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Biondi M, Marino M, Mantini D, Spironelli C. Unveiling altered connectivity between cognitive networks and cerebellum in schizophrenia. Schizophr Res 2024; 271:47-58. [PMID: 39013344 DOI: 10.1016/j.schres.2024.06.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 06/12/2024] [Accepted: 06/23/2024] [Indexed: 07/18/2024]
Abstract
Cognitive functioning is a crucial aspect in schizophrenia (SZ), and when altered it has devastating effects on patients' quality of life and treatment outcomes. Several studies suggested that they could result from altered communication between the cortex and cerebellum. However, the neural correlates underlying these impairments have not been identified. In this study, we investigated resting state functional connectivity (rsFC) in SZ patients, by considering the interactions between cortical networks supporting cognition and cerebellum. In addition, we investigated the relationship between SZ patients' rsFC and their symptoms. We used fMRI data from 74 SZ patients and 74 matched healthy controls (HC) downloaded from the publicly available database SchizConnect. We implemented a seed-based connectivity approach to identify altered functional connections between specific cortical networks and cerebellum. We considered ten commonly studied resting state networks, whose functioning encompasses specific cognitive functions, and the cerebellum, whose involvement in supporting cognition has been recently identified. We then explored the relationship between altered rsFC values and Positive and Negative Syndrome Scale (PANSS) scores. The SZ group showed increased connectivity values compared with HC group for cortical networks involved in attentive processes, which were also linked to PANSS items describing attention and language-related processing. We also showed decreased connectivity between cerebellar regions, and increased connectivity between them and attentive networks, suggesting the contribution of cerebellum to attentive and affective deficits. In conclusion, our findings highlighted the link between negative symptoms in SZ and altered connectivity within the cerebellum and between the same and cortical networks supporting cognition.
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Affiliation(s)
| | - Marco Marino
- Department of General Psychology, University of Padova, Italy; Movement Control and Neuroplasticity Research Group, KU, Leuven, Belgium
| | - Dante Mantini
- Movement Control and Neuroplasticity Research Group, KU, Leuven, Belgium.
| | - Chiara Spironelli
- Padova Neuroscience Center, University of Padova, Italy; Department of General Psychology, University of Padova, Italy
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2
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Shain C, Kean H, Casto C, Lipkin B, Affourtit J, Siegelman M, Mollica F, Fedorenko E. Distributed Sensitivity to Syntax and Semantics throughout the Language Network. J Cogn Neurosci 2024; 36:1427-1471. [PMID: 38683732 DOI: 10.1162/jocn_a_02164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Abstract
Human language is expressive because it is compositional: The meaning of a sentence (semantics) can be inferred from its structure (syntax). It is commonly believed that language syntax and semantics are processed by distinct brain regions. Here, we revisit this claim using precision fMRI methods to capture separation or overlap of function in the brains of individual participants. Contrary to prior claims, we find distributed sensitivity to both syntax and semantics 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.
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Affiliation(s)
| | - Hope Kean
- Massachusetts Institute of Technology
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3
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Tilton-Bolowsky V, Stockbridge MD, Hillis AE. Remapping and Reconnecting the Language Network after Stroke. Brain Sci 2024; 14:419. [PMID: 38790398 PMCID: PMC11117613 DOI: 10.3390/brainsci14050419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 04/22/2024] [Accepted: 04/23/2024] [Indexed: 05/26/2024] Open
Abstract
Here, we review the literature on neurotypical individuals and individuals with post-stroke aphasia showing that right-hemisphere regions homologous to language network and other regions, like the right cerebellum, are activated in language tasks and support language even in healthy people. We propose that language recovery in post-stroke aphasia occurs largely by potentiating the right hemisphere network homologous to the language network and other networks that previously supported language to a lesser degree and by modulating connection strength between nodes of the right-hemisphere language network and undamaged nodes of the left-hemisphere language network. Based on this premise (supported by evidence we review), we propose that interventions should be aimed at potentiating the right-hemisphere language network through Hebbian learning or by augmenting connections between network nodes through neuroplasticity, such as non-invasive brain stimulation and perhaps modulation of neurotransmitters involved in neuroplasticity. We review aphasia treatment studies that have taken this approach. We conclude that further aphasia rehabilitation with this aim is justified.
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Affiliation(s)
| | | | - Argye E. Hillis
- Departments of Neurology, Physical Medicine & Rehabilitation, and Cognitive Science, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA; (V.T.-B.); (M.D.S.)
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4
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Zhang G, Xu Y, Wang X, Li J, Shi W, Bi Y, Lin N. A social-semantic working-memory account for two canonical language areas. Nat Hum Behav 2023; 7:1980-1997. [PMID: 37735521 DOI: 10.1038/s41562-023-01704-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 08/22/2023] [Indexed: 09/23/2023]
Abstract
Language and social cognition are traditionally studied as separate cognitive domains, yet accumulative studies reveal overlapping neural correlates at the left ventral temporoparietal junction (vTPJ) and the left lateral anterior temporal lobe (lATL), which have been attributed to sentence processing and social concept activation. We propose a common cognitive component underlying both effects: social-semantic working memory. We confirmed two key predictions of our hypothesis using functional MRI. First, the left vTPJ and lATL showed sensitivity to sentences only when the sentences conveyed social meaning; second, these regions showed persistent social-semantic-selective activity after the linguistic stimuli disappeared. We additionally found that both regions were sensitive to the socialness of non-linguistic stimuli and were more tightly connected with the social-semantic-processing areas than with the sentence-processing areas. The converging evidence indicates the social-semantic working-memory function of the left vTPJ and lATL and challenges the general-semantic and/or syntactic accounts for the neural activity of these regions.
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Affiliation(s)
- Guangyao Zhang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
| | - Yangwen Xu
- Center for Mind/Brain Sciences, University of Trento, Trento, Italy
| | - Xiuyi Wang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Jixing Li
- Department of Linguistics and Translation, City University of Hong Kong, Hong Kong SAR, China
| | - Weiting Shi
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Yanchao Bi
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Nan Lin
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China.
