Goal-directedness enhances letter-speech sound learning and consolidation in an unknown orthography

Toward a Mechanistic Understanding of Reading Difficulties: Deviant Audiovisual Learning Dynamics and Network Connectivity in Children with Poor Reading Skills

Mastering the associations between letters and their corresponding speech sounds (LSS) is pivotal in the early stages of reading development, requiring an effective reorganization of brain networks. Children with poor reading skills often show difficulties in LSS learning. To date, however, it remains unclear how the interaction of brain regions integral to the processing and integration of letters and speech sounds changes with LSS learning. Characterizing these changes and potential differences between children with typical (TR) or poor (PR) reading skills on both behavioral and neural levels is essential for a more comprehensive mechanistic understanding of reading impairments. In this study, we investigated brain network alterations underlying LSS learning and their association with reading skills using functional magnetic resonance imaging in 80 schoolchildren (6.9-10.8 years, 36 females, 27 PR) with a wide range of reading skills. We applied a reinforcement learning drift-diffusion model to LSS learning data and analyzed the corresponding effective connectivity and activation measures in the brain. While both groups learned well, PR showed slower adaptation of responses than TR as trials progressed. This could be explained by a slower adjustment of the drift rate and decision boundary while learning and longer nondecision times. Alongside deviant connectivity in the network of visual, auditory, and associative brain regions, PR also showed reduced striatal modulation of connectivity from visual to audiovisual association areas throughout learning. These findings indicate impaired information transfer to integrative areas, which aids to explain the difficulties in achieving proficient reading skills from a neuroscientific perspective.

Unraveling individual differences in learning potential: A dynamic framework for the case of reading development

Children show an enormous capacity to learn during development, but with large individual differences in the time course and trajectory of learning and the achieved skill level. Recent progress in developmental sciences has shown the contribution of a multitude of factors including genetic variation, brain plasticity, socio-cultural context and learning experiences to individual development. These factors interact in a complex manner, producing children's idiosyncratic and heterogeneous learning paths. Despite an increasing recognition of these intricate dynamics, current research on the development of culturally acquired skills such as reading still has a typical focus on snapshots of children's performance at discrete points in time. Here we argue that this 'static' approach is often insufficient and limits advancements in the prediction and mechanistic understanding of individual differences in learning capacity. We present a dynamic framework which highlights the importance of capturing short-term trajectories during learning across multiple stages and processes as a proxy for long-term development on the example of reading. This framework will help explain relevant variability in children's learning paths and outcomes and fosters new perspectives and approaches to study how children develop and learn.

Dyslexia, the Amsterdam Way

The current aim is to illustrate our research on dyslexia conducted at the Developmental Psychology section of the Department of Psychology, University of Amsterdam, in collaboration with the nationwide IWAL institute for learning disabilities (now RID). The collaborative efforts are institutionalized in the Rudolf Berlin Center. The first series of studies aimed at furthering the understanding of dyslexia using a gamified tool based on an artificial script. Behavioral measures were augmented with diffusion modeling in one study, and indices derived from the electroencephalogram were used in others. Next, we illustrated a series of studies aiming to assess individuals who struggle with reading and spelling using similar research strategies. In one study, we used methodology derived from the machine learning literature. The third series of studies involved intervention targeting the phonics of language. These studies included a network analysis that is now rapidly gaining prominence in the psychopathology literature. Collectively, the studies demonstrate the importance of letter-speech sound mapping and word decoding in the acquisition of reading. It was demonstrated that focusing on these abilities may inform the prediction, classification, and intervention of reading difficulties and their neural underpinnings. A final section examined dyslexia, conceived as a neurobiological disorder. This analysis converged on the conclusion that recent developments in the psychopathology literature inspired by the focus on research domain criteria and network analysis might further the field by staying away from longstanding debates in the dyslexia literature (single vs. a multiple deficit, category vs. dimension, disorder vs. lack of skill).