The representation of noun-verb distinction in left posterior middle temporal gyrus: evidence from representation similarity analyses.

Nouns and verbs are fundamental grammatical building blocks of languages. A key question is whether and where the noun-verb division was represented in the brain. Previous studies mainly used univariate analyses to examine this issue. However, the interpretation of activated brain regions in univariate analyses may be confounded with general cognitive processing and/or confounding variables. We addressed these limitations by using partial representation similarity analysis (RSA) of Chinese nouns and verbs with different levels of imageability. Participants were asked to complete the 1-back grammatical class probe (GCP; an explicit measure) and the 1-back word probe (WP; an implicit measure) tasks while undergoing functional magnetic resonance imaging. RSA results showed that the activation pattern in the left posterior middle temporal gyrus (LpMTG) was significantly correlated with the grammatical class representational dissimilarity matrix in the GCP task after eliminating the potential confounding variables. Moreover, the LpMTG did not overlap with the frontal-parietal regions that were activated by verbs vs. nouns or the task effect (CRP vs. WP) in univariate analyses. These results highlight the role of LpMTG in distinguishing nouns from verbs rather than general cognitive processing.

Perceptual uncertainty explains activation differences between audiovisual congruent speech and McGurk stimuli.

Face-to-face communication relies on the integration of acoustic speech signals with the corresponding facial articulations. In the McGurk illusion, an auditory /ba/ phoneme presented simultaneously with a facial articulation of a /ga/ (i.e., viseme), is typically fused into an illusory 'da' percept. Despite its widespread use as an index of audiovisual speech integration, critics argue that it arises from perceptual processes that differ categorically from natural speech recognition. Conversely, Bayesian theoretical frameworks suggest that both the illusory McGurk and the veridical audiovisual congruent speech percepts result from probabilistic inference based on noisy sensory signals. According to these models, the inter-sensory conflict in McGurk stimuli may only increase observers' perceptual uncertainty. This functional magnetic resonance imaging (fMRI) study presented participants (20 male and 24 female) with audiovisual congruent, McGurk (i.e., auditory /ba/ + visual /ga/), and incongruent (i.e., auditory /ga/ + visual /ba/) stimuli along with their unisensory counterparts in a syllable categorization task. Behaviorally, observers' response entropy was greater for McGurk compared to congruent audiovisual stimuli. At the neural level, McGurk stimuli increased activations in a widespread neural system, extending from the inferior frontal sulci (IFS) to the pre-supplementary motor area (pre-SMA) and insulae, typically involved in cognitive control processes. Crucially, in line with Bayesian theories these activation increases were fully accounted for by observers' perceptual uncertainty as measured by their response entropy. Our findings suggest that McGurk and congruent speech processing rely on shared neural mechanisms, thereby supporting the McGurk illusion as a valid measure of natural audiovisual speech perception.

Parafoveal and foveal N400 effects in natural reading: A timeline of semantic processing from fixation-related potentials.

The depth at which parafoveal words are processed during reading is an ongoing topic of debate. Recent studies using RSVP-with-flanker paradigms have shown that implausible words within sentences elicit an N400 component while they are still in parafoveal vision, suggesting that the semantics of parafoveal words can be accessed to rapidly update the sentence representation. To study this effect in natural reading, we combined the coregistration of eye movements and EEG with the deconvolution modeling of fixation-related potentials (FRPs) to test whether semantic plausibility is processed parafoveally during Chinese sentence reading. For one target word per sentence, both its parafoveal and foveal plausibility were orthogonally manipulated using the boundary paradigm. Consistent with previous eye movement studies, we observed a delayed effect of parafoveal plausibility on fixation durations that only emerged on the foveal word. Crucially, in FRPs aligned to the pretarget fixation, a clear N400 effect emerged already based on parafoveal plausibility, with more negative voltages for implausible previews. Once participants fixated the target, we again observed an N400 effect of foveal plausibility. Interestingly, this foveal N400 was absent whenever the preview had been implausible, indicating that when a word's (im)plausibility is already processed in parafoveal vision, this information is not revised anymore upon direct fixation. Implausible words also elicited a late positive component (LPC), but exclusively when in foveal vision. Our results not only provide convergent neural and behavioral evidence for the parafoveal uptake of semantic information, but also indicate different contributions of parafoveal versus foveal information toward higher level sentence processing.

Photoelectrochemical immunosensor for HER2 detection based on BiVO4-Bi2S3 heterojunction as photoactive material and CdS as signal probe.

A sandwiched photoelectrochemical (PEC) sensor was developed for sensitive detection of human epidermal growth factor receptor 2 (HER2) based on BiVO4-Bi2S3 heterojunction as the photoelectric material accompanied with magnetic nanoparticles for enrichment of HER2 and CdS for signal amplification. The in situ generation of Bi2S3 on the surface of BiVO4 forming a BiVO4-Bi2S3 heterojunction is more conducive to the transit of electron-hole pairs. Antibody-modified MNs are utilized to capture and separate HER2 from samples. After forming a sandwich immune structure, under illumination, the photocurrent shows an increasing trend with the increment of HER2 concentration. The PEC immunosensor displays a good linear concentration range between 1.00 and 1.00 × 103 pg·mL-1 and a low limit of detection down to 0.680 pg·mL-1 (S/N = 3) for HER2 under a bias voltage of 0.1 V (vs. Ag/AgCl electrode). Furthermore, the sensor was successfully applied to detect HER2 in serum samples with recoveries that ranged between 96.1 and 114% with RSDs between 1.3 and 5.9%.

Neural Fingerprints Underlying Individual Language Learning Profiles.

Human language learning differs significantly across individuals in the process and ultimate attainment. Although decades of research exploring the neural substrates of language learning have identified distinct and overlapping neural networks subserving learning of different components, the neural mechanisms that drive the large interindividual differences are still far from being understood. Here we examine to what extent the neural dynamics of multiple brain networks in men and women across sessions of training contribute to explaining individual differences in learning multiple linguistic components (i.e., vocabulary, morphology, and phrase and sentence structures) of an artificial language in a 7 d training and imaging paradigm with functional MRI. With machine-learning and predictive modeling, neural activation patterns across training sessions were highly predictive of individual learning success profiles derived from the four components. We identified four neural learning networks (i.e., the Perisylvian, frontoparietal, salience, and default-mode networks) and examined their dynamic contributions to the learning success prediction. Moreover, the robustness of the predictions systematically changes across networks depending on specific training phases and the learning components. We further demonstrate that a subset of network nodes in the inferior frontal, insular, and frontoparietal regions increasingly represent newly acquired language knowledge, while the multivariate connectivity between these representation regions is enhanced during learning for more successful learners. These findings allow us to understand why learners differ and are the first to attribute not only the degree of success but also patterns of language learning across components, to neural fingerprints summarized from multiple neural network dynamics.SIGNIFICANCE STATEMENT Individual differences in learning a language are widely observed not only within the same component of language but also across components. This study demonstrates that the dynamics of multiple brain networks across four imaging sessions of a 7 d artificial language training contribute to individual differences in learning-outcome profiles derived from four language components. With machine-learning predictive modeling, we identified four neural learning networks, including the Perisylvian, frontoparietal, salience, and default-mode networks, that contribute to predicting individual learning-outcome profiles and revealed language-component-general and component-specific prediction patterns across training sessions. These findings provide significant insights in understanding training-dependent neural dynamics underlying individual differences in learning success across language components.

The role of left angular gyrus in the representation of linguistic composition relations.

Language comprehension is compositional: individual words are combined structurally to form larger meaning representations. The neural basis for compositionality is at the center of a growing body of recent research. Previous work has largely used univariate analysis to investigate the question, a technique that could potentially lead to the loss of fined-grained information due to the procedure of averaging over neural responses. In a functional magnetic resonance imaging experiment, the present study examined different types of composition relations in Chinese phrases, using a 1-back composition relation probe (CRP) task and a 1-back word probe (WP) task. We first analyzed the data using the multivariate representation similarity analysis, which better captures the fine-grained representational differences in the stimuli. The results showed that the left angular gyrus (AG) represents different types of composition relations in the CRP task, but no brain areas were identified in the WP task. We also conducted a traditional univariate analysis and found greater activations in the bilateral inferior frontal gyrus in the CRP task relative to the WP task. We discuss the methodological and theoretical implications of our findings in the context of the larger language neural network identified in previous studies. Our findings highlight the role of left AG in representing and distinguishing fine-grained linguistic composition relations.

