During rest, the fMRI BOLD signal shows strong intrinsic low-frequency fluctuations that are correlated between different brain regions. The main idea behind "resting state connectivity analysis" is that brain networks that normally communicate with each other will also share common fluctuations when not engaged in a particular task. Using resting-state functional connectivity analysis, a number of papers have maped the connectivity between the neocortex and the cerebellum (Krienen et al., 2009; O'Reilly et al., 2009; Marek et al., 2019). We have included two such parcellations (Buckner et al. 2011, Ji et al. 2019), both based on large resting-state data set (N=1000), in our atlas package.
Buckner et al. (2011)
The image shows a set of cortical networks calculated by searching for clusters of voxels that show high temporal coherence in their resting BOLD activity (Yeo et al., 2011). Each cerebellar voxel was then assigned to the cortical network, with which it shared the highest temporal correlation (Buckner et al., 2011). The paper presents a 7-Network and a 17-Network parcellation of the cerebellum. As expected, one can observe connectivity between the anterior lobe and lobule VIII and cortical motor and premotor areas (Networks 3,4,6, and 7). Also clearly visible is the connectivity between lobule VII and IX to prefrontal and parietal association areas (Networks 8, 12, 13, 14, 16, 17). The details of this connectivity - especially the medial to lateral organization of Crus I and II - were revealed in these maps for the first time.
We include a version of these maps aligned to SUIT and MNI space in the atlas package. We used a cerebellar mask that is based on the SUIT isolation, which lies somewhere between the "loose" and the "tight" mask presented in Buckner et al. (2011). While the MNI space alignment used in Buckner et al. (2011) and SUIT alignment are roughly identical, there are some smaller non-linear differences between the two templates, which we here corrected for. The maps for the 7 and 17 network versions are provided as nifti-image files. We also projected the maps to the cerebellar surface as
Ji et al. (2011)
A more recent 10-Networks parcellation was derived by Ji et al. from the HCP resting-state data set. The maps are based on a different cortical parcellation, explaining the differences to the Buckner et al. (2011) maps. All connectivity maps can be downloaded in SUIT and MNI space in the cerebellar atlas package.
- Buckner, R. L., Krienen, F. M., Castellanos, A., Diaz, J. C., Yeo, B. T. T., & Yeo, T. (2011). The organization of the human cerebellum estimated by intrinsic functional connectivity. Journal of neurophysiology, 2322-45.
- Yeo, B. T. T., Krienen, F. M., Sepulcre, J., Sabuncu, M. R., Lashkari, D., Hollinshead, M., Roffman, J. L., Smoller, J. W., Zöllei, L., Polimeni, J. R., Fischl, B., Liu, H., Buckner, R. L. (2011). The organization of the human cerebral cortex estimated by intrinsic functional connectivity. Journal of neurophysiology, 1125-65
- Ji, J. L., Spronk, M., Kulkarni, K., Repovs, G., Anticevic, A., & Cole, M. W. (2019). Mapping the human brain’s cortical-subcortical functional network organization. NeuroImage, 185, 35-57.