Blood Oxygen Level-Dependent Signal Variability Is More than Just Noise

TLDR

Functional magnetic resonance imaging (fMRI) research often attributes blood oxygen level-dependent (BOLD) signal variance to measurement-related confounds, yet this variance may reflect vital brain function. We examined fMRI signal variability during fixation baseline periods and compared SD‑ and mean‑based spatial patterns and their relations with chronological age (20–85 years). The study compared standard deviation (SD)–based and mean‑based spatial patterns of BOLD signal during fixation, assessing their spatial and statistical differences across ages. The SD‑based pattern was robust, spatially and statistically distinct from the mean‑based pattern, and its age‑predictive power exceeded that of the mean‑based pattern by more than fivefold, indicating that BOLD signal variability contains meaningful information beyond noise.

Abstract

Functional magnetic resonance imaging (fMRI) research often attributes blood oxygen level-dependent (BOLD) signal variance to measurement-related confounds. However, what is typically considered “noise” variance in data may be a vital feature of brain function. We examined fMRI signal variability during fixation baseline periods, and then compared SD- and mean-based spatial patterns and their relations with chronological age (20–85 years). We found that not only was the SD-based pattern robust, it differed greatly, both spatially and statistically, from the mean-based pattern. Notably, the unique age-predictive power of the SD-based pattern was more than five times that of the mean-based pattern. This reliable SD-based pattern of activity highlights an important “signal” within what is often considered measurement-related “noise.” We suggest that examination of BOLD signal variability may reveal a host of novel brain-related effects not previously considered in neuroimaging research.