Literature DB >> 20408233

Functional volumes modeling: theory and preliminary assessment.

P T Fox1, J L Lancaster, L M Parsons, J H Xiong, F Zamarripa.   

Abstract

A construct for metanalytic modeling of the functional organization of the human brain, termed functional volumes modeling (FVM), is presented and preliminarily tested. FVM uses the published literature to model brain functional areas as spatial probability distributions. The FVM statistical model estimates population variance (i.e., among individuals) from the variance observed among group-mean studies, these being the most prevalent type of study in the functional imaging literature. The FVM modeling strategy is tested by: (1) constructing an FVM of the mouth region of primary motor cortex using published, group-mean, functional imaging reports as input, and (2) comparing the confidence bounds predicted by that FVM with those observed in 10 normal subjects performing overt-speech tasks. The FVM model correctly predicted the mean location and spatial distribution of per-subject functional responses. FVM has a wide range of applications, including hypothesis testing for statistical parametric images. Copyright (c) 1997 Wiley-Liss, Inc.

Entities:  

Year:  1997        PMID: 20408233     DOI: 10.1002/(SICI)1097-0193(1997)5:4<306::AID-HBM17>3.0.CO;2-B

Source DB:  PubMed          Journal:  Hum Brain Mapp        ISSN: 1065-9471            Impact factor:   5.038


  17 in total

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

Authors:  P T Fox; A Y Huang; L M Parsons; J H Xiong; L Rainey; J L Lancaster
Journal:  Hum Brain Mapp       Date:  1999       Impact factor: 5.038

2.  Evaluation of octree regional spatial normalization method for regional anatomical matching.

Authors:  P Kochunov; J Lancaster; P Thompson; A Boyer; J Hardies; P Fox
Journal:  Hum Brain Mapp       Date:  2000-11       Impact factor: 5.038

3.  Automated Talairach atlas labels for functional brain mapping.

Authors:  J L Lancaster; M G Woldorff; L M Parsons; M Liotti; C S Freitas; L Rainey; P V Kochunov; D Nickerson; S A Mikiten; P T Fox
Journal:  Hum Brain Mapp       Date:  2000-07       Impact factor: 5.038

4.  Modeling of activation data in the BrainMap database: detection of outliers.

Authors:  Finn Arup Nielsen; Lars Kai Hansen
Journal:  Hum Brain Mapp       Date:  2002-03       Impact factor: 5.038

Review 5.  Coordinate-based voxel-wise meta-analysis: dividends of spatial normalization. Report of a virtual workshop.

Authors:  Peter T Fox; Angela R Laird; Jack L Lancaster
Journal:  Hum Brain Mapp       Date:  2005-05       Impact factor: 5.038

6.  Meta-analysis of functional imaging data using replicator dynamics.

Authors:  Jane Neumann; Gabriele Lohmann; Jan Derrfuss; D Yves von Cramon
Journal:  Hum Brain Mapp       Date:  2005-05       Impact factor: 5.038

7.  Meta-analytic connectivity and behavioral parcellation of the human cerebellum.

Authors:  Michael C Riedel; Kimberly L Ray; Anthony S Dick; Matthew T Sutherland; Zachary Hernandez; P Mickle Fox; Simon B Eickhoff; Peter T Fox; Angela R Laird
Journal:  Neuroimage       Date:  2015-05-19       Impact factor: 6.556

8.  Meta Analysis of Functional Neuroimaging Data via Bayesian Spatial Point Processes.

Authors:  Jian Kang; Timothy D Johnson; Thomas E Nichols; Tor D Wager
Journal:  J Am Stat Assoc       Date:  2011-03-01       Impact factor: 5.033

9.  The coordinate-based meta-analysis of neuroimaging data.

Authors:  Pantelis Samartsidis; Silvia Montagna; Thomas E Nichols; Timothy D Johnson
Journal:  Stat Sci       Date:  2017-11-28       Impact factor: 2.901

10.  Visualizing data mining results with the brede tools.

Authors:  Finn Arup Nielsen
Journal:  Front Neuroinform       Date:  2009-07-28       Impact factor: 4.081

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