Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/185984
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Grasemann, Uli | - |
dc.contributor.author | Peñaloza, Claudia | - |
dc.contributor.author | Dekhtyar, Maria | - |
dc.contributor.author | Miikkulainen, Risto | - |
dc.contributor.author | Kiran, Swathi | - |
dc.date.accessioned | 2022-05-24T16:54:51Z | - |
dc.date.available | 2022-05-24T16:54:51Z | - |
dc.date.issued | 2021-05-18 | - |
dc.identifier.issn | 2045-2322 | - |
dc.identifier.uri | http://hdl.handle.net/2445/185984 | - |
dc.description.abstract | Predicting language therapy outcomes in bilinguals with aphasia (BWA) remains challenging due to the multiple pre- and poststroke factors that determine the defcits and recovery of their two languages. Computational models that simulate language impairment and treatment outcomes in BWA can help predict therapy response and identify the optimal language for treatment. Here we used the BiLex computational model to simulate the behavioral profle of language defcits and treatment response of a retrospective sample of 13 Spanish-English BWA who received therapy in one of their languages. Specifcally, we simulated their prestroke naming ability and poststroke naming impairment in each language, and their treatment response in the treated and the untreated language. BiLex predicted treatment efects accurately and robustly in the treated language and captured diferent degrees of cross-language generalization in the untreated language in BWA. Our cross-validation approach further demonstrated that BiLex generalizes to predict treatment response for patients whose data were not used in model training. These fndings support the potential of BiLex to predict therapy outcomes for BWA and suggest that computational modeling may be helpful to guide individually tailored rehabilitation plans for this population. | - |
dc.format.extent | 11 p. | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | eng | - |
dc.publisher | Nature Publishing Group | - |
dc.relation.isformatof | Reproducció del document publicat a: https://doi.org/10.1038/s41598-021-89443-6 | - |
dc.relation.ispartof | Scientific Reports, 2021, vol. 11, p. 10497 | - |
dc.relation.uri | https://doi.org/10.1038/s41598-021-89443-6 | - |
dc.rights | cc-by (c) Grasemann, Uli et al., 2021 | - |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
dc.source | Articles publicats en revistes (Cognició, Desenvolupament i Psicologia de l'Educació) | - |
dc.subject.classification | Afàsia | - |
dc.subject.classification | Trastorns del llenguatge | - |
dc.subject.classification | Logopèdia | - |
dc.subject.classification | Bilingüisme | - |
dc.subject.classification | Xarxes neuronals (Informàtica) | - |
dc.subject.other | Aphasia | - |
dc.subject.other | Language disorders | - |
dc.subject.other | Speech therapy | - |
dc.subject.other | Bilingualism | - |
dc.subject.other | Neural networks (Computer science) | - |
dc.title | Predicting language treatment response in bilingual aphasia using neural network-based patient models | - |
dc.type | info:eu-repo/semantics/article | - |
dc.type | info:eu-repo/semantics/publishedVersion | - |
dc.identifier.idgrec | 712561 | - |
dc.date.updated | 2022-05-24T16:54:51Z | - |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | - |
Appears in Collections: | Articles publicats en revistes (Cognició, Desenvolupament i Psicologia de l'Educació) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
712561.pdf | 2.55 MB | Adobe PDF | View/Open |
This item is licensed under a
Creative Commons License