Visualizing temporal brain-state changes for fMRI using t-distributed stochastic neighbor embedding.

ABSTRACT: Purpose: Currently, functional magnetic resonance imaging (fMRI) is the most commonly used technique for obtaining dynamic information about the brain. However, because of the complexity of the data, it is often difficult to directly visualize the temporal aspect of the fMRI data. Approach: We outline a t -distributed stochastic neighbor embedding (t-SNE)-based postprocessing technique that can be used for visualization of temporal information from a 4D fMRI data. Apart from visualization, we also show its utility in detection of major changes in the brain meta-states during the scan duration. Results: The t-SNE approach is able to detect brain-state changes from task to rest and vice versa for single- and multitask fMRI data. A temporal visualization can also be obtai

SUBMITTER: Parmar H 

PROVIDER: S-EPMC8366791 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature