Semantic Processing Research Articles

Development and validation of a nonverbal consensus-based semantic memory paradigm in patients with epilepsy.

Brain areas implicated in semantic memory can be damaged in patients with epilepsy (PWE). However, it is challenging to delineate semantic processing deficits from acoustic, linguistic, and other verbal aspects in current neuropsychological assessments. We developed a new Visual-based Semantic Association Task (ViSAT) to evaluate nonverbal semantic processing in PWE. The ViSAT was adapted from similar predecessors (Pyramids & Palm Trees test, PPT; Camels & Cactus Test, CCT) comprised of 100 unique trials using real-life color pictures that avoid demographic, cultural, and other potential confounds. We obtained performance data from 23 PWE participants and 24 control participants (Control), along with crowdsourced normative data from 54 Amazon Mechanical Turk (Mturk) workers. ViSAT reached a consensus >90% in 91.3% of trials compared to 83.6% in PPT and 82.9% in CCT. A deep learning model demonstrated that visual features of the stimulus images (color, shape; i.e., non-semantic) did not influence top answer choices (p = 0.577). The PWE group had lower accuracy than the Control group (p = 0.019). PWE had longer response times than the Control group in general and this was augmented for the semantic processing (trial answer) stage (both p < 0.001). This study demonstrated performance impairments in PWE that may reflect dysfunction of nonverbal semantic memory circuits, such as seizure onset zones overlapping with key semantic regions (e.g., anterior temporal lobe). The ViSAT paradigm avoids confounds, is repeatable/longitudinal, captures behavioral data, and is open-source, thus we propose it as a strong alternative for clinical and research assessment of nonverbal semantic memory.

Reading processes of public and private middle school and high school students.

Reading has been widely discussed, mainly due to the published results of international performance tests of schoolchildren. The gaps generated in literacy hinder the development of basic skills necessary for reading, which will have a negative impact on the teaching-learning process from elementary school to high school. This study aimed to compare the reading performance of the students in public and private schools through tests of the Brazilian reading processes-PROLEC-SE-R. Cross-sectional study. The Brazilian adaptation of the PROLEC-SE-R was administered to 436 students: 221 from the state school (G1 6th year, n = 30; G2 7th year, n = 33; G3 8th year, n = 35; G4 9th year, n = 31; G5 1st year, n = 32; G6 2nd year, n = 30; G7 3rd year, n = 30) e 215 private schools (G8 6th year, n = 31; G9 7th year, n = 31; G10 8th year, n = 30; G11 9th year, n = 31; G12 1st year, n = 30; G13 2nd year, n = 31; G14 3rd year, n = 31). Tools of descriptive and bivariate analysis were used. Superior performance of the private school students on spelling tests helps their reading as evidenced by their scores for syntactic and semantic processes. When the knowledge of the use of the word in text, extraction of meaning and its understanding was needed, the difficulty of access to the mental lexicon of the studied population became evident. The PROLEC-SE-R, in addition to establishing the reading profile of elementary and high school students, shows that the gaps in teaching and learning, which exist between public and private education in the literacy period, accompany students throughout the basic education cycle. Knowing the reading profile and in which process there is a disruption is important so that the teaching of specific strategies can be promoted throughout the entire schooling process, especially in primary and secondary education.

Bilingualism and ageing independently impact on language processing: evidence from comprehension and production

Abstract To examine the combined effects of ageing and bilingualism in language processing, we tested young and older mono- and bilingual speakers in L1 comprehension and production. In Experiment 1, bilinguals were slower to detect words than monolinguals in sentences with a low-constraint context, but not when a high-constraint context was provided. Older adults tended to outperform younger adults in high-constraint sentences. In Experiment 2, older speakers were slower than younger speakers to produce small-scope prepositional phrases (e.g., ‘the cone above the grape), suggesting more extensive planning. Bilingual disadvantages were observed in larger-scope complex phrases (e.g., ‘the cone and the pink grape’). Individual differences in language proficiency did not modulate the effects. The results support bilingual disadvantages in syntactic processing and age-preserved syntax, alongside semantic processing unaffected by either bilingualism or age. We found no interactions between age and bilingualism, suggesting that these two factors independently impact language processing.

