Multi-aspect data analysis for investigating human computation mechanism

Abstract

In the paper, we present a multi-aspect data analysis approach for investigating human computation mechanism. Multi-aspect analysis in multiple human brain data sources is an important methodology in Brain Informatics, which emphasizes on a systematic way for investigating human information processing mechanisms, including measuring, collecting, modeling, transforming, managing, and mining multiple human brain data obtained from various cognitive experiments by using powerful equipments, such as fMRI and EEG. After giving an outline of Brain Informatics methodology, we describe how to design cognitive experiments of mental arithmetic task with multiple difficulty levels for obtaining multiple EEG and fMRI data sources, and how to analyze such data for investigating the spatiotemporal characteristics and flow of human computation processing. Such an investigation can be regarded as a case study using Brain Informatics methodology. Experimental results show the usefulness of our approach.