Robert W. Thatcher

EEG and intelligence: Relations between EEG coherence, EEG phase delay and power

OBJECTIVE There are two inter-related categories of EEG measurement: 1, EEG currents or power and; 2, EEG network properties such as coherence and phase delays. The purpose of this study was to compare the ability of these two different categories of EEG measurement to predict performance on the Weschler Intelligence test (WISC-R). METHODS Resting eyes closed EEG was recorded from 19 scalp locations with a linked ears reference from 442 subjects aged 5-52 years. The Weschler Intelligence test was administered to the same subjects but not while the EEG was recorded. Subjects were divided into high IQ (> or = 120) and low IQ (< or = 90) groups. EEG variables at P<.05 were entered into a factor analysis and then the single highest loading variable on each factor was entered into a discriminant analysis where groups were high IQ vs. low.Q. RESULTS Discriminant analysis of high vs. low IQ was 92.81-97.14% accurate. Discriminant scores of intermediate IQ subjects (i.e. 90 < IQ < 120) were intermediate between the high and low IQ groups. Linear regression predictions of IQ significantly correlated with the discriminant scores (r = 0.818-0.825, P < 10(-6)). The ranking of effect size was EEG phase > EEG coherence > EEG amplitude asymmetry > absolute power > relative power and power ratios. The strongest correlations to IQ were short EEG phase delays in the frontal lobes and long phase delays in the posterior cortical regions, reduced coherence and increased absolute power. CONCLUSIONS The findings are consistent with increased neural efficiency and increased brain complexity as positively related to intelligence, and with frontal lobe synchronization of neural resources as a significant contributing factor to EEG and intelligence correlations. SIGNIFICANCE Quantitative EEG predictions of intelligence provide medium to strong effect size estimates of cognitive functioning while simultaneously revealing a deeper understanding of the neurophysiological substrates of intelligence.

Development of cortical connections as measured by EEG coherence and phase delays.

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 ∼ 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. Hum Brain Mapp, 2008.

Biophysical Linkage between MRI and EEG Amplitude in Closed Head Injury

Nuclear magnetic resonance of brain water proton (1H) T2 relaxation times and measures of absolute amplitude of EEG were obtained from 19 closed head injured patients. The relationship between EEG and T2 relaxation time differed as a function of both EEG frequency and gray matter versus white matter. White matter T2 relaxation time was positively correlated with increased EEG amplitude in the delta frequency band (0.5-3.5 Hz). In contrast, lengthened gray matter T2 relaxation time was inversely correlated with EEG amplitude in the alpha and beta frequency bands (7-22 Hz). These findings are consistent with clinical EEG studies in which white matter lesions are related to increased EEG delta amplitude and gray matter lesions are related to decreased EEG alpha and beta frequency amplitude. Estimates of the severity of injury were obtained by neuropsychological measurements, in which lengthened T2 relaxation times in both the neocortical gray and white matter were correlated with diminished cognitive function. Decreased EEG beta and alpha amplitude and increased EEG delta amplitude were also correlated with diminished cognitive function. The findings imply a biophysical linkage between the state of protein-lipid structures of the brain as measured by the MRI and the scalp-recorded EEG.

Biophysical linkage between MRI and EEG coherence in closed head injury.

Using conventional MRI procedures, nuclear magnetic resonance (NMR) of brain water proton (1H) T2 relaxation times and EEG coherence were obtained from two independent groups of closed head injured (CHI) patients and a group of normal control subjects. Statistically significant intercorrelations were observed between 1H T2 relaxation times of the cortical gray and white matter and EEG coherence. The analyses showed that lengthened 1H T2 relaxation times of the cortical gray and white matter were related to: (1) decreased EEG coherence between short interelectrode distances (e.g., 7 cm) and increased EEG coherence between long interelectrode distances (e.g., 28 cm), (2) differences in EEG frequency in which T2 relaxation time was most strongly related to the gray matter in the delta and theta frequencies in CHI patients, and (3) increased T2 relaxation time and decreased short-distance EEG coherence were related to reduced cognitive function. The results were interpreted in terms of reduced integrity of protein/lipid neural membranes and the efficiency and effectiveness of short- and long-distance neural synchronization following traumatic brain injury.

Intelligence and EEG phase reset: a two compartmental model of phase shift and lock.

OBJECTIVES The purpose of this study was to explore the relationship between EEG phase reset and performance on the Wechsler Intelligence test. METHODS The electroencephalogram (EEG) was recorded from 19 scalp locations from 378 subjects ranging in age from 5 years to 17.6 years. The Wechsler Intelligence test (WISC-R) was administered to the same subjects on the same day but not while the EEG was recorded. Complex demodulation was used to compute instantaneous EEG phase differences between pairs of electrodes and the 1st and 2nd derivatives were used to measure phase reset by phase shift duration and phase lock duration. The dependent variable was full scale I.Q. and the independent variables were phase shift duration (SD) and phase lock duration (LD) with age as a covariate. RESULTS Phase shift duration (40-90 ms) was positively related to intelligence (P<.00001) and the phase lock duration (100-800 ms) was negatively related to intelligence (P<.00001). Phase reset in short interelectrode distances (6 cm) was more highly correlated to I.Q. (P<.0001) than in long distances (>12 cm). CONCLUSIONS The duration of unstable phase dynamics and phase locking represent a bounded optimization process, for example, too long a duration of phase locking then less flexibility and too short of a phase shift then reduced neural resources. A two compartmental model of local field coupling and neuron synchrony to a preferred phase was developed to explain the findings.

