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Hum Brain Mapp. 1999;8(2-3):143-50.

Functional volumes modeling: scaling for group size in averaged images.

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  • 1Research Imaging Center, University of Texas Health Science Center, San Antonio, Texas 78284-6240, USA.


Functional volumes modeling (FVM) is a statistical construct for metanalytic modeling of the locations of brain functional areas as spatial probability distributions. FV models have a variety of applications, in particular, to serve as spatially explicit predictions of the Talairach-space locations of functional activations, thereby allowing voxel-based analyses to be hypothesis testing rather than hypothesis generating. As image averaging is often applied in the analysis of functional images, an important feature of FVM is that a model can be scaled to accommodate any degree of intersubject image averaging in the data set to which the model is applied. In this report, the group-size scaling properties of FVM were tested. This was done by: (1) scaling a previously constructed FV model of the mouth representation of primary motor cortex (M1-mouth) to accommodate various degrees of averaging (number of subjects per image = n = 1, 2, 5, 10), and (2) comparing FVM-predicted spatial probability contours to location-distributions observed in averaged images of varying n composed from randomly sampling a 30-subject validation data set.

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