A blood oxygenation-level dependent (BOLD) functional magnetic resonance imaging (fMRI) study produces a four-dimensional (4D) complex-valued data set. Conventional magnitude-based brain functional mapping is an indirect measure of brain activity due to a dataflow in a cascade of MRI transformations (e.g., a dipole convolution). The MRI transformations also impose a MRI parameter dependence to BOLD fMRI data (e.g. the dependence on B0 and TE). By solving an inverse MRI problem, we may reconstruct a brain magnetic susceptibility source distribution (denoted by χ) from a brain MR image, thereby achieving a more direct representation of the vascular origin than the MRI data representation. For a complex-valued BOLD fMRI dataset, we can extract net BOLD phase responses (δP) through a complex division, and then reconstruct BOLD susceptibility responses (δχ) therefrom. In this paper, we compare the functional maps depicted in different dataspaces (magnitude image, δP image, δχ source) based on numeric characterizations of activation blobs by pattern analysis. Through an experimental demonstration with high-field (7 T) and high-resolution (0.5 mm in-plane) finger-tapping experiment, we show that the δχ-depicted functional map reveals task-evoked bidirectional BOLD δχ responses at the motor cortex region. The positive and negative activations are spatially separated and balanced, indicating conservation of concurrent excitations and inhibitions. We also observe that the source-depicted activation spots are more compact than the image-depicted spots, which is attributed to the dipole effect removal by inverse MRI.