Lexical-semantic Representations Research Articles

Decoding speech perception from non-invasive brain recordings

Decoding speech from brain activity is a long-awaited goal in both healthcare and neuroscience. Invasive devices have recently led to major milestones in this regard: deep-learning algorithms trained on intracranial recordings can now start to decode elementary linguistic features such as letters, words and audio-spectrograms. However, extending this approach to natural speech and non-invasive brain recordings remains a major challenge. Here we introduce a model trained with contrastive learning to decode self-supervised representations of perceived speech from the non-invasive recordings of a large cohort of healthy individuals. To evaluate this approach, we curate and integrate four public datasets, encompassing 175 volunteers recorded with magneto-encephalography or electro-encephalography while they listened to short stories and isolated sentences. The results show that our model can identify, from 3 seconds of magneto-encephalography signals, the corresponding speech segment with up to 41% accuracy out of more than 1,000 distinct possibilities on average across participants, and with up to 80% in the best participants—a performance that allows the decoding of words and phrases absent from the training set. The comparison of our model with a variety of baselines highlights the importance of a contrastive objective, pretrained representations of speech and a common convolutional architecture simultaneously trained across multiple participants. Finally, the analysis of the decoder’s predictions suggests that they primarily depend on lexical and contextual semantic representations. Overall, this effective decoding of perceived speech from non-invasive recordings delineates a promising path to decode language from brain activity, without putting patients at risk of brain surgery.

Contribution and functional connectivity between cerebrum and cerebellum on sub-lexical and lexical-semantic processing of verbs.

Language comprehension involves both sub-lexical (e.g., phonological) and lexical-semantic processing. We conducted a task using functional magnetic resonance imaging (fMRI) to compare the processing of verbs in these two domains. Additionally, we examined the representation of concrete-motor and abstract-non-motor concepts by including two semantic categories of verbs: motor and mental. The findings indicate that sub-lexical processing during the reading of pseudo-verbs primarily involves the left dorsal stream of the perisylvian network, while lexical-semantic representation during the reading of verbs predominantly engages the ventral stream. According to the embodied or grounded cognition approach, modality-specific mechanisms (such as sensory-motor systems) and the well-established multimodal left perisylvian network contribute to the semantic representation of both concrete and abstract verbs. Our study identified the visual system as a preferential modality-specific system for abstract-mental verbs, which exhibited functional connectivity with the right crus I/lobule VI of the cerebellum. Taken together, these results confirm the dissociation between sub-lexical and lexical-semantic processing and provide neurobiological evidence of functional coupling between specific visual modality regions and the right cerebellum, forming a network that supports the semantic representation of abstract concepts. Further, the results shed light on the underlying mechanisms of semantic processing and contribute to our understanding of how the brain processes abstract concepts.

MANIFESTATIONS OF VISUAL PERCEPTUAL PROCESSING IN ADULT WITH BROCA APHASIA _ A NEUROCOGNITIVE APPROACH: VERBAL SEMANTIC REPRESENTATION AND WORD EVOCATION_

Neurological injury to the areas responsible for language comprehension and production can lead to its disruption or even loss, resulting in what is known in neuropsychology as Broca's aphasia. The clinical profile of individuals with Broca's aphasia generally exhibits a specific deficit called "Broca's non-fluent aphasia," characterized by word retrieval difficulties and the inability to produce the target word when required. These impairments involve linguistic disturbances that affect levels of the lexical-semantic processing system for words. Therefore,the aim of this scientific paper is to explore the manifestations of visual cognitive processing of images in individuals with Broca's aphasia during picture naming, using a neuropsycholinguistic approach to lexical-semantic representation and word retrieval. Additionally, we aim to present the most important compensatory strategies adopted by individuals with Broca's aphasia to overcome naming failures. Finally, we will conclude by offering a range of suggestions that can enhance diagnostic procedures and treatment methods.

Analogical inference from distributional structure: What recurrent neural networks can tell us about word learning

One proposal that can explain the remarkable pace of word learning in young children is that they leverage the language-internal distributional similarity of familiar and novel words to make analogical inferences about possible meanings of novel words (Lany and Gómez, 2008; Lany and Saffran, 2011; Savic et al., 2022b; Unger and Fisher, 2021; Wojcik and Saffran, 2015). However, a cognitively and developmentally plausible computational account of how language-internal lexical representations are acquired to enable this kind of analogical inference has not been previously investigated. In this work, we tested the feasibility of using the SRN (Elman, 1990) as the supplier of language-internal representations for use in analogical inference. While the SRN is in many ways well suited to this task, we discuss several theoretical challenges that might limit its success. In a series of simulations with controlled artificial languages and the CHILDES corpus, we show that Recurrent Neural Networks (RNNs) are prone to acquiring ‘entangled’ lexical semantic representations, where some features of a word are partially encoded in the representations of other frequently co-occurring words. However, we also show that this problem is mitigated when RNNs are first trained on language input to young children, due to the fact that its distributional structure more reliably predicts semantic category membership of individual words. Overall, our work sheds light on the conditions under which RNNs organize their learned knowledge so that word-level information can be more easily extracted and used in downstream processes, such as word learning.

ЛЕКСИКО-СЕМАНТИЧНЕ ПОЛЕ ЛОКУСІВ ШОТЛАНДСЬКОЇ КАЗКИ

The article is devoted to the study of a special type of literary discourse – the discourse of the Scottish fairy tale, which is understood as a complex sociocultural communicative product of the thought process of the collective linguistic personality of the ethnic group. A fairy tale is the most extensive type of oral folk art, it is a symbol of culture, a work created collectively by a certain nation, which reflects its spiritual state, morality, customs and traditions; it is a way of preserving culture in different historical periods, awareness of the spiritual values ​​of the people, history, traditions, beliefs and ideals. One of the important basic categories in human being is the category of space, as it is the universal form of existence of matter. When studying the lexical-semantic representations of the field "space", the hierarchical system of the functional-semantic field "space" N.D. Tkachenko was taken as a basis and two microfields (names of natural space and artificial space) are distinguished, which consist of 12 thematic groups (names of land masses; names of relief; names of lowlands; names of forests; names of mountains and hills; names of water space; names of swamps; names of administrative divisions of the earth surface; names of countries; names of settlements; names of communication routes; names of housing). The largest number of nominations includes the thematic group of names of settlements (60%), the second in terms of words is the group of names of mountains and hills (13%). Nominations of groups of water space names and country names make up 12% and 9%, respectively. Considering the obtained results, it can be stated that spatial lexemes and toponyms are symbols that reflect the specifics of national self-awareness, the nation's reflection on its own history and culture. The space of geographical names of fairy tales should be considered as a special microcosm in which the real reality familiar to every person is reflected.

Contributions of semantic and phonological working memory to narrative language independent of single word production: Evidence from acute stroke

ABSTRACT Neuropsychological case studies have provided evidence that individuals with semantic, but not phonological, working memory (WM) deficits have difficulty producing phrases containing several content words. These findings supported the claim of a phrasal scope of planning at the grammatical formulation stage of production, where semantic WM supports the maintenance of lexical-semantic representations as they are inserted into slots in phrasal constituents. Recent narrative production results for individuals at the acute stage of stroke supported the role for semantic WM in phrasal elaboration while suggesting a role for phonological WM at a subsequent phonological encoding stage in supporting fluent, rapid speech. In the present study, we employed a larger participant sample while controlling for single word production abilities at semantic and phonological levels. Results confirmed the relations between semantic WM and phrasal elaboration whereas the relation between phonological WM and speech rate was eliminated. There was, however, evidence that both impaired phonological retrieval and restricted phonological WM were related to the tendency to produce short, highly frequent words such as pronouns rather than longer, less frequent words. Future research is needed to address whether the results relating to phonological WM depend on damage specific to an output rather than an input phonological capacity.

Affective valence of words differentially affects visual and auditory word recognition.

Recognizing written or spoken words involves a sequence of processing stages, transforming sensory features into lexical-semantic representations. Whereas the later processing stages are common across modalities, the initial stages are modality-specific. In the visual modality, previous studies have shown that words with positive valence are recognized faster than neutral words. Here, we examined whether the effects of valence on word recognition are specific to the visual modality or are common across visual and auditory modalities. To address this question, we analyzed multiple large databases of visual and auditory lexical decision tasks, relating the valence of words to lexical decision times while controlling for a large number of variables, including arousal and frequency. We found that valence differentially influenced visual and auditory word recognition. Valence had an asymmetric effect on visual lexical decision times, primarily speeding up recognition of positive words. By contrast, valence had a symmetric effect on auditory lexical decision times, with both negative and positive words speeding up word recognition relative to neutral words. The modality-specificity of valence effects were consistent across databases and were observed when the same sets of words were compared across modalities. We interpret these findings as indicating that valence influences word recognition partly at the sensory-perceptual stage. We relate these effects to the effects of positive (reward) and negative (punishment) reinforcers on perception. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The elusive impact of L2 immersion on translation priming

