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Lipkin, B.

Publications and source records attributed to Lipkin, B..

9 recordsLinked to original sources

The cerebellar components of the human language network

The cerebellums capacity for neural computation is arguably unmatched. Yet despite now ample evidence of cerebellar contributions to cognition, including language, its precise role in language processing remains debated. Here, we systematically characterize cerebellar language-responsive regions using precision fMRI. We identify four cerebellar regions that respond to language across modalities (Experiments 1a-b, n=754). One region--spanning Crus I/II/lobule VIIb--is selective for language relative to diverse non-linguistic perceptual, cognitive, and motor tasks (Experiments 2a-f, n=732), and the rest exhibit mixed-selective profiles, responding strongly to language but also to one or more of the non-linguistic conditions. Similar to the neocortical language system, the language-selective region is engaged by sentence-level meanings during comprehension and production (Experiments 3a-b, n=100) and shows fine-grained sensitivity to linguistic processing difficulty (Experiment 3c, n=5). Further, this regions response to language is not due to the frequent presence of social content in language, as it is strongly engaged by both social and nonsocial sentences (Experiment 3d, n=10). Finally, all four regions, but especially Crus I/II/VIIb, are functionally connected to the neocortical language system (Experiment 4, n=85). We propose that these cerebellar regions constitute components of the extended language network, with one region supporting linguistic semantic processing and closely mirroring the selectivity of the neocortical language network, and the other three plausibly integrating information from diverse neocortical regions.

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The extended language network: Language selective brain areas whose contributions to language remain to be discovered

Although language neuroscience has largely focused on core left frontal and temporal brain areas and their right-hemisphere homotopes, numerous other areas--cortical and subcortical--have been implicated in linguistic processing. However, these areas contributions to language remain unclear given that the evidence for their recruitment comes from diverse paradigms, many of which conflate language processing with perceptual, motor, or task-related cognitive processes. Using fMRI data from 772 participants (438 females, 334 males) performing an extensively validated language localizer paradigm that isolates language processing from other processes, we a) delineate a comprehensive set of areas that respond reliably to language across written and auditory modalities, and b) evaluate these areas selectivity for language relative to a demanding non-linguistic task. In line with prior claims, many areas outside the core fronto-temporal network respond during language processing, and most of them show selectivity for language relative to general task demands. These language-selective areas of the extended language network include areas around the temporal poles, in the medial frontal cortex, in the hippocampus, and in the cerebellum, among others. Although distributed across many parts of the brain, the extended language-selective network still only comprises a small fraction (<5%) of the grey matter volume, challenging the view that the entire brain processes language. These newly identified language-selective areas can now be systematically characterized to decipher their contributions to language processing, including testing whether these contributions differ from those of the core language areas. Significance statementLanguage processing consistently recruits a left-lateralized fronto-temporal brain network, but language tasks often additionally engage areas outside this core system. In an fMRI dataset of 772 participants performing a validated language localizer task, we identified 17 brain areas outside the core fronto-temporal network that respond to both auditory and written language. Most of these areas show selectivity for language, including regions in the temporal poles, medial frontal cortex, hippocampus, and cerebellum. Despite its large number of components, this extended language network still only takes up a small fraction of the grey matter volume, challenging the view that the entire brain processes language. These findings lay the foundation for systematic characterization of these newly identified non-canonical language areas.

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Precision fMRI reveals that the language network exhibits adult-like left-hemispheric lateralization by 4 years of age

In adults, left hemisphere (LH) damage often leads to aphasia, but many cases of early damage leave linguistic processing intact, with a functional language system developing in the right hemisphere. To explain this early apparent equipotentiality of the two hemispheres for language, some have proposed that the language system is more bilateral during early development and becomes increasingly left-lateralized with age. We examined language lateralization using fMRI in two large developmental cohorts (total n=273 children aged 4-16 years; n=107 adults). Strong, adult-like LH lateralization (in response magnitude and activation volume) was evident by age 4, although other features of the LH language network showed protracted development, including the magnitude of language response and the strength of functional connectivity. Thus, although the RH can take over language function in some cases of early brain damage, this plasticity occurs in spite of adult-level LH bias present by age 4 years.

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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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Preserved functional organization of human auditory cortex in individuals missing one temporal lobe from infancy

Human cortical responses to natural sounds, measured with fMRI, can be approximated as the weighted sum of a small number of canonical response patterns (components), each having interpretable functional and anatomical properties. Here, we asked whether this organization is preserved in cases where only one temporal lobe is available due to early brain damage by investigating a unique family: one sibling born without a left temporal lobe, another without a right temporal lobe, and a third anatomically neurotypical. We analyzed fMRI responses to diverse natural sounds within the intact hemispheres of these individuals and compared them to 12 neurotypical participants. All siblings manifested the neurotypical auditory responses in their intact hemispheres. These results suggest that the development of the auditory cortex in each hemisphere does not depend on the existence of the other hemisphere, highlighting the redundancy and equipotentiality of the bilateral auditory system.

