Brain and Language

Second language (L2) processing engages both language-specific and domain-general control systems, yet how these systems vary with L2 proficiency remains unclear. We used functional magnetic resonance imaging (fMRI) to examine neural activity during L2 English processing in Korean-English (K-E) bilinguals across three proficiency levels (beginner, intermediate, advanced). Participants performed rhyme and spelling judgement tasks manipulating orthographic-phonological conflict. Behaviourally, conflict conditions reduced accuracy, with proficiency effects observed selectively in the rhyme task. fMRI results showed that conflict processing recruited frontoparietal control regions, including inferior frontal and parietal cortices, accompanied by deactivation in default mode network regions. Critically, proficiency-related effects differed by task. During rhyme judgement, advanced bilinguals showed greater activation in the left supramarginal gyrus (SMG) and cerebellum, whereas intermediate bilinguals exhibited greater recruitment of the left middle orbital gyrus and dorsomedial prefrontal cortex. During spelling judgement, advanced bilinguals showed greater thalamic activation alongside greater deactivation of the right dorsolateral prefrontal cortex. Activity in the left SMG and cerebellum was positively associated with L2 reading score, and cerebellar activity was also associated with rhyme-task performance, whereas right DLPFC activity was negatively associated with the scores. These findings suggest that increasing L2 proficiency is associated less with altered recruitment of core reading regions than with task-specific shifts in the balance between phonological-specialized, subcortical attentional, and domain-general control systems supporting L2 processing.

Language experience is a powerful driver of neurocognitive plasticity, shown to modulate attentional and executive processing in speakers of multiple languages. This paper investigated how immersion in a second-language environment shapes attentional processing of speech. Fifty-eight bilingual Chinese-English speakers matched on their English language proficiency listened to competing continuous speech streams in a naturalistic listening task. They were immersed either in their native language environment (Beijing, China), or in the second language environment (Cambridge, UK). In an identical EEG experiment across the two immersion contexts, we assessed the listeners cortical tracking of attended and unattended speech and task-related attentional allocation using Temporal Response Function (mTRF) and Power Spectral Density (PSD) analyses. Behavioral comprehension of the attended narratives was uniformly high. PSD analyses showed no group difference in task-related attentional allocation, but mTRF results revealed robust differences in cortical tracking, with increased tracking of attended - but not unattended - streams in the immersed group, driven by the delta band (1-4 Hz). This boost in tracking of the attended signal declined with prolonged immersion, indicative of changes to attentional speech processing as the language environment stabilizes and consistent with the expansion-renormalization framework of neurocognitive adaptation. Jointly, these data imply that immersion in second-language environments shapes the way listeners encode speech, sharpening the brains ability to extract target auditory information from background noise. They furthermore suggest that, rather than being static or monotonous, this modulation reflects a flexible and dynamic process that is continuously shaped by changes in environmental demands and their duration. Key pointsO_LISecond language immersion boosts cortical tracking of attended speech, driven by the delta band (1-4 Hz). C_LIO_LIThis boost decreases with prolonged immersion, reflecting the dynamic, expansion-renormalization adaptation trajectory. C_LIO_LIImmersion does not influence task-related attentional allocation. C_LI

Language comprehension requires the continuous transformation of speech into a hierarchy of linguistic units, from phonemes to syllables to words. Because speech unfolds rapidly, listeners are thought to predict upcoming content to keep pace. Previous research has provided empirical evidence for predictive processes operating at multiple linguistic levels during naturalistic listening, including words and phonemes. However, it remains unclear whether prediction also operates concurrently at other levels, such as syllabic and phrasal representation. Here we use Mandarin Chinese to examine the neural signatures of predictive processing across multiple levels of linguistic granularity during natural speech comprehension. Mandarin comprises four representational levels: phoneme, sub-syllabic, character and word, and its lexical identity is largely constrained at the sub-syllabic level, potentially redistributing predictive weight across linguistic representations. We recorded magnetoencephalography (MEG) data while 34 native Mandarin speakers (21 females) listened to a naturalistic audiobook and applied linear regression modeling to examine how linguistic features modulated neural activity. We found that the brain activity of listeners segmented speech into hierarchical units, and that surprisal modulated responses simultaneously across sub-syllabic, character and word levels. In contrast to findings from Indo-European languages, however, we did not observe unique surprisal effects at the lowest, phonemic level. Furthermore, the surprisal of lexical tone in Mandarin modulated brain activity only when integrated with its phonological components. These findings suggest that predictive processing during Mandarin speech comprehension operates concurrently across multiple (though not necessarily all) levels of linguistic granularity, with its implementation shaped by language-specific structural properties. Significance statementLanguage comprehension involves segmenting a continuous acoustic stream into multiple linguistic units, from phonemes to words, and generating predictions at these levels. However, direct neural evidence remains limited regarding how segmentation and prediction operate simultaneously across levels of linguistic granularity, particularly outside Indo-European languages. Using temporal response function analysis of magnetoencephalography data recorded during naturalistic Mandarin listening, we show that predictive processing occurs across multiple levels of linguistic granularity. Specifically, we find evidence for prediction-related neural responses at sub-syllabic, character, and word levels, but not a reliable unique effect at the phonemic level. These results indicate that predictive processing also operates during Mandarin speech comprehension, and its neural implementation is shaped by language-specific structural properties.

