scholarly journals Expanding the language network: Domain-specific hippocampal recruitment during high-level linguistic processing

2016 ◽  
Author(s):  
Idan A. Blank ◽  
Melissa C. Duff ◽  
Sarah Brown-Schmidt ◽  
Evelina Fedorenko
Keyword(s):  
Language Processing ◽  
Language Comprehension ◽  
Memory Task ◽  
Brain Network ◽  
Healthy Adults ◽  
Hippocampal Damage ◽  
Story Comprehension ◽  
Linguistic Processing ◽  
Language Network ◽  
Relational Binding

AbstractLanguage processing requires us to encode linear relations between acoustic forms and map them onto hierarchical relations between meaning units. Such relational binding of linguistic elements might recruit the hippocampus given its engagement by similar operations in other cognitive domains. Historically, hippocampal engagement in online language use has received little attention because patients with hippocampal damage are not aphasic. However, recent studies have found that these patients exhibit language impairments when the demands on flexible relational binding are high, suggesting that the hippocampus does, in fact, contribute to linguistic processing. A fundamental question is thus whether language processing engages domain-general hippocampal mechanisms that are also recruited across other cognitive processes or whether, instead, it relies on certain language-selective areas within the hippocampus. To address this question, we conducted the first systematic analysis of hippocampal engagement during comprehension in healthy adults (n=150 across three experiments) using fMRI. Specifically, we functionally localized putative “language-regions” within the hippocampus using a language comprehension task, and found that these regions (i) were selectively engaged by language but not by six non-linguistic tasks; and (ii) were coupled in their activity with the cortical language network during both “rest” and especially story comprehension, but not with the domain-general “multiple-demand (MD)” network. This functional profile did not generalize to other hippocampal regions that were localized using a non-linguistic, working memory task. These findings suggest that some hippocampal mechanisms that maintain and integrate information during language comprehension are not domain-general but rather belong to the language-specific brain network.Significance statementAccording to popular views, language processing is exclusively supported by neocortical mechanisms. However, recent patient studies suggest that language processing may also require the hippocampus, especially when relations among linguistic elements have to be flexibly integrated and maintained. Here, we address a core question about the place of the hippocampus in the cognitive architecture of language: are certain hippocampal operations language-specific rather than domain-general? By extensively characterizing hippocampal recruitment during language comprehension in healthy adults using fMRI, we show that certain hippocampal subregions exhibit signatures of language specificity in both their response profiles and their patterns of activity synchronization with known functional regions in the neocortex. We thus suggest that the hippocampus is a satellite constituent of the language network.

Similarity of Computations Across Domains Does Not Imply Shared Implementation: The Case of Language Comprehension

2021 ◽  
Vol 30 (6) ◽  
pp. 526-534
Author(s):  
Evelina Fedorenko ◽  
Cory Shain
Keyword(s):  
Language Processing ◽  
Language Comprehension ◽  
Fluid Intelligence ◽  
Linguistic Knowledge ◽  
Domain Specific ◽  
Cognitive Operations ◽  
High Level ◽  
General Circuits ◽  
The Mind ◽  
Language Network

Understanding language requires applying cognitive operations (e.g., memory retrieval, prediction, structure building) that are relevant across many cognitive domains to specialized knowledge structures (e.g., a particular language’s lexicon and syntax). Are these computations carried out by domain-general circuits or by circuits that store domain-specific representations? Recent work has characterized the roles in language comprehension of the language network, which is selective for high-level language processing, and the multiple-demand (MD) network, which has been implicated in executive functions and linked to fluid intelligence and thus is a prime candidate for implementing computations that support information processing across domains. The language network responds robustly to diverse aspects of comprehension, but the MD network shows no sensitivity to linguistic variables. We therefore argue that the MD network does not play a core role in language comprehension and that past findings suggesting the contrary are likely due to methodological artifacts. Although future studies may reveal some aspects of language comprehension that require the MD network, evidence to date suggests that those will not be related to core linguistic processes such as lexical access or composition. The finding that the circuits that store linguistic knowledge carry out computations on those representations aligns with general arguments against the separation of memory and computation in the mind and brain.

scholarly journals Linguistic input drives brain network configuration during language comprehension

2020 ◽  
Author(s):  
Ileana Quiñones ◽  
Nicola Molinaro ◽  
César Caballero-Gaudes ◽  
Simona Mancini ◽  
Juan Andrés Hernández-Cabrera ◽  
...  
Keyword(s):  
Graph Theory ◽  
Language Processing ◽  
Language Comprehension ◽  
Sentence Comprehension ◽  
Experimental Manipulation ◽  
Brain Network ◽  
Angular Gyrus ◽  
Network Configuration ◽  
Linguistic Input ◽  
Gender Type

