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Mineroff, Z.

Publications and source records attributed to Mineroff, Z..

12 recordsLinked to original sources

Functional characterization of the language network of polyglots and hyperpolyglots with precision fMRI

How do polyglots--individuals who speak five or more languages--process their languages, and what can this population tell us about the language system? Using fMRI, we identified the language network in each of 34 polyglots (including 16 hyperpolyglots with knowledge of 10+ languages) and examined its response to the native language, non-native languages of varying proficiency, and unfamiliar languages. All language conditions engaged all areas of the language network relative to a control condition. Languages that participants rated as higher-proficiency elicited stronger responses, except for the native language, which elicited a similar or lower response than a non-native language of similar proficiency. Furthermore, unfamiliar languages that were typologically related to the participants high-to-moderate-proficiency languages elicited a stronger response than unfamiliar unrelated languages. The results suggest that the language networks response magnitude scales with the degree of engagement of linguistic computations (e.g., related to lexical access and syntactic-structure building). We also replicated a prior finding of weaker responses to native language in polyglots than non-polyglot bilinguals. These results contribute to our understanding of how multiple languages co-exist within a single brain and provide new evidence that the language network responds more strongly to stimuli that more fully engage linguistic computations.

neuroscience↗

LanA (Language Atlas): A probabilistic atlas for the language network based on fMRI data from >800 individuals

Two analytic traditions characterize fMRI language research. One relies on averaging activations voxel-wise across individuals. This approach has limitations: because of inter-individual variability in the locations of language areas, a location in a common brain space cannot be meaningfully linked to function. An alternative approach relies on identifying language areas in each individual using a functional localizer. Because of its greater sensitivity, functional resolution, and interpretability, functional localization is gaining popularity, but it is not always feasible, and cannot be applied retroactively to past studies. We provide a solution for bridging these currently disjoint approaches in the form of a probabilistic functional atlas created from fMRI data for an extensively validated language localizer in 806 individuals. This atlas enables estimating the probability that any given location in a common brain space belongs to the language network, and thus can help interpret group-level peaks and meta-analyses of such peaks, and lesion locations in patient investigations. More meaningful comparisons of findings across studies should increase robustness and replicability in language research.

neuroscience↗

The universal language network: A cross-linguistic investigation spanning 45 languages and 11 language families.

To understand the architecture of human language, it is critical to examine diverse languages; yet most cognitive neuroscience research has focused on a handful of primarily Indo-European languages. Here, we report an investigation of the fronto-temporo-parietal language network across 45 languages and establish the robustness to cross-linguistic variation of its topography and key functional properties, including left-lateralization, strong functional integration among its brain regions, and functional selectivity for language processing.

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Frontal language areas do not emerge in the absence of temporal language areas: A case study of an individual born without a left temporal lobe

Language relies on a left-lateralized fronto-temporal brain network. How this network emerges ontogenetically remains debated. We asked whether frontal language areas emerge in the absence of temporal language areas through a deep-data investigation of an individual (EG) born without her left temporal lobe. Using fMRI methods that have been validated to elicit reliable individual-level responses, we find that--as expected for early left hemisphere damage--EG has a fully functional language network in her right hemisphere (comparable to that in n=145 controls) and performs normally on language assessments. However, we detect no response to language in EGs left frontal lobe (replicated across two sessions, 3 years apart). Another network--the multiple demand network--is robustly present in frontal lobes bilaterally, suggesting that EGs left frontal cortex can support non-linguistic cognition. The existence of temporal language areas therefore appears to be a prerequisite for the emergence of the frontal language areas.

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Differential tracking of linguistic vs. mental state content in naturalistic stimuli by language and Theory of Mind (ToM) brain networks

Language and social cognition, especially the ability to reason about mental states, known as Theory of Mind (ToM), are deeply related in development and everyday use. However, whether these cognitive faculties rely on distinct, overlapping, or the same mechanisms remains debated. Some evidence suggests that, by adulthood, language and ToM draw on largely distinct--though plausibly interacting--cortical networks. However, the broad topography of these networks is similar, and some have emphasized the importance of social content / communicative intent in the linguistic signal for eliciting responses in the language areas. Here, we combine the power of individual-subjects functional localization with the naturalistic-cognition inter-subject correlation approach to illuminate the language-ToM relationship. Using fMRI, we recorded neural activity as participants (n=43) listened to stories and dialogs with mental state content (+linguistic, +ToM), viewed silent animations and live action films with mental state content but no language (-linguistic, +ToM), or listened to an expository text (+linguistic, -ToM). The ToM network robustly tracked stimuli rich in mental state information regardless of whether mental states were conveyed linguistically or non-linguistically, while tracking a +linguistic/-ToM stimulus only weakly. In contrast, the language network tracked linguistic stimuli more strongly than a) non-linguistic stimuli, and than b) the ToM network, and showed reliable tracking even for the linguistic condition devoid of mental state content. These findings suggest that in spite of their indisputably close links, language and ToM dissociate robustly in their neural substrates--and thus plausibly cognitive mechanisms--including during the processing of rich naturalistic materials.