Can grammatical gender in a bilingual's first language shape gender-stereotype processing in a second language? Spanish (L1)-English (L2) bilinguals (n = 28) and English monolinguals (n = 28) completed an event-related potential (ERP) priming task in which English pronouns (SHE/HE) followed gender-stereotyped English nouns, half of which had gender-marked Spanish translation equivalents (e.g., NURSE 'enfermera/o', SURGEON 'cirujana/o'), and half unmarked translation equivalents (e.g., SINGER 'cantante', JANITOR 'conserje'). Both groups showed asymmetric stereotype priming: male pronouns elicited a larger N400 for incongruent than congruent primes, whereas female pronouns elicited a larger P300 for incongruent than congruent primes. Crucially, only bilinguals showed modulation by Spanish grammatical gender marking: the N400 effect for male pronouns was larger for primes with gender-marked than unmarked Spanish translations. These findings provide neural evidence that grammatical gender in a bilingual's first language can influence gender-stereotype processing in a second language, linking cross-linguistic activation to social cognition.

Languages vary in whether and how they encode gender. As societies pursue greater inclusiveness, gender-inclusive language (GIL) has emerged as a debated innovation, introducing pronouns and morphological strategies to neutralize grammatical gender (e.g., todxs, for todos/todas, "all"). Yet whether GIL actually reduces gender expectations remains empirically underexplored. Evidence at the neural level is especially scarce. To address this gap, we asked Italian speakers to categorize masculine (lui, "he") and feminine (lei, "she") pronouns following nouns with canonical (masculine -o, feminine -a) or neutralized endings (-*, -{schwa}). Noun gender-stereotypical association was independently manipulated (male-oriented, e.g., chirurgo/a/{schwa}/*, "surgeon"; female-oriented, e.g., maestra/o/{schwa}/*, "teacher"; neutral, e.g., vicina/o/{schwa}/*, "neighbor"). Recording response times and event-related potentials (ERPs) to target pronouns allowed us to assess their automatic integration and processing costs. Gender-incongruent pronouns after canonical forms elicited longer response times and larger N400 and P300 amplitudes, reflecting increased processing difficulty and reanalysis. Pronouns following GIL forms showed an intermediate processing profile. Response times fell between consistent and inconsistent conditions, N400 amplitude was larger than in the consistent condition, and P300 amplitude was reduced compared to the inconsistent condition. Together these findings indicate that both pronouns remained viable interpretations and could ultimately be integrated. Stereotype-based knowledge shaped early processing without preventing integration, predominantly for masculine pronouns. Overall, our findings provide the first neural evidence that, despite processing costs, GIL forms can foster gender-neutral representations, with relevance to ongoing societal debates and broader cross-linguistic implications.

Successful speech perception requires listeners to bin continuous acoustic information into discrete phonetic categories. However, some people maintain within-category acoustic information (gradient) while others discard category-irrelevant information (discrete) during perception. Listeners also vary in how consistently they label speech sounds and more gradient/consistent labeling has been linked with better speech-in-noise (SIN) perception. Here, we test how neuroanatomical properties of the brain's major speech-language and auditory pathways relate to individual differences in speech categorization and SIN processing. We measured phonetic categorization and SIN comprehension via phoneme labeling and QuickSIN tasks. Diffusion-weighted imaging (DWI) with probabilistic tractography estimated axonal density within the bilateral arcuate fasciculi and brainstem-cortical auditory projections. Anatomical morphology (surface area, gray matter volume, thickness) was also quantified in the adjacent frontotemporal cortical areas and midbrain. Behaviorally, we found more consistent categorizers had better performance on the QuickSIN. DWI showed that more gradient listeners had greater white matter density in the left arcuate fasciculus and brainstem-cortical auditory pathways, while better SIN performance was predicted by denser white matter in the brainstem-cortical auditory pathways. Morphometric results revealed more consistent listening was associated with greater cortical thickness in right superior temporal gyrus and more gradient listening was associated with greater surface area in right pars opercularis. We infer that individual differences in phonetic categorization relate to SIN comprehension and are at least partially explained by neuroanatomical properties of the auditory-linguistic brain.

