Neural substrates of L2-L1 transfer effects on phonological awareness in young Chinese-English bilingual children.

The growing trend of bilingual education between Chinese and English has contributed to a rise in the number of early bilingual children, who were exposed to L2 prior to formal language instruction of L1. The L2-L1 transfer effect in an L1-dominant environment has been well established. However, the threshold of L2 proficiency at which such transfer manifests remains unclear. This study investigated the behavioral and neural processes involved when manipulating phonemes in an auditory phonological task to uncover the transfer effect in young bilingual children. Sixty-two first graders from elementary schools in Taiwan were recruited in this study (29 Chinese monolinguals, 33 Chinese-English bilinguals). The brain activity was measured using fNIRS (functional near-infrared spectroscopy). Bilingual children showed right lateralization to process Chinese and left lateralization to process English, which supports more on the accommodation effect within the framework of the assimilation-accommodation hypothesis. Also, compared to monolinguals, bilingual children showed more bilateral frontal activation in Chinese, potentially reflecting a mixed influence from L2-L1 transfer effects and increased cognitive load of bilingual exposure. These results elucidate the developmental adjustments in the neural substrates associated with early bilingual exposure in phonological processing, offering valuable insights into the bilingual learning process.

Multi-time-point analysis: A time course analysis with functional near-infrared spectroscopy.

In the data analysis of functional near-infrared spectroscopy (fNIRS), linear model frameworks, in particular mass univariate analysis, are often used when researchers consider examining the difference between conditions at each sampled time point. However, some statistical issues, such as assumptions of linearity, autocorrelation and multiple comparison problems, influence statistical inferences when mass univariate analysis is used on fNIRS time course data. In order to address these issues, the present study proposes a novel perspective, multi-time-point analysis (MTPA), to discriminate signal differences between conditions by combining temporal information from multiple time points in fNIRS. In addition, MTPA adopts the random forest algorithm from the statistical learning domain, followed by a series of cross-validation procedures, providing reasonable power for detecting significant time points and ensuring generalizability. Using a real fNIRS data set, the proposed MTPA outperformed mass univariate analysis in detecting more time points, showing significant differences between experimental conditions. Finally, MTPA was also able to make comparisons between different areas, leading to a novel viewpoint of fNIRS time course analysis and providing additional theoretical implications for future fNIRS studies. The data set and all source code are available for researchers to replicate the analyses and to adapt the program for their own needs in future fNIRS studies.

Developing a reading concentration monitoring system by applying an artificial bee colony algorithm to e-books in an intelligent classroom.

A growing number of educational studies apply sensors to improve student learning in real classroom settings. However, how can sensors be integrated into classrooms to help instructors find out students' reading concentration rates and thus better increase learning effectiveness? The aim of the current study was to develop a reading concentration monitoring system for use with e-books in an intelligent classroom and to help instructors find out the students' reading concentration rates. The proposed system uses three types of sensor technologies, namely a webcam, heartbeat sensor, and blood oxygen sensor to detect the learning behaviors of students by capturing various physiological signals. An artificial bee colony (ABC) optimization approach is applied to the data gathered from these sensors to help instructors understand their students' reading concentration rates in a classroom learning environment. The results show that the use of the ABC algorithm in the proposed system can effectively obtain near-optimal solutions. The system has a user-friendly graphical interface, making it easy for instructors to clearly understand the reading status of their students.

Examining the phonological neighborhood density effect using near infrared spectroscopy.

Phonological density refers to the number of words that can be generated by replacing a phoneme in a target word with another phoneme in the same position. Although the precise nature of the phonological neighborhood density effect is not firmly established, many behavioral psycholinguistic studies have shown that visual recognition of individual words is influenced by the number and type of neighbors the words have. This study explored neurobehavioral correlates of phonological neighborhood density in skilled readers of English using near infrared spectroscopy. On the basis of a lexical decision task, our findings showed that words with many phonological neighbors (e.g., FRUIT) were recognized more slowly than words with few phonological neighbors (e.g., PROOF), and that words with many neighbors elicited significantly greater changes in blood oxygenation in the left than in the right hemisphere of the brain, specifically in the areas BA 22/39/40. In previous studies these brain areas have been implicated in fine-grained phonological processing in readers of English. The present findings provide the first demonstration that areas BA 22/39/40 are also sensitive to phonological density effects.

Optical imaging of phonological processing in two distinct orthographies.

Recent fMRI studies comparing the processing of alphabetic versus logographic scripts provide evidence for shared and orthography-specific regions of neural activity. The present study used near-infrared spectroscopy to compare (within and across brain regions) the time course of neural activation for these two distinct orthographies. Native readers of English and of Chinese were tested on a homophone judgment task. Differences across groups were obtained in the time course of hemodynamic change for the left middle frontal, left superior temporal, and left supramarginal gyri. Results thus support previous findings using fMRI and suggest that different neural mappings arise depending on whether an individual has learned to process written language using an alphabetic or logographic script.

Proverb preferences across cultures: dialecticality or poeticality?

Peng and Nisbett (1999) claimed that members of Asian cultures show a greater preference than Euro-Americans for proverbs expressing paradox (so-called dialectical proverbs; e.g., Too humble is half proud). The present research sought to replicate this claim with the same set of stimuli used in Peng and Nisbett's Experiment 2 and a new set of dialectical and nondialectical proverbs that were screened to be comparably pleasing in phrasing. Whereas the proverbs were rated as more familiar and (in Set 1) more poetic by Chinese than by American participants, no group differences were found in relation to proverb dialecticality. Both the Chinese and Americans in our study rated the dialectical proverbs from Peng and Nisbett's study as more likable, higher in wisdom, and higher in poeticality than the nondialectical proverbs. For Set 2, both groups found the dialectical proverbs to be as likable, wise, and poetic as the nondialectical proverbs. When poeticality was covaried out, dialectical proverbs were liked better than nondialectical proverbs across both stimulus sets by the Chinese and the Americans alike, and when wisdom was covaried out, the effect of dialecticality was reduced in both sets and groups. Our findings indicate that caution should be taken in ascribing differences in proverb preferences solely to cultural differences in reasoning.