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Billot A, Kiran S. Disentangling neuroplasticity mechanisms in post-stroke language recovery. BRAIN AND LANGUAGE 2024; 251:105381. [PMID: 38401381 PMCID: PMC10981555 DOI: 10.1016/j.bandl.2024.105381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 11/28/2023] [Accepted: 01/12/2024] [Indexed: 02/26/2024]
Abstract
A major objective in post-stroke aphasia research is to gain a deeper understanding of neuroplastic mechanisms that drive language recovery, with the ultimate goal of enhancing treatment outcomes. Subsequent to recent advances in neuroimaging techniques, we now have the ability to examine more closely how neural activity patterns change after a stroke. However, the way these neural activity changes relate to language impairments and language recovery is still debated. The aim of this review is to provide a theoretical framework to better investigate and interpret neuroplasticity mechanisms underlying language recovery in post-stroke aphasia. We detail two sets of neuroplasticity mechanisms observed at the synaptic level that may explain functional neuroimaging findings in post-stroke aphasia recovery at the network level: feedback-based homeostatic plasticity and associative Hebbian plasticity. In conjunction with these plasticity mechanisms, higher-order cognitive control processes dynamically modulate neural activity in other regions to meet communication demands, despite reduced neural resources. This work provides a network-level neurobiological framework for understanding neural changes observed in post-stroke aphasia and can be used to define guidelines for personalized treatment development.
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Affiliation(s)
- Anne Billot
- Center for Brain Recovery, Boston University, Boston, USA; Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, USA; Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Swathi Kiran
- Center for Brain Recovery, Boston University, Boston, USA.
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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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Zhu H, Fitzhugh MC, Keator LM, Johnson L, Rorden C, Bonilha L, Fridriksson J, Rogalsky C. How can graph theory inform the dual-stream model of speech processing? a resting-state fMRI study of post-stroke aphasia. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.17.537216. [PMID: 37131756 PMCID: PMC10153155 DOI: 10.1101/2023.04.17.537216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
The dual-stream model of speech processing has been proposed to represent the cortical networks involved in speech comprehension and production. Although it is arguably the prominent neuroanatomical model of speech processing, it is not yet known if the dual-stream model represents actual intrinsic functional brain networks. Furthermore, it is unclear how disruptions after a stroke to the functional connectivity of the dual-stream model's regions are related to specific types of speech production and comprehension impairments seen in aphasia. To address these questions, in the present study, we examined two independent resting-state fMRI datasets: (1) 28 neurotypical matched controls and (2) 28 chronic left-hemisphere stroke survivors with aphasia collected at another site. Structural MRI, as well as language and cognitive behavioral assessments, were collected. Using standard functional connectivity measures, we successfully identified an intrinsic resting-state network amongst the dual-stream model's regions in the control group. We then used both standard functional connectivity analyses and graph theory approaches to determine how the functional connectivity of the dual-stream network differs in individuals with post-stroke aphasia, and how this connectivity may predict performance on clinical aphasia assessments. Our findings provide strong evidence that the dual-stream model is an intrinsic network as measured via resting-state MRI, and that weaker functional connectivity of the hub nodes of the dual-stream network defined by graph theory methods, but not overall average network connectivity, is weaker in the stroke group than in the control participants. Also, the functional connectivity of the hub nodes predicted specific types of impairments on clinical assessments. In particular, the relative strength of connectivity of the right hemisphere's homologues of the left dorsal stream hubs to the left dorsal hubs versus right ventral stream hubs is a particularly strong predictor of post-stroke aphasia severity and symptomology.
