Complementary methods for interpreting brain signals: linear versus nonlinear techniques

Annu Int Conf IEEE Eng Med Biol Soc. 2007:2007:1969-72. doi: 10.1109/IEMBS.2007.4352704.

Abstract

Magnetoencephalography (MEG) brain signals are characterized using both linear and nonlinear dynamical methods. The linear approach employs the power analysis in a spatial visualization. The nonlinear approach estimates the value of d(infinity) to characterize the system's asymptotic chaotic behavior using a computationally less onerous method than the conventional one for d(infinity). Both methods are applied here to study a female patient with obsessive compulsive disorder and an age-sex matched normal subject. MEG time series were obtained using dual 37-channel bio-magnetometers (4-D Neuroimaging, San Diego, CA).

MeSH terms

  • Brain / pathology*
  • Brain Mapping
  • Case-Control Studies
  • Data Interpretation, Statistical*
  • Electroencephalography / instrumentation
  • Equipment Design
  • Female
  • Humans
  • Linear Models
  • Magnetoencephalography / instrumentation*
  • Magnetoencephalography / methods
  • Models, Statistical
  • Nonlinear Dynamics
  • Obsessive-Compulsive Disorder / diagnosis*
  • Obsessive-Compulsive Disorder / pathology
  • Signal Processing, Computer-Assisted*