Flexible and fine-grained simulation of speed in language processing

According to the embodied cognition theory, language comprehension is achieved through mental simulation. This account is supported by a number of studies reporting action simulations during language comprehension. However, which details of sensory-motor experience are included in these simulations is still controversial. Here, three experiments were carried out to examine the simulation of speed in action language comprehension. Experiment 1 adopted a lexical decision task and a semantic similarity judgment task on isolated fast and slow action verbs. It has been shown that fast action verbs were processed significantly faster than slow action verbs when deep semantic processing is required. Experiment 2 and Experiment 3 investigated the contextual influence on the simulation of speed, showing that the processing of verbs, either depicting fast actions or neutral actions, would be slowed down when embedded in the slow action sentences. These experiments together demonstrate that the fine-gained information, speed, is an important part of action representation and can be simulated but may not in an automatic way. Moreover, the speed simulation is flexible and can be modulated by the context.

Using Monte-Carlo simulation to test predictions about the time-course of semantic and lexical access in reading.

One of the main theoretical distinctions between reading models is how and when they predict semantic processing occurs. Some models assume semantic activation occurs after word-form is retrieved. Other models assume there is no-word form, and that what people think of as word-form is actually just semantics. These models thus predict semantic effects should occur early in reading. Results showing words with inconsistent spelling-sound correspondences are faster to read aloud if they are imageable/concrete compared to if they are abstract have been used as evidence supporting this prediction, although null-effects have also been reported. To investigate this, I used Monte-Carlo simulation to create a large set of simulated experiments from RTs taken from different databases. The results showed significant main effects of concreteness and spelling-sound consistency, as well as age-of-acquisition, a variable that can potentially confound the results. Alternatively, simulations showing a significant interaction between spelling-sound consistency and concreteness did not occur above chance, even without controlling for age-of-acquisition. These results support models that use lexical form. In addition, they suggest significant interactions from previous experiments may have occurred due to idiosyncratic items affecting the results and random noise causing the occasional statistical error.

[The EEG N400 component as a marker of language acquisition and processing in cochlear implant users].

Language processing can be measured objectively using late components in the evoked brain potential. The most established component in this area of research is the N400 component, a negativity that peaks at about 400 ms after stimulus onset with a centro-parietal maximum. It reflects semantic processing. Its presence, as well as its temporal and quantitative expression, allows to conclude about the quality of processing. It is therefore suitable for measuring speech comprehension in special populations, such as cochlear implant (CI) users. The following is an overview of the use of the N400 component as a tool for studying language processes in CI users. We present studies with adult CI users, where the N400 reflects the quality of speech comprehension with the new hearing device and we present studies with children where the emergence of the N400 component reflects the acquisition of their very first vocabulary.

Training semantic long-term memory retrieval transfers to executive function and reading fluency

The retrieval of information from long-term memory is a fundamental cognitive ability, crucial for most aspects of successful human functioning. Whether and how long-term memory retrieval (LTMR) can be improved with training has clear societal importance but also theoretical value for furthering our understanding of underlying mechanisms. Here, we provide electrophysiological evidence for the plasticity of semantic LTMR. Thirty-five university students were randomly assigned to adaptive semantic LTMR training (using a Posner task) or to a non-adaptive version of the training. Before and after training they were assessed on measures of semantic LTMR, working memory, central executive function (interference control, switching), reading fluency, and fluid intelligence. Adaptive LTMR training (relative to non-adaptive training) led to significant improvements in semantic LTMR. The intervention group (in contrast to the control group) also showed a significant reduction in the mean amplitude of the N400 ERP component and 700–1000 ms measured during a semantic LTMR task, suggesting that changes in retrieval occurred at an early/automatic point and retrieval processing in semantic processing. Moreover, transfer effects were observed for switching, working memory and reading fluency, but not for interference control or fluid intelligence. These results point to the plasticity of semantic LTMR, and suggest that improvement in this ability can transfer to other domains for which LTMR is key.