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
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5
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Murphy E, Forseth KJ, Donos C, Snyder KM, Rollo PS, Tandon N. The spatiotemporal dynamics of semantic integration in the human brain. Nat Commun 2023; 14:6336. [PMID: 37875526 PMCID: PMC10598228 DOI: 10.1038/s41467-023-42087-8] [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: 09/12/2022] [Accepted: 09/28/2023] [Indexed: 10/26/2023] Open
Abstract
Language depends critically on the integration of lexical information across multiple words to derive semantic concepts. Limitations of spatiotemporal resolution have previously rendered it difficult to isolate processes involved in semantic integration. We utilized intracranial recordings in epilepsy patients (n = 58) who read written word definitions. Descriptions were either referential or non-referential to a common object. Semantically referential sentences enabled high frequency broadband gamma activation (70-150 Hz) of the inferior frontal sulcus (IFS), medial parietal cortex, orbitofrontal cortex (OFC) and medial temporal lobe in the left, language-dominant hemisphere. IFS, OFC and posterior middle temporal gyrus activity was modulated by the semantic coherence of non-referential sentences, exposing semantic effects that were independent of task-based referential status. Components of this network, alongside posterior superior temporal sulcus, were engaged for referential sentences that did not clearly reduce the lexical search space by the final word. These results indicate the existence of complementary cortical mosaics for semantic integration in posterior temporal and inferior frontal cortex.
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Affiliation(s)
- Elliot Murphy
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.
- Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.
| | - Kiefer J Forseth
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
- Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Cristian Donos
- Faculty of Physics, University of Bucharest, Măgurele, 077125, Bucharest, Romania
| | - Kathryn M Snyder
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
- Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Patrick S Rollo
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
- Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Nitin Tandon
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.
- Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA.
- Memorial Hermann Hospital, Texas Medical Center, Houston, TX, 77030, USA.
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Yan J, Li W, Zhang T, Zhang J, Jin Z, Li L. Structural and functional neural substrates underlying the concreteness effect. Brain Struct Funct 2023; 228:1493-1510. [PMID: 37389616 DOI: 10.1007/s00429-023-02668-1] [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: 01/09/2023] [Accepted: 06/13/2023] [Indexed: 07/01/2023]
Abstract
The concreteness effect refers to the advantage in speed and accuracy of processing concrete words over abstract words. Previous studies have shown that the processing of the two types of words is mediated by distinct neural mechanisms, but these studies were mainly conducted with task-based functional magnetic resonance imaging. This study investigates the associations between the concreteness effect and grey matter volume (GMV) of brain regions as well as resting-state functional connectivity (rsFC) of these identified regions. The results show that the GMV of left inferior frontal gyrus (IFG), right middle temporal gyrus (MTG), right supplementary motor area and right anterior cingulate cortex (ACC) negatively correlates with the concreteness effect. The rsFC of the left IFG, the right MTG and the right ACC with the nodes, mainly in default mode network, frontoparietal network and dorsal attention network positively correlates with the concreteness effect. The GMV and rsFC jointly and respectively predict the concreteness effect in individuals. In conclusion, stronger connectivity amongst functional networks and higher coherent engagement of the right hemisphere predict a greater difference in the verbal memory of abstract and concrete words.
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Affiliation(s)
- Jing Yan
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Psychiatry and Psychology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
- School of Foreign Languages, Southwest Jiaotong University, Chengdu, Sichuan, China
| | - Wenjuan Li
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Psychiatry and Psychology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Tingting Zhang
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Psychiatry and Psychology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Junjun Zhang
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Psychiatry and Psychology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Zhenlan Jin
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Psychiatry and Psychology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Ling Li
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Psychiatry and Psychology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
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7
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Woolnough O, Donos C, Murphy E, Rollo PS, Roccaforte ZJ, Dehaene S, Tandon N. Spatiotemporally distributed frontotemporal networks for sentence reading. Proc Natl Acad Sci U S A 2023; 120:e2300252120. [PMID: 37068244 PMCID: PMC10151604 DOI: 10.1073/pnas.2300252120] [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: 01/09/2023] [Accepted: 03/14/2023] [Indexed: 04/19/2023] Open
Abstract
Reading a sentence entails integrating the meanings of individual words to infer more complex, higher-order meaning. This highly rapid and complex human behavior is known to engage the inferior frontal gyrus (IFG) and middle temporal gyrus (MTG) in the language-dominant hemisphere, yet whether there are distinct contributions of these regions to sentence reading is still unclear. To probe these neural spatiotemporal dynamics, we used direct intracranial recordings to measure neural activity while reading sentences, meaning-deficient Jabberwocky sentences, and lists of words or pseudowords. We isolated two functionally and spatiotemporally distinct frontotemporal networks, each sensitive to distinct aspects of word and sentence composition. The first distributed network engages the IFG and MTG, with IFG activity preceding MTG. Activity in this network ramps up over the duration of a sentence and is reduced or absent during Jabberwocky and word lists, implying its role in the derivation of sentence-level meaning. The second network engages the superior temporal gyrus and the IFG, with temporal responses leading those in frontal lobe, and shows greater activation for each word in a list than those in sentences, suggesting that sentential context enables greater efficiency in the lexical and/or phonological processing of individual words. These adjacent, yet spatiotemporally dissociable neural mechanisms for word- and sentence-level processes shed light on the richly layered semantic networks that enable us to fluently read. These results imply distributed, dynamic computation across the frontotemporal language network rather than a clear dichotomy between the contributions of frontal and temporal structures.
