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Multimodal Neural and Behavioral Data Predict Response to Rehabilitation in Chronic Poststroke Aphasia
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In: Stroke (2022)
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Selective Functional Network Changes Following tDCS-Augmented Language Treatment in Primary Progressive Aphasia
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In: Front Aging Neurosci (2021)
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Predicting language recovery in post-stroke aphasia using behavior and functional MRI
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In: Sci Rep (2021)
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Distinct Neural Substrates Support Phonological and Orthographic Working Memory: Implications for Theories of Working Memory
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Distinct Neural Substrates Support Phonological and Orthographic Working Memory: Implications for Theories of Working Memory
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In: Front Neurol (2021)
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A Tool for Automatic Scoring of Spelling Performance
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In: J Speech Lang Hear Res (2020)
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Reading Proficiency Influences the effects of Transcranial Direct Current Stimulation: Evidence from Selective Modulation of Dorsal and Ventral Pathways of reading in Bilinguals
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In: Brain Lang (2020)
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Different patterns of functional network re-organization across the variants of primary progressive aphasia: A graph theoretic analysis
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In: Neurobiol Aging (2020)
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Reliability of BOLD signals in chronic stroke-induced aphasia ...
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Language network re-organization associated with word- and sentence-level language interventions in chronic aphasia ...
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The use of spelling for variant classification in primary progressive aphasia: Theoretical and practical implications
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In: Neuropsychologia (2019)
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Abstract:
Currently, variant subtyping in primary progressive aphasia (PPA) requires an expert neurologist and extensive language and cognitive testing. Spelling impairments appear early in the development of the disorder, and the three PPA variants (non-fluent - nfvPPA; semantic - svPPA; logopenic - lvPPA) reportedly show fairly distinct spelling profiles. Given the theoretical and empirical evidence indicating that spelling may serve as a proxy for spoken language, the current study aimed to determine whether spelling performance alone, when evaluated with advanced statistical analyses, allows for accurate PPA variant classification. A spelling to dictation task (with real words and pseudowords) was administered to 33 PPA individuals: 17 lvPPA, 10 nfvPPA, 6 svPPA. Using machine learning classification algorithms, we obtained pairwise variant classification accuracies that ranged between 67 and 100%. In additional analyses that assumed no prior knowledge of each case's variant, classification accuracies ranged between 59 and 70%. To our knowledge, this is the first time that all the PPA variants, including the most challenging logopenic variant, have been classified with such high accuracy when using information from a single language task. These results underscore the rich structure of the spelling process and support the use of a spelling task in PPA variant classification.
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Article
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URL: https://doi.org/10.1016/j.neuropsychologia.2019.107157 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6817413/ http://www.ncbi.nlm.nih.gov/pubmed/31401078
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Local response heterogeneity indexes experience-based neural differentiation in reading
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Learning in complex, multi-component cognitive systems: Different learning challenges within the same system
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In: J Exp Psychol Learn Mem Cogn (2018)
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Right hemisphere grey matter volume and language functions in stroke aphasia
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Intrahemispheric Perfusion in Chronic Stroke-Induced Aphasia
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Right Hemisphere Grey Matter Volume and Language Functions in Stroke Aphasia
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Intrahemispheric Perfusion in Chronic Stroke-Induced Aphasia
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Right Hemisphere Grey Matter Volume and Language Functions in Stroke Aphasia
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