Influence of age, gender, health status, and depression on quantitative EEG

Neuropsychobiology. 2005;52(2):71-6. doi: 10.1159/000086608. Epub 2005 Jun 29.

Abstract

Quantitative electroencephalography (QEEG) has shown increasing utility in assessing brain function in clinical research studies of depression. QEEG findings may be influenced by a variety of factors other than the presence of depression, including age, gender, depression severity, and physical health status. Many of these factors have not been systematically evaluated. We therefore examined QEEG measures in 104 subjects with depression and normal controls to determine the influence of these factors. We examined QEEG power as well as cordance, a QEEG measure that has a stronger association with cerebral perfusion than conventional QEEG measures. Prefrontal cordance in the theta band has been associated with the pathophysiology of depression and response to treatment. We found that prefrontal cordance and relative power in the theta band were unaffected by age, gender, severity of depression, and health status, while prefrontal absolute power was higher in women than men. All of these measures were different from global measures of absolute and relative power, which were influenced by age, gender, and health status. These findings suggest that prefrontal cordance in depressed patients is not significantly affected by factors of age, gender, severity of depression, or physical illness. Global measures of power, and to a lesser extent prefrontal absolute power, must be interpreted with regard to confounding factors of age, gender, physical illness, and severity of depression.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Aging / physiology*
  • Algorithms
  • Brain Mapping
  • Demography
  • Depression / physiopathology*
  • Electrodes
  • Electroencephalography*
  • Female
  • Health Status Indicators
  • Health Status*
  • Humans
  • Male
  • Middle Aged
  • Psychiatric Status Rating Scales
  • Sex Characteristics*
  • Signal Processing, Computer-Assisted