Spatiotemporal organization of brain dynamics and intelligence: an EEG study in adolescents

Assessment of linear and nonlinear synchronization measures for analyzing EEG in a mild epileptic paradigm

Epilepsy is one of the most common brain disorders and may result in brain dysfunction and cognitive disturbances. Epileptic seizures usually begin in childhood without being accommodated by brain damage and are tolerated by drugs that produce no brain dysfunction. In this study, cognitive function is evaluated in children with mild epileptic seizures controlled with common antiepileptic drugs. Under this prism, we propose a concise technical framework of combining and validating both linear and nonlinear methods to efficiently evaluate (in terms of synchronization) neurophysiological activity during a visual cognitive task consisting of fractal pattern observation. We investigate six measures of quantifying synchronous oscillatory activity based on different underlying assumptions. These measures include the coherence computed with the traditional formula and an alternative evaluation of it that relies on autoregressive models, an information theoretic measure known as minimum description length, a robust phase coupling measure known as phase-locking value, a reliable way of assessing generalized synchronization in state-space and an unbiased alternative called synchronization likelihood. Assessment is performed in three stages; initially, the nonlinear methods are validated on coupled nonlinear oscillators under increasing noise interference; second, surrogate data testing is performed to assess the possible nonlinear channel interdependencies of the acquired EEGs by comparing the synchronization indexes under the null hypothesis of stationary, linear dynamics; and finally, synchronization on the actual data is measured. The results on the actual data suggest that there is a significant difference between normal controls and epileptics, mostly apparent in occipital-parietal lobes during fractal observation tests.

Differential topographic pattern of EEG coherence between simultaneous and successive coding tasks

The concept of two types of information coding, simultaneous and successive processing, is now well supported by extensive studies with factor analysis. However, few EEG evidence on processing types have been reported. In the present study we investigated whether varying demands on simultaneous or successive processing are reflected by different pattern of EEG coherence change from the passive condition to the active condition. We computed EEG coherence during simultaneous and successive processing tasks in both passive and active conditions. Under the passive condition, participants were just to perceive the presented stimuli. In the active condition, participants were required to remember the presented stimuli and then reproduce or recognize the remembered stimuli. Our result revealed the different topographic patterns of coherence change from the passive to the active condition between the simultaneous and the successive task. In the successive processing task, bilateral frontal-left temporal coherence in beta showed a significant decrease during the active condition, supporting Luria's model of the two information coding types. The condition effect of coherence in the simultaneous processing task was rather unclear. Our data also indicated that more task related cognitive processes, rather than the task-independent processes such as attentional demand, were reflected in EEG coherence of higher frequency bands. The different EEG coherence patterns seen in the simultaneous and successive tasks suggested the first step evidence that EEG coherence pattern may differentiate two distinctive types of information coding.

Brain wave synchronization and entrainment to periodic acoustic stimuli

As known, different brainwave frequencies show synchronies related to different perceptual, motor or cognitive states. Brainwaves have also been shown to synchronize with external stimuli with repetition rates of ca. 10-40 Hz. However, not much is known about responses to periodic auditory stimuli with periodicities found in human rhythmic behavior (i.e. 0.5-5 Hz). In an EEG study we compared responses to periodic stimulations (drum sounds and clicks with repetition rates of 1-8 Hz), silence, and random noise. Here we report inter-trial coherence measures taken at the Cz-electrode that show a significant increase in brainwave synchronization following periodic stimulation. Specifically, we found (1) a tonic synchronization response in the delta range with a maximum response at 2 Hz, (2) a phasic response covering the theta range, and (3) an augmented phase synchronization throughout the beta/gamma range (13-44 Hz) produced through increased activity in the lower gamma range and modulated by the stimulus periodicity. Periodic auditory stimulation produces a mixture of evoked and induced, rate-specific and rate-independent increases in stimulus related brainwave synchronization that are likely to affect various cognitive functions. The synchronization responses in the delta range may form part of the neurophysiological processes underlying time coupling between rhythmic sensory input and motor output; the tonic 2 Hz maximum corresponds to the optimal tempo identified in listening, tapping synchronization, and event-interval discrimination experiments. In addition, synchronization effects in the beta and gamma range may contribute to the reported influences of rhythmic entrainment on cognitive functions involved in learning and memory tasks.

