and graph theory metrics. We calculated intra-class correlations between sessions for infants with sufficient data for both sessions (N's = 19-41, depending on the segmentation method). Reliability for the whole brain dbWPLI was higher across many short epochs, whereas reliability for the whole brain PLI was higher across fewer long epochs. However, the PLI is confounded by the number of available segments. Reliability was higher for whole brain connectivity than graph theory metrics. Thus, segmenting available data into a high number of short epochs and calculating the dbWPLI is most appropriate for characterising connectivity in populations with limited availability of EEG data.
大脑区域之间连接的非典型性与一系列神经认知障碍有关。我们需要指标来评估发育中大脑连接的稳定个体差异，同时面临着数据质量和数量有限的挑战。在这里，我们研究了核心处理参数的变化如何优化婴儿脑电图连接测量的重测信度。在 10 个月大的婴儿中，每隔一周进行两次脑电图记录。在不同的时间窗口长度和数量上，使用相位滞后指数 (PLI) 和无偏加权 PLI (dbWPLI)，测量整个头部连接和图论指标的 EEG 阿尔法连接。对于两个时间窗口都有足够数据的婴儿（取决于分段方法，N's = 19-41），我们计算了会话之间的组内相关系数。对于许多短时间窗口，整个大脑 dbWPLI 的可靠性更高，而对于较少的长时间窗口，整个大脑 PLI 的可靠性更高。然而，PLI 受到可用段数的影响。整个大脑连接的可靠性高于图论指标。因此，将可用数据分割成大量短时间窗口，并计算 dbWPLI 最适合于描述 EEG 数据有限的人群中的连接。