In school-aged children, resting-state posterior alpha activity has been linked to thalamocortical signal coordination and literacy-related cognition. However, findings are mixed, partly because conventional band power measures conflate oscillatory (periodic) activity with the broadband aperiodic (1/f) background. We tested Chinese-English bilingual children in Grades 1 to 5 (N = 121; 72 families; mean age = 8.23 years, SD = 0.81) to examine if posterior periodic alpha power (8-12 Hz), isolated from aperiodic components, predicts foundational biliteracy skills (Chinese and English word reading and dictation). We also tested whether Chinese digit rapid automatized naming (CDRAN) mediates these associations. In regression models that accounted for family clustering and controlled for age, socioeconomic status (SES), and aperiodic components (exponent and offset), higher periodic alpha power uniquely predicted better performance on all four literacy outcomes. In structural equation models that accounted for family clustering, periodic alpha power predicted CDRAN ({beta} = .213, p = .011), and CDRAN significantly predicted Chinese word reading ({beta} = .442, p < .001), Chinese dictation ({beta} = .346, p = .003), English word reading ({beta} = .302, p < .001), and English dictation ({beta} = .349, p < .001). Indirect effects via CDRAN were significant for all outcomes. These findings suggest that aperiodic-adjusted periodic alpha power is associated with biliteracy variation across Chinese and English and that its association with biliteracy operates in part through rapid serial naming efficiency.

Sentence comprehension requires the incremental construction of syntactic structure and semantic interpretation. Prior neural work (Nelson et al., 2017) identified key neural events at major phrase boundaries during sentence comprehension. To investigate a behavioral correlation of these processes, we used self-paced reading to examine the impact of syntactic phase boundaries, semantic congruence, and sentence structure on sentence processing. Participants read object-relative, subject-relative, and canonical control sentences one word at a time and a subsequent comprehension task. Reading times were analyzed relative to phrase boundaries, node-closing operations, and semantic congruence. Object-relative sentences produced the greatest processing difficulty, demonstrated by increased reading times and decreased comprehension accuracy. Reading times peaked at the phrase boundaries, indicating that processing costs are tied to constituent completion rather than individual lexical categories. Reading times also increased with the number of syntactic constituents completed at a phrase boundary. Agent-patient semantic congruence produced its largest effects in object-relative sentences, suggesting that semantic information interacts with syntactic computations when processing demands are greatest. These findings demonstrate that self-paced reading is sensitive to the incremental processing associated with syntactic constituent completion. Processing costs are tied more closely to phrase completion than to individual lexical categories, scale with the amount of syntactic structure completed at a boundary and interact with agent-patient semantic interpretation during object-relative sentence comprehension. Together, these findings support a view of sentence comprehension in which syntactic structure building and semantic interpretation proceed incrementally and interact continuously throughout online language processing.

Listeners discretize the speech signal by assigning sounds to phonetic categories, though there is variability in how individuals accomplish categorization. Having more consistent categorization of sounds may be advantageous for understanding speech-in-noise (SIN). Though, it is unclear how different levels of neural processing in the auditory system reflect these perceptual differences. We recorded brainstem frequency-following responses (FFRs) and cortical event-related potentials (ERPs) while listeners actively labeled vowels along an acoustic-phonetic continuum using a visual analog scale. We computed intertrial consistency of neural responses to index the stability of listeners' neural speech representations across stimulus presentations. We also assessed how faithfully midbrain and cortical responses represented stimulus acoustics using representational dissimilarity matrices (RDMs) computed across all token pairs. Neural RDMs were then compared with acoustic and phonetic category RDMs to assess whether FFRs and ERPs carried gradient vs. categorical information of the speech signal. We found greater behavioral consistency during phoneme labeling was correlated with improved SIN scores. Neurally, we found greater cortical or subcortical consistency predicted greater behavioral consistency. RDMs revealed subcortical responses retained more acoustic details, while cortical responses more closely reflected abstract phoneme categories. Our findings reveal important benefits of perceptual consistency to other domains of speech perception. We find perceptual consistency is driven by more consistent encoding of speech at either a cortical or subcortical level. More consistent sensory processing could provide a more stable readout of the speech signal to higher cortical brain areas which could confer advantages to later perceptual processes downstream.

