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Graves WW, Levinson HJ, Staples R, Boukrina O, Rothlein D, Purcell J. An inclusive multivariate approach to neural localization of language components. Brain Struct Funct 2024; 229:1243-1263. [PMID: 38693340 PMCID: PMC11147878 DOI: 10.1007/s00429-024-02800-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 04/22/2024] [Indexed: 05/03/2024]
Abstract
To determine how language is implemented in the brain, it is important to know which brain areas are primarily engaged in language processing and which are not. Existing protocols for localizing language are typically univariate, treating each small unit of brain volume as independent. One prominent example that focuses on the overall language network in functional magnetic resonance imaging (fMRI) uses a contrast between neural responses to sentences and sets of pseudowords (pronounceable nonwords). This contrast reliably activates peri-sylvian language areas but is less sensitive to extra-sylvian areas that are also known to support aspects of language such as word meanings (semantics). In this study, we assess areas where a multivariate, pattern-based approach shows high reproducibility across multiple measurements and participants, identifying these areas as multivariate regions of interest (mROI). We then perform a representational similarity analysis (RSA) of an fMRI dataset where participants made familiarity judgments on written words. We also compare those results to univariate regions of interest (uROI) taken from previous sentences > pseudowords contrasts. RSA with word stimuli defined in terms of their semantic distance showed greater correspondence with neural patterns in mROI than uROI. This was confirmed in two independent datasets, one involving single-word recognition, and the other focused on the meaning of noun-noun phrases by contrasting meaningful phrases > pseudowords. In all cases, areas of spatial overlap between mROI and uROI showed the greatest neural association. This suggests that ROIs defined in terms of multivariate reproducibility can help localize components of language such as semantics. The multivariate approach can also be extended to focus on other aspects of language such as phonology, and can be used along with the univariate approach for inclusively mapping language cortex.
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Affiliation(s)
- William W Graves
- Department of Psychology, Rutgers University, Smith Hall, Room 301, 101 Warren Street, Newark, NJ, 07102, USA.
| | - Hillary J Levinson
- Department of Psychology, Rutgers University, Smith Hall, Room 301, 101 Warren Street, Newark, NJ, 07102, USA
| | - Ryan Staples
- Georgetown University Medical Center, Washington, DC, USA
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Fedorenko E, Ivanova AA, Regev TI. The language network as a natural kind within the broader landscape of the human brain. Nat Rev Neurosci 2024; 25:289-312. [PMID: 38609551 DOI: 10.1038/s41583-024-00802-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/23/2024] [Indexed: 04/14/2024]
Abstract
Language behaviour is complex, but neuroscientific evidence disentangles it into distinct components supported by dedicated brain areas or networks. In this Review, we describe the 'core' language network, which includes left-hemisphere frontal and temporal areas, and show that it is strongly interconnected, independent of input and output modalities, causally important for language and language-selective. We discuss evidence that this language network plausibly stores language knowledge and supports core linguistic computations related to accessing words and constructions from memory and combining them to interpret (decode) or generate (encode) linguistic messages. We emphasize that the language network works closely with, but is distinct from, both lower-level - perceptual and motor - mechanisms and higher-level systems of knowledge and reasoning. The perceptual and motor mechanisms process linguistic signals, but, in contrast to the language network, are sensitive only to these signals' surface properties, not their meanings; the systems of knowledge and reasoning (such as the system that supports social reasoning) are sometimes engaged during language use but are not language-selective. This Review lays a foundation both for in-depth investigations of these different components of the language processing pipeline and for probing inter-component interactions.
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Affiliation(s)
- Evelina Fedorenko
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA.
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
- The Program in Speech and Hearing in Bioscience and Technology, Harvard University, Cambridge, MA, USA.
| | - Anna A Ivanova
- School of Psychology, Georgia Institute of Technology, Atlanta, GA, USA
| | - Tamar I Regev
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
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Arvidsson C, Torubarova E, Pereira A, Uddén J. Conversational production and comprehension: fMRI-evidence reminiscent of but deviant from the classical Broca-Wernicke model. Cereb Cortex 2024; 34:bhae073. [PMID: 38501383 PMCID: PMC10949358 DOI: 10.1093/cercor/bhae073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 02/02/2024] [Accepted: 02/03/2024] [Indexed: 03/20/2024] Open
Abstract
A key question in research on the neurobiology of language is to which extent the language production and comprehension systems share neural infrastructure, but this question has not been addressed in the context of conversation. We utilized a public fMRI dataset where 24 participants engaged in unscripted conversations with a confederate outside the scanner, via an audio-video link. We provide evidence indicating that the two systems share neural infrastructure in the left-lateralized perisylvian language network, but diverge regarding the level of activation in regions within the network. Activity in the left inferior frontal gyrus was stronger in production compared to comprehension, while comprehension showed stronger recruitment of the left anterior middle temporal gyrus and superior temporal sulcus, compared to production. Although our results are reminiscent of the classical Broca-Wernicke model, the anterior (rather than posterior) temporal activation is a notable difference from that model. This is one of the findings that may be a consequence of the conversational setting, another being that conversational production activated what we interpret as higher-level socio-pragmatic processes. In conclusion, we present evidence for partial overlap and functional asymmetry of the neural infrastructure of production and comprehension, in the above-mentioned frontal vs temporal regions during conversation.
