Biology subjects

Blank, I.

Publications and source records attributed to Blank, I..

10 recordsLinked to original sources

bioRxiv2024

The language network ages well: Preserved selectivity, lateralization, and within-network functional synchronization in older brains

Healthy aging is associated with structural and functional brain changes. However, cognitive abilities vary in how they change with age: whereas executive functions, like working memory, show age-related decline, aspects of linguistic processing remain relatively preserved. The heterogeneity of the cognitive-behavioral landscape in aging predicts differences among brain networks in whether and how they should change with age. To evaluate this prediction, we used individual-subject fMRI analyses (precision fMRI) to examine the language-selective network and--for control purposes--the Multiple Demand (MD) network, which supports executive functions, in older adults (n=64) relative to young controls (n=483). In line with past claims, relative to young adults, the MD network of older adults shows weaker, less spatially extensive, and more topographically variable activations during an executive function task and reduced within-network functional connectivity. However, in stark contrast to the MD network, we find remarkable preservation of the language network in older adults. Their language network responds during language comprehension as strongly and selectively as in younger adults, and shows a similar degree of left-hemispheric lateralization and within-network functional connectivity. Our findings suggest that the language network remains young-like--at least on standard measures of function and connectivity--and align with behavioral preservation of language comprehension in healthy aging.

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bioRxiv2023

Functional identification of language-responsive channels in individual participants in MEG investigations

Making meaningful inferences about the functional architecture of the language system requires the ability to refer to the same neural units across individuals and studies. Traditional brain imaging approaches align and average brains together in a common space. However, lateral frontal and temporal cortices, where the language system resides, is characterized by high structural and functional inter-individual variability, which reduces the sensitivity and functional resolution of group-averaging analyses. This issue is compounded by the fact that language areas lay in close proximity to regions of other large-scale networks with different functional profiles. A solution inspired by visual neuroscience is to identify language areas functionally in each individual brain using a localizer task (e.g., a language comprehension task). This approach has proven productive in fMRI, yielding a number of robust and replicable findings about the language system. Here, we extend this approach to MEG. Across two experiments (one in Dutch speakers, n=19; one in English speakers, n=23), we examined neural responses to the processing of sentences and a control condition (nonword sequences). In both the time and frequency domains, we demonstrated that the topography of neural responses to language is spatially stable within individuals but varies across individuals. Consequently, analyses that take this inter-individual variability into account are characterized by greater sensitivity, compared to the group-level analyses. In summary, similar to fMRI, functional identification within individuals yields benefits in MEG, thus opening the door to future investigations of language processing including questions where whole-brain coverage and temporal resolution are both critical.

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bioRxiv2022

Non-literal language processing is jointly supported by the language and Theory of Mind networks: Evidence from a novel meta-analytic fMRI approach

Going beyond the literal meaning of utterances is key to communicative success. However, the mechanisms that support non-literal inferences remain debated. Using a novel meta-analytic approach, we evaluate the contribution of linguistic, social-cognitive, and executive mechanisms to non-literal interpretation. We identified 74 fMRI experiments (n=1,430 participants) from 2001-2021 that contrasted non-literal language comprehension with a literal control condition, spanning ten phenomena (e.g., metaphor, irony, indirect speech). Applying the activation likelihood estimation approach to the 825 activation peaks yielded six left-lateralized clusters. We then evaluated the locations of both the individual-study peaks and the clusters against probabilistic functional atlases (cf. macroanatomy, as is typically done) for three candidate brain networks--the language-selective network (Fedorenko et al., 2011), which supports language processing, the Theory of Mind (ToM) network (Saxe & Kanwisher, 2003), which supports social inferences, and the domain-general Multiple-Demand (MD) network (Duncan, 2010), which supports executive control. These atlases were created by overlaying individual activation maps of participants who performed robust and extensively validated localizer tasks that target each network in question (n=806 for language; n=198 for ToM; n=691 for MD). We found that both the individual-study peaks and the ALE clusters fell primarily within the language network and the ToM network. These results suggest that non-literal processing is supported by both i) mechanisms that process literal linguistic meaning, and ii) mechanisms that support general social inference. They thus undermine a strong divide between literal and non-literal aspects of language and challenge the claim that non-literal processing requires additional executive resources.

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bioRxiv2022

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.

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bioRxiv2021

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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bioRxiv2018

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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bioRxiv2017

The processing of dynamic faces in the human brain: Support for an integrated neural framework of face processing.

Faces convey rich information including identity, gender and expression. Current neural models of face processing suggest a dissociation between the processing of invariant facial aspects such as identity and gender, that engage the fusiform face area (FFA) and the processing of changeable aspects, such as expression and eye gaze, that engage the posterior superior temporal sulcus face area (pSTS-FA). Recent studies report a second dissociation within this network such that the pSTS-FA, but not the FFA, shows much stronger response to dynamic than static faces. The aim of the current study was to test a unified model that accounts for these two major functional characteristics of the neural face network. In an fMRI experiment, we presented static and dynamic faces while subjects judged an invariant (gender) or a changeable facial aspect (expression). We found that the pSTS-FA was more engaged in processing dynamic than static faces and changeable than invariant facial aspects, whereas the OFA and FFA showed similar response across all four conditions. Our results reveal no dissociation between the processing of changeable and invariant facial aspects, but higher sensitivity to the processing of changeable facial aspects by the motion-sensitive face area in the superior temporal sulcus.

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bioRxiv2017

A robust dissociation among the language, multiple demand, and default mode networks: evidence from inter-region correlations in effect size

Complex cognitive processes, including language, rely on multiple mental operations that are carried out by several large-scale functional networks in the frontal, temporal, and parietal association cortices of the human brain. The central division of cognitive labor is between two fronto-parietal bilateral networks: (a) the multiple demand (MD) network, which supports executive processes, such as working memory and cognitive control, and is engaged by diverse task domains, including language, especially when comprehension gets difficult; and (b) the default mode network (DMN), which supports introspective processes, such as mind wandering, and is active when we are not engaged in processing external stimuli. These two networks are strongly dissociated in both their functional profiles and their patterns of activity fluctuations during naturalistic cognition. Here, we focus on the functional relationship between these two networks and a third network: (c) the fronto-temporal left-lateralized \"core\" language network, which is selectively recruited by linguistic processing. Is the language network distinct and dissociated from both the MD network and the DMN, or is it synchronized and integrated with one or both of them? Recent work has provided evidence for a dissociation between the language network and the MD network. However, the relationship between the language network and the DMN is less clear, with some evidence for coordinated activity patterns and similar response profiles, perhaps due to the role of both in semantic processing. Here we use a novel fMRI approach to examine the relationship among the three networks: we measure the strength of activations in different language, MD, and DMN regions to functional contrasts typically used to identify each network, and then test which regions co-vary in their contrast effect sizes across 60 individuals. We find that effect sizes correlate strongly within each network (e.g., one language region and another language region, or one DMN region and another DMN region), but show little or no correlation for region pairs across networks (e.g., a language region and a DMN region). Thus, we replicate the language/MD network dissociation discovered previously with other methods, and also show that the language network is robustly dissociated from the DMN, overall suggesting that these three networks support distinct computations and contribute to high-level cognition in different ways. Inter-individual differences in effect sizes therefore do not simply reflect general differences in vascularization or attention, but exhibit sensitivity to the functional architecture of the brain. The strength of activation in each network can thus be probed separately in studies that attempt to link neural variability to behavioral or genetic variability.

neuroscience↗

bioRxiv2017

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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bioRxiv2016

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

Language 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.\n\nSignificance 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.

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