"N-Back Related ERPs Depend on Stimulus Type, Task Structure, Pre-processing, and Lab Factors"

Project Scientist Anja Pahor (right) published an article on variations of an N-Back task in Frontiers in Neuroscience.

The title of the article is “N-Back Related ERPs Depend on Stimulus Type, Task Structure, Pre-processing, and Lab Factors.”
 
Co-authors are Mahsa Alizadeh Shalchy (UC Riverside), Valentina Pergher (Harvard), Marc M. Van Hulle (KU Leuven, Belgium) and Aaron R. Seitz (UC Riverside).

​Pahor studies the mechanisms underlying higher-level cognitive functions, particularly memory and reasoning. She is currently working on two multi-site research projects involving assessment and training of executive functions in children and adults. At UCI, she is a member of the UC Irvine Working Memory and Plasticity (WMP) Lab and the UC Riverside Brain Game Center for Mental Fitness and Well-being. Pahor has a Ph.D. in Psychology and Cognitive Neuroscience from the University of Maribor in Slovenia. She completed a post doc at the University of California, Riverside.

​Abstract

​The N-Back, a common working memory (WM) updating task, is increasingly used in basic and applied psychological research. As such, an increasing number of electroencephalogram (EEG) studies have sought to identify the electrophysiological signatures of N-Back task performance. However, stimulus type, task structure, pre-processing methods, and differences in the laboratory environment, including the EEG recording setup employed, greatly vary across studies, which in turn may introduce inconsistencies in the obtained results. Here we address this issue by conducting nine different variations of an N-Back task manipulating stimulus type and task structure. Furthermore, we explored the effect of the pre-processing method used and differences in the laboratory environment. Results reveal significant differences in behavioral and electrophysiological signatures in response to N-Back stimulus type, task structure, pre-processing method, and laboratory environment. In conclusion, we suggest that experimental factors, analysis pipeline, and laboratory differences, which are often ignored in the literature, need to be accounted for when interpreting findings and making comparisons across studies.