Semantic unification, the process by which small blocks of semantic information are combined into a coherent utterance, has been studied with various types of tasks. However, whether the brain activations reported in these studies are attributed to semantic unification per se or to other task-induced concomitant processes still remains unclear. The neural basis for semantic unification in sentence comprehension was examined using event-related potentials (ERP) and functional Magnetic Resonance Imaging (fMRI). The semantic unification load was manipulated by varying the goodness of fit between a critical word and its preceding context (in high cloze, low cloze and violation sentences). The sentences were presented in a serial visual presentation mode. The participants were asked to perform one of three tasks: semantic congruency judgment (SEM), silent reading for comprehension (READ), or font size judgment (FONT), in separate sessions. The ERP results showed a similar N400 amplitude modulation by the semantic unification load across all of the three tasks. The brain activations associated with the semantic unification load were found in the anterior left inferior frontal gyrus (aLIFG) in the FONT task and in a widespread set of regions in the other two tasks. These results suggest that the aLIFG activation reflects a semantic unification, which is different from other brain activations that may reflect task-specific strategic processing.
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Semantic unification during sentence comprehension has been associated with amplitude change of the N400 in event-related potential (ERP) studies, and activation in the left inferior frontal gyrus (IFG) in functional magnetic resonance imaging (fMRI) studies. However, the specificity of this activation to semantic unification remains unknown. To more closely examine the brain processes involved in semantic unification, we employed simultaneous EEG-fMRI to time-lock the semantic unification related N400 change, and integrated trial-by-trial variation in both N400 and BOLD change beyond the condition-level BOLD change difference measured in traditional fMRI analyses. Participants read sentences in which semantic unification load was parametrically manipulated by varying cloze probability. Separately, ERP and fMRI results replicated previous findings, in that semantic unification load parametrically modulated the amplitude of N400 and cortical activation. Integrated EEG-fMRI analyses revealed a different pattern in which functional activity in the left IFG and bilateral supramarginal gyrus (SMG) was associated with N400 amplitude, with the left IFG activation and bilateral SMG activation being selective to the condition-level and trial-level of semantic unification load, respectively. By employing the EEG-fMRI integrated analyses, this study among the first sheds light on how to integrate trial-level variation in language comprehension.
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During sentence level language comprehension, semantic and syntactic unification are functionally distinct operations. Nevertheless, both recruit roughly the same brain areas (spatially overlapping networks in the left frontotemporal cortex) and happen at the same time (in the first few hundred milliseconds after word onset). We tested the hypothesis that semantic and syntactic unification are segregated by means of neuronal synchronization of the functionally relevant networks in different frequency ranges: gamma (40 Hz and up) for semantic unification and lower beta (10–20 Hz) for syntactic unification. EEG power changes were quantified as participants read either correct sentences, syntactically correct though meaningless sentences (syntactic prose), or sentences that did not contain any syntactic structure (random word lists). Other sentences contained either a semantic anomaly or a syntactic violation at a critical word in the sentence. Larger EEG gamma-band power was observed for semantically coherent than for semantically anomalous sentences. Similarly, betaband power was larger for syntactically correct sentences than for incorrect ones. These results confirm the existence of a functional dissociation in EEG oscillatory dynamics during sentence level language comprehension that is compatible with the notion of a frequency-based segregation of syntactic and semantic unification.
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Gamma-band neuronal synchronization during sentence-level language comprehension has previously been linked with semantic unification. Here, we attempt to further narrow down the functional significance of gamma during language comprehension, by distinguishing between two aspects of semantic unification: successful integration of word meaning into the sentence context, and prediction of upcoming words. We computed eventrelated potentials (ERPs) and frequency band-specific electroencephalographic (EEG) power changes while participants read sentences that contained a critical word (CW) that was (1) both semantically congruent and predictable (high cloze, HC), (2) semantically congruent but unpredictable (low cloze, LC), or (3) semantically incongruent (and therefore also unpredictable; semantic violation, SV). The ERP analysis showed the expected parametric N400 modulation (HC < LC < SV). The time-frequency analysis showed qualitatively different results. In the gamma-frequency range, we observed a power increase in response to the CW in the HC condition, but not in the LC and the SV conditions. Additionally, in the theta frequency range we observed a power increase in the SV condition only. Our data provide evidence that gamma power increases are related to the predictability of an upcoming word based on the preceding sentence context, rather than to the integration of the incoming word's semantics into the preceding context. Further, our theta band data are compatible with the notion that theta band synchronization in sentence comprehension might be related to the detection of an error in the language input.
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This study provides ERP and oscillatory dynamics data associated with the comprehension of narratives involving counterfactual events. Participants were given short stories describing an initial situation ("Marta wanted to plant flowers in her garden...."), followed by a critical sentence describing a new situation in either a factual ("Since she found a spade, she started to dig a hole") or counterfactual format ("If she had found a spade, she would have started to dig a hole"), and then a continuation sentence that was either related to the initial situation ("she bought a spade") or to the new one ("she planted roses"). The ERPs recorded for the continuation sentences related to the initial situation showed larger negativity after factuals than after counterfactuals, suggesting that the counterfactual's presupposition - the events did not occur - prevents updating the here-and-now of discourse. By contrast, continuation sentences related to the new situation elicited similar ERPs under both factual and counterfactual contexts, suggesting that counterfactuals also activate momentarily an alternative "as if" meaning. However, the reduction of gamma power following counterfactuals, suggests that the "as if" meaning is not integrated into the discourse, nor does it contribute to semantic unification processes.
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The relationship between the evoked responses (ERPs/ERFs) and the event-related changes in EEG/MEG power that can be observed during sentence-level language comprehension is as yet unclear. This study addresses a possible relationship between MEG power changes and the N400m component of the event-related field. Whole-head MEG was recorded while subjects listened to spoken sentences with incongruent (IC) or congruent (C) sentence endings. A clear N400m was observed over the left hemisphere, and was larger for the IC sentences than for the C sentences. A time-frequency analysis of power revealed a decrease in alpha and beta power over the left hemisphere in roughly the same time range as the N400m for the IC relative to the C condition. A linear regression analysis revealed a positive linear relationship between N400m and beta power for the IC condition, not for the C condition. No such linear relation was found between N400m and alpha power for either condition. The sources of the beta decrease were estimated in the LIFG, a region known to be involved in semantic unification operations. One source of the N400m was estimated in the left superior temporal region, which has been related to lexical retrieval. We interpret our data within a framework in which beta oscillations are inversely related to the engagement of task-relevant brain networks. The source reconstructions of the beta power suppression and the N400m effect support the notion of a dynamic communication between the LIFG and the left superior temporal region during language comprehension.
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To study the ways in which compounds can induce adverse effects, toxicologists have been constructing Adverse Outcome Pathways (AOPs). An AOP can be considered as a pragmatic tool to capture and visualize mechanisms underlying different types of toxicity inflicted by any kind of stressor, and describes the interactions between key entities that lead to the adverse outcome on multiple biological levels of organization. The construction or optimization of an AOP is a labor intensive process, which currently depends on the manual search, collection, reviewing and synthesis of available scientific literature. This process could however be largely facilitated using Natural Language Processing (NLP) to extract information contained in scientific literature in a systematic, objective, and rapid manner that would lead to greater accuracy and reproducibility. This would support researchers to invest their expertise in the substantive assessment of the AOPs by replacing the time spent on evidence gathering by a critical review of the data extracted by NLP. As case examples, we selected two frequent adversities observed in the liver: namely, cholestasis and steatosis denoting accumulation of bile and lipid, respectively. We used deep learning language models to recognize entities of interest in text and establish causal relationships between them. We demonstrate how an NLP pipeline combining Named Entity Recognition and a simple rules-based relationship extraction model helps screen compounds related to liver adversities in the literature, but also extract mechanistic information for how such adversities develop, from the molecular to the organismal level. Finally, we provide some perspectives opened by the recent progress in Large Language Models and how these could be used in the future. We propose this work brings two main contributions: 1) a proof-of-concept that NLP can support the extraction of information from text for modern toxicology and 2) a template open-source model for recognition of toxicological entities and extraction of their relationships. All resources are openly accessible via GitHub (https://github.com/ontox-project/en-tox).
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Background: The aging population is increasingly faced with daily life limitations, threatening their Functional Independence (FI). These limitations extend different life domains and require a broad range of community-care professionals to be addressed. The Decision Support Tool for Functional Independence (DST-FI) facilitates community-care professionals in providing uncontradictory recommendations regarding the maintenance of FI in community-dwelling older people. The current study aims to determine the validity and reliability of the DST-FI. Methods: Sixty community-care professionals completed a twofold assessment. To assess construct validity, participants were asked to assign predefined recommendations to fifty cases of older people to maintain their level of FI. Hypotheses were tested regarding the expected recommendations per case. Content validity was assessed by questions on relevance, comprehensiveness, and comprehensibility of the current set of recommendations. Twelve participants repeated the assessment after two weeks to enable both within- and between rater reliability properties, expressed by an Intraclass Correlation Coefficient. Results: Seven out of eight predefined hypotheses confirmed expectations, indicating high construct validity. As the recommendations were indicated 'relevant' and 'complete', content validity was high as well. Agreement between raters was poor to moderate while agreement within raters was moderate to excellent, resulting in moderate overall reliability. Conclusion: The DST-FI suggests high validity and moderate reliability properties when used in a population of community-dwelling older people. The tool could facilitate community-care professionals in their task to preserve FI in older people. Future research should focus on psychometric properties like feasibility, acceptability, and developing and piloting strategies for implementation in community-care.
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