Sensitivity to meaningful regularities acquired through experience

AbstractEnglish spelling provides multiple cues to word meaning, and these cues are readily exploited by skilled readers. In two crowdsourcing studies, we tested skilled readers' sensitivity to a large number of morphological as well as nonmorphological orthographic cues by asking them to classify nonwords as adjectives or nouns. We observed a substantial variability across individuals and orthographic cues. In this paper, we discuss some sources of this variation. Specifically, we found consistent correlations between readers' sensitivity to cues and their performance on language tasks (reading, spelling, and author recognition tests) suggesting that reading experience is critical for assimilating spelling-to-meaning regularity from written language. Further, we identified characteristics that may be important for the learning and exploitation of orthographic cues that are related to the nature of their function and use in context

From specific examples to general knowledge in language learning

AbstractThe extraction of general knowledge from individual episodes is critical if we are to learn new knowledge or abilities. Here we uncover some of the key cognitive mechanisms that characterise this process in the domain of language learning. In five experiments adult participants learned new morphological units embedded in fictitious words created by attaching new affixes (e.g., -afe) to familiar word stems (e.g., “sleepafe is a participant in a study about the effects of sleep”). Participants’ ability to generalise semantic knowledge about the affixes was tested using tasks requiring the comprehension and production of novel words containing a trained affix (e.g., sailafe). We manipulated the delay between training and test (Experiment 1), the number of unique exemplars provided for each affix during training (Experiment 2), and the consistency of the form-to-meaning mapping of the affixes (Experiments 3–5). In a task where speeded online language processing is required (semantic priming), generalisation was achieved only after a memory consolidation opportunity following training, and only if the training included a sufficient number of unique exemplars. Semantic inconsistency disrupted speeded generalisation unless consolidation was allowed to operate on one of the two affix-meanings before introducing inconsistencies. In contrast, in tasks that required slow, deliberate reasoning, generalisation could be achieved largely irrespective of the above constraints. These findings point to two different mechanisms of generalisation that have different cognitive demands and rely on different types of memory representations

Mapping visual symbols onto spoken language along the ventral visual stream.

Reading involves transforming arbitrary visual symbols into sounds and meanings. This study interrogated the neural representations in ventral occipitotemporal cortex (vOT) that support this transformation process. Twenty-four adults learned to read 2 sets of 24 novel words that shared phonemes and semantic categories but were written in different artificial orthographies. Following 2 wk of training, participants read the trained words while neural activity was measured with functional MRI. Representational similarity analysis on item pairs from the same orthography revealed that right vOT and posterior regions of left vOT were sensitive to basic visual similarity. Left vOT encoded letter identity and representations became more invariant to position along a posterior-to-anterior hierarchy. Item pairs that shared sounds or meanings, but were written in different orthographies with no letters in common, evoked similar neural patterns in anterior left vOT. These results reveal a hierarchical, posterior-to-anterior gradient in vOT, in which representations of letters become increasingly invariant to position and are transformed to convey spoken language information

Shades of meaning: Uncovering the geometry of ambiguous word representations through contextualised language models

Lexical ambiguity presents a profound and enduring challenge to the language sciences. Researchers for decades have grappled with the problem of how language users learn, represent and process words with more than one meaning. Our work offers new insight into psychological understanding of lexical ambiguity through a series of simulations that capitalise on recent advances in contextual language models. These models have no grounded understanding of the meanings of words at all; they simply learn to predict words based on the surrounding context provided by other words. Yet, our analyses show that their representations capture fine-grained meaningful distinctions between unambiguous, homonymous, and polysemous words that align with lexicographic classifications and psychological theorising. These findings provide quantitative support for modern psychological conceptualisations of lexical ambiguity and raise new challenges for understanding of the way that contextual information shapes the meanings of words across different timescales

Moving beyond the monosyllable in models of skilled reading:Mega-study of disyllabic nonword reading

AbstractMost English words are polysyllabic, yet research on reading aloud typically focuses on monosyllables. Forty-one skilled adult readers read aloud 915 disyllabic nonwords that shared important characteristics with English words. Stress, pronunciation, and naming latencies were analyzed and compared to data from three computational accounts of disyllabic reading, including a rule-based algorithm (Rastle & Coltheart, 2000) and connectionist approaches (the CDP++ model of Perry, Ziegler, & Zorzi, 2010, and the print-to-stress network of Ševa, Monaghan, & Arciuli, 2009). Item-based regression analyses revealed orthographic and phonological influences on modal human stress assignment, pronunciation variability, and naming latencies, while human and model data comparisons revealed important strengths and weaknesses of the opposing accounts. Our dataset provides the first normative nonword corpus for British English and the largest database of its kind for any language; hence, it will be critical for assessing generalization performance in future developments of computational models of reading