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ft_headmovement.m
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ft_headmovement.m
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function [grad] = ft_headmovement(cfg)
% FT_HEADMOVEMENT creates a representation of the CTF gradiometer definition
% in which the headmovement in incorporated. The result can be used
% for source reconstruction.
%
% Use as
% grad = ft_headmovement(cfg)
% where the configuration should contain
% cfg.dataset = string with the filename
% cfg.trl = Nx3 matrix with the trial definition, see FT_DEFINETRIAL
% cfg.numclusters = number of segments with constant headposition in which to split the data (default = 12)
%
% This method and related methods are described by Stolk et al., Online and
% offline tools for head movement compensation in MEG. NeuroImage, 2012.
%
% See also FT_REGRESSCONFOUND FT_REALTIME_HEADLOCALIZER
% Copyright (C) 2008-2010, Jan-Mathijs Schoffelen
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% for the documentation and details.
%
% FieldTrip is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% FieldTrip is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with FieldTrip. If not, see <http://www.gnu.org/licenses/>.
%
% $Id$
revision = '$Id$';
% do the general setup of the function
ft_defaults
ft_preamble init
ft_preamble provenance
ft_preamble trackconfig
ft_preamble debug
% the abort variable is set to true or false in ft_preamble_init
if abort
return
end
% check if the input cfg is valid for this function
cfg = ft_checkconfig(cfg, 'dataset2files', {'yes'});
% set the defaults
if ~isfield(cfg, 'numclusters'), cfg.numclusters = 12; end
% read the header information
hdr = ft_read_header(cfg.headerfile);
% work with gradiometers in dewar coordinates, since HLCs are also
% in dewar coords. at present I did not find the nas, lpa, rpa channels,
% which according to ctf's documentation should contain the positions
% of these channels directly (HDAC channels). FIXME
grad_head = ctf2grad(hdr.orig, 0);
grad_dewar = ctf2grad(hdr.orig, 1);
grad_head = ft_datatype_sens(grad_head); % ensure up-to-date sensor description (Oct 2011)
grad_dewar = ft_datatype_sens(grad_dewar); % ensure up-to-date sensor description (Oct 2011)
grad = grad_dewar; % we want to work with dewar coordinates, ...
grad.chanpos = grad_head.chanpos; % except the chanpos, which should remain in head coordinates
% read HLC-channels
% HLC0011 HLC0012 HLC0013 x, y, z coordinates of nasion-coil in m.
% HLC0021 HLC0022 HLC0023 x, y, z coordinates of lpa-coil in m.
% HLC0031 HLC0032 HLC0033 x, y, z coordinates of rpa-coil in m.
tmpcfg = [];
tmpcfg.dataset = cfg.dataset;
tmpcfg.trl = cfg.trl;
tmpcfg.channel = {'HLC0011' 'HLC0012' 'HLC0013'...
'HLC0021' 'HLC0022' 'HLC0023'...
'HLC0031' 'HLC0032' 'HLC0033'};
tmpcfg.continuous = 'yes';
data = ft_preprocessing(tmpcfg);
%resample doesn't work, because data will be demeaned
%tmpcfg = [];
%tmpcfg.resamplefs = 100;
%data = resampledata(tmpcfg, data);
dat = zeros(length(data.label), 0);
wdat = zeros(1, 0);
for k = 1:length(data.trial)
tmpdat = data.trial{k};
utmpdat = unique(tmpdat','rows')';
dat = [dat utmpdat];
wtmpdat = zeros(1,size(utmpdat,2));
for m = 1:size(utmpdat,2)
wtmpdat(1,m) = sum(sum(tmpdat-utmpdat(:,m)*ones(1,size(tmpdat,2))==0,1)==9);
end
wdat = [wdat wtmpdat];
end
dat(:, wdat<100) = [];
wdat(wdat<100) = [];
switch grad.unit
case 'm'
%do nothing
case 'cm'
dat = dat.*100;
case 'mm'
dat = dat.*1000;
otherwise
keyboard
end
nhcoils = size(dat,1);
nsmp = size(dat,2);
[bin, cluster] = kmeans(dat', cfg.numclusters);
selnas = strmatch('HLC001', data.label);
sellpa = strmatch('HLC002', data.label);
selrpa = strmatch('HLC003', data.label);
ubin = unique(bin);
for k = 1:length(ubin)
nas(k, :) = cluster(k, selnas);
lpa(k, :) = cluster(k, sellpa);
rpa(k, :) = cluster(k, selrpa);
numperbin(k) = sum(wdat(bin==ubin(k)));
end
if 1,
hc = read_ctf_hc([cfg.datafile(1:end-4),'hc']);
trf = hc.homogenous;
xdir = trf(1,1:3);
ydir = trf(2,1:3);
zdir = trf(3,1:3);
trf2 = inv(hc.homogenous);
origin = trf2(1:3,4)';
xaxis = [repmat(origin, [15 1]) + [0:14]'*xdir];
yaxis = [repmat(origin, [9 1]) + [0:8]'*ydir; ...
repmat(origin, [9 1]) - [0:8]'*ydir];
zaxis = [repmat(origin, [10 1]) + [0:9]'*zdir; ...
repmat(origin, [3 1]) - [0:2]'*zdir];
% plot some stuff
figure; hold on;
plot3(xaxis(:,1),xaxis(:,2),xaxis(:,3),'k.-');
plot3(yaxis(:,1),yaxis(:,2),yaxis(:,3),'k.-');
plot3(zaxis(:,1),zaxis(:,2),zaxis(:,3),'k.-');
fiducials = [nas;lpa;rpa];
h = plot3(fiducials(:,1), fiducials(:,2), fiducials(:,3), 'b.');
plot3(hc.dewar.nas(1), hc.dewar.nas(2), hc.dewar.nas(3), 'ro');
plot3(hc.dewar.lpa(1), hc.dewar.lpa(2), hc.dewar.lpa(3), 'ro');
plot3(hc.dewar.rpa(1), hc.dewar.rpa(2), hc.dewar.rpa(3), 'ro');
axis vis3d; axis off
end
% compute transformation matrix from dewar to head coordinates
transform = zeros(4, 4, size(nas,1));
for k = 1:size(transform, 3)
transform(:,:,k) = ft_headcoordinates(nas(k,:), lpa(k,:), rpa(k,:), 'ctf');
end
npos = size(transform, 3);
ncoils = size(grad.coilpos, 1);
gradnew = grad;
gradnew.coilpos = zeros(size(grad.coilpos,1)*npos, size(grad.coilpos,2));
gradnew.coilori = zeros(size(grad.coilpos,1)*npos, size(grad.coilpos,2));
gradnew.tra = repmat(grad.tra, [1 npos]);
for m = 1:npos
tmptransform = transform(:,:,m);
gradnew.coilpos((m-1)*ncoils+1:(m*ncoils), :) = ft_warp_apply(tmptransform, grad.coilpos); % back to head-crd
tmptransform(1:3, 4) = 0; % keep rotation only
gradnew.coilori((m-1)*ncoils+1:(m*ncoils), :) = ft_warp_apply(tmptransform, grad.coilori);
gradnew.tra(:, (m-1)*ncoils+1:(m*ncoils)) = grad.tra.*(numperbin(m)./sum(numperbin));
end
grad = gradnew;
% do the general cleanup and bookkeeping at the end of the function
ft_postamble debug
ft_postamble trackconfig
ft_postamble provenance