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Affiliation(s)
- Caroline Arvidsson
- Department of Linguistics, Stockholm University, Universitetsvägen 10 C, 114 18 Stockholm, Sweden
| | - Ekaterina Torubarova
- Division of Speech, Music, and Hearing, KTH Royal Institute of Technology, Lindstedtsvägen 24, 114 28 Stockholm, Sweden
| | - André Pereira
- Division of Speech, Music, and Hearing, KTH Royal Institute of Technology, Lindstedtsvägen 24, 114 28 Stockholm, Sweden
| | - Julia Uddén
- Department of Linguistics, Stockholm University, Universitetsvägen 10 C, 114 18 Stockholm, Sweden
- Department of Psychology, Stockholm University, Albanovägen 12, 114 19 Stockholm, Sweden
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Meier EL, Sheppard SM, Sebastian R, Berube S, Goldberg EB, Shea J, Stein CM, Hillis AE. Resting state correlates of picture description informativeness in left vs. right hemisphere chronic stroke. Front Neurol 2023; 14:1288801. [PMID: 38145117 PMCID: PMC10744570 DOI: 10.3389/fneur.2023.1288801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 11/20/2023] [Indexed: 12/26/2023] Open
Abstract
Introduction Despite a growing emphasis on discourse processing in clinical neuroscience, relatively little is known about the neurobiology of discourse production impairments. Individuals with a history of left or right hemisphere stroke can exhibit difficulty with communicating meaningful discourse content, which implies both cerebral hemispheres play a role in this skill. However, the extent to which successful production of discourse content relies on network connections within domain-specific vs. domain-general networks in either hemisphere is unknown. Methods In this study, 45 individuals with a history of either left or right hemisphere stroke completed resting state fMRI and the Cookie Theft picture description task. Results Participants did not differ in the total number of content units or the percentage of interpretative content units they produced. Stroke survivors with left hemisphere damage produced significantly fewer content units per second than individuals with right hemisphere stroke. Intrinsic connectivity of the left language network was significantly weaker in the left compared to the right hemisphere stroke group for specific connections. Greater efficiency of communication of picture scene content was associated with stronger left but weaker right frontotemporal connectivity of the language network in patients with a history of left hemisphere (but not right hemisphere) stroke. No significant relationships were found between picture description measures and connectivity of the dorsal attention, default mode, or salience networks or with connections between language and other network regions. Discussion These findings add to prior behavioral studies of picture description skills in stroke survivors and provide insight into the role of the language network vs. other intrinsic networks during discourse production.
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Affiliation(s)
- Erin L. Meier
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
| | - Shannon M. Sheppard
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
| | - Rajani Sebastian
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University, Baltimore, MD, United States
| | - Shauna Berube
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
| | - Emily B. Goldberg
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
| | - Jennifer Shea
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
| | - Colin M. Stein
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
| | - Argye E. Hillis
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University, Baltimore, MD, United States
- Department of Cognitive Science, Johns Hopkins University, Baltimore, MD, United States
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Seghier ML, Price CJ. Interpreting and validating complexity and causality in lesion-symptom prognoses. Brain Commun 2023; 5:fcad178. [PMID: 37346231 PMCID: PMC10279811 DOI: 10.1093/braincomms/fcad178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 05/08/2023] [Accepted: 06/04/2023] [Indexed: 06/23/2023] Open
Abstract
This paper considers the steps needed to generate pragmatic and interpretable lesion-symptom mappings that can be used for clinically reliable prognoses. The novel contributions are 3-fold. We first define and inter-relate five neurobiological and five methodological constraints that need to be accounted for when interpreting lesion-symptom associations and generating synthetic lesion data. The first implication is that, because of these constraints, lesion-symptom mapping needs to focus on probabilistic relationships between Lesion and Symptom, with Lesion as a multivariate spatial pattern, Symptom as a time-dependent behavioural profile and evidence that Lesion raises the probability of Symptom. The second implication is that in order to assess the strength of probabilistic causality, we need to distinguish between causal lesion sites, incidental lesion sites, spared but dysfunctional sites and intact sites, all of which might affect the accuracy of the predictions and prognoses generated. We then formulate lesion-symptom mappings in logical notations, including combinatorial rules, that are then used to evaluate and better understand complex brain-behaviour relationships. The logical and theoretical framework presented applies to any type of neurological disorder but is primarily discussed in relationship to stroke damage. Accommodating the identified constraints, we discuss how the 1965 Bradford Hill criteria for inferring probabilistic causality, post hoc, from observed correlations in epidemiology-can be applied to lesion-symptom mapping in stroke survivors. Finally, we propose that rather than rely on post hoc evaluation of how well the causality criteria have been met, the neurobiological and methodological constraints should be addressed, a priori, by changing the experimental design of lesion-symptom mappings and setting up an open platform to share and validate the discovery of reliable and accurate lesion rules that are clinically useful.
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Affiliation(s)
- Mohamed L Seghier
- Correspondence to: Mohamed Seghier Department of Biomedical Engineering Khalifa University of Science and Technology PO BOX: 127788, Abu Dhabi, UAE E-mail:
| | - Cathy J Price
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, UK
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