scholarly journals The domain-general multiple demand (MD) network does not support core aspects of language comprehension: a large-scale fMRI investigation

2019 ◽  
Author(s):  
Evgeniia Diachek ◽  
Idan Blank ◽  
Matthew Siegelman ◽  
Josef Affourtit ◽  
Evelina Fedorenko

AbstractAside from the language-selective left-lateralized fronto-temporal network, language comprehension sometimes additionally recruits a domain-general bilateral fronto-parietal network implicated in executive functions: the multiple demand (MD) network. However, the nature of the MD network’s contributions to language comprehension remains debated. To illuminate the role of this network in language processing, we conducted a large-scale fMRI investigation using data from 30 diverse word and sentence comprehension experiments (481 unique participants, 678 scanning sessions). In line with prior findings, the MD network was active during many language tasks. Moreover, similar to the language-selective network, which is robustly lateralized to the left hemisphere, these responses were stronger in the left-hemisphere MD regions. However, in stark contrast with the language-selective network, the MD network responded more strongly (i) to lists of unconnected words than to sentences, and critically, (ii) in paradigms with an explicit task compared to passive comprehension paradigms. In fact, many passive comprehension tasks failed to elicit a response above the fixation baseline in the MD network, in contrast to strong responses in the language-selective network. In tandem, these results argue against a role for the MD network in core aspects of sentence comprehension like inhibiting irrelevant meanings or parses, keeping intermediate representations active in working memory, or predicting upcoming words or structures. These results align with recent evidence of relatively poor tracking of the linguistic signal by the MD regions during naturalistic comprehension, and instead suggest that the MD network’s engagement during language processing likely reflects effort associated with extraneous task demands.Significance StatementDomain-general executive processes, like working memory and cognitive control, have long been implicated in language comprehension, including in neuroimaging studies that have reported activation in domain-general multiple demand (MD) regions for linguistic manipulations. However, much prior evidence has come from paradigms where language interpretation is accompanied by extraneous tasks. Using a large fMRI dataset (30 experiments/481 participants/678 sessions), we demonstrate that MD regions are engaged during language comprehension in the presence of task demands, but not during passive reading/listening—conditions that strongly activate the fronto-temporal language network. These results present a fundamental challenge to proposals whereby linguistic computations, like inhibiting irrelevant meanings, keeping representations active in working memory, or predicting upcoming elements, draw on domain-general executive resources.

Author(s):  
Bora Eom ◽  
Jee Eun Sung

Purpose This study investigated whether sentence repetition–based working-memory (SR-WM) treatment increased sentence-repetition abilities and the treatment effects generalized to sentence-comprehension abilities, WM-span tasks, and general language-assessment tasks. Method Six individuals with aphasia participated in the study. The treatment consisted of 12 sessions of approximately 1 hr per day, 3 times per week. The SR-WM treatment protocol followed components including maintenance and computation of linguistic units by facilitating a chunking strategy. We manipulated the length and syntactic structures of the sentence-repetition stimuli using a limited set of vocabulary. Results Participants demonstrated significant increased repetition ability in treated and untreated sentences after treatment. Furthermore, they showed generalization effects on the sentence-comprehension task, WM measures, and general language tasks, but with some differential patterns, depending on task demands. Conclusions The SR-WM treatment approach, by manipulating syntactic structures and minimizing top-down semantic processing, elicited increased performance on sentence repetition as well as other linguistic domains. Results indicated that it is clinically and theoretically important to examine whether WM treatment serves as a potentially underlying treatment approach that facilitates the distributed network associated with language processing.