Evaluation and validity of a LORETA normative EEG database.

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 Institutes 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 2,394 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.

Self‐organized criticality and the development of EEG phase reset

Objectives: The purpose of this study was to explore human development of self‐organized criticality as measured by EEG phase reset from infancy to 16 years of age. Methods: The electroencephalogram (EEG) was recorded from 19 scalp locations from 458 subjects ranging in age from 2 months to 16.67 years. Complex demodulation was used to compute instantaneous phase differences between pairs of electrodes and the 1st and 2nd derivatives were used to detect the sudden onset and offset times of a phase shift followed by an extended period of phase locking. Mean phase shift duration and phase locking intervals were computed for two symmetrical electrode arrays in the posterior‐to‐anterior locations and the anterior‐to‐posterior directions in the α frequency band (8–13 Hz). Results: Log–log spectral plots demonstrated 1/f α distributions (α ≈ 1) with longer slopes during periods of phase shifting than during periods of phase locking. The mean duration of phase locking (150–450 msec) and phase shift (45–67 msec) generally increased as a function of age. The mean duration of phase shift declined over age in the local frontal regions but increased in distant electrode pairs. Oscillations and growth spurts from mean age 0.4–16 years were consistently present. Conclusions: The development of increased phase stability in local systems is paralleled by lengthened periods of unstable phase in distant connections. Development of the number and/or density of synaptic connections is a likely order parameter to explain oscillations and growth spurts in self‐organized criticality during human brain maturation. Hum Brain Mapp, 2009.

Tomographic Electroencephalography/Magnetoencephalography: Dynamics of Human Neural Network Switching

New developments in multimodal registration of electroencephalography (EEG), magnetic resonance imaging (MRI), and pOSitron emission tomography (PET) are presented as a method to create a tomographic EEG. Three‐dimensional information about the x,y,z location of the sources of event‐related potentials is corroborated through the use of experimental design and coregistration with MRI and PET. Once the three‐dimension allocation of event‐related potential dipole sources IS identified and corroborated, pseudoinverse procedures are used to derive a new EEG voltage sequence from each of the dipoles Each denved EEG dipole time series is analogous to recording EEG from a deeply implanted electrode and constitutes a four‐dimensional tomographic EEG (ie, three‐dimensional space plus time) EEG coherence and phase analyses are then performed on the dipole‐derived time series to study the temporal and spatial dynamics of neural network switching during voluntary finger movements. The purpose of this article is to demonstrate a new method to exploit the time domain dynamics of neural network switching in behaving human subjects.

EEG Database-Guided Neurotherapy

Publisher Summary The chapter presents a brief integration of biofeedback of the electroencephalogram (EEG) with the field of neuroimaging as well as introduction of non-Gaussian distributed statistics in the form of modern nonparametric statistics. There has been a veritable explosion in new discoveries in the field of neuroscience during the last 10 years. It has resulted in the rapid growth of a new discipline called functional neuroimaging , which embodies the ability to measure four dimensional biophysical brain processes related to many aspects of normal and pathological brain function, including perception and cognition. The evidence of the growth is the commonly reported high spatial and temporal resolution of EEG that yields 3-D current sources capable of being coregistered with PET using spherical and/or realistic head models as determined by conventional Magnetic Resonance Imaging (MRI). The MRI-based spectroscopic methods measure biophysical processes related to the concentrations of organic and nonorganic compounds found in the bioenergetics of cells and the membrane contents of cells. A biophysically based MRI integration to EEG is a welcome arrival because it harkens a measurable linkage between membrane and molecular biology and the electrogenesis of the EEG.

Psychopathology of early frontal lobe damage: Dependence on cycles of development

A new theory of frontal lobe development is presented in which the role of the human frontal lobes during normal development and the psychopathological consequences of early frontal lobe injury are explored. Analyses of the development of human electroencephalograph (EEG) coherence indicate that there are oscillations and cyclic growth processes along the mediolateral and anterior-posterior planes of the brain. The cycles of EEG coherence are interpreted as repetitive sequences of increasing and decreasing synaptic effectiveness that reflects a convergence process that narrows the disparity between structure and function by slowly sculpting and reshaping the brains microanatomy. This process is modeled as a developmental spiral staircase in which brain structures are periodically revisited resulting in stepwise increases in differentiation and integration. The frontal lobes play a crucial role because they are largely responsible for the selection and pruning of synaptic contacts throughout the postnatal period. A mathematical model of cycles of synaptic effectiveness is presented in which the frontal lobes behave as gentle synaptic “predators” whereas posterior cortical regions behave as synaptic “prey” in a periodic reorganization process. The psychopathological consequences of early frontal lobe damage are discussed in the context of this model.