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No evidence of theory of mind reasoning in the human language network

Language comprehension and the ability to infer others thoughts (theory of mind, ToM) are interrelated during development and language use. However, neural evidence that bears on the relationship between language and ToM mechanisms is mixed. Although robust dissociations have been reported in brain disorders, brain activations for contrasts that target language and ToM bear similarities, and some have reported overlap (Deen et al., 2015). We take another look at the language-ToM relationship by evaluating the response of the language network (Fedorenko et al., 2010), as measured with fMRI, to verbal and non-verbal ToM across 151 participants. Individual-subject analyses reveal that all core language regions respond more strongly when participants read vignettes about false beliefs compared to the control vignettes. However, we show that these differences are largely due to linguistic confounds, and no such effects appear in a non-verbal ToM task. These results argue against cognitive and neural overlap between language processing and ToM. In exploratory analyses, we find responses to social processing in the "periphery" of the language network--right hemisphere homotopes of core language areas and areas in bilateral angular gyri--but these responses are not selectively ToM-related and may reflect general visual semantic processing.

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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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'Constituent length' effects in fMRI do not provide evidence for abstract syntactic processing

Human language has a remarkable capacity to encode complex ideas. This capacity arises because language is compositional: the form and arrangement of words in sentences (structure) determine the conceptual relations that hold between the words referents (meaning). A foundational question in human cognition is whether the brain regions that support language are similarly factored into structure-selective and meaning-selective areas. In an influential study, Pallier et al. (2011, PNAS) used fMRI to investigate the brain response to sequences of real words and pseudowords and reported a sharp dissociation between structure-selective and meaning-selective brain regions. In the present study, we argue that no such dissociation emerges when individual differences in brain anatomy are considered. We report three experiments (including a close conceptual replication of Pallier et al.s original study) that use precision fMRI methods to capture separation or overlap of function in the brains of individual participants. Our results replicate Pallier et al.s finding that the brains response is modulated by the sequential structure of language but paint a different picture with respect to the structure-meaning relationship. Instead of distinct structure-selective and meaning-selective brain areas, we find distributed sensitivity to both linguistic structure and meaning throughout a broad frontotemporal brain network. Our results join a growing body of evidence for an integrated network for language in the human brain within which internal specialization is primarily a matter of degree rather than kind, in contrast with influential proposals that advocate distinct specialization of different brain areas for different types of linguistic functions. Significance StatementUsing fMRI, we show that a broad network of frontal and temporal areas in the left hemisphere of the human brain is sensitive to both the structure of language and the meaning that it encodes. This finding challenges many current theories of the neurobiology of language, which propose a sharp separation between areas that encode structure and areas that encode meaning. Instead, results support a broad distribution of word- and sentence-level processing across an integrated brain network for language. This PDF file includes: Main Text Figures 1 to 3 Tables 1 to 1

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Functional alterations in cortical processing of speech in glioma-infiltrated cortex

Recent developments in the biology of malignant gliomas have demonstrated that glioma cells interact with neurons through both paracrine signaling and electrochemical synapses. Glioma-neuron interactions consequently modulate the excitability of local neuronal circuits, and it is unclear the extent to which glioma-infiltrated cortex can meaningfully participate in neural computations. For example, gliomas may result in a local disorganization of activity that impedes the transient synchronization of neural oscillations. Alternatively, glioma-infiltrated cortex may retain the ability to engage in synchronized activity, in a manner similar to normal-appearing cortex, but exhibit other altered spatiotemporal patterns of activity with subsequent impact on cognitive processing. Here, we use subdural electrocorticography to sample both normal-appearing and glioma-infiltrated cortex during speech. We find that glioma-infiltrated cortex engages in synchronous activity during task performance in a manner similar to normal-appearing cortex, but recruits a diffuse spatial network. On a temporal scale, we show that glioma-infiltrated cortex has lower capacity for information encoding when performing nuanced tasks such as speech production of monosyllabic versus polysyllabic words. As a result, temporal decoding strategies for distinguishing monosyllabic from polysyllabic words were feasible for signals arising from normal-appearing cortex, but not from glioma-infiltrated cortex. These findings inform our understanding of cognitive processing in chronic disease states and have implications for neuromodulation and prosthetics in patients with malignant gliomas. Significance StatementAs gliomas proliferate, they infiltrate healthy brain tissue. Often, patients with such tumors in the language areas of the brain develop aphasia. Understanding how gliomas interact with normal neural circuits is critical for developing neuroprostheses that restore speech. Recent evidence demonstrates that glioma cells interact synaptically with neurons, and thus can modulate neural circuits. However, it is unclear the extent to which glioma-infiltrated cortex participates in cognitive processing. Using electrocorticography to record both glioma-infiltrated and normal-appearing cortex during speech, we found that glioma-infiltrated cortex is capable of coordinated neural responses, but has reduced capacity for information encoding. Instead, glioma-infiltrated cortex recruits a broader network of cortical regions during speech, which may represent a compensatory mechanism with implications for future neuroprostheses.

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