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.

scholarly journals The Role of the Primary Sensory Cortices in Early Language Processing

2017 ◽  
Vol 29 (10) ◽  
pp. 1755-1765 ◽  
Author(s):  
Andrew C. Papanicolaou ◽  
Marina Kilintari ◽  
Roozbeh Rezaie ◽  
Shalini Narayana ◽  
Abbas Babajani-Feremi
Keyword(s):  
Left Hemisphere ◽  
Language Processing ◽  
Stimulus Onset ◽  
Linguistic Processing ◽  
Feature Processing ◽  
Sensory Cortices ◽  
Linguistic Analyses ◽  
The Brain ◽  
Language Network

The results of this magnetoencephalography study challenge two long-standing assumptions regarding the brain mechanisms of language processing: First, that linguistic processing proper follows sensory feature processing effected by bilateral activation of the primary sensory cortices that lasts about 100 msec from stimulus onset. Second, that subsequent linguistic processing is effected by left hemisphere networks outside the primary sensory areas, including Broca's and Wernicke's association cortices. Here we present evidence that linguistic analysis begins almost synchronously with sensory, prelinguistic verbal input analysis and that the primary cortices are also engaged in these linguistic analyses and become, consequently, part of the left hemisphere language network during language tasks. These findings call for extensive revision of our conception of linguistic processing in the brain.

scholarly journals Developments in diffusion MRI and tractography to study language network alterations following very preterm birth

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 240
Author(s):  
Piergiorgio Salvan ◽  
Chiara Nosarti
Keyword(s):  
Preterm Birth ◽  
Language Processing ◽  
Large Scale ◽  
Structural Connectivity ◽  
Brain Network ◽  
Very Preterm ◽  
Very Preterm Birth ◽  
Technological Advances ◽  
Language Network

Language is key for human interactions and relies on a well-known set of brain cortical areas linked by large-scale white-matter fasciculi. However, very little is known about the ontogeny of the language network, how it is affected by very preterm birth, or how structural connectivity profiles observable before language acquisition may predispose distinct computational mechanisms associated with later language processing. Recent advances in diffusion-weighted magnetic resonance imaging and tractography are allowing researchers to provide novel, insightful understanding of the human language brain network through in vivo non-invasive investigations across the whole lifespan. Here, we propose a commentary on a series of papers which aimed to summarise the latest technological advances in neuroimaging research in order to provide future directions to study language development following very preterm birth.

scholarly journals Frequency-specific directed interactions in the human brain network for language

2017 ◽  
Vol 114 (30) ◽  
pp. 8083-8088 ◽  
Author(s):  
Jan-Mathijs Schoffelen ◽  
Annika Hultén ◽  
Nietzsche Lam ◽  
André F. Marquand ◽  
Julia Uddén ◽  
...  
Keyword(s):  
Language Processing ◽  
Brain Regions ◽  
Brain Network ◽  
Causality Analysis ◽  
Linguistic Processing ◽  
Functional Topology ◽  
Using Data ◽  
Beta Frequency ◽  
Bidirectional Interactions

The brain’s remarkable capacity for language requires bidirectional interactions between functionally specialized brain regions. We used magnetoencephalography to investigate interregional interactions in the brain network for language while 102 participants were reading sentences. Using Granger causality analysis, we identified inferior frontal cortex and anterior temporal regions to receive widespread input and middle temporal regions to send widespread output. This fits well with the notion that these regions play a central role in language processing. Characterization of the functional topology of this network, using data-driven matrix factorization, which allowed for partitioning into a set of subnetworks, revealed directed connections at distinct frequencies of interaction. Connections originating from temporal regions peaked at alpha frequency, whereas connections originating from frontal and parietal regions peaked at beta frequency. These findings indicate that the information flow between language-relevant brain areas, which is required for linguistic processing, may depend on the contributions of distinct brain rhythms.

scholarly journals Functionally distinct language and Theory of Mind networks are synchronized at rest and during language comprehension

2019 ◽  
Vol 121 (4) ◽  
pp. 1244-1265 ◽  
Author(s):  
Alexander M. Paunov ◽  
Idan A. Blank ◽  
Evelina Fedorenko
Keyword(s):  
Theory Of Mind ◽  
Functional Mri ◽  
Language Processing ◽  
Language Comprehension ◽  
Mental States ◽  
Brain Regions ◽  
Blood Oxygenation ◽  
Social Reasoning ◽  
Story Comprehension ◽  
Dependent Signal