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Low TA, Lindland K, Kirton A, Carlson HL, Harris AD, Goodyear BG, Monchi O, Hill MD, Dukelow SP. Repetitive transcranial magnetic stimulation (rTMS) combined with multi-modality aphasia therapy for chronic post-stroke non-fluent aphasia: A pilot randomized sham-controlled trial. BRAIN AND LANGUAGE 2023; 236:105216. [PMID: 36525719 DOI: 10.1016/j.bandl.2022.105216] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Revised: 10/22/2022] [Accepted: 12/03/2022] [Indexed: 06/17/2023]
Abstract
Repetitive transcranial magnetic stimulation (rTMS) shows promise in improving speech production in post-stroke aphasia. Limited evidence suggests pairing rTMS with speech therapy may result in greater improvements. Twenty stroke survivors (>6 months post-stroke) were randomized to receive either sham rTMS plus multi-modality aphasia therapy (M-MAT) or rTMS plus M-MAT. For the first time, we demonstrate that rTMS combined with M-MAT is feasible, with zero adverse events and minimal attrition. Both groups improved significantly over time on all speech and language outcomes. However, improvements did not differ between rTMS or sham. We found that rTMS and sham groups differed in lesion location, which may explain speech and language outcomes as well as unique patterns of BOLD signal change within each group. We offer practical considerations for future studies and conclude that while combination therapy of rTMS plus M-MAT in chronic post-stroke aphasia is safe and feasible, personalized intervention may be necessary.
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Affiliation(s)
- Trevor A Low
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Kevin Lindland
- Department of Allied Health, Alberta Health Services, Calgary, Alberta, Canada
| | - Adam Kirton
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Department of Pediatrics, Cummings School of Medicine, University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Helen L Carlson
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Department of Pediatrics, Cummings School of Medicine, University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Ashley D Harris
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Bradley G Goodyear
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Oury Monchi
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Michael D Hill
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Sean P Dukelow
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Division of Physical Medicine and Rehabilitation, University of Calgary, Calgary, Alberta, Canada.
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Yan Z, Xu S, Wei D, He X, Li C, Zhang Y, Chen M, Zhang J, Li X, Yang Q, Jia J. Comparison of three cognitive assessment methods in post-stroke aphasia patients. Front Psychol 2022; 13:896095. [PMID: 36337480 PMCID: PMC9631299 DOI: 10.3389/fpsyg.2022.896095] [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: 06/11/2022] [Accepted: 09/29/2022] [Indexed: 11/19/2022] Open
Abstract
Background The cognitive level of post-stroke aphasia (PSA) patients is generally lower than non-aphasia patients, and cognitive impairment (CI) affects the outcome of stroke. However, for different types of PSA, what kind of cognitive assessment methods to choose is not completely clear. We investigated the Montreal Cognitive Assessment (MoCA), the Mini-Mental State Examination (MMSE), and the Non-language-based Cognitive Assessment (NLCA) to observe the evaluation effect of CI in patients with fluent aphasia (FA) and non-fluent aphasia (NFA). Methods 92 stroke patients were included in this study. Demographic and clinical data of the stroke group were documented. The language and cognition were evaluated by Western Aphasia Battery (WAB), MoCA, MMSE, and NLCA. PSA were divided into FA and NFA according to the Chinese aphasia fluency characteristic scale. Pearson’s product–moment correlation coefficient test and multiple linear regression analysis were performed to explore the relationship between the sub-items of WAB and cognitive scores. The classification rate of CI was tested by Pearson’s Chi-square test or Fisher’s exact test. Results The scores of aphasia quotient (AQ), MoCA, MMSE, and NLCA in NFA were lower than FA. AQ was positively correlated with MoCA, MMSE, and NLCA scores. Stepwise multiple linear regression analysis suggested that naming explained 70.7% of variance of MoCA and 79.9% of variance of MMSE; comprehension explained 46.7% of variance of NLCA. In the same type of PSA, there was no significant difference in the classification rate. The classification rate of CI in NFA by MoCA and MMSE was higher than that in FA. There was no significant difference in the classification rate of CI between FA and NFA by NLCA. Conclusion MoCA, MMSE, and NLCA can be applied in FA. NLCA is recommended for NFA.
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Affiliation(s)
- Zhijie Yan
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
- Department of Rehabilitation Medicine, The Third Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Shuo Xu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Dongshuai Wei
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Xinyuan He
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Chong Li
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Yongli Zhang
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Mengye Chen
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Jingna Zhang
- Department of Rehabilitation Medicine, The Third Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Xiaofang Li
- Department of Rehabilitation Medicine, The Third Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Qing Yang
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
- *Correspondence: Qing Yang,
| | - Jie Jia
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
- Jie Jia,
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