The mechanism underlying backward priming in a lexical decision task: Spreading activation versus semantic matching

Koriat (1981) demonstrated that an association from the target to a preceding prime, in the absence of an association from the prime to the target, facilitates lexical decision and referred to this effect as "backward priming". Backward priming is of relevance, because it can provide information about the mechanism underlying semantic priming effects. Following Neely (1991), we distinguish three mechanisms of priming: spreading activation, expectancy, and semantic matching/integration. The goal was to determine which of these mechanisms causes backward priming, by assessing effects of backward priming on a language-relevant ERP component, the N400, and reaction time (RT). Based on previous work, we propose that the N400 priming effect reflects expectancy and semantic matching/integration, but in contrast with RT does not reflect spreading activation. Experiment 1 shows a backward priming effect that is qualitatively similar for the N400 and RT in a lexical decision task. This effect was not modulated by an ISI manipulation. Experiment 2 clarifies that the N400 backward priming effect reflects genuine changes in N400 amplitude and cannot be ascribed to other factors. We will argue that these backward priming effects cannot be due to expectancy but are best accounted for in terms of semantic matching/integration

Aberrant activity in conceptual networks underlies N400 deficits and unusual thoughts in schizophrenia.

BackgroundThe N400 event-related potential (ERP) is triggered by meaningful stimuli that are incongruous, or unmatched, with their semantic context. Functional magnetic resonance imaging (fMRI) studies have identified brain regions activated by semantic incongruity, but their precise links to the N400 ERP are unclear. In schizophrenia (SZ), N400 amplitude reduction is thought to reflect overly broad associations in semantic networks, but the abnormalities in brain networks underlying deficient N400 remain unknown. We utilized joint independent component analysis (JICA) to link temporal patterns in ERPs to neuroanatomical patterns from fMRI and investigate relationships between N400 amplitude and neuroanatomical activation in SZ patients and healthy controls (HC).MethodsSZ patients (n = 24) and HC participants (n = 25) performed a picture-word matching task, in which words were either matched (APPLE→apple) by preceding pictures, or were unmatched by semantically related (in-category; IC, APPLE→lemon) or unrelated (out of category; OC, APPLE→cow) pictures, in separate ERP and fMRI sessions. A JICA "data fusion" analysis was conducted to identify the fMRI brain regions specifically associated with the ERP N400 component. SZ and HC loading weights were compared and correlations with clinical symptoms were assessed.ResultsJICA identified an ERP-fMRI "fused" component that captured the N400, with loading weights that were reduced in SZ. The JICA map for the IC condition showed peaks of activation in the cingulate, precuneus, bilateral temporal poles and cerebellum, whereas the JICA map from the OC condition was linked primarily to visual cortical activation and the left temporal pole. Among SZ patients, fMRI activity from the IC condition was inversely correlated with unusual thought content.ConclusionsThe neural networks associated with the N400 ERP response to semantic violations depends on conceptual relatedness. These findings are consistent with a distributed network underlying neural responses to semantic incongruity including unimodal visual areas as well as integrative, transmodal areas. Unusual thoughts in SZ may reflect impaired processing in transmodal hub regions such as the precuneus, leading to overly broad semantic associations

An ERP study of low and high relevance semantic features

It is believed that the N400 elicited by concepts belonging to Living is larger than N400 to Non-living. This is considered as evidence that concepts are organized, in the brain, on the basis of categories. We conducted a feature-verification experiment where Living and Non-living concepts were matched for relevance of semantic features. Relevance is a measure of the contribution of semantic features to the “core” meaning of a concept. We found that when relevance is low the N400 is large. In addition, we found that when the two categories of Living and Non-living are equated for relevance the seemingly category effect at behavioral and neural level disappeared. In sum, N400 is sensitive, rather than to categories, to semantic features, thus showing that previously reported effects of semantic categories may arise as a consequence of the differing relevance of concepts belonging to Living and Non-living categories

N400-like potentials and reaction times index semantic relations between highly repeated individual words

