This study investigates the consistency of resting-state networks across healthy subjects using functional MRI (fMRI). The authors apply tensor probabilistic independent component analysis (tensor-PICA) to resting-state fMRI data to identify coherencies that are consistent across subjects and sessions. They quantify the consistency of these patterns using bootstrapping and estimate the BOLD amplitude modulation and voxel-wise cross-subject variation. The analysis identifies 10 patterns with potential functional relevance, including regions involved in motor function, visual processing, executive functioning, auditory processing, memory, and the default-mode network. These patterns show significant temporal dynamics, with BOLD signal changes up to 3%. The findings suggest that the baseline activity of the brain is consistent across subjects, exhibiting significant temporal dynamics comparable to task-related signals. The study highlights the importance of understanding these resting-state fluctuations for interpreting task-related fMRI results and their implications in clinical settings.This study investigates the consistency of resting-state networks across healthy subjects using functional MRI (fMRI). The authors apply tensor probabilistic independent component analysis (tensor-PICA) to resting-state fMRI data to identify coherencies that are consistent across subjects and sessions. They quantify the consistency of these patterns using bootstrapping and estimate the BOLD amplitude modulation and voxel-wise cross-subject variation. The analysis identifies 10 patterns with potential functional relevance, including regions involved in motor function, visual processing, executive functioning, auditory processing, memory, and the default-mode network. These patterns show significant temporal dynamics, with BOLD signal changes up to 3%. The findings suggest that the baseline activity of the brain is consistent across subjects, exhibiting significant temporal dynamics comparable to task-related signals. The study highlights the importance of understanding these resting-state fluctuations for interpreting task-related fMRI results and their implications in clinical settings.