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Phonological awareness (PA) is at the foundation of reading development: PA is introduced before formal reading instruction, has predictive value for later reading abilities, is a primary target for early intervention, and is considered one of the core mechanisms in developmental dyslexia. Conventional approaches to assessing PA are time-consuming and resource intensive: assessments must be individually administered, require expertise, and scoring verbal responses is challenging and subjective. Therefore, we introduce a rapid, automated, online measure of PA — The Rapid Online Assessment of Reading - Phonological Awareness (ROAR-PA) — that can be widely implemented in classrooms and research studies without a test administrator. We explored whether this gamified, online task, that relies on touchscreen/click responses, can serve as an accurate and reliable measure of PA and as a good predictor of reading development. We found that ROAR-PA is well correlated with standardized measures of PA (CTOPP-2, r = .80) and reading (Woodcock-Johnson, r = .50), for children from Pre-K through fourth grade and achieves exceptional reliability (𝜶 = .96) in a 12-minute automated, online assessment. Furthermore, validation in 50 first and second grade classrooms shows reliable implementation in large, public school classrooms with predictive value of future reading development.

Purpose: It is generally accepted that adults use visual cues to improve speech intelligibility in noisy environments, but findings regarding visual speech benefit in children are mixed. We explored factors that contribute to audiovisual (AV) gain in young children's speech understanding. We examined whether there is an AV benefit to speech-in-noise recognition in children in first grade and if visual salience of phonemes influences their AV benefit. We explored if individual differences in AV speech enhancement could be explained by vocabulary knowledge, phonological awareness, or general psychophysical testing performance. Method: Thirty-seven first graders completed online psychophysical experiments. We used an online single-interval, four-alternative forced-choice picture-pointing task with age-appropriate consonant–vowel–consonant words to measure auditory-only, visual-only, and AV word recognition in noise at −2 and −8 dB SNR. We obtained standard measures of vocabulary and phonological awareness and included a general psychophysical test to examine correlations with AV benefits. Results: We observed a significant overall AV gain among children in first grade. This effect was mainly attributed to the benefit at −8 dB SNR, for visually distinct targets. Individual differences were not explained by any of the child variables. Boys showed lower auditory-only performances, leading to significantly larger AV gains. Conclusions: This study shows AV benefit, of distinctive visual cues, to word recognition in challenging noisy conditions in first graders. The cognitive and linguistic constraints of the task may have minimized the impact of individual differences of vocabulary and phonological awareness on AV benefit. The gender difference should be studied on a larger sample and age range.

The latency of neural responses in the visual cortex changes systematically across the lifespan. Here, we test the hypothesis that development of visual white matter pathways mediates maturational changes in the latency of visual signals. Thirty‐eight children participated in a cross‐sectional study including diffusion magnetic resonance imaging (MRI) and magnetoencephalography (MEG) sessions. During the MEG acquisition, participants performed a lexical decision and a fixation task on words presented at varying levels of contrast and noise. For all stimuli and tasks, early evoked fields were observed around 100 ms after stimulus onset (M100), with slower and lower amplitude responses for low as compared to high contrast stimuli. The optic radiations and optic tracts were identified in each individual's brain based on diffusion MRI tractography. The diffusion properties of the optic radiations predicted M100 responses, especially for high contrast stimuli. Higher optic radiation fractional anisotropy (FA) values were associated with faster and larger M100 responses. Over this developmental window, the M100 responses to high contrast stimuli became faster with age and the optic radiation FA mediated this effect. These findings suggest that the maturation of the optic radiations over childhood accounts for individual variations observed in the developmental trajectory of visual cortex responses., This study elucidates the relationship between structural and functional properties of the visual pathways and how they change during childhood. Developmental changes of visual white matter pathways account for latency variations in electrophysiological responses of visual cortex. The present findings are an example of how relating white matter properties to functional aspects of the brain can help us reach a more complete understanding of the link between development of brain connectivity and changes in electrophysiology.

Diffusion-weighted magnetic resonance imaging (dMRI) is the primary method for noninvasively studying the organization of white matter in the human brain. Here we introduce QSIPrep, an integrative software platform for the processing of diffusion images that is compatible with nearly all dMRI sampling schemes. Drawing on a diverse set of software suites to capitalize on their complementary strengths, QSIPrep facilitates the implementation of best practices for processing of diffusion images. QSIPrep is a software platform for processing of most diffusion MRI datasets and ensures that adequate workflows are used.

