Artificial Intelligence and Information Analysis Laboratory, Department of Informatics, Aristotle University, Thessaloniki, Greece; 3rd Department of Neurology, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece.
School of Medicine, University of Crete, Heraklion, Greece; Institute of Computer Science, Computational Biomedicine Laboratory, Foundation for Research and Technology, Heraklion, Greece.
Int J Psychophysiol. 2018 Apr;126:20-29. doi: 10.1016/j.ijpsycho.2018.02.008. Epub 2018 Feb 21.
Neuroimaging studies have identified a variety of structural and functional connectivity abnormalities in students experiencing reading difficulties. The present study adopted a novel approach to assess the dynamics of resting-state neuromagnetic recordings in the form of symbolic sequences (i.e., repeated patterns of neuromagnetic fluctuations within and/or between sensors). Participants were 25 students experiencing severe reading difficulties (RD) and 27 age-matched non-impaired readers (NI) aged 7-14 years. Sensor-level data were first represented as symbolic sequences in eight conventional frequency bands. Next, dominant types of sensor-to-sensor interactions in the form of intra and cross-frequency coupling were computed and subjected to graph modeling to assess group differences in global network characteristics. As a group RD students displayed predominantly within-frequency interactions between neighboring sensors which may reflect reduced overall global network efficiency and cost-efficiency of information transfer. In contrast, sensor networks among NI students featured a higher proportion of cross-frequency interactions. Brain-reading achievement associations highlighted the role of left hemisphere temporo-parietal functional networks, at rest, for reading acquisition and ability.
神经影像学研究已经确定了在阅读困难的学生中存在各种结构和功能连接异常。本研究采用了一种新的方法来评估静息状态神经磁记录的动力学，以符号序列的形式呈现（即传感器内和/或传感器之间的神经磁波动的重复模式）。参与者包括 25 名患有严重阅读障碍（RD）的学生和 27 名年龄匹配的非受损阅读者（NI），年龄在 7-14 岁之间。首先，将传感器级别的数据表示为八个常规频带中的符号序列。接下来，计算传感器间以同频和跨频耦合形式的主要交互类型，并对其进行图建模，以评估全局网络特征的组间差异。作为一个整体，RD 学生表现出相邻传感器之间主要的同频相互作用，这可能反映了整体全局网络效率和信息传递的成本效率降低。相比之下，NI 学生的传感器网络中跨频相互作用的比例更高。大脑阅读成绩的关联强调了静息时左半球颞顶叶功能网络对阅读习得和能力的作用。
