Dynamic functional connectivity properties are differentially affected by anesthesia protocols and compare across species

Functional magnetic resonance imaging (fMRI) in rodents is an emerging field that allows for examination of brain networks in a preclinical setting. To maintain stable experimental conditions, animals are typically sedated during acquisition. However, the choice of anesthetic regimens impacts functional connectivity (FC) measures as defined by the temporal dependence of brain activity between distinct regions. Determining which anesthetic regimen best conserves natural FC is an ongoing field of investigation. There has been growing support for the idea that treating FC as a constant property does not fully describe the complex spatio-temporal organization of FC between brain areas, but instead, that FC undergoes global reorganization over time, a property referred to as dynamic FC (dFC). Anesthesia reduces the complexity of these global dynamics, suggesting that greater dFC is reflective of conserved brain dynamics. In this work, we investigated markers of conserved brain dynamics through comparison of dFC properties in mice with different anesthetic regimens and in standard human fMRI. We found group differences in the temporal variability in FC that might distinguish anesthesia regimens based on the conservation of brain dynamics. We further demonstrate that richer FC variability is not random, but tends to be captured by coordinated patterns of covariance described using principal component analysis. Finally, we identified that static measures of FC, the current gold standard for FC studies, is tightly related to underlying dFC properties, and this relationship holds in mice across anesthesia regimen as well as in humans. This work demonstrates for the first time that dFC properties can be differentially affected depending on the choice of anesthesia protocols in mouse fMRI experiments. Perhaps most importantly, our results provide evidence that dFC can reveal novel information about brain dynamics which wouldn’t be captured by standard FC measurements, and hence, stresses the importance of unraveling the contributions of these processes to the organization of major brain networks.