Brain development and aging are complex processes that unfold in multiple brain regions simultaneously. Recently, models of brain age prediction have aroused great interest, as these models can potentially help to understand neurological diseases and elucidate basic neurobiological mechanisms. We test whether quantitative magnetic resonance imaging can contribute to such age prediction models. Using R1, the longitudinal rate of relaxation, we explore lifespan dynamics in cortical gray matter. We compare R1 with cortical thickness, a well-established biomarker of brain development and aging. Using 160 healthy individuals (6–81 years old), we found that R1 and cortical thickness predicted age similarly, but the regions contributing to the prediction differed. Next, we characterized R1 development and aging dynamics. Compared with anterior regions, in posterior regions we found an earlier R1 peak but a steeper postpeak decline. We replicate these findings: firstly, we tested a subset (N = 10) of the original dataset for whom we had additional scans at a lower resolution; and second, we verified the results on an independent dataset (N = 34). Finally, we compared the age prediction models on a subset of 10 patients with multiple sclerosis. The patients are predicted older than their chronological age using R1 but not with cortical thickness.

Research shows that, on average, children with dyslexia behave less categorically in phoneme categorization tasks. This study investigates three subtle ways that struggling readers may perform differently than their typically developing peers in this experimental context: sensitivity to the frequency distribution from which speech tokens are drawn, bias induced by previous stimulus presentations, and fatigue during the course of the task. We replicate findings that reading skill is related to categorical labeling, but we do not find evidence that sensitivity to the stimulus frequency distribution, the influence of previous stimulus presentations, and a measure of task engagement differs in children with dyslexia. It is, therefore, unlikely that the reliable relationship between reading skill and categorical labeling is attributable to artifacts of the task design, abnormal neural encoding, or executive function. Rather, categorical labeling may index a general feature of linguistic development whose causal relationship to literacy remains to be ascertained.

Education sculpts specialized neural circuits for skills like reading that are critical to success in modern society but were not anticipated by the selective pressures of evolution. Does the emergence of brain regions that selectively process novel visual stimuli like words occur at the expense of cortical representations of other stimuli like faces and objects? To answer this question we conducted a randomized controlled trial with pre-school children (five years of age). We found that being taught reading versus oral language skills induced different patterns of change in category-selective regions of visual cortex. Reading instruction enhanced the response to text but did not diminish the response to other categories. How these changes play out over a longer timescale is still unknown but, based on these data, we can surmise that high-level visual cortex undergoes rapid changes as children enter school and begin establishing new skills like literacy.

Diffusion MRI is a powerful tool for imaging brain structure, but it is challenging to discern the biological underpinnings of plasticity inferred from these and other non-invasive MR measurements. Biophysical modeling of the diffusion signal aims to render a more biologically rich image of tissue microstructure, but the application of these models comes with important caveats. A separate approach for gaining biological specificity has been to seek converging evidence from multi-modal datasets. Here we use metrics derived from diffusion kurtosis imaging (DKI) and the white matter tract integrity (WMTI) model along with quantitative MRI measurements of T1 relaxation to characterize changes throughout the white matter during an 8-week, intensive reading intervention (160 total hours of instruction). Behavioral measures, multi-shell diffusion MRI data, and quantitative T1 data were collected at regular intervals during the intervention in a group of 33 children with reading difficulties (7-12 years old), and over the same period in an age-matched non-intervention control group. Throughout the white matter, mean ‘extra-axonal’ diffusivity was inversely related to intervention time. In contrast, model estimated axonal water fraction (AWF), overall diffusion kurtosis, and T1 relaxation time showed no significant change over the intervention period. Both diffusion and quantitative T1 based metrics were correlated with pre-intervention reading performance, albeit with distinct anatomical distributions. These results are consistent with the view that rapid changes in diffusion properties reflect phenomena other than widespread changes in myelin density. We discuss this result in light of recent work highlighting non-axonal factors in experience-dependent plasticity and learning.HighlightsDiffusion MRI measurements in white matter show changes linked to an educational intervention.Tissue modeling results point to changes within the extra-axonal space.Complementary MRI measurements fail to suggest a widespread change in white matter in myelination over the intervention period.Both diffusion and quantitative T1 measures correlate with pre-intervention reading skill.