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Affiliation(s)
- Oscar Woolnough
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, TX77030
- Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX77030
| | - Cristian Donos
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, TX77030
- Faculty of Physics, University of Bucharest, 050663Bucharest, Romania
| | - Elliot Murphy
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, TX77030
- Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX77030
| | - Patrick S. Rollo
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, TX77030
- Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX77030
| | - Zachary J. Roccaforte
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, TX77030
- Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX77030
| | - Stanislas Dehaene
- Cognitive Neuroimaging Unit, Université Paris-Saclay, INSERM, CEA, NeuroSpin Center, 91191Gif-sur-Yvette, France
- Collège de France, 75005Paris, France
| | - Nitin Tandon
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School at UT Health Houston, Houston, TX77030
- Texas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX77030
- Memorial Hermann Hospital, Texas Medical Center, Houston, TX77030
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8
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Palaniyappan L, Homan P, Alonso-Sanchez MF. Language Network Dysfunction and Formal Thought Disorder in Schizophrenia. Schizophr Bull 2023; 49:486-497. [PMID: 36305160 PMCID: PMC10016399 DOI: 10.1093/schbul/sbac159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
BACKGROUND Pathophysiological inquiries into schizophrenia require a consideration of one of its most defining features: disorganization and impoverishment in verbal behavior. This feature, often captured using the term Formal Thought Disorder (FTD), still remains to be one of the most poorly understood and understudied dimensions of schizophrenia. In particular, the large-scale network level dysfunction that contributes to FTD remains obscure to date. STUDY DESIGN In this narrative review, we consider the various challenges that need to be addressed for us to move towards mapping FTD (construct) to a brain network level account (circuit). STUDY RESULTS The construct-to-circuit mapping goal is now becoming more plausible than it ever was, given the parallel advent of brain stimulation and the tools providing objective readouts of human speech. Notwithstanding this, several challenges remain to be overcome before we can decisively map the neural basis of FTD. We highlight the need for phenotype refinement, robust experimental designs, informed analytical choices, and present plausible targets in and beyond the Language Network for brain stimulation studies in FTD. CONCLUSIONS Developing a therapeutically beneficial pathophysiological model of FTD is a challenging endeavor, but holds the promise of improving interpersonal communication and reducing social disability in schizophrenia. Addressing the issues raised in this review will be a decisive step in this direction.
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Affiliation(s)
- Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Quebec, Canada
- Robarts Research Institute, Western University, London, Ontario, Canada
- Department of Medical Biophysics, Western University, London, Canada
| | - Philipp Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital of the University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University and ETH Zurich, Zurich, Switzerland
| | - Maria F Alonso-Sanchez
- Robarts Research Institute, Western University, London, Ontario, Canada
- CIDCL, Fonoaudiología, Facultad de Medicina, Universidad de Valparaíso, Valparaiso, Chile
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9
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Bartoň M, Rapcsak SZ, Zvončák V, Mareček R, Cvrček V, Rektorová I. Functional neuroanatomy of reading in Czech: Evidence of a dual-route processing architecture in a shallow orthography. Front Psychol 2023; 13:1037365. [PMID: 36726504 PMCID: PMC9885179 DOI: 10.3389/fpsyg.2022.1037365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 12/21/2022] [Indexed: 01/19/2023] Open
Abstract
Introduction According to the strong version of the orthographic depth hypothesis, in languages with transparent letter-sound mappings (shallow orthographies) the reading of both familiar words and unfamiliar nonwords may be accomplished by a sublexical pathway that relies on serial grapheme-to-phoneme conversion. However, in languages such as English characterized by inconsistent letter-sound relationships (deep orthographies), word reading is mediated by a lexical-semantic pathway that relies on mappings between word-specific orthographic, semantic, and phonological representations, whereas the sublexical pathway is used primarily to read nonwords. Methods In this study, we used functional magnetic resonance imaging to elucidate neural substrates of reading in Czech, a language characterized by a shallo worthography. Specifically, we contrasted patterns of brain activation and connectivity during word and nonword reading to determine whether similar or different neural mechanisms are involved. Neural correlates were measured as differences in simple whole-brain voxel-wise activation, and differences in visual word form area (VWFA) task-related connectivity were computed on the group level from data of 24 young subject. Trial-to-trial reading reaction times were used as a measure of task difficulty, and these effects were subtracted from the activation and connectivity effects in order to eliminate difference in cognitive effort which is naturally higher for nonwords and may mask the true lexicality effects. Results We observed pattern of activity well described in the literature mostly derived from data of English speakers - nonword reading (as compared to word reading) activated the sublexical pathway to a greater extent whereas word reading was associated with greater activation of semantic networks. VWFA connectivity analysis also revealed stronger connectivity to a component of the sublexical pathway - left inferior frontal gyrus (IFG), for nonword compared to word reading. Discussion These converging results suggest that the brain mechanism of skilled reading in shallow orthography languages are similar to those engaged when reading in languages with a deep orthography and are supported by a universal dual-pathway neural architecture.
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Affiliation(s)
- Marek Bartoň
- Applied Neuroscience Research Group, Central European Institute of Technology – CEITEC, Masaryk University, Brno, Czechia
| | - Steven Z. Rapcsak
- Department of Neurology, University of Arizona, Tucson, AZ, United States
| | - Vojtěch Zvončák
- Department of Telecommunications, Faculty of Electrical Engineering and Communication, Brno University of Technology, Brno, Czechia
| | - Radek Mareček
- Applied Neuroscience Research Group, Central European Institute of Technology – CEITEC, Masaryk University, Brno, Czechia
| | - Václav Cvrček
- Institute of the Czech National Corpus, Charles University, Prague, Czechia
| | - Irena Rektorová
- Applied Neuroscience Research Group, Central European Institute of Technology – CEITEC, Masaryk University, Brno, Czechia,International Clinical Research Center, ICRC, St. Anne’s University Hospital and Faculty of Medicine, Masaryk University, Brno, Czechia,*Correspondence: Irena Rektorová, ✉ ; ✉
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10
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Ren W, Jia C, Zhou Y, Zhao J, Wang B, Yu W, Li S, Hu Y, Zhang H. A precise language network revealed by the independent component-based lesion mapping in post-stroke aphasia. Front Neurol 2022; 13:981653. [PMID: 36247758 PMCID: PMC9561861 DOI: 10.3389/fneur.2022.981653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 09/09/2022] [Indexed: 11/17/2022] Open
Abstract
Brain lesion mapping studies have provided the strongest evidence regarding the neural basis of cognition. However, it remained a problem to identify symptom-specific brain networks accounting for observed clinical and neuroanatomical heterogeneity. Independent component analysis (ICA) is a statistical method that decomposes mixed signals into multiple independent components. We aimed to solve this issue by proposing an independent component-based lesion mapping (ICLM) method to identify the language network in patients with moderate to severe post-stroke aphasia. Lesions were first extracted from 49 patients with post-stroke aphasia as masks applied to fMRI data in a cohort of healthy participants to calculate the functional connectivity (FC) within the masks and non-mask brain voxels. ICA was further performed on a reformatted FC matrix to extract multiple independent networks. Specifically, we found that one of the lesion-related independent components (ICs) highly resembled classical language networks. Moreover, the damaged level within the language-related lesioned network is strongly associated with language deficits, including aphasia quotient, naming, and auditory comprehension scores. In comparison, none of the other two traditional lesion mapping methods found any regions responsible for language dysfunction. The language-related lesioned network extracted with the ICLM method showed high specificity in detecting aphasia symptoms compared with the performance of resting ICs and classical language networks. In total, we detected a precise language network in patients with aphasia and proved its efficiency in the relationship with language symptoms. In general, our ICLM could successfully identify multiple lesion-related networks from complicated brain diseases, and be used as an effective tool to study brain-behavior relationships and provide potential biomarkers of particular clinical behavioral deficits.
