Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 1999;8(2-3):143-50.
doi: 10.1002/(sici)1097-0193(1999)8:2/3<143::aid-hbm12>;2-9.

Functional Volumes Modeling: Scaling for Group Size in Averaged Images


Functional Volumes Modeling: Scaling for Group Size in Averaged Images

P T Fox et al. Hum Brain Mapp. .


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.

Similar articles

See all similar articles

Cited by 7 articles

See all "Cited by" articles

Publication types

LinkOut - more resources