The bestersell effect: Nuances in positional encoding of morphemes in visual word recognition.

In the present study, the role of phonological information in visual word recognition is investigated by adopting a large-scale data-driven approach that exploits a new consistency measure based on distributional semantics methods. A recent study by Marelli, Amenta, and Crepaldi (2015) showed that the consistency between an orthographic string and the meanings to which it is associated in a large corpus is a relevant predictor in lexical decision experiments. Exploiting irregular mappings between orthography and phonology in English, we were able to compute a phonology-to-semantics consistency measure that dissociates from its orthographic counterpart and tested both measures on lexical decision data taken from the British Lexicon Project (Keuleers et al., 2012). Results showed that both orthography and phonology are activated during visual word recognition. However, their contribution is crucially determined by the extent to which they are informative of the word semantics, and phonology plays a crucial role in accessing word meaning.

Semantic priming: On the role of awareness in visual word recognition in the absence of an expectancy

A number of studies have shown that syllables play an important role in visual word recognition in Spanish. We report three lexical decision experiments with a masked priming technique that examined whether syllabic effects are phonological or orthographic in nature. In all cases, primes were nonwords. In Experiment 1, latencies to CV words were faster when primes and targets shared the first syllable (ju.nas-JU.NIO) than when they shared the initial letters but not the first syllable (jun.tu-JU.NIO). In Experiment 2, this syllabic overlap could be phonological+orthographical (vi.rel-VI.RUS) or just phonological (bi.rel-VI.RUS). A syllable priming effect was found for CV words in both the phonological+orthographical and the phonological condition. In Experiment 3 we compared a “phonological-syllable” condition (bi.rel-VI.RUS) with two control conditions (fi.rel-VI.RUS and vir.ga-VI.RUS). We found faster latencies for the phonological-syllabic condition than for the control conditions. These results suggest that syllabic effects are phonological in nature.

Masked morphological priming in visual word recognition

Automatic activation of phonology in visual word recognition has been well documented. It has been attributed, at least in part, to the sequential development of speech and literacy which results in the tendency for children to match orthographical input to phonological representation at the early stages of literacy development (e.g., Bosman & De Groot, 1996; Davis, Castles, & Iakovidis, 1998; Goswami, 1993). In contrast to the development of speech prior to literacy in first language (L1) acquisition, second language (L2) learners typically learn to speak and read at the same time. This raises the question of whether phonology is also automatically activated in L2 reading. This issue was investigated in this study by exploring the pseudohomophone effect in L2 reading using a lexical decision task. The role of learners’ L1 was also examined by including both alphabetic and non-alphabetic learners of English as L2. A strong pseudohomophone effect was found in reaction time among native English speakers and alphabetic non-native speakers. Non-alphabetic learners, however, showed a pseudohomophone effect in error rate but not in reaction time. The findings were discussed in terms of how learning experiences and L1 background affect phonological activation in visual L2 word recognition.

Previous research has reported that lexical access in bilinguals is language non-selective. In the present study, we explored the extent to which cross-language orthographic neighborhood size (N-size) effects, an index of language non-selectivity, should be dissociated from markedness effects, a sub-lexical orthographic variable referring to the degree of language- shared (unmarked) versus specific (marked) orthography. Two proficiency groups of French/English bilinguals performed an English (L2) lexical decision task with three word and non-word conditions: (1) English words with large French N-size/unmarked orthography (price), (2) small French N-size/unmarked orthography (drive), and (3) small French N-size/marked orthography (write). Evidence was found for orthographic markedness effects, albeit with a different pattern for word and non-word processing: while marked words were facilitated (responded to faster and more accurately) compared to unmarked words, the opposite pattern emerged for non-words. The pattern of results was comparable in both proficiency groups. No evidence emerged for the influence of first language (L1) neighborhood on L2 word or non-word processing. Thus, the results emphasize the need to integrate orthographic markedness as a relevant psycholinguistic variable in bilingual models of visual word recognition such as BIA/+ and to take it into account when investigating cross- language effects and the issue of language non-selectivity during visual word recognition.

Orthography-semantics consistency (OSC) is a measure that quantifies the degree of semantic relatedness between a word and its orthographic relatives. OSC is computed as the frequency-weighted average semantic similarity between the meaning of a given word and the meanings of all the words containing that very same orthographic string, as captured by distributional semantic models. We present a resource including optimized estimates of OSC for 15,017 English words. In a series of analyses, we provide a progressive optimization of the OSC variable. We show that computing OSC from word-embeddings models (in place of traditional count models), limiting preprocessing of the corpus used for inducing semantic vectors (in particular, avoiding part-of-speech tagging and lemmatization), and relying on a wider pool of orthographic relatives provide better performance for the measure in a lexical-processing task. We further show that OSC is an important and significant predictor of reaction times in visual word recognition and word naming, one that correlates only weakly with other psycholinguistic variables (e.g., family size, word frequency), indicating that it captures a novel source of variance in lexical access. Finally, some theoretical and methodological implications are discussed of adopting OSC as one of the predictors of reaction times in studies of visual word recognition.

The neural/mental operations involved in the process of visual word recognition (VWR) are fundamental for the efficient comprehension of written/printed words during reading. The present study used CiteSpace, a visual analysis software, to identify the intellectual landscape where VWR has been reviewed in the past decade. Thus, synthesized co-citation networks were analyzed to explore and discuss the main questions raised in the VWR literature: the research fronts and the emerging trends of research on this topic. Our results showed that the main questions addressed in VWR studies during the last decade have been focused on four main aspects related to "what," "where," "when," and "how" of VWR; to be specific, the different types of representations assessed during VWR ("what"), the locations and the timing of the brain activity involved in VWR ("where" and "when"), and the interactivity among different representations during processing ("how"). Among the revised studies, letter position coding was found to be the main topic of interest, possibly reflecting the critical role of this process. Furthermore, the evidence found in these studies consistently supported that VWR implies access to phonological, semantic, and morphological representations, which interact and modulate the processing of written words, particularly during early stages. Altogether, our findings showed the evolution in VWR literature regarding the different cognitive and neural operations involved in this process, highlighting the growing interest over the last decade toward the top-down way that mental representations interact.

Aging, alzheimer's disease, and word recognition: A review of the recent literature

The present study investigated the representation and processing of segmental and tonal information in visual Chinese word recognition in native and non‐native Chinese readers. Two experiments using homophone judgement paradigm were conducted. When judging two Chinese characters (Experiment 1), both groups showed difficulties when the segmental but not tonal information was shared (i.e., S+T− condition), with stronger interference for non‐native readers. When judging a Pinyin and a Chinese character (Experiment 2), non‐native readers' S+T− disadvantage was significantly reduced. Finally, when their L1s share the Latin alphabets with Pinyin, the participants showed stronger segmental reliance compared with the native readers. These findings suggest that while both native and non‐native readers rely more on segmental information in Chinese visual word recognition, this reliance is stronger among non‐native readers. Furthermore, the alphabetic nature of the Pinyin orthography may help non‐native readers' phonological representation and processing in a nonalphabetic writing system.

The reading comprehension and visual word recognition in 50 deaf children and adolescents with at least 3 years of cochlear implant (CI) use were evaluated. Their skills were contrasted with reference data of 500 deaf children without CIs. The reading comprehension level in children with CIs was expected to surpass that in deaf children without implants, partly via improved visual word recognition. Reading comprehension scores of children with implants were significantly better than those of deaf children without implants, although the performance in implant users was substantially lagging behind that in hearing children. Visual word recognition was better in children with CIs than in children without implants, in secondary education only. No difference in visual word recognition was found between the children with CIs and the hearing children, whereas the deaf children without implants showed a slightly poorer performance. The difference in reading comprehension performance of the deaf children with and without CIs remained present when visual word recognition was controlled for. This indicates that other reading-related skills were also contributing to the improved reading comprehension skills of deaf children with CIs.

Transposed-letter and laterality effects in lexical decision

In the last decade, reading research has seen a paradigmatic shift. A new wave of computational models of orthographic processing that offer various forms of noisy position or context-sensitive coding have revolutionized the field of visual word recognition. The influx of such models stems mainly from consistent findings, coming mostly from European languages, regarding an apparent insensitivity of skilled readers to letter order. Underlying the current revolution is the theoretical assumption that the insensitivity of readers to letter order reflects the special way in which the human brain encodes the position of letters in printed words. The present article discusses the theoretical shortcomings and misconceptions of this approach to visual word recognition. A systematic review of data obtained from a variety of languages demonstrates that letter-order insensitivity is neither a general property of the cognitive system nor a property of the brain in encoding letters. Rather, it is a variant and idiosyncratic characteristic of some languages, mostly European, reflecting a strategy of optimizing encoding resources, given the specific structure of words. Since the main goal of reading research is to develop theories that describe the fundamental and invariant phenomena of reading across orthographies, an alternative approach to model visual word recognition is offered. The dimensions of a possible universal model of reading, which outlines the common cognitive operations involved in orthographic processing in all writing systems, are discussed.

