Relationship between behavioral maturation measured by the ?Baum? test and EEG frequency. A pilot study on monozygotic and dizygotic twins

Abstract

In a pilot study, the possible influence of the inherited electroencephalogram (EEG) pattern on aspects of psychologic maturation was investigated. The twin sample consisted of 208 pairs, 110 monozygotic (MZ) and 98 dizygotic (DZ), mostly children and adolescents. The study showed a greater similarity between MZ compared with DZ twins in an immaturity score constructed from the Baum test (Koch 1976) and in a teacher's maturity scoring of essays. For both parameters, a correlation between occipital alpha-frequency and the test criterium could be demonstrated. This correlation was in the direction expected, and it was significant statistically. This result suggests an influence of genetically determined variation of brain maturation on interindividual variability of psychologic variation. Due to shortcomings of the methods used in the study, more specific conclusions cannot be drawn; the problem needs further elucidation using modern methods.

On the use of EEG features towards person identification via neural networks

“…It was found that the correlations of mean frequenting among family members were greater than those among non-family members for the alpha rhythm sub-bands. These results were consistent with the ® ndings for the spectral power data but, except for the alpha band, these ® ndings were not as statistically strong as those found for the spectral power measures [18]. Similar results were obtained in the cases of monozygotic twins [3].…”

Person Identification from the EEG using Nonlinear Signal Classification

“…If g denotes time point g = max(p, m, k) + 1, the joint probability density function of the random variables {e g+1 , e g+2 , ... , e N } given by: (7) As the Jacobian of the transformation from {e g+1 , e g+2 , ... , e N } to {x g+1 , x g+2 , ... , x N } is unity, the likelihood function of {x g+1 , x g+2 , ... , x N } is the same as the joint probability density function of {e g+1 , e g+2 , ... , e N }. In light of (7), maximization of the likelihood function is approximately equivalent to minimization of the function Q(⍜) 8) with respect to the parameter vector ⍜. Minimization of Q(⍜) with respect to ⍜ yields the conditional maximum likelihood estimate of ⍜, conditioned on the data {x t }.…”

“…In the first class, the research was carried out among members of the same family [3][4][5]. In the second class, the common characteristics between monozygotic and dizygotic twins [6][7][8][9] were researched while in the third class, different EEGs from the same person were compared, with the objective of extracting the common characteristics among them (personal EEG invariants) [10][11][12][13].…”

Comparative analysis of the computational geometry and neural network classification methods for person identification purposes via the EEG : Part 1

“…These segments were of varying size and were obtained from the monomorphic spectral EEG sub-band, which is known to carry "genetic" information (Ref. 4). More details on this method are presented in Appendix A.…”