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Affiliation(s)
- Weijing Ren
- School of Rehabilitation, Capital Medical University, Beijing, China
- Department of Neurorehabilitation, China Rehabilitation Research Center, Beijing Bo'ai Hospital, Beijing, China
- University of Health and Rehabilitation Sciences, Qingdao, China
| | - Chunying Jia
- Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| | - Ying Zhou
- Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| | - Jingdu Zhao
- School of Rehabilitation, Capital Medical University, Beijing, China
- Department of Neurorehabilitation, China Rehabilitation Research Center, Beijing Bo'ai Hospital, Beijing, China
| | - Bo Wang
- Department of Hearing and Language Rehabilitation, China Rehabilitation Research Center, Beijing Bo'ai Hospital, Beijing, China
| | - Weiyong Yu
- Department of Radiology, China Rehabilitation Research Center, Beijing Bo'ai Hospital, Beijing, China
| | - Shiyi Li
- Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| | - Yiru Hu
- Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| | - Hao Zhang
- School of Rehabilitation, Capital Medical University, Beijing, China
- Department of Neurorehabilitation, China Rehabilitation Research Center, Beijing Bo'ai Hospital, Beijing, China
- University of Health and Rehabilitation Sciences, Qingdao, China
- *Correspondence: Hao Zhang
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11
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Fan L, Li C, Huang ZG, Zhao J, Wu X, Liu T, Li Y, Wang J. The longitudinal neural dynamics changes of whole brain connectome during natural recovery from poststroke aphasia. NEUROIMAGE: CLINICAL 2022; 36:103190. [PMID: 36174256 PMCID: PMC9668607 DOI: 10.1016/j.nicl.2022.103190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 07/24/2022] [Accepted: 09/08/2022] [Indexed: 12/14/2022] Open
Abstract
Poststroke aphasia is one of the most dramatic functional deficits that results from direct damage of focal brain regions and dysfunction of large-scale brain networks. The reconstruction of language function depends on the hierarchical whole-brain dynamic reorganization. However, investigations into the longitudinal neural changes of large-scale brain networks for poststroke aphasia remain scarce. Here we characterize large-scale brain dynamics in left-frontal-stroke aphasia through energy landscape analysis. Using fMRI during an auditory comprehension task, we find that aphasia patients suffer serious whole-brain dynamics perturbation in the acute and subacute stages after stroke, in which the brains were restricted into two major activity patterns. Following spontaneous recovery process, the brain flexibility improved in the chronic stage. Critically, we demonstrated that the abnormal neural dynamics are correlated with the aberrant brain network coordination. Taken together, the energy landscape analysis exhibited that the acute poststroke aphasia has a constrained, low dimensional brain dynamics, which were replaced by less constrained and high dimensional dynamics at chronic aphasia. Our study provides a new perspective to profoundly understand the pathological mechanisms of poststroke aphasia.
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Affiliation(s)
- Liming Fan
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi 710049, PR China,National Engineering Research Center of Health Care and Medical Devices. Guangzhou, Guangdong 510500, PR China
| | - Chenxi Li
- Department of the Psychology of Military Medicine, Air Force Medical University, Xi’an, Shaanxi 710032, PR China
| | - Zi-gang Huang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi 710049, PR China,National Engineering Research Center of Health Care and Medical Devices. Guangzhou, Guangdong 510500, PR China
| | - Jie Zhao
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi 710049, PR China,National Engineering Research Center of Health Care and Medical Devices. Guangzhou, Guangdong 510500, PR China
| | - Xiaofeng Wu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi 710049, PR China,National Engineering Research Center of Health Care and Medical Devices. Guangzhou, Guangdong 510500, PR China
| | - Tian Liu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi 710049, PR China,National Engineering Research Center of Health Care and Medical Devices. Guangzhou, Guangdong 510500, PR China
| | - Youjun Li
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi 710049, PR China,National Engineering Research Center of Health Care and Medical Devices. Guangzhou, Guangdong 510500, PR China,Corresponding authors at: The Key Laboratory of Biomedical Information Engineering of Ministry of Education, and Institute of Biomedical Engineering, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an 710049, PR China.
| | - Jue Wang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi 710049, PR China,National Engineering Research Center of Health Care and Medical Devices. Guangzhou, Guangdong 510500, PR China,The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs, Xi’an, Shaanxi 710049, PR China,Corresponding authors at: The Key Laboratory of Biomedical Information Engineering of Ministry of Education, and Institute of Biomedical Engineering, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an 710049, PR China.
