Vascular physiology drives functional brain networks

• Published in: NeuroImage (Orlando, Fla.) Fla.), 2020-08, Vol.217, p.116907-116907, Article 116907
• Main Authors: Bright, Molly G., Whittaker, Joseph R., Driver, Ian D., Murphy, Kevin
• Format: Article
• Language: English
• Subjects: Adult; Blood Vessels - diagnostic imaging; Blood Vessels - drug effects; Blood Vessels - physiology; Brain; Brain Mapping; Carbon dioxide; Carbon Dioxide - pharmacology; Datasets; Design; Female; fMRI; Functional magnetic resonance imaging; Humans; Inhalation; Magnetic Resonance Imaging; Male; Medical imaging; Memory, Short-Term - drug effects; Memory, Short-Term - physiology; Mental task performance; Nerve Net - diagnostic imaging; Nerve Net - physiology; Networks; Neural networks; Neuroimaging; Neurovascular; Neurovascular Coupling - physiology; Oxygen - blood; Photic Stimulation; Psychomotor Performance - drug effects; Psychomotor Performance - physiology; Regression Analysis; Short term memory; Vascular
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2020.116907

We present the first evidence for vascular regulation driving fMRI signals in specific functional brain networks. Using concurrent neuronal and vascular stimuli, we collected 30 BOLD fMRI datasets in 10 healthy individuals: a working memory task, flashing checkerboard stimulus, and CO2 inhalation challenge were delivered in concurrent but orthogonal paradigms. The resulting imaging data were averaged together and decomposed using independent component analysis, and three “neuronal networks” were identified as demonstrating maximum temporal correlation with the neuronal stimulus paradigms: Default Mode Network, Task Positive Network, and Visual Network. For each of these, we observed a second network component with high spatial overlap. Using dual regression in the original 30 datasets, we extracted the time-series associated with these network pairs and calculated the percent of variance explained by the neuronal or vascular stimuli using a normalized R2 parameter. In each pairing, one network was dominated by the appropriate neuronal stimulus, and the other was dominated by the vascular stimulus as represented by the end-tidal CO2 time-series recorded in each scan. We acquired a second dataset in 8 of the original participants, where no CO2 challenge was delivered and CO2 levels fluctuated naturally with breathing variations. Although splitting of functional networks was not robust in these data, performing dual regression with the network maps from the original analysis in this new dataset successfully replicated our observations. Thus, in addition to responding to localized metabolic changes, the brain’s vasculature may be regulated in a coordinated manner that mimics (and potentially supports) specific functional brain networks. Multi-modal imaging and advances in fMRI acquisition and analysis could facilitate further study of the dual nature of functional brain networks. It will be critical to understand network-specific vascular function, and the behavior of a coupled vascular-neural network, in future studies of brain pathology. •Using neural and vascular stimuli we find pairs of spatially similar brain networks.•One network timeseries reflects a neural stimulus, the other a vascular stimulus.•The brain’s vasculature may be regulated to support specific functional networks.•Understanding network-specific vascular function is critical to interpreting fMRI.