TY - JOUR A1 - Lotz, Anja A1 - Kinder, Annette A1 - Lachnit, Harald T1 - Multiple regression analyses in artificial-grammar learning : the importance of control groups N2 - In artificial-grammar learning, it is crucial to ensure that above-chance performance in the test stage is due to learning in the training stage but not due to judgemental biases. Here we argue that multiple regression analysis call be successfully combined with the use of control groups to assess whether participants were able to transfer knowledge acquired during training where making judgements about test stimuli. We compared the regression weights of judgements in a transfer condition (training and test strings were constructed by the same grammar but with different letters) with those in a control condition. Predictors were identical in both conditions-judgements of control participants were treated as if they were based oil knowledge gained in a standard training stage. The results of this experiment as well as reanalyses of a former study support the usefulness of our approach. Y1 - 2009 UR - http://www.informaworld.com/openurl?genre=journal&issn=1747-0218 U6 - https://doi.org/10.1080/17470210802103739 SN - 1747-0218 ER - TY - JOUR A1 - Kinder, Annette A1 - Rolfs, Martin A1 - Kliegl, Reinhold T1 - Sequence learning at optimal stimulus-response mapping : evidence from a serial reaction-time task N2 - We propose a new version of the serial reaction time (SRT) task in which participants merely looked at the target instead of responding manually. As response locations were identical to target locations, stimulus - response compatibility was maximal in this task. We demonstrated that saccadic response times decreased during training and increased again when a new sequence was presented. It is unlikely that this effect was caused by stimulus - response (S - R) learning because bonds between (visual) stimuli and (oculomotor) responses were already well established before the experiment started. Thus, the finding shows that the building of S - R bonds is not essential for learning in the SRT task. Y1 - 2008 UR - http://tandfprod.literatumonline.com/doi/full/10.1080/17470210701557555 U6 - https://doi.org/10.1080/17470210701557555 ER - TY - JOUR A1 - Kinder, Annette A1 - Lotz, Anja T1 - Connectionist models of artificial grammar learning : what type of knowledge is acquired? N2 - Two experiments are presented that test the predictions of two associative learning models of Artificial Grammar Learning. The two models are the simple recurrent network (SRN) and the competitive chunking (CC) model. The two experiments investigate acquisition of different types of knowledge in this task: knowledge of frequency and novelty of stimulus fragments (Experiment 1) and knowledge of letter positions, of small fragments, and of large fragments up to entire strings (Experiment 2). The results show that participants acquired all types of knowledge. Simulation studies demonstrate that the CC model explains the acquisition of all types of fragment knowledge but fails to account for the acquisition of positional knowledge. The SRN model, by contrast, accounts for the entire pattern of results found in the two experiments. Y1 - 2009 UR - http://www.springerlink.com/content/101575 U6 - https://doi.org/10.1007/s00426-008-0177-z SN - 0340-0727 ER - TY - JOUR A1 - Lotz, Anja A1 - Kinder, Annette T1 - Transfer in artificial grammar learning : the role of repetition information N2 - In this article, the authors report 2 experiments that investigated the sources of information used in transfer and nontransfer tasks in artificial grammar learning. Multiple regression analyses indicated that 2 types of information about repeating elements were crucial for performance in both tasks: information about the repetition of adjacent elements and information about repetition of elements in the whole item. Similarity of test items to specific training items and chunk information influenced participants' judgments only in nontransfer tasks Y1 - 2006 UR - http://www.apa.org/pubs/journals/xlm/ U6 - https://doi.org/10.1037/0278-7393.32.4.707 SN - 0278-7393 ER - TY - JOUR A1 - Laubrock, Jochen A1 - Kinder, Annette T1 - Incidental sequence learning in a motion coherence discrimination task: how response learning affects perception JF - Journal of experimental psychology : Human perception and performance N2 - The serial reaction time task (SRTT) is a standard task used to investigate incidental sequence learning. Whereas incidental learning of motor sequences is well-established, few and disputed results support learning of perceptual sequences. Here we adapt a motion coherence discrimination task (Newsome & Pare, 1988) to the sequence learning paradigm. The new task has 2 advantages: (a) the stimulus is presented at fixation, thereby obviating overt eye movements, and (b) by varying coherence a perceptual threshold measure is available in addition to the performance measure of RT. Results from 3 experiments show that action relevance of the sequence is necessary for sequence learning to occur, that the amount of sequence knowledge varies with the ease of encoding the motor sequence, and that sequence knowledge, once acquired, has the ability to modify perceptual thresholds. KW - sequence learning KW - motion discrimination KW - psychophysics KW - perception-action-coupling Y1 - 2014 U6 - https://doi.org/10.1037/a0037315 SN - 0096-1523 SN - 1939-1277 VL - 40 IS - 5 SP - 1963 EP - 1977 PB - American Psychological Association CY - Washington ER -