Article

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

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Abstract

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.

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... Furthermore, the time course of recovery following desynchronization differed for these two rhythms, with faster ones recovering more quickly [131]. These data suggest that mu rhythm is not a unitary phenomenon but an aggregation of different processes involved in the transformation of ''seeing'' and ''hearing'' into ''doing,'' with distinct aspects of that process reflected in these different frequencies (i.e., [8][9][10][10][11][12][15][16][17][18][19][20][21][22][23][24][25]. ...
... The coupling or resonant state of local alpha networks is also supported by evidence that fronto-occipital and frontofrontal alpha coherences decouple or become weaker from wakefulness to drowsiness and finally to REM sleep. These networks seem to maintain a mutual inter-dependency during wakefulness, whereas, during the transition to human sleep, the anterior and posterior areas appear to work quite independently [17]. This coupling -decoupling or localglobal coherence is consistent with the idea that synchronized alpha-like rhythms are the result of powerful inhibitory effects on thalamocortical information transfer [64]. ...
... These changes in rhythmic activity must be viewed within the context of a local -global organization. Furthermore, the evidence of functionally distinct lower (8-10 Hz), middle (10)(11)(12), and upper (15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25) bands that may reflect different aspects of this global versus local processing [111] suggests that these bands should be examined independently. Nevertheless, the evidence indicates that several distinct states may be possible: (1) local suppression due to desynchronized activity in a restricted cortical region as a function of asynchronous activation of the network-this produces alpha-like suppression, overall greater cellular firing, and stronger BOLD signals; (2) local enhancement due to synchronized activity of a smaller population of cells in a restricted cortical region-this produces mu enhancement but overall less cellular firing and hence reduced BOLD signals; (3) global enhancement due to synchronized activity across widely distributed networks-this produces alpha-like enhancement, more cellular activity, and stronger BOLD signals; and (4) global suppression due to synchronized activity of a smaller subset of the networksthis produces alpha-like suppression, less cellular activity, and reduced BOLD signals [32,33]. ...
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Existing evidence indicates that mu and other alpha-like rhythms are independent phenomena because of differences in source generation, sensitivity to sensory events, bilateral coherence, frequency, and power. Although mu suppression and enhancement echo sensorimotor processing in frontoparietal networks, they are also sensitive to cognitive and affective influences and likely reflect more than an idling brain state. Mu rhythms are present at early stages of human development and in other mammalian species. They exhibit adaptive and dynamically changing properties, including frequency acceleration and posterior-to-anterior shifts in focus. Furthermore, individuals can learn to control mu rhythms volitionally in a very short period of time. This raises questions about the mu rhythm's open neural architecture and ability to respond to cognitive, affective, and motor imagery, implying an even greater developmental and functional role than has previously been ascribed to it. Recent studies have suggested that mu rhythms reflect downstream modulation of motor cortex by prefrontal mirror neurons, i.e., cells that may play a critical role in imitation learning and the ability to understand the actions of others. It is proposed that mu rhythms represent an important information processing function that links perception and action-specifically, the transformation of "seeing" and "hearing" into "doing." In a broader context, this transformation function results from an entrainment/gating mechanism in which multiple alpha networks (visual-, auditory-, and somatosensory-centered domains), typically producing rhythmic oscillations in a locally independent manner, become coupled and entrained. A global or 'diffuse and distributed alpha system' comes into existence when these independent sources of alpha become coherently engaged in transforming perception to action.
... For instance, REM-sleep is considered as a state of brain activation where EEGsignals show low voltage fast activity including Beta and Gamma oscillations (Rechtschaffen and Kales, 1968;LLinás and Ribary, 1993;Achermann 2016), whereas Non-REM sleep (NREM) is characterized by high voltage, Delta and Theta oscillations containing special signatures like sleep spindles and K-complexes (Rechtschaffen and Kales, 1968;Steriade, 1997;Steriade and McCarley, 1990). In addition to changes of the power of ongoing electrical activity, the temporal coupling among brain regions is modified during sleep stages relative to wakefulness in a state-dependent manner (Corsi-Cabrera et al., 1987;Nielsen et al., 1990;LLinás and Ribary,1993;Kaminski et al.,1997;Achermann and Borbely, 1998;Cantero et al 2000;Pérez-Garci et al., 2001 This paper has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof. ...
... The final published version may differ from this proof. Cabrera et al., 1987;Nielsen et al., 1990;LLinás and Ribary,1993;Kaminski et al.,1997;Achermann and Borbely, 1998;Cantero et al 2000;Pérez-Garci et al., 2001;De Gennaro et al, 2001;Corsi-Cabrera et al., 2003, Duckrow andZaveri, 2005;Voss et al., 2009, Gast et al. 2014 given that, beside of the exception of two subjects, all medians are clearly above 0.85. ...
Article
Since the discovery of electrical activity of the brain electroencephalographic recordings (EEG) constitute one of the most popular techniques of brain research. However, EEG-signals are highly non-stationary and one should expect that averages of the cross-correlation coefficient, which may take positive and negative values with equal probability, (almost) vanish when estimated over long data segments. Instead, we found that the average zero-lag cross-correlation matrix estimated with a running window over the whole night of sleep EEGs, or of resting state during eyes-open and eyes-closed condition of healthy subjects shows a characteristic correlation pattern containing pronounced non-zero values. A similar correlation structure has already been encountered in scalp EEG-signals containing focal onset seizures. Therefore, we conclude that this structure is independent of the physiological state. Because of its pronounced similarity across subjects, we believe that it depicts a generic feature of the brain dynamics. Namely, we interpret this pattern as a manifestation of a dynamical ground state of the brain activity, necessary to preserve an efficient operational mode, or, expressed in terms of dynamical system theory, we interpret it as a "shadow" of the evolution on (or close to) an attractor in phase space. Non-stationary dynamical aspects of higher cerebral processes should manifest in deviations from this stable pattern. We confirm this hypothesis via a correlation analysis of EEG recordings of 10 healthy subjects during night sleep, 20 recordings of 9 epilepsy patients and 42 recordings of 21 healthy subjects in resting state during eyes-open and eyes-closed condition. In particular we show that the estimation of deviations from the stationary correlation structures provides a more significant differentiation of physiological states and more homogeneous results across subjects.
... Pineda (2005) suggested that the common base frequency range for both the motor (mu rhythm) and visual (alpha rhythm) cortex can provide communication between these areas of the cortex during complex perception tasks. Studies of other neural processes have revealed evidence of the functional connection of independent alpha networks (for example, during sleep: Cantero et al. 2000), but the features and sensitivity of the occipital alpha and central mu rhythms during observation of actions have yet to be studied. ...
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Increasingly, in the field of communication, education, and business, people are switching to video interaction, and interlocutors frequently complain that the perception of nonverbal information and concentration suffer. We investigated this issue by analyzing electroencephalogram (EEG) oscillations of the sensorimotor (mu rhythm) and visual (alpha rhythm) cortex of the brain in an experiment with action observation live and on video. The mu rhythm reflects the activity of the mirror neuron system, and the occipital alpha rhythm shows the level of visual attention. We used 32-channel EEG recorded during live and video action observation in 83 healthy volunteers. The ICA method was used for selecting the mu- and alpha-components; the Fourier Transform was used to calculate the suppression index relative to the baseline (stationary demonstrator) of the rhythms. The main range of the mu rhythm was indeed sensitive to social movement and was highly dependent on the conditions of interaction—live or video. The upper mu-range appeared to be less sensitive to the conditions, but more sensitive to different movements. The alpha rhythm did not depend on the type of movement; however, a live performance initially caused a stronger concentration of visual attention. Thus, subtle social and nonverbal perceptions may suffer in remote video interactions.
... Pineda (2005) suggested that the common base frequency range for both the motor (mu rhythm) and visual (alpha rhythm) cortex can provide communication between these areas of the cortex during complex perception tasks. Studies of other neural processes have revealed evidence of the functional connection of independent alpha networks (for example, during sleep: Cantero et al. 2000), but the features and sensitivity of the occipital alpha and central mu rhythms during observation of actions have yet to be studied. ...
Preprint
Increasingly, in the field of communication, education and business, people are switching to video interaction, and interlocutors frequently complain that the perception of non-verbal information and concentration suffer. We investigated this issue by analyzing EEG oscillations of the sensorimotor (mu-rhythm) and visual (alpha-rhythm) cortex of the brain in an experiment with observation of identical action demonstrators live and on video. The mu-rhythm reflects the activity of the mirror neuron system, which is responsible for social perception of the actions and body language of other people, and the occipital alpha-rhythm shows the level of visual attention. We used 32-channel EEG recorded during live and video action observation in 83 healthy volunteers. The ICA infomax method was used for decomposing and selecting the components of the mu- and alpha-rhythms; the Fourier Transform was used to calculate the suppression index relative to the baseline (stationary demonstrator) of the two sub-bands (8-13 Hz and 13-24 Hz) of the mu-rhythm and the alpha-rhythm. Our work shows that the main range, 8-13 Hz, of the mu-rhythm is indeed sensitive to biological and social movement and is highly dependent on the conditions of interaction - live or video. The upper mu-range of 13-24 Hz appeared to be less sensitive to the type of demonstration, but more sensitive to different movements. The alpha-rhythm does not depend on the type of movement, however, a live performance initially causes a stronger concentration of visual attention. Thus, subtle social and nonverbal perceptions may suffer in remote video interactions.
... Indeed, Pineda (2005) suggested that a common underlying frequency band for both motor (mu) and sensory (alpha) cortices can act together and allow for communication across cortical regions. Research into other neural processes have found evidence for the functional coupling of independent alpha networks (e.g., during sleep: Cantero et al., 2000), but whether such coupling exists between occipital alpha and central mu during action observation has yet to be explored. Mirroring and attention processes may be mediated by a common functional network and a shared oscillatory frequency (mu/alpha). ...
... Sleep deprivation induces known effects on the spectral content of eyes-closed spontaneous EEG signals such as a decrease of alpha power and coherence [10,11,25,26,53,54], but also an increase in theta power, which has been considered a useful measure of accumulated sleep pressure during long periods of sustained wakefulness [7][8][9]12,26]. Low frequency power changes are most apparent in frontal brain areas, indicating that the prefrontal cortex may be especially susceptible to the effects of prolonged wakefulness [55]. ...
Article
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Sleep deprivation (SD) has adverse effects on mental and physical health, affecting the cognitive abilities and emotional states. Specifically, cognitive functions and alertness are known to decrease after SD. The aim of this work was to identify the directional information transfer after SD on scalp EEG signals using transfer entropy (TE). Using a robust methodology based on EEG recordings of 18 volunteers deprived from sleep for 36 h, TE and spectral analysis were performed to characterize EEG data acquired every 2 h. Correlation between connectivity measures and subjective somnolence was assessed. In general, TE showed medium- and long-range significant decreases originated at the occipital areas and directed towards different regions, which could be interpreted as the transfer of predictive information from parieto-occipital activity to the rest of the head. Simultaneously, short-range increases were obtained for the frontal areas, following a consistent and robust time course with significant maps after 20 h of sleep deprivation. Changes during sleep deprivation in brain network were measured effectively by TE, which showed increased local connectivity and diminished global integration. TE is an objective measure that could be used as a potential measure of sleep pressure and somnolence with the additional property of directed relationships.
... After SD, alpha synchronization was decreased during eyes-closed resting state. A decrease in alpha coherence has been related to drowsiness [Cantero et al., 1999[Cantero et al., , 2000]. However, one has to realize that the methodology of the studies by Cantero et al. are systematically different from ours: (1) they acquired the different vigilance states (awake-drowsiness-REM sleep) while the subjects went to sleep; this setting is different from the AAT in our study where subjects sit upright and have to fixate on a black circle on a computer screen; (2) drowsiness was specifically specified when ''slow eye movements appeared simultaneously with alpha activity,'' whereas in our current study we excluded epochs with slow eye movements; ...
... Occipital regions have been considered in terms of their relation to sleep events. According to Cantero et al. (2000), the occipital structures may be the driving force for REMalpha bursts generation. Jeong et al. (2001) showed that 24 h sleep-deprived states had lower average correlation dimension values at the left occipital channel compared to the baseline values. ...
... The corpus callosum plays an important role in the maintenance of inter-hemispheric communication through homotopic and heterotopic callosal projections (Innocenti 1986), also affecting inter-hemispheric coordination of EEG-alpha oscillatory properties (Cantero et al. 2000;Koeda et al. 1995). Previous studies have reported failures Coordinates (x-y-z) are in the skull-stripped MNI-Colin27 brain anatomical space, and correspond to the voxel of maximum significance within the cluster. ...
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Our current knowledge about the anatomical substrate of impaired resting-state cortical oscillatory coupling in mild cognitive impairment is still rudimentary. Here, we show that both resting-state oscillatory coupling and its anatomical correlates clearly distinguish healthy older (HO) adults from individuals with amnestic mild cognitive impairment (aMCI). aMCI showed failures in neural-phase coupling of resting-state electroencephalographic alpha activity mostly evident between fronto-temporal and parietal regions. As oligomers of amyloid-beta (Aβ) are linked to synaptic dysfunction in Alzheimer's disease (AD), we further investigated whether plasma concentrations of these oligomers (Aβ40 and Aβ42) accounted for impaired patterns of oscillatory coupling in aMCI. Results revealed that decreased plasma Aβ42 was associated with augmented coupling of parieto-temporal regions in HO subjects, but no relationship was found in aMCI. Oscillatory coupling of frontal regions was also significantly reduced in aMCI carriers of the ε4 allele of the Apolipoprotein E (ApoE) compared to ε4 noncarriers, although neither neuroanatomical nor plasma Aβ changes accounted for this difference. However, the abnormal pattern of oscillatory coupling in aMCI was negatively related to volume of the angular gyrus, and positively related to volume of the precuneus and the splenium of the corpus callosum. Previous evidence suggests that all these regions are neuropathological targets of AD. The current study takes that scenario one step further, suggesting that this anatomical damage could be responsible for disrupted cortical oscillatory coupling in aMCI. Together, these data shed light on how the MCI status modifies anatomo-functional relationships underlying coordination of large-scale cortical systems in the resting-state.
... Alpha waves contribute to RISE in different states of vigilance. Anterior and posterior alpha patterns of the characteristic waking-alpha rhythm are seemingly interconnected via corticocortical synapses and modulated thalamic inputs [3]; this could explain the large extension of synchronization peaks in RISE with waking-alpha activity as well as the results of EEG coherence studies [32,[52][53][54]. REM-specific alpha waves might be due to a distinct pattern of corticocortical coupling [3,52], but they contribute to RISE the same way as alpha waves in waking and N1. ...
Article
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Pointwise transinformation (PTI) provides a quantitative nonlinear approach to spatiotemporal synchronization patterns of the rhythms of coupled cortical oscillators. We applied PTI to the waking and sleep EEGs of 21 healthy sleepers; we calculated the mean levels and distances of synchronized episodes and estimated the dominant frequency shift from unsynchronized to synchronized EEG segments by spectral analysis. Recurrent EEG synchronization appeared and ceased abruptly in the anterior, central, and temporal derivations; in the posterior derivations it appeared more fluctuating. This temporal dynamics of synchronization remained stable throughout all states of vigilance, while the dominant frequencies of synchronized phases changed markedly. Mean synchronization had high frontal and occipital levels and low central and midtemporal levels. Thus, a fundamental coupling pattern with recurrent increases of synchronization in the EEG ("RISE") seems to exist during the brain's resting state. The generators of RISE could be coupled corticocortical neuronal assemblies which might be modulated by subcortical structures. RISE designates the recurrence of transiently synchronized cortical microstates that are independent of specific EEG waves, the spectral content of the EEG, and especially the current state of vigilance. Therefore, it might be suited for EEG analysis in clinical situations without stable vigilance.
... These synchronizations also correlate with unconscious states, by impeding responsiveness to external stimuli (Ching et al., 2010;Hayashi et al., 2010;Buzsáki, 2006). While frontal thalamocortical regulation is thus important for reflection of neural regulation during anesthesia and unconsciousness, the occipital region is also thought to play a notable role in consciousness (Cantero et al., 2000;Lörincz et al., 2008). ...
Article
Occipital electroencephalogram (EEG) activity is known to be different from the frontal EEG during wakefulness and anesthesia. However, less is known about occipital non-linear dynamics analyzed by EEG-bicoherence, which can reflect the oscillatory features that are dependent on thalamocortical modulation. Forty patients were anesthetized using sevoflurane (1% or 3%) combined with remifentanil. Frontal and occipital EEGs were simultaneously collected, and bicoherence was analyzed before and after induction of anesthesia. Occipital awake EEGs often demonstrate a bicoherence α peak, differing from frontal awake EEGs in the absence of bicoherence growth. With 1% sevoflurane, occipital α bicoherence disappeared and frontal α bicoherence peaks appeared. Although 3% sevoflurane caused an increase in occipital δ-θ normalized power, similar to the frontal region (peak relative δ-θ power, 13.1±2.2% vs. 12.2±2.7%, p>0.05), occipital bicoherence showed no growth in any frequency area, contrasting with the frontal bicoherence spectrum with a conspicuous peak in the δ-θ area (19.8±8.9 vs. 43.6±13.8, p<0.05). The occipital bicoherence spectrum in the peri-anesthesia period is quite different from the frontal bicoherence spectrum, which is not usually obvious in the power spectrum. Nonlinear regulation of the occipital EEG is different from the frontal EEG during every stage of anesthesia.
... After SD, alpha synchronization was decreased during eyes-closed resting state. A decrease in alpha coherence has been related to drowsiness [Cantero et al., 1999[Cantero et al., , 2000]. However, one has to realize that the methodology of the studies by Cantero et al. are systematically different from ours: (1) they acquired the different vigilance states (awake-drowsiness-REM sleep) while the subjects went to sleep; this setting is different from the AAT in our study where subjects sit upright and have to fixate on a black circle on a computer screen; (2) drowsiness was specifically specified when ''slow eye movements appeared simultaneously with alpha activity,'' whereas in our current study we excluded epochs with slow eye movements; ...
Article
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Previous studies have shown that healthy anatomical as well as functional brain networks have small-world properties and become less optimal with brain disease. During sleep, the functional brain network becomes more small-world-like. Here we test the hypothesis that the functional brain network during wakefulness becomes less optimal after sleep deprivation (SD). Electroencephalography (EEG) was recorded five times a day after a night of SD and after a night of normal sleep in eight young healthy subjects, both during eyes-closed and eyes-open resting state. Overall synchronization was determined with the synchronization likelihood (SL) and the phase lag index (PLI). From these coupling strength matrices the normalized clustering coefficient C (a measurement of local clustering) and path length L (a measurement of global integration) were computed. Both measures were normalized by dividing them by their corresponding C-s and L-s values of random control networks. SD reduced alpha band C/C-s and L/L-s and theta band C/C-s during eyes-closed resting state. In contrast, SD increased gamma-band C/C-s and L/L-s during eyes-open resting state. Functional relevance of these changes in network properties was suggested by their association with sleep deprivation-induced performance deficits on a sustained attention simple reaction time task. The findings indicate that SD results in a more random network of alpha-coupling and a more ordered network of gamma-coupling. The present study shows that SD induces frequency-specific changes in the functional network topology of the brain, supporting the idea that sleep plays a role in the maintenance of an optimal functional network. Hum Brain Mapp, 2011. © 2011 Wiley Periodicals, Inc.
... These EEG band defi nitions are specifi c to humans and are different in lower mammals (Klimesch 1999). The sources, functions, and behavior of alpha and theta rhythms have been the subject of much theoretical and empirical research, but the detailed mechanics of these observed fi ndings remain far from being understood or agreed upon by researchers (Sadato et al 1998; Klimesch 1999; Liley et al 1999; Cantero et al 2000; Nunez 2000; Nunez et al 2001). Alpha and theta EEG bands are probably the most extensively researched EEG spectrums in humans, and regardless of the confusion over the physiological brain events underlying these rhythms a few phenomenological properties of alpha and theta EEG rhythms have been well established. ...
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The novel wake-promoting agent modafinil has been in use for the treatment of several sleep disorders for a few years and is now undergoing clinical trials for its use in the treatment of stimulant addiction, but its primary mechanism of action remains elusive. Previous laboratory studies have shown that modafinil has antioxidative and neuroprotective effects, which have not previously been suggested to be related to its wake-promoting effects. However, recent research indicates that free radicals may be related to sleep induction as well as cellular damage, suggesting that a common target of action may mediate modafinil's ability to oppose both of these effects. In this review we summarize and discuss previously published research on modafinil's neural, cytoprotective, and cognitive effects, and we propose possible primary biochemical targets that could underlie the effects of modafinil observed in these studies. We also suggest neurocognitive mechanisms responsible for modafinil's cognitive enhancing effects and its therapeutic potential in the treatment of stimulant addiction.
... As a final consideration, the normal transition of human sleep onset might present transient electrophysiological events preceding the first K-complex/sleep spindle. These events might be accompanied by specific transient changes in functional coupling of brain rhythmicity (Cantero et al., 2000), to be evaluated by time–frequency approaches such as wavelet– power or wavelet–coherence. In this regard, it should be remarked that the present study was focused on the ÔdirectionÕ of the functional coupling of brain rhythmicity across the human wake–sleep transition. ...
Article
The aim of this study was to assess the functional coupling between anterior and posterior areas as induced by the sleep onset process. The functional coupling was indexed by an analysis of spectral coherence and directed transfer function (DTF) from electroencephalographic (EEG) data. As it has been reported that more anterior areas first synchronize sleep EEG activity, we hypothesized a fronto-posterior direction of the cortical functional coupling during the sleep onset process. Ten normal right-handed male students slept for two-nights (one adaptation, one baseline) in the laboratory, with standard polysomnographic recordings. Spectral coherence and DTF were computed on data recorded by anterior (FzA1) and posterior (PzA1, OzA1) derivations. EEG coherence at the delta/theta band was higher during the presleep period than the sleep onset period, while EEG coherence at the alpha band was higher during the sleep onset period than the presleep period. The DTF findings indicated a prevalence of the occipital-to-frontal information flow at delta/theta and alpha bands during the presleep period and a prevalence of the frontal-to-parieto-occipital information flow at all bands during the sleep onset period. The coherent pattern of changes in EEG coherence and in DTF values at sleep onset lends further support to the notion of sleep as a local process, showing that the sleep onset process is subserved by the functional coordination of a cortical fronto-posterior network. In this network, prefrontal areas may play a leading role in the propagation of synchronizing signals conveyed at frequencies spanning delta to beta rhythms.
... Occipital regions have been considered in terms of their relation to sleep events. According to Cantero et al. (2000), the occipital structures may be the driving force for REMalpha bursts generation. Jeong et al. (2001) showed that 24 h sleep-deprived states had lower average correlation dimension values at the left occipital channel compared to the baseline values. ...
