Analyzing for information, not activation, to exploit high-resolution fMRI

High-resolution functional magnetic resonance imaging (hi-res fMRI) promises to help bridge the gap between the macro- and the microview of brain function afforded by conventional neuroimaging and invasive cell recording, respectively. Hi-res fMRI (voxel volume ≤ (2 mm)3) is robustly achievable in human studies today using widely available clinical 3-Tesla scanners. However, the neuroscientific exploitation of the greater spatial detail poses four challenges: (1) Hi-res fMRI may give inaccurate (i.e. blurred, displaced and distorted) images of fine-scale neuronal activity patterns. (2) Single small voxels yield very noisy measurements. (3) The greater number of voxels complicates interpretation and poses a more severe multiple-comparisons problem. (4) The functional correspondency mapping between individual brains is unknown at the fine scale of millimeters. Here we argue that these challenges can be met by shifting the focus of brain mapping and visualizing, not the activity patterns themselves, but the amount of information they convey about the experimental conditions.