Fig 1.
Representation of individual fingers in the human cerebellum.
Shown is the classification accuracy with which the moved finger can be determined from the local pattern of activity, with a threshold of z>1 [17]. (A) Data projected onto a surface based on a single anatomy [2] displays single closed activation clusters as a fractured series of blobs. (B) Projection to the new flatmap ensures that single clusters in the volume are also presented as such on the surface.
Fig 2.
Surfaces defined on a group-averaged anatomical template image of the human cerebellum.
(A) The outer surface constitutes a hull around the average grey matter body. (B) The inner surface is placed on the boundary between average white and grey masses.
Fig 3.
Distortion of the flatmap in representing cerebellar grey-matter volume as surface area.
(A) Flatmap with superimposed distortion factor (ratio of Area to Volume). Orange / red areas indicate regions that are disproportionally large on the flatmap, turquoise / blue areas indicate regions that are disproportionally small. Dotted lines indicate boundaries between lobules. Thick black lines on the perimeter indicate where cuts have been made to the map. The areas connected with dashed lines are immediately adjacent in the volume, but are unfolded in the flatmap to minimize distortion. (B) Volume of each lobule (in % of total grey-matter volume) plotted against the corresponding area on the flatmap (in % of total map area). Plotted are 28 compartments, hemisphere and vermis of each of the main lobules, as defined in the probabilistic atlas of the human cerebellum.
Fig 4.
Surface-based mapping pipeline for cerebellar data.
Functional data is first normalized using standard volume-based methods and then projected onto the flat representations using corresponding vertices on outer and inner surface. For the process of surface projection, it is therefore important to take into account the type of volume-based normalization algorithm used.
Fig 5.
Probabilistic atlas of the cerebellar lobules.
(A) The compartments of the cerebellar atlas [16] projected to the flatmap. Note that for lobule VI-X, a vermal and two hemispheric compartments (shown in slightly different colors) are defined. (B) The same data displayed on a posterior view of the outer surface.
Fig 6.
Atlas of cerebellar-cortical connectivity.
(A) Cortical networks of resting-state connectivity [23]. 17 networks are shown on an inflated cortical surface of the left and right hemisphere—with both the lateral and medial surface shown. (B) Map showing the cortical resting-state network that correlated best with the activity in the corresponding cerebellar area [18]. Maps are based on N = 1000 subjects.
Fig 7.
Functional activity maps from the Human Connectome Project.
(A) Sensorimotor topography of activation for hand, foot and tongue movements. (B) Working memory; contrast between a 2-back and 0-back condition. (C) Emotion processing; contrast between matching emotional faces vs. matching neutral shapes. (D) Social cognition; observing dot motion with intentional content vs. random dot motion. (E) Language vs. mathematical processing. Positive values indicate higher activity during processing of a story vs. arithmetic operations. Negative values represent the opposite contrast. All maps are based on N = 100 subjects. All colored areas in cognitive maps (B-E) exceed an FWE-corrected significance threshold of p<0.05.