Department of Communications Engineering, University of Malaga, Malaga, Spain.
DaSCI Andalusian Institute of Data Science and Computational Intelligence, University of Granada, Granada, Spain.
Int J Neural Syst. 2020 Jul;30(7):2050037. doi: 10.1142/S0129065720500379. Epub 2020 May 28.
The Temporal Sampling Framework (TSF) theorizes that the characteristic phonological difficulties of dyslexia are caused by an atypical oscillatory sampling at one or more temporal rates. The LEEDUCA study conducted a series of Electroencephalography (EEG) experiments on children listening to amplitude modulated (AM) noise with slow-rythmic prosodic (0.5-1[Formula: see text]Hz), syllabic (4-8[Formula: see text]Hz) or the phoneme (12-40[Formula: see text]Hz) rates, aimed at detecting differences in perception of oscillatory sampling that could be associated with dyslexia. The purpose of this work is to check whether these differences exist and how they are related to children's performance in different language and cognitive tasks commonly used to detect dyslexia. To this purpose, temporal and spectral inter-channel EEG connectivity was estimated, and a denoising autoencoder (DAE) was trained to learn a low-dimensional representation of the connectivity matrices. This representation was studied via correlation and classification analysis, which revealed ability in detecting dyslexic subjects with an accuracy higher than 0.8, and balanced accuracy around 0.7. Some features of the DAE representation were significantly correlated ([Formula: see text]) with children's performance in language and cognitive tasks of the phonological hypothesis category such as phonological awareness and rapid symbolic naming, as well as reading efficiency and reading comprehension. Finally, a deeper analysis of the adjacency matrix revealed a reduced bilateral connection between electrodes of the temporal lobe (roughly the primary auditory cortex) in DD subjects, as well as an increased connectivity of the F7 electrode, placed roughly on Broca's area. These results pave the way for a complementary assessment of dyslexia using more objective methodologies such as EEG.
时间采样框架（TSF）理论认为，阅读障碍的典型语音困难是由一个或多个时间率的异常振荡采样引起的。LEEDUCA 研究对儿童进行了一系列的脑电图（EEG）实验，这些儿童听的是调幅（AM）噪声，其韵律具有缓慢的节奏（0.5-1[Formula: see text]Hz）、音节（4-8[Formula: see text]Hz）或音素（12-40[Formula: see text]Hz）率，旨在检测与阅读障碍相关的振荡采样感知差异。本工作的目的是检查这些差异是否存在，以及它们与儿童在用于检测阅读障碍的不同语言和认知任务中的表现有何关系。为此，估计了时间和频谱间通道 EEG 连通性，并训练了去噪自动编码器（DAE）以学习连通性矩阵的低维表示。通过相关性和分类分析研究了该表示，结果表明，检测阅读障碍患者的能力准确率高于 0.8，平衡准确率约为 0.7。DAE 表示的一些特征与儿童在语音假设类别（如语音意识和快速符号命名）的语言和认知任务中的表现显著相关（[Formula: see text]），也与阅读效率和阅读理解相关。最后，对邻接矩阵的更深入分析表明，DD 患者的颞叶（大致为初级听觉皮层）电极之间的双侧连接减少，而 F7 电极（大致位于布洛卡区）的连接增加。这些结果为使用更客观的方法（如脑电图）对阅读障碍进行补充评估铺平了道路。
