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The purpose of this study was to explore human development of EEG coherence and phase differences over the period from infancy to 16 years of age. The electroencephalogram (EEG) was recorded from 19 scalp locations from 458 subjects ranging in age from 2 months to 16.67 years. EEG coherence and EEG phase differences were computed for the left and right hemispheres in the posterior-to-anterior direction (O1/2-P3/4, O1/2-C3/4, O1/2-F3/4, and O1/2-Fp1/2) and the anterior-to- posterior direction (Fp1/2-F3/4, Fp1/2-C3/4, Fp1/2-P3/4, and Fp1/2-O1/2) in the beta frequency band (13-25 Hz). Sliding averages of EEG coherence and phase were computed using 1 year averages and 9 month overlapping that produced 64 means from 0.44 years of age to 16.22 years of age. Rhythmic oscillations in coherence and phase were noted in all electrode combinations. Different developmental trajectories were present for coherence and phase differences and for anterior-to-posterior and posterior-to-anterior directions and inter-electrode distance. Large changes in EEG coherence and phase were present from approximately 6 months to 4 years of age followed by a significant linear trend to higher coherence in short distance inter-electrode distances and longer phase delays in long inter-electrode distances. The results are consistent with a genetic model of rhythmic long term connection formation that occurs in cycles along a curvilinear trajectory toward adulthood. Competition for dendritic space, development of complexity, and nonlinear dynamic oscillations are discussed.

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To evaluate the reliability and validity of a Z-score normative EEG database for Low Resolution Electromagnetic Tomography (LORETA), EEG digital samples (2 second intervals sampled 128 Hz, 1 to 2 minutes eyes closed) were acquired from 106 normal subjects, and the cross-spectrum was computed and multiplied by the Key Institute's LORETA 2,394 gray matter pixel T Matrix. After a log10 transform or a Box-Cox transform the mean and standard deviation of the *.lor files were computed for each of the 2394 gray matter pixels, from 1 to 30 Hz, for each of the subjects. Tests of Gaussianity were computed in order to best approximate a normal distribution for each frequency and gray matter pixel. The relative sensitivity of a Z-score database was computed by measuring the approximation to a Gaussian distribution. The validity of the LORETA normative database was evaluated by the degree to which confirmed brain pathologies were localized using the LORETA normative database. Log10 and Box-Cox transforms approximated Gaussian distribution in the range of 95.64% to 99.75% accuracy. The percentage of normative Z-score values at 2 standard deviations ranged from 1.21% to 3.54%, and the percentage of Z-scores at 3 standard deviations ranged from 0% to 0.83%. Left temporal lobe epilepsy, right sensory motor hematoma and a right hemisphere stroke exhibited maximum Z-score deviations in the same locations as the pathologies. We conclude: (1) Adequate approximation to a Gaussian distribution can be achieved using LORETA by using a log10 transform or a Box-Cox transform and parametric statistics, (2) a Z-Score normative database is valid with adequate sensitivity when using LORETA, and (3) the Z-score LORETA normative database also consistently localized known pathologies to the expected Brodmann areas as an hypothesis test based on the surface EEG before computing LORETA.

Objectives: The purpose of this study was to explore phase reset of 3-dimensional current sources in Brodmann areas located in the human default mode network (DMN) using Low Resolution Electromagnetic Tomography (LORETA) of the human electroencephalogram (EEG).Methods: The EEG was recorded from 19 scalp locations from 70 healthy normal subjects ranging in age from 13 to 20 years. A time point by time point computation of LORETA current sources were computed for 14 Brodmann areas comprising the DMN in the delta frequency band. The Hilbert transform of the LORETA time series was used to compute the instantaneous phase differences between all pairs of Brodmann areas. Phase shift and lock durations were calculated based on the 1st and 2nd derivatives of the time series of phase differences.Results: Phase shift duration exhibited three discrete modes at approximately: (1) 25 ms, (2) 50 ms, and (3) 65 ms. Phase lock duration present primarily at: (1) 300–350 ms and (2) 350–450 ms. Phase shift and lock durations were inversely related and exhibited an exponential change with distance between Brodmann areas.Conclusions: The results are explained by local neural packing density of network hubs and an exponential decrease in connections with distance from a hub. The results are consistent with a discrete temporal model of brain function where anatomical hubs behave like a “shutter” that opens and closes at specific durations as nodes of a network giving rise to temporarily phase locked clusters of neurons for specific durations.