Learning to read a second language requires the brain to incorporate a new writing system into an already established native-language reading network, yet how this process reshapes the Visual Word Form Area (VWFA) remains poorly understood. Using fMRI with a passive viewing paradigm, we systematically investigated how VWFA responses to Chinese (L1) and English (L2) words evolved across three groups of native Mandarin-speaking children at distinct stages of L2 literacy acquisition: L2 pre-readers, L2 beginning readers, and L2 advanced readers. We combined univariate activation analyses, representational similarity analysis, and supervised machine learning classification to investigate two theoretical accounts of VWFA reorganization: the Overlay Model, which predicts stable L1 responses as L2 responses emerge, and the Competing Model, which predicts competitive reallocation of neural resources from L1 to L2. We found that although the VWFA already exhibited robust selective responses to L1 words, L2-word selectivity was absent in L2 pre-readers but emerged robustly in beginning readers, with L1-word selectivity remaining stable throughout. Representational similarity analysis further revealed that robust L2 word representations within the VWFA emerged only after children began learning to read L2, while L1 word representations remained stable across all three groups. Finally, supervised machine learning analyses successfully discriminated among the three L2 literacy groups on the basis of L2 but not L1 activation patterns, indicating that VWFA responses to L2 alone were sufficient to capture childrens stages of L2 literacy acquisition, whereas responses to L1 were insensitive to L2 learning experience, providing no support for the Competing Models prediction of competitive neural reallocation away from L1. Together, these findings support the Overlay Model, demonstrating that the VWFA incorporates a new writing system within its existing cortical resources without compromising L1 print processing.

Face-to-face communication requires listeners to attend, integrate, and weigh multiple communicative signals, including auditory speech, mouth movements, and co-speech gestures. The contribution of these signals may depend on the reliability of auditory input and the informativeness of the available signals. We utilized rapid invisible frequency tagging (RIFT) with EEG to examine how participants attend to and integrate these different signals in clear and adverse listening conditions. Participants watched videos of an actress producing clear or noise-vocoded sentences. Auditory speech was amplitude-modulated at 58Hz, while the luminance of the gesture and mouth regions was frequency-tagged at 63Hz and 65Hz. Degraded speech elicited stronger responses at the auditory tagged frequency, suggesting increased attentional gain to the auditory signal when listening was challenging. In contrast, clear speech elicited stronger responses at the gesture tagged frequency and a stronger 2Hz intermodulation response (65-63Hz), reflecting enhanced nonlinear coupling between mouth movements and gestures. Finally, in degraded speech, the informativeness of mouth movement, but not gesture, was associated with intermodulation strength, suggesting that the informativeness of mouth movements plays a greater role in multisensory interaction when listening is challenging. Our findings demonstrate that both signal reliability and informativeness shape multisensory integration during spoken language comprehension.

The Visual Word Form Area (VWFA), located in ventral occipitotemporal cortex, plays a critical role in skilled reading. Researchers have theorized that the VWFA develops in its specific anatomical location due to the convergence of major white matter tracts and proximity to functionally similar regions. This suggests that precise anatomical positioning may be crucial for optimal VWFA function. Previous research has identified several functional differences in this region between typical and struggling readers (i.e. dyslexia): struggling readers show weaker text-selective responses and often exhibit a smaller or even absent VWFA. However, it remains unexplored whether the precise anatomical location of this region also differs between typical and struggling readers. We tested whether VWFA anatomy differs between children with and without dyslexia (N=87). Participants completed a functional localizer, which we used to manually define the VWFA in each individuals native anatomy. We examined whether: (1) VWFA anatomical location relates to reading ability, (2) children with dyslexia show greater variability in VWFA location compared to typical readers, and (3) VWFA location with respect to white matter tracts relates to reading ability. Results reveal that, despite being smaller in children with dyslexia, there is no relationship between VWFA location and reading ability. Specifically, individual VWFA location relative to anatomy, relative to others VWFAs, and relative to white matter tracts, is not related to reading ability. These findings suggest that while the VWFAs general anatomy may be facilitated by development, its precise location remains stable and unrelated to reading proficiency.