Communication requires the abilities to generate and interpret utterances and to infer the beliefs, desires, and goals of others (“Theory of Mind”; ToM). These two abilities have been shown to dissociate: individuals with aphasia retain the ability to think about others’ mental states; and individuals with autism are impaired in social reasoning, but their basic language processing is often intact. In line with this evidence from brain disorders, functional MRI (fMRI) studies have shown that linguistic and ToM abilities recruit distinct sets of brain regions. And yet, language is a social tool that allows us to share thoughts with one another. Thus, the language and ToM brain networks must share information despite being implemented in distinct neural circuits. Here, we investigated potential interactions between these networks during naturalistic cognition using functional correlations in fMRI. The networks were functionally defined in individual participants, in terms of preference for sentences over nonwords for language, and for belief inference over physical-event processing for ToM, with both a verbal and a nonverbal paradigm. Although, across experiments, interregion correlations within each network were higher than between-network correlations, we also observed above-baseline synchronization of blood oxygenation level-dependent signal fluctuations between the two networks during rest and story comprehension. This synchronization was functionally specific: neither network was synchronized with the executive control network (functionally defined in terms of preference for a harder over easier version of an executive task). Thus, coordination between the language and ToM networks appears to be an inherent and specific characteristic of their functional architecture.NEW & NOTEWORTHY Humans differ from nonhuman primates in their abilities to communicate linguistically and to infer others’ mental states. Although linguistic and social abilities appear to be interlinked onto- and phylogenetically, they are dissociated in the adult human brain. Yet successful communication requires language and social reasoning to work in concert. Using functional MRI, we show that language regions are synchronized with social regions during rest and language comprehension, pointing to a possible mechanism for internetwork interaction.

scholarly journals Domain-general brain regions do not track linguistic input as closely as language-selective regions

2016 ◽  
Author(s):  
Idan Blank ◽  
Evelina Fedorenko
Keyword(s):  
Language Comprehension ◽  
Brain Regions ◽  
Cognitive Effort ◽  
Network Activity ◽  
Story Comprehension ◽  
Linguistic Features ◽  
Wide Range ◽  
Linguistic Input ◽  
Time Courses ◽  
Language Network

AbstractLanguage comprehension engages a cortical network of left frontal and temporal regions. Activity in this network is language-selective, showing virtually no modulation by non-linguistic tasks. In addition, language comprehension engages a second network consisting of bilateral frontal, parietal, cingulate, and insular regions. Activity in this “Multiple Demand (MD)” network scales with comprehension difficulty, but also with cognitive effort across a wide range of non-linguistic tasks in a domain-general fashion. Given the functional dissociation between the language and MD networks, their respective contributions to comprehension are likely distinct, yet such differences remain elusive. Critically, given that each network is sensitive to some linguistic features, prior research has assumed – implicitly or explicitly – that both networks track linguistic input closely, and in a manner consistent across individuals. Here, we used fMRI to directly test this assumption by comparing the BOLD signal time-courses in each network across different people listening to the same story. Language network activity showed fewer individual differences, indicative of closer input tracking, whereas MD network activity was more idiosyncratic and, moreover, showed lower reliability within an individual across repetitions of a story. These findings constrain cognitive models of language comprehension by suggesting a novel distinction between the processes implemented in the language and MD networks.Significance StatementLanguage comprehension recruits both language-specific mechanisms and domain-general mechanisms that are engaged in many cognitive processes. In the human cortex, language-selective mechanisms are implemented in the left-lateralized “core language network”, whereas domain-general mechanisms are implemented in the bilateral “Multiple Demand (MD)” network. Here, we report the first direct comparison of the respective contributions of these networks to naturalistic story comprehension. Using a novel combination of neuroimaging approaches we find that MD regions track stories less closely than language regions. This finding constrains the possible contributions of the MD network to comprehension, contrasts with accounts positing that this network has continuous access to linguistic input, and suggests a new typology of comprehension processes based on their extent of input tracking.

scholarly journals Reduced Left Lateralization of Language in Congenitally Blind Individuals

2017 ◽  
Vol 29 (1) ◽  
pp. 65-78 ◽  
Author(s):  
Connor Lane ◽  
Shipra Kanjlia ◽  
Hilary Richardson ◽  
Anne Fulton ◽  
Akira Omaki ◽  
...  
Keyword(s):  
Language Processing ◽  
Reading Ability ◽  
Sentence Comprehension ◽  
Memory Task ◽  
Developmental Factors ◽  
Two Samples ◽  
Congenitally Blind ◽  
Cortical Regions ◽  
Blind Individuals ◽  
Language Network