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12
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Zahnert F, Kräling G, Melms L, Belke M, Kleinholdermann U, Timmermann L, Hirsch M, Jansen A, Mross P, Menzler K, Habermehl L, Knake S. Diffusion magnetic resonance imaging connectome features are predictive of functional lateralization of semantic processing in the anterior temporal lobes. Hum Brain Mapp 2022; 44:496-508. [PMID: 36098483 PMCID: PMC9842893 DOI: 10.1002/hbm.26074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 07/22/2022] [Accepted: 08/18/2022] [Indexed: 01/25/2023] Open
Abstract
Assessment of regional language lateralization is crucial in many scenarios, but not all populations are suited for its evaluation via task-functional magnetic resonance imaging (fMRI). In this study, the utility of structural connectome features for the classification of language lateralization in the anterior temporal lobes (ATLs) was investigated. Laterality indices for semantic processing in the ATL were computed from task-fMRI in 1038 subjects from the Human Connectome Project who were labeled as stronger rightward lateralized (RL) or stronger leftward to bilaterally lateralized (LL) in a data-driven approach. Data of unrelated subjects (n = 432) were used for further analyses. Structural connectomes were generated from diffusion-MRI tractography, and graph theoretical metrics (node degree, betweenness centrality) were computed. A neural network (NN) and a random forest (RF) classifier were trained on these metrics to classify subjects as RL or LL. After classification, comparisons of network measures were conducted via permutation testing. Degree-based classifiers produced significant above-chance predictions both during cross-validation (NN: AUC-ROC[CI] = 0.68[0.64-0.73], accuracy[CI] = 68.34%[63-73.2%]; RF: AUC-ROC[CI] = 0.7[0.66-0.73], accuracy[CI] = 64.81%[60.9-68.5]) and testing (NN: AUC-ROC[CI] = 0.69[0.53-0.84], accuracy[CI] = 68.09[53.2-80.9]; RF: AUC-ROC[CI] = 0.68[0.53-0.84], accuracy[CI] = 68.09[55.3-80.9]). Comparison of network metrics revealed small effects of increased node degree within the right posterior middle temporal gyrus (pMTG) in subjects with RL, while degree was decreased in the right posterior cingulate cortex (PCC). Above-chance predictions of functional language lateralization in the ATL are possible based on diffusion-MRI connectomes alone. Increased degree within the right pMTG as a right-sided homologue of a known semantic hub, and decreased hubness of the right PCC may form a structural basis for rightward-lateralized semantic processing.
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Affiliation(s)
- Felix Zahnert
- Epilepsy Center Hesse, Department for NeurologyUniversity Hospital Marburg, Philipps University MarburgMarburgGermany
| | - Gunter Kräling
- Department of Medical TechnologyUniversity Hospital MarburgMarburgGermany
| | - Leander Melms
- Institute for Artificial IntelligenceUniversity Hospital Marburg, Philipps University MarburgMarburgGermany
| | - Marcus Belke
- Epilepsy Center Hesse, Department for NeurologyUniversity Hospital Marburg, Philipps University MarburgMarburgGermany,LOEWE Center for Personalized Translational Epilepsy Research (CePTER)Goethe‐University FrankfurtFrankfurt Am MainGermany
| | - Urs Kleinholdermann
- Department for NeurologyUniversity Hospital Marburg, Philipps University MarburgMarburgGermany
| | - Lars Timmermann
- Department for NeurologyUniversity Hospital Marburg, Philipps University MarburgMarburgGermany,Center for Mind, Brain and Behavior (CMBB)Philipps‐University MarburgMarburgGermany,Core Facility Brainimaging, Faculty of MedicineUniversity of MarburgMarburgGermany
| | - Martin Hirsch
- Institute for Artificial IntelligenceUniversity Hospital Marburg, Philipps University MarburgMarburgGermany
| | - Andreas Jansen
- Center for Mind, Brain and Behavior (CMBB)Philipps‐University MarburgMarburgGermany,Core Facility Brainimaging, Faculty of MedicineUniversity of MarburgMarburgGermany,Department for Psychiatry and PsychotherapyUniversity Hospital Marburg, Philipps University MarburgMarburgGermany
| | - Peter Mross
- Epilepsy Center Hesse, Department for NeurologyUniversity Hospital Marburg, Philipps University MarburgMarburgGermany
| | - Katja Menzler
- Epilepsy Center Hesse, Department for NeurologyUniversity Hospital Marburg, Philipps University MarburgMarburgGermany,Center for Mind, Brain and Behavior (CMBB)Philipps‐University MarburgMarburgGermany,Core Facility Brainimaging, Faculty of MedicineUniversity of MarburgMarburgGermany
| | - Lena Habermehl
- Epilepsy Center Hesse, Department for NeurologyUniversity Hospital Marburg, Philipps University MarburgMarburgGermany
| | - Susanne Knake
- Epilepsy Center Hesse, Department for NeurologyUniversity Hospital Marburg, Philipps University MarburgMarburgGermany,LOEWE Center for Personalized Translational Epilepsy Research (CePTER)Goethe‐University FrankfurtFrankfurt Am MainGermany,Center for Mind, Brain and Behavior (CMBB)Philipps‐University MarburgMarburgGermany,Core Facility Brainimaging, Faculty of MedicineUniversity of MarburgMarburgGermany
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13
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Silvestri E, Moretto M, Facchini S, Castellaro M, Anglani M, Monai E, D’Avella D, Della Puppa A, Cecchin D, Bertoldo A, Corbetta M. Widespread cortical functional disconnection in gliomas: an individual network mapping approach. Brain Commun 2022; 4:fcac082. [PMID: 35474856 PMCID: PMC9034119 DOI: 10.1093/braincomms/fcac082] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 02/04/2022] [Accepted: 04/04/2022] [Indexed: 11/14/2022] Open
Abstract
Abstract
Assessment of impaired/preserved cortical regions in brain tumours is typically performed via intraoperative direct brain stimulation of eloquent areas or task-based functional MRI. One main limitation is that they overlook distal brain regions or networks that could be functionally impaired by the tumour.
This study aims: 1) to investigate the impact of brain tumours on the cortical synchronization of brain networks measured with resting-state functional magnetic resonance imaging (resting-state networks) both near the lesion and remotely; 2) to test whether potential changes in resting state networks correlate with cognitive status.
