# Neurofeedback Effects on EEG Connectivity among Children with Reading Disorders: I. Coherence
### EEG Characteristics in Children with RD  
The human electroencephalogram (EEG) reflects the ongoing rhythmic electrical activity of the brain. EEG characteristics are different depending on recording conditions. In this section, references will be made exclusively to the EEG recorded at rest. The most commonly reported resting-state EEG pattern in children with RDs is an excess of slow activity, primarily in the theta frequency range [22; 23; 24; 25; 26; 27; 28; 29], and an alpha activity deficit [26; 28; 29; 30; 31; 32] when compared to children with typical development. However, there is no consensus regarding what brain regions with atypical patterns are implicated. Some authors have found theta excess in almost all leads [23; 26], and other studies have found theta excess in bilateral frontal lobes [22; 24; 30], the left temporal region [22; 25], the right temporal region [27] or bilateral parieto occipital areas [25; 28]. Regarding alpha power, some authors found alpha deficits in all leads except in the bilateral occipital and right centroparietal areas [26], while other studies have found deficits in the bilateral occipital area [22]. Most studies found alpha deficits in the parietoocortical area [25; 28; 30; 32] with left predominance [25]. However, [PERSON] et al. [23] detected alpha deficits in right frontal and left frontocentral leads when they controlled for socioeconomic status, and [PERSON] and [PERSON] [24] reported alpha deficits in the left frontal region of children with nonspecified learning disorders and the left centro-temporal-parietal region of children with learning disorders with verbal deficits. The increased theta and decreased alpha activity pattern described in children with RDs correspond to a normal EEG pattern of a younger child; therefore, this finding has been interpreted as these children with RDs exhibiting a delay in electroencephalographic maturation [23; 31]. The nervous system is organized into neural networks for information processing. Therefore, the study of brain connectivity is relevant. However, most studies exploring brain activity in children with learning disorders using EEGs have been based on EEG power analysis, and few have focused on functional connectivity measures. Functional connectivity is a way of measuring the strength of the connection between different structures. There is an increasing number of theoretical and empirical studies that approach the study of the function of the human brain from a network perspective. Specifically, in this study, it is of interest to examine the connection between the regions that constitute the reading network, namely, the posterior dorsal pathway, the posterior ventral pathway, and the anterior network, located in the left hemisphere, to evaluate processes involved in reading in children with RDs (phonological decoding, fast orthographic word recognition, and phonological and articulatory processes). Examining these connections may explain the behavioral deficits observed in accuracy, comprehension, and reading speed. Studying brain connectivity not only allows for the identification of isolated brain areas that participate in a certain function but also shows the neural networks involved and their interactions [33]. EEG coherence has been widely used to study the functional connectivity between different brain areas [34] because it provides a quantifiable measure of the synchrony between the electrical activity of structures beneath the recording electrodes on the scalp [35; 36; 37; 38]. Currently, there are better measures to assess EEG connectivity [27]; however, in this study, the coherence between sensors was examined because it is the measure that is used in the clinical setting. Furthermore, coherence has been previously used to characterize the EEGs of children with RDs, and thus, it is possible to compare the results of the present study with previous results and validate their reproducibility.