The current study used functional MRI (fMRI) to obtain a comprehensive understanding of the neural network underlying visual word recognition in Hindi/Devanagari, an alphasyllabic - partly alphabetic and partly syllabic Indian writing system on which little research has hitherto been carried out.Sixteen (5F, 11M) neurologically healthy, native Hindi/Devanagari readers aged 21 to 50 named aloud 240 Devanagari words which were either visually linear - had no diacritics or consonant ligatures above or below central plane of text, e.g. फल, वाहन, or nonlinear - had at least one diacritic and/or ligature, e.g. फूल, किरण, and which further included 120 words each of high and low frequency. Words were presented in alternating high and low frequency blocks of 10 words each at 2s/word in a block design, with linear and nonlinear words in separate runs. Word reading accuracy was manually coded, while fMRI images were acquired on a 3T scanner with an 8-channel head-coil, using a T2*-weighted EPI sequence (TR/TE = 2s/35ms).After ensuring high word naming accuracy (M = 97.6%, SD = 2.3), fMRI data analyses (at FDR P < 0.005) revealed that reading Devanagari words elicited robust activations in bilateral occipito-temporal, inferior frontal and precentral regions as well as both cerebellar hemispheres. Other common areas of activation included left inferior parietal and right superior temporal cortices. Primary differences seen between nonlinear and linear word reading networks were in the right temporal areas and cerebellum.Distinct from alphabetic scripts, which are linear in their spatial organization, and recruit a primarily left-lateralized network for word reading, our results revealed a bilateral reading network for Devanagari. We attribute the additional activations in Devanagari to increased visual processing demands arising from the complex visuospatial arrangement of symbols in this ancient script.
Aims and objectives: Few previous studies of bilingual cognition have theorized the impact of being literate in distinct orthographies. This study examined: (1) How do differences in the way writing systems represent sound affect biscriptal bilinguals’ segmentation of spoken words in each language? and (2) What is the impact of the first learned orthography? These questions were addressed in native and non-native readers of Hindi and English. The primary unit of writing in Hindi is the akshara, which corresponds to a syllable in most cases, whereas for English the unit of writing corresponds to a phoneme. Method: Hindi-English users listened to cross-language homophones in Hindi and English. Participants were instructed to take away “the first sound” of each word and say aloud what remained. Data analysis: Percent deletion of the initial phoneme was examined. Exp. 1 included 44 bilinguals. Exp. 2 tested 13 bilinguals. Findings/conclusions: For native English readers the first phoneme was deleted regardless of language. For native readers of Hindi, performance differed by language: the “first sound” was a phoneme for English words but a syllable for Hindi words (except for vowel-initial words). Originality: Using a novel paradigm, this study demonstrates that biscriptal bilinguals’ conceptions of speech sounds are differentially shaped by their knowledge of the written forms of those sounds: deleting “the first sound” in /sʌfʌr/ resulted in /fʌr/ when it was presented as a Hindi word but as /ʌfʌr/ when presented as English. Thus, the very same spoken word can yield different conceptions depending on whether it is heard as a word belonging to one language or another. Significance/implications: The findings indicate that language-specific orthographic knowledge influences biscriptal bilinguals’ conceptualization of speech sounds in their respective languages. More generally, our study argues for more research on biscriptal bilinguals in the study of bilingual cognition.
Abstract We applaud Ram Frost for highlighting the need for multicultural perspectives while developing universal models of visual word recognition. We second Frost's proposal that factors like lexical morphology should be incorporated besides purely orthographic features in modeling word recognition. In support, we provide fresh evidence from Hindi (written in Devanagari), an example of hitherto under-represented alphasyllabic orthographies, in which flexible encoding of akṣara (character) position is constrained by the morphological structure of words.
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