Generalizable predictive modeling of semantic processing ability from functional brain connectivity.

Semantic processing (SP) is one of the critical abilities of humans for representing and manipulating conceptual and meaningful information. Neuroimaging studies of SP typically collapse data from many subjects, but its neural organization and behavioral performance vary between individuals. It is not yet understood whether and how the individual variabilities in neural network organizations contribute to the individual differences in SP behaviors. We aim to identify the neural signatures underlying SP variabilities by analyzing functional connectivity (FC) patterns based on a large-sample Human Connectome Project (HCP) dataset and rigorous predictive modeling. We used a two-stage predictive modeling approach to build an internally cross-validated model and to test the model's generalizability with unseen data from different HCP samples and other out-of-sample datasets. FC patterns within a putative semantic brain network were significantly predictive of individual SP scores summarized from five SP-related behavioral tests. This cross-validated model can be used to predict unseen HCP data. The model generalizability was enhanced in the language task compared with other tasks used during scanning and was better for females than males. The model constructed from the HCP dataset can be partially generalized to two independent cohorts that participated in different semantic tasks. FCs connecting to the Perisylvian language network show the most reliable contributions to predictive modeling and the out-of-sample generalization. These findings contribute to our understanding of the neural sources of individual differences in SP, which potentially lay the foundation for personalized education for healthy individuals and intervention for SP and language deficits patients.

A distributed dynamic brain network mediates linguistic tone representation and categorization.

Successful categorization requires listeners to represent the incoming sensory information, resolve the "blooming, buzzing confusion" inherent to noisy sensory signals, and leverage the accumulated evidence towards making a decision. Despite decades of intense debate, the neural systems underlying speech categorization remain unresolved. Here we assessed the neural representation and categorization of lexical tones by native Mandarin speakers (N = 31) across a range of acoustic and contextual variabilities (talkers, perceptual saliences, and stimulus-contexts) using functional magnetic imaging (fMRI) and an evidence accumulation model of decision-making. Univariate activation and multivariate pattern analyses reveal that the acoustic-variability-tolerant representations of tone category are observed within the middle portion of the left superior temporal gyrus (STG). Activation patterns in the frontal and parietal regions also contained category-relevant information that was differentially sensitive to various forms of variability. The robustness of neural representations of tone category in a distributed fronto-temporoparietal network is associated with trial-by-trial decision-making parameters. These findings support a hybrid model involving a representational core within the STG that operates dynamically within an extensive frontoparietal network to support the representation and categorization of linguistic pitch patterns.

Neural dynamics underlying the acquisition of distinct auditory category structures.

Despite the multidimensional and temporally fleeting nature of auditory signals we quickly learn to assign novel sounds to behaviorally relevant categories. The neural systems underlying the learning and representation of novel auditory categories are far from understood. Current models argue for a rigid specialization of hierarchically organized core regions that are fine-tuned to extracting and mapping relevant auditory dimensions to meaningful categories. Scaffolded within a dual-learning systems approach, we test a competing hypothesis: the spatial and temporal dynamics of emerging auditory-category representations are not driven by the underlying dimensions but are constrained by category structure and learning strategies. To test these competing models, we used functional Magnetic Resonance Imaging (fMRI) to assess representational dynamics during the feedback-based acquisition of novel non-speech auditory categories with identical dimensions but differing category structures: rule-based (RB) categories, hypothesized to involve an explicit sound-to-rule mapping network, and information integration (II) based categories, involving pre-decisional integration of dimensions via a procedural-based sound-to-reward mapping network. Adults were assigned to either the RB (n = 30, 19 females) or II (n = 30, 22 females) learning tasks. Despite similar behavioral learning accuracies, learning strategies derived from computational modeling and involvements of corticostriatal systems during feedback processing differed across tasks. Spatiotemporal multivariate representational similarity analysis revealed an emerging representation within an auditory sensory-motor pathway exclusively for the II learning task, prominently involving the superior temporal gyrus (STG), inferior frontal gyrus (IFG), and posterior precentral gyrus. In contrast, the RB learning task yielded distributed neural representations within regions involved in cognitive-control and attentional processes that emerged at different time points of learning. Our results unequivocally demonstrate that auditory learners' neural systems are highly flexible and show distinct spatial and temporal patterns that are not dimension-specific but reflect underlying category structures and learning strategies.

