fMRI evidence that left posterior temporal cortex contributes to N400 effects of predictability independent of congruity

Comprehensive investigation of predictive processing: A cross- and within-cognitive domains fMRI meta-analytic approach

Predictive processing (PP) stands as a predominant theoretical framework in neuroscience. While some efforts have been made to frame PP within a cognitive domain-general network perspective, suggesting the existence of a "prediction network," these studies have primarily focused on specific cognitive domains or functions. The question of whether a domain-general predictive network that encompasses all well-established cognitive domains exists remains unanswered. The present meta-analysis aims to address this gap by testing the hypothesis that PP relies on a large-scale network spanning across cognitive domains, supporting PP as a unified account toward a more integrated approach to neuroscience. The Activation Likelihood Estimation meta-analytic approach was employed, along with Meta-Analytic Connectivity Mapping, conjunction analysis, and behavioral decoding techniques. The analyses focused on prediction incongruency and prediction congruency, two conditions likely reflective of core phenomena of PP. Additionally, the analysis focused on a prediction phenomena-independent dimension, regardless of prediction incongruency and congruency. These analyses were first applied to each cognitive domain considered (cognitive control, attention, motor, language, social cognition). Then, all cognitive domains were collapsed into a single, cross-domain dimension, encompassing a total of 252 experiments. Results pertaining to prediction incongruency rely on a defined network across cognitive domains, while prediction congruency results exhibited less overall activation and slightly more variability across cognitive domains. The converging patterns of activation across prediction phenomena and cognitive domains highlight the role of several brain hubs unfolding within an organized large-scale network (Dynamic Prediction Network), mainly encompassing bilateral insula, frontal gyri, claustrum, parietal lobules, and temporal gyri. Additionally, the crucial role played at a cross-domain, multimodal level by the anterior insula, as evidenced by the conjunction and Meta-Analytic Connectivity Mapping analyses, places it as the major hub of the Dynamic Prediction Network. Results support the hypothesis that PP relies on a domain-general, large-scale network within whose regions PP units are likely to operate, depending on the context and environmental demands. The wide array of regions within the Dynamic Prediction Network seamlessly integrate context- and stimulus-dependent predictive computations, thereby contributing to the adaptive updating of the brain's models of the inner and external world.

Information entropy facilitates (not impedes) lexical processing during language comprehension

It is well known that contextual predictability facilitates word identification, but it is less clear whether the uncertainty associated with the current context (i.e., its lexical entropy) influences sentence processing. On the one hand, high entropy contexts may lead to interference due to greater number of lexical competitors. On the other hand, predicting multiple lexical competitors may facilitate processing through the preactivation of shared semantic features. In this study, we examined whether entropy measured at the trial level (i.e., for each participant, for each item) corresponds to facilitatory or inhibitory effects. Trial-level entropy captures each individual's knowledge about specific contexts and is therefore a more valid and sensitive measure of entropy (relative to the commonly employed item-level entropy). Participants (N = 112) completed two experimental sessions (with counterbalanced orders) that were separated by a 3- to 14-day interval. In one session, they produced up to 10 completions for sentence fragments (N = 647). In another session, they read the same sentences including a target word (whose entropy value was calculated based on the produced completions) while reading times were measured. We observed a facilitatory (not inhibitory) effect of trial-level entropy on lexical processing over and above item-level measures of lexical predictability (including cloze probability, surprisal, and semantic constraint). Extra analyses revealed that greater semantic overlap between the target and the produced responses facilitated target processing. Thus, the results lend support to theories of lexical prediction maintaining that prediction involves broad activation of semantic features rather than activation of full lexical forms.

Predictive Coding and Internal Error Correction in Speech Production

Speech production involves the careful orchestration of sophisticated systems, yet overt speech errors rarely occur under naturalistic conditions. The present functional magnetic resonance imaging study sought neural evidence for internal error detection and correction by leveraging a tongue twister paradigm that induces the potential for speech errors while excluding any overt errors from analysis. Previous work using the same paradigm in the context of silently articulated and imagined speech production tasks has demonstrated forward predictive signals in auditory cortex during speech and presented suggestive evidence of internal error correction in left posterior middle temporal gyrus (pMTG) on the basis that this area tended toward showing a stronger response when potential speech errors are biased toward nonwords compared to words (Okada et al., 2018). The present study built on this prior work by attempting to replicate the forward prediction and lexicality effects in nearly twice as many participants but introduced novel stimuli designed to further tax internal error correction and detection mechanisms by biasing speech errors toward taboo words. The forward prediction effect was replicated. While no evidence was found for a significant difference in brain response as a function of lexical status of the potential speech error, biasing potential errors toward taboo words elicited significantly greater response in left pMTG than biasing errors toward (neutral) words. Other brain areas showed preferential response for taboo words as well but responded below baseline and were less likely to reflect language processing as indicated by a decoding analysis, implicating left pMTG in internal error correction.

Spatiotemporal and sensory modality attention processing with domain-specific representations in frontoparietal areas

The frontoparietal network (FPN), including bilateral frontal eye field, inferior parietal sulcus, and supplementary motor area, has been linked to attention processing, including spatiotemporal and sensory modality domains. However, it is unclear whether FPN encodes representations of these domains that are generalizable across subdomains. We decomposed multivariate patterns of functional magnetic resonance imaging activity from 20 participants into domain-specific components and identified latent multivariate representations that generalized across subdomains. The 30 experimental conditions were organized into unimodal-bimodal and spatial-temporal models. We found that brain areas in the FPN, form the primary network that modulated during attention across domains. However, the activation patterns of areas within the FPN were reorganized according to the specific attentional demand, especially when pay attention to different sensory, suggesting distinct regional neural representations associated with specific attentional processes within FPN. In addition, there were also other domain-specific areas outside the FPN, such as the dorsolateral prefrontal cortex. Our conclusion is that, according to the results of the analysis of representation similarity, 2 types of activated brain regions, related to attention domain detailed information processing and general information processing, can be revealed.

Lexical Frequency and Sentence Context Influence the Brain's Response to Single Words

Typical adults read remarkably quickly. Such fast reading is facilitated by brain processes that are sensitive to both word frequency and contextual constraints. It is debated as to whether these attributes have additive or interactive effects on language processing in the brain. We investigated this issue by analysing existing magnetoencephalography data from 99 participants reading intact and scrambled sentences. Using a cross-validated model comparison scheme, we found that lexical frequency predicted the word-by-word elicited MEG signal in a widespread cortical network, irrespective of sentential context. In contrast, index (ordinal word position) was more strongly encoded in sentence words, in left front-temporal areas. This confirms that frequency influences word processing independently of predictability, and that contextual constraints affect word-by-word brain responses. With a conservative multiple comparisons correction, only the interaction between lexical frequency and surprisal survived, in anterior temporal and frontal cortex, and not between lexical frequency and entropy, nor between lexical frequency and index. However, interestingly, the uncorrected index × frequency interaction revealed an effect in left frontal and temporal cortex that reversed in time and space for intact compared to scrambled sentences. Finally, we provide evidence to suggest that, in sentences, lexical frequency and predictability may independently influence early (<150 ms) and late stages of word processing, but also interact during late stages of word processing (>150-250 ms), thus helping to converge previous contradictory eye-tracking and electrophysiological literature. Current neurocognitive models of reading would benefit from accounting for these differing effects of lexical frequency and predictability on different stages of word processing.

Differential contributions of left-hemispheric language regions to basic semantic composition

Semantic composition, the ability to combine single words to form complex meanings, is a core feature of human language. Despite growing interest in the basis of semantic composition, the neural correlates and the interaction of regions within this network remain a matter of debate. We designed a well-controlled two-word fMRI paradigm in which phrases only differed along the semantic dimension while keeping syntactic information alike. Healthy participants listened to meaningful ("fresh apple"), anomalous ("awake apple") and pseudoword phrases ("awake gufel") while performing an implicit and an explicit semantic task. We identified neural signatures for distinct processes during basic semantic composition. When lexical information is kept constant across conditions and the evaluation of phrasal plausibility is examined (meaningful vs. anomalous phrases), a small set of mostly left-hemispheric semantic regions, including the anterior part of the left angular gyrus, is found active. Conversely, when the load of lexical information-independently of phrasal plausibility-is varied (meaningful or anomalous vs. pseudoword phrases), conceptual combination involves a wide-spread left-hemispheric network comprising executive semantic control regions and general conceptual representation regions. Within this network, the functional coupling between the left anterior inferior frontal gyrus, the bilateral pre-supplementary motor area and the posterior angular gyrus specifically increases for meaningful phrases relative to pseudoword phrases. Stronger effects in the explicit task further suggest task-dependent neural recruitment. Overall, we provide a separation between distinct nodes of the semantic network, whose functional contributions depend on the type of compositional process under analysis.

