Resting-state functional connectivity MRI (rs-fcMRI) can be reliably performed in mice, producing high-resolution whole-brain images. The functional connections strongly align with the brain's structural wiring, as mapped by anterograde tracer studies. Large-scale network properties previously seen only in primates also exist in rodents, though with some differences. A potential default mode network (DMN)—a system important for social cognition and disrupted in many disorders—was identified in the mouse brain both structurally and functionally. These findings validate mouse rs-fcMRI as a translational bridge, allowing stronger links between cellular and molecular manipulations in mice and human brain conditions.
The critical coupling strength that separates chaotic from ordered dynamics in recurrent neural networks also differentiates two learning strategies: networks initialized with low coupling learn rich representations, while those with larger variance learn lazier solutions. Training moves both stable and chaotic networks closer to the edge of chaos. Biologically realistic connectivity fosters stability across a wide range of variances. The transition to chaos is reflected in the perturbational complexity index (PCIst), a measure that clinically discriminates levels of consciousness. Networks with high PCIst exhibit stable dynamics and rich learning, suggesting a consciousness prior may promote rich learning. The results indicate a relationship between critical dynamics, learning regimes, and complexity-based measures of consciousness.