Inter- and intrahemispheric EEG coherence during light drowsiness

QEEG findings in nonsyndromic sagittal craniosynostosis

Despite the undertaken treatment, children with nonsyndromic sagittal craniosynostosis (NSC) are burdened with problems with speech development, visuospatial and other cognitive deficits. The electroencephalographic assessment has not influenced the diagnostics and treatment strategy of craniosynostosis so far but the introduction of quantitative EEG (QEEG) protocols renewed an interest in the functional aspect of this disease. In this study we retrospectively assessed the QEEG records of 25 children with NSC aged 1-18 months (mean age 9.62 months) before and after surgery. In each case, the amplitude, interhemispheric (ICoh) and intrahemispheric (HCoh) coherence indices were calculated. Obtained data were compared to age-matched control group of 25 normocephalic children. Children with NSC presented significantly lower values of amplitudes and intrahemispheric coherence in occipital, posterior parietal and posterior temporal regions than normocephalic children. The values of amplitudes, ICoh and HCoh in pre- and postoperative QEEG records mostly remained unchanged, with a slight improvement in HCoh in centro-parietal area. These findings suggest that NSC children present their own QEEG profile. The operative treatment improves an intrahemispheric connectivity, but there still exists a significant difference in the occipitotemporal, frontotemporal and centro-frontal areas, which may be considered as a functional substrate of reported speech and neurocognitive problems. QEEG findings in nonsyndromic sagittal craniosynostosis.

Identification of Electroencephalogram Signals in Alzheimer's Disease by Multifractal and Multiscale Entropy Analysis

Alzheimer's disease (AD) is the most common form of dementia and is a progressive neurodegenerative disease that primarily develops in old age. In recent years, it has been reported that early diagnosis of AD and early intervention significantly delays disease progression. Hence, early diagnosis and intervention are emphasized. As a diagnostic index for AD patients, evaluating the complexity of the dependence of the electroencephalography (EEG) signal on the temporal scale of Alzheimer's disease (AD) patients is effective. Multiscale entropy analysis and multifractal analysis have been performed individually, and their usefulness as diagnostic indicators has been confirmed, but the complemental relationship between these analyses, which may enhance diagnostic accuracy, has not been investigated. We hypothesize that combining multiscale entropy and fractal analyses may add another dimension to understanding the alteration of EEG dynamics in AD. In this study, we performed both multiscale entropy and multifractal analyses on EEGs from AD patients and healthy subjects. We found that the classification accuracy was improved using both techniques. These findings suggest that the use of multiscale entropy analysis and multifractal analysis may lead to the development of AD diagnostic tools.

Classification Methods Based on Complexity and Synchronization of Electroencephalography Signals in Alzheimer's Disease

Electroencephalography (EEG) has long been studied as a potential diagnostic method for Alzheimer's disease (AD). The pathological progression of AD leads to cortical disconnection. These disconnections may manifest as functional connectivity alterations, measured by the degree of synchronization between different brain regions, and alterations in complex behaviors produced by the interaction among wide-spread brain regions. Recently, machine learning methods, such as clustering algorithms and classification methods, have been adopted to detect disease-related changes in functional connectivity and classify the features of these changes. Although complexity of EEG signals can also reflect AD-related changes, few machine learning studies have focused on the changes in complexity. Therefore, in this study, we compared the ability of EEG signals to detect characteristics of AD using different machine learning approaches one focused on functional connectivity and the other focused on signal complexity. We examined functional connectivity, estimated by phase lag index (PLI) in EEG signals in healthy older participants [healthy control (HC)] and patients with AD. We estimated signal complexity using multi-scale entropy. Utilizing a support vector machine, we compared the identification accuracy of AD based on functional connectivity at each frequency band and complexity component. Additionally, we evaluated the relationship between synchronization and complexity. The identification accuracy of functional connectivity of the alpha, beta, and gamma bands was significantly high (AUC 1.0), and the identification accuracy of complexity was sufficiently high (AUC 0.81). Moreover, the relationship between functional connectivity and complexity exhibited various temporal-scale-and-regional-specific dependency in both HC participants and patients with AD. In conclusion, the combination of functional connectivity and complexity might reflect complex pathological process of AD. Applying a combination of both machine learning methods to neurophysiological data may provide a novel understanding of the neural network processes in both healthy brains and pathological conditions.

Atypical temporal-scale-specific fractal changes in Alzheimer's disease EEG and their relevance to cognitive decline

Recent advances in nonlinear analytic methods for electroencephalography have clarified the reduced complexity of spatiotemporal dynamics in brain activity observed in Alzheimer’s disease (AD). However, there are far fewer studies exploring temporal scale dependent fractal properties in AD, despite the importance of studying the dynamics of brain activity within physiologically relevant frequency ranges. Higuchi’s fractal dimension is a widely used index for evaluating fractality in brain activity, but temporal-scale-specific characteristics are lost due to its requirement of averaging over the entire range of temporal scales. In this study, we adapted Higuchi’s fractal algorithm into a method for investigating temporal-scale-specific fractal properties. We then compared the values of the temporal-scale-specific fractal dimension between healthy control (HC) and AD patient groups. Our data indicate that relative to the HC group, the AD group demonstrated reduced fractality at both slow and fast temporal scales. Moreover, we confirmed that the fractality at fast temporal scales correlates with cognitive decline. These properties might serve as a basis for a useful approach to characterizing temporal neural dynamics in AD or other neurodegenerative disorders.

Sequential EEG Analysis during Intermittent Photic Stimulation in Never-Medicated Patients with Schizophrenia

To investigate sequential changes in electroencephalograms (EEGs) during intermittent photic stimulation (IPS), quantitative EEG analysis for the alpha band (related to stimulus frequency) was performed in 18 drug-naïve schizophrenic patients and 18 sex- and age-matched control subjects. IPS consisted of white flickers at 10 flashes/sec, lasting 10 sec and repeated six times at 10 sec intervals. The differences between the two groups were assessed for two conditions (i.e., during photic stimulation (PS) and inter-PS). During stimulus, the absolute 9–11 Hz band power of the patient group was higher at the posterior than that at the anterior sites throughout the 10 sec periods. However, this difference between sites was not seen during the first 1 sec in the control group. During the nonstimulus period, posterior dominance of 9–11 Hz band power was prominent in the patient group throughout. In the control group, however, this difference was minor, especially during the latter half of the period. These results suggest that schizophrenic patients show fewer changes in posterior alpha activity during both stimulus and nonstimulus, and this continuity of posterior dominance may reflect hyperarousal, which counteracts any decrease in vigilance throughout the IPS.

Memory load effect in auditory-verbal short-term memory task: EEG fractal and spectral analysis

The objective of this preliminary study was to quantify changes in complexity of EEG using fractal dimension (FD) alongside linear methods of spectral power, event-related spectral perturbations, coherence, and source localization of EEG generators for theta (4-7 Hz), alpha (8-12 Hz), and beta (13-23 Hz) frequency bands due to a memory load effect in an auditory-verbal short-term memory (AVSTM) task for words. We examined 20 healthy individuals using the Sternberg's paradigm with increasing memory load (three, five, and seven words). The stimuli were four-letter words. Artifact-free 5-s EEG segments during retention period were analyzed. The most significant finding was the increase in FD with the increase in memory load in temporal regions T3 and T4, and in parietal region Pz, while decrease in FD with increase in memory load was registered in frontal midline region Fz. Results point to increase in frontal midline (Fz) theta spectral power, decrease in alpha spectral power in parietal region-Pz, and increase in beta spectral power in T3 and T4 region with increase in memory load. Decrease in theta coherence within right hemisphere due to memory load was obtained. Alpha coherence increased in posterior regions with anterior decrease. Beta coherence increased in fronto-temporal regions. Source localization delineated theta activity increase in frontal midline region, alpha decrease in superior parietal region, and beta increase in superior temporal gyrus with increase in memory load. In conclusion, FD as a nonlinear measure may serve as a sensitive index for quantifying dynamical changes in EEG signals during AVSTM tasks.

Changes in EEG complexity with electroconvulsive therapy in a patient with autism spectrum disorders: a multiscale entropy approach

Autism spectrum disorders (ASD) are heterogeneous neurodevelopmental disorders that are reportedly characterized by aberrant neural networks. Recently developed multiscale entropy analysis (MSE) can characterize the complexity inherent in electroencephalography (EEG) dynamics over multiple temporal scales in the dynamics of neural networks. We encountered an 18-year-old man with ASD whose refractory catatonic obsessive–compulsive symptoms were improved dramatically after electroconvulsive therapy (ECT). In this clinical case study, we strove to clarify the neurophysiological mechanism of ECT in ASD by assessing EEG complexity using MSE. Along with ECT, the frontocentral region showed decreased EEG complexity at higher temporal scales, whereas the occipital region expressed an increase at lower temporal scales. Furthermore, these changes were associated with clinical improvement associated with the elevation of brain-derived neurotrophic factor, which is a molecular hypothesis of ECT, playing key roles in ASD pathogenesis. Changes in EEG complexity in a region-specific and temporal scale-specific manner that we found might reflect atypical EEG dynamics in ASD. Although MSE is not a direct approach to measuring neural connectivity and the results are from only a single case, they might reflect specific aberrant neural network activity and the therapeutic neurophysiological mechanism of ECT in ASD.

The Impact of Sound on Electroencephalographic Waves during Sleep in Patients Suffering from Tinnitus

Based on the knowledge that sensory processing continues during sleep and that a relationship exists between sleep and learning, a new strategy for treatment of idiopathic subjective tinnitus, consisted of customized sound stimulation presented during sleep, was tested. It has been previously shown that this treatment induces a sustained decrease in tinnitus intensity; however, its effect on brain activity has not yet been studied. In this work, we compared the impact of sound stimulation in tinnitus patients in the different sleep stages. Ten patients with idiopathic tinnitus were treated with sound stimulation mimicking tinnitus during sleep. Power spectra and intra- and inter-hemispheric coherence of electroencephalographic waves from frontal and temporal electrodes were measured with and without sound stimulation for each sleep stage (stages N2 with sleep spindles; N3 with slow wave sleep and REM sleep with Rapid Eye Movements). The main results found were that the largest number of changes, considering both the power spectrum and wave׳s coherence, occurred in stages N2 and N3. The delta and theta bands were the most changed, with important changes also in coherence of spindles during N2. All changes were more frequent in temporal areas. The differences between the two hemispheres do not depend, at least exclusively, on the side where the tinnitus is perceived and, hence, of the stimulated side. These results demonstrate that sound stimulation during sleep in tinnitus patients׳ influences brain activity and open an avenue for investigating the mechanism underlying tinnitus and its treatment.

Neurophysiological basis of creativity in healthy elderly people: a multiscale entropy approach

OBJECTIVES

Creativity, which presumably involves various connections within and across different neural networks, reportedly underpins the mental well-being of older adults. Multiscale entropy (MSE) can characterize the complexity inherent in EEG dynamics with multiple temporal scales. It can therefore provide useful insight into neural networks. Given that background, we sought to clarify the neurophysiological bases of creativity in healthy elderly subjects by assessing EEG complexity with MSE, with emphasis on assessment of neural networks.

METHODS

We recorded resting state EEG of 20 healthy elderly subjects. MSE was calculated for each subject for continuous 20-s epochs. Their relevance to individual creativity was examined concurrently with intellectual function.

RESULTS

Higher individual creativity was linked closely to increased EEG complexity across higher temporal scales, but no significant relation was found with intellectual function (IQ score).

CONCLUSIONS

Considering the general "loss of complexity" theory of aging, our finding of increased EEG complexity in elderly people with heightened creativity supports the idea that creativity is associated with activated neural networks.

SIGNIFICANCE

Results reported here underscore the potential usefulness of MSE analysis for characterizing the neurophysiological bases of elderly people with heightened creativity.