The sample included twenty-four glioma patients (mean age 58.1 ± 16.4y) with different pathological staging. We developed a new method for single subject localization of resting state networks abnormalities. First, we derived the spatial pattern of the main resting state networks by means of the group guided independent component analysis. This was informed by a high-resolution resting state networks template derived from an independent sample of healthy controls. Second, we developed a spatial similarity index to measure differences in network topography and strength between healthy controls and individual brain tumour patients. Next, we investigated the spatial relationship between altered networks and tumour location. Finally, multivariate analyses related cognitive scores across multiple cognitive domains (attention, language, memory, decision making) with patterns of multi-network abnormality.
We found that brain gliomas cause broad alterations of resting state networks topography that occurred mainly in structurally normal regions outside the tumour and oedema region. Cortical regions near the tumour often showed normal synchronization. Finally, multi-network abnormalities predicted attention deficits.
Overall, we present a novel method for the functional localization of resting state networks abnormalities in individual glioma patients. These abnormalities partially explain cognitive disabilities and shall be carefully navigated during surgery.
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Affiliation(s)
- Erica Silvestri
- Department of Information Engineering, University of Padova, 35131 Padova, Italy
- Padova Neuroscience Center, University of Padova, 35129 Padova, Italy
| | - Manuela Moretto
- Department of Information Engineering, University of Padova, 35131 Padova, Italy
- Padova Neuroscience Center, University of Padova, 35129 Padova, Italy
| | - Silvia Facchini
- Padova Neuroscience Center, University of Padova, 35129 Padova, Italy
- Department of Neuroscience, University of Padova, 35128 Padova, Italy
| | - Marco Castellaro
- Department of Information Engineering, University of Padova, 35131 Padova, Italy
- Padova Neuroscience Center, University of Padova, 35129 Padova, Italy
| | | | - Elena Monai
- Padova Neuroscience Center, University of Padova, 35129 Padova, Italy
- Department of Neuroscience, University of Padova, 35128 Padova, Italy
| | - Domenico D’Avella
- Department of Neuroscience, University of Padova, 35128 Padova, Italy
| | - Alessandro Della Puppa
- Neurosurgery, Department of NEUROFARBA, University Hospital of Careggi, University of Florence, 50139 Florence, Italy
| | - Diego Cecchin
- Padova Neuroscience Center, University of Padova, 35129 Padova, Italy
- Department of Medicine, Unit of Nuclear Medicine, University of Padova, 35128 Padova, Italy
| | - Alessandra Bertoldo
- Department of Information Engineering, University of Padova, 35131 Padova, Italy
- Padova Neuroscience Center, University of Padova, 35129 Padova, Italy
| | - Maurizio Corbetta
- Padova Neuroscience Center, University of Padova, 35129 Padova, Italy
- Department of Neuroscience, University of Padova, 35128 Padova, Italy
- Venetian Institute of Molecular Medicine, 35129 Padova, Italy
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14
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Fallahi A, Pooyan M, Habibabadi JM, Hashemi-Fesharaki SS, Tabatabaei NH, Ay M, Nazem-Zadeh MR. A novel approach for extracting functional brain networks involved in mesial temporal lobe epilepsy based on self organizing maps. INFORMATICS IN MEDICINE UNLOCKED 2022. [DOI: 10.1016/j.imu.2022.100876] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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15
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Smirnov AS, Melnikova-Pitskhelauri TV, Sharaev MG, Yarkin VE, Turkin AM, Afandiev RM, Khasieva LM, Bernshtein AV, Pitskhelauri DI, Pronin IN. [Comparison of resting state and task-based functional MRI in preoperative mapping in patients with brain gliomas]. ZHURNAL VOPROSY NEIROKHIRURGII IMENI N. N. BURDENKO 2022; 86:33-40. [PMID: 35942835 DOI: 10.17116/neiro20228604133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
OBJECTIVE To analyze and compare the results of cerebral cortex mapping with task-based (tb-fMRI) and resting-state functional MRI in patients with glioma of eloquent cortical areas. MATERIAL AND METHODS There were 55 patients (24 men and 31 women aged 24 - 74 years, median 39) with glial tumors. In 26 patients, the tumor was located in motor areas. Twenty-nine patients had lesions of Broca and Wernicke's areas. All patients underwent preoperative tb-fMRI and rs-fMRI. Then, resection of tumor was carried out in all cases. RESULTS Comparison of fMRI and rs-fMRI activation maps was assessed by calculating the Dice coefficient for inclusive speech and motor cortex masks and exclusive masks without brainstem, cerebellum, subcortical nuclei. Inclusive Dice coefficient for motor cortex ranged from 0.11 to 0.50, for speech cortex - from 0.006 to 0.240 (p<0.05). In case of exclusive masks, this value ranged from 0.15 to 0.55 for motor cortex and from 0.004 to 0.205 for speech cortex (p<0.05). CONCLUSION When comparing the results of cortical mapping in patients with glial tumors, the use of hemispheric exclusive and inclusive masks did not significantly increase activation maps matching. Probably, low degree of correspondence was associated with different genesis of activations, as well as with high variability of speech cortex.
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Affiliation(s)
- A S Smirnov
- Burdenko Neurosurgery Center, Moscow, Russia
| | | | - M G Sharaev
- Skolkovo Institute of Science and Technology, Moscow, Russia
| | - V E Yarkin
- Skolkovo Institute of Science and Technology, Moscow, Russia
| | - A M Turkin
- Burdenko Neurosurgery Center, Moscow, Russia
| | | | - L M Khasieva
- Sechenov First Moscow State Medical University, Moscow, Russia
| | - A V Bernshtein
- Skolkovo Institute of Science and Technology, Moscow, Russia
| | | | - I N Pronin
- Burdenko Neurosurgery Center, Moscow, Russia
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16
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Lee SW, Cha H, Jang TY, Kim E, Song H, Chang Y, Lee SJ. The Neural Correlates of Positive Versus Negative Thought-action Fusion in Healthy Young Adults. CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE 2021; 19:628-639. [PMID: 34690118 PMCID: PMC8553530 DOI: 10.9758/cpn.2021.19.4.628] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 11/03/2020] [Accepted: 12/11/2020] [Indexed: 12/02/2022]
Abstract
Objective Thought-action fusion (TAF), one of the most-studied dysfunctional beliefs in obsessive-compulsive disorder, represents an individual’s belief that his/her thoughts directly influence events. TAF belief types are divided into personal thoughts relating to positive (positive TAF) and negative outcomes (negative TAF). However, the neural mechanisms underlying both aspects of the TAF response remain elusive. Methods This functional magnetic resonance imaging study aimed to investigate the neural circuits related to positive and negative TAF and their relationships with psychological measures. Thirty-one healthy male volunteers participated in a modified TAF task wherein they were asked to read the name of a close person embedded in positive statements (PS) or negative statements (NS). Results Conjunction analysis revealed activation of the fusiform and lingual gyri, midcingulate and superior medial frontal gyri, inferior orbitofrontal gyrus, and temporoparietal junction. The NS > PS comparison showed additional activation in the precuneus and medial prefrontal cortex, superior frontal gyrus, insula, globus pallidus, thalamus, and midbrain. Precuneus activity was associated with the TAF score among these areas. Moreover, activity in the inferior orbitofrontal gyrus, insula, superior, middle and medial frontal gyri, globus pallidus, inferior parietal lobule, and precuneus was associated with dimensional obsessive-compulsive scores. In contrast, the PS > NS comparison revealed no significant activation. Conclusion These results suggest that negative TAF, relative to positive TAF, recruits additional regions for self-referential processing, salience, and habitual responding, which may contribute to the activation of the belief that a negative thought increases the probability of that negative outcome.
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Affiliation(s)
- Sang Won Lee
- Department of Psychiatry, Kyungpook National University Chilgok Hospital, Daegu, Korea.,Departments of Psychiatry, School of Medicine, Kyungpook National University, Daegu, Korea
| | - Hyunsil Cha
- Departments of Medical & Biological Engineering, School of Medicine, Kyungpook National University, Daegu, Korea
| | - Tae Yang Jang
- Departments of Psychiatry, School of Medicine, Kyungpook National University, Daegu, Korea.,Department of Psychiatry, Kyungpook National University Hospital, Daegu, Korea
| | - Eunji Kim
- Departments of Medical & Biological Engineering, School of Medicine, Kyungpook National University, Daegu, Korea
| | - Huijin Song
- Biomedical Research Institute, Seoul National University Hospital, Seoul, Korea
| | - Yongmin Chang
- Department of Molecular Medicine, School of Medicine, Kyungpook National University, Daegu, Korea.,Department of Radiology, Kyungpook National University Hospital, Daegu, Korea
| | - Seung Jae Lee
- Departments of Psychiatry, School of Medicine, Kyungpook National University, Daegu, Korea.,Department of Psychiatry, Kyungpook National University Hospital, Daegu, Korea
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17
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Smith SD, Nadeau C, Sorokopud-Jones M, Kornelsen J. The Relationship Between Functional Connectivity and Interoceptive Sensibility. Brain Connect 2021; 12:417-431. [PMID: 34210151 DOI: 10.1089/brain.2020.0777] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Background: Interoceptive signals related to changes in heartbeat, respiration, and gastric functioning continuously feedback to the brain. The interpretation of these signals influences several cognitive, affective, and motoric functions. Previous research has highlighted the distinction between the ability to accurately detect interoceptive information (i.e., interoceptive accuracy) and an individual's beliefs about his or her interoceptive abilities (i.e., interoceptive sensibility). Although numerous studies have delineated the neural substrates of interoceptive accuracy, less is known about the brain areas involved with interoceptive sensibility. Materials and Methods: In the current study, 28 healthy participants completed the Multidimensional Assessment of Interoceptive Awareness (MAIA), a self-report measure of interoceptive sensibility, before undergoing a 7-min resting-state functional magnetic resonance imaging scan. IRB ethics approval was obtained prior to data collection. Results: Overall MAIA scores, as well as scores on its eight subscales, were entered as covariates in subsequent region-of-interest and independent-component analyses. These analyses yielded three key results. First, interoceptive sensibility was negatively correlated with the functional connectivity of visual regions. Second, the cerebellar resting-state network showed positive correlations with two MAIA subscales, suggesting that this structure plays a role in interoceptive functions. Finally, the functional connectivity of the insula, a structure critical for interoceptive accuracy, was not correlated with any of the MAIA scores. Conclusion: These results demonstrate that the brain areas associated with individual differences in interoceptive sensibility show relatively little overlap with those involved with the accurate detection of interoceptive information.
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Affiliation(s)
- Stephen D Smith
- Department of Psychology, University of Winnipeg, Winnipeg, Canada
| | - Catherine Nadeau
- Department of Psychology, University of Winnipeg, Winnipeg, Canada
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18
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Both activation and deactivation of functional networks support increased sentence processing costs. Neuroimage 2020; 225:117475. [PMID: 33169698 DOI: 10.1016/j.neuroimage.2020.117475] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 10/12/2020] [Accepted: 10/13/2020] [Indexed: 12/28/2022] Open
Abstract
The research on the neural correlates underlying the language system has gradually moved away from the traditional Broca-Wernicke framework to a network perspective in the past 15 years. Language processing is found to be supported by the co-activation of both core and peripheral brain regions. However, the dynamic co-activation patterns of these brain regions serving different language functions remain to be fully revealed. The present functional magnetic resonance imaging (fMRI) study focused on sentence processing at different syntactic complexity levels to examine how the co-activation of different brain networks will be modulated by increased processing costs. Chinese relative clauses were used to probe the two dimensions of syntactic complexity: embeddedness (left-branching vs. center-embedded) and gap-filler dependency (subject-gap vs. object-gap) using the general linear model (GLM) approach, independent component analysis (ICA) and graph theoretical analysis. In contrast to localized activation revealed by the GLM approach, ICA identified more extensive networks both positively and negatively correlated with the task. We found that the posterior default mode network was anti-correlated to the gap-filler integration costs with increased deactivation for the left-branching object relative clauses compared to subject relative clauses, suggesting the involvement of this network in leveraging the cognitive resources based on the complexity level of the language task. Concurrent activation and deactivation of networks were found to be associated with the higher costs induced by center-embedding and its interaction with gap-filler integration. The graph theoretical analysis further unveiled that center-embeddedness imposed more attentional demand on the subject relative clause, as characterized by its higher degree and strength in the ventral attention network, and higher processing costs of syntactic reanalysis on the object relative clause, as characterized by increased intermodular connections of the language network with other networks. The results suggest that network activation and deactivation profiles are modulated by different dimensions of syntactic complexity to serve the higher demand of creating a coherent semantic representation.