Understanding the cognitive architecture of the human language faculty requires exploring the boundaries of both predisposition and environmental experience. However, previous research on extraordinary multilingualism has often confounded language aptitude with multilingual experience, obscuring their distinct neural correlates. Here, we leveraged a linguistically diverse sample (N=121) and extensive behavioural testing to dissociate language aptitude from multilingual experience, modelling both dimensions continuously in whole-brain speech processing. Language aptitude and multilingual experience were weakly related, and their dissociation was also evident at the neural level. Higher language aptitude showed a neural signature of efficiency, characterised by lower activation in core perisylvian regions. In contrast, higher multilingualism was associated with greater engagement of regions implicated in narrative, multimodal, and memory processing, and with recruitment of traditional language hubs only during degraded speech processing, likely reflecting active attempts to decode unintelligible input. Finally, aptitude and experience interacted within sensorimotor regions. Continuous quantification of multilingual experience proved more sensitive than artificial grouping. By disentangling language aptitude from multilingual experience, this work provides a more precise account of the multilingual brain, and shows that its neurobiology can be better understood by modelling predisposition and experience as distinct but interacting dimensions.

Neural oscillations synchronize to the rhythmic structure of speech, a process known as cortical tracking that is thought to support speech perception and language acquisition. Individual differences in cortical tracking during infancy predict later language outcomes, yet little is known about whether this neural mechanism can be shaped by recent auditory experience early in development. Here, we tested whether brief exposure to structured musical rhythms modulates cortical tracking of speech in Spanish-Basque bilingual infants at 6 and 10 months of age. Infants listened to speech preceded by either temporally regular musical sequences that mirrored the rhythmic structure of the speech signal or rhythmically irregular musical sequences. Cortical tracking was measured using electroencephalography and quantified as speech-brain coherence in the delta and theta frequency bands. Regular musical sequences enhanced subsequent cortical tracking of speech, but the effects varied across age, language, and frequency band. In Spanish, rhythmic priming enhanced delta-band tracking at 10 months of age, whereas in Basque it enhanced theta-band tracking at both 6 and 10 months. These language-specific effects suggest that rhythmic priming interacts with the temporal properties of individual languages and infants' developing linguistic experience. Together, the findings demonstrate that cortical tracking is a highly flexible neural mechanism during infancy and can be rapidly modulated by structured rhythmic input. Thus, we identify rhythmic experience as a potential pathway through which infants' auditory environment shapes neural speech processing during language development.

We present the BCCWJ-Brain dataset, a multi-modal neuroimaging resource comprising functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), and electroencephalography (EEG) data recorded from native Japanese speakers reading newspaper articles from the Balanced Corpus of Contemporary Written Japanese (BCCWJ). Neural data were collected from 112 participants (36 fMRI, 35 MEG, and 41 EEG) as they read twenty newspaper articles presented in a Rapid Serial Visual Presentation (RSVP) paradigm. By providing three complementary neuroimaging modalities collected under identical naturalistic reading stimuli, this dataset provides a cognitive benchmark for computational models such as large language models. The dataset is publicly available on the OpenNeuro platform, offering a valuable resource for neuroscience, natural language processing, and related research fields.

Audiovisual semantic matching can be achieved using either written words or pictures, yet whether these formats engage shared semantic matching representations with similar temporal dynamics remains unclear. We recorded electroencephalography from 27 participants while they performed audiovisual semantic matching tasks in which spoken words were paired with either written words or pictures. Stimuli included both natural and man-made objects. Time-resolved multivariate pattern analyses (MVPA or decoding), cross-decoding, and temporal generalization analyses were used to characterize the temporal dynamics of semantic processing. Reliable decoding of matching versus mismatching judgments emerged in both word and picture conditions. Decoding onset that significant above chance level occurred earlier for written words than for pictures and cross-decoding analyses revealed successful generalization between word and picture formats. Temporal generalization analyses further demonstrated distinct representational dynamics across formats, with word processing characterized by predominantly time-specific neural representations and picture processing showing more sustained and temporally stable representations. In addition, matching-related discrimination emerged earlier for natural objects than for man-made objects across both formats. The results suggest that speech-word matching shows earlier neural evidence of audiovisual alignment than speech-picture matching, potentially reflecting differences in how auditory linguistic input is integrated with visual information across representational formats.

