Parallel imaging in the form of multiband radiofrequency excitation, together with reduced k-space coverage in the phaseencode direction, was applied to human gradient echo functional MRI at 7 T for increased volumetric coverage and concurrent high spatial and temporal resolution. Echo planar imaging with simultaneous acquisition of four coronal slices separated by 44mm and simultaneous 4-fold phase-encoding undersampling, resulting in 16-fold acceleration and up to 16-fold maximal aliasing, was investigated. Task/stimulusinduced signal changes and temporal signal behavior under basal conditions were comparable for multiband and standard single-band excitation and longer pulse repetition times. Robust, whole-brain functional mapping at 7 T, with 2 3 2 3 2mm 3 (pulse repetition time 1.25 sec) and 1 3 1 3 2mm 3 (pulse repetition time 1.5 sec) resolutions, covering fields of view of 256 3 256 3 176mm 3 and 192 3 172 3 176mm 3 , respectively, was demonstrated with current gradient performance.

At high magnetic field, MR images exhibit large, undesirable signal intensity variations commonly referred to as “intensity field bias”. Such inhomogeneities mostly originate from heterogeneous RF coil B1 profiles and, with no appropriate correction, are further pronounced when utilizing rooted sum of square reconstruction with receive coil arrays. These artifacts can significantly alter whole brain high resolution T1-weighted (T1w) images that are extensively utilized for clinical diagnosis, for gray/white matter segmentation as well as for coregistration with functional time series. In T1 weighted 3D-MPRAGE sequences, it is possible to preserve a bulk amount of T1 contrast through space by using adiabatic inversion RF pulses that are insensitive to transmit B1 variations above a minimum threshold. However, large intensity variations persist in the images, which are significantly more difficult to address at very high field where RF coil B1 profiles become more heterogeneous. Another characteristic of T1w MPRAGE sequences is their intrinsic sensitivity to Proton Density and T2* contrast, which cannot be removed with post-processing algorithms utilized to correct for receive coil sensitivity. In this paper, we demonstrate a simple technique capable of producing normalized, high resolution T1w 3D-MPRAGE images that are devoid of receive coil sensitivity, Proton Density and T2* contrast. These images, which are suitable for routinely obtaining whole brain tissue segmentation at 7 Tesla, provide higher T1 contrast specificity than standard MPRAGE acquisitions. Our results show that removing the Proton Density component can help identifying small brain structures and that T2* induced artifacts can be removed from the images. The resulting unbiased T1w images can also be used to generate Maximum Intensity Projection angiograms, without additional data acquisition, that are inherently registered with T1w structural images. In addition, we introduce a simple technique to reduce residual signal intensity variations induced by Transmit B1 heterogeneity. Because this approach requires two 3D images, one divided with the other, head motion could create serious problems, especially at high spatial resolution. To alleviate such inter-scan motion problems, we developed a new sequence where the two contrast acquisitions are interleaved within a single scan. This interleaved approach however comes with greater risk of intra-scan motion issues because of a longer single scan time. Users can choose between these two trade offs depending on specific protocols and patient populations. We believe that the simplicity and the robustness of this double contrast based approach to address intensity field bias at high field and improve T1 contrast specificity, together with the capability of simultaneously obtaining angiography maps, advantageously counter balance the potential drawbacks of the technique, mainly a longer acquisition time and a moderate reduction in signal to noise ratio.

Recent multi-voxel pattern classification (MVPC) studies have shown that in early visual cortex patterns of brain activity generated during mental imagery are similar to patterns of activity generated during perception. This finding implies that low-level visual features (e.g., space, spatial frequency, and orientation) are encoded during mental imagery. However, the specific hypothesis that low-level visual features are encoded during mental imagery is difficult to directly test using MVPC. The difficulty is especially acute when considering the representation of complex, multi-object scenes that can evoke multiple sources of variation that are distinct from low-level visual features. Therefore, we used a voxel-wise modeling and decoding approach to directly test the hypothesis that low-level visual features are encoded in activity generated during mental imagery of complex scenes. Using fMRI measurements of cortical activity evoked by viewing photographs, we constructed voxel-wise encoding models of tuning to low-level visual features. We also measured activity as subjects imagined previously memorized works of art. We then used the encoding models to determine if putative low-level visual features encoded in this activity could pick out the imagined artwork from among thousands of other randomly selected images. We show that mental images can be accurately identified in this way; moreover, mental image identification accuracy depends upon the degree of tuning to low-level visual features in the voxels selected for decoding. These results directly confirm the hypothesis that low-level visual features are encoded during mental imagery of complex scenes. Our work also points to novel forms of brain-machine interaction: we provide a proof-of-concept demonstration of an internet image search guided by mental imagery.