The impact of computer-assisted technology on literacy acquisition during COVID-19-related school closures: Group-level effects and predictors of individual-level outcomes.

Introduction: The COVID-19 pandemic led to school closure and loss of in-person instruction during the 2019-2020 academic year across the United States, which had a profound impact on the reading development of beginning readers. In this study we tested if a research-informed educational technology (EdTech) program-GraphoLearn-could help alleviate the COVID-19 slide. We also sought to understand the profiles of children who benefitted most from this EdTech program.

How you read affects what you gain: Individual differences in the functional organization of the reading system predict intervention gains in children with reading disabilities.

There is now considerable evidence regarding the types of interventions that are effective at remediating reading disabilities on average. It is generally unclear, however, what predicts the magnitude of individual-level change following a given intervention. We examine new predictors of intervention gains that are theoretically grounded in computational models of reading and focus on individual differences in the functional organization of the reading system.

Prediction of long-term hospitalisation and all-cause mortality in patients with chronic heart failure on Dutch claims data: a machine learning approach.

Background: Accurately predicting which patients with chronic heart failure (CHF) are particularly vulnerable for adverse outcomes is of crucial importance to support clinical decision making. The goal of the current study was to examine the predictive value on long term heart failure (HF) hospitalisation and all-cause mortality in CHF patients, by exploring and exploiting machine learning (ML) and traditional statistical techniques on a Dutch health insurance claims database.

Methods: Our study population consisted of 25,776 patients with a CHF diagnosis code between 2012 and 2014 and one year and three years follow-up HF hospitalisation (1446 and 3220 patients respectively) and all-cause mortality (2434 and 7882 patients respectively) were measured from 2015 to 2018.

Theory-driven classification of reading difficulties from fMRI data using Bayesian latent-mixture models.

Decades of research have led to several competing theories regarding the neural contributors to impaired reading. But how can we know which theory (or theories) identifies the types of markers that indeed differentiate between individuals with reading disabilities (RD) and their typically developing (TD) peers? To answer this question, we propose a new analytical tool for theory evaluation and comparison, grounded in the Bayesian latent-mixture modeling framework. We start by constructing a series of latent-mixture classification models, each reflecting one existing theoretical claim regarding the neurofunctional markers of RD (highlighting network-level differences in either mean activation, inter-subject heterogeneity, inter-region variability, or connectivity).

The brain signature of emerging reading in two contrasting languages.

Despite dissimilarities among scripts, a universal hallmark of literacy in skilled readers is the convergent brain activity for print and speech. Little is known, however, whether this differs as a function of grapheme to phoneme transparency in beginning readers. Here we compare speech and orthographic processing circuits in two contrasting languages, Polish and English, in 100 7-year-old children performing fMRI language localizer tasks.

Individual differences in learning the regularities between orthography, phonology and semantics predict early reading skills.

Statistical views of literacy development maintain that proficient reading requires the assimilation of myriad statistical regularities present in the writing system. Indeed, previous studies have tied statistical learning (SL) abilities to reading skills, establishing the existence of a link between the two. However, some issues are currently left unanswered, including questions regarding the underlying bases for these associations as well as the types of statistical regularities actually assimilated by developing readers.

Adult dyslexic readers benefit less from visual input during audiovisual speech processing: fMRI evidence.

The aim of the present fMRI study was to investigate whether typical and dyslexic adult readers differed in the neural correlates of audiovisual speech processing. We tested for Blood Oxygen-Level Dependent (BOLD) activity differences between these two groups in a 1-back task, as they processed written (word, illegal consonant strings) and spoken (auditory, visual and audiovisual) stimuli. When processing written stimuli, dyslexic readers showed reduced activity in the supramarginal gyrus, a region suggested to play an important role in phonological processing, but only when they processed strings of consonants, not when they read words.

Increased Response to Altered Auditory Feedback in Dyslexia: A Weaker Sensorimotor Magnet Implied in the Phonological Deficit.

Purpose: The purpose of this study was to examine whether developmental dyslexia (DD) is characterized by deficiencies in speech sensory and motor feedforward and feedback mechanisms, which are involved in the modulation of phonological representations.

Method: A total of 42 adult native speakers of Dutch (22 adults with DD; 20 participants who were typically reading controls) were asked to produce /bep/ while the first formant (F1) of the /e/ was not altered (baseline), increased (ramp), held at maximal perturbation (hold), and not altered again (after-effect). The F1 of the produced utterance was measured for each trial and used for statistical analyses.