Modeling the neurocognitive dynamics of language across the lifespan.

Healthy aging is associated with a heterogeneous decline across cognitive functions, typically observed between language comprehension and language production (LP). Examining resting-state fMRI and neuropsychological data from 628 healthy adults (age 18-88) from the CamCAN cohort, we performed state-of-the-art graph theoretical analysis to uncover the neural mechanisms underlying this variability. At the cognitive level, our findings suggest that LP is not an isolated function but is modulated throughout the lifespan by the extent of inter-cognitive synergy between semantic and domain-general processes. At the cerebral level, we show that default mode network (DMN) suppression coupled with fronto-parietal network (FPN) integration is the way for the brain to compensate for the effects of dedifferentiation at a minimal cost, efficiently mitigating the age-related decline in LP. Relatedly, reduced DMN suppression in midlife could compromise the ability to manage the cost of FPN integration. This may prompt older adults to adopt a more cost-efficient compensatory strategy that maintains global homeostasis at the expense of LP performances. Taken together, we propose that midlife represents a critical neurocognitive juncture that signifies the onset of LP decline, as older adults gradually lose control over semantic representations. We summarize our findings in a novel synergistic, economical, nonlinear, emergent, cognitive aging model, integrating connectomic and cognitive dimensions within a complex system perspective.

The cognitive effects of stopping and starting antipsychotics on changes in cognitive functioning

Objectives The current study uses longitudinal data from the National Alzheimer’s Coordinating Center (NACC) to assess the effects of antipsychotic medication use on changes in cognitive functioning among adults in the United States. Methods Linear mixed models were conducted that included study visits, days between visits, sex, age, education, and medical history (i.e. diabetes, seizures, traumatic brain injury, stroke, and Parkinson’s disease). The Neuropsychiatric Inventory Questionnaire (NPI-Q) was used to create variables assessing changes in psychotic symptoms, manic symptoms, and agitation/disinhibition. Results The results indicated that starting an antipsychotic medication was associated with a greater decline in semantic fluency (Fruit and Vegetable Naming), processing speed (Digit Symbol and Trail Making Test, Part A), and cognitive flexibility (Trail Making Test, Part B). Conversely, stopping an antipsychotic medication was protective against declines in the same cognitive skills. The effect of antipsychotic medications on cognitive functioning did not appear to differ by reported changes in psychiatric symptoms after adjusting for false discovery. Conclusion The results suggest that prescribers should consider discontinuance of an antipsychotic if the patient is reporting cognitive problems and their symptoms are manageable off the medications. The findings hope to spark future research into the effects of antipsychotic use on biomarkers of progressive dementias (e.g. Alzheimer’s disease).

Semantic Stroop interference is modulated by the availability of executive resources: Insights from delta-plot analyses and cognitive load manipulation.

We investigated whether, during visual word recognition, semantic processing is modulated by attentional control mechanisms directed at matching semantic information with task-relevant goals. In previous research, we analyzed the semantic Stroop interference as a function of response latency (delta-plot analyses) and found that this phenomenon mainly occurs in the slowest responses. Here, we investigated whether this pattern is due to reduced ability to proactively maintain the task goal in these slowest trials. In two pairs of experiments, participants completed two semantic Stroop tasks: a classic semantic Stroop task (Experiment 1A and 2A) and a semantic Stroop task combined with an n-back task (Experiment 1B and 2B). The two pairs of experiments only differed in the trial pace, which was slightly faster in Experiments 2A and 2B than in Experiments 1A and 1B. By taxing the executive control system, the n-back task was expected to hinder proactive control. Delta-plot analyses of the semantic Stroop task replicated the enhanced effect in the slowest responses, but only under sufficient time pressure. Combining the semantic Stroop task with the n-back task produced a change in the distributional profile of semantic Stroop interference, which we ascribe to a general difficulty in the use of proactive control. Our findings suggest that semantic Stroop interference is, to some extent, dependent on the available executive resources, while also being sensitive to subtle variations in task conditions.

