Single pooled ICA of all subjects avoids cross-group decomposition bias

Evidence

In contrast, we adopted a strategy where the data is pooled over all participants and data-modalities (restingand fixed-state data). In this way, the data-decomposition is not determined in a potentially different way for both groups, leaving out the necessity of post-ICA matching of corresponding component maps. This allows for a better group-estimate of the components. In addition, by using a dual regression technique we can obtain subject-specific maps and perform group-wise analyses on these maps (Filippini et al. 2009 ). Using this methodological approach we found a significant group effects for the DMN. — Dijk, Pim van, Physiology, Psychoacoustics and…, 2753

Categorization

• QUESTION: Worth chasing: does pooled single-ICA analysis meaningfully outperform separate per-group ICA in detecting true resting-state group differences?