Independent Component Analysis of Magnetoencephalography Data

Abstract

Independent Component Analysis (ICA) is applied to the Magnetoencephalography (MEC) data of a subject performing a yoga breathing exercise specific for the treatment of obsessive compulsive disorder, The spatio-temporal dynamics observed using a whole-head 148-channel MEC instrument are split into the fundamental modes, thus isolating separate brain activity signals, Experiments were performed on data from different brain regions, Spectral analysis of the more significant signals are presented. Moreover a new tool is developed as a Matlab toolbox to support the scientist both in the visualization and computation phases.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA409677

Entities

People

  • D.s. Shannahoff-khalsa
  • L. Fortuna
  • M. Bucolo
  • M. Frasca
  • M. Larosa

Organizations

  • University of Catania

Tags

Communities of Interest

  • Advanced Electronics
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Data Analysis
  • Data Visualization
  • Detection
  • Electrical Equipment
  • Electrodes
  • Fourier Analysis
  • Frequency
  • Head (Anatomy)
  • Magnetic Fields
  • Magnetoencephalography
  • Magnetometers
  • Measurement
  • Power Distribution
  • Power Spectra
  • Respiration
  • Spatial Distribution

Readers

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