This handbook reviews the current state of the art in the field of psycholinguistics. Part I deals with language comprehension at the sublexical, lexical, and sentence and discourse levels. It explores concepts of speech representation and the search for universal speech segmentation mechanisms against a background of linguistic diversity and compares first language with second language segmentation. It also discusses visual word recognition, lexico-semantics, the different forms of lexical ambiguity, sentence comprehension, text comprehension, and language in deaf populations. Part II focuses on language production, with chapters covering topics such as word production and related processes based on evidence from aphasia, the major debates surrounding grammatical encoding. Part III considers various aspects of interaction and communication, including the role of gesture in language processing, approaches to the study of perspective-taking, and the interrelationships between language comprehension, emotion, and sociality. Part IV is concerned with language development and evolution, focusing on topics ranging from the development of prosodic phonology, the neurobiology of artificial grammar learning, and developmental dyslexia. The book concludes with Part V, which looks at methodological advances in psycholinguistic research, such as the use of intracranial electrophysiology in the area of language processing.


Author(s):  
Megan C. Fitzhugh ◽  
Arianna N. LaCroix ◽  
Corianne Rogalsky

Purpose Sentence comprehension deficits are common following a left hemisphere stroke and have primarily been investigated under optimal listening conditions. However, ample work in neurotypical controls indicates that background noise affects sentence comprehension and the cognitive resources it engages. The purpose of this study was to examine how background noise affects sentence comprehension poststroke using both energetic and informational maskers. We further sought to identify whether sentence comprehension in noise abilities are related to poststroke cognitive abilities, specifically working memory and/or attentional control. Method Twenty persons with chronic left hemisphere stroke completed a sentence–picture matching task where they listened to sentences presented in three types of maskers: multispeakers, broadband noise, and silence (control condition). Working memory, attentional control, and hearing thresholds were also assessed. Results A repeated-measures analysis of variance identified participants to have the greatest difficulty with the multispeakers condition, followed by broadband noise and then silence. Regression analyses, after controlling for age and hearing ability, identified working memory as a significant predictor of listening engagement (i.e., mean reaction time) in broadband noise and multispeakers and attentional control as a significant predictor of informational masking effects (computed as a reaction time difference score where broadband noise is subtracted from multispeakers). Conclusions The results from this study indicate that background noise impacts sentence comprehension abilities poststroke and that these difficulties may arise due to deficits in the cognitive resources supporting sentence comprehension and not other factors such as age or hearing. These findings also highlight a relationship between working memory abilities and sentence comprehension in background noise. We further suggest that attentional control abilities contribute to sentence comprehension by supporting the additional demands associated with informational masking. Supplemental Material https://doi.org/10.23641/asha.14984511


2020 ◽  
Author(s):  
Ileana Quiñones ◽  
Nicola Molinaro ◽  
César Caballero-Gaudes ◽  
Simona Mancini ◽  
Juan Andrés Hernández-Cabrera ◽  
...  

AbstractAssessing the synchrony and interplay between distributed neural regions is critical to understanding how language is processed. Here, we investigated possible neuro-functional links between form and meaning during sentence comprehension combining a classical whole-brain approach, which characterizes patterns of brain activation resulting from our experimental manipulation, and a novel multivariate network-based approach, which uses graph-theory measures to unravel the architectural configuration of the language system. Capitalizing on the Spanish gender agreement system, we experimentally manipulated formal and conceptual factors: whether the noun-adjective grammatical gender relationship was congruent or not and whether the noun gender type was semantically informative or strictly formal. Left inferior and middle frontal gyri, as well as left MTG/STG emerged as critical areas for the computation of grammatical relations. We demonstrate how the interface between formal and conceptual features depends on the synergic articulation of brain areas divided in three subnetworks that extend beyond the classical left-lateralized perisylvian language circuit. Critically, we isolated a subregion of the left angular gyrus showing a significant interaction between gender congruency and gender type. The functional interplay between the angular gyrus and left perisylvian language-specific circuit proves crucial for constructing coherent and meaningful messages. Importantly, using graph theory we show that this complex system is functionally malleable: the role each node plays within the network changes depending on the available linguistic cues.Significance StatementNeural networks can be described as graphs comprising distributed and interconnected nodes. These nodes share functional properties but also differ in terms of functional specialization and the number of interconnections mediating the efficient transfer of information. Previous work has shown functional connectivity differences based on graph-theory properties between typical and atypical samples. However, here we have used concepts from graph theory to characterize connectivity during language processing using task-related fMRI. This approach allowed us to demonstrate how linguistic input drives brain network configuration during language comprehension. This is the first evidence of functional flexibility in language networks: the communicative capacity of each hub changes depending on whether the linguistic input grants access to meaning or is purely formal.


