Improving measurement of functional connectivity through decreasing partial volume effects at 7 T

Abstract

Several applications of fMRI at high field have taken advantage of the increased BOLD contrast to increase spatial resolution, but the potential benefits of higher fields for detecting and analyzing functional connectivity have largely been unexplored. We measured the influence of spatial resolution at 7 T on estimates of functional connectivity through decreased partial volume averaging. Ten subjects were imaged at 7 T with a range of spatial resolutions (1×1×2 mm to 3×3×2 mm) during performance of a finger tapping task and in the resting state. We found that resting state correlations within the sensory-motor system increase as voxel dimensions decreased from 3×3×2 mm to 1×1×2 mm, whereas connectivity to other brain regions was unaffected. This improvement occurred even as overall signal to noise ratios decrease. Our data suggest that this increase may be due to decreased partial volume averaging, and that functional connectivity within the primary seed region is heterogeneous on the scale of single voxels.

Figure 1

An example of the network definitions across resolution. Cross hairs highlight the seed voxel location chosen in this subject.

Figure 2

Examples of individual subject connectivity maps illustrating increased specificity associated with mapping functional connectivity with higher spatial resolution. The cross hairs indicate the location of the seed voxel.

Figure 3

(top) The distributions of functional connectivity (correlation) among MOTOR and NON-MOTOR voxels at each resolution. A Gaussian curve was fit to the mean distribution across subjects at each resolution. (bottom) A direct comparison of the distributions of correlation among motor and non-motor voxels at each resolution. Note the increase in separation between the motor and non-motor distributions (i.e. contrast) as voxel volume approach 1×1×2mm.

Figure 4

Pair-wise correlation matrices measuring the correlation between 100 randomly selected motor voxels and 200 randomly selected non-motor voxels. Each plot represents the average correlation matrix across subjects. Only the bottom half of the matrix is shown to avoid redundancy, and lines are inserted to aid in identifying the transitions between motor and non-motor voxels within the matrix. Note the significant improvement in contrast between the within network correlations (i.e. motor to motor) over those to the rest of the brain (i.e. motor to non-motor).

Figure 5

(top) An example of activation changes as a function of spatial resolution. Note that activity becomes more focal as voxel volume decreases. (bottom left) A plot of the estimated activated volume measured at each available spatial resolution. Circles represent individual measurements made in each subject. Box lines are at the lower quartile, median, and upper quartile of the data. Whiskers extend from each end of the box to the adjacent values in the data. (bottom right) The average distribution of resting state tSNR measured among motor voxels, averaged across subjects. Note the expected increase in tSNR as voxel volume increases. Voxel counts were normalized by the total number of voxels in the image to adjust for the changing total number of active voxels from one resolution to another.

Figure 6

The effect of decreased partial volume averaging on task-related activation, the residual model error, and voxel volume. All points/bars represent the mean/standard deviation across subjects of the average value across active voxels. (top left) T-statistics decrease with decreasing voxel volume in a nonlinear fashion. (bottom left) The deviation of the model error decreases as voxel volume increases. (center) The decrease in the T-statistic as a function of model error is less than would be predicted by theory. The dotted line represents the theoretical decrease given the initial point measured with 3×3×2mm voxels, marked by an additional circle. (right) Functional contrast increases as voxel volume decreases, indicating less dilution of the functional signals by partial volume averaging.