PrAGMATiC: a Probabilistic and Generative Model of Areas Tiling the Cortex
Abstract
Much of the human cortex seems to be organized into topographic cortical maps. Yet few quantitative methods exist for characterizing these maps. To address this issue we developed a modeling framework that can reveal group-level cortical maps based on neuroimaging data. PrAGMATiC, a probabilistic and generative model of areas tiling the cortex, is a hierarchical Bayesian generative model of cortical maps. This model assumes that the cortical map in each individual subject is a sample from a single underlying probability distribution. Learning the parameters of this distribution reveals the properties of a cortical map that are common across a group of subjects while avoiding the potentially lossy step of co-registering each subject into a group anatomical space. In this report we give a mathematical description of PrAGMATiC, describe approximations that make it practical to use, show preliminary results from its application to a real dataset, and describe a number of possible future extensions.
Cite
@article{arxiv.1504.03622,
title = {PrAGMATiC: a Probabilistic and Generative Model of Areas Tiling the Cortex},
author = {Alexander G. Huth and Thomas L. Griffiths and Frederic E. Theunissen and Jack L. Gallant},
journal= {arXiv preprint arXiv:1504.03622},
year = {2015}
}