Correlation between spectral EEG parameters and intelligence test variables in school-age children.

Objectives: The objective of the study was to investigate the relationship between the degree of intelligence and spectral electroencephalographic (EEG) parameters and to find out which EEG variables are relevant for this correlation.Methods: Bipolar 1 min EEG recordings were derived for the fronto-central and parieto-occipital leads from 155 clinically healthy 10-year-old children in vigilance state awake with eyes closed. Relative spectral power parameters were calculated by Fast Fourier Transform. Two-group t tests according to the score values of the 'WISC-R' intelligence test as well as univariate and multiple correlation analyses between spectral and intelligence test variables were carried out.Results: A statistically significant positive correlation of the intelligence test variables with the spectral alpha power and a significant negative correlation with the spectral power of lower frequency bands was observed. Predicting the spectral parameters by means of intelligence test variables, significant multiple correlation coefficients were revealed in the frequency ranges: 0.5-1.5, 3.0-5.0 and 9.0-10.5 Hz. The highest significance (P<0.0001) was found for the spectral value at 9.0 Hz.Conclusions: The results of t tests and correlation analyses confirm the strong relationship between spectral EEG parameters and the degree of intelligence indicating that the 'EEG recordings do reflect intellectual abilities'. It may be supposed that the amount of the intelligence quotient is correlated with the degree of EEG maturation and thus reflects the active number of synapses and the degree of differentiation of the neuronal controlling system

Correlation of developmental neurological findings with spectral analytical EEG evaluations in pre-school age children.

For the differentiation of developmental neurological disorders in pre-school age children, the relationship between automatically derived EEG parameters and developmental neurological findings was investigated. Within the scope of the Munich Pediatric Longitudinal Study, the sample sets of 4- and 5-year-old children (according to the frontal and parieto-occipital EEG derivations) with selected abnormal findings categorized by special items were compared with the corresponding control groups. This was carried out by means of one-sided t tests and relative frequency band-related as well as single-step spectral power parameters in the alpha range of the EEG. Automatic analysis using single-step power values was superior to that using band-related parameters. This led to the conclusion that use of age-specific single-step parameters for a quantitative EEG analysis and ignoring the classical frequency bands will yield statistically greatly improved results. For 4- and 5-year-old children, the best separation of the neurologically abnormal groups from the normal control groups was obtained using relative spectral values in the frequency range of 9.0-9.8 Hz with a maximum at 9.4 Hz. At the same time, the topographical conditions of brain immaturation should be taken into account. The results for the children examined in this study differ in a stronger distinction over the frontocentral brain region of 4- and 5-year-olds (P < 0.01) and through an additional distinction over the parietooccipital region of the 5-year-olds (P < 0.001). It still must be tested whether the spectral parameter at 9.4 Hz is age-specific for 4- and 5-year-old children or whether in other age groups different spectral parameters are of use. As an examiner-independent method, the automatic EEG analysis should become an integral component of developmental neurological diagnostics