2021 ◽  
Author(s):  
Samuel El Bouzaïdi Tiali ◽  
Anna Borne ◽  
Lucile Meunier ◽  
Monica Bolocan ◽  
Monica Baciu ◽  
...  

Purpose: Canonical sentence structures are the most frequently used in a given language. Less frequent or non-canonical sentences tend to be more challenging to process and to induce a higher cognitive load. To deal with this complexity several authors suggest that not only linguistic but also non-linguistic (domain-general) mechanisms are involved. In this study, we were interested in evaluating the relationship between non-canonical oral sentence comprehension and individual cognitive control abilities.Method: Participants were instructed to perform a sentence-picture verification task with canonical and non-canonical sentences. Sentence structures (i.e., active or passive) and sentence types (i.e., affirmative or negative) were manipulated. Furthermore, each participant performed four cognitive control tasks measuring inhibitory processes, updating in working memory, flexibility and sustained attention. We hypothesized that more complex sentence structures would induce a cognitive cost reflecting involvement of additional processes, and also that this additional cost should be related with cognitive control performances.Results: Results showed better performances for canonical sentences compared to non-canonical ones supporting previous work on passive and negative sentence processing. Correlation results suggest a close relationship between cognitive control mechanisms and non-canonical sentence processing.Conclusion: This study adds evidence for the hypothesis of a domain-general mechanism implication during oral language comprehension and highlights the importance of taking task demands into consideration when exploring language comprehension mechanisms.


2019 ◽  
Vol 56 (4) ◽  
pp. 557-580 ◽  
Author(s):  
Sebastian Gabel ◽  
Daniel Guhl ◽  
Daniel Klapper

The authors propose a new, exploratory approach for analyzing market structures that leverages two recent methodological advances in natural language processing and machine learning. They customize a neural network language model to derive latent product attributes by analyzing the co-occurrences of products in shopping baskets. Applying dimensionality reduction to the latent attributes yields a two-dimensional product map. This method is well-suited to retailers because it relies on data that are readily available from their checkout systems and facilitates their analyses of cross-category product complementarity, in addition to within-category substitution. The approach has high usability because it is automated, is scalable and does not require a priori assumptions. Its results are easy to interpret and update as new market basket data are collected. The authors validate their approach both by conducting an extensive simulation study and by comparing their results with those of state-of-the-art, econometric methods for modeling product relationships. The application of this approach using data collected at a leading German grocery retailer underlines its usefulness and provides novel findings that are relevant to assortment-related decisions.


2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Mianisha C. Finney ◽  
James W. Montgomery ◽  
Ronald B. Gillam ◽  
Julia L. Evans

The present study evaluated a two-mechanism memory model of the online auditory comprehension of object relative (OR) sentences in 7–11-year-old typically developing children. Mechanisms of interest included working memory storage (WMS) and attention focus switching. We predicted that both mechanisms would be important for comprehension. Forty-four children completed a listening span task indexing WMS, an auditory attention focus switching task, and an agent selection task indexing spoken sentence comprehension. Regression analyses indicated that WMS and attention focus switching accuracy each accounted for significant and unique variance in the children’s OR comprehension after accounting for age. Results were interpreted to suggest that WMS is important for OR comprehension by supporting children’s ability to retain both noun phrase 1 and noun phrase 2 prior to their reactivating noun phrase 1 from memory in order to integrate it into a developing structure. Attention focus switching was interpreted to be critical in supporting children’s noun phrase 1 reactivation, as they needed to switch their focus of attention momentarily away from ongoing language processing to memory retrieval.


