When constructing MR images from acquired spatial frequency data, it can be beneficial to apply a low-pass filter to remove high frequency noise from the resulting images. This amounts to attenuating high spatial frequency fluctuations that can affect detected MR signal. A study is presented of spatially filtering MR data and possible ramifications on detecting regionally specific activation signal. It is shown that absolute activation levels are strongly dependent on the parameters of the filter used in image construction and that significance of an activation signal can be enhanced through appropriate filter selection. A comparison is made between spatially filtering MR image data and applying a Gaussian convolution kernel to statistical parametric maps.