ICA analysis of fMRI with real-time constraints: an evaluation of fast detection performance as function of algorithms, parameters and a priori conditions

Independent Component Analysis (ICA) techniques offer a data-driven possibility to analyse brain functional MRI data in real-time. Typical ICA methods used in fMRI, however, have been until now mostly developed and optimized for the off-line case in which all data is available. Real-time experiments are ill-posed for ICA in that several constraints are added: limited data, limited analysis time and dynamic changes in the data and computational speed. Previous studies have shown that particular choices of ICA parameters can be used to monitor real-time fMRI brain activation, but it is unknown how other choices would perform. In this real-time fMRI simulation study we investigate and compare the performance of 14 different publicly available ICA algorithms systematically sampling different growing window lengths, model order as well as a priori conditions (none, spatial or temporal). Performance is evaluated by computing the spatial and temporal correlation to a target component as well ...