Intelligence and cognitive flexibility: fluid intelligence correlates with feature "unbinding" across perception and action

People integrate the features of perceived events and of action plans, as well as of episodic stimulus-response relations, into event files. We investigated whether the management of event files, and particularly the speed of updating the binding between the task-relevant stimulus feature and the response, correlates with fluid intelligence. Indeed, the performance of participants scoring high on Raven's Standard Progressive Matrices test was less impaired by a mismatch between the stimulus-response relation in the current and the previous trial. This result suggests that high intelligence is accompanied by a higher degree of flexibility in handling event files--that is, by higher efficiency in updating episodic representations.

Intelligence and EEG current density using low-resolution electromagnetic tomography (LORETA)

The purpose of this study was to compare EEG current source densities in high IQ subjects vs. low IQ subjects. Resting eyes closed EEG was recorded from 19 scalp locations with a linked ears reference from 442 subjects ages 5 to 52 years. The Wechsler Intelligence Test was administered and subjects were divided into low IQ (< or =90), middle IQ (>90 to <120) and high IQ (> or =120) groups. Low-resolution electromagnetic tomographic current densities (LORETA) from 2,394 cortical gray matter voxels were computed from 1-30 Hz based on each subject's EEG. Differences in current densities using t tests, multivariate analyses of covariance, and regression analyses were used to evaluate the relationships between IQ and current density in Brodmann area groupings of cortical gray matter voxels. Frontal, temporal, parietal, and occipital regions of interest (ROIs) consistently exhibited a direct relationship between LORETA current density and IQ. Maximal t test differences were present at 4 Hz, 9 Hz, 13 Hz, 18 Hz, and 30 Hz with different anatomical regions showing different maxima. Linear regression fits from low to high IQ groups were statistically significant (P < 0.0001). Intelligence is directly related to a general level of arousal and to the synchrony of neural populations driven by thalamo-cortical resonances. A traveling frame model of sequential microstates is hypothesized to explain the results.

Increased information transmission during scientific hypothesis generation: Mutual information analysis of multichannel EEG

Hypothesis generation has been regarded as one of the core reasoning processes in creative thinking and scientific discovery. To investigate changes in the amount of information transmission during scientific hypothesis generation, the averaged cross-mutual-information (A-CMI) of EEGs was estimated. Twenty-five 5th grade students were sampled in this study. EEG signals from 16 electrodes on each subject's scalp were recorded using a 32-channel EEG system. In order to generate hypotheses, the students were asked to observe 20 quail eggs that gave rise to questions such as: Why do different sizes and shapes of patterns appear on the surface of the eggs? After the observation, they were asked to generate a scientific hypothesis-a tentative causal explanation for the evoked question. The results of experimentation indicated several distinct brain activities during hypothesis generation interacting between different local brain regions. In addition, it was observed that the amount of information transmission during hypothesis generation increased in a large part of the brain region encompassing the temporal, parietal, and occipital cortexes, which implies the use of declarative and procedural memory systems. Furthermore, this study suggested the possibility that neuropsychological approaches may be potential tools to investigate the neuronal activity of EEGs during hypothesis generation.

Nonlinear analysis of discharge patterns in monkey basal ganglia

Spontaneous discharge of basal ganglia neurons is often analyzed with time- or frequency-domain methods. However, it has been shown that sequences of inter-spike interval series are not fully described by such linear procedures. We therefore carried out a characterization of the nonlinear features of spontaneous discharge of neurons in the primate basal ganglia. We studied the spontaneous activity of neurons in the subthalamic nucleus (22 cells), as well as neurons in the external and internal pallidal segments (53 and 39 cells, respectively), recorded with standard extracellular recording methods in two awake Rhesus monkeys. As a measure of the statistical irregularity of neuronal discharge, we compared the approximate entropy of inter-spike interval sequences with that of shuffled representations of the same data. In all three basal ganglia structures, approximately 95% of the original data showed lower approximate entropy values than the shuffled data, suggesting a temporal organization in the original sequence. Fano factor analysis confirmed the presence of a temporal organization of inter-spike interval sequences, and indicated the presence of self-similarity in the great majority of them. In addition, Hurst exponent analysis showed that the inter-spike interval series are persistent. Hurst exponents often differ between short and long scaling ranges. Subsequent principal component analyses allowed us to identify three distinct patterns of the temporal evolution of inter-spike interval sequences in the phase space. These types were found in varying distributions in all three nuclei. Our analyses demonstrate that the discharge of most neurons in the basal ganglia of awake monkeys has nonlinear features that may be important for information coding in the basal ganglia.

