Eye Movement Evidence for Simultaneous Cognitive Processing in Reading.

Measuring simultaneous processing, a reliable predictor of reading development and reading difficulties (RDs), has traditionally involved cognitive tasks that test reaction or response time, which only capture the efficiency at the output processing stage and neglect the internal stages of information processing. However, with eye-tracking methodology, we can reveal the underlying temporal and spatial processes involved in simultaneous processing and investigate whether these processes are equivalent across chronological or reading age groups. This study used eye-tracking to investigate the simultaneous processing abilities of 15 Grade 6 and 15 Grade 3 children with RDs and their chronological-age controls (15 in each Grade). The Grade 3 typical readers were used as reading-level (RL) controls for the Grade 6 RD group. Participants were required to listen to a question and then point to a picture among four competing illustrations demonstrating the spatial relationship raised in the question. Two eye movements (fixations and saccades) were recorded using the EyeLink 1000 Plus eye-tracking system. The results showed that the Grade 3 RD group produced more and longer fixations than their CA controls, indicating that the pattern of eye movements of young children with RD is typically deficient compared to that of their typically developing counterparts when processing verbal and spatial stimuli simultaneously. However, no differences were observed between the Grade 6 groups in eye movement measures. Notably, the Grade 6 RD group outperformed the RL-matched Grade 3 group, yielding significantly fewer and shorter fixations. The discussion centers on the role of the eye-tracking method as a reliable means of deciphering the simultaneous cognitive processing involved in learning.

Phonological ability and neural congruency: Phonological loop or more?

OBJECTIVE: We explored neural components in Electroencephalography (EEG) signals during a phonological processing task to assess (a) the neural origins of Baddeley's working-memory components contributing to phonological processing, (b) the unitary structure of phonological processing and (c) the neural differences between children with dyslexia (DYS) and controls (CAC). METHODS: EEG data were collected from sixty children (half with dyslexia) while performing the initial- and final- phoneme elision task. We explored a novel machine-learning-based approach to identify the neural components in EEG elicited in response to the two conditions and capture differences between DYS and CAC. RESULTS: Our method identifies two sets of phoneme-related neural congruency components capturing neural activations distinguishing DYS and CAC across conditions. CONCLUSIONS: Neural congruency components capture the underlying neural mechanisms that drive the relationship between phonological deficits and dyslexia and provide insights into the phonological loop and visual-sketchpad dimensions in Baddeley's model at the neural level. They also confirm the unitary structure of phonological awareness with EEG data. SIGNIFICANCE: Our findings provide novel insights into the neural origins of the phonological processing differences in children with dyslexia, the unitary structure of phonological awareness, and further verify Baddeley's model as a theoretical framework for phonological processing and dyslexia.

RAN-related neural-congruency: a machine learning approach toward the study of the neural underpinnings of naming speed.

Objective: Naming speed, behaviorally measured via the serial Rapid automatized naming (RAN) test, is one of the most examined underlying cognitive factors of reading development and reading difficulties (RD). However, the unconstrained-reading format of serial RAN has made it challenging for traditional EEG analysis methods to extract neural components for studying the neural underpinnings of naming speed. The present study aims to explore a novel approach to isolate neural components during the serial RAN task that are (a) informative of group differences between children with dyslexia (DYS) and chronological age controls (CAC), (b) improve the power of analysis, and (c) are suitable for deciphering the neural underpinnings of naming speed. Methods: We propose a novel machine-learning-based algorithm that extracts spatiotemporal neural components during serial RAN, termed RAN-related neural-congruency components. We demonstrate our approach on EEG and eye-tracking recordings from 60 children (30 DYS and 30 CAC), under phonologically or visually similar, and dissimilar control tasks. Results: Results reveal significant differences in the RAN-related neural-congruency components between DYS and CAC groups in all four conditions. Conclusion: Rapid automatized naming-related neural-congruency components capture the neural activity of cognitive processes associated with naming speed and are informative of group differences between children with dyslexia and typically developing children. Significance: We propose the resulting RAN-related neural-components as a methodological framework to facilitate studying the neural underpinnings of naming speed and their association with reading performance and related difficulties.

Expanding horizons of cross-linguistic research on reading: The Multilingual Eye-movement Corpus (MECO).

Scientific studies of language behavior need to grapple with a large diversity of languages in the world and, for reading, a further variability in writing systems. Yet, the ability to form meaningful theories of reading is contingent on the availability of cross-linguistic behavioral data. This paper offers new insights into aspects of reading behavior that are shared and those that vary systematically across languages through an investigation of eye-tracking data from 13 languages recorded during text reading. We begin with reporting a bibliometric analysis of eye-tracking studies showing that the current empirical base is insufficient for cross-linguistic comparisons. We respond to this empirical lacuna by presenting the Multilingual Eye-Movement Corpus (MECO), the product of an international multi-lab collaboration. We examine which behavioral indices differentiate between reading in written languages, and which measures are stable across languages. One of the findings is that readers of different languages vary considerably in their skipping rate (i.e., the likelihood of not fixating on a word even once) and that this variability is explained by cross-linguistic differences in word length distributions. In contrast, if readers do not skip a word, they tend to spend a similar average time viewing it. We outline the implications of these findings for theories of reading. We also describe prospective uses of the publicly available MECO data, and its further development plans.

Fixation-related potentials in naming speed: A combined EEG and eye-tracking study on children with dyslexia.

OBJECTIVE: We combined electroencephalography (EEG) and eye-tracking recordings to examine the underlying factors elicited during the serial Rapid-Automatized Naming (RAN) task that may differentiate between children with dyslexia (DYS) and chronological age controls (CAC). METHODS: Thirty children with DYS and 30 CAC (Mage = 9.79 years; age range 7.6 through 12.1 years) performed a set of serial RAN tasks. We extracted fixation-related potentials (FRPs) under phonologically similar (rime-confound) or visually similar (resembling lowercase letters) and dissimilar (non-confounding and discrete uppercase letters, respectively) control tasks. RESULTS: Results revealed significant differences in FRP amplitudes between DYS and CAC groups under the phonologically similar and phonologically non-confounding conditions. No differences were observed in the case of the visual conditions. Moreover, regression analysis showed that the average amplitude of the extracted components significantly predicted RAN performance. CONCLUSION: FRPs capture neural components during the serial RAN task informative of differences between DYS and CAC and establish a relationship between neurocognitive processes during serial RAN and dyslexia. SIGNIFICANCE: We suggest our approach as a methodological model for the concurrent analysis of neurophysiological and eye-gaze data to decipher the role of RAN in reading.

Is rapid automatized naming related to reading and mathematics for the same reason(s)? A follow-up study from kindergarten to Grade 1.

We examined (a) what rapid automatized naming (RAN) components (articulation time and/or pause time) predict reading and mathematics ability and (b) what processing skills involved in RAN (speed of processing, response inhibition, working memory, and/or phonological awareness) may explain its relationship with reading and mathematics. A sample of 72 children were followed from the beginning of kindergarten until the end of Grade 1 and were assessed on measures of RAN, general cognitive ability, speed of processing, attention, working memory, phonological awareness, reading, and mathematics. The results indicated that pause time was the critical component in both the RAN-reading and RAN-mathematics relationships and that it shared most of its predictive variance in reading and mathematics with speed of processing and working memory. Our findings further suggested that, unlike the relationship between RAN and reading fluency in Grade 1, there is nothing in the RAN task that is uniquely related to math.

Rapid naming speed components and reading development in a consistent orthography.

We examined how rapid automatized naming (RAN) components-articulation time and pause time-predict word and text reading fluency in a consistent orthography (Greek). In total, 68 children were followed from Grade 2 to Grade 6 and were assessed three times on RAN (Digits and Objects), phonological awareness, orthographic processing, speed of processing, and reading fluency. Both RAN components were strongly related to reading fluency and, with few exceptions, accounted for unique variance over and above the contribution of speed of processing, phonological awareness, and orthographic processing. The amount of predictive variance shared between the components and the cognitive processing skills varied across time. The implications of these findings for the RAN-reading relationship are discussed.