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Observation of new excited ${B} ^0_{s} $ states
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In: Eur.Phys.J.C ; https://hal.archives-ouvertes.fr/hal-03010999 ; Eur.Phys.J.C, 2021, 81 (7), pp.601. ⟨10.1140/epjc/s10052-021-09305-3⟩ (2021)
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sj-docx-1-ijb-10.1177_13670069211022851 – Supplemental material for Language changes medical judgments and beliefs ...
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sj-docx-1-ijb-10.1177_13670069211022851 – Supplemental material for Language changes medical judgments and beliefs ...
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Pre-treatment graph measures of a functional semantic network are associated with naming therapy outcomes in chronic aphasia
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In: Brain Lang (2020)
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A lesion and connectivity-based hierarchical model of chronic aphasia recovery dissociates patients and healthy controls
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A lesion and connectivity-based hierarchical model of chronic aphasia recovery dissociates patients and healthy controls
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Treatment-related changes in neural activation vary according to treatment response and extent of spared tissue in patients with chronic aphasia
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In: Cortex (2019)
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The utility of lesion classification in predicting language and treatment outcomes in chronic stroke-induced aphasia
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In: Brain Imaging Behav (2019)
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Abstract:
Stroke recovery models can improve prognostication of therapy response in patients with chronic aphasia, yet quantifying the effect of lesion on recovery is challenging. This study aimed to evaluate the utility of lesion classification via gray matter (GM)-only versus combined GM plus white matter (WM) metrics and to determine structural measures associated with aphasia severity, naming skills, and treatment outcomes. Thirty-four patients with chronic aphasia due to left hemisphere infarct completed T1-weighted and DTI scans and language assessments prior to receiving a 12-week naming treatment. GM metrics included the amount of spared tissue within five cortical masks. WM integrity was indexed by spared tissue and fractional anisotropy (FA) from four homologous left and right association tracts. Clustering of GM-only and GM+WM metrics via k-medoids yielded four patient clusters that captured two lesion characteristics, size and location. Linear regression models revealed that both GM-only and GM+WM clustering predicted baseline aphasia severity and naming skills, but only GM+WM clustering predicted treatment outcomes. Spearman correlations revealed that without controlling for lesion volume, the majority of left hemisphere metrics were related to language measures. However, adjusting for lesion volume, no relationships with aphasia severity remained significant. FA from two ventral left WM tracts was related to naming and treatment success, independent of lesion size. In sum, lesion volume and GM metrics are sufficient predictors of overall aphasia severity in patients with chronic stroke, whereas diffusion metrics reflecting WM tract integrity may add predictive power to language recovery outcomes after rehabilitation.
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Keyword:
Article
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URL: http://www.ncbi.nlm.nih.gov/pubmed/31093842
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6527352/
https://doi.org/10.1007/s11682-019-00118-3
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Spousal Concordance in Academic Achievements and Intelligence and Family-Based Association Studies Identified Novel Loci Associated with Intelligence.
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In: Electronic Theses and Dissertations (2010)
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