Understanding the organization of large-scale brain networks remains a central problem in neuroscience. Work in both humans and rodents shows that the brain can be decomposed in terms of several networks (e.g., "default network"). Whereas the bulk of what we know is based on the blood-oxygenation level-dependent (BOLD) signal, the relationship between BOLD and neuronal activity is complex, which poses several challenges to interpreting networks revealed by this technique. To resolve these challenges, here we employed wide-field Ca2+imaging simultaneously recorded with fMRI-BOLD in a highly-sampled group of GCaMP6f-expressing mice. This allowed us to determine the relationship between networks discovered by BOLD and Ca2+signals both at the group level and in individual animals. Network partition used a mixed-membership stochastic blockmodel algorithm, which allows networks to be overlapping, such that a brain region may be assigned to multiple networks with varying strengths. Here, we tested the hypothesis that functional networks of the mouse brain are organized in an overlapping manner for both BOLD and Ca2+data. Our findings demonstrate that BOLD large-scale networks can be detected via Ca2+signals. In addition: (1) Overlapping networks were reliably estimated at the group level via random-effects statistical analysis. (2) Functional organization was generally similar for BOLD and Ca2+; e.g., with seven networks, cosine similarity was very high in five instances (values between 0.82-0.90; max possible value of 1), moderate in one case (0.73) and different in one case (0.26). (3) We discovered overlapping network organization in both data modalities, which was quantified in multiple ways; e.g., the proportion of regions that belonged to multiple networks was 75\% for BOLD and 60\% for Ca2+. (4) The large-scale functional organization of the mouse cortex as determined by Ca2+signals is considerably more similar to that with BOLD when both signal modalities are considered in the low temporal frequency range (0.01 to 0.5 Hz). (5) Although many similarities were observed between data modalities, finer characterization uncovered key differences related to functional hubs believed to play important roles in the integration and/or segregation of signals. In particular, the spatial distribution of membership diversity (i.e., the extent to which a region affiliates with multiple networks), differed for the two types of signals. In conclusion, Ca2+mesoscale signals revealed that the mouse cortex is functionally organized in terms of large-scale networks in a manner that reflects many of the properties observed using BOLD. Despite many similarities, important differences were also uncovered, suggesting that mesoscale Ca2+has a strong potential to uncover additional properties of the large-scale organization of the mouse brain.

Large-scale functional networks have been characterized in both rodent and human brains, typically by analyzing fMRI-BOLD signals. However, the relationship between fMRI-BOLD and underlying neural activity is complex and incompletely understood, which poses challenges to interpreting network organization obtained using this technique. Additionally, most work has assumed a disjoint functional network organization (i.e., brain regions belong to one and only one network). Here, we employed wide-field Ca2+ imaging simultaneously with fMRI-BOLD in mice expressing GCaMP6f in excitatory neurons. We determined cortical networks discovered by each modality using a mixed-membership algorithm to test the hypothesis that functional networks are overlapping rather than disjoint. Our results show that multiple BOLD networks are detected via Ca2+ signals; there is considerable network overlap (both modalities); networks determined by low-frequency Ca2+ signals are only modestly more similar to BOLD networks; and, despite similarities, important differences are detected across modalities (e.g., brain region “network diversity”). In conclusion, Ca2+ imaging uncovered overlapping functional cortical organization in the mouse that reflected several, but not all, properties observed with fMRI-BOLD signals.