Word classes such as nouns, verbs, and adjectives are fundamental units of language, but their neural encoding remains unclear. Here, we investigate whether word classes are processed as invariant, context-independent lexical categories or depend on sentence context during language processing. We analyse source-localized magnetoencephalography (MEG) data from 200 native Dutch participants who read or listened to sentences and their scrambled counterparts (word lists) from the MOUS dataset. Time-resolved encoding models are used to predict neural responses from major word classes (noun, verb, adjective) and other linguistic variables including word frequency, surprisal, entropy, word length, and ordinal position. Across modalities, we observe a significant interaction between word class and context (sentences vs. word lists), manifest as dynamic modulation of neural responses in a widespread cortical network including bilateral perisylvian, frontal, and midline regions previously implicated in lexicosemantic, structural, and pragmatic processing. This interaction emerges early and reappears later in processing, with distinct temporal profiles for reading and listening. Within-condition effects reveal that word class contributes to neural responses at the level of individual words, but this contribution is context-dependent: it is robust in sentences across modalities and in word-list reading, but absent in auditory word lists. These results indicate that word-class encoding is shaped by the interaction between word-level properties and sentence context during real-time language processing.

Aphasia is characterized by impaired word retrieval, yet most cognitive models of word production assume that underlying conceptual-semantic representations are largely preserved. This study investigated whether concept-level semantic structure remains decodable from BOLD signals in chronic post-stroke aphasia and which semantic models best explain neural representational geometry during covert semantic feature generation. Eight healthy adults and six individuals with chronic aphasia completed a dense-sampling fMRI protocol in which they viewed 57 pictured nouns while silently generating semantic features. Representational similarity analysis showed that an experiential model (Exp48) best matched neural geometry in both people with aphasia and controls, outperforming taxonomic (WordNet) and distributional (Word2Vec, GloVe) models. Using representational similarity decoding, concept identity was recovered well above chance in both groups. No relationship was found between decoding accuracy and language measures from individuals with aphasia. These findings suggest that experiential semantic structure remains robustly represented and decodable in chronic aphasia despite lesion-related language impairments, highlighting preserved conceptual representations alongside altered anatomy.

Building upon foundational psychological theories of event segmentation, this study addresses the limitation of overreliance on temporal boundaries as the primary segmentation criterion. Drawing on two experiments of direct and indirect causation in Mandarin Chinese, this study demonstrates how cognitive segmentation granularity and semantic integration jointly shape syntactic encoding. Results reveal distinct event encoding patterns for direct and indirect causation: coarse-grained segmentation leads to compact syntactic structures (e.g., verb-resultatives), while fine-grained segmentation yields varied multi-clausal expressions. Chinese speakers update event models via prediction errors of intentionality and protagonists, and tend to establish event boundaries at goal-relevant action endpoints when construing causal chains. These conceptual dimensions exert a modulating influence on both event segmentation and semantic integration. We propose a triad model integrating event segmentation, semantic integration, and linguistic specificity, providing a unified framework for elucidating the mind-language interface in conceptual construction and event coding of causation.

In non-invasive studies of the human brain, semantic processing during language comprehension has been extensively studied using the N400, a component of the electrophysiological evoked response that is strongly modulated by semantic context. More recently, a complementary approach has emerged that uses multivariate pattern analysis to perform neural decoding of semantic vectors from brain activity, operating on the basis that semantic vectors that more closely align with representations in the brain can be more accurately decoded. To consolidate these two approaches, we investigated the relationship between N400 modulation and semantic decoding performance using magnetoencephalography (MEG) in a controlled priming experiment. Twenty-five native speakers of Finnish read word triplets, for which the semantic relatedness between the two primes and the target word was manipulated based on distance in a word2vec embedding space (highly related, moderately related, or unrelated). We found that words presented after unrelated primes elicited higher N400 responses and provided the best examples for training a decoder to map distributed MEG responses to semantic vectors. Semantic information was decodable from approximately 100 to 500 ms after stimulus onset, at all three levels of contextual support. Soon after the N400 peak, neural responses no longer seemed to encode information that could be mapped to context-invariant semantic vectors. This suggests that the end of the N400 window may correspond to a turning point where the representation shifts from being word-specific to encoding the greater semantic context.