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Functional boundaries in the human cerebellum revealed by a multi-domain task battery

Nature Neuroscience volume 22, pages 1371–1378 (2019)Cite this article

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Abstract

There is compelling evidence that the human cerebellum is engaged in a wide array of motor and cognitive tasks. A fundamental question centers on whether the cerebellum is organized into distinct functional subregions. To address this question, we employed a rich task battery designed to tap into a broad range of cognitive processes. During four functional MRI sessions, participants performed a battery of 26 diverse tasks comprising 47 unique conditions. Using the data from this multi-domain task battery, we derived a comprehensive functional parcellation of the cerebellar cortex and evaluated it by predicting functional boundaries in a novel set of tasks. The new parcellation successfully identified distinct functional subregions, providing significant improvements over existing parcellations derived from task-free data. Lobular boundaries, commonly used to summarize functional data, did not coincide with functional subdivisions. The new parcellation provides a functional atlas to guide future neuroimaging studies.

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Fig. 1: MDTB.
Fig. 2: DCBC.
Fig. 3: MDTB parcellation reveals functional boundaries in the cerebellar cortex.
Fig. 4: Comparison of MDTB and task-free parcellations of the cerebellum.
Fig. 5: Cognitive descriptors for the ten functional regions in the MDTB parcellation.

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Data availability

The activation maps and functional parcellations are available from http://www.diedrichsenlab.org/imaging/mdtb.htm. The raw behavioral and imaging data for the cerebellum are also available on the data sharing repository https://openneuro.org/.

Code availability

The experimental code is available at https://github.com/maedbhk/MDTB-Cerebellum.

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Acknowledgements

This work was supported by the James S. McDonnell Foundation (Scholar award to J.D.), the Canadian Institutes of Health Research (no. PJT 159520 to J.D.), a Platform Support Grant from Brain Canada and the Canada First Research Excellence Fund (BrainsCAN to Western University), the National Science Foundation (no. OAC-1649658 to R.A.P.) and the National Institute of Health (nos. NS092079 and NS105839 to R.B.I.). Data from the Human Connectome Project were analyzed by the Washington University–University of Minnesota Consortium (principal investigators: D. Van Essen and K. Ugurbil; no. 1U54MH091657) funded by the 16 National Institutes of Health (NIH) institutes and centers that support the NIH Blueprint for Neuroscience Research and by the McDonnell Center for Systems Neuroscience at Washington University. Thanks to J. Walters for assistance in task annotation.

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Authors and Affiliations

  1. Department of Psychology, University of California, CA, Berkeley, USA

    Maedbh King & Richard B. Ivry

  2. Brain and Mind Institute, Western University, Ontario, London, Canada

    Maedbh King, Carlos R. Hernandez-Castillo & Jörn Diedrichsen

  3. Department of Psychology, Stanford University, CA, Stanford, USA

    Russell A. Poldrack

  4. Department of Statistical and Actuarial Sciences, Western University, London, Ontario, Canada

    Jörn Diedrichsen

  5. Department of Computer Science, Western University, London, Ontario, Canada

    Jörn Diedrichsen

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  1. Maedbh King
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  2. Carlos R. Hernandez-Castillo
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  3. Russell A. Poldrack
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  4. Richard B. Ivry
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  5. Jörn Diedrichsen
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Contributions

R.B.I. and J.D. originally conceived of the project. M.K., J.D. and R.B.I. designed the study. M.K. and C.R.H.-C. collected the data. M.K. and J.D. performed the analyses. R.A.P., M.K., J.D. and R.B.I. annotated the cognitive tasks. M.K., J.D. and R.B.I. wrote the manuscript. All authors discussed the results and contributed to the final manuscript.

Corresponding author

Correspondence to Jörn Diedrichsen.

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The authors declare no competing interests.

Additional information

Journal peer review information: Nature Neuroscience thanks Fenna Krienen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Integrated supplementary information

Supplementary Figure 1 Unthresholded, group-averaged activation maps for the 47 unique task conditions displayed on a surface-based representation of the cerebellar cortex14.

All activations are calculated relative to the mean activation across all conditions. Red-to-yellow colors indicate increases in activation and blue colors indicate decreases in activation. Activity is normalized by the root-mean-square-error of the time-series fit for each voxel.

Supplementary Figure 2 Unthresholded, individual activation maps for 4 representative tasks and motor feature maps for 11 representative participants.

All activations are calculated relative to the mean activation across all conditions. Red-to-yellow colors indicate increases in activation and blue colors indicate decreases in activation. Activity is normalized by the root-mean-square-error of the time-series fit for each voxel.

Supplementary Figure 3 Stability of task performance.

Percent accuracy, averaged across two scanning sessions, each composed of eight runs. Average across all tasks is shown in black. Poorest performance was on the spatial map task (red line) and best performance was on the IAPS emotion task (green line). Error-bars indicate between-subject (N=24) standard error.

Supplementary Figure 4 Representational task space for 47 unique task conditions.

(a) Group-averaged representational dissimilarity matrix (RDM) data for the unique 47 task conditions. Shared tasks are averaged across the four scanning sessions. Dark blue represents low dissimilarity between pairwise task-evoked activity patterns while high distances (bright yellow) represent high dissimilarity between pairwise task-evoked activity patterns. Thresholded values are shown below the diagonal (dark blue cells indicating pairwise comparisons between task conditions were not significant (p<.001, e.g., pleasant and unpleasant scenes). (b) A multi-dimensional scaling plot (MDS, using first three PCs for display purposes), showing the relative similarity of the task-evoked activity patterns after correction for activity related to basic motor output. Hierarchical clustering was applied to the tasks, with colors in both the RDM and MDS indicating cluster membership.

Supplementary Figure 5 Comparison of task-based and task-free parcellations.

7, 10, and 17 region parcellations derived from task-free HCP (a-c) and MDTB (d-f) data. (g) Average Rand coefficient between task-free parcellations, computed locally (1cm sphere) around each cerebellar voxel. (h) Average Rand coefficient between MDTB parcellations. (i) Average difference of Rand coefficients for the MDTB and task-free parcellations.

Supplementary Figure 6 Cross-validated evaluation of MDTB parcellation on a subset of 7 tasks, selected to be most dissimilar to task conditions included in the data set.

For comparison purposes, task-free parcellations are evaluated on the same tasks. (a) MDTB parcellation trained on Set A and evaluated on 7 tasks from Set B (Mental Rotation Easy, Mental Rotation Medium, Mental Rotation Hard, Spatial Map Medium, Spatial Map Hard, Animated Movie, and Nature Movie). (b) MDTB parcellation trained on Set B and evaluated on 7 tasks from Set A (Sad Faces, Interval Timing, Go, Theory of Mind, Word Reading, Motor Imagery, Math). Error-bars indicate between-subject standard error (N=24).

Supplementary Figure 7 Pearson correlation between the task-profiles of the 10 regions of the MDTB parcellation.

The values in the correlation matrix are scaled between 0 (blue) and 1 (yellow). The bar on the right denotes the colors of each of the 10 regions (see Fig 5).

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King, M., Hernandez-Castillo, C.R., Poldrack, R.A. et al. Functional boundaries in the human cerebellum revealed by a multi-domain task battery. Nat Neurosci 22, 1371–1378 (2019). https://doi.org/10.1038/s41593-019-0436-x

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