Visual linguistic statistical learning is traceable through neural entrainment.

The human brain can detect statistical regularities in the environment across a wide variety of contexts. The importance of this process is well-established not just in language acquisition but across different modalities; in addition, several neural correlates of statistical learning have been identified. A current technique for tracking the emergence of regularity learning and localizing its neural background is frequency tagging (FT). FT can detect neural entrainment not only to the frequency of stimulus presentation but also to that of a hidden structure. Auditory learning paradigms with linguistic and nonlinguistic stimuli, along with a visual paradigm using nonlinguistic stimuli, have already been tested with FT. To complete the picture, we conducted an FT experiment using written syllables as stimuli and a hidden triplet structure. Both behavioral and neural entrainment data showed evidence of structure learning. In addition, we localized two electrode clusters related to the process, which spread across the frontal and parieto-occipital areas, similar to previous findings. Accordingly, we conclude that fast-paced visual linguistic regularities can be acquired and are traceable through neural entrainment. In comparison with the literature, our findings support the view that statistical learning involves a domain-general network.

Just a mark: Diacritic function does not play a role in the early stages of visual word recognition.

A very common feature in most writing systems is the presence of diacritics: distinguishing marks that are added for various linguistic reasons. Most models of reading, however, have not yet captured the nature of these marks. Recent priming experiments in several languages have attempted to resolve how diacritical letters are represented in the visual word recognition system. Since the function and appearance of diacritics can change from one language to the other, it is hard to interpret the accumulated evidence. With this in mind, we conducted two masked priming lexical decision experiments in Hungarian, a transparent orthography with a wide use of diacritic vowels that allows for clear-cut manipulations. In the two experiments, we manipulated the presence or absence of the same diacritic (i.e., the acute accent) on two specific sets of letters that behave differently. In Experiment 1, the manipulation changed only the length of vowels, whereas in Experiment 2, it also changed the quality (e.g., a↝/ɒ/ vs. á↝/aː/). In both experiments, we found that primes with an omitted diacritic work just as good as the identity primes (nema→NÉMA = néma→NÉMA [mute]), whereas the addition of a diacritic comes with a cost (mése→MESE > mese→MESE [tale]). This asymmetry favors a purely perceptual account of the very early stages of word recognition, making it blind to the function of diacritics. We suggest that the linguistic functions of diacritics originate at later processing stages.

Can rotated words be processed automatically? Evidence from rotated repetition priming.

Visual word processing has its own dedicated neural system that, due to the novelty of this activity, is unlikely to have acquired its specialization through natural selection. Understanding the properties of this system could shed light on its recruitment and the background of its disorders. Although recognition of simple visual objects is orientation invariant, this is not necessarily the case for written words. We used a masked repetition priming paradigm to find out whether words retain their readability when viewed in atypical orientations. Subjects had to read out upright target words that were preceded by rotated prime words of the same or different identity. Priming duration was varied in Experiment 1 to assess the temporal emergence of a rotated priming effect. In Experiment 2, the letter order of the prime words was reversed in order to differentiate the processing stage where priming occurs. The orientational pattern of the priming effects seen in our results mostly confirms earlier word recognition models, but also serves a more detailed view about the effects of orientation on word form processing.