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.

中文翻译：

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使用降噪自动编码器检测阅读障碍的脑电图连接分析

时间采样框架 (TSF) 认为，阅读障碍的特征性语音困难是由一个或多个时间速率的非典型振荡采样引起的。LEEDUCA 研究对儿童用慢节奏韵律（0.5-1[公式：见正文]Hz）、音节（4-8[公式：见正文）收听调幅 (AM) 噪声进行了一系列脑电图 (EEG) 实验]Hz）或音素（12-40[公式：见文本]Hz）速率，旨在检测可能与阅读障碍相关的振荡采样感知的差异。这项工作的目的是检查这些差异是否存在，以及它们与儿童在通常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，估计了时间和频谱通道间脑电图连接，并且训练去噪自动编码器（DAE）来学习连接矩阵的低维表示。这种表示是通过相关性和分类分析进行研究的，它揭示了检测阅读障碍受试者的能力，准确度高于 0.8，平衡准确度在 0.7 左右。DAE 表征的一些特征与儿童在语音假设类别的语言和认知任务（如语音意识和快速符号命名）以及阅读效率和阅读理解方面的表现显着相关（[公式：见文本]）。最后，对邻接矩阵的更深入分析揭示了 DD 受试者颞叶（大致为初级听觉皮层）电极之间的双边连接减少，以及增加的 F7 电极的连接性，大致位于 Broca 区域。这些结果为使用更客观的方法（如 EEG）对阅读障碍进行补充评估铺平了道路。