# General information:
- Data in this repository has been acquired as part of Nicole Eichert's PhD project at the University of Oxford, which was supervised by Rogier B. Mars and Kate E. Watkins.

- Funding for this project was provided by the Wellcome Trust [203730/Z/16/Z]

- Data in this repository has been used in multiple projects that involved different collaborators. For project-specific authorship and acknowledgements, please refer to the relevant references.

- Main data papers:
    - Eichert N, Robinson EC, Bryant KL, Jbabdi S, Jenkinson M, Li L, Krug K, Watkins KE, Mars RB. 2020. Cross-species cortical alignment identifies different types of anatomical reorganization in the primate temporal lobe. eLife 9. doi:10.7554/eLife.53232
    - Eichert N, Papp D, Mars RB, Watkins KE. 2020. Mapping Human Laryngeal Motor Cortex during Vocalization. Cerebral Cortex 30:6254–6269. doi:10.1093/cercor/bhaa182
    - Eichert N, Watkins KE, Mars RB, Petrides M. 2020. Morphological and functional variability in central and subcentral motor cortex of the human brain. Brain Structure and Function (accepted). doi:10.1007/s00429-020-02180-w

- not all scripts in the related code repositories run directly on the OpenNeuro dataset because it does not contain all intermediate data

- all missing intermediate data can, in principle, be reconstructed using the provided code, but file paths might have to be adapted

# Data related to Eichert et al. 2020 eLife:
- related processing code and result scene files can be found at [https://git.fmrib.ox.ac.uk/neichert/project_msm](https://git.fmrib.ox.ac.uk/neichert/project_msm/-/tree/master/)
- relevant data are subfolder /dwi, surface reconstructions and T1w/T2w myelin maps

# Data related to Eichert et al. 2020 Cerebral Cortex:
- related processing code can be found at [https://git.fmrib.ox.ac.uk/neichert/project_larynx](https://git.fmrib.ox.ac.uk/neichert/project_larynx/-/tree/master/)
- the first 25 volumes of all individual bold task scans need to be discarded prior to analysis. These volumes were acquired during the time, where noise-cancelling headphones 'learned' the scanner noise
- the fieldmap for subject 11 can only be applied to the 'ArtVoc' bold task scan and not to the 'Factorial' bold task scan
- average inflated surfaces are stored in `/derivatives/group/anat/group.{hemi}.inflated.32k_fs_LR.surf.gii` (and 164k)
- individual native midthickness surfaces are stored in `/derivatives/sub-{sub}/anat/sub-{sub}.{hemi}.midthickness.native.surf.gii`

- Figure 1C - breathing traces:
    - cropped individual breathing traces are stored in `/derivatives/sub-{sub}/beh/sub-{sub}_breathing-traces.pkl`. The file can be loaded using Python's pandas package.
    - raw data containing subject's breathing traces during the functional scan is stored in `/sub-{sub}/beh/sub-{sub}/sub-{sub}_biopac.mat`

- Figure 2 and Figure 3 - group level fMRI results:
    - task: 'ArtVoc' for the basic localizer task and 'Factorial' for the syllable production task
    - contrast: lip, tongue, vowel for 'ArtVoc' (Figure 3); vocalization, articulation for 'Factorial' (Figure 2)
    - volumetric results in MNI space are stored in `/derivatives/group/func/task/group_task-{task}_{contrast}_zstat1.nii.gz`
    - surface count maps are stored in `/derivatives/group/func/task/group_task-{task}_{contrast}_{hemi}_32k_fs_LR.func.gii`

- Figure 4 - surface metrics
    - average T1w/T2w and thickness maps are stored in `/derivatives/group/anat`
    - averate mpm maps are stored in `/derivatives/group/mpm`
    - individual surface maps are stored in `derivatives/sub-{sub}/anat` and `derivatives/sub-{sub}/mpm`

- Figure 5 - quantitative analysis
    - numerical values underlying the figures are stored as csv-files in `/derivatives/group/mpm/*csv`

# Data related to Eichert et al. 2020 Brain Structure and Function:
- related processing code can be found at [https://git.fmrib.ox.ac.uk/neichert/project_variability](https://git.fmrib.ox.ac.uk/neichert/project_variability/-/tree/master/)
- Subject-IDs 01 - 20 refer to the subjects that contributed both structural and functional data (also used for the other two papers)
- Subject-IDs 21 - 50 refer to the HCP subjects that only contributed structural data (to be shared)

- Fig. 1B - individual example
    - data of sub-20 is shown

- Fig. 3 - probability maps
    - volumetric and surface probability maps are stored in `/derivatives/group/sulci/`
    
- Fig. 4 - Anatomical measures:
    - numerical values are provided in the file `/derivatives/group/sulci/anatomical_quantifications.csv`

- Fig. 5 - All individual sulci and peaks
    - all individual sulcal labels and functional activation peaks in native space are provided in the files `/derivatives/sub-{sub}/anat/sulci_{hemi}.label.gii` and `derivatives/sub-{sub}/func/peaks_{hemi}.func.gii`
    - the manually drawn ventral ROI to extract the ventral peak is provided in `/derivatives/sub-{sub}/anat/ventral_ROI_{hemi}.func.gii`
    - they can be displayed together with the native surface in `/derivatives/sub-{sub}/anat/sub-{sub}.{hemi}.midthickness.native.surf.gii`

- Fig. 6 - Effect of registrations
    - numerical values are provided in the file `/derivatives/group/anat/sulci/peak_distances.csv`

- Fig. 7 (Supplementary Material) - Anatomical measures per morphological type
    - numerical values are provided in the file `/derivatives/group/sulci/anatomical_quantifications.csv`

- Table 1 - Morphological types
    - numbers can be inferred from the provided csv file `/derivatives/group/sulci/structure_function_links.csv`
    
- Table 2 - Coordinates
    - can be derived from volumetric probability maps
    
- Table 3 - Structure-function-relationships
    - numbers can be inferred from the provided csv file `/derivatives/group/sulci/structure_function_links.csv`