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    Metadata details:
    filename: spm_slice_timing_mb.m
    path of file: ./repos/bspm/thirdparty/spm8
    
    the code of the file until where you have to start completion: function spm_slice_timing_mb(P, sliceorder, refslice, timing, prefix)

    
function spm_slice_timing_mb(P, sliceorder, refslice, timing, prefix)
% Correct differences in slice acquisition times
% FORMAT spm_slice_timing(P, sliceorder, refslice, timing, prefix)
% INPUT:
%   P          - nimages x ? Matrix with filenames
%                can also be a cell array of the above (multiple subj).
%   sliceorder - slice acquisition order, a vector of integers, each
%                integer referring the slice number in the image file
%                (1=first), and the order of integers representing their
%                temporal acquisition order
%                Multi-Band: array
%                [ [ 1 4]      same timepoint 1
%                  [ 3 6]      same timepoint 2
%                  [ 2 5] ]    same timepoint 3
%   refslice   - slice for time 0
%   timing     - additional information for sequence timing
%                timing(1) = time between slices
%                timing(2) = time between last slices and next volume
%   prefix     - filename prefix for corrected image files, defaults to 'a'
%
%   If no input is specified the function serves as a GUI           
%
% OUTPUT:
%   None
%
%   Slice-time corrected files are prepended with an 'a'
%
%   Note: The sliceorder arg that specifies slice acquisition order is
%   a vector of N numbers, where N is the number of slices per volume.
%   Each number refers to the position of a slice within the image file.
%   The order of numbers within the vector is the temporal order in which
%   those slices were acquired.
%
%   To check the order of slices within an image file, use the SPM Display
%   option and move the crosshairs to a voxel co-ordinate of z=1.  This
%   corresponds to a point in the first slice of the volume.
%
%   The function corrects differences in slice acquisition times.
%   This routine is intended to correct for the staggered order of
%   slice acquisition that is used during echoplanar scanning. The
%   correction is necessary to make the data on each slice correspond
%   to the same point in time. Without correction, the data on one
%   slice will represent a point in time as far removed as 1/2 the TR
%   from an adjacent slice (in the case of an interleaved sequence).
%
%   This routine "shifts" a signal in time to provide an output
%   vector that represents the same (continuous) signal sampled
%   starting either later or earlier. This is accomplished by a simple
%   shift of the phase of the sines that make up the signal.
%
%   Recall that a Fourier transform allows for a representation of any
%   signal as the linear combination of sinusoids of different
%   frequencies and phases. Effectively, we will add a constant
%   to the phase of every frequency, shifting the data in time.
%
%    Shifter - This is the filter by which the signal will be convolved
%    to introduce the phase shift. It is constructed explicitly in
%    the Fourier domain. In the time domain, it may be described as
%    an impulse (delta function) that has been shifted in time the
%    amount described by TimeShift.
%
%   The correction works by lagging (shifting forward) the time-series
%     data on each slice using sinc-interpolation. This results in each
%     time series having the values that would have been obtained had
%     the slice been acquired at the same time as the reference slice.
%
%   To make this clear, consider a neural event (and ensuing hemodynamic
%     response) that occurs simultaneously on two adjacent slices. Values
%     from slice "A" are acquired starting at time zero, simultaneous to
%     the neural event, while values from slice "B" are acquired one
%     second later. Without corection, the "B" values will describe a
%     hemodynamic response that will appear to have began one second
%     EARLIER on the "B" slice than on slice "A". To correct for this,
%     the "B" values need to be shifted towards the Right, i.e., towards
%     the last value.
%
%   This correction assumes that the data are band-limited (i.e. there
%     is no meaningful information present in the data at a frequency
%     higher than that of the Nyquist). This assumption is support by
%     the study of Josephs et al (1997, NeuroImage) that obtained
%     event-related data at an effective TR of 166 msecs. No physio-
%     logical signal change was present at frequencies higher than our
%     typical Nyquist (0.25 HZ).
%
% Written by Darren Gitelman at Northwestern U., 1998
%
% Based (in large part) on ACQCORRECT.PRO from Geoff Aguirre and
% Eric Zarahn at U. Penn.
%
% v1.0  07/04/98    DRG
% v1.1  07/09/98    DRG fixed code to reflect 1-based indices
%               of matlab vs. 0-based of pvwave
%
% Modified by R Henson, C Buechel and J Ashburner, FIL, to
% handle different reference slices and memory mapping.
%
% Modified by M Erb, at U. Tuebingen, 1999, to ask for non-continuous
% slice timing and number of sessions.
%
% Modified by R Henson for more general slice order and SPM2
%
% Modified by M Erb, at U. Tuebingen, 2013, for multiband
% slice timing
%_______________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging

% Darren Gitelman
% $Id: spm_slice_timing.m 4310 2011-04-18 16:07:35Z guillaume $


SPMid = spm('FnBanner',mfilename,'$Rev: 4310 $');
[Finter,Fgraph,CmdLine] = spm('FnUIsetup','Slice timing',0);

if nargin < 1,
        % get number of subjects
        nsubjects = spm_input('number of subjects/sessions',1, 'e', 1);
        if nsubjects < 1,
                spm_figure('Clear','Interactive');
                return;
        end