AbstractA growing consensus sees the bilingual lexicon as an integrated, nonselective system. However, the way bilingual experience shapes the architecture and functioning of the lexicon is not well understood. This study investigates bilingual lexical-semantic representation and processing employing written translation priming. We focus on the role of active exposure to and use of the second language (L2)—primarily operationalized as immersion. We tested 200 highly proficient Spanish–English bilinguals in two groups differing in their societal language (immersed vs. nonimmersed) and amount of L2 use. L2 proficiency was controlled across participants, allowing us to disentangle its effects from those of L2 use. Overall, however, the immersion’s impact on our data was minimal. This suggests a ceiling effect for the influence of active L2 use on bilingual lexical functioning when L2 development is maximal. The present data provide relevant insights into the nature of the bilingual lexicon, informing developmental models.

Investigating Lexical Concept and Semantic Representation of Covid-19 in Coronavirus Corpus: A Corpus-Based Study

This article discusses the lexical and semantic representation through the collocation that appeared in the Coronavirus Corpus. This research investigates the frequent collocates that appeared together with the node word Corona and find out how those collocates construct the meaning through the linguistic system and conceptual system as they are involved in lexical representation. This research offers a new insight into teaching language using Lexical Concepts and Cognitive Models (Evans, 2009). The data collected are from the Coronavirus corpus by using the corpus-based method. The strength of the keywords and collocate is measured by using Mutual Information (MI). The MI was set in 5; therefore, three lexemes resulted, i.e., cases, patients, and outbreak. The data were analyzed using the lexical concept and cognitive model proposed by Evans (2009). The research results, in general, reveal that the information is coming from the “authorized institution” and “government’s representative”; it needs “the official approval or agreement” before publishing to the media, and in the passive form, it describes the foregrounded information and agentless informational assertion. Therefore, the information should be accurate and firm. However, another lexical concept reveals that the information is terrorizing and terrifying; the educated and trained person should also conduct the treatment.

LEXICAL-SEMANTIC REPRESENTATION OF SOLIDARITY THROUGH COLLOCATIONS IN THE RUSSIAN AND GERMAN LANGUAGES

Purpose. The study is aimed at determining the general and linguocultural specific characteristics of the lexico-semantic representation of the phenomenon of solidarity in the Russian and German linguocultures through a multi-aspect analysis of verb collocations.
 Methodology. Collocations are considered as statistically stable phrases that reflect the language usage as well as the native speakers’ concept of solidarity. The structure, internal and external transitivity / intransitivity, objectivity, subjectivity, seriality, structural-semantic models, thematic codes, pragmatic component of the meaning of collocations are described. The established characteristics of the lexical-semantic representation of solidarity in two linguistic cultures are compared. The descriptive, comparative method, structural-semantic modeling, semantic, distributive analysis, classification method, quantitative calculations are used.
 Results. The vector nature of the keywords interlingual correspondence, the predominance of a positive presentation of solidarity in both languages are established; differences in the presentation of solidarity situations as initiated by the subject / involuntary, in frequency subject codes and a tendency to form a series of collocations, in lexical-semantic differentiation of various solidarity situations and grounds for a negative assessment of solidarity are identified.
 Practical implications. The results can be used in lexicographic practice, in research on related topics; in university courses on lexicology and semantics.

Multichannel CNN Model for Biomedical Entity Reorganization.

