Purpose: Task-based fMRI has traditionally been used to locate eloquent regions of the brain that are relevant to specific cognitive tasks. These locations have, in turn, been used successfully to inform surgical planning. Resting-state functional MRI (fMRI) uses alternative methods to find networks, but does not require any task performance by a patient.
Materials and Methods: Resting-state fMRI uses correlations in the blood oxygen level–dependent (BOLD) signal to identify connected regions across the brain that form networks. Several methods of analyzing the data have been applied to calculate resting-state networks. In particular, seed-based correlation mapping and independent component analysis (ICA) are two commonly used techniques.
Results: Several studies using these analysis techniques are described in this chapter. Resting-state data has been used successfully as a presurgical planning tool in tumor patients and epilepsy patients.
Conclusions: Resting-state fMRI has been compared favorably to other methods of determining functional connectivity, including task-based fMRI and electrocortical stimulation. These results demonstrate great promise for the future of resting-state fMRI in presurgical planning.