Prediction of task-related BOLD fMRI with amplitude signatures of resting-state fMRI

Blood oxygen contrast-fMRI signals are a convolution of neural and vascular components. Several studies indicate that task-related (T-fMRI) or resting state (R-fMRI) responses linearly relate to hypercapnic task responses. Based on the linearity R-fMRI and T-fMRI with hypercapnia demonstrated by different groups using different study designs, we hypothesized that R-fMRI and TfMRI signals are governed by a common physiological mechanism and that RSFA should be linearly related to T-fMRI responses. We tested this prediction in a group of healthy younger humans where R-fMRI, T-fMRI and hypercapnic (breath hold; BH) task measures were obtained form the same scan session during resting state and during performance of motor and breath-hold (BH) tasks. Within individual subjects, significant linear correlations were observed between motor and BH task responses across voxels. When averaged over the whole brain, the subject-wise correlation between the motor and BH tasks showed a similar linear relationship within the group. Likewise, a significant linear correlation was observed between motor task activity and RSFA across voxels and subjects. The linear rest-task (R-T) relationship between motor activity and RSFA suggested that R-fMRI and T-fMRI responses are governed by similar physiological mechanisms. A practical use of the R-T relationship is its potential to estimate T-fMRI responses in special populations unable to perform tasks during fMRI scanning. Using the R-T relationship determined from the first group of 12 healthy subjects, we predicted the T-fMRI responses in a second group of 7 healthy subjects. RSFA in both the lower and higher frequency ranges robustly predicted the magnitude of T-fMRI responses at the subject and voxel levels. We propose that T-fMRI responses are reliably predictable to the voxel level in situations where only R-fMRI measures are possible, and may be useful for assessing neural activity in task non-compliant clinical populations.