Biomedical researchers and biologists often search a large amount of literature to find the relationship between biological entities, such as drug-drug and compound-protein. With the proliferation of medical literature and the development of deep learning, the automatic extraction of biological entity interaction relationships from literature has shown great potential. The fundamental scope of this research is that the approach described in this research uses technologies like dynamic word vectors and multichannel convolution to learn a larger variety of relational expression semantics, allowing it to detect more entity connections. The extraction of biological entity relationships is the foundation for achieving intelligent medical care, which may increase the effectiveness of intelligent medical question answering and enhance the development of precision healthcare. In the past, deep learning methods have achieved specific results, but there are the following problems: the model uses static word vectors, which cannot distinguish polysemy; the weight of words is not considered, and the extraction effect of long sentences is poor; the integration of various models can improve the sample imbalance problem, the model is more complex. The purpose of this work is to create a global approach for eliminating different physical entity links, such that the model can effectively extract the interpretation of the expression relationship without having to develop characteristics manually. To this end, a deep multichannel CNN model (MC-CNN) based on the residual structure is proposed, generating dynamic word vectors through BERT (Bidirectional Encoder Representation from Transformers) to improve the accuracy of lexical semantic representation and uses multihead attention to capture the dependencies of long sentences and by designing the Ranking loss function to replace the multimodel ensemble to reduce the impact of sample imbalance. Tested on multiple datasets, the results show that the proposed method has good performance.

Fuzzy or Clear? A Computational Approach Towards Dynamic L2 Lexical-Semantic Representation

In this paper, we present a computational approach to bilingual speakers’ non-native (L2) lexical-semantic representations. Specifically, based on detailed analyses of the error patterns shown in our previous simulation results (Zhao and Li Int. J. Bilingual. Educ. Bilingual., 2010, 13, 505–524;Zhao and Li, Bilingualism, 2013, 16, 288–303), we aim at revealing the underlying learning factors that may affect the extent of fuzzy category boundaries within bilinguals’ L2 representation. Here, we first review computational bilingual models in the literature that have focused on simulating L2 lexical representations, including the Developmental Lexicon II (DevLex-II) model (Zhao and Li, Int. J. Bilingual. Educ. Bilingual., 2010, 13, 505–524;Zhao and Li, Bilingualism, 2013, 16, 288–303), on which the current study is based. The DevLex-II modeling results indicate a strong age of acquisition (AoA) effect: When the learning of L2 is early relative to that of native language (L1), functionally distinct lexical representations may be established for both languages; when the learning of L2 is significantly delayed relative to that of L1, fuzzy L2 representations may occur due to the structural consolidation (or theentrenchment) of the L1 lexicon. Next, we explore the error patterns shown in both lexical comprehension and production in DevLex-II. A novel contribution of the current study is that we systematically compare the computational simulation results with empirical findings. Such model-based error analyses extend our previous findings by indicating, especially in the late L2 learning condition, that fuzzy L2 semantic representations emerge and lead to processing errors, including errors in unstable phonology-semantic and semantic-phonemic mappings. The DevLex-II model provides a computational account of the development of bilinguals’ L2 representation with reference to the dynamic interaction and competition between the two lexicons. We point to future directions in which fuzzy L2 representations may be overcome, through a framework that highlights the social learning of L2 (SL2) and the embodied semantic representation of the lexicon in the new language (Li and Jeong, Npj Sci. Learn., 2020, 5, 1–9;Zhang, Yang, Wang and Li, Lang. Cogn. Neurosci., 2020, 35, 1223–1238).

A lexical semantic approach to the L2 acquisition of Spanish psych verbs

This study builds on prior research on second language (L2) Spanish psych verbs, which has centered on morphosyntactic properties, by examining their syntactic distribution, which relies on lexical semantic knowledge. The fact that certain forms are licensed for some verbs, but not others, is the result of an underlying lexical semantic difference across verb classes, represented here as a difference in formal feature strength. To fully acquire the relevant grammatical distribution, L2 learners must successfully acquire (i) licensing restrictions on argument structure and (ii) underlying lexical semantic representations of individual verbs. Three groups of L2 learners ( n = 66) and a group of native Spanish speakers ( n = 19) completed two judgment tasks (one with aural stimuli and one with written stimuli) which presented object experiencer psych verbs in multiple argument structures. Results show that advanced L2 learners are largely sensitive to the distribution tested here; however, while they have acquired relevant licensing restrictions, they may associate fixed feature settings with verbs that allow variable feature settings. These results are consistent with predictions made by the Feature Reassembly Hypothesis and highlight the role of lexical semantic features in second language acquisition.