Cortical reorganization after hand immobilization: the beta qEEG spectral coherence evidences

There is increasing evidence that hand immobilization is associated with various changes in the brain. Indeed, beta band coherence is strongly related to motor act and sensitive stimuli. In this study we investigate the electrophysiological and cortical changes that occur when subjects are submitted to hand immobilization. We hypothesized that beta coherence oscillations act as a mechanism underlying inter- and intra-hemispheric changes. As a methodology for our study fifteen healthy individuals between the ages of 20 and 30 years were subjected to a right index finger task before and after hand immobilization while their brain activity pattern was recorded using quantitative electroencephalography. This analysis revealed that hand immobilization caused changes in frontal, central and parietal areas of the brain. The main findings showed a lower beta-2 band in frontal regions and greater cortical activity in central and parietal areas. In summary, the coherence increased in the frontal, central and parietal cortex, due to hand immobilization and it adjusted the brains functioning, which had been disrupted by the procedure. Moreover, the brain adaptation upon hand immobilization of the subjects involved inter- and intra-hemispheric changes.

Cortical reorganization after hand immobilization: the beta qEEG spectral coherence evidences

There is increasing evidence that hand immobilization is associated with various changes in the brain. Indeed, beta band coherence is strongly related to motor act and sensitive stimuli. In this study we investigate the electrophysiological and cortical changes that occur when subjects are submitted to hand immobilization. We hypothesized that beta coherence oscillations act as a mechanism underlying inter- and intra-hemispheric changes. As a methodology for our study fifteen healthy individuals between the ages of 20 and 30 years were subjected to a right index finger task before and after hand immobilization while their brain activity pattern was recorded using quantitative electroencephalography. This analysis revealed that hand immobilization caused changes in frontal, central and parietal areas of the brain. The main findings showed a lower beta-2 band in frontal regions and greater cortical activity in central and parietal areas. In summary, the coherence increased in the frontal, central and parietal cortex, due to hand immobilization and it adjusted the brains functioning, which had been disrupted by the procedure. Moreover, the brain adaptation upon hand immobilization of the subjects involved inter- and intra-hemispheric changes.

Assessment of EEG dynamical complexity in Alzheimer's disease using multiscale entropy

OBJECTIVE

Multiscale entropy (MSE) is a recently proposed entropy-based index of physiological complexity, evaluating signals at multiple temporal scales. To test this method as an aid to elucidating the pathophysiology of Alzheimer's disease (AD), we examined MSE in resting state EEG activity in comparison with traditional EEG analysis.

METHODS

We recorded EEG in medication-free 15 presenile AD patients and 18 age- and sex-matched healthy control (HC) subjects. MSE was calculated for continuous 60-s epochs for each group, concurrently with power analysis.

RESULTS

The MSE results from smaller and larger scales were associated with higher and lower frequencies of relative power, respectively. Group analysis demonstrated that the AD group had less complexity at smaller scales in more frontal areas, consistent with previous findings. In contrast, higher complexity at larger scales was observed across brain areas in AD group and this higher complexity was significantly correlated with cognitive decline.

CONCLUSIONS

MSE measures identified an abnormal complexity profile across different temporal scales and their relation to the severity of AD.

SIGNIFICANCE

These findings indicate that entropy-based analytic methods with applied at temporal scales may serve as a complementary approach for characterizing and understanding abnormal cortical dynamics in AD.

Age-related variation in EEG complexity to photic stimulation: a multiscale entropy analysis

OBJECTIVE

This study was intended to examine variations in electroencephalographic (EEG) complexity in response to photic stimulation (PS) during aging to test the hypothesis that the aging process reduces physiologic complexity and functional responsiveness.

METHODS

Multiscale entropy (MSE), an estimate of time-series signal complexity associated with long-range temporal correlation, is used as a recently proposed method for quantifying EEG complexity with multiple coarse-grained sequences. We recorded EEG in 13 healthy elderly subjects and 12 healthy young subjects during pre-PS and post-PS conditions and estimated their respective MSE values.

RESULTS

For the pre-PS condition, no significant complexity difference was found between the groups. However, a significant MSE change (complexity increase) was found post-PS only in young subjects, thereby revealing a power-law scaling property, which means long-range temporal correlation.

CONCLUSIONS

Enhancement of long-range temporal correlation in young subjects after PS might reflect a cortical response to stimuli, which was absent in elderly subjects. These results are consistent with the general "loss of complexity/diminished functional response to stimuli" theory of aging.

SIGNIFICANCE

Our findings demonstrate that application of MSE analysis to EEG is a powerful approach for studying age-related changes in brain function.

Neurophysiologic and neuroimaging studies of brain plasticity in children with spastic cerebral palsy

Patients with cerebral palsy (CP) may have some problems other than this motor impairment: mental retardation, epilepsy and sensory disturbance. Healthy children and children with CP have an enhanced capacity for learning and memory compared to adults. There are few tools for brain plasticity investigations. The utility of the neurophysiologic and MRI techniques in the determination of brain reorganization and repair in patients with cerebral palsy is described. The authors discuss their results of quantitative EEG and spectroscopy MRI studies in children with CP. Quantitative EEG and spectroscopy MRI can be useful tools in the determination of these processes in children with CP.

EEG coherence analysis in never-medicated patients with panic disorder

To investigate the functional abnormalities in the central nervous system (CNS) of patients with panic disorder (PD), we compared the electroencephalography (EEG) coherence values in 18 never-medicated PD patients with those in age-matched normal control subjects, and examined the relationships between EEG coherence values and both the duration of disease and the severity of panic attacks. EEG data were recorded in the resting state. The PD patients had lower coherence values with significant differences in F3-F4, C3-C4, P3-P4, F7-T5, and F8-T6. There were positive correlations for the higher alpha band between coherence values and both the duration of disease and the severity of panic attacks. These findings provide further evidence that PD patients have a lower degree of inter-hemispheric functional connectivity in the frontal region and intra-hemispheric functional connectivity in the bilateral temporal region, and that chronic condition or frequent panic attacks in PD patients may be related to the pathophysiological CNS changes.

Automatic recognition of alertness and drowsiness from EEG by an artificial neural network

We present a novel method for classifying alert vs drowsy states from 1 s long sequences of full spectrum EEG recordings in an arbitrary subject. This novel method uses time series of interhemispheric and intrahemispheric cross spectral densities of full spectrum EEG as the input to an artificial neural network (ANN) with two discrete outputs: drowsy and alert. The experimental data were collected from 17 subjects. Two experts in EEG interpretation visually inspected the data and provided the necessary expertise for the training of an ANN. We selected the following three ANNs as potential candidates: (1) the linear network with Widrow-Hoff (WH) algorithm; (2) the non-linear ANN with the Levenberg-Marquardt (LM) rule; and (3) the Learning Vector Quantization (LVQ) neural network. We showed that the LVQ neural network gives the best classification compared with the linear network that uses WH algorithm (the worst), and the non-linear network trained with the LM rule. Classification properties of LVQ were validated using the data recorded in 12 healthy volunteer subjects, yet whose EEG recordings have not been used for the training of the ANN. The statistics were used as a measure of potential applicability of the LVQ: the t-distribution showed that matching between the human assessment and the network output was 94.37+/-1.95%. This result suggests that the automatic recognition algorithm is applicable for distinguishing between alert and drowsy state in recordings that have not been used for the training.

Electroencephalography Activity Associated with Driver Fatigue: Implications for a Fatigue Countermeasure Device

Abstract This paper reviews the association between electroencephalography (EEG) activity and driver fatigue. The current literature shows substantial evidence of changes in brain wave activity, such as simultaneous changes in slow-wave activity (e.g., delta and theta activity) as well as alpha activity during driver fatigue. It is apparent from the literature review that EEG is a promising neurophysiological indicator of driver fatigue and has the potential to be incorporated into the development of a fatigue countermeasure device. The findings from this review are discussed in the light of directions for future fatigue research studies.