The Role of the Motor System in L1 and L2 Action Verb Processing for Chinese Learners of English: Evidence from MuRhythm Desynchronization

The nature of semantic representation has long been a key question in linguistic research. The Embodied Cognition theory challenges the traditional view of language representation, stating that semantic information stems from the sensory-motor cortex, which is activated automatically during semantic processing. However, most of the evidence comes from monolingual studies; it remains unclear whether second-language (L2) comprehension involves different semantic representations or mirrors the pattern seen in first-language (L1) processing. Therefore, the present study investigated the role of the sensory-motor system in language processing via making Electroencephalography (EEG) recordings during the processing of L1 and L2 action verbs. The results showed that L1 (Chinese) action verbs generated higher mu-event-related desynchronization (ERD) than L1 abstract verbs in the early processing stage (250 ms after verb presentation), and the same phenomenon was also observed for L2 (English). The results also indicated that language modulated the processing of action verbs, with L1 action verbs eliciting stronger ERD than L2 action verbs. These results demonstrate that the sensory-motor cortex plays a crucial role in comprehending both L1 and L2 action verbs.

An Embedding-Unleashing Video Polyp Segmentation Framework via Region Linking and Scale Alignment

Automatic polyp segmentation from colonoscopy videos is a critical task for the development of computer-aided screening and diagnosis systems. However, accurate and real-time video polyp segmentation (VPS) is a very challenging task due to low contrast between background and polyps and frame-to-frame dramatic variations in colonoscopy videos. We propose a novel embedding-unleashing framework consisting of a proposal-generative network (PGN) and an appearance-embedding network (AEN) to comprehensively address these challenges. Our framework, for the first time, models VPS as an appearance-level semantic embedding process to facilitate generate more global information to counteract background disturbances and dramatic variations. Specifically, PGN is a video segmentation network to obtain segmentation mask proposals, while AEN is a network we specially designed to produce appearance-level embedding semantics for PGN, thereby unleashing the capability of PGN in VPS. Our AEN consists of a cross-scale region linking (CRL) module and a cross-wise scale alignment (CSA) module. The former screens reliable background information against background disturbances by constructing linking of region semantics, while the latter performs the scale alignment to resist dramatic variations by modeling the center-perceived motion dependence with a cross-wise manner. We further introduce a parameter-free semantic interaction to embed the semantics of AEN into PGN to obtain the segmentation results. Extensive experiments on CVC-612 and SUN-SEG demonstrate that our approach achieves better performance than other state-of-the-art methods. Codes are available at https://github.com/zhixue-fang/EUVPS.

LEXICAL-SEMANTIC CHARACTERISTICS OF FRENCH СIVIL ENGINEERING TERMS BORROWED FROM GERMANIC FAMILY OF LANGUAGES

The research deals with the problems of the borrowed  Germanic terms in French  сivil engineering terminology. We analyze the assimilation degree of  borrowings from Germanic family of languages and  semantic processes that occur when these lexical units enter the system  of  French civil engineering terms.

The neural basis of naturalistic semantic and social cognition

Decoding social environments and engaging meaningfully with other people are critical aspects of human cognition. Multiple cognitive systems, including social and semantic cognition, work alongside each other to support these processes. This study investigated shared processing between social and semantic systems using neuroimaging data collected during movie-viewing, which captures the multimodal environment in which social knowledge is exchanged. Semantic and social content from movie events (event-level) and movie transcripts (word-level) were used in parametric modulation analyses to test (1) the degree to which semantic and social information is processed within each respective network and (2) engagement of the same cross-network regions or the same domain-general hub located within the semantic network during semantic and social processing. Semantic word and event-level content engaged the same fronto-temporo-parietal network and a portion of the semantic hub in the anterior temporal lobe (ATL). Social word and event-level content engaged the supplementary motor area and right angular gyrus within the social network, but only social words engaged the domain-general semantic hub in left ATL. There was evidence of shared processing between the social and semantic systems in the dorsolateral portion of right ATL which was engaged by word and event-level semantic and social content. Overlap between the semantic and social word and event results was highly variable within and across participants, with the most consistent loci of overlap occurring in left inferior frontal, bilateral precentral and supramarginal gyri for social and semantic words and in bilateral superior temporal gyrus extending from ATL posteriorly into supramarginal gyri for social and semantic events. These results indicate a complex pattern of shared and distinct regions for social and semantic cognition during naturalistic processing.Protocol registrationThe stage 1 protocol for this Registered Report was accepted in principle on October 11, 2022. The protocol, as accepted by the journal, can be found at: https://doi.org/10.17605/OSF.IO/ACWQY.

Measuring the menu, not the food: "psychometric" data may instead measure "lingometrics" (and miss its greatest potential).

This is a review of a range of empirical studies that use digital text algorithms to predict and model response patterns from humans to Likert-scale items, using texts only as inputs. The studies show that statistics used in construct validation is predictable on sample and individual levels, that this happens across languages and cultures, and that the relationship between variables are often semantic instead of empirical. That is, the relationships among variables are given a priori and evidently computable as such. We explain this by replacing the idea of "nomological networks" with "semantic networks" to designate computable relationships between abstract concepts. Understanding constructs as nodes in semantic networks makes it clear why psychological research has produced constant average explained variance at 42% since 1956. Together, these findings shed new light on the formidable capability of human minds to operate with fast and intersubjectively similar semantic processing. Our review identifies a categorical error present in much psychological research, measuring representations instead of the purportedly represented. We discuss how this has grave consequences for the empirical truth in research using traditional psychometric methods.

Natural language command parsing for agricultural measurement and control based on AMR and entity recognition

There is scope to enhance agricultural measurement and control systems user interactivity, which typically necessitates training for users to perform specific operations successfully. With the continuous development of natural language semantic processing technology, it has become essential to augment the user-friendliness of multifaceted control and query operations in the agricultural measurement and control sector, ultimately leading to reduced operation costs for users. The study aims to focus on command parsing. The proposed AMR-OPO semantic parsing framework is based on the natural language understanding method of Abstract Meaning Representation of Rooted Markup Graphs (AMR). It transforms the user’s natural language inputs into structured ternary (OPO) statements (operation-place-object) and converts the corresponding parameters of the user’s input commands. The framework subsequently sends the transformed commands to the relevant devices via the IoT gateway. To tackle the intricate task of parsing instructions, we developed a BERT-BiLSTM-ATT-CRF-OPO entity recognition model. This model can detect and extract entities from agricultural instructions, and precisely populate them into OPO statements. Our model shows exceptional accuracy in instruction parsing, with precision, recall, and F-value all measuring at 92.13%, 93.12%, and 92.76%, correspondingly. The findings from our experiment reveal outstanding and precise performance of our approach. It is anticipated that our algorithm will enhance the user experience offered by agricultural measurement and control systems, while also making them more user-friendly.

Warning before misinformation exposure modulates memory encoding.

Exposure to misleading information after witnessing an event can impair future memory reports about the event. This pervasive form of memory distortion, termed the misinformation effect, can be significantly reduced if individuals are warned about the reliability of post-event information before exposure to misleading information. The present fMRI study investigated whether such prewarnings improve subsequent memory accuracy by influencing encoding-related neural activity during exposure to misinformation. We employed a repeated retrieval misinformation paradigm in which participants watched a crime video (Witnessed Event), completed an initial test of memory, listened to a post-event auditory narrative that contained consistent, neutral, and misleading details (Post-Event Information), and then completed a final test of memory. At the behavioral level, participants who were given a prewarning before the Post-Event Information were less susceptible to misinformation on the final memory test compared with participants who were not given a warning (Karanian et al., Proceedings of the National Academy of Sciences of the United States of America, 117, 22771-22779, 2020). This protection from misinformation was accompanied by greater activity in frontal regions associated with source encoding (lateral PFC) and conflict detection (ACC) during misleading trials as well as a more global reduction in activity in auditory cortex and semantic processing regions (left inferior frontal gyrus) across all trials(consistent, neutral, misleading) of the Post-Event Informationnarrative. Importantly, the strength of these warning-related activity modulations was associated with better protection from misinformation on the final memory test (improved memory accuracy on misleading trials). Together, these results suggest that warnings modulate encoding-related neural activity during exposure to misinformation to improve memory accuracy.

False memories through auditory distraction: When irrelevant speech produces memory intrusions in the absence of semantic interference.

Task-irrelevant speech is known to cause disruption of short-term memory, either through specific interference with encoding processes (e.g., seriation, semantic processing) or by diverting attention from the focal task. Previous studies found that semantically related background speech can induce memory intrusions of words that were not part of the to-be-remembered list. While these findings suggest false memories due to semantic interference, the present study aims to test whether the presence of task-irrelevant speech affects the susceptibility to memory intrusions also in the absence of semantic interference. Therefore, incomprehensible to-be-ignored speech was presented during encoding of semantically related words. It was found across three experiments that incomprehensible changing-state speech increased the rate of false memories of non-presented but semantically related words in a subsequent recognition (Experiments 1 and 2) or recall test (Experiment 3), compared with white noise or steady-state speech. The findings indicate that speech interfered with serial-order processing of the to-be-remembered items, thus urging participants to rely on semantic information to encode and retrieve the presented words. While a focus on semantic information enabled participants to correctly recollect the majority of presented words, it most likely also increased the proportion of false memories of words with semantic associations to the presented words both in recall and recognition tests. In all three experiments, the presence of an auditory deviant in background speech did not increase the rate of false memories, suggesting that attentional capture alone does not necessarily induce source monitoring errors. However, Experiment 3 revealed that an increase in visual task-encoding load attenuated the changing-state effect on the production of false memories. This indicates that the semantic organisation processes initiated as a result of the loss of order information in case of changing-state speech may be sensitive to attentional control.

The influences of narrative perspective shift and scene detail on narrative semantic processing

Abstract The embodied view of semantic processing holds that readers achieve reading comprehension through mental simulation of the objects and events described in the narrative. However, it remains unclear whether and how the encoding of linguistic factors in narrative descriptions impacts narrative semantic processing. This study aims to explore this issue under the narrative context with and without perspective shift, which is an important and common linguistic factor in narratives. A sentence-picture verification paradigm combined with eye-tracking measures was used to explore the issue. The results showed that (1) the inter-role perspective shift made the participants’ to evenly allocate their first fixation to different elements in the scene following the new perspective; (2) the internal–external perspective shift increased the participants’ total fixation count when they read the sentence with the perspective shift; (3) the scene detail depicted in the picture did not influence the process of narrative semantic processing. These results suggest that perspective shift can disrupt the coherence of situation model and increase the cognitive load of readers during reading. Moreover, scene detail could not be constructed by readers in natural narrative reading.

A semantic-based methodology for the management of document workflows in e-government: a case study for judicial processes

AbstractTrial excessive duration is a common problem in Juridical systems worldwide, even if some countries seem to be more affected by it than others. The European Council has provided metrics and statistics to identify this problem and has pointed out solutions, such as the simplification of norms and the digitization of Juridical procedures. The Italian Telematic Civil Process (TCP) is an example of this digitization effort that has surely positively influenced the duration of Trials, their traceability and general complexity. However, there are still many possible actions that can be taken to simplify the work of Judges and Chancellors, and to support their daily operations in dealing with several Trials at once, and with the consistent number of documents that are involved in them. This paper presents a toolchain and a related methodology for the management of documentation attached to Trials, based on semantic technologies and Natural Language Processing techniques, which will help Judges in faster assessing the situation of each Trial they follow, and will also provide the means to identify potential correlations among different Juridical procedures. The methodology is tested against a case study, i.e. the compensation requests related to road accidents, which has been provided and described by Domain Experts from the Italian Ministry of Justice.