Statistical learning is a learning mechanism that does not directly depend on knowledge of
a language but predicts language and literacy outcomes for children and adults. Research …

Patterns of neural activity are systematically elicited as the brain experiences categorical
stimuli and a major challenge is to understand what these patterns represent. Two influential …

Time-resolved multivariate pattern analysis (MVPA), a popular technique for analyzing
magneto- and electro-encephalography (M/EEG) neuroimaging data, quantifies the extent and …

The MRI environment restricts the types of populations and tasks that can be studied by
cognitive neuroscientists (eg, young infants, face-to-face communication). FNIRS is a …

Access to literacy is critical to children's futures, but formal education may be insufficient for
fostering early literacy, especially in low-resource contexts. Educational technologies used at …

Studies of non‐linguistic statistical learning (SL) have often linked performance in SL tasks
with differences in language outcomes. Most of these studies have focused on Western and …

Objectives: Understanding speech in adverse listening environments is challenging for older
adults. Individual differences in pure tone averages and working memory are known to be …

Successful knowledge acquisition requires a cognitive system that is both sensitive to statistical
information and able to distinguish among multiple structures (ie, to detect pattern shifts …

Prior research has demonstrated the benefits (ie, task-relevant attentional selection) and
costs (ie, task-irrelevant attentional capture) of prior knowledge on search for an individual …

Two sets of items can share the same underlying conceptual structure, while appearing
unrelated at a surface level. Humans excel at recognizing and using alignments between such …