The N400 ERP is an electrophysiological index of semantic processing. Its amplitude varies with the semantic category of words, their concreteness, or whether their meaning matches that of a preceding context. The results of a number of studies suggest that these effects could be markedly reduced or suppressed for stimuli that are repeated. Nevertheless, we have recently shown that significant effects of semantic matching and category could be obtained on N400-like potentials elicited by massively repeated target words in a prime–target semantic categorization task. If such effects could be obtained when primes also are repeated, it would then be possible to study the semantic associations between individual words. The present study thus aimed to test this hypothesis while (1) controlling for a potential contribution of physical matching to the processing of repeated targets and (2) testing if the N400-like effects obtained in these conditions are modulated by task instruction, as are classic N400 effects. Two category words were used as primes and two exemplars as targets. In one block of trials, subjects had to respond according to the semantic relation between prime and target (semantic instruction) and, in another block, they had to report changes in letter case (physical instruction). Results showed that the amplitude of the N400-like ERP obtained was modulated by semantic matching and category but not by letter case. The effect of semantic matching was observed only in the semantic instruction block. Interestingly, the effect of category was not modulated by task instruction. An independent component analysis showed that the component that made the greatest contribution to the effect of semantic matching in the time window of the N400-like potential had a scalp distribution similar to that reported for the N400 and was best fit as a bilateral generator in the superior temporal gyrus. The use of repetition could thus allow, at least in explicit semantic tasks, a drastic simplification of N400 protocols. Highly repeated individual words could be used to study semantic relations between individual concepts

Examining the cognitive costs of counterfactual language comprehension: Evidence from ERPs

Recent empirical research suggests that understanding a counterfactual event (e.g. ‘If Josie had revised, she would have passed her exams’) activates mental representations of both the factual and counterfactual versions of events. However, it remains unclear when readers switch between these models during comprehension, and whether representing multiple ‘worlds’ is cognitively effortful. This paper reports two ERP studies where participants read contexts that set up a factual or counterfactual scenario, followed by a second sentence describing a consequence of this event. Critically, this sentence included a noun that was either consistent or inconsistent with the preceding context, and either included a modal verb to indicate reference to the counterfactual-world or not (thus referring to the factual-world). Experiment 2 used adapted versions of the materials used in Experiment 1 to examine the degree to which representing multiple versions of a counterfactual situation makes heavy demands on cognitive resources by measuring individuals’ working memory capacity. Results showed that when reference to the counterfactual-world was maintained by the ongoing discourse, readers correctly interpreted events according to the counterfactual-world (i.e. showed larger N400 for inconsistent than consistent words). In contrast, when cues referred back to the factual-world, readers showed no difference between consistent and inconsistent critical words, suggesting that they simultaneously compared information against both possible worlds. These results support previous dual-representation accounts for counterfactuals, and provide new evidence that linguistic cues can guide the reader in selecting which world model to evaluate incoming information against. Crucially, we reveal evidence that maintaining and updating a hypothetical model over time relies upon the availability of cognitive resources

Predictability's aftermath: Downstream consequences of word predictability as revealed by repetition effects

Stimulus processing in language and beyond is shaped by context, with predictability having a particularly well-attested influence on the rapid processes that unfold during the presentation of a word. But does predictability also have downstream consequences for the quality of the constructed representations? On the one hand, the ease of processing predictablewordsmight free up time or cognitive resources, allowing for relatively thorough processing of the input. On the other hand, predictabilitymight allowthe systemto run in a top-down “verificationmode”, at the expense of thorough stimulus processing. This electroencephalogram (EEG) study manipulated word predictability, which reduced N400 amplitude and inter-trial phase clustering (ITPC), and then probed the fate of the (un)predictable words in memory by presenting them again. More thorough processing of predictable words should increase repetition effects, whereas less thorough processing should decrease them. Repetition was reflected in N400 decreases, late positive complex (LPC) enhancements, and late alpha/beta band power decreases. Critically, prior predictability tended to reduce the repetition effect on the N400, suggesting less priming, and eliminated the repetition effect on the LPC, suggesting a lack of episodic recollection. These findings converge on a top-down verification account, on which the brain processes more predictable input less thoroughly. More generally, the results demonstrate that predictability hasmultifaceted downstreamconsequences beyond processing in the momen

Understanding language-elicited EEG data by predicting it from a fine-tuned language model

Electroencephalography (EEG) recordings of brain activity taken while participants read or listen to language are widely used within the cognitive neuroscience and psycholinguistics communities as a tool to study language comprehension. Several time-locked stereotyped EEG responses to word-presentations -- known collectively as event-related potentials (ERPs) -- are thought to be markers for semantic or syntactic processes that take place during comprehension. However, the characterization of each individual ERP in terms of what features of a stream of language trigger the response remains controversial. Improving this characterization would make ERPs a more useful tool for studying language comprehension. We take a step towards better understanding the ERPs by fine-tuning a language model to predict them. This new approach to analysis shows for the first time that all of the ERPs are predictable from embeddings of a stream of language. Prior work has only found two of the ERPs to be predictable. In addition to this analysis, we examine which ERPs benefit from sharing parameters during joint training. We find that two pairs of ERPs previously identified in the literature as being related to each other benefit from joint training, while several other pairs of ERPs that benefit from joint training are suggestive of potential relationships. Extensions of this analysis that further examine what kinds of information in the model embeddings relate to each ERP have the potential to elucidate the processes involved in human language comprehension.Comment: To appear in Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistic