In this paper, we present a subspace approach for functional magnetic resonance imaging (fMRI) time series analysis. The signal subspace is formed of the eigenvectors of data correlation matrix. The approach is utilized both for single-trial estimation of blood oxygenation level dependent (BOLD) responses in fMRI time series and for studying the functional connectivity of BOLD responses from different spatial areas.