Decoding the Real-Time Neurobiological Properties of Incremental Semantic Interpretation

Communication through spoken language is a central human capacity, involving a wide range of complex computations that incrementally interpret each word into meaningful sentences. However, surprisingly little is known about the spatiotemporal properties of the complex neurobiological systems that support these dynamic predictive and integrative computations. Here, we focus on prediction, a core incremental processing operation guiding the interpretation of each upcoming word with respect to its preceding context. To investigate the neurobiological basis of how semantic constraints change and evolve as each word in a sentence accumulates over time, in a spoken sentence comprehension study, we analyzed the multivariate patterns of neural activity recorded by source-localized electro/magnetoencephalography (EMEG), using computational models capturing semantic constraints derived from the prior context on each upcoming word. Our results provide insights into predictive operations subserved by different regions within a bi-hemispheric system, which over time generate, refine, and evaluate constraints on each word as it is heard.

Meaning to multiply: Electrophysiological evidence that children and adults treat multiplication facts differently

Multiplication tables are typically memorized verbally, with fluent retrieval leading to better performance in advanced math. Arithmetic development is characterized by strategy shifts from procedural operations to direct fact retrieval, which would not necessitate access to the facts' conceptual meaning. This study tested this hypothesis using a combination of event related brain potentials (ERP) and behavioral measures with 3rd-5th grade children and young adults. Participants verified the solutions to simple multiplication problems (2 × 3 = 6 or = 7) and the semantic fit of word-picture pairs, separately. Children showed an N400 effect to multiplication solutions with larger (more negative) amplitude for incorrect than correct solutions, reflecting meaning-level processing. A similar ERP response was observed in the word-picture verification task, with larger negative amplitude for word-picture pairs that were semantically mismatched compared to matched. In contrast, adults showed a P300 response for correct solutions, suggesting that they treated these solutions as potential targets in over-rehearsed mathematical expressions. This P300 response was specific to math fact processing, as the word-picture verification task elicited a classic N400 in adults. These ERP findings reveal an overlooked developmental transition that occurs after fifth grade, and speak to theories of arithmetic that have been based primarily on adult data.

Semantic Processing in Healthy Aging and Alzheimer's Disease: A Systematic Review of the N400 Differences

Semantic deficits are common in individuals with Alzheimer’s disease (AD). These deficits notably impact the ability to understand words. In healthy aging, semantic knowledge increases but semantic processing (i.e., the ability to use this knowledge) may be impaired. This systematic review aimed to investigate semantic processing in healthy aging and AD through behavioral responses and the N400 brain event-related potential. The results of the quantitative and qualitative analyses suggested an overall decrease in accuracy and increase in response times in healthy elderly as compared to young adults, as well as in individuals with AD as compared to age-matched controls. The influence of semantic association, as measured by N400 effect amplitudes, appears smaller in healthy aging and even more so in AD patients. Thus, semantic processing differences may occur in both healthy and pathological aging. The establishment of norms of healthy aging for these outcomes that vary between normal and pathological aging could eventually help early detection of AD.

Spatiotemporal dynamics of predictive brain mechanisms during speech processing: an MEG study

Rapid and efficient speech processing benefits from the prediction derived from prior expectations based on the identification of individual words. It is known that speech processing is carried out within a distributed frontotemporal network. However, the spatiotemporal causal dynamics of predictive brain mechanisms in sound-to-meaning mapping within this network remain unclear. Using magnetoencephalography, we adopted a semantic anomaly paradigm which consists of expected, unexpected and time-reversed Mandarin Chinese speech, and localized the effects of violated expectation in frontotemporal brain regions, the sensorimotor cortex and the supramarginal gyrus from 250 ms relative to the target words. By further investigating the causal cortical dynamics, we provided the description of the causal dynamic network within the framework of the dual stream model, and highlighted the importance of the connections within the ventral pathway, the top-down modulation from the left inferior frontal gyrus and the cross-stream integration during the speech processing of violated expectation.