Sleep spindle-related activity in the human EEG and its relation to general cognitive and learning abilities

Stage 2 sleep spindles have been previously viewed as useful markers for the development and integrity of the CNS and were more currently linked to 'offline re-processing' of implicit as well as explicit memory traces. Additionally, it had been discussed if spindles might be related to a more general learning or cognitive ability. In the present multicentre study we examined the relationship of automatically detected slow (< 13 Hz) and fast (> 13 Hz) stage 2 sleep spindles with: (i) the Raven's Advanced Progressive Matrices (testing 'general cognitive ability'); as well as (ii) the Wechsler Memory scale-revised (evaluating memory in various subdomains). Forty-eight healthy subjects slept three times (separated by 1 week) for a whole night in a sleep laboratory with complete polysomnographic montage. Whereas the first night only served adaptation and screening purposes, the two remaining nights were preceded either by an implicit mirror-tracing or an explicit word-pair association learning or (corresponding) control task. Robust relationships of slow and fast sleep spindles with both cognitive as well as memory abilities were found irrespectively of whether learning occurred before sleep. Based on the present findings we suggest that besides being involved in shaping neuronal networks after learning, sleep spindles do reflect important aspects of efficient cortical-subcortical connectivity, and are thereby linked to cognitive- and memory-related abilities alike.

Genetic influences on dynamic complexity of brain oscillations

Human electroencephalogram (EEG) consists of complex aperiodic oscillations that are assumed to indicate underlying neural dynamics such as the number and degree of independence of oscillating neuronal networks. EEG complexity can be estimated using measures derived from nonlinear dynamic systems theory. Variations in such measures have been shown to be associated with normal individual differences in cognition and some neuropsychiatric disorders. Despite the increasing use of EEG complexity measures for the study of normal and abnormal brain functioning, little is known about genetic and environmental influences on these measures. Using the pointwise dimension (PD2) algorithm, this study assessed heritability of EEG complexity at rest in a sample of 214 young female twins consisting of 51 monozygotic (MZ) and 56 dizygotic (DZ) pairs. In MZ twins, intrapair correlations were high and statistically significant; in DZ twins, correlations were substantially smaller. Genetic analyses using linear structural equation modeling revealed high and significant heritability of EEG complexity: 62-68% in the eyes-closed condition, and 46-60% in the eyes-open condition. Results suggest that individual differences in the complexity of resting electrocortical dynamics are largely determined by genetic factors. Neurophysiological mechanisms mediating genetic variation in EEG complexity may include the degree of structural connectivity and functional differentiation among cortical neuronal assemblies.

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.

Nonlinear dynamical analysis of EEG and MEG: review of an emerging field

Many complex and interesting phenomena in nature are due to nonlinear phenomena. The theory of nonlinear dynamical systems, also called 'chaos theory', has now progressed to a stage, where it becomes possible to study self-organization and pattern formation in the complex neuronal networks of the brain. One approach to nonlinear time series analysis consists of reconstructing, from time series of EEG or MEG, an attractor of the underlying dynamical system, and characterizing it in terms of its dimension (an estimate of the degrees of freedom of the system), or its Lyapunov exponents and entropy (reflecting unpredictability of the dynamics due to the sensitive dependence on initial conditions). More recently developed nonlinear measures characterize other features of local brain dynamics (forecasting, time asymmetry, determinism) or the nonlinear synchronization between recordings from different brain regions. Nonlinear time series has been applied to EEG and MEG of healthy subjects during no-task resting states, perceptual processing, performance of cognitive tasks and different sleep stages. Many pathologic states have been examined as well, ranging from toxic states, seizures, and psychiatric disorders to Alzheimer's, Parkinson's and Cre1utzfeldt-Jakob's disease. Interpretation of these results in terms of 'functional sources' and 'functional networks' allows the identification of three basic patterns of brain dynamics: (i) normal, ongoing dynamics during a no-task, resting state in healthy subjects; this state is characterized by a high dimensional complexity and a relatively low and fluctuating level of synchronization of the neuronal networks; (ii) hypersynchronous, highly nonlinear dynamics of epileptic seizures; (iii) dynamics of degenerative encephalopathies with an abnormally low level of between area synchronization. Only intermediate levels of rapidly fluctuating synchronization, possibly due to critical dynamics near a phase transition, are associated with normal information processing, whereas both hyper-as well as hyposynchronous states result in impaired information processing and disturbed consciousness.