Language processing depends on a left-lateralized network of frontotemporal cortical regions. This network is remarkably consistent across individuals and cultures. However, there is also evidence that developmental factors, such as delayed exposure to language, can modify this network. Recently, it has been found that, in congenitally blind individuals, the typical frontotemporal language network expands to include parts of “visual” cortices. Here, we report that blindness is also associated with reduced left lateralization in frontotemporal language areas. We analyzed fMRI data from two samples of congenitally blind adults (n = 19 and n = 13) and one sample of congenitally blind children (n = 20). Laterality indices were computed for sentence comprehension relative to three different control conditions: solving math equations (Experiment 1), a memory task with nonwords (Experiment 2), and a “does this come next?” task with music (Experiment 3). Across experiments and participant samples, the frontotemporal language network was less left-lateralized in congenitally blind than in sighted individuals. Reduction in left lateralization was not related to Braille reading ability or amount of occipital plasticity. Notably, we observed a positive correlation between the lateralization of frontotemporal cortex and that of language-responsive occipital areas in blind individuals. Blind individuals with right-lateralized language responses in frontotemporal cortices also had right-lateralized occipital responses to language. Together, these results reveal a modified neurobiology of language in blindness. Our findings suggest that, despite its usual consistency across people, the neurobiology of language can be modified by nonlinguistic experiences.

The Opposition of Surprisal and Semantic Similarity in the Prediction of Language Processing: Evidence from Eye-tracking Data

2020 ◽  
Author(s):  
Kun Sun
Keyword(s):  
Eye Tracking ◽  
Semantic Similarity ◽  
Cognitive Processing ◽  
Language Processing ◽  
Language Comprehension ◽  
Word Processing ◽  
Reading Time ◽  
Computational Models ◽  
Tracking Data ◽  
Dynamic Approach

Expectations or predictions about upcoming content play an important role during language comprehension and processing. One important aspect of recent studies of language comprehension and processing concerns the estimation of the upcoming words in a sentence or discourse. Many studies have used eye-tracking data to explore computational and cognitive models for contextual word predictions and word processing. Eye-tracking data has previously been widely explored with a view to investigating the factors that influence word prediction. However, these studies are problematic on several levels, including the stimuli, corpora, statistical tools they applied. Although various computational models have been proposed for simulating contextual word predictions, past studies usually preferred to use a single computational model. The disadvantage of this is that it often cannot give an adequate account of cognitive processing in language comprehension. To avoid these problems, this study draws upon a massive natural and coherent discourse as stimuli in collecting the data on reading time. This study trains two state-of-art computational models (surprisal and semantic (dis)similarity from word vectors by linear discriminative learning (LDL)), measuring knowledge of both the syntagmatic and paradigmatic structure of language. We develop a `dynamic approach' to compute semantic (dis)similarity. It is the first time that these two computational models have been merged. Models are evaluated using advanced statistical methods. Meanwhile, in order to test the efficiency of our approach, one recently developed cosine method of computing semantic (dis)similarity based on word vectors data adopted is used to compare with our `dynamic' approach. The two computational and fixed-effect statistical models can be used to cross-verify the findings, thus ensuring that the result is reliable. All results support that surprisal and semantic similarity are opposed in the prediction of the reading time of words although both can make good predictions. Additionally, our `dynamic' approach performs better than the popular cosine method. The findings of this study are therefore of significance with regard to acquiring a better understanding how humans process words in a real-world context and how they make predictions in language cognition and processing.

scholarly journals Listener’s personality traits predict changes in pupil size during auditory language comprehension

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Isabell Hubert Lyall ◽  
Juhani Järvikivi
Keyword(s):  
Personality Traits ◽  
Language Processing ◽  
Language Comprehension ◽  
Pupil Size ◽  
Pupil Dilation ◽  
Systematic Research ◽  
Cognitive Resources ◽  
Personality Profiles ◽  
Pupillary Responses ◽  
Grammatical Errors

AbstractResearch suggests that listeners’ comprehension of spoken language is concurrently affected by linguistic and non-linguistic factors, including individual difference factors. However, there is no systematic research on whether general personality traits affect language processing. We correlated 88 native English-speaking participants’ Big-5 traits with their pupillary responses to spoken sentences that included grammatical errors, "He frequently have burgers for dinner"; semantic anomalies, "Dogs sometimes chase teas"; and statements incongruent with gender stereotyped expectations, such as "I sometimes buy my bras at Hudson's Bay", spoken by a male speaker. Generalized additive mixed models showed that the listener's Openness, Extraversion, Agreeableness, and Neuroticism traits modulated resource allocation to the three different types of unexpected stimuli. No personality trait affected changes in pupil size across the board: less open participants showed greater pupil dilation when processing sentences with grammatical errors; and more introverted listeners showed greater pupil dilation in response to both semantic anomalies and socio-cultural clashes. Our study is the first one demonstrating that personality traits systematically modulate listeners’ online language processing. Our results suggest that individuals with different personality profiles exhibit different patterns of the allocation of cognitive resources during real-time language comprehension.

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