Psychological Research

, Volume 78, Issue 6, pp 821–835 | Cite as

Individual differences in cognitive plasticity: an investigation of training curves in younger and older adults

  • Céline N. BürkiEmail author
  • Catherine Ludwig
  • Christian Chicherio
  • Anik de Ribaupierre
Original Article


To date, cognitive intervention research has provided mixed but nevertheless promising evidence with respect to the effects of cognitive training on untrained tasks (transfer). However, the mechanisms behind learning, training effects and their predictors are not fully understood. Moreover, individual differences, which may constitute an important factor impacting training outcome, are usually neglected. We suggest investigating individual training performance across training sessions in order to gain finer-grained knowledge of training gains, on the one hand, and assessing the potential impact of predictors such as age and fluid intelligence on learning rate, on the other hand. To this aim, we propose to model individual learning curves to examine the intra-individual change in training as well as inter-individual differences in intra-individual change. We recommend introducing a latent growth curve model (LGCM) analysis, a method frequently applied to learning data but rarely used in cognitive training research. Such advanced analyses of the training phase allow identifying factors to be respected when designing effective tailor-made training interventions. To illustrate the proposed approach, a LGCM analysis using data of a 10-day working memory training study in younger and older adults is reported.


Fluid Intelligence Work Memory Training Latent Growth Curve Model Implicit Sequence Learning Training Gain 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This study was supported by the Hedwig Widmer Foundation, Zurich, Switzerland. The authors thank Philippe Golay and Paolo Ghisletta for the support regarding the application and the selection of the latent growth curve model. This study is based on Céline Bürki’s doctoral dissertation (Bürki 2012).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Céline N. Bürki
    • 1
    • 2
    Email author
  • Catherine Ludwig
    • 3
  • Christian Chicherio
    • 4
  • Anik de Ribaupierre
    • 5
  1. 1.Felix Platter-HospitalUniversity Center for Medicine of Aging BaselBaselSwitzerland
  2. 2.Division of Diagnostic and Interventional Neuroradiology, Department of RadiologyUniversity of Basel HospitalBaselSwitzerland
  3. 3.School of Health - GenevaUniversity of Applied Sciences Western SwitzerlandGenevaSwitzerland
  4. 4.Neuropsychology Unit, Neurology Clinic, Department of Clinical NeurosciencesGeneva University HospitalsGenevaSwitzerland
  5. 5.Faculty of Psychology and Educational SciencesUniversity of GenevaGenevaSwitzerland

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