@article{MaetzigVasishthEngelmannetal.2018,
  author    = {M{\"a}tzig, Paul and Vasishth, Shravan and Engelmann, Felix and Caplan, David and Burchert, Frank},
  title     = {A computational investigation of sources of variability in sentence comprehension difficulty in aphasia},
  series = {Topics in cognitive science},
  volume    = {10},
  journal   = {Topics in cognitive science},
  number    = {1},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {1756-8757},
  doi       = {10.1111/tops.12323},
  pages     = {161 -- 174},
  year      = {2018},
  abstract  = {We present a computational evaluation of three hypotheses about sources of deficit in sentence comprehension in aphasia: slowed processing, intermittent deficiency, and resource reduction. The ACT-R based Lewis and Vasishth (2005) model is used to implement these three proposals. Slowed processing is implemented as slowed execution time of parse steps; intermittent deficiency as increased random noise in activation of elements in memory; and resource reduction as reduced spreading activation. As data, we considered subject vs. object relative sentences, presented in a self-paced listening modality to 56 individuals with aphasia (IWA) and 46 matched controls. The participants heard the sentences and carried out a picture verification task to decide on an interpretation of the sentence. These response accuracies are used to identify the best parameters (for each participant) that correspond to the three hypotheses mentioned above. We show that controls have more tightly clustered (less variable) parameter values than IWA; specifically, compared to controls, among IWA there are more individuals with slow parsing times, high noise, and low spreading activation. We find that (a) individual IWA show differential amounts of deficit along the three dimensions of slowed processing, intermittent deficiency, and resource reduction, (b) overall, there is evidence for all three sources of deficit playing a role, and (c) IWA have a more variable range of parameter values than controls. An important implication is that it may be meaningless to talk about sources of deficit with respect to an abstract verage IWA; the focus should be on the individual's differential degrees of deficit along different dimensions, and on understanding the causes of variability in deficit between participants.},
  language  = {en}
}
@misc{MaruschJaegerNeissetal.2018,
  author    = {Marusch, Tina and J{\"a}ger, Lena Ann and Neiß, Leander and Burchert, Frank and Nickels, Lyndsey},
  title     = {Overt language production of German past participles},
  series = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe},
  number    = {492},
  issn      = {1866-8364},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-420621},
  pages     = {21},
  year      = {2018},
  abstract  = {We report two experiments and Bayesian modelling of the data collected. In both experiments, participants performed a long-lag primed picture naming task. Black-and-white line drawings were used as targets, which were overtly named by the participants. Their naming latencies were measured. In both experiments, primes consisted of past participle verbs (er tanzt/er hat getanzt "he dances/he has danced") and the relationship between primes and targets was either morphological or unrelated. Experiment 1 additionally had phonologically and semantically related prime-target pairs as well as present tense primes. Both in Experiment 1 and 2, participants showed significantly faster naming latencies for morphologically related targets relative to the unrelated verb primes. In Experiment 1, no priming effects were observed in phonologically and semantically related control conditions. In addition, the production latencies were not influenced by verb type.},
  language  = {en}
}