Analysis of cortical connectivity using Hopfield neural network

S. Dixit, Kristine Mosier

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Functional magnetic resonance imaging (fMRI) is increasingly recognized as a standard technique for brain mapping and determining the connectivity between cortical regions. Statistical approaches to determining cortical connectivity, e.g. structural equation modeling between various regions of interest in the active brain can be computationally inefficient. This study explores the utility of a Hopfield neural network to determine cortical connectivity in an fMRI data set.

Original languageEnglish (US)
Pages (from-to)1163-1170
Number of pages8
JournalNeurocomputing
Volume58-60
DOIs
StatePublished - Jun 2004
Externally publishedYes

Fingerprint

Hopfield neural networks
Brain mapping
Magnetic Resonance Imaging
Brain Mapping
Brain
Datasets

Keywords

  • Artificial neural networks
  • Functional magnetic resonance imaging
  • Neural network
  • Neurocomputing
  • Neuroinformatics

ASJC Scopus subject areas

  • Artificial Intelligence
  • Cellular and Molecular Neuroscience

Cite this

Analysis of cortical connectivity using Hopfield neural network. / Dixit, S.; Mosier, Kristine.

In: Neurocomputing, Vol. 58-60, 06.2004, p. 1163-1170.

Research output: Contribution to journalArticle

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