Hi-
The definitions are provided in the helpfile of 3dTrackID, under the description of the *.grid files. I probably shouldn't paste the helpfile, but I will, below.
3) *.grid ASCII-text file (output in ALL modes).
Simple text file of output stats of WM-ROIs. It outputs the means and
standard deviations of parameter quantities (such as FA, MD, L1, etc.)
as well as counts of tracks and volumes of WM-ROIs. Each matrix is
square, with dimension N_ROI by N_ROI. Like the locations in a standard
correlation matrix, each element reflects associativity with target
ROIs. A value at element (1,3) is the same as that at (3,1) and tells
about the property of a WM-ROI connecting target ROIs 1 and 3 (consider
upper left corner as (1,1)); diagonal elements provide info of tracks
through (at minimum) that single target ROI-- like OR logic connection.
Format of *.grid file is:
Line 1: number of ROIs in network (padded with #-signs)
Line 2: number of output matrices of stats info (padded with #-signs)
Line 3: list of N_ROI labels for that network
Lines following: first line, label of a property (padded with #), and
then N_ROI lines of the N_ROI-by-N_ROI matrix of that
property;
/repeat/
The first *five* matrices are currently (this may change over time):
NT = number of tracks in that WM-ROI
fNT = fractional number of tracks in that WM-ROI, defined as NT
divided by total number of tracts found (may not be relevant)
PV = physical volume of tracks, in mm^3
fNV = fractional volume of tracks compared to masked (internally or
'-mask'edly) total volume; would perhaps be useful if said
mask represents the whole brain volume well.
NV = number of voxels in that WM-ROI.
Then, there can be a great variety in the remaining matrices, depending
on whether one is in DTI or HARDI mode and how many scalar parameter
files get input (max is 10). For each scalar file there are two
matrices: first a label (e.g., 'FA') and then an N_ROI-by-N_ROI matrix
of the means of that parameter in each WM-ROI; then a label (here,
would be 'sFA') and then an N_ROI-by-N_ROI matrix of the standard
deviations of that parameter in each WM-ROI.
NB: for exactness, I note that your definition (and similar for L2 and L3):
Quote
L1 - direction 1
isn't quite how I would phrase it; the eigen*vectors* (V1, V2, V3; or, sometimes written in papers as e1, e2, e3) provide the direction/orientation of each ellipsoid semiaxis; the eigen*values* (L1, L2, L3) are related to the amount of diffusion along each ellipsoid semiaxis.
--pt