Enhancing the network specific individual characteristics in rs-fMRI functional connectivity by dictionary learning.

ABSTRACT: Most fMRI inferences are based on analyzing the scans of a cohort. Thus, the individual variability of a subject is often overlooked in these studies. Recently, there has been a growing interest in individual differences in brain connectivity also known as individual connectome. Various studies have demonstrated the individual specific component of functional connectivity (FC), which has enormous potential to identify participants across consecutive testing sessions. Many machine learning and dictionary learning-based approaches have been used to extract these subject-specific components either from the blood oxygen level dependent (BOLD) signal or from the FC. In addition, several studies have reported that some resting-state networks have more individual-specific information than others.

SUBMITTER: Jain P 

PROVIDER: S-EPMC10171559 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature