Attentional modulation of neural sound tracking in children with and without dyslexia.

Auditory selective attention forms an important foundation of children's learning by enabling the prioritisation and encoding of relevant stimuli. It may also influence reading development, which relies on metalinguistic skills including the awareness of the sound structure of spoken language. Reports of attentional impairments and speech perception difficulties in noisy environments in dyslexic readers are also suggestive of the putative contribution of auditory attention to reading development. To date, it is unclear whether non-speech selective attention and its underlying neural mechanisms are impaired in children with dyslexia and to which extent these deficits relate to individual reading and speech perception abilities in suboptimal listening conditions. In this EEG study, we assessed non-speech sustained auditory selective attention in 106 7-to-12-year-old children with and without dyslexia. Children attended to one of two tone streams, detecting occasional sequence repeats in the attended stream, and performed a speech-in-speech perception task. Results show that when children directed their attention to one stream, inter-trial-phase-coherence at the attended rate increased in fronto-central sites; this, in turn, was associated with better target detection. Behavioural and neural indices of attention did not systematically differ as a function of dyslexia diagnosis. However, behavioural indices of attention did explain individual differences in reading fluency and speech-in-speech perception abilities: both these skills were impaired in dyslexic readers. Taken together, our results show that children with dyslexia do not show group-level auditory attention deficits but these deficits may represent a risk for developing reading impairments and problems with speech perception in complex acoustic environments. RESEARCH HIGHLIGHTS: Non-speech sustained auditory selective attention modulates EEG phase coherence in children with/without dyslexia Children with dyslexia show difficulties in speech-in-speech perception Attention relates to dyslexic readers' speech-in-speech perception and reading skills Dyslexia diagnosis is not linked to behavioural/EEG indices of auditory attention.

Genome-wide association study reveals new insights into the heritability and genetic correlates of developmental dyslexia.

Developmental dyslexia (DD) is a learning disorder affecting the ability to read, with a heritability of 40-60%. A notable part of this heritability remains unexplained, and large genetic studies are warranted to identify new susceptibility genes and clarify the genetic bases of dyslexia. We carried out a genome-wide association study (GWAS) on 2274 dyslexia cases and 6272 controls, testing associations at the single variant, gene, and pathway level, and estimating heritability using single-nucleotide polymorphism (SNP) data. We also calculated polygenic scores (PGSs) based on large-scale GWAS data for different neuropsychiatric disorders and cortical brain measures, educational attainment, and fluid intelligence, testing them for association with dyslexia status in our sample. We observed statistically significant (p < 2.8 × 10-6) enrichment of associations at the gene level, for LOC388780 (20p13; uncharacterized gene), and for VEPH1 (3q25), a gene implicated in brain development. We estimated an SNP-based heritability of 20-25% for DD, and observed significant associations of dyslexia risk with PGSs for attention deficit hyperactivity disorder (at pT = 0.05 in the training GWAS: OR = 1.23[1.16; 1.30] per standard deviation increase; p = 8 × 10-13), bipolar disorder (1.53[1.44; 1.63]; p = 1 × 10-43), schizophrenia (1.36[1.28; 1.45]; p = 4 × 10-22), psychiatric cross-disorder susceptibility (1.23[1.16; 1.30]; p = 3 × 10-12), cortical thickness of the transverse temporal gyrus (0.90[0.86; 0.96]; p = 5 × 10-4), educational attainment (0.86[0.82; 0.91]; p = 2 × 10-7), and intelligence (0.72[0.68; 0.76]; p = 9 × 10-29). This study suggests an important contribution of common genetic variants to dyslexia risk, and novel genomic overlaps with psychiatric conditions like bipolar disorder, schizophrenia, and cross-disorder susceptibility. Moreover, it revealed the presence of shared genetic foundations with a neural correlate previously implicated in dyslexia by neuroimaging evidence.

Numerical predictors of arithmetic success in grades 1-6.

Math relies on mastery and integration of a wide range of simpler numerical processes and concepts. Recent work has identified several numerical competencies that predict variation in math ability. We examined the unique relations between eight basic numerical skills and early arithmetic ability in a large sample (N = 1391) of children across grades 1-6. In grades 1-2, children's ability to judge the relative magnitude of numerical symbols was most predictive of early arithmetic skills. The unique contribution of children's ability to assess ordinality in numerical symbols steadily increased across grades, overtaking all other predictors by grade 6. We found no evidence that children's ability to judge the relative magnitude of approximate, nonsymbolic numbers was uniquely predictive of arithmetic ability at any grade. Overall, symbolic number processing was more predictive of arithmetic ability than nonsymbolic number processing, though the relative importance of symbolic number ability appears to shift from cardinal to ordinal processing.

What basic number processing measures in kindergarten explain unique variability in first-grade arithmetic proficiency?

Relations between children's mathematics achievement and their basic number processing skills have been reported in both cross-sectional and longitudinal studies. Yet, some key questions are currently unresolved, including which kindergarten skills uniquely predict children's arithmetic fluency during the first year of formal schooling and the degree to which predictors are contingent on children's level of arithmetic proficiency. The current study assessed kindergarteners' non-symbolic and symbolic number processing efficiency. In addition, the contribution of children's underlying magnitude representations to differences in arithmetic achievement was assessed. Subsequently, in January of Grade 1, their arithmetic proficiency was assessed. Hierarchical regression analysis revealed that children's efficiency to compare digits, count, and estimate numerosities uniquely predicted arithmetic differences above and beyond the non-numerical factors included. Moreover, quantile regression analysis indicated that symbolic number processing efficiency was consistently a significant predictor of arithmetic achievement scores regardless of children's level of arithmetic proficiency, whereas their non-symbolic number processing efficiency was not. Finally, none of the task-specific effects indexing children's representational precision was significantly associated with arithmetic fluency. The implications of the results are 2-fold. First, the findings indicate that children's efficiency to process symbols is important for the development of their arithmetic fluency in Grade 1 above and beyond the influence of non-numerical factors. Second, the impact of children's non-symbolic number processing skills does not depend on their arithmetic achievement level given that they are selected from a nonclinical population.

The COVID generation: Online dyslexia treatment equally effective as face-to-face treatment in a Dutch sample.

Due to pandemic-induced lockdown(s) in 2020, dyslexia treatment was forced to move to online platforms. This study examined whether Dutch children who received online treatment progressed as much in their reading and spelling performance as children who received the usual face-to-face treatment. To this end, 254 children who received treatment-as-usual were compared to 162 children who received online treatment with Bayesian methods. The advantage of a Bayesian approach is that it can provide evidence for and against the null hypothesis whereas frequentist approaches only provide evidence against it. We found that children in the online treatment condition received slightly fewer treatment sessions but progressed equally after controlling for the number of sessions compared to the treatment-as-usual condition. These results have clinical and practical implications as they show that reading treatment can be successfully delivered online.

Predictors of developmental dyslexia in European orthographies with varying complexity.

BACKGROUND: The relationship between phoneme awareness, rapid automatized naming (RAN), verbal short-term/working memory (ST/WM) and diagnostic category is investigated in control and dyslexic children, and the extent to which this depends on orthographic complexity. METHODS: General cognitive, phonological and literacy skills were tested in 1,138 control and 1,114 dyslexic children speaking six different languages spanning a large range of orthographic complexity (Finnish, Hungarian, German, Dutch, French, English). RESULTS: Phoneme deletion and RAN were strong concurrent predictors of developmental dyslexia, while verbal ST/WM and general verbal abilities played a comparatively minor role. In logistic regression models, more participants were classified correctly when orthography was more complex. The impact of phoneme deletion and RAN-digits was stronger in complex than in less complex orthographies. CONCLUSIONS: Findings are largely consistent with the literature on predictors of dyslexia and literacy skills, while uniquely demonstrating how orthographic complexity exacerbates some symptoms of dyslexia.

Orthographic depth and its impact on universal predictors of reading: a cross-language investigation.

Alphabetic orthographies differ in the transparency of their letter-sound mappings, with English orthography being less transparent than other alphabetic scripts. The outlier status of English has led scientists to question the generality of findings based on English-language studies. We investigated the role of phonological awareness, memory, vocabulary, rapid naming, and nonverbal intelligence in reading performance across five languages lying at differing positions along a transparency continuum (Finnish, Hungarian, Dutch, Portuguese, and French). Results from a sample of 1,265 children in Grade 2 showed that phonological awareness was the main factor associated with reading performance in each language. However, its impact was modulated by the transparency of the orthography, being stronger in less transparent orthographies. The influence of rapid naming was rather weak and limited to reading and decoding speed. Most predictors of reading performance were relatively universal across these alphabetic languages, although their precise weight varied systematically as a function of script transparency.

Long-term cognitive dynamics of fluent reading development.

Most theories of reading development assume a shift from slow sequential subword decoding to automatic processing of orthographic word forms. We hypothesized that this shift should be reflected in a concomitant shift in reading-related cognitive functions. The current study investigated the cognitive dynamics underlying reading development in a large school sample ranging from beginning to experienced readers. The results showed that phonological awareness (PA) and rapid automatized naming (RAN) contributed substantially to reading fluency over all six primary school grades. However, the relationship between PA and word (but not pseudoword) reading fluency decreased as a function of reading experience, whereas the relationship between RAN and word reading fluency increased gradually. Moreover, this cognitive shift was most pronounced for high-frequency words. The results seem to point to the development of one (and only one) reading network for all types of words in which processing load or type of processing depends on word familiarity and amount of reading experience.

Naming problems do not reflect a second independent core deficit in dyslexia: double deficits explored.

The double deficit hypothesis states that naming speed problems represent a second core deficit in dyslexia independent from a phonological deficit. The current study investigated the main assumptions of this hypothesis in a large sample of well-diagnosed dyslexics. The three main findings were that (a) naming speed was consistently related only to reading speed; (b) phonological processing speed and naming speed loaded on the same factor, and this factor contributed strongly to reading speed; and (c) although general processing speed was involved in speeded naming of visual items, it did not explain the relationship between naming speed and reading speed. The results do not provide support for the existence of a second independent core naming deficit in dyslexia and indicate that speeded naming tasks are mainly phonological processing speed tasks with an important addition: fast cross-modal matching of visual symbols and phonological codes.

Genome-wide association scan identifies new variants associated with a cognitive predictor of dyslexia.

Developmental dyslexia (DD) is one of the most prevalent learning disorders, with high impact on school and psychosocial development and high comorbidity with conditions like attention-deficit hyperactivity disorder (ADHD), depression, and anxiety. DD is characterized by deficits in different cognitive skills, including word reading, spelling, rapid naming, and phonology. To investigate the genetic basis of DD, we conducted a genome-wide association study (GWAS) of these skills within one of the largest studies available, including nine cohorts of reading-impaired and typically developing children of European ancestry (N = 2562-3468). We observed a genome-wide significant effect (p < 1 × 10-8) on rapid automatized naming of letters (RANlet) for variants on 18q12.2, within MIR924HG (micro-RNA 924 host gene; rs17663182 p = 4.73 × 10-9), and a suggestive association on 8q12.3 within NKAIN3 (encoding a cation transporter; rs16928927, p = 2.25 × 10-8). rs17663182 (18q12.2) also showed genome-wide significant multivariate associations with RAN measures (p = 1.15 × 10-8) and with all the cognitive traits tested (p = 3.07 × 10-8), suggesting (relational) pleiotropic effects of this variant. A polygenic risk score (PRS) analysis revealed significant genetic overlaps of some of the DD-related traits with educational attainment (EDUyears) and ADHD. Reading and spelling abilities were positively associated with EDUyears (p ~ [10-5-10-7]) and negatively associated with ADHD PRS (p ~ [10-8-10-17]). This corroborates a long-standing hypothesis on the partly shared genetic etiology of DD and ADHD, at the genome-wide level. Our findings suggest new candidate DD susceptibility genes and provide new insights into the genetics of dyslexia and its comorbities.

Cognitive and familial risk evidence converged: A data-driven identification of distinct and homogeneous subtypes within the heterogeneous sample of reading disabled children.

The evident degree of heterogeneity observed in reading disabled children has puzzled reading researchers for decades. Recent advances in the genetic underpinnings of reading disability have indicated that the heritable, familial risk for dyslexia is a major risk factor. The present data-driven, classification attempt aims to revisit the possibility of identifying distinct cognitive deficit profiles in a large sample of second to fourth grade reading disabled children. In this sample, we investigated whether genetic and environmental risk factors are able to distinguish between poor reader subtypes. In this profile, we included reading-related measures of phonemic awareness, letter-speech sound processing and rapid naming, known as candidate vulnerability markers associated with dyslexia and familial risk for dyslexia, as well as general cognitive abilities (non-verbal IQ and vocabulary). Clustering was based on a 200 multi-start K-means approach. Results revealed four emerging subtypes of which the first subtype showed no cognitive deficits underlying their poor reading skills (Reading-only impaired poor readers). The other three subtypes shared a core phonological deficit (PA) with a variable and discriminative expression across the other underlying vulnerability markers. More specific, type 2 showed low to poor performance across all reading-related and general cognitive abilities (general poor readers), type 3 showed a specific letter-speech sound mapping deficit next to a PA deficit (PA-LS specific poor readers) and type 4 showed a specific rapid naming deficit complementing their phonological weakness (PA-RAN specific poor readers). The first three poor reader profiles were more characterized by variable environmental risk factor, while the fourth, PA-RAN poor reader subtype showed a significantly strong familial risk for dyslexia. Overall, when we zoom in on the heterogeneous phenomenon of reading disability, unique and distinct cognitive subtypes can be identified, distinguishing between those poor readers more influences by the role of genes and those more influenced by environmental risk factors. Taking into account this diversity of distinct cognitive subtypes, instead of looking at the reading disabled sample as a whole, will help tailor future diagnostic and intervention efforts more specifically to the needs of children with such a specific deficit and risk pattern, as well as providing a more promising way forward for genetic studies of dyslexia.

Cognitive subtypes of mathematics learning difficulties in primary education.

It has been asserted that children with mathematics learning difficulties (MLD) constitute a heterogeneous group. To date, most researchers have investigated differences between predefined MLD subtypes. Specifically MLD children are frequently categorized a priori into groups based on the presence or absence of an additional disorder, such as a reading disorder, to examine cognitive differences between MLD subtypes. In the current study 226 third to six grade children (M age=131 months) with MLD completed a selection of number specific and general cognitive measures. The data driven approach was used to identify the extent to which performance of the MLD children on these measures could be clustered into distinct groups. In particular, after conducting a factor analysis, a 200 times repeated K-means clustering approach was used to classify the children's performance. Results revealed six distinguishable clusters of MLD children, specifically (a) a weak mental number line group, (b) weak ANS group, (c) spatial difficulties group, (d) access deficit group, (e) no numerical cognitive deficit group and (f) a garden-variety group. These findings imply that different cognitive subtypes of MLD exist and that these can be derived from data-driven approaches to classification. These findings strengthen the notion that MLD is a heterogeneous disorder, which has implications for the way in which intervention may be tailored for individuals within the different subtypes.

Genetic analysis of dyslexia candidate genes in the European cross-linguistic NeuroDys cohort.

Dyslexia is one of the most common childhood disorders with a prevalence of around 5-10% in school-age children. Although an important genetic component is known to have a role in the aetiology of dyslexia, we are far from understanding the molecular mechanisms leading to the disorder. Several candidate genes have been implicated in dyslexia, including DYX1C1, DCDC2, KIAA0319, and the MRPL19/C2ORF3 locus, each with reports of both positive and no replications. We generated a European cross-linguistic sample of school-age children - the NeuroDys cohort - that includes more than 900 individuals with dyslexia, sampled with homogenous inclusion criteria across eight European countries, and a comparable number of controls. Here, we describe association analysis of the dyslexia candidate genes/locus in the NeuroDys cohort. We performed both case-control and quantitative association analyses of single markers and haplotypes previously reported to be dyslexia-associated. Although we observed association signals in samples from single countries, we did not find any marker or haplotype that was significantly associated with either case-control status or quantitative measurements of word-reading or spelling in the meta-analysis of all eight countries combined. Like in other neurocognitive disorders, our findings underline the need for larger sample sizes to validate possibly weak genetic effects.

Support systems for poor readers: empirical data from six EU member states.

This study surveyed and compared support systems for poor readers in six member states of the European Union (EU). The goal was to identify features of effective support systems. A large-scale questionnaire survey was conducted among mainstream teachers (n = 4,210) and remedial teachers (n = 2,395). Results indicate that the six support systems differed substantially, with effective support systems showing high performance on all variables measured. More specifically, effective support systems were characterized by (a) high levels of both teacher and student support and (b) frequent interactions between teachers and remedial teachers as well as between remedial teachers and diagnosticians. The high prevalence of poor reading ability in the current EU member states demonstrates that educational reforms are critically needed. The results of this study provide concrete starting points for improving support systems for poor readers.