Spatial correlation of the infant and adult electroencephalogram

Clin Neurophysiol. 2003 Sep;114(9):1594-608. doi: 10.1016/s1388-2457(03)00122-6.


Objective: To examine the effects of volume conduction of current on measurements of spatial correlation in the high-density electroencephalogram (EEG) at extremes of human development: infancy and adulthood.

Methods: To calculate theoretical spatial correlation of EEG from volume conduction of uncorrelated cortical sources and compare theory with observations of intra/interhemispheric coherence.

Results: Result verified prediction of reduced spatial correlation in infants due to volume conduction. Theoretical magnitude of spatial correlation from volume conduction demonstrated as lower bound on observed magnitude of coherence (MC). MC of adults is greater than MC of infants. Adult intrahemispheric MC is greater than interhemispheric MC. Scalp muscle electromyogram (EMG) produces artifactually low values of MC.

Conclusions: Volume conduction of current from uncorrelated cortical sources produces an erroneous component of spatial correlation that is smaller in infants than adults. The increased MC in adults is indicative of increased adult neuronal myelination. EMG artifact causes erroneous observations of coherence.

Significance: Measured EEG spatial correlation contains contributions from both neural activity and volume conduction of current. This is an important issue when measurements are used to deduce physiological correlates of neuropsychological phenomena. Measurements of the neural component of spatial correlation are more accurate early in life because of reduced volume conduction.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Age Factors
  • Brain Mapping
  • Electric Conductivity*
  • Electrodes
  • Electroencephalography*
  • Electromyography
  • Evoked Potentials / physiology
  • Functional Laterality
  • Humans
  • Infant
  • Models, Neurological*
  • Scalp / physiology
  • Signal Processing, Computer-Assisted
  • Sleep
  • Statistics as Topic
  • Wakefulness