Toxicity evaluation of mesoporous silica particles Santa Barbara No. 15 amorphous in human umbilical vein endothelial cells: influence of particle morphology.

Morphology plays a vital role in determining the biological effects of silica nanoparticles (NPs), but its influence on the toxicity of silica NPs in endothelial cells (ECs) is still inconclusive. We synthesized five kinds of Santa Barbara 15 amorphous (SBA-15) particles with different shapes and added them to human umbilical vein endothelial cells (HUVEC). After 24 After incubation and treatment with 100 ml, more than 80% of the cells are still alive. The microgram/ml of SBA-15 indicates that SBA-15 has high biocompatibility. Fibrous SBA-15 (5) leads to the highest Si element concentration in HUVEC. No NP reduces the release of NO, and NO is an important signaling molecule in the vascular system. Only the aggregated spherical SBA-15 (3) will moderately reduce the endothelial nitric oxide synthase (eNOS) protein. Regarding transcription factors regulating eNOS, we found that all SBA-15 types significantly increased Kruppel-like factor 2 (KLF2) protein, irregular SBA-15 (1), non-aggregated spherical SBA-15 (2) and aggregation The spherical SBA-15 (3) greatly reduces KLF4 by more than 50%. Overall, our results indicate that SBA-15 with different morphologies can be internalized into HUVEC and only cause moderate cytotoxicity. All silica NPs have the smallest effect on the NO-eNOS pathway, but the irregular spherical SBA-15 reduces the eNOS modifier KLF4. The rod-shaped SBA-15 (4) seems to have higher biocompatibility because they are internalized and have negligible adverse effects on HUVEC. These results provide new evidence for the toxic effects of different forms of silica nanoparticles on HUVEC.

Task-General and Acoustic-Invariant Neural Representation of Speech Categories in the Human Brain.

A significant neural challenge in speech perception includes extracting discrete phonetic categories from continuous and multidimensional signals despite varying task demands and surface-acoustic variability. While neural representations of speech categories have been previously identified in frontal and posterior temporal-parietal regions, the task dependency and dimensional specificity of these neural representations are still unclear. Here, we asked native Mandarin participants to listen to speech syllables carrying 4 distinct lexical tone categories across passive listening, repetition, and categorization tasks while they underwent functional magnetic resonance imaging (fMRI). We used searchlight classification and representational similarity analysis (RSA) to identify the dimensional structure underlying neural representation across tasks and surface-acoustic properties. Searchlight classification analyses revealed significant "cross-task" lexical tone decoding within the bilateral superior temporal gyrus (STG) and left inferior parietal lobule (LIPL). RSA revealed that the LIPL and LSTG, in contrast to the RSTG, relate to 2 critical dimensions (pitch height, pitch direction) underlying tone perception. Outside this core representational network, we found greater activation in the inferior frontal and parietal regions for stimuli that are more perceptually similar during tone categorization. Our findings reveal the specific characteristics of fronto-tempo-parietal regions that support speech representation and categorization processing.

[Semantic processing in language comprehension: evidence from multi-methodologies].

Semantic processing plays a key role in the language comprehension. In the past more than two decades, by using different kinds of cognitive neuroscience methods, the time course and the neural basis of semantic processing had been comprehensively investigated, and a few classic models had been proposed based on these studies. Future studies should focus more on a precise and systematic definition of the concept of semantic processing. Furthermore, by using the convergence evidence from multi-methodologies, more systematic studies on semantic processing should be carried out from the perspective of the wholeness and the interactivity of the brain function to understand the processes.

Distinct patterns of discrimination and orienting for temporal processing of speech and nonspeech in Chinese children with autism: an event-related potential study.

