Variability of neuronal responses is thought to underlie flexible and optimal brain function. Because previous work investigating BOLD signal variability has been conducted within task-based fMRI contexts on adults and older individuals, very little is currently known regarding regional changes in spontaneous BOLD signal variability in the human brain across the lifespan. The current study used resting-state fMRI data from a large sample of male and female human participants covering a wide age range (6-85 years) across two different fMRI acquisition parameters (TR = 0.645 and 1.4 s). Variability in brain regions including a key node of the salience network (anterior insula) increased linearly across the lifespan across datasets. In contrast, variability in most other large-scale networks decreased linearly over the lifespan. These results demonstrate unique lifespan trajectories of BOLD variability related to specific regions of the brain and add to a growing literature demonstrating the importance of identifying normative trajectories of functional brain maturation. Although brain signal variability has traditionally been considered a source of unwanted noise, recent work demonstrates that variability in brain signals during task performance is related to brain maturation in old age as well as individual differences in behavioral performance. The current results demonstrate that intrinsic fluctuations in resting-state variability exhibit unique maturation trajectories in specific brain regions and systems, particularly those supporting salience detection. These results have implications for investigations of brain development and aging, as well as interpretations of brain function underlying behavioral changes across the lifespan.

The past decade of functional neuroimaging research has seen the application of increasingly sophisticated advanced methods to characterize intrinsic functional brain organization. Accompanying these techniques are a patchwork of empirical ndings highlighting novel properties of intrinsic functional brain organization. To date, there has been little attempt to understand whether there is an underlying unity across this patchwork of empirical ndings. Our study conducted a systematic survey of popular analytic techniques and their output on a large sample of resting-state fMRI data. We found that the apparent complexity of intrinsic functional brain organization can be seamlessly reduced to three fundamental low-frequency spatiotemporal patterns. Our study demonstrates that a long list of previously observed phenomena, including functional connectivity gradients, the task-positive/tasknegative pattern, the global signal, time-lag propagation patterns, the quasiperiodic pattern and the network structure of the functional connectome are simply manifestations of these three spatiotemporal patterns. An in-depth characterization of these three spatiotemporal patterns using a novel time-varying complex pattern analysis revealed that these three patterns may arise from a single hemodynamic mechanism.