English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
  Model-based clustering of meta-analytic functional Imaging data

Neumann, J., von Cramon, D., & Lohmann, G. (2008). Model-based clustering of meta-analytic functional Imaging data. Human Brain Mapping, 29(2), 177-192. doi:10.1002/hbm.20380.

Item is

Files

show Files

Locators

show
hide
Description:
-
OA-Status:

Creators

show
hide
 Creators:
Neumann, J, Author
von Cramon, DY, Author
Lohmann, G1, Author           
Affiliations:
1External Organizations, ou_persistent22              

Content

show
hide
Free keywords: -
 Abstract: We present a method for the analysis of meta‐analytic functional imaging data. It is based on Activation Likelihood Estimation (ALE) and subsequent model‐based clustering using Gaussian mixture models, expectation‐maximization (EM) for model fitting, and the Bayesian Information Criterion (BIC) for model selection. Our method facilitates the clustering of activation maxima from previously performed imaging experiments in a hierarchical fashion. Regions with a high concentration of activation coordinates are first identified using ALE. Activation coordinates within these regions are then subjected to model‐based clustering for a more detailed cluster analysis. We demonstrate the usefulness of the method in a meta‐analysis of 26 fMRI studies investigating the well‐known Stroop paradigm.

Details

show
hide
Language(s): eng - English
 Dates: 2008-02
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1002/hbm.20380
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Human Brain Mapping
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: New York : Wiley-Liss
Pages: - Volume / Issue: 29 (2) Sequence Number: - Start / End Page: 177 - 192 Identifier: ISSN: 1065-9471
CoNE: https://pure.mpg.de/cone/journals/resource/954925601686