Abstract
Clustering is a promising tool for grouping the sequence of similar time-points aimed to identify the attention blocks in spatiotemporal event-related potentials (ERPs) analysis. It is most likely to elicit the appropriate time window for ERP of interest if a suitable clustering method is applied to spatiotemporal ERP. However, how to reliably estimate a proper time window from entire individual subjects’ data is still challenging. In this study, we developed a novel multiset consensus clustering method in which several clustering results of multiple subjects were combined to retrieve the best fitted clustering for all the subjects within a group. Then, the obtained clustering was processed by a newly proposed time-window detection method to determine the most suitable time window for identifying the ERP of interest in each condition/group. Applying the proposed method to the simulated ERP data and real data indicated that the brain responses from the individual subjects can be collected to determine a reliable time window for different conditions/groups. Our results revealed more precise time windows to identify N2 and P3 components in the simulated data compared to the state-of-the-art methods. Additionally, our proposed method achieved more robust performance and outperformed statistical analysis results in the real data for N300 and prospective positivity components. To conclude, the proposed method successfully estimates the time window for ERP of interest by processing the individual data, offering new venues for spatiotemporal ERP processing.
Highlights
The event-related potentials (ERPs) carry important information about the cognitive process evoked by the brain response in milliseconds of the temporal domain
K-means, fuzzy c-means (FCM), self-organizing maps (SOMs), diffusion map spectral clustering, agglomerate hierarchical clustering (AAHC), and modified k-means methods were selected for the clustering of real data (Table 1). (iii) Generating stabilized clustering from stochastic clustering methods: following the optimal repeat for modified k-means and standard k-means was obtained in five and seven repeats for the simulated data (Figure 3)
Our results revealed no significant difference for prospective positivity regarding group factor; a larger positive potential was localized over central electrodes (p < 0.0001) in the ongoing task comparing to the prospective memory (PM) task
Summary
The event-related potentials (ERPs) carry important information about the cognitive process evoked by the brain response in milliseconds of the temporal domain. Almost all the ERP components are influenced by the attention corresponding to the latencies from the individual and a group of subjects (Luck and Kappenman, 2012). The latencies of ERP components can be ERP Multi-Set Consensus Clustering considered as a stable brain electric field configuration (topography map) in milliseconds associated with the specific psychological process (i.e., attention module) (Lehmann, 1990). Measuring the ERP of interest undertakes a fundamental role in identifying and interpreting the cognitive process in the experiment. Thereby, an important issue in the analysis of ERPs is how to define or select time windows. This influences both identifying components and performing statistical analyses. If the time window is not appropriately defined, the comparison between different conditions/groups can lead to unreliable and wrong psychological interpretations (Luck and Gaspelin, 2017)
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