HowTo #2:
			  Experiment Background

Block design -  visual processing of human motion versus tool motion.


The Experiment:

     In this example, subjects were presented with pictures of various
     moving objects, which fell into one of four categories:

		1. Animate Human (a)
		2. Moving Tool (t)
		3. Low Contrast Moving Grating (l)
		4. High Contrast Moving Grating (h)

         (Note: Gratings consisted of concentric light and dark rings with
                either a high or low color contrast between the rings.)
     
     For each 275 second MR run, subjects viewed 21-second blocks of no visual
     stimulation (white fixation crosshairs on a gray background), alternating
     with six 21-second blocks of visual motion stimulation (white fixation 
     crosshairs overlaid on a motion stimulus on a gray background).  Each
     21-second block contained seven 3-second trials of a single type of motion
     stimulus.  The blocks were presented in pseudo random order that differed 
     in each MR scan series.  


The Data:
 
   The following data were collected from subject 'DD': 

		* One spoiled grass anatomical scan.
		* Four echo planar time series scans.
	
    The spoiled grass data consist of 124 sagittal slices, from 70.0 mm Left
    to 77.6 mm Right (orientation is ASL).  Each slice is a 256 x 256 voxel
    image, with each voxel being a 0.938 mm square.  The slice thickness 
    (i.e., the distance between 2 slices) is 1.2 mm.

    The echo planar data consist of 110 volumes, 27 sagittal slices, from 
    69 mm Right to 35 mm Left (orientation is SPR).  Each slice is a 64 x 64 
    voxel image, with a voxel resolution of 3.75 mm square.  The thickness of 
    each of the 27 slcies is 5.0 mm.

    The SPGR data are located under the 'SPGR_data' directory, in 124 I-files 
    (i.e., I.001 through I.124).

    The EPI data are located under the 'EPI_data' directory.  Each image file 
    is labeled by: (1) run number, (2) slice number, and (3) time point.  For 
    example, the first image file in this directory is 'DDr1_01.001', which 
    represents run 1, slice 1, time point 1 for subject DD.  The last image
    file in this directory is 'DDr4_27.110', which represents the fourth run,
    27th slice, and 110th time point for subject DD. 


Predictions:

    Visual processing within the lateral occipital-temporal cortex 
    (i.e., area MT) will be examined.  This brain region appears to be 
    differentially sensitive to the motional properties of different visual 
    categories.  
		
    Specific regions within area MT, such as the Superior Temporal Sulcus (STS)
    and Middle Temporal Gyrus (MTG) are believed to specialize in motion 
    detection of specific types of objects.  

    Primarily, the STS responds to moving and static biological objects, such 
    as human beings or animals.  The MTG responds to moving and static objects 
    that are manipulable, but non-biological in nature (e.g., tools) but not to
    static, unmanipulable objects such as buildings.


Results:

	* Areas MT, STS, and MTG each responded to the motion stimuli, and all
	  three areas preferred human and tool movement to moving gratings.

	* Area MT showed no significant preference for human or tool motion.

	* Area STS showed a larger response for human motion compared with 
	  tool motion.

	* Area MTG showed a larger response for tool motion compared with human
	  motion.

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Steps taken to analyze the data:

We have created and run a shell script (called @DDmb_analyze), which performs 
the following steps:

   o  Create AFNI bricks for SPGR and EPI data with 'to3d'.
   
   o  Use '3dTcat' to concatenate the four EPI volumes into one large dataset 
      containing 432 time points (110 times points x 4 = 440, but first two 2 
      time points in each run were removed, 440 - 8 = 432).
 
   o  Use '3dvolreg' to register each time point in our concatenated EPI 
      dataset with the last time point.  This process will correct for small
      subject head movements that may have occurred during the scanning 
      session.

   o  For each stimulus condition, use 'cat' to concatenate the stimulus 
      timing files from the four runs into one large file.

   o  Use 'waver' to create an ideal hemodynamic response function, one for 
      each stimulus times series.

   o  Create a functional brick with program '3dDeconvolve'.  This program 
      is used to calculate the least squares estimates of the linear 
      regression coefficients, t-statistics for significance of the 
      coefficients, partial F-statistics for significance of the individual 
      input stimuli, and the F-statistic for significance of the overall 
      regression.  Additional general linear tests will also be conducted.
      These statistics will be saved in one large "bucket" dataset.