Published Nov 17, 2021 The validity of research results depends on the reliability of analysis methods. In recent years, there have been concerns about the validity of research that uses diffusion-weighted MRI (dMRI) to understand human brain white matter connections in vivo, in part based on the reliability of analysis methods used in this field. We defined and assessed three dimensions of reliability in dMRI-based tractometry, an analysis technique that assesses the physical properties of white matter pathways: (1) reproducibility, (2) test-retest reliability, and (3) robustness. To facilitate reproducibility, we provide software that automates tractometry (https://yeatmanlab.github.io/pyAFQ). In measurements from the Human Connectome Project, as well as clinical-grade measurements, we find that tractometry has high test-retest reliability that is comparable to most standardized clinical assessment tools. We find that tractometry is also robust: showing high reliability with different choices of analysis algorithms. Taken together, our results suggest that tractometry is a reliable approach to analysis of white matter connections. The overall approach taken here both demonstrates the specific trustworthiness of tractometry analysis and outlines what researchers can do to establish the reliability of computational analysis pipelines in neuroimaging. This work was supported through grant 1RF1MH121868- 01 from the National Institute of Mental Health/the BRAIN Initiative, through grant 5R01EB027585-02 to Eleftherios Garyfallidis (Indiana University) from the National Institute of Biomedical Imaging and Bioengineering, through Azure Cloud Computing Credits for Research & Teaching provided through the University of Washington’s Research Computing unit and the University of Washington eScience Institute, and NICHD R21HD092771 to Jason D. Yeatman

Literacy is an essential skill. Learning to read is a requirement for becoming a self-providing human being. However, while spoken language is acquired naturally with exposure to language without explicit instruction, reading and writing need to be taught explicitly. Decades of research have shown that well-structured teaching of phonological awareness, letter knowledge, and letter-to-sound mapping is crucial in building solid foundations for the acquisition of reading. During the COVID-19 pandemic, children worldwide did not have access to consistent and structured teaching and are, as a consequence, predicted to be behind in the development of their reading skills. Subsequent evidence confirms this prediction. With the best evidence-based practice in mind, we developed an online version of a well-structured early literacy training program (Reading Camp) for 5-year-old children. This 2-week online Reading Camp program is designed for pre-K children. It incorporates critical components of the fundamental skills essential to learning to read and is taught online in an interactive, multi-sensory, and peer-learning environment. We measure the participants’ literacy skills and other related skills before and after participating in the online Reading Camp and compare the results to no-treatment controls. Results show that children who participated in the online Reading Camp improved significantly on all parameters in relation to controls. Our results demonstrate that a well-structured evidence-based reading instruction program, even if online and short-term, benefits 5-year-old children in learning to read. With the potential to scale up this online program, the evidence presented here, alongside previous evidence for the efficacy of the in-person program, indicates that the online Reading Camp program is effective and can be used to tackle a variety of questions regarding structural and functional plasticity in the early stages of reading acquisition.

Education has faced unprecedented disruption during the COVID pandemic. Understanding how students have adapted as we have entered a different phase of the pandemic and some communities have returned to more typical schooling will inform a suite of policy interventions and subsequent research. We use data from an oral reading fluency (ORF) assessment—a rapid assessment taking only a few minutes that measures a fundamental reading skill—to examine COVID’s effects on children’s reading ability during the pandemic. We find that students in the first 200 days of the 2020–2021 school year tended to experience slower growth in ORF relative to prepandemic years. We also observe slower growth in districts with a high percentage of English language learners and/or students eligible for free and reduced-price lunch. These findings offer valuable insight into the effects of COVID on one of the most fundamental skills taught to children.

