Spin echo (SE) pulse sequences have not been widely used for fMRI due to their decreased sensitivity compared to GRE despite higher spatial specificity^1-3. In this study, the functional sensitivity was quantified by measuring the number of activated voxels, however, fair comparison between SE and GRE methods requires that their intrinsic resolution differences be equalized. We have defined "functional resolution" as a quantitative metric to evaluate spatial specificity of BOLD contrast fMRI and measured it in SE, asymmetric spin echo (ASE), and GRE. Using spatial smoothing, we equalized their functional resolutions and compared functional sensitivity. The results demonstrate that SE provides the highest spatial specificity and ASE provides higher spatial specificity than GRE. In comparison with GRE, lightly T2'-weighted ASE and SE greatly enhance functional sensitivity in all brain regions. fMRI Acquisition We scanned 16 healthy subjects on a 3.0T GE whole-body scanner during breath hold (BH) tasks. Figure 1 shows GRE, ASE and SE pulse sequence diagrams. We chose effective TE = 30ms for the GRE and 65ms for the ASE that maximized BOLD contrasts at 3.0 T. The ASE had additional T2'-weighting with Echoshift = -50, -40, -30, -20, -10, 0 (SE), +10ms associated as TE = TH + Echoshift. The Echoshift determined the degree of T2'-weighting. Thus, as we varied Echoshift from -50ms to 0, the ASE BOLD contrasts properties varied from T2*-weighted GRE-like ASE to T2-weighted SE-like ASE. Other parameters remained constant throughout all scans. fMRI Analysis & Functional Resolution We generated activation maps with correlation analysis. In order to measure functional resolution, we calculated autocorrelation functions from threshholded activation maps. The functional resolution was defined as full-width 70% magnitude in both image dimensions, of the autocorrelation function. Then functional resolutions in 2D direction were combined into a single geometric mean. Spatial Smoothing & Functional Sensitivity We performed spatial smoothing in k-space using a 2D Gaussian kernel and repeated voxel-wise analysis to obtain activation maps. The Gaussian kernel size was chosen in each slice in order that the functional resolution of a smoothed ASE was equalized to that of GRE. Functional resolution Figure 2 shows functional resolutions for BH tasks of a representative slice from ASE with Echoshift varied and from GRE, and Fig. 3 shows the averaged functional resolution. These quantitative results affirm that any set of ASEs provides enhanced functional resolutions compared with that of GRE at 3T. Specifically, as an ASE approached SE - Echoshift close to 0ms, its functional resolution tended to be higher. Spatial smoothing & Functional sensitivity Figure 4 presents the activation maps before and after spatial smoothing compared with GRE, and Figure 5 shows the averaged percentage of activation in all and SFGs regions. Resolution equalization increased relative activation greatly, and the ASEs that were close to SE resulted in significant improvement in functional sensitivity. Therefore, in the range of negative Echoshift, ASEs with spatial smoothing provided comparable or greater BOLD contrast with GRE. In susceptibility-compromised regions, while GRE lost all signal, ASEs retained the activation up to 5% and 6% without/with spatial smoothing. ASE BOLD contrasts include more extravascular components than GRE; therefore the smoothed ASE is dominated by T2-weighted extravascular components while GRE is dominated by T2*-weighted intravascular components. This is particularly beneficial on lightly T2'-weighted ASE, thus the optimal Echoshift that gives rise to the greatest activation is shifted close to 0.When properly accounting for resolution differences, lightly T2'-weighted ASE can achieve both high functional sensitivity and spatial specificity compared with GRE and SE.