Functional Localizers for Motor Areas of the Brain Using fMRI. (28th May 2022)

• Record Type: Journal Article
• Authors: Madkhali, Yahia; Aldehmi, Norah; Pollick, Frank
• Other Names: Khan Rahim Academic Editor.
• Is Part Of: Computational intelligence and neuroscience. Volume 2022(2022)
• Publication Date: 2022-05-28
• Subjects: Neurosciences -- Data processing -- Periodicals; Computational intelligence -- Periodicals; Computational neuroscience -- Periodicals; 612.80285
• DOI: 10.1155/2022/7589493
• Languages: English
• ISSNs: 1687-5265

Abstract

Abstract : Neuroimaging researchers increasingly take advantage of the known functional properties of brain regions to localize motor regions in the brain and investigate changes in their activity under various conditions. Using this noninvasive functional MRI (fMRI) method makes it possible to identify and localize brain activation. There are many localizers that can be used to identify brain areas, namely, motor areas such as functional localizer, anatomical localizer, or Atlas mask. Eighteen right-handed participants were recruited for this research to test the reliability of five localizers for primary motor cortex (M1), supplementary motor area (SMA), premotor cortex (PMC), motor cerebellum, and motor thalamus. Motor execution task, namely, hand clenching was used to activate M1, SMA, and motor cerebellum. A combined action observation and motor imagery (AOMI) task was used to functionally activate PMC. Finally, a mask based on Talairach coordinates Atlas was created and used to identify the motor thalamus. Our results show that all localizers were successfully activated in the desired regions of interest. Motor execution successfully activated M1, SMA, and motor cerebellum. A novel localizer based on AOMI was successfully activated in PMC, and the motor thalamus mask obtained from the thalamus mask was successfully implemented on each participant. In conclusion, all five localizers tested in this research were reliable and can be used for rt-fMRI neurofeedback research to define the regions of interest.