A low-variance subspace underlies individual differences in resting state fMRI.

ABSTRACT: People differ remarkably from one another, yet isolating individual differences in their brain activity remains challenging. Non-invasive whole-brain recordings of human brain activity, such as those from resting state fMRI (rs-fMRI), are complex and noisy, making it difficult to isolate stable dimensions of individual differences. Ideally, we want to find a few core dimensions that vary across people but have high test-retest reliability, giving the same value each time they are measured in the same person. However, it is still unknown whether any such reliable dimensions exist, and if they do, what could drive this reliability. Here, we show that there is a low-dimensional linear subspace of highly-reliable rs-fMRI activity. These dimensions form personal fingerprints, allowing participa

SUBMITTER: Borovykh A 

PROVIDER: S-EPMC12873822 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature