Structural gray matter features and behavioral preliterate skills predict future literacy - A machine learning approach.

When children learn to read, their neural system undergoes major changes to become responsive to print. There seem to be nuanced interindividual differences in the neurostructural anatomy of regions that later become integral parts of the reading network. These differences might affect literacy acquisition and, in some cases, might result in developmental disorders like dyslexia. Consequently, the main objective of this longitudinal study was to investigate those interindividual differences in gray matter morphology that might facilitate or hamper future reading acquisition. We used a machine learning approach to examine to what extent gray matter macrostructural features and cognitive-linguistic skills measured before formal literacy teaching could predict literacy 2 years later. Forty-two native German-speaking children underwent T1-weighted magnetic resonance imaging and psychometric testing at the end of kindergarten. They were tested again 2 years later to assess their literacy skills. A leave-one-out cross-validated machine-learning regression approach was applied to identify the best predictors of future literacy based on cognitive-linguistic preliterate behavioral skills and cortical measures in a priori selected areas of the future reading network. With surprisingly high accuracy, future literacy was predicted, predominantly based on gray matter volume in the left occipito-temporal cortex and local gyrification in the left insular, inferior frontal, and supramarginal gyri. Furthermore, phonological awareness significantly predicted future literacy. In sum, the results indicate that the brain morphology of the large-scale reading network at a preliterate age can predict how well children learn to read.

Neural processing of vision and language in kindergarten is associated with prereading skills and predicts future literacy.

The main objective of this longitudinal study was to investigate the neural predictors of reading acquisition. For this purpose, we followed a sample of 54 children from the end of kindergarten to the end of second grade. Preliterate children were tested for visual symbol (checkerboards, houses, faces, written words) and auditory language processing (spoken words) using a passive functional magnetic resonance imaging paradigm. To examine brain-behavior relationships, we also tested cognitive-linguistic prereading skills at kindergarten age and reading performance of 48 of the same children 2 years later. Face-selective response in the bilateral fusiform gyrus was positively associated with rapid automatized naming (RAN). Response to both spoken and written words at preliterate age was negatively associated with RAN in the dorsal temporo-parietal language system. Longitudinally, neural response to faces in the ventral stream predicted future reading fluency. Here, stronger neural activity in inferior and middle temporal gyri at kindergarten age was associated with higher reading performance. Our results suggest that interindividual differences in the neural system of language and reading affect literacy acquisition and thus might serve as a marker for successful reading acquisition in preliterate children.

Neural correlates of affective contributions to lexical decisions in children and adults.

The goal of the present study was to investigate whether 6-9-year old children and adults show similar neural responses to affective words. An event-related neuroimaging paradigm was used in which both age cohorts performed the same auditory lexical decision task (LDT). The results show similarities in (auditory) lexico-semantic network activation as well as in areas associated with affective information. In both age cohorts' activations were stronger for positive than for negative words, thus exhibiting a positivity superiority effect. Children showed less activation in areas associated with affective information in response to all three valence categories than adults. Our results are discussed in the light of computational models of word recognition, and previous findings of affective contributions to LDT in adults.

Neuroimaging of valence decisions in children and adults.

To date, the neural underpinnings of affective components in language processing in children remain largely unknown. To fill this gap, the present study examined behavioural and neural correlates of children and adults performing the same auditory valence decision task with an event-related fMRI paradigm. Based on previous findings in adults, activations in anterior and posterior cingulate cortex, orbitofrontal cortex and left inferior frontal gyrus were expected for both positive and negative valence categories. Recent behavioural findings on valence decisions showed similar ratings and reaction time patterns in children and adults. This finding was successfully replicated in the present study. On a neural level, our analysis of affective language processing showed activations in regions associated with both semantic (superior and middle temporal and frontal) and affective (anterior and posterior cingulate, orbitofrontal and inferior frontal, insula and amygdala) processing. Neural activations in children and adults were systematically different in explicit affective word processing. In particular, adults showed a more distributed semantic network activation while children recruited additional subcortical structures.

Reading Shakespeare Sonnets: Combining Quantitative Narrative Analysis and Predictive Modeling -an Eye Tracking Study.

As a part of a larger interdisciplinary project on Shakespeare sonnets' reception (1, 2), the present study analyzed the eye movement behavior of participants reading three of the 154 sonnets as a function of seven lexical features extracted via Quantitative Narrative Analysis (QNA). Using a machine learning-based predictive modeling approach five 'surface' features (word length, orthographic neighborhood density, word frequency, orthographic dissimilarity and sonority score) were detected as important predictors of total reading time and fixation probability in poetry reading. The fact that one phonological feature, i.e., sonority score, also played a role is in line with current theorizing on poetry reading. Our approach opens new ways for future eye movement research on reading poetic texts and other complex literary materials(3).

The Berlin Affective Word List for Children (kidBAWL): Exploring Processing of Affective Lexical Semantics in the Visual and Auditory Modalities.

While research on affective word processing in adults witnesses increasing interest, the present paper looks at another group of participants that have been neglected so far: pupils (age range: 6-12 years). Introducing a variant of the Berlin Affective Wordlist (BAWL) especially adapted for children of that age group, the "kidBAWL," we examined to what extent pupils process affective lexical semantics similarly to adults. In three experiments using rating and valence decision tasks in both the visual and auditory modality, it was established that children show the two ubiquitous phenomena observed in adults with emotional word material: the asymmetric U-shaped function relating valence to arousal ratings, and the inversely U-shaped function relating response times to valence decision latencies. The results for both modalities show large structural similarities between pupil and adult data (taken from previous studies) indicating that in the present age range, the affective lexicon and the dynamic interplay between language and emotion is already well-developed. Differential effects show that younger children tend to choose less extreme ratings than older children and that rating latencies decrease with age. Overall, our study should help to develop more realistic models of word recognition and reading that include affective processes and offer a methodology for exploring the roots of pleasant literary experiences and ludic reading.