The human brain exhibits temporal variability at every level of neural organization. The utility of signal variability approaches for understanding broad-scale individual differences in human brain function continues to gain traction, but the nature and driving forces of within-region brain signal variability remain opaque. Given that animal and computational models demonstrate that dynamic regional activity can be a primary function of its synaptic inputs, we tested in humans whether greater temporal variability in local brain regions can be captured by the dimensionality of functional network composition. Using publicly available fMRI data, our results indicate that persons with higher local temporal variability maintained a lower-dimensional network fingerprint regardless of adult age, specific frequency band, dimensionality estimation method, global signal, or regions/networks of interest. Strikingly, signal variability in the bilateral thalamus was the strongest negative correlate of network dimensionality, in line with a purported role of the thalamus as a putative generator of neural dynamics in cortex. Our findings thus indicate that the degree of local temporal variability primarily reflects the level of functional integration in the human brain rather than locally generated noise.
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