Attention modulates hemispheric differences in functional connectivity: evidence from MEG recordings

The present study examined intrahemispheric functional connectivity during rest and dichotic listening in 8 male and 9 female healthy young adults measured with magnetoencephalography (MEG). Generalized synchronization within the separate hemispheres was estimated by means of the synchronization likelihood that is sensitive to linear as well as non-linear coupling of MEG signals. We found higher functional intrahemispheric connectivity of frontal and temporal areas within the right as compared to the left hemisphere in the lower and higher theta band during rest and in the lower theta band during dichotic listening. In addition, higher synchronization in the lower theta band correlated with better task performance. In the upper alpha band, hemispheric differences in intrahemispheric connectivity of the frontal regions were found to be modulated by focused attention instructions. That is, attention to the right ear exaggerates the pattern of higher synchronization likelihood for the right frontal region, while attention to the left ear has an opposite effect. We found higher intrahemispheric connectivity in males compared to females as shown by higher synchronization in the lower alpha band. Taken together, our results reflect a physiological basis for functional hemispheric laterality and support the general assumption of sex differences in brain organization. Furthermore, in addition to studies that show that controlled attention processes modulate activation of the frontal areas, our study indicates that attention modulates ipsilateral functional connectivity in the frontal areas. This supports the idea of a supervisory role for the frontal cortex in attention processes.

Sex differences in brain activity related to general and emotional intelligence

The study investigated gender differences in resting EEG (in three individually determined narrow alpha frequency bands) related to the level of general and emotional intelligence. Brain activity of males decreased with the level of general intelligence, whereas an opposite pattern of brain activity was observed in females. This difference was most pronounced in the upper-alpha band which is related to semantic memory processes. It was further found that highly intelligent males displayed greater decoupling of frontal brain areas, whereas highly intelligent females showed more coupling between frontal and parietal/occipital brain areas. Similar, but less significant differences were observed for the two area scores of strategic and experiential emotional intelligence. It appears that males and females have different resting EEG correlates of IQ.

Assessment of EEG synchronization based on state-space analysis

Cortical computation involves the formation of cooperative neuronal assemblies characterized by synchronous oscillatory activity. A traditional method for the identification of synchronous neuronal assemblies has been the coherence analysis of EEG signals. Here, we suggest a new method called S estimator, whereby cortical synchrony is defined from the embedding dimension in a state-space. We first validated the method on clusters of chaotic coupled oscillators and compared its performance to that of other methods for assessing synchronization. Then nine adult subjects were studied with high-density EEG recordings, while they viewed in the two hemifields (hence with separate hemispheres) identical sinusoidal gratings either arranged collinearly and moving together, or orthogonally oriented and moving at 90 degrees . The estimated synchronization increased with the collinear gratings over a cluster of occipital electrodes spanning both hemispheres, whereas over temporo-parietal regions of both hemispheres, it decreased with the same stimulus and it increased with the orthogonal gratings. Separate calculations for different EEG frequencies showed that the occipital clusters involved synchronization in the beta band and the temporal clusters in the alpha band. The gamma band appeared to be insensitive to stimulus diversity. Different stimulus configurations, therefore, appear to cause a complex rearrangement of synchronous neuronal assemblies distributed over the cortex, in particular over the visual cortex.

Adults with dyslexia: theta power changes during performance of a sequential motor task

Performance deficits during cerebellar intensive motor tasks maybe reflected by discrepant theta activity in the cerebral cortex. The present experiment examined the relationship between performance on a novel motor task and theta activity in adults with developmental dyslexia (DD) and an age- and IQ-matched control group (CG). Time-locked tonic and phasic lower and upper theta measures were derived and separate event-related theta band power (ERBP) scores were calculated for each of three experimental trials. The DD made significantly more errors than CG during Trials 1 and 2 of the motor task. Tonic theta did not differ between groups; however, the DD group displayed a significant decrease in ERBP across all trials and sites, specifically in central and parietal regions during Trial 3. No significant behavioral or physiological evidence supported the notion of conscious compensation (CC). Rather, deficient task performance in the DD group was associated with a general inability to recruit sufficient working memory processes.

Differences in induced gamma and upper alpha oscillations in the human brain related to verbal/performance and emotional intelligence

Participating in the study were 30 respondents, who could be clustered as high-average verbal/performance intelligent (HIQ/AIQ), or emotionally intelligent (HEIQ/AEIQ). The EEG was recorded while students were performing two tasks: the Raven's advanced progressive matrices (RAPM), and identifying emotions in pictures (IDEM). Significant differences in event-related desynchronization/synchronization (ERD/ERS) related to verbal/performance intelligence were only observed while respondents solved the RAPM. The HIQ and AIQ groups displayed temporal and spatial differently induced gamma band activity. Significant differences in ERD/ERS related to emotional intelligence were only observed for the IDEM task. HEIQ individuals displayed more gamma band ERS and less upper alpha band ERD than did AEIQ individuals. It can be concluded that HIQ and HEIQ individuals employed more adequate strategies for solving the problems at hand. The results further suggest that emotional intelligence and verbal/performance intelligence represent distinct components of the cognitive architecture.

Functional correlations of spatial quantitative EEG and intelligences in a nonalphabetical language group

This study investigated any functional correlations between intelligences and spatially recorded quantitative electroencephalograms (QEEGs) in a nonalphabetical language group. Participants, between 6 and 8 years old, were sampled in a teaching hospital located at the central Taiwan region. The Chinese Wechsler Intelligence Scale for Children-III (WISC-III) intelligence test and quantitative electroencephalograph recording procedures were both administrated to collect data. Intelligences were divided into two categories, verbal and performance intelligences, for statistical investigations. Statistical analyses of the noncontaminated QEEG dataset investigated the differentiability of each frequency on a single cortical region and coherence between cortical regions. Low QEEG frequencies were found to have a significant correlation with intelligences on some cortical regions. Coherence between symmetric cortical regions was found to be an important factor in predicting intelligences. Results showed the feasibility of functional brain mapping in the particular language population.

Relationship between resting alpha activity and the ERPs obtained during a highly demanding selective attention task

In spite of previous reports on the relationship between ongoing EEG and ERPs, there remains a lack of agreement on the nature of their nexuses. The aim of the present study was to evaluate the relationship between resting EEG and the ERP components in two groups of healthy subjects with different levels of performance in a highly demanding selective visual attention task. Young adults were classified according to the amount of their correct responses in the task, into high (HP; averaged hits (AH): 86%) and low performance groups (LP; AH: 59%). EEG was recorded during rest, prior to task performance and absolute (AP) and relative power (RP), as well as inter- (rTER) and intrahemispheric (rTRA) correlation were calculated. ERPs during task performance were also obtained and their amplitude and latency measures were assessed. Results showed that individuals with better behavioral performance had a higher synchronization between both hemispheres during rest as well as higher amplitude and shorter latencies of N2 and P3. Principal Component Analysis revealed that alpha2 AP and RP were inversely related to P2 and N2 latency. Higher values of alpha1 and alpha2 rTER were clustered with higher P3 amplitude and shorter reaction time. In conclusion, the differences in the cortical organization of HP and LP at rest (EEG) seem to be associated to the way the brain reacts during information processing (ERPs).

EEG dynamics in patients with Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disorder characterized by cognitive and intellectual deficits and behavior disturbance. The electroencephalogram (EEG) has been used as a tool for diagnosing AD for several decades. The hallmark of EEG abnormalities in AD patients is a shift of the power spectrum to lower frequencies and a decrease in coherence of fast rhythms. These abnormalities are thought to be associated with functional disconnections among cortical areas resulting from death of cortical neurons, axonal pathology, cholinergic deficits, etc. This article reviews main findings of EEG abnormalities in AD patients obtained from conventional spectral analysis and nonlinear dynamical methods. In particular, nonlinear alterations in the EEG of AD patients, i.e. a decreased complexity of EEG patterns and reduced information transmission among cortical areas, and their clinical implications are discussed. For future studies, improvement of the accuracy of differential diagnosis and early detection of AD based on multimodal approaches, longitudinal studies on nonlinear dynamics of the EEG, drug effects on the EEG dynamics, and linear and nonlinear functional connectivity among cortical regions in AD are proposed to be investigated. EEG abnormalities of AD patients are characterized by slowed mean frequency, less complex activity, and reduced coherences among cortical regions. These abnormalities suggest that the EEG has utility as a valuable tool for differential and early diagnosis of AD.

Differences in induced brain activity during the performance of learning and working-memory tasks related to intelligence

Thirteen high intelligent (H-IQ) and 13 low intelligent (L-IQ) individuals solved two figural working-memory (WM) tasks and two figural learning tasks while their EEG was recorded. For the WM tasks, only in the theta band group related differences in induced event-related desynchronization/synchronization (ERD/ERS) were observed. L-IQ individuals displayed greater theta synchronization in the later phases of task completion (1000-2000 ms) as compared to H-IQ individuals. For the learning tasks group related differences in the three alpha bands were observed. In the upper alpha band L-IQ individuals showed greater ERD in the frontal brain areas, whereas H-IQ individuals displayed greater ERD in the parieto-occipital brain areas.

EEG synchronization in mild cognitive impairment and Alzheimer's disease

OBJECTIVES

To compute the synchronization likelihood of multichannel electroencephalogram (EEG) data in Alzheimer (AD) patients, subjects with mild cognitive impairment (MCI) and subjects with subjective memory complaints (SC).

MATERIAL AND METHODS

EEGs (200 Hz sample frequency; 21 channels; average reference) were recorded in 10 AD patients (two males; age 76.2; SD 9.36; range 59-86), 17 subjects with MCI (eight males; age 77.41; SD 6.25; range 62-88) and 20 subjects with SCI (11 males; age 68.9; SD 12.96; range: 51-89). The synchronization likelihood, a novel type of coherence measure, was computed, comparing each channel with all other channels, for the 2-6, 6-10, 10-14, 14-18, 18-22 and 22-50 Hz band.

RESULTS

The synchronization likelihood was significantly decreased in the 14-18 and 18-22 Hz band in AD patients compared with both MCI subjects and healthy controls. Lower beta band synchronization correlated with lower Mini-Mental state examination (MMSE) scores.

CONCLUSION

Loss of beta band synchronization occurs early in mildly affected AD patients and correlates with cognitive impairment.

Spatiotemporal brain activity related to intelligence: a low resolution brain electromagnetic tomography study

Differences in current density between high intelligent (IQ=124), and average intelligent individuals (IQ=110), while solving two complex cognitive tasks (analytical-figural, and identification of emotions) were analyzed with low resolution brain electromagnetic tomography (LORETA). High intelligent individuals, as compared with average ones in both tasks displayed a lesser full width at half maximum (FWHM) volume-indicating the amount of spatial dispersion of the source. High and average intelligent individuals also differed in their source location. The source location of high intelligent individuals was in the inferior right hemispheric brain areas, whereas the source location of average intelligent individuals was in the superior left hemispheric brain areas. The findings were explained in the light of the neural efficiency model.

Nonlinear synchronization in EEG and whole-head MEG recordings of healthy subjects

According to Friston, brain dynamics can be modelled as a large ensemble of coupled nonlinear dynamical subsystems with unstable and transient dynamics. In the present study, two predictions from this model (the existence of nonlinear synchronization between macroscopic field potentials and itinerant nonlinear dynamics) were investigated. The dependence of nonlinearity on the method of measuring brain activity (EEG vs. MEG) was also investigated. Dataset I consisted of 10 MEG recordings in 10 healthy subjects. Dataset II consisted of simultaneously recorded MEG (126 channels) and EEG (19 channels) in 5 healthy subjects. Nonlinear coupling was assessed with the synchronization likelihood S and dynamic itinerancy with the synchronization entropy Hs. Significance was assessed with a bootstrap procedure ("surrogate data testing"), comparing S and Hs with their distribution under the null hypothesis of stationary, linear dynamics. Significant nonlinear synchronization was detected in 14 of 15 subjects. The nonlinear dynamics were associated with a high index of itinerant behaviour. Nonlinear interdependence was significantly more apparent in MEG data than EEG. Synchronous oscillations in MEG and EEG recordings contain a significant nonlinear component that exhibits characteristics of unstable and itinerant behaviour. These findings are in line with Friston's proposal that the brain can be conceived as a large ensemble of coupled nonlinear dynamical subsystems with labile and unstable dynamics. The spatial scale and physical properties of MEG acquisition may increase the sensitivity of the data to underlying nonlinear structure.

Generalized synchronization of MEG recordings in Alzheimer's Disease: evidence for involvement of the gamma band

The purpose of this study was to investigate interdependencies in whole-head magnetoencephalography (MEG) of Alzheimer patients and healthy control subjects. Magnetoencephalograms were recorded in 20 Alzheimer patients (11 men; mean age, 69.0 years [standard deviation, 8.2 years]); Mini-Mental State Examination score, 21.3 points; range, 15 to 27 points) and 20 healthy control subjects (9 men; mean age, 66.4 years [standard deviation, 9.0 years]) during a no-task eyes-closed condition with a 151 channel whole-head MEG system. Synchronization likelihood (a new measure for linear as well as nonlinear interdependencies between signals) and coherence were computed for each channel in different frequency bands (2 to 6, 6 to 10, 10 to 14, 14 to 18, 18 to 22, 22 to 40 Hz). Synchronization was lower in Alzheimer patients in the upper alpha band (10 to 14 Hz), the upper beta band (18 to 22 Hz), and the gamma band (22 to 40 Hz). In contrast, coherence did not show significant group differences at the p<0.05 level. The synchronization likelihood showed a spatial pattern (high synchronization central, parietal and right frontal; low synchronization, occipital and temporal). This study confirms a widespread loss of functional interactions in the alpha and beta bands, and provides the first evidence for loss of gamma band synchronization in Alzheimer's disease. Synchronization likelihood may be more sensitive to detect such changes than the commonly used coherence analysis.

Variability of EEG synchronization during a working memory task in healthy subjects

Working memory is associated with an increase in EEG theta synchronization and a decrease in lower alpha band synchronization. We investigated whether such changes in mean synchronization level are accompanied by changes in small scale fluctuations of synchronization. EEGs (19 channels; average reference; sample frequency 250 Hz) were recorded in 21 healthy subjects (12 males; mean age 62.5 years; S.D. 2.1) at rest and during a visual working memory condition. EEG synchronization was computed in six frequency bands (2-6; 6-10; 10-14; 14-18; 18-22; 22-50 Hz) using the synchronization likelihood. Variability of the synchronization was quantified with synchronization entropy. During the working memory condition synchronization increased in the 2-6 Hz band, and decreased in the 6-10, 14-18 and 18-22 Hz bands. Working memory was associated with increased variability in the 2-6 Hz band, and decreased variability in the 6-10 Hz band and, to a lesser extent, in the 14-18 and 18-22 Hz bands. Working memory is accompanied not only by characteristic changes in the mean level of interactions between neural networks, but also by changes in small scale fluctuations in such interactions. Strong, but rapidly fluctuating coupling between neural systems might provide a mechanism to optimize the balance between local differentiation and global integration of brain activity.

Sepsis research in the next millennium: concentrate on the software rather than the hardware

Today the basic principles of septic conditions are understood. Nevertheless, sepsis research has reached a critical point. To integrate our knowledge towards a consistent theory of the disease process and to derive effective therapies, new perspectives for future research that fit the complexity of the problem have to be found. We conducted a review of the literature concerning systemic inflammatory response syndrome (SIRS) and sepsis with particular reference to liver pathophysiology. And compared our findings with characteristic features of complex systems. The complexity of sepsis is broadly recognized. A review of the different aspects of liver inflammation during SIRS and sepsis, i.e. endotoxin challenge, cytokine induced dysfunction, the mechanisms of leukocyte transmigration, and hormonal and neuroendocrine regulatory mechanisms is given. Key aspects of complex systems, including parallelism, locality, emergence, and cross-scale interactions are introduced. We conclude that sepsis research needs new perspectives that allow us to handle the complex interactions occurring during the disease process. We propose to focus research on the interactions between the constituents of the system rather than only describing isolated aspects of the disease process. We also conclude that the ideas and techniques of non-linear systems theory are suitable tools for the analysis of complex and dynamic diseases like SIRS and sepsis.