Although many studies have reported domain-general impaired duration perception for speech and nonspeech sounds in children with autism, it remained unclear whether this phenomenon is universally applicable regardless of language background. In some languages such as Finnish and Japanese, vowel duration serves a phonemic role that can signify semantic distinction, and in others (e.g., Mandarin Chinese), vowel duration does not carry this phonemic function. The present event-related potential study investigated neural sensitivity to duration contrasts in speech and nonspeech contexts in Mandarin-speaking children with autism and a control group of age-matched typically developing (TD) children. A passive oddball paradigm was adopted to elicit the mismatch negativity (MMN) and involuntary orienting response (P3a) for change detection. A pure tone condition and a vowel condition were used. The MMN results showed that the autism group had diminished response amplitude and delayed latency in the pure tone condition compared to the TD group, whereas no group difference was found in the vowel condition. The P3a results showed no significant between-group MMN difference in the pure tone condition. In the vowel condition, the autism group had smaller P3a than the TD group. Together, the distinct patterns of discrimination and orienting responses for duration contrasts in pure tones and vowels are consistent with the 'allophonic perception' theory for autism, which may reflect a compromised perceptual weighting system for speech learning.

Training-induced brain activation and functional connectivity differentiate multi-talker and single-talker speech training.

In second language acquisition studies, the high talker variability training approach has been frequently used to train participants to learn new speech patterns. However, the neuroplasticity induced by training is poorly understood. In the present study, native English speakers were trained on non-native pitch patterns (linguistic tones from Mandarin Chinese) in multi-talker (N = 16) or single-talker (N = 16) training conditions. We focused on two aspects of multi-talker training, voice processing and lexical phonology accessing, and used functional magnetic resonance imaging (fMRI) to measure the brain activation and functional connectivity (FC) of two regions of interest in a tone identification task conducted before and after training, namely the anterior part of the right superior temporal gyrus (aRSTG) and the posterior left superior temporal gyrus (pLSTG). The results showed distinct patterns of associations between neural signals and learning success for multi-talker training. Specifically, post-training brain activation in the aRSTG and FC strength between the aRSTG and pLSTG were correlated with learning success in the multi-talker training group but not in the single-talker group. These results suggest that talker variability in the training procedure may enhance neural efficiency in these brain areas and strengthen the cooperation between them. Our findings highlight the brain processing of newly learned speech patterns is influenced by the given training approach.

MELD-SCH: A megastudy of lexical decision in simplified Chinese.

Here we report on MELD-SCH (MEgastudy of Lexical Decision in Simplified CHinese), a dataset that contains the lexical decision data of 1,020 one-character, 10,022 two-character, 949 three-character, and 587 four-character simplified Chinese words obtained from 504 native Chinese users. It also includes a number of word-level and character-level variables. Analyses showed that the reliability of the dataset is satisfactory, as indicated by split-half correlations and comparisons with other datasets. Item-based regression showed that both word-level and character-level variables contributed significantly to the reaction times and error rates of lexical decision. Moreover, we discovered a U-shape relationship between word-length and reaction times, which has not been reported in Chinese before. MELD-SCH can facilitate research in Chinese word recognition by providing high quality normative data and information of different linguistic variables. It also encourages researchers to extend their empirical findings, which are mostly based on one-character and two-character words, to words of different lengths.

Separate Brain Circuits Support Integrative and Semantic Priming in the Human Language System.

Semantic priming is a crucial phenomenon to study the organization of semantic memory. A novel type of priming effect, integrative priming, has been identified behaviorally, whereby a prime word facilitates recognition of a target word when the 2 concepts can be combined to form a unitary representation. We used both functional and anatomical imaging approaches to investigate the neural substrates supporting such integrative priming, and compare them with those in semantic priming. Similar behavioral priming effects for both semantic (Bread-Cake) and integrative conditions (Cherry-Cake) were observed when compared with an unrelated condition. However, a clearly dissociated brain response was observed between these 2 types of priming. The semantic-priming effect was localized to the posterior superior temporal and middle temporal gyrus. In contrast, the integrative-priming effect localized to the left anterior inferior frontal gyrus and left anterior temporal cortices. Furthermore, fiber tractography showed that the integrative-priming regions were connected via uncinate fasciculus fiber bundle forming an integrative circuit, whereas the semantic-priming regions connected to the posterior frontal cortex via separated pathways. The results point to dissociable neural pathways underlying the 2 distinct types of priming, illuminating the neural circuitry organization of semantic representation and integration.

Enzyme-antibody dual-film modified gold nanoparticle probe for ultrasensitive detection of alpha fetoprotein.

