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Interval Histogram Analysis of Period of the Electroencephalogram in Relation to Age During Growth and Development in Normal Children
Author(s) -
Surwillo Walter W.
Publication year - 1975
Publication title -
psychophysiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.661
H-Index - 156
eISSN - 1469-8986
pISSN - 0048-5772
DOI - 10.1111/j.1469-8986.1975.tb00036.x
Subject(s) - kurtosis , skewness , statistics , histogram , regression analysis , confidence interval , linear regression , psychology , mathematics , electroencephalography , regression , correlation , normal distribution , audiology , medicine , geometry , artificial intelligence , psychiatry , computer science , image (mathematics)
EEGs were recorded in a group of 41 healthy children aged 5–17 yrs, under conditions where state of the organism was carefully controlled, For each child, durations of a sample of 760 EEG half wavelengths were measured and distributed into an interval histogram. A central‐moments analysis revealed that the first four central moments of the distributions‐which measure the central tendency, dispersion, skewness, and kurtosis of the interval histograms‐were significantly correlated (p<.01) with age of the children. Multiple regression analysis yielded a statistically‐significant multiple correlation coefficient (R) which was equal to 711. Successive recomputations of R using fewer than the four predictor predictor variable yielded an R of .704, when only the measures of dispersion, skewness. and kurtosis were employed. The Predictive value of the multiple regression equation based on the three predictor variables was tested in an independent group of 42 children also aged 5‐17 yrs. EEGs were recorded us in the previous sample, and the second, third, and fourth moments of their distributions of 760 EEG half wavelength were determined. When used in the previously‐derived multiple regression equation, these moments yielded estimated ages which correlated significantly (.47) with the children's actual ages. Since the regression equation could reduce from chance the error of predicting age in the 5–17 yr old range by about 22%, it was concluded that the higher‐order central moments of EEG interval histograms can be of use in charting the course of normal growth and development.