P25.1 ERP evidence of therapy-related reorganization of language of patients with post stroke chronic aphasia

2011 ◽  
Vol 122 ◽  
pp. S172 ◽  
Author(s):  
J.P. Lara ◽  
M.A. Barbancho ◽  
M.L. Berthier ◽  
C. Green ◽  
P. Navas ◽  
...  
Keyword(s):  
Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Caroline Schnakers ◽  
Zhong Sheng Zheng ◽  
Henry Millan ◽  
Sharon Lee ◽  
Melissa Howard ◽  
...  

Background: There is growing evidence even amongst those with chronic aphasia that transcranial direct current stimulation (tDCS) combined with behavioral speech therapy could boost language. However, current findings do not allow making strong recommendations for using tDCS in order to improve language in post-stroke aphasia. The efficacy of tDCS therefore still needs to be established using double-blind controlled randomized trials in large samples. Intervention: In this ongoing double-blind randomized placebo controlled trial study, participants were randomly assigned either to the tDCS group or to the sham group. Both groups had five consecutive days of 20 minutes session, using a FDA approved tDCS device (soterixmedical.com). Behavioral and neuroimaging data were performed the week before/after tDCS/sham intervention and again 3 months following treatment. Participants: 42 post-stroke patients with chronic aphasia (32 males; age: 61±11y; 0.9-18years post-injury; 32 ischemic stroke; 19 non-fluent aphasia). Eighteen patients were in the tDCS group. Main Outcome Measures: The Western Aphasia Battery-Revised (WAB-R), Communication Outcomes after Stroke, patient and family report (COAST). MRI Diffusion Tensor Imaging data (64 dir) were also collected. Statistical Analyses: Anova with repeated measures was used on the behavioral outcome measures with aphasia severity, age and time since injury as covariates in SPSS. The average fractional anisotropy (FA) and mean diffusivity (MD) were extracted per ROI from each participant and timepoint. Main Results: a) Behavioral. Groups differed, pre/post intervention, on the WAB-R total score, for the Auditory-Verbal Comprehension and Repetition subscores; b) Neuroimaging. Change in Spontaneous Speech and Auditory Verbal Comprehension negatively correlated with change in mean MD and FA, respectively, in Superior Cerebellar Peduncle for tDCS, but not sham. Conclusion: Our preliminary findings show a higher improvement in language functions (for both receptive and expressive language skills) in response to treatment (vs. sham). Neuroplasticity was observed in superior cerebellar peduncle in response to tDCS mediated language improvement.


Aphasiology ◽  
2021 ◽  
pp. 1-11
Author(s):  
Rosaria De Luca ◽  
Simona Leonardi ◽  
Giuseppa Maresca ◽  
Foti Cuzzola Marilena ◽  
Desiree Latella ◽  
...  

2020 ◽  
Author(s):  
Michael Iorga ◽  
James Higgins ◽  
David Caplan ◽  
Richard Zinbarg ◽  
Swathi Kiran ◽  
...  

Abstract Background: Language outcomes after speech and language therapy in post-stroke aphasia are challenging to predict. This study examines behavioral language measures and resting state fMRI (rsfMRI) as prognostics for response to language therapy. Methods: Seventy patients with chronic aphasia were recruited and treated for one of three deficits: anomia, agrammatism, or dysgraphia. Treatment effect was measured by performance on a treatment-specific language measure, assessed before and after three months of language therapy. Each patient also underwent an additional 27 language assessments and an fMRI scan at baseline. Patient scans were decomposed into 20 components by group independent component analysis, and each component time series was summarized by its fractional amplitude of low-frequency fluctuations (fALFF). Results: Treatment effects were modelled with elastic net regression, using clinical language measures and fALFF imaging predictors independently. Correlation analyses showed high performance for language measures in anomia (r = 0.958, n = 30) and for fALFF predictors in agrammatism (r = 0.940, n = 11) and dysgraphia (r = 0.925, n = 18). These models are state-of-the-art for aphasia recovery prediction. Conclusion: Predicting aphasia recovery with rsfMRI features may outperform predictions from clinical language measures in some patient populations. This suggests rsfMRI may have prognostic value for chronic aphasia patients undergoing language therapy. Differentiating patients who respond to therapy from those who do not is a first step towards personalized treatment in post-stroke aphasia.


Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Barbara K Marebwa ◽  
Julius Fridriksson ◽  
Grigori Yourganov ◽  
Lynda Feenaughty ◽  
Chris Rorden ◽  
...  

Introduction: Many stroke survivors who suffer from aphasia in the acute period experience spontaneous recovery within the first six months post-stroke. About 20% sustain permanent and disabling language problems and the factors that drive incomplete recovery are not clear. Cortical dysfunction may occur in areas seemingly spared by the stroke due to changes to metabolism as well as loss of white matter connectivity and disruption of cortical and subcortical network integrity. We hypothesized that residual white matter connectivity could provide a personalized predictor of the severity of chronic aphasia. Methods: We reconstructed the individual structural whole-brain connectome from 90 right handed participants with a single left hemisphere ischemic or hemorrhagic stroke. All participants underwent language assessment using the Western Aphasia Battery (WAB-AQ). Data analysis was performed on each subject’s individual connectome, a weighted adjacency matrix M of size 189 x 189. We measured comprehensive white matter topological network organization using Newman’s modularity algorithm and calculated the probability of brain regions clustering together though a community affiliation index, which was used to determine the structural fragmentation of white matter networks in the left hemisphere relative to right hemisphere, expressed by a fragmentation index. Results: Patients with greater post-stroke left hemisphere network fragmentation and higher modularity index had more severe chronic aphasia, controlling for the size of the stroke lesion. Modularity and fragmentation index significantly increased with aphasia severity (r = -0.42), and (r = -0.43) respectively. Even when the left hemisphere was relatively spared, patients with disorganized community structure had significantly worse aphasia. Conclusion: Our findings confirm that residual white matter integrity and disorganization of neuronal networks are important determinants of chronic aphasia severity. Furthermore, the assessment of residual connectome white matter organization through modularity provides a comprehensive and personalized measurement that may be used as a marker for clinical staging and aphasia treatment planning.


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