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No evidence for a special role of language in feature-based categorization

The relationship between language and human thought is the subject of long-standing debate. One specific claim implicates language in feature-based categorization. According to this view, language resources facilitate object categorization based on a certain feature (e.g., color). Specifically, it is hypothesized that verbal labels help maintain focus on a relevant categorization criterion and reduce interference from irrelevant features. As a result, language impairment is expected to affect categorization of items grouped according to a single feature (low-dimensional categories, e.g., Things that are yellow), where many irrelevant features need to be inhibited, more than categorization of items that share many features (high-dimensional categories, e.g., Animals), where few irrelevant features need to be inhibited. In two behavioral studies with individuals with aphasia, we failed to find consistent support for the role of language in low-dimensional categorization. We also collected fMRI data from healthy adults and observed little activity in language-responsive brain regions during both low-dimensional and high-dimensional categorization. Combined, these results demonstrate that the language system is not implicated in object categorization. Our work adds to the growing evidence that, although language may assist in accessing task-relevant information (e.g., instructions), many cognitive tasks in adult brains proceed without recruiting the language system.

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Reduced language lateralization in autism and the broader autism phenotype as assessed with robust individual-subjects analyses

One of the few replicated functional brain differences between individuals with autism spectrum disorders (ASD) and neurotypical (NT) controls is reduced language lateralization. However, most prior reports relied on comparisons of group-level activation maps or functional markers that had not been validated at the individual-subject level, and/or used tasks that do not isolate language processing from other cognitive processes, complicating interpretation. Furthermore, few prior studies have examined functional responses in other functional networks, as needed to determine the selectivity of the effect. Using fMRI, we compared language lateralization between 28 ASD participants and carefully pairwise-matched controls, with the language regions defined individually with a well-validated language localizer. ASD participants showed less lateralized responses due to stronger right hemisphere activations. Further, this effect did not stem from a ubiquitous reduction in lateralization across the brain: ASD participants did not differ from controls in the lateralization of two other large-scale networks--the Theory of Mind network and the Multiple Demand network. Finally, in an exploratory study, we tested whether reduced language lateralization may also be present in NT individuals with high autistic trait load. Indeed, autistic trait load in a large set of NT participants (n=189) was associated with less lateralized language activations. These results suggest that reduced language lateralization is a robust and spatially selective neural marker of autism, present in individuals with ASD, but also in NT individuals with higher genetic liability for ASD, in line with a continuum model of underlying genetic risk.

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The language network is recruited but not required for non-verbal semantic processing

The ability to combine individual meanings into complex representations of the world is often associated with language. Yet people also construct combinatorial event-level representations from non-linguistic input, e.g. from visual scenes. Here, we test whether the language network in the human brain is involved in and necessary for semantic processing of nonverbal events. In Experiment 1, we scanned participants with fMRI while they performed a semantic plausibility judgment task vs. a difficult perceptual control task on sentences and line drawings that describe/depict simple agent-patient interactions. We found that the language network responded robustly during the semantic task but not during the perceptual control task. This effect was observed for both sentences and pictures (although the response to sentences was stronger). Thus, language regions in healthy adults are engaged during a semantic task performed on pictorial depictions of events. But is this engagement necessary? In Experiment 2, we tested two individuals with global aphasia, who have sustained massive damage to perisylvian language areas and display severe language difficulties, against a group of age-matched control participants. Individuals with aphasia were severely impaired on a task of matching sentences and pictures. However, they performed close to controls in assessing the plausibility of pictorial depictions of agent-patient interactions. Overall, our results indicate that the left fronto-temporal language network is recruited but not necessary for semantic processing of nonverbal events.

neuroscience↗

Word meanings and sentence structure recruit the same set of fronto-temporal regions during comprehension

To understand what you are reading now, your mind retrieves the meanings of words and constructions from a linguistic knowledge store (lexico-semantic processing) and identifies the relationships among them to construct a complex meaning (syntactic or combinatorial processing). Do these two sets of processes rely on distinct, specialized mechanisms or, rather, share a common pool of resources? Linguistic theorizing, empirical evidence from language acquisition and processing, and computational modeling have jointly painted a picture whereby lexico-semantic and syntactic processing are deeply inter-connected and perhaps not separable. In contrast, many current proposals of the neural architecture of language continue to endorse a view whereby certain brain regions selectively support syntactic/combinatorial processing, although the locus of such "syntactic hub", and its nature, vary across proposals. Here, we searched for selectivity for syntactic over lexico-semantic processing using a powerful individual-subjects fMRI approach across three sentence comprehension paradigms that have been used in prior work to argue for such selectivity: responses to lexico-semantic vs. morpho-syntactic violations (Experiment 1); recovery from neural suppression across pairs of sentences differing in only lexical items vs. only syntactic structure (Experiment 2); and same/different meaning judgments on such sentence pairs (Experiment 3). Across experiments, both lexico-semantic and syntactic conditions elicited robust responses throughout the left fronto-temporal language network. Critically, however, no regions were more strongly engaged by syntactic than lexico-semantic processing, although some regions showed the opposite pattern. Thus, contra many current proposals of the neural architecture of language, syntactic/combinatorial processing is not separable from lexico-semantic processing at the level of brain regions--or even voxel subsets--within the language network, in line with strong integration between these two processes that has been consistently observed in behavioral and computational language research. The results further suggest that the language network may be generally more strongly concerned with meaning than syntactic form, in line with the primary function of language--to share meanings across minds.

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High local mutual information drives the response in the human language network

The fronto-temporal language network responds robustly and selectively to sentences. But the features of linguistic input that drive this response and the computations these language areas support remain debated. Two key features of sentences are typically confounded in natural linguistic input: words in sentences a) are semantically and syntactically combinable into phrase- and clause-level meanings, and b) occur in an order licensed by the languages grammar. Inspired by recent psycholinguistic work establishing that language processing is robust to word order violations, we hypothesized that the core linguistic computation is composition, and, thus, can take place even when the word order violates the grammatical constraints of the language. This hypothesis predicts that a linguistic string should elicit a sentence-level response in the language network as long as the words in that string can enter into dependency relationships as in typical sentences. We tested this prediction across two fMRI experiments (total N=47) by introducing a varying number of local word swaps into naturalistic sentences, leading to progressively less syntactically well-formed strings. Critically, local dependency relationships were preserved because combinable words remained close to each other. As predicted, word order degradation did not decrease the magnitude of the BOLD response in the language network, except when combinable words were so far apart that composition among nearby words was highly unlikely. This finding demonstrates that composition is robust to word order violations, and that the language regions respond as strongly as they do to naturalistic linguistic input as long as composition can take place.

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An attempt to replicate a dissociation between syntax and semantics during sentence comprehension reported by Dapretto & Bookheimer (1999, Neuron)

Does processing the meanings of individual words vs. assembling words into phrases and sentences rely on distinct pools of cognitive and neural resources? Many have argued for such a dissociation, although the field is lacking a consensus on which brain region(s) support lexico-semantic vs. syntactic processing. Although some have also argued against such a dissociation, the dominant view in the field remains that distinct brain regions support these two fundamental components of language. One of the earlier and most cited pieces of evidence in favor of this dissociation comes from a paper by Dapretto & Bookheimer (1999, Neuron; DB). Using a sentence meaning comparison task, DB observed two distinct peaks within the left inferior frontal gyrus (LIFG): one more active when comparisons relied on lexico-semantic cues, and another - when they instead relied on syntactic cues. Although the paper has been highly cited over the years, no attempt has been made, to our knowledge, to replicate the original finding. We here report an fMRI study that attempts to do so. Using a combination of three approaches - whole-brain, group-level ROIs, and individual functional ROIs - we fail to replicate the originally reported dissociation. In particular, parts of the LIFG respond reliably more strongly during lexico-semantic than syntactic processing, but no part of the LIFG (including in the region defined around the peak reported by DB) shows the opposite response pattern. We hypothesize that the original result was a false positive, possibly driven by one participant or item given the use of a fixed-effects analysis and a small number of items (8 per condition) and participants (n=8).

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Multiple Demand (MD) system’s activity predicts individual differences in working memory and fluid intelligence

Numerous brain lesion and fMRI studies have linked individual differences in executive abilities and fluid intelligence to brain regions of the fronto-parietal "multiple-demand" (MD) network. Yet, fMRI studies have yielded conflicting evidence as to whether better executive abilities are associated with stronger or weaker MD activations and whether this relationship is restricted to the MD network. Here, in a large-sample (n=216) fMRI investigation, we found that stronger activity in MD regions - functionally defined in individual participants - was robustly associated with more accurate and faster responses on a spatial working memory task performed in the scanner, as well as fluid intelligence measured independently (n=114). In line with some prior claims about a relationship between language and fluid intelligence, we also found a weak association between activity in the brain regions of the left fronto-temporal language network during an independent passive reading task, and performance on the working memory task. However, controlling for the level of MD activity abolished this relationship, whereas the MD activity-behavior association remained highly reliable after controlling for the level of activity in the language network. Finally, we demonstrate how unreliable MD activity measures, coupled with small sample sizes, could falsely lead to the opposite, negative, association that has been reported in some prior studies. Taken together, these results demonstrate that a core component of individual differences variance in executive abilities and fluid intelligence is selectively and robustly positively associated with the level of activity in the MD network, a result that aligns well with lesion studies.

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