Лексико-конструкционный подход к синтаксической альтернации

Syntactic alternation cannot be treated as a lexical or as a constructional phenomenon (as is in lexical and constructional approaches, respectively). Realizing the significance of both factors, in the present paper I offer a lexical-constructional account of syntactic alternation which seems to prevail against previous ones by eliminating their shortcomings but exploiting their advantages. I demonstrate the explanatory power of my conception by thorough analysis of three Russian verb classes. They include the alternation of manner-of-motion and directional motion verbs as well as the locative alternation and instrument–subject alternation. The fundamental feature of my proposal is the underspecified character of lexical-semantic representations. Although underspecification may have several forms, the general idea consists in postulating optional components in lexical representations. It can be stated that verbs alternate syntactically if they own an underspecified but encyclopedically and pragmatically enriched representation, so being compatible with all meanings appearing in alternations. If a verb does not have a lexical-semantic representation that can result in different interpretations, it cannot participate in an alternation. Because of the possible lexical specification of either variant, an underspecified type of representation is inevitably required for alternating verbs. The lexical-constructional approach to syntactic alternation naturally extends to lexical pragmatics. This extension means that the hypotheses about the characteristics of word meaning representations can also be applied to cases where words reach their full meanings in corresponding contexts without the change of syntactic structure.

Predictive pre-activation of orthographic and lexical-semantic representations facilitates visual word recognition.

To a crucial extent, the efficiency of reading results from the fact that visual word recognition is faster in predictive contexts. Predictive coding models suggest that this facilitation results from pre-activation of predictable stimulus features across multiple representational levels before stimulus onset. Still, it is not sufficiently understood which aspects of the rich set of linguistic representations that are activated during reading-visual, orthographic, phonological, and/or lexical-semantic-contribute to context-dependent facilitation. To investigate in detail which linguistic representations are pre-activated in a predictive context and how they affect subsequent stimulus processing, we combined a well-controlled repetition priming paradigm, including words and pseudowords (i.e., pronounceable nonwords), with behavioral and magnetoencephalography measurements. For statistical analysis, we used linear mixed modeling, which we found had a higher statistical power compared to conventional multivariate pattern decoding analysis. Behavioral data from 49 participants indicate that word predictability (i.e., context present vs. absent) facilitated orthographic and lexical-semantic, but not visual or phonological processes. Magnetoencephalography data from 38 participants show sustained activation of orthographic and lexical-semantic representations in the interval before processing the predicted stimulus, suggesting selective pre-activation at multiple levels of linguistic representation as proposed by predictive coding. However, we found more robust lexical-semantic representations when processing predictable in contrast to unpredictable letter strings, and pre-activation effects mainly resembled brain responses elicited when processing the expected letter string. This finding suggests that pre-activation did not result in "explaining away" predictable stimulus features, but rather in a "sharpening" of brain responses involved in word processing.

Lexical-Semantic Representations at the Time of the Coronavirus Pandemic

This paper examines some cases of lexical adaptation and innovation in present-day English resulting from changed communicative needs brought about by the current coronavirus pandemic. The data analysed consists of 15 lexical items retrieved in the NOW Corpus, a web-based collection of newspapers and magazines freely accessible online. The study shows that certain already existing words and expressions tend to be used more frequently in coronavirus-related discourse than in other contexts prior to the current crisis; others appear to be undergoing a re-adaptation of their semantic range, while new ones seem to have emerged and to be making their way into dictionaries. At the same time, there are certain free-word combinations built “on the fly” whose stability is still uncertain.

Delimiting durative events with manner

Abstract Durative events by default are atelic. However, temporal targets are typically required for durative verbs with a rushing manner, such as ‘We are catching the 3:30 flight’ and ‘The farmer rushed to harvest before the storm’. Why and how does manner introduce delimiting temporal concepts to durative verbs? This puzzle is addressed by our current study of two near-synonymous Mandarin durative verbs describing events carried out in a rushing manner: 赶 gǎn and 抢 qiǎng. Our event-based account will examine both their compositional meanings and their constructional patterns. We will show that 赶 gǎn and 抢 qiǎng not only coerce eventive readings from their nominal objects, but also require certain delineating temporal targets. The verb 赶 gǎn requires an understood deadline, while the verb 抢 qiǎng requires the presupposition of the limited availability of the object. As neither temporal targets mark the time of the actual activities, these are exceptional cases of aktionsart. We will show that the different ways to delineate event meanings of the constructions [gǎn/qiǎng+ noun] can be predicted from the lexical meaning of the two verbs and can in turn predict the event types represented by the object with the MARVS theory. Based on this lexical semantic representation, we further show that the Generative Lexicon theory predicts the coercions of the rushing meaning from the original activity verb senses, and that the Construction Grammar theory accounts for their sharing of the same syntactic configuration.

