Referral to description of layerification algorithm in LN2_LAYERS

How can one assign layers to discrete voxels? Is it possible to perform topographical fMRI analyses across layers and columns directly in the original voxel space that raw data from the scanner come in? 

New additions in LAYNII make it possible.

Faruk Gulban purged, restructured, and debugged old layerificaton algorithms in LAYNII, he added capabilities of new data types (incl. nii.gz) to all LAYNII programs and revised the package structure. 

However, most importantly, he also added a new layerification program to it; LN2_LAYERS:

  • This program can estimate equi-distance and equi-volume layers of any segmented NIFTI image.
  • The input data do not need to be closed volumes that fulfil topological constraints. Instead, the algorithm works in any segmented data e.g. the conventional whole brain anatomy or in EPI-space, in slab data, and with unconnected areas. 
  • The program reads and writes nii and nii.gz in any common data types: 16bit, 32bit, 63bit, om ints and floats. 
  • It is so fast, that it processes equi-distance layers of the entire 200μm BigBrain in 2 min (12 min for equi-vol) with a single core.  
  • As a side result, it calculates multiple additional useful metrics: mid-gray matter, curvature estimates, columnar units. 
  • The algorithm is using his pet concept of simplex space and is largely based on an iterative growing algorithm.

Faruk describes the program’s algorithm step-by-step in a highly entertaining blog post here: https://thingsonthings.org/ln2_layers/

Faruk's description of LN2_LAYERS

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