Featquery - FEAT Results Interrogation
User Guide


Introduction

Featquery is a script which allows you to interrogate FEAT results by defining a mask (or co-ordinates of a single-voxel) in standard-space, highres-space or lowres-space, to get mean, max etc stats values and time-series within that mask or at that voxel position. For example, you might define a standard-space mask for the motor cortex, and Featquery will tell you the mean (and peak) % signal change associated with your modelled experimental paradigm within that area.

First you must select a previously-created FEAT output directory whose results you wish to investigate. You can run multiple queries by changing the Number of FEAT directories. The results of running Featquery will be saved in a directory ("featquery") inside each FEAT directory chosen. If you have already run Featquery on a FEAT directory, a "+" will be appended to the subdirectory name, e.g. "featquery+".

Choosing stats images to investigate

Once you have selected a FEAT directory, a list of all possibly interesting stats images inside that FEAT directory will appear on the Featquery GUI. Turn on the ones you are interested in. (If you turn on filtered_func_data you will be given mean (and max etc) stats values within the defined mask, including searching over time as well as space.)

If you select Convert PE/COPE values to %, any PE or COPE parameter estimate or contrast values will be converted to percentage change values before reporting. This is achieved by dividing the PE/COPE values by the mean image from filtered_func_data. Warning: this % is based on the assumption that the "height" of the model waveform is 1, which in general it is for FEAT-created block designs, but in general is not for event-related designs or custom waveforms. In order to get a true % change value you must multiply the output by the height of the relevant model waveform (see the design.mat file). In the case of contrasts (COPEs), the interpretation of this % needs even more careful thought.

Setting up a mask or voxel co-ordinates

You must now choose a Mask image. This would normally be a binary image in standard-space, highres-space or lowres-space, with a region-of-interest (ROI), for example, the visual cortex, created by any method. Featquery will automatically detect which space this mask is in (ie standard-space, highres-space or lowres-space) and will transform it into the native lowres space of example_func; of course this can only work if FEAT registration was setup and carried out.

If you want a different mask for each selected FEAT directory, specify a mask name as a relative filename (ie without a "/"). This mask will then be looked for relative to each FEAT directory.

Alternatively, you can specify a single position (in voxels or mm) at which to extract values from the chosen stats images. This still requires a "mask" image to be chosen, as it is relative to this mask image that the co-ordinates have meaning. Thus if you want the co-ordinates to be in lowres space, just select "mask" or "example_func"; if you want to specify standard-space co-ordinates ("Talairach space") then choose "reg/standard". It is wise to be careful here - after running Featquery, have a look at the created featquery/mask image to check that the voxel finally chosen is in a sensible place!

Advanced options

If you want to only allow stats values above a threshold to enter into the calculations (of mean, max etc) then turn on Apply threshold and select a value.

If you have selected a mask image in standard or highres space, this will get transformed into lowres space as described above. This involves interpolation; at the edges of the mask there will be a continuous range of values from 1 down to 0. In order to get back to a binary mask, this must be thresholded at some value - the default is 0.5. However, if you want the mask to be slightly more or less inclusive than that default, you can Change mask post-interpolation thresholding - for example, by reducing the value to 0.3, the final lowres mask will be slightly larger.

Go

When you press Go, Featquery produces all the requested stats values including mean, min, max and position of max. These get logged to the file report.txt inside the featquery subdirectory inside the FEAT directory, and also copied to the screen. Also, various timeseries textfiles are saved; one for the mean timeseries over the mask, and also one for each of the positions of the max value of each of the stats images.


Copyright © 2002, University of Oxford. Written by S. Smith.