@misc{GallitWyschkonPoltzetal.2018,
  author    = {Gallit, Finja and Wyschkon, Anne and Poltz, Nadine and Moraske, Svenja and Kucian, Karin and von Aster, Michael G. and Esser, G{\"u}nter},
  title     = {Henne oder Ei},
  series = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe},
  number    = {632},
  issn      = {1866-8364},
  doi       = {10.25932/publishup-44135},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-441356},
  pages     = {81 -- 92},
  year      = {2018},
  abstract  = {Fragestellung: Ziel war die Untersuchung der Entwicklung und wechselseitigen Beziehung von Zahlen- und Mengenvorwissen (ZMW), Arbeitsged{\"a}chtnis (AG) und Intelligenz sowie deren Vorhersagekraft f{\"u}r die Rechenleistung in der ersten Klasse. Methodik: 1897 Kindergartenkinder nahmen an dieser Studie teil. Ein Teil dieser Kinder wurde 9 Monate sp{\"a}ter und erneut in der ersten Klasse untersucht. Ergebnisse: W{\"a}hrend des Kindergartenjahres verbesserten sich die Kinder in allen untersuchten Leistungen. Reziproke Zusammenh{\"a}nge zwischen den drei erhobenen Vorl{\"a}uferf{\"a}higkeiten konnten nachgewiesen werden. Das ZMW erwies sich als guter Pr{\"a}diktor f{\"u}r die AG- und Intelligenzleistung. Bei der {\"U}berpr{\"u}fung der Vorhersage des Rechnens erwies sich das ZMW als bester Pr{\"a}diktor der sp{\"a}teren Rechenleistung. Erwartungsgem{\"a}ß zeigten die zu t1 erfassten allgemein-kognitiven Leistungen indirekte Effekte {\"u}ber das ZMW auf die Rechenleistung. Die Intelligenz und das AG zu t2 konnten direkt zur Vorhersage des Rechnens in der ersten Klasse beitragen. Schlussfolgerungen: Die Ergebnisse verdeutlichen, dass das AG und die Intelligenz zwar an dem Aufbau des ZMW beteiligt sind, aber vor allem selbst durch dieses vorhergesagt werden. Die Daten sprechen daf{\"u}r das Potenzial des ZMWs in Trainingsprogrammen zu nutzen, durch dessen F{\"o}rderung auch intellektuelle und Ged{\"a}chtnisleistungen zunehmen k{\"o}nnen, die allesamt die schulische Rechenleistung positiv beeinflussen.},
  language  = {de}
}
@phdthesis{Zakarias2018,
  author    = {Zakari{\´a}s, Lilla},
  title     = {Transfer effects after working memory training in post-stroke aphasia},
  doi       = {10.25932/publishup-42360},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-423600},
  school      = {Universit{\"a}t Potsdam},
  pages     = {178},
  year      = {2018},
  abstract  = {Background: Individuals with aphasia after stroke (IWA) often present with working memory (WM) deficits. Research investigating the relationship between WM and language abilities has led to the promising hypothesis that treatments of WM could lead to improvements in language, a phenomenon known as transfer. Although recent treatment protocols have been successful in improving WM, the evidence to date is scarce and the extent to which improvements in trained tasks of WM transfer to untrained memory tasks, spoken sentence comprehension, and functional communication is yet poorly understood. Aims: We aimed at (a) investigating whether WM can be improved through an adaptive n-back training in IWA (Study 1-3); (b) testing whether WM training leads to near transfer to unpracticed WM tasks (Study 1-3), and far transfer to spoken sentence comprehension (Study 1-3), functional communication (Study 2-3), and memory in daily life in IWA (Study 2-3); and (c) evaluating the methodological quality of existing WM treatments in IWA (Study 3). To address these goals, we conducted two empirical studies - a case-controls study with Hungarian speaking IWA (Study 1) and a multiple baseline study with German speaking IWA (Study 2) - and a systematic review (Study 3). Methods: In Study 1 and 2 participants with chronic, post-stroke aphasia performed an adaptive, computerized n-back training. 'Adaptivity' was implemented by adjusting the tasks' difficulty level according to the participants' performance, ensuring that they always practiced at an optimal level of difficulty. To assess the specificity of transfer effects and to better understand the underlying mechanisms of transfer on spoken sentence comprehension, we included an outcome measure testing specific syntactic structures that have been proposed to involve WM processes (e.g., non-canonical structures with varying complexity). Results: We detected a mixed pattern of training and transfer effects across individuals: five participants out of six significantly improved in the n-back training. Our most important finding is that all six participants improved significantly in spoken sentence comprehension (i.e., far transfer effects). In addition, we also found far transfer to functional communication (in two participants out of three in Study 2) and everyday memory functioning (in all three participants in Study 2), and near transfer to unpracticed n-back tasks (in four participants out of six). Pooled data analysis of Study 1 and 2 showed a significant negative relationship between initial spoken sentence comprehension and the amount of improvement in this ability, suggesting that the more severe the participants' spoken sentence comprehension deficit was at the beginning of training, the more they improved after training. Taken together, we detected both near far and transfer effects in our studies, but the effects varied across participants. The systematic review evaluating the methodological quality of existing WM treatments in stroke IWA (Study 3) showed poor internal and external validity across the included 17 studies. Poor internal validity was mainly due to use of inappropriate design, lack of randomization of study phases, lack of blinding of participants and/or assessors, and insufficient sampling. Low external validity was mainly related to incomplete information on the setting, lack of use of appropriate analysis or justification for the suitability of the analysis procedure used, and lack of replication across participants and/or behaviors. Results in terms of WM, spoken sentence comprehension, and reading are promising, but further studies with more rigorous methodology and stronger experimental control are needed to determine the beneficial effects of WM intervention. Conclusions: Results of the empirical studies suggest that WM can be improved with a computerized and adaptive WM training, and improvements can lead to transfer effects to spoken sentence comprehension and functional communication in some individuals with chronic post-stroke aphasia. The fact that improvements were not specific to certain syntactic structures (i.e., non-canonical complex sentences) in spoken sentence comprehension suggest that WM is not involved in the online, automatic processing of syntactic information (i.e., parsing and interpretation), but plays a more general role in the later stage of spoken sentence comprehension (i.e., post-interpretive comprehension). The individual differences in treatment outcomes call for future research to clarify how far these results are generalizable to the population level of IWA. Future studies are needed to identify a few mechanisms that may generalize to at least a subpopulation of IWA as well as to investigate baseline non-linguistic cognitive and language abilities that may play a role in transfer effects and the maintenance of such effects. These may require larger yet homogenous samples.},
  language  = {en}
}