Preface. How to Use this Book. Section A. Introduction. 1. The Study of Language. Introduction. Why Study Language and Why Is It So Difficult? What is Language? How Has Language Changed Over Time? What is Language For? The History and Methods of Psycholinguistics. Models in Psycholinguistics. Language and the Brain. Themes and Controversies. Summary. Some Questions to Think About. Further Reading. 2. Describing Language. Introduction. How to Describe Speech Sounds. Consonants. Vowels. Syllables. Linguistic Approaches to Syntax. Summary. Some Questions to Think About. Further Reading. Section B. The Biological and Developmental Bases of Language. 3. The Foundations of Language. Introduction. Where Did Language Come From? Do Animals Have Language? The Biological Basis of Language. Is There a Critical Period for Language Development? The Cognitive Basis of Language. The Social Basis of Language. What is the Relation Between Language and Thought? Summary. Some Questions to Think About. Further Reading. 4. Language Development. Introduction. What Drives Language Development. The Language Acquisition Device. Phonological Development. Syntactic Development. Summary. Some Questions to Think About. Further Reading. 5. Bilingualism and Second Language Acquisition. Introduction. Bilingualism. Second Language Acquisition. Evaluation of Work on Bilingualism and Second Language Acquisition. Summary. Some Questions to Think About. Further reading. Section C. Word Recognition. 6. Recognizing Visual Words. Introduction. Basic Methods and Findings. What Makes Word Recognition Easier (or Harder)? Attentional Processes in Visual Word Recognition. Do Different Tasks Give Consistent Results? Is There a Dedicated Visual Word Recognition System? Meaning-based Facilitation of Visual Word Recognition. Processing Morphologically Complex Words. Models of Visual Word Recognition. Coping with Lexical Ambiguity. Summary. Some Questions to Think About. Further Reading. 7. Reading. Introduction. The Writing System. A Preliminary Model of Reading. The Processes of Normal Reading. The Neuroscience of Adult Reading Disorders. Models of Word Naming. Connectionism Models of Dyslexia. Comparison of Models. Summary. Some Questions to Think About. Further Reading. 8. Learning to Read and Spell. Introduction. Normal Reading Development. Phonological Awareness. How Should Reading be Taught? Learning to Spell. Developmental Dyslexia. Summary. Some Questions to Think About. Further Reading. 9. Understanding Speech. Introduction. Recognizing Speech. Models of Speech Recognition. The Neuroscience of Spoken Word Recognition. Summary. Some Questions to Think About. F urther Reading. Section D. Meaning and Using Language. 10. Understanding the Structure of Sentences. Introduction. Dealing with Structural Ambiguity. Early work on Parsing. Processing Structural Ambiguity. Gaps, Traces, and Unbounded Dependencies. The Neuroscience of Parsing. Summary. Some Questions to Think About. Further Reading. 11. Word Meaning. Introduction. Classic Approaches to Semantics. Semantic Networks. Semantic Features. Family Resemblance Models. Combining Concepts. Figurative Language. The Neuroscience of Semantics. Summary. Some Questions to Think About. Further Reading. 12. Comprehension. Introduction. Memory for Text and Inferences. Inferences. References and Ambiguity. Models of Text Processing. Individual Differences in Comprehension Skills. The Neuroscience of Text and Discourse Processing. Summary. Some Questions to Think About. Further Reading. Section E. Production and Other Aspects of Language. 13. Language Production. Introduction. Slips of the Tongue. Syntactic Planning. Lexicalization. Phonological Encoding. The Analysis of Hesitations. The Neuroscience of Speech Production. Writing and Agraphia. Summary. Some Questions to Think About. Further Reading. 14. How Do We Use Language? Introduction. Making Inferences in Conversation. The Structure of Conversation. Collaboration in Dialog. Sound and Vision. Summary. Some Questions to Think About. Further Reading. 15. The Structure of the Language System. Introduction. What are the Modules of Language? How Many Lexicons are There? Language and Short-term Memory. Summary. Some Questions to Think About. Further Reading. 16. New Directions. Introduction. Themes in Psycholinguistics Revisited. Some Growth Areas? Conclusion. Appendix: Connectionism. Interactive Activation Models. Back-propagation. Further Reading. Glossary. Example of Sentence Analysis. References. Author Index. Subject Index.

Although interactivity is considered a fundamental principle of cognitive (and computational) models of reading, it has received far less attention in neural models of reading that instead focus on serial stages of feed-forward processing from visual input to orthographic processing to accessing the corresponding phonological and semantic information. In particular, the left ventral occipito-temporal (vOT) cortex is proposed to be the first stage where visual word recognition occurs prior to accessing nonvisual information such as semantics and phonology. We used functional magnetic resonance imaging (fMRI) to investigate whether there is evidence that activation in vOT is influenced top-down by the interaction of visual and nonvisual properties of the stimuli during visual word recognition tasks. Participants performed two different types of lexical decision tasks that focused on either visual or nonvisual properties of the word or word-like stimuli. The design allowed us to investigate how vOT activation during visual word recognition was influenced by a task change to the same stimuli and by a stimulus change during the same task. We found both stimulus- and task-driven modulation of vOT activation that can only be explained by top-down processing of nonvisual aspects of the task and stimuli. Our results are consistent with the hypothesis that vOT acts as an interface linking visual form with nonvisual processing in both bottom up and top down directions. Such interactive processing at the neural level is in agreement with cognitive and computational models of reading but challenges some of the assumptions made by current neuro-anatomical models of reading.