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Meta-Analysis
. 1999;8(2-3):143-50.
doi: 10.1002/(sici)1097-0193(1999)8:2/3<143::aid-hbm12>3.0.co;2-9.

Functional Volumes Modeling: Scaling for Group Size in Averaged Images

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Meta-Analysis

Functional Volumes Modeling: Scaling for Group Size in Averaged Images

P T Fox et al. Hum Brain Mapp. .

Abstract

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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