While online experiments have shown tremendous potential to study larger and more diverse participant samples than is possible in the lab, the uncontrolled online environment has prohibited many types of psychophysical studies due to difficulties controlling the viewing distance and stimulus size. We introduce the Virtual Chinrest, a method that measures a participant’s viewing distance in the web browser by detecting a participant’s blind spot location. This makes it possible to automatically adjust stimulus configurations based on an individual’s viewing distance. We validated the Virtual Chinrest in two laboratory studies in which we varied the viewing distance and display size, showing that our method estimates participants’ viewing distance with an average error of 3.25 cm. We additionally show that by using the Virtual Chinrest we can reliably replicate measures of visual crowding, which depends on a precise calculation of visual angle, in an uncontrolled online environment. An online experiment with 1153 participants further replicated the findings of prior laboratory work, demonstrating how visual crowding increases with eccentricity and extending this finding by showing that young children, older adults and people with dyslexia all exhibit increased visual crowding, compared to adults without dyslexia. Our method provides a promising pathway to web-based psychophysical research requiring controlled stimulus geometry.

It is established that individuals with dyslexia are less consistent at auditory phoneme categorization than typical readers. One hypothesis attributes these differences in phoneme labeling to differences in auditory cue integration over time, suggesting that the performance of individuals with dyslexia would improve with longer exposure to informative phonetic cues. Here, the relationship between phoneme labeling and reading ability was investigated while manipulating the duration of steady-state auditory information available in a consonant-vowel syllable. Children with dyslexia obtained no more benefit from longer cues than did children with typical reading skills, suggesting that poor task performance is not explained by deficits in temporal integration or temporal sampling.

Over the past two decades, researchers have tried to uncover how the human brain can extract linguistic information from a sequence of visual symbols. The description of how the brain’s visual system processes words and enables reading has improved with the progressive refinement of experimental methodologies and neuroimaging techniques. This review provides a brief overview of this research journey. We start by describing classical models of object recognition in non-human primates, which represent the foundation for many of the early models of visual word recognition in humans. We then review functional neuroimaging studies investigating the word-selective regions in visual cortex. This research led to the differentiation of highly specialized areas, which are involved in the analysis of different aspects of written language. We then consider the corresponding anatomical measurements and provide a description of the main white matter pathways carrying neural signals crucial to word recognition. Finally, in an attempt to integrate structural, functional, and electrophysiological findings, we propose a view of visual word recognition, accounting for spatial and temporal facets of word-selective neural processes. This multi-modal perspective on the neural circuitry of literacy highlights the relevance of a posterior-anterior differentiation in ventral occipitotemporal cortex for visual processing of written language and lexical features. It also highlights unanswered questions that can guide us towards future research directions. Bridging measures of brain structure and function will help us reach a more precise understanding of the transformation from vision to language.

Development of myelin, a fatty sheath that insulates nerve fibers, is critical for brain function. Myelination during infancy has been studied with histology, but postmortem data cannot evaluate the longitudinal trajectory of white matter development. Here, we obtained longitudinal diffusion MRI and quantitative MRI measures of R1 in 0, 3 and 6 months-old human infants, and (ii) developed an automated method to identify white matter bundles and quantify their properties in each infant’s brain. We find that R1 increases from newborns to 6-months-olds in all bundles. R1 development is nonuniform: there is faster development in white matter that is less mature in newborns, and along inferior-to-superior as well as anterior-to-posterior spatial gradients. As R1 is linearly related to myelin fraction in white matter bundles, these findings open new avenues to elucidate typical and atypical white matter myelination in early infancy, which has important implications for early identification of neurodevelopmental disorders.

Development of myelin, a fatty sheath that insulates nerve fibers, is critical for brain function. Myelination during infancy has been studied with histology, but postmortem data cannot evaluate the longitudinal trajectory of white matter development. Here, we obtained longitudinal diffusion MRI and quantitative MRI measures of longitudinal relaxation rate (R1) of white matter in 0, 3 and 6 months-old human infants, and developed an automated method to identify white matter bundles and quantify their properties in each infant’s brain. We find that R1 increases from newborns to 6-months-olds in all bundles. R1 development is nonuniform: there is faster development in white matter that is less mature in newborns, and development rate increases along inferior-to-superior as well as anterior-to-posterior spatial gradients. As R1 is linearly related to myelin fraction in white matter bundles, these findings open new avenues to elucidate typical and atypical white matter myelination in early infancy.

Available online 27 January 2021 Skilled reading requires years of practice associating visual symbols with speech sounds. Over the course of the learning process, this association becomes effortless and automatic. Here we test whether automatic activation of spoken-language circuits in response to visual words is a hallmark of skilled reading. Magnetoencephalography was used to measure word-selective responses under multiple cognitive tasks (N = 42, 7–12 years of age). Even when attention was drawn away from the words by performing an attention-demanding fixation task, strong word-selective responses were found in a language region (i.e., superior temporal gyrus) starting at ~300 ms after stimulus onset. Critically, this automatic word-selective response was indicative of reading skill: the magnitude of word-selective responses correlated with individual reading skill. Our results suggest that automatic recruitment of spoken-language circuits is a hallmark of skilled reading; with practice, reading becomes effortless as the brain learns to automatically translate letters into sounds and meaning. This work was supported under the framework of international cooperation program managed by the National Research Foundation of Korea (NRF) (No. 2018K2A9A2A20088926 and 2019R1C1C1009383) to SJJ. This work was also funded by NSF BCS 1551330, NICHD R21HD092771 and R01HD09586101 and Jacobs Foundation Research Fellowship to JDY. SC was funded by the European Commission (H2020-MSCA-IF-2018-837228-ENGRAVING). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 837228

Research on educational technologies for reading instruction is disproportionate to the myriad applications in the marketplace. Here we assess a web-based reading tool, Sound it Out, that assists struggling readers in decoding by annotating vowels with small icons indicating the associate phoneme. Created as a collaboration between researchers and technology developers, the phonemic-image cue was designed to scaffold letter-sound correspondence. Study 1 examined whether Sound it Out provides an immediate benefit to reading performance in thirty struggling readers (ages 8-10) randomly assigned to counterbalanced groups in a single-session. Results showed that, without a period of practice, children were not able to capitalize on the cues for improved text reading. Study 2 utilized a repeated measures randomized controlled trial design to determine if an extended practice period (1 month) produced gains and whether a caregiver supervised practice (“dyadic reading”) enhanced benefits. Seventy-six struggling readers (ages 7-13) were randomly assigned to two intervention groups (independent and dyadic reading) and one control group. Results showed significant, dose-response benefits to decoding accuracy and passage reading accuracy for the combined intervention groups in comparison to controls. Moreover, supervised dyadic reading enhanced the effect of practice. These results highlight the potential for an evidenced-based supplemental learning technology to support both independent and shared reading for struggling readers.

The speed-accuracy tradeoff suggests that responses generated under time constraints will be less accurate. While it has undergone extensive experimental verification, it is less clear whether it applies in settings where time pressures are not being experimentally manipulated (but where respondents still vary in their utilization of time). Using a large corpus of 29 response time datasets containing data from cognitive tasks without experimental manipulation of time pressure, we probe whether the speed-accuracy tradeoff holds across a variety of tasks using idiosyncratic within-person variation in speed. We find inconsistent relationships between marginal increases in time spent responding and accuracy; in many cases, marginal increases in time do not predict increases in accuracy. However, we do observe time pressures (in the form of time limits) to consistently reduce accuracy and for rapid responses to typically show the anticipated relationship (i.e., they are more accurate if they are slower). We also consider analysis of items and individuals. We find substantial variation in the item-level associations between speed and accuracy. On the person side, respondents who exhibit more within-person variation in response speed are typically of lower ability. Finally, we consider the predictive power of a person's response time in predicting out-of-sample responses; it is generally a weak predictor. Collectively, our findings suggest the speed-accuracy tradeoff may be limited as a conceptual model in its application in non-experimental settings and, more generally, offer empirical results and an analytic approach that will be useful as more response time data is collected.

Competing theories of dyslexia posit that reading difficulties arise from impaired visual, auditory, phonological, or statistical learning mechanisms. Importantly, many theories posit that dyslexia reflects a cascade of impairments emanating from a single “core deficit”. Here we report two studies evaluating core deficit and multifactorial models. In Study 1, we use publicly available data from the Healthy Brain Network to test the accuracy of phonological processing measures for predicting dyslexia diagnosis and find that over 30% of cases are misclassified (sensitivity = 66.7%; specificity = 68.2%). In Study 2, we collect a battery of psychophysical measures of visual motion processing and standardized measures of phonological processing in 106 school‐aged children to investigate whether dyslexia is best conceptualized under a core‐deficit model, or as a disorder with heterogenous origins. Specifically, by capitalizing on the drift diffusion model to analyze performance on a visual motion discrimination experiment, we show that deficits in visual motion processing, perceptual decision‐making, and phonological processing manifest largely independently. Based on statistical models of how variance in reading skill is parceled across measures of visual processing, phonological processing, and decision‐making, our results challenge the notion that a unifying deficit characterizes dyslexia. Instead, these findings indicate a model where reading skill is explained by several distinct, additive predictors, or risk factors, of reading (dis)ability., Using predictors from a visual motion processing experiment and linguistic measures, we show that a single‐mechanism model of reading disability cannot account for the range of linguistic and sensory processing outcomes observed in children. We propose an additive risk factor model where different aspects of sensory, cognitive and language function each contribute independently to reading development.

Diffusion-weighted magnetic resonance imaging (dMRI) has become the primary method for non-invasively studying the organization of white matter in the human brain. While many dMRI acquisition sequences have been developed, they all sample q-space in order to characterize water diffusion. Numerous software platforms have been developed for processing dMRI data, but most work on only a subset of sampling schemes or implement only parts of the processing workflow. Reproducible research and comparisons across dMRI methods are hindered by incompatible software, diverse file formats, and inconsistent naming conventions. Here we introduce QSIPrep, an integrative software platform for the processing of diffusion images that is compatible with nearly all dMRI sampling schemes. Drawing upon a diverse set of software suites to capitalize upon their complementary strengths, QSIPrep automatically applies best practices for dMRI preprocessing, including denoising, distortion correction, head motion correction, coregistration, and spatial normalization. Throughout, QSIPrep provides both visual and quantitative measures of data quality as well as “glass-box” methods reporting. Taken together, these features facilitate easy implementation of best practices for processing of diffusion images while simultaneously ensuring reproducibility.

Published18 March 2021 An accurate model of the factors that contribute to individual differences in reading ability depends on data collection in large, diverse and representative samples of research participants. However, that is rarely feasible due to the constraints imposed by standardized measures of reading ability which require test administration by trained clinicians or researchers. Here we explore whether a simple, two-alternative forced choice, time limited lexical decision task (LDT), self-delivered through the webbrowser, can serve as an accurate and reliable measure of reading ability. We found that performance on the LDT is highly correlated with scores on standardized measures of reading ability such as the Woodcock-Johnson Letter Word Identification test (r = 0.91, disattenuated r = 0.94). Importantly, the LDT reading ability measure is highly reliable (r = 0.97). After optimizing the list of words and pseudowords based on item response theory, we found that a short experiment with 76 trials (2–3 min) provides a reliable (r = 0.95) measure of reading ability. Thus, the self-administered, Rapid Online Assessment of Reading ability (ROAR) developed here overcomes the constraints of resourceintensive, in-person reading assessment, and provides an efficient and automated tool for effective online research into the mechanisms of reading (dis)ability. We would like to thank the Pavlovia and PsychoPy team for their support on the browser-based experiments. This work was funded by NIH NICHD R01HD09586101, research grants from Microsoft and Jacobs Foundation Research Fellowship to J.D.Y.

An accurate model of the factors that contribute to individual differences in reading ability depends on data collection in large, diverse and representative samples of research participants. However, that is rarely feasible due to the constraints imposed by standardized measures of reading ability which require test administration by trained clinicians or researchers. Here we explore whether a simple, two-alternative forced choice, time limited lexical decision task (LDT), self-delivered through the web-browser, can serve as an accurate and reliable measure of reading ability. We found that performance on the LDT is highly correlated with scores on standardized measures of reading ability such as the Woodcock-Johnson Letter Word Identification test administered in the lab (r = 0.91, disattenuated r = 0.94). Importantly, the LDT reading ability measure is highly reliable (r = 0.97). After optimizing the list of words and pseudowords based on item response theory, we found that a short experiment with 80 words (2-3 minutes) provides a reliable (r = 0.95) measure of reading ability. Thus, the self-administered, rapid online assessment of reading ability (ROAR) developed here overcomes the constraints of resource-intensive, in-person reading assessment, and provides an efficient and automated tool for effective online research into the mechanisms of reading (dis)ability.