baselineCorrect.m

function xBL = baselineCorrect(xIn, samps)

% xBL = baselineCorrect(xIn, samps)
% -----------------------------------
% Blair - Oct. 19, 2015
% This function takes in the channels x time EEG data matrix X and returns
% an output matrix xBL, whose rows have been baseline corrected by
% subtracting from each row the mean of voltages indexed by samps.
%
% Typically xIn is one trial of data, and samps indexes the sample numbers
% corresponding to the pre-stimulus or < 50ms post-stimulus interval.
%
% Nov. 13, 2017: Now uses nanmean rather than mean

% This software is licensed under the 3-Clause BSD License (New BSD License), 
% as follows:
% -------------------------------------------------------------------------
% Copyright 2015 Blair Kaneshiro
% 
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions are met:
% 
% 1. Redistributions of source code must retain the above copyright notice, 
% this list of conditions and the following disclaimer.
% 
% 2. Redistributions in binary form must reproduce the above copyright notice, 
% this list of conditions and the following disclaimer in the documentation 
% and/or other materials provided with the distribution.
% 
% 3. Neither the name of the copyright holder nor the names of its 
% contributors may be used to endorse or promote products derived from this 
% software without specific prior written permission.
% 
% THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS ?AS IS?
% AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 
% IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE 
% ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE 
% LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR 
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% CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) 
% ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 
% POSSIBILITY OF SUCH DAMAGE.

xBL = xIn - repmat(nanmean(xIn(:,samps),2), 1, size(xIn,2));