Power spectra and coherence in the EEG of a vegetative patient with severe asymmetric brain damage

OBJECTIVES

To examine differences in power spectra and intra-hemispheric coherence between the left and right hemispheres in the presence of severe asymmetric brain damage.

METHODS

Power spectra and coherence functions were computed for a patient with severe damage to subcortical gray matter structures on the right side but relative preservation on the left.

RESULTS

Power spectra differed modestly over the hemispheres, with greater low frequency power and less high frequency power over the more damaged right hemisphere. Coherence differed dramatically, with marked reduced coherence over the right hemisphere, particularly frontally where the damage was most extensive.

CONCLUSIONS

Damage to subcortical structures of one hemisphere may result in a marked reduction in coherence in the ipsilateral EEG with only a modest change in the power spectrum. We speculate that the physiologic basis of this selective change is damage to structures mediating communication between cortical areas.

State-modulation of cortico-cortical connections underlying normal EEG alpha variants

Normal electroencephalographic (EEG) alpha variants appear during relaxed wakefulness with closed eyes, drowsiness period at sleep onset, and rapid eye movement (REM) sleep in bursts without arousal signals. Previous results revealed that fronto-occipital and fronto-frontal alpha coherences became weaker from wakefulness to drowsiness, and finally to REM sleep. The present work was aimed at determining whether a generalized or a unidirectional deactivation of the long fronto-occipital fasciculi, previously proposed to be involved in the alpha rhythm generation, could explain the above-mentioned results. Polynomial regression analyses, applied to the change of alpha coherence with distance along the antero-posterior axis, suggested that the anterior and posterior local circuits show a similar level of activation in all brain states. Bivariate partial correlation analyses between local alpha coherences revealed that such local circuits maintain a reciprocal dependency during wakefulness, but unidirectional during drowsiness (anterior-to-posterior, A-P) and REM sleep (posterior-to-anterior, P-A). From these findings, both anterior and posterior cortical structures are suggested as being involved in the generation of the three alpha variants. If the implication of a double cortical generation source (anterior and posterior) of alpha variants is assumed, these two generators seem to maintain a mutual inter-dependency during wakefulness, whereas during the transition to human sleep, the anterior areas work quite independently of the posterior regions. Finally, the occipital structures may be the driving force for the REM-alpha bursts generation, since involvement of frontal regions demonstrated a high dependence on the posterior neural circuits in the genesis of this sleep event.

Electroencephalographic coherence analysis in multiple sclerosis: correlation with clinical, neuropsychological, and MRI findings

OBJECTIVE

To explore functional corticocortical connections in multiple sclerosis by means of coherence of the EEG, and to evaluate their correlations with the degree of cognitive impairment and with brain lesion load assessed by MRI.

METHODS

EEG coherence was studied from 28 patients with clinically definite multiple sclerosis. Ten minutes of resting EEG were recorded with 20 scalp electrodes, with binaural reference. FFT power and coherence were calculated in artifact free epochs of 1 second and compared with values from 22 control subjects of comparable age and sex distribution. Patients also underwent MRI (n=27) and neuropsychological examination (n=21).

RESULTS

Compared with controls, patients with multiple sclerosis showed increased theta power in the frontotemporal-central regions (p<0.005). theta Band coherence was decreased between homologous areas (p<0.02). alpha Band coherence was decreased both in the local and long distance connections (p<0.0005). These findings were most striking both in patients with high MRI subcortical lesion load and in patients with cognitive involvement. A significant correlation was found between interhemispheric theta (p=0.02) and alpha (p=0. 017) and anteroposterior alpha (p=0.013) coherence and subcortical MRI lesion load, but not with exclusively periventricular lesion load.

CONCLUSIONS

These findings support the hypothesis that cognitive impairment in multiple sclerosis is mostly dependent on involvement of corticocortical connections related to demyelination and/or axonal loss within the white matter immediately underlying the cortex.

