Neurocognitive Correlates of Statistical Learning of Orthographic-Semantic Connections in Chinese Adult Learners

Electrophysiological markers of orthographic pattern learning in school-aged children with reading challenges: An ERP investigation

BACKGROUND

Previous studies suggested that children with reading difficulty have impaired statistical learning ability in extracting distributional orthographic regularities. However, the neural mechanisms underlying have not been fully investigated.

AIMS

The current study aimed to identify the electrophysiological markers and to examine the neural underpinnings of statistical learning of orthographic regularities in children with reading difficulties.

METHODS AND PROCEDURES

Using the event-related potentials (ERPs) and the orthographic learning task, 157 children were exposed to a sequence of artificial pseudocharacters with varying levels of positional and semantic consistency (low at 60 %, moderate at 80 %, and high at 100 %).

OUTCOMES AND RESULTS

Poor readers elicited an increased N170 response in the low consistency and a lack of left-lateralized P300 effect when learning positional regularities of radicals. Similarly, larger N170 effects were observed in poor readers, while similar N400 effects were found in both poor and average readers when learning semantic regularities of radicals.

CONCLUSIONS AND IMPLICATIONS

Our findings indicate that poor readers may have trouble using statistical information for early-stage orthographic pattern extraction, yet they can identify semantic inconsistencies after sufficient exposure. These results deepen our understanding of the neural mechanisms involved in statistical learning for poor readers and aid in improving criteria for differentiating between typically developing children and those with reading challenges.

Seeking the neural representation of statistical properties in print during implicit processing of visual words

Statistical learning (SL) plays a key role in literacy acquisition. Studies have increasingly revealed the influence of distributional statistical properties of words on visual word processing, including the effects of word frequency (lexical level) and mappings between orthography, phonology, and semantics (sub-lexical level). However, there has been scant evidence to directly confirm that the statistical properties contained in print can be directly characterized by neural activities. Using time-resolved representational similarity analysis (RSA), the present study examined neural representations of different types of statistical properties in visual word processing. From the perspective of predictive coding, an equal probability sequence with low built-in prediction precision and three oddball sequences with high built-in prediction precision were designed with consistent and three types of inconsistent (orthographically inconsistent, orthography-to-phonology inconsistent, and orthography-to-semantics inconsistent) Chinese characters as visual stimuli. In the three oddball sequences, consistent characters were set as the standard stimuli (probability of occurrence p = 0.75) and three types of inconsistent characters were set as deviant stimuli (p = 0.25), respectively. In the equal probability sequence, the same consistent and inconsistent characters were presented randomly with identical occurrence probability (p = 0.25). Significant neural representation activities of word frequency were observed in the equal probability sequence. By contrast, neural representations of sub-lexical statistics only emerged in oddball sequences where short-term predictions were shaped. These findings reveal that the statistical properties learned from long-term print environment continues to play a role in current word processing mechanisms and these mechanisms can be modulated by short-term predictions.

Neural correlates of statistical learning in developmental dyslexia: An electroencephalography study

The human brain extracts statistical regularities from the surrounding environment in a process called statistical learning. Behavioural evidence suggests that developmental dyslexia affects statistical learning. However, surprisingly few studies have assessed how developmental dyslexia affects the neural processing underlying this type of learning. We used electroencephalography to explore the neural correlates of an important aspect of statistical learning - sensitivity to transitional probabilities - in individuals with developmental dyslexia. Adults diagnosed with developmental dyslexia (n = 17) and controls (n = 19) were exposed to a continuous stream of sound triplets. Every so often, a triplet ending had a low transitional probability given the triplet's first two sounds ("statistical deviants"). Furthermore, every so often a triplet ending was presented from a deviant location ("acoustic deviants"). We examined mismatch negativity elicited by statistical deviants (sMMN), and MMN elicited by location deviants (i.e., acoustic changes). Acoustic deviants elicited a MMN which was larger in the control group than in the developmental dyslexia group. Statistical deviants elicited a small, yet significant, sMMN in the control group, but not in the developmental dyslexia group. However, the difference between the groups was not significant. Our findings indicate that the neural mechanisms underlying pre-attentive acoustic change detection and implicit statistical auditory learning are both affected in developmental dyslexia.

The different brain areas occupied for integrating information of hierarchical linguistic units: a study based on EEG and TMS

Human language units are hierarchical, and reading acquisition involves integrating multisensory information (typically from auditory and visual modalities) to access meaning. However, it is unclear how the brain processes and integrates language information at different linguistic units (words, phrases, and sentences) provided simultaneously in auditory and visual modalities. To address the issue, we presented participants with sequences of short Chinese sentences through auditory, visual, or combined audio-visual modalities while electroencephalographic responses were recorded. With a frequency tagging approach, we analyzed the neural representations of basic linguistic units (i.e. characters/monosyllabic words) and higher-level linguistic structures (i.e. phrases and sentences) across the 3 modalities separately. We found that audio-visual integration occurs in all linguistic units, and the brain areas involved in the integration varied across different linguistic levels. In particular, the integration of sentences activated the local left prefrontal area. Therefore, we used continuous theta-burst stimulation to verify that the left prefrontal cortex plays a vital role in the audio-visual integration of sentence information. Our findings suggest the advantage of bimodal language comprehension at hierarchical stages in language-related information processing and provide evidence for the causal role of the left prefrontal regions in processing information of audio-visual sentences.

The Brain Connectome for Chinese Reading

Chinese, as a logographic language, fundamentally differs from alphabetic languages like English. Previous neuroimaging studies have mainly focused on alphabetic languages, while the exploration of Chinese reading is still an emerging and fast-growing research field. Recently, a growing number of neuroimaging studies have explored the neural circuit of Chinese reading. Here, we summarize previous research on Chinese reading from a connectomic perspective. Converging evidence indicates that the left middle frontal gyrus is a specialized hub region that connects the ventral with dorsal pathways for Chinese reading. Notably, the orthography-to-phonology and orthography-to-semantics mapping, mainly processed in the ventral pathway, are more specific during Chinese reading. Besides, in addition to the left-lateralized language-related regions, reading pathways in the right hemisphere also play an important role in Chinese reading. Throughout, we comprehensively review prior findings and emphasize several challenging issues to be explored in future work.