- How to use Blocked fMRI Session Profile

Before you start to analyze Blocked fMRI scan data, you need to input 
data and parameters. You also would like to save the inputted information
into a file for later retrieval.

This SESSION PROFILE window provides you with an efficient way to input
and save the data and parameters, as well as to create a corresponding
datamat.

One Blocked fMRI Session represents one subject, which includes a group
of runs in a set of conditions. Each condition will have different blocks
of onset images for different runs. The length of block can be varied.



- Session Description

It is nice to have a Sesson Description to describe what this experiment 
will include.



- Working Directory

To use this window, you MUST provide a PLS Data Directory name (or you
can also call it 'Working Directory'). In this directory, you will 
save the session file, datamat, and result file.

Like the way you prepare the data for command_line PLS analysis for
Blocked fMRI scan, you already have several runs of the subject data. 
They should be organized in a way such as each run has its own directory,
and inside the directory, there will be scan files for that run. It will 
be convenient for you if you put runs' directories immediately under your
working directory.



- Datamat Prefix

It is more convenient to tell the data from its file name, before open
it. We use '_fMRIsession.mat' to represent Blocked fMRI session 
profile; use '_fMRIdatamat.mat' to represent Blocked fMRI datamat; 
use '_fMRIresult.mat' to represent Blocked fMRI result data. So, 
enter a meaningful datamat prefix here will make yourself easy later.



- Edit Conditions

Click 'Input Conditions' to enter the condition names under which you 
get those experiment data. The 'Reference Scan Onset' and 'Number of 
Reference Scans' are options you can use if you would like to use 
multiple scans (we call it reference scans) to express the stimulus 
effect, instead of just 1 scan. By default, stimulus effects for a block
are calculated with respect to the first scan of the time series.  
Changing the values in these fields allows you to use a different set of 
images to define the pre-stimulus interval.  The 'Reference Scan Onset'
is the first image scan for the reference scans. After you click 'DONE',
the number of conditions you entered will be displayed in 'Number of 
Conditions:' field. 



- Edit Run

In order to click 'Edit Run', you must first enter the number of runs to
be used for the PLS analysis. Once you click the 'Edit Run', the Run
Information window will open.

First, you need to provide Number of Scans that will be used for PLS 
analysis. Then, click 'Browse' to select the same amount of scan files
from the run directory. In the Block Onsets frame, you provide the the
scan numbers at the onset of all stimulus event (like 12 24 36) for each
condition. Onsets are specified in terms of scan number, which starting 
from 0.  If a onset is located between two scans, decimal number can be 
used for the onset. However, it will be converted to the closest smaller
integer number. You also need to provide the length of block for each
stimulus. If you just enter one value in the Length field, it will 
automatically apply this value to all the stimulus in this condition.

Click '>>' button to the next run, and repeat the above steps for all
the runs until the '>>' button is disabled. Then, click 'DONE'.

You can leave some some task condition empty for some runs; however, you
can not leave one condition empty across all the runs.

TIPS -

Input Onset:
	Onsets can be inputted by calling a MATLAB statement.  If the first 
	character of the onset edit line is '@', the rest of the line will 
	be interpreted as a MATLAB command which return a vector for the
	onsets.  Before the line being executed as MATLAB statement, any
	words of '{run#}' and '{cond#}' in the statement will be replaced
	by the current run number and condition number, respectively.

	To repeat the last MATLAB statement, put '@@' in the onset edit 
	line. 



- Create Datamat

In Block fMRI, one session file will have one (and only one) datamat
file, each session file (or datamat file) is corresponding to one
subject. It will need both session and datamat file to run analysis 
and display result.

Before creating datamat, you muse have the session profile saved first.
Click the 'Create Datamat ...' will lead you to Create Datamat window.

In the Brain Region frame, you can either use a predefined brain region 
image, or enter a value in the threshold field to define the brain 
region. Any voxels with values below 1/threshold of the max. value in 
the volumes will be removed.

If 'Number of scans to be skipped' field is not zero, it stands for the
number of image files that were not included in the selected Data Files
list in the 'Browse Data File' in 'Run Information' window, while the
onset is numbered from the whole file list.

If there is no image files excluded, or if you number the onset based on
the selected file list (from 'Browse Data File' in the 'Run Information'
window), you can always keep the 'Number of scans to be skipped' field 0,
which is the default value of the program.

The default value for 'Run to be included' list is [1:max_run]. You can 
modify this list to exclude some runs. The default value for 'Slices to
be ignored' list is empty, and you can modify this list to exclude some
slices in Z direction. If you normalize data with the volume mean 
(default), for each row (or each scan, or each volume), the data will be
divided by the mean of this row. If you normalize data with the baseline
(default), for each row (or each scan, or each volume), the data will be
divided by the mean of the baseline scans. If you merge data of each 
condition within each run only, same condition in different runs will be
on a separate row; otherwise, all same condition will be averaged in the
same row.

If you prepare to run Behavior PLS, you MUST also provide the behavior 
data, which is not required for running Task PLS. The number of rows of
your behavior data must match the Behavior PLS test you are running. For
example, if there are 3 conditions, and you chose 'across all runs', the
number of rows in behavior data will be 3. If you chose 'within each run'
and you have 5 runs, then, the number of rows in behavior data will be 
3*5 = 15

The behavior data is prepared in ASCII format.

Once you click 'Edit Behavior Data' button, the 'Edit Behavior Data'
window will open. You can click the 'Browse' button to get the behavior
data text file you prepared, or you can also directly enter the number
into the text input area.

Depending on how many column in the 'Behavior Data', the 'Behavior Name'
will automatically be filled as 'behav1 behav2 ...'. You can change the
behavior name by edit them. You can use any alphanumeric or '_' charactor
for behavior name. Don't use special charactors, also don't use space,
which acts like a delimiter.

If you chose 'across all runs', the row order of behavior data is the
same as condition order. If you chose 'within each run', the row order
of behavior data is in the form of [cond1/run1; cond1/run2; ... ;
cond2/run1; cond2/run2; ...;]. i.e. in the order of each run, then in
the order of each condition.

After you click 'OK' button, the data you entered will be saved into 
the session file, corresponding to either 'across all run' or 'within
each run'. So, each session file can save 2 sets of behavior data.