TY  - GEN
A1  - Arslan, Seçkin
A1  - Felser, Claudia
T1  - Comprehension of wh-questions in Turkish–German bilinguals with aphasia
BT  - a dual-case study
T2  - Postprints der Universität Potsdam : Humanwissenschaftliche Reihe
N2  - The aim of our study was to examine the extent to which linguistic
approaches to sentence comprehension deficits in aphasia can
account for differential impairment patterns in the comprehension
of wh-questions in bilingual persons with aphasia (PWA). We investi-
gated the comprehension of subject and object wh-questions in both
Turkish, a wh-in-situ language, and German, a wh-fronting language,
in two bilingual PWA using a sentence-to-picture matching task. Both
PWA showed differential impairment patterns in their two languages.
SK, an early bilingual PWA, had particular difficulty comprehending
subject which-questions in Turkish but performed normal across all
conditions in German. CT, a late bilingual PWA, performed more
poorly for object which-questions in German than in all other condi-
tions, whilst in Turkish his accuracy was at chance level across all
conditions. We conclude that the observed patterns of selective
cross-linguistic impairments cannot solely be attributed either to
difficulty with wh-movement or to problems with the integration of
discourse-level information. Instead our results suggest that differ-
ences between our PWA’s individual bilingualism profiles (e.g. onset
of bilingualism, premorbid language dominance) considerably
affected the nature and extent of their impairments.
T3  - Zweitveröffentlichungen der Universität Potsdam : Humanwissenschaftliche Reihe - 462 
KW  - bilingual aphasia
KW  - wh- questions
KW  - Turkish-German bilingualism
KW  - wh-in-situ
KW  - wh- movement
Y1  - 2018
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-412813
IS  - 462
ER  - 
TY  - JOUR
A1  - Arslan, Seçkin
A1  - Gür, Eren
A1  - Felser, Claudia
T1  - Predicting the sources of impaired wh-question comprehension in non-fluent aphasia
BT  - a cross-linguistic machine learning study on Turkish and German
JF  - Cognitive neuropsychology
N2  - This study investigates the comprehension of wh-questions in individuals with aphasia (IWA) speaking Turkish, a non-wh-movement language, and German, a wh-movement language. We examined six German-speaking and 11 Turkish-speaking IWA using picture-pointing tasks. Findings from our experiments show that the Turkish IWA responded more accurately to both object who and object which questions than to subject questions, while the German IWA performed better for subject which questions than in all other conditions. Using random forest models, a machine learning technique used in tree-structured classification, on the individual data revealed that both the Turkish and German IWA’s response accuracy is largely predicted by the presence of overt and unambiguous case marking. We discuss our results with regard to different theoretical approaches to the comprehension of wh-questions in aphasia.
KW  - Non-fluent aphasia
KW  - random forest algorithm
KW  - sentence comprehension
KW  - wh-in-situ
KW  - wh-questions
KW  - wh-movement
Y1  - 2017
U6  - https://doi.org/10.1080/02643294.2017.1394284
SN  - 0264-3294
SN  - 1464-0627
VL  - 34
SP  - 312
EP  - 331
PB  - Taylor & Francis
CY  - Abingdon
ER  - 
TY  - GEN
A1  - Arslan, Seçkin
A1  - Gür, Eren
A1  - Felser, Claudia
T1  - Predicting the sources of impaired wh-question comprehension in non-fluent aphasia
BT  - a cross-linguistic machine learning study on Turkish and German
T2  - Postprints der Universität Potsdam : Humanwissenschaftliche Reihe
N2  - This study investigates the comprehension of wh-questions in individuals with aphasia (IWA) speaking Turkish, a non-wh-movement language, and German, a wh-movement language. We examined six German-speaking and 11 Turkish-speaking IWA using picture-pointing tasks. Findings from our experiments show that the Turkish IWA responded more accurately to both object who and object which questions than to subject questions, while the German IWA performed better for subject which questions than in all other conditions. Using random forest models, a machine learning technique used in tree-structured classification, on the individual data revealed that both the Turkish and German IWA’s response accuracy is largely predicted by the presence of overt and unambiguous case marking. We discuss our results with regard to different theoretical approaches to the comprehension of wh-questions in aphasia.
T3  - Zweitveröffentlichungen der Universität Potsdam : Humanwissenschaftliche Reihe - 464 
KW  - Non-fluent aphasia
KW  - random forest algorithm
KW  - sentence comprehension
KW  - wh-in-situ
KW  - wh-questions
KW  - wh-movement
Y1  - 2018
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-412717
IS  - 464
ER  -