A highly ecological ability such as reading is often investigated through non-ecological experimental paradigms. The present work aims at complementing this approach by providing the community with a developmental database of eye movement measures during natural reading. Eye movements were recorded from a large sample of Italian developing readers (N=140), aged 8–11, as they read 12 multi-lined passages taken from story books for children (1566 tokens and 762 distinct types). Eye-tracking data were also recorded from a group of skilled adult readers (N=33), for comparison.

Constituent morphemes within complex words are identified during visual word processing, and likewise the presence of real morphemes slows down pseudoword rejection. Previous studies suggest that the identification of constituents in compound words is, to a certain degree, position-independent, reflecting the fact that constituents can occur in any position within compounds across the language (e.g., boathouse - houseboat). However, some stems occur more often in the first position of a compound (e.g., doorstep, doorstop, doorknob, doorbell vs.

Here we investigate the neural representation of morphemes, both stems and suffixes, in a Fast Periodic Visual Stimulation (FPVS) paradigm combined with MEG. We find that the brain automatically detects morphological structure in stimuli that are entirely made up of morphemes, but not in nonwords that contain only a stem, or only a suffix. Further exploration of the neural sources behind these sensor-level data will provide more refined spatial information on the brain mechanisms underlying morpheme identification.

We learn new words via our everyday reading experience, but the precise mechanisms behind this learning are still unclear. In this experiment we tracked the development of lexical representations in adults combining behavioural measures of lexical processing with EEG signatures of visual word sensitivity. Participants learned novel letter strings using two different routines, one based on the standard explicit procedure typically used in the literature, and one based on a more pro-active feedback-based learning.