A Genetic Perspective on the Developing Brain

Changes in genetic and environmental influences on electroencephalographic (EEG) and event-related potential (ERP) indices of neural development were studied in two large cohorts of young (N = 418) and adolescent (N = 426) twins. Individual differences in these indices were largely influenced by genetic factors, and throughout development, the stable part of the variance was mainly genetic. Both EEG power (which describes the amount of variability in brain electrical potentials that can be attributed to different frequencies) and long-distance EEG coherence (which is the squared cross-correlation between two EEG signals at different scalp locations and can be regarded as an index for cortico-cortical connectivity) were highly heritable. ERP-P300 latencies and amplitudes were low to moderately heritable. Clear differences between young children and adolescents could be observed in the heritabilities of EEG and ERP indices. The heritabilities of EEG power and EEG coherence were higher in adolescents than in children, whereas the heritabilities of P300 latencies were lower. Both cohorts (young children and adolescents) were measured twice: The children were tested when they were 5 and again at 7 years, the adolescents when they were 16 and again at 18 years. Therefore, within these age ranges a more detailed analysis of age-related changes in heritabilities and in the emergence of new genetic influences could be studied. The heritabilities of EEG powers and P300 amplitudes and latencies did not change much from age 5 to age 7 and from age 16 to 18 years. The heritabilities of a substantial number of connections within the cortex, however, as indexed by EEG coherence, changed significantly from age 5 to age 7, though not from age 16 to 18. The only changes in the heritabilities in adolescents were connections within the prefrontal cortex, which is in agreement with theories of adolescent development. These age-related changes in the heritabilities may reflect a larger impact of maturation on cortico-cortical connectivity in childhood than in adolescence. Evidence was found for qualitative changes in brain electrophysiology in young children: New genetic factors emerged at age 7 for posterior EEG coherences and for P300 latency at some scalp locations. This supports theories of qualitative stage transitions in this age range, as previously suggested using behavioral and EEG data.

Differences in EEG current density related to intelligence

Differences in current density between high intelligent (IQ=127), and low intelligent individuals (IQ=87), while solving two oddball tasks (auditive and visual) were analyzed with low resolution brain electromagnetic tomography (LORETA). In highly intelligent individuals a decrease in the volume of activated cortical gray matter between the P300 onset and the P300 peak amplitude was observed. The EEG of low intelligent individuals showed a reverse pattern of cortical activity. In the auditive oddball task the decrease in the activated cortical volume in high intelligent individuals was accompanied by an increase in current density, and a more left hemispheric source location at maximum current density. The results suggest that high intelligent individuals more efficiently distributed their cognitive resources needed to cope with the oddball tasks.

Correlations between ERP parameters and intelligence: a reconsideration

The present study investigated differences in ERP parameters related to intelligence. For that purpose 74 individuals (Intelligence: M=107; S.D.=12; range 73-135), of average creativity passively listened to two tones and performed two auditory, and two visual oddball tasks while their EEG was recorded. The approximate entropy parameters, peak latencies and amplitudes were determined. The correlation coefficients indicated that in the attended conditions, the more intelligent individuals showed more regular ERP waveforms than less intelligent individuals. It was further found that less intelligent individuals showed increased P300 latencies and reduced amplitudes. The differences were explained with a more specific engagement of neural networks in more intelligent individuals.

Theta synchronization predicts efficient memory encoding of concrete and abstract nouns

Functional and topographical differences between processing of spoken nouns which were remembered or which were forgotten were shown by means of EEG coherence analysis. Later recalled nouns were related with increased neuronal synchronization (= cooperation) between anterior and posterior brain regions regardless of presented word category (either concrete or abstract nouns). However, theta coherence exhibited topographical differences during encoding of concrete and abstract nouns whereby former were related with higher short-range (mainly intrahemispheric), later with higher long-range (mainly interhemispheric) coherence. Thus, theta synchronization possibly is a general phenomenon always occurring if task demand increases and more efficient information processing is required. Measurement of EEG coherence yields new information about the neuronal interaction of involved brain regions during memory encoding of different word classes.

Brain dynamics in theta and alpha frequency bands and working memory performance in humans

In this study non-linear and linear global electroencephalogram (EEG) changes during a visual working memory task were studied using a separate analysis of theta, lower alpha and upper alpha band filtered data. EEGs were recorded in 21 healthy subjects (62.5 year; SD 2.1; 12 females, nine males) during an eyes-closed no-task condition and a working memory condition. Coarse-grained dimension was estimated for both conditions from spatially embedded EEG data filtered in the theta band and both alpha bands. Linear measures of coupling and mean amplitude were also computed. During the working memory condition lower alpha band dimension increased. Linear analysis showed alpha1 band desynchronization. Female subjects had a higher dimension in the theta band as well as more desynchronization in the theta and alpha1 band. Working memory capacity correlated with a lower theta band dimension during the no-task condition in female subjects. The increase in alpha1 band complexity can be interpreted as increased desynchronization corresponding with attentional processes. Higher complexity/desynchronization in females seems to be a more structural phenomenon and may be more intimately related to task performance.