Hierarchical topographic factor analysis

Jeremy R. Manning, Rajesh Ranganath, Waitsang Keung, Nicholas B. Turk-Browne, Jonathan D. Cohen, Kenneth A. Norman, David M. Blei

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Recent work has revealed that cognitive processes are often reflected in patterns of functional connectivity throughout the brain (for review see [16]). However, examining functional connectivity patterns using traditional methods carries a substantial computational burden (of computing time and memory). Here we present a technique, termed Hierarchical topographic factor analysis, for efficiently discovering brain networks in large multi-subject neuroimaging datasets.

Original languageEnglish (US)
Title of host publicationProceedings - 2014 International Workshop on Pattern Recognition in Neuroimaging, PRNI 2014
PublisherIEEE Computer Society
ISBN (Print)9781479941506
DOIs
StatePublished - 2014
Event4th International Workshop on Pattern Recognition in Neuroimaging, PRNI 2014 - Tubingen, Germany
Duration: Jun 4 2014Jun 6 2014

Publication series

NameProceedings - 2014 International Workshop on Pattern Recognition in Neuroimaging, PRNI 2014

Other

Other4th International Workshop on Pattern Recognition in Neuroimaging, PRNI 2014
Country/TerritoryGermany
CityTubingen
Period6/4/146/6/14

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Biomedical Engineering

Fingerprint

Dive into the research topics of 'Hierarchical topographic factor analysis'. Together they form a unique fingerprint.

Cite this