A tutorial on data-driven methods for statistically assessing ERP topographies

Dynamic changes in ERP topographies can be conveniently analyzed by means of microstates, the so-called "atoms of thoughts", that represent brief periods of quasi-stable synchronized network activation. Comparing temporal microstate features such as on- and offset or duration between groups and conditions therefore allows a precise assessment of the timing of cognitive processes. So far, this has been achieved by assigning the individual time-varying ERP maps to spatially defined microstate templates obtained from clustering the grand mean data into predetermined numbers of topographies (microstate prototypes). Features obtained from these individual assignments were then statistically compared. This has the problem that the individual noise dilutes the match between individual topographies and templates leading to lower statistical power. We therefore propose a randomization-based procedure that works without assigning grand-mean microstate prototypes to individual data. In addition, we propose a new criterion to select the optimal number of microstate prototypes based on cross-validation across subjects. After a formal introduction, the method is applied to a sample data set of an N400 experiment and to simulated data with varying signal-to-noise ratios, and the results are compared to existing methods. In a first comparison with previously employed statistical procedures, the new method showed an increased robustness to noise, and a higher sensitivity for more subtle effects of microstate timing. We conclude that the proposed method is well-suited for the assessment of timing differences in cognitive processes. The increased statistical power allows identifying more subtle effects, which is particularly important in small and scarce patient populations.

The bivalency effect represents an interference-triggered adjustment of cognitive control: an ERP study

When bivalent stimuli (i.e., stimuli with relevant features for two different tasks) occur occasionally among univalent stimuli, performance is slowed on subsequent univalent stimuli even if they have no overlapping stimulus features. This finding has been labeled the bivalency effect. It indexes an adjustment of cognitive control, but the underlying mechanism is not well understood yet. The purpose of the present study was to shed light on this question, using event-related potentials. We used a paradigm requiring predictable alternations between three tasks, with bivalent stimuli occasionally occurring on one task. The results revealed that the bivalency effect elicited a sustained parietal positivity and a frontal negativity, a neural signature that is typical for control processes implemented to resolve interference. We suggest that the bivalency effect reflects interference, which may be caused by episodic context binding.

A Team-Oriented Investigation of ERP Post-Implementation Integration Projects: How Cross-Functional Collaboration Influences ERP Benefits

The benefits companies achieve by implementing an ERP system vary considerably. Many companies need to adapt their ERP integration solution in the post-implementation stage. But after the completion of such a usually very complex integration project, benefits do not emerge by all means. A misfit between the organization and the IS, especially the aspect of cross-functional team collaboration, could explain these divergences. Using an initial theoretical framework, we conducted a single case study to explore the team-oriented perceptions in a post-implementation ERP integration project. To analyze the benefits and the influences in greater depth we disentangled the integration benefits into their particular parts (process, system and information quality). Our findings show that post-implementation ERP integration changes are not always perceived as beneficiary by the involved teams and that cross-functional collaboration has an important influence.