Abstract

Purpose: Task functional MRI (fMRI) has traditionally been used to locate eloquent regions of the brain that are relevant to specific cognitive tasks, such as motor and language. This information is routinely used for pre-surgical planning. Resting-state 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 are two commonly used techniques. Results: Multiple studies using these analysis techniques are described in this chapter. Resting-state data has been compared successfully with task fMRI and electrocortical stimulation mapping. Resting-state fMRI has been used as an adjunct to task fMRI in patients with brain tumors and epilepsy. Conclusions: Resting-state fMRI has been compared favorably to other methods of determining functional connectivity, including task fMRI and electrocortical stimulation. These results demonstrate great promise for the future of resting-state fMRI in pre-surgical planning.

Original languageEnglish
Title of host publicationMedical Radiology
PublisherSpringer Science and Business Media Deutschland GmbH
Pages197-215
Number of pages19
DOIs
StatePublished - 2022

Publication series

NameMedical Radiology
ISSN (Print)0942-5373
ISSN (Electronic)2197-4187

Keywords

  • Default mode network
  • Eloquent cortex
  • Functional connectivity
  • Language network
  • Pre-surgical planning

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