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19
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Fedorenko E, Blank IA, Siegelman M, Mineroff Z. Lack of selectivity for syntax relative to word meanings throughout the language network. Cognition 2020; 203:104348. [PMID: 32569894 DOI: 10.1101/477851] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Revised: 05/14/2020] [Accepted: 05/31/2020] [Indexed: 05/25/2023]
Abstract
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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Affiliation(s)
- Evelina Fedorenko
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, USA.
| | - Idan Asher Blank
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; Department of Psychology, UCLA, Los Angeles, CA 90095, USA
| | - Matthew Siegelman
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; Department of Psychology, Columbia University, New York, NY 10027, USA
| | - Zachary Mineroff
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; Eberly Center for Teaching Excellence & Educational Innovation, CMU, Pittsburgh, PA 15213, USA
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20
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Fedorenko E, Blank IA, Siegelman M, Mineroff Z. Lack of selectivity for syntax relative to word meanings throughout the language network. Cognition 2020; 203:104348. [PMID: 32569894 PMCID: PMC7483589 DOI: 10.1016/j.cognition.2020.104348] [Citation(s) in RCA: 72] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Revised: 05/14/2020] [Accepted: 05/31/2020] [Indexed: 12/31/2022]
Abstract
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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Affiliation(s)
- Evelina Fedorenko
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, USA.
| | - Idan Asher Blank
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; Department of Psychology, UCLA, Los Angeles, CA 90095, USA
| | - Matthew Siegelman
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; Department of Psychology, Columbia University, New York, NY 10027, USA
| | - Zachary Mineroff
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; Eberly Center for Teaching Excellence & Educational Innovation, CMU, Pittsburgh, PA 15213, USA
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21
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Blank IA, Fedorenko E. No evidence for differences among language regions in their temporal receptive windows. Neuroimage 2020; 219:116925. [PMID: 32407994 DOI: 10.1016/j.neuroimage.2020.116925] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Revised: 03/20/2020] [Accepted: 05/06/2020] [Indexed: 10/24/2022] Open
Abstract
The "core language network" consists of left frontal and temporal regions that are selectively engaged in linguistic processing. Whereas functional differences among these regions have long been debated, many accounts propose distinctions in terms of representational grain-size-e.g., words vs. phrases/sentences-or processing time-scale, i.e., operating on local linguistic features vs. larger spans of input. Indeed, the topography of language regions appears to overlap with a cortical hierarchy reported by Lerner et al. (2011) wherein mid-posterior temporal regions are sensitive to low-level features of speech, surrounding areas-to word-level information, and inferior frontal areas-to sentence-level information and beyond. However, the correspondence between the language network and this hierarchy of "temporal receptive windows" (TRWs) is difficult to establish because the precise anatomical locations of language regions vary across individuals. To directly test this correspondence, we first identified language regions in each participant with a well-validated task-based localizer, which confers high functional resolution to the study of TRWs (traditionally based on stereotactic coordinates); then, we characterized regional TRWs with the naturalistic story listening paradigm of Lerner et al. (2011), which augments task-based characterizations of the language network by more closely resembling comprehension "in the wild". We find no region-by-TRW interactions across temporal and inferior frontal regions, which are all sensitive to both word-level and sentence-level information. Therefore, the language network as a whole constitutes a unique stage of information integration within a broader cortical hierarchy.
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Affiliation(s)
- Idan A Blank
- Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
| | - Evelina Fedorenko
- Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
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Branco P, Seixas D, Castro SL. Mapping language with resting-state functional magnetic resonance imaging: A study on the functional profile of the language network. Hum Brain Mapp 2020; 41:545-560. [PMID: 31609045 PMCID: PMC7268076 DOI: 10.1002/hbm.24821] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Revised: 09/26/2019] [Accepted: 09/27/2019] [Indexed: 12/05/2022] Open
Abstract
Resting-state functional magnetic resonance imaging (rsfMRI) is a promising technique for language mapping that does not require task-execution. This can be an advantage when language mapping is limited by poor task performance, as is common in clinical settings. Previous studies have shown that language maps extracted with rsfMRI spatially match their task-based homologs, but no study has yet demonstrated the direct participation of the rsfMRI language network in language processes. This demonstration is critically important because spatial similarity can be influenced by the overlap of domain-general regions that are recruited during task-execution. Furthermore, it is unclear which processes are captured by the language network: does it map rather low-level or high-level (e.g., syntactic and lexico-semantic) language processes? We first identified the rsfMRI language network and then investigated task-based responses within its regions when processing stimuli of increasing linguistic content: symbols, pseudowords, words, pseudosentences and sentences. The language network responded only to language stimuli (not to symbols), and higher linguistic content elicited larger brain responses. The left fronto-parietal, the default mode, and the dorsal attention networks were examined and yet none showed language involvement. These findings demonstrate for the first time that the language network extracted through rsfMRI is able to map language in the brain, including regions subtending higher-level syntactic and semantic processes.
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Affiliation(s)
- Paulo Branco
- Centre for PsychologyUniversity of PortoPortoPortugal
- Department of BiomedicineUniversity of PortoPortoPortugal
| | - Daniela Seixas
- Department of BiomedicineUniversity of PortoPortoPortugal
| | - São L. Castro
- Centre for PsychologyUniversity of PortoPortoPortugal
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