In this study, we designed a comprehensive strategy for the ultrasensitive detection of alpha fetoprotein (AFP) with high specificity using gold nanoparticle (AuNP)-based enzyme-linked immunosorbent assay (ELISA). A dual-film modified probe was synthesized by coating AuNPs with horseradish peroxidase (HRP) on its surface. Anti-AFP monoclonal antibody (McAb) was immobilized on the surface of the enzyme using glutaraldehyde cross-linking method. AuNPs, employed as support for the immobilization of HRP. HRP was used not only as the enzymatic-amplified tracer but also as a bridge for loading McAb. The limit of detection was 2 ng mL-1. The developed probes can provide an alternative approach with high sensitivity and a simple process similar to that of the traditional HRP-McAb based ELISA for the ultrasensitive detection of AFP in serum.

Dynamic brain architectures in local brain activity and functional network efficiency associate with efficient reading in bilinguals.

The human brain is organized as a dynamic network, in which both regional brain activity and inter-regional connectivity support high-level cognitive processes, such as reading. However, it is still largely unknown how the functional brain network organizes to enable fast and effortless reading processing in the native language (L1) but not in a non-proficient second language (L2), and whether the mechanisms underlying local activity are associated with connectivity dynamics in large-scale brain networks. In the present study, we combined activation-based and multivariate graph-theory analysis with functional magnetic resonance imaging data to address these questions. Chinese-English unbalanced bilinguals read narratives for comprehension in Chinese (L1) and in English (L2). Compared with L2, reading in L1 evoked greater brain activation and recruited a more globally efficient but less clustered network organization. Regions with both increased network efficiency and enhanced brain activation in L1 reading were mostly located in the fronto-temporal reading-related network (RN), whereas regions with decreased global network efficiency, increased clustering, and more deactivation in L2 reading were identified in the default mode network (DMN). Moreover, functional network efficiency was closely associated with local brain activation, and such associations were also modulated by reading efficiency in the two languages. Our results demonstrate that an economical and integrative brain network topology is associated with efficient reading, and further reveal a dynamic association between network efficiency and local activation for both RN and DMN. These findings underscore the importance of considering interregional connectivity when interpreting local BOLD signal changes in bilingual reading.

Left middle temporal and inferior frontal regions contribute to speed of lexical decision: a TMS study.

Activation of left anterior inferior frontal gyrus (aLIFG) and left middle temporal gyrus (LMTG) has been observed in some functional neuroimaging studies of lexical decision but not others. It is thus unclear whether these two regions are necessary for word recognition. By applying continuous theta-burst transcranial magnetic stimulation (TMS) which temporally suppresses local brain function, we examined whether aLIFG and LMTG play causal roles in word recognition in a visual lexical decision task (LDT). Furthermore, we manipulated stimulus onset asynchrony (SOA) between prime and target to test whether these regions contribute to word recognition differently. In the LDT task, target words were preceded by semantically related primes (Related Condition; RC) or semantically unrelated words (Unrelated Condition; UC), under both short (150 ms) and long (600 ms) SOA conditions. TMS of aLIFG and LMTG significantly affected the word recognition speed compared to TMS of Vertex. Our results provide evidence that both aLIFG and LMTG contribute to word recognition speed. Furthermore, at short SOA, TMS of aLIFG or LMTG prolonged reaction time (RT). In contrast, at long SOA, there was a significant region by SOA by TMS interaction such that TMS of aLIFG prolonged RT, whereas TMS of LMTG speeded RT. These results suggest that aLIFG and LMTG may play different roles in word recognition.

The effect of event impact on fear of missing out: the chain mediation effect of coping styles and anxiety.

The fear of missing out is a generalized anxiety stemming from the possibility of not being present at new events or advantageous situations of others. To explore potential mechanisms, a survey measuring the impact of event, coping style, anxiety, and fear of missing out was conducted with 1,014 college students (367 males and 647 females, aged 19-24 years). In addition, the study delved deeper into the dimensions of intrusion, avoidance, and hyperarousal concerning the impact of event, examining their roles in coping style, anxiety, and fear of missing out. Results showed that: (1) The impact of event could predict the fear of missing out positively. (2) A more positive coping style is negatively associated with anxiety. (3) A chain mediation effect of coping style and anxiety is observed in the path from hyperarousal and avoidance to the fear of missing out. (4) In contrast to the hyperarousal or avoidance, the path from intrusion to the fear of missing out is mediated by anxiety but not coping style. These findings motivate us to implement different intervention tactics for varying impacts of events.