Effects of scopolamine on interhemispheric EEG coherence in healthy subjects: analysis during rest and photic stimulation

The present study of coherence analysis, in 16 healthy male volunteers, aged 24-31 years, showed that the administration of 0.25 mg of scopolamine significantly reduced interhemispheric coherence in the delta and beta-1 bands in the resting state. Scopolamine also caused a significant increase both in EEG coherence during PS and in PS-related coherence reactivity in the beta band. In addition, this compound significantly reduced total WMS scores. These findings suggest that, in addition to causing cognitive impairments, central cholinergic dysfunction can alter interhemispheric functional connectivity under both nonstimulus and stimulus conditions.

EEG coherence in pathological conditions

Coherence analysis of the electroencephalogram is considered an indicator of functional cortico-cortical connections, which makes it suitable for the neurophysiologic investigation of brain connectivity in normal and pathological conditions. In the clinical environment, coherence analysis has been applied in the study of brain development and in the assessment of diseases potentially involving brain connectivity, such as cortical and subcortical dementia, schizophrenia, and corpus callosum lesions. Whereas coherence decrease, at least for the high-frequency bands, is considered the expression of decreased functional cortico-cortical connections, more work needs to be performed in interpreting coherence increases. A special consideration is also required by technical aspects, such as the recording conditions and the reference used, which may greatly influence the results and need to be accounted for when drawing physiopathological interpretations. At present, whereas coherence analysis resulted successful in differentiating patients groups from the normal population, the specificity of coherence changes in various pathological conditions is questionable at the best. The same limits apply to the diagnostic value of the technique in individual patients.

Alpha EEG coherence in different brain states: an electrophysiological index of the arousal level in human subjects

The functional relationships between the brain areas supposedly involved in the generation of the alpha activity were quantified by means of INTRA- and INTER-hemispheric coherences during different arousal states (relaxed wakefulness, drowsiness at sleep onset, and rapid eye movement sleep) where such an activity can be clearly detectable in the human EEG. A significant decrease in the fronto-occipital as well as in the inter-frontal coherence values in the alpha range was observed with the falling of the vigilance level, which suggests that the brain mechanisms underlying these coherences are state dependent. Making fronto-frontal coherence values in the alpha frequency band useful indexes to discern between brain functional states characterized by a different arousal level.

Interhemispheric EEG coherence in never-medicated patients with paranoid schizophrenia: analysis at rest and during photic stimulation

We assessed functional relationships between hemispheres by calculating interhemispheric EEG coherence at rest and during photic stimulation in 18 never-medicated patients with paranoid schizophrenia and 30 control subjects. Although no significant group differences were found in the resting EEG, the schizophrenic patients had significantly higher coherence on EEGs recorded during photic stimulation, compared to the control subjects. In this study, we also examined the changes in interhemispheric coherence from rest to the stimulus condition (i.e., stimulation-related coherence reactivity); the patients were found to show significantly greater coherence reactivity to photic stimulation. These findings provide further evidence that schizophrenic patients have a higher degree of interhemispheric functional connectivity and thus have less lateralized cerebral organization than normal subjects. Our results also suggest that schizophrenic patients have excessive functional reorganization between hemispheres in association with photic stimulation.

Electroencephalographic coherence abnormalities in preterm diplegia

Twelve patients with spastic diplegia (SD) and visuoperceptual impairments from preterm birth were evaluated for electroencephalogram (EEG) spectral power density, interhemispheric (ICoh) and intrahemispheric (HCoh) coherence, and asymmetry of coherence between the right and left hemispheres in and compared with normal children under resting conditions. There were no significant differences in EEG spectral power density. The SD group revealed lower ICoh at the occipital pair for the alpha band (P = .0034) and a higher value at the frontal pair for the theta band (P = .0047). Higher HCoh in SD was pronounced in the left hemisphere for the delta, theta, and beta bands (P < .01). There were no higher values in the control group. Higher HCoh asymmetry was exhibited in the left hemisphere in the control group, while very little asymmetry was found in the SD group. In both groups 91.7% were classified correctly by discriminant analysis. We suggest that these neurophysiologic abnormalities in preterm SD children correspond neuroanatomically to the callosal thinning and neuropsychologically to the visuoperceptual impairments.