2020 ◽  
Vol 29 (6) ◽  
pp. 575-582
Author(s):  
Kara D. Federmeier ◽  
Suzanne R. Jongman ◽  
Jakub M. Szewczyk

When we use language, we combine sounds, signs, and letters into words that then form sentences, which together tell a story. Both language production and language comprehension rely on representations that need to be continuously and rapidly activated, selected, and combined. These representations are specific to language, but many processes that regulate their use, such as inhibition of competitors or updating of working memory, are domain-general abilities that apply across different kinds of tasks. Here, we provide an overview of the behavioral and neurophysiological evidence for domain-general abilities underpinning language skills and describe which aspects of production and comprehension draw on such cognitive resources. We discuss how this line of research reveals important similarities between production and comprehension and also helps establish links between language and other cognitive domains. Finally, we argue that studying how domain-general abilities are used in language leads to important insights into the highly dynamic communication between brain networks that is necessary to successfully go from sounds to stories.


2021 ◽  
pp. 096372142199517
Author(s):  
Randi C. Martin

Although research on the role of verbal working memory (WM) in language processing has focused on phonological maintenance, considerable evidence indicates that the maintenance of semantic information plays a more critical role. This article reviews studies of brain-damaged and healthy individuals demonstrating the contribution of semantic WM to language processing. On the sentence-comprehension side, semantic WM supports the retention of individual word meanings prior to their integration. It also serves to maintain semantic information in an activated state such that semantic interference between sentence constituents can be resolved. Phonological WM does not appear to support either of these functions, though it contributes to verbatim sentence recall. On the production side, evidence points to the phrase as the minimal scope of advance planning in sentence formulation, and to semantic WM as supporting the representation of the meanings of the content words within a phrase. Planning at the phonological level appears to have a very limited scope, making few demands on phonological WM. These findings imply that treatment of semantic but not phonological WM deficits should lead to improved sentence comprehension and production, and preliminary findings support that view.


2021 ◽  
Author(s):  
Cory Shain ◽  
Idan A. Blank ◽  
Evelina Fedorenko ◽  
Edward Gibson ◽  
William Schuler

AbstractA standard view of human language processing is that comprehenders build richly structured mental representations of natural language utterances, word by word, using computationally costly memory operations supported by domain-general working memory resources. However, three core claims of this view have been questioned, with some prior work arguing that (1) rich word-by-word structure building is not a core function of the language comprehension system, (2) apparent working memory costs are underlyingly driven by word predictability (surprisal), and/or (3) language comprehension relies primarily on domain-general rather than domain-specific working memory resources. In this work, we simultaneously evaluate all three of these claims using naturalistic comprehension in fMRI. In each participant, we functionally localize (a) a language-selective network and (b) a ‘multiple-demand’ network that supports working memory across domains, and we analyze the responses in these two networks of interest during naturalistic story listening with respect to a range of theory-driven predictors of working memory demand under rigorous surprisal controls. Results show robust surprisal-independent effects of word-by-word memory demand in the language network and no effect of working memory demand in the multiple demand network. Our findings thus support the view that language comprehension (1) entails word-by-word structure building using (2) computationally intensive memory operations that are not explained by surprisal. However, these results challenge (3) the domain-generality of the resources that support these operations, instead indicating that working memory operations for language comprehension are carried out by the same neural resources that store linguistic knowledge.Significance StatementThis study uses fMRI to investigate signatures of working memory (WM) demand during naturalistic story listening, using a broad range of theoretically motivated estimates of WM demand. Results support a strong effect of WM demand in language-selective brain regions but no effect of WM demand in “multiple demand” regions that have previously been associated with WM in non-linguistic domains. We further show evidence that WM effects in language regions are distinct from effects of word predictability. Our findings support a core role for WM in incremental language processing, using WM resources that are specialized for language.


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