Decode surface data

Correlates the significant clusters of an earlier vertex-wise analysis with a database of task-based fMRI and voxel-based morphometric statistical maps and associate them with relevant key words. Decoding currently works with surfaces in fsaverage5 space only."

Usage

decode_surf_data(surf_data, contrast = "positive", VWR_check = TRUE)

Arguments

surf_data

A numeric vector or object containing the surface data, in fsaverage5 (1 x 20484 vertices). It can only be one row of vertices (not a cohort surface data matrix).

contrast

A string object indicating whether to decode the positive or negative mask ('positive' or 'negative')

VWR_check

A boolean object specifying whether to check and validate system requirements. Default is TRUE.

Value

A data.frame object listing the keywords and their Pearson's R values

Details

The 'NiMARE' python module is used for the imaging decoding and is imported via the reticulate package. The function also downloads the 'Neurosynth' database in the package's inst/extdata directory (~8 Mb) for the analysis.

Examples

CTv = rbinom(20484, 1, 0.001) 
decoding = decode_surf_data(CTv, 'positive', VWR_check=FALSE);
#> Converting and interpolating the surface data ... 
#> ✓ 
#>  Correlating input image with images in the neurosynth database. This may take a while ... 
#> ✓ 
head(decoding)
#>         keyword     r
#> 195    encoding 0.052
#> 538   retrieval 0.051
#> 311    language 0.046
#> 510 recognition 0.044
#> 202    episodic 0.043
#> 381       motor 0.041