The invariant properties of human cortical neurons cannot be studied directly by fMRI due to its limited spatial resolution. One voxel obtained from a fMRI scan contains several hundred thousands neurons. Therefore, the fMRI signal may average out a heterogeneous group of highly selective neurons. Here, we present a novel experimental paradigm for fMRI, functional magnetic resonance-adaptation (fMR-A), that enables to tag specific neuronal populations within an area and investigate their functional properties. This approach contrasts with conventional mapping methods that measure the averaged activity of a region. The application of fMR-A to study the functional properties of cortical neurons proceeds in two stages: First, the neuronal population is adapted by repeated presentation of a single stimulus. Second, some property of the stimulus is varied and the recovery from adaptation is assessed. If the signal remains adapted, it will indicate that the neurons are invariant to that attribute. However, if the fMRI signal will recover from the adapted state it would imply that the neurons are sensitive to the property that was varied. Here, an application of fMR-A for studying the invariant properties of high-order object areas (lateral occipital complex--LOC) to changes in object size, position, illumination and rotation is presented. The results show that LOC is less sensitive to changes in object size and position compared to changes of illumination and viewpoint. fMR-A can be extended to other neuronal systems in which adaptation is manifested and can be used with event-related paradigms as well. By manipulating experimental parameters and testing recovery from adaptation it should be possible to gain insight into the functional properties of cortical neurons which are beyond the spatial resolution limits imposed by conventional fMRI.