Detection without further processing or processing without automatic detection? Differential ERP responses to lexical-semantic processing in toddlers at high clinical risk for autism and language disorder

Delays in early expressive vocabulary can reflect a specific delay in language acquisition or more general impairments in social communication. The neural mechanisms underlying the (dis)ability to establish the first lexical–semantic representations remain relatively unknown. Here, we investigate the electrophysiological underpinnings of these mechanisms during the critical phase of lexical acquisition in two groups of 19-month-old toddlers at risk for neurodevelopmental disorders, i.e., children characterized by low expressive vocabulary (late talkers, N = 18) and children with early signs of Autism Spectrum Disorder (ASD, N = 18) as compared to typically developing children (N = 28), with the aim to identify similarities and specificities in lexical-semantic processing between these groups. ERPs elicited by words (either congruous or incongruous with the previous picture context) and pseudo-words are investigated within a picture-word matching paradigm. In order to further interpret ERP responses, we look at longitudinal intra-group associations with language and socio-communications skills at age 24 months.As expected, we found differences between the groups that might underlie specificities, but also similarities. On the one side, late talkers differed from the other two groups in the early component (phonological-lexical priming effect) reflecting detection of the correspondence between the heard word and the lexical representation pre-activated by the picture. On the other side, children with early symptoms of ASD differed from the other two groups in the late component (late positive component) reflecting the effortful semantic re-analysis following a violation. The functional interpretation of the two components is corroborated by significant correlations suggesting that the early component is associated with later socio-communication skills, whereas the late component is associated with linguistic skills. Results point in the direction of differential impaired mechanisms in the two populations, i.e., impaired automatic detection of incongruencies in late talkers vs. absence of high-level re-analysis of such incongruencies in children with early signs of ASD.

Causation in Polish anticausatives

The aims of this paper are twofold. The first objective is to check whether Polish anticausatives are causative in their lexical semantic or syntactic representation. Four diagnostics supporting the presence of a cause in anticausatives are examined against the Polish data, including cause PPs, modification by by itself, the interpretation of negation, and the occurrence of dative causes. Evidence is provided that none of these diagnostics proves the presence of a cause in syntax or semantics of Polish anticausatives. The causative meaning of anticausatives comes from the complex event structure built in the syntax, but interpreted as causative at the syntax-semantics interface. The paper also aims to offer a syntactic analysis of Polish anticausatives in the Minimalist Program of Chomsky (2000, et seq.). The validity of three approaches to the structure of anticausatives is tested against the Polish data, including the unaccusative analysis of Schäfer (2008), the reflexive account of Koontz-Garboden (2009) and Cuervo (2014, 2015), and the predication-based approach of Den Dikken and Dekány (2019). Schäfer's (2008) analysis seems to best fit the Polish data, since Polish anticausatives are unaccusative and contain a reflexive marker, equipped with φ-features, but lacking a theta role, hence functioning as an A-expletive.

Distinct fronto-temporal substrates of distributional and taxonomic similarity among words: evidence from RSA of BOLD signals

A class of semantic theories defines concepts in terms of statistical distributions of lexical items, basing meaning on vectors of word co-occurrence frequencies. A different approach emphasizes abstract hierarchical taxonomic relationships among concepts. However, the functional relevance of these different accounts and how they capture information-encoding of lexical meaning in the brain still remains elusive.We investigated to what extent distributional and taxonomic models explained word-elicited neural responses using cross-validated representational similarity analysis (RSA) of functional magnetic resonance imaging (fMRI) and model comparisons.Our findings show that the brain encodes both types of semantic information, but in distinct cortical regions. Posterior middle temporal regions reflected lexical-semantic similarity based on hierarchical taxonomies, in coherence with the action-relatedness of specific semantic word categories. In contrast, distributional semantics best predicted the representational patterns in left inferior frontal gyrus (LIFG, BA 47). Both representations coexisted in the angular gyrus supporting semantic binding and integration. These results reveal that neuronal networks with distinct cortical distributions across higher-order association cortex encode different representational properties of word meanings. Taxonomy may shape long-term lexical-semantic representations in memory consistently with the sensorimotor details of semantic categories, whilst distributional knowledge in the LIFG (BA 47) may enable semantic combinatorics in the context of language use.Our approach helps to elucidate the nature of semantic representations essential for understanding human language.