Article
The purpose of the present study was to investigate the effects of total sleep deprivation (TSD) on brain functions with an identification procedure for strongly interactive brain regions, relying on functional cluster (FC) analysis in multichannel electroencephalogram (EEG) data. EEGs from 16 electrodes in 18 healthy, right-handed, young male volunteers were recorded before TSD (after normal sleep) and after 24 h of experimentally induced sleep deprivation. We estimated cluster index to characterize joint interactions among many brain regions in order to determine if a particular FC is present or not, and if so, its anatomy. As a result, we confirmed the presence of FC and found different FC patterns in both before and after TSD. The C3 and F7 locations were outside the cluster under the TSD condition, but belonged to the cluster with C4 and F8 before the TSD condition, and the F3/F4, and O1 locations were new entries to the functional cluster during sustained wakefulness. These results indicate that the neuronal activities of the C3 and F7 location are functionally unrelated, whereas the F3/F4 locations are functionally involved with the C4, F8, and O1 locations after 24 h TSD. Our results suggest that FC changes with elapsed awake time and reflects the change of brain function due to TSD. This paper shows the existence of FC both before and after TSD, and the anatomy of each FC is different. So FC analysis would be a potential tool to investigate the simultaneous neuronal activity of human EEGs.
... The concurrent increase of low-frequency oscillations and decrease of alpha waves in frontal cortex was claimed to correlate with successful transfer of information between working memory and long-term memory systems [Sauseng et al., 2002]. Further, interfrontal alpha coherence could also decrease with the weakening of internal attentive mechanisms [Cantero et al., 1999[Cantero et al., , 2000. Additionally, this interfrontal alpha desynchronization in the artists is likely to be affected by the frontal eye field (crucial for gaze control) because non-artists made more inconsistent and irregular scans of the visual fields than artists did while looking at paintings [Nordine et al., 1993] or drawing portraits [Miall and Tchalenko, 2001]. ...
Article
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Our primary question was to learn whether mentally composing drawings of their own choice produce different brain electric features in artists and laymen. To this purpose, we studied multichannel electroencephalograph (EEG) signals from two broad groups (all participants were females): artists (professionally trained in visual arts) and non-artists (without any training in art). To assess the underlying synchronization, which is assumed to be the platform for general cognitive integration between different cortical regions, three measures inspired by nonlinear dynamical system theory were applied as follows: (1) index based on generalized synchronization; (2) index based on mean phase coherence; and (3) index of phase synchrony based on entropy. Results consistent over all three measures were as follows: comparing the tasks to rest, the artists showed significantly stronger short- and long-range delta band synchronization, whereas the non-artists showed enhancement in short-range beta and gamma band synchronization primarily in frontal regions; comparing the two groups during the tasks, the artists showed significantly stronger delta band synchronization and alpha band desynchronization than did the non-artists. Strong right hemispheric dominance in terms of synchronization was found in the artists. In artists, the higher synchrony in the low-frequency band is possibly due to the involvement of a more advanced long-term visual art memory and to extensive top-down processing. The results demonstrate that in artists, patterns of functional cooperation between cortical regions during mental creation of drawings were significantly different from those in non-artists.
... It has been proposed to be an intrinsic property of the brain involved in broader functions such as cognition and consciousness (Crick, 1994;Llinás and Paré, 1996;Singer, 1996). Analyses of coherent activity during sleep have revealed that spectral power is not enough to account for differences between sleep and wakefulness; several studies have demonstrated significant differences in inter-and intrahemispheric coherent activity between wakefulness (W), stage 2, stage 4 and REM sleep (Corsi-Cabrera et al., 1987, 1996, 2003Guevara et al., 1995;Wright et al., 1995;Morikawa et al., 1997;Achermann and Borbély, 1998;Cantero et al., 2000;Tanaka et al., 2000;Pérez-Garci et al., 2001); however, the differences between stage 1 and REM sleep, as already mentioned, have not been thoroughly investigated. The characterization of EEG activity and determination of differences between these two sleep stages may contribute to the understanding of REM sleep physiology and the process of falling asleep; therefore, in this study we analyzed spectral power and spectral correlation during stage 1 from the first non-REM sleep episode of the night and compared it with W and the first REM sleep episode. ...
Article
The objective of this work is to determine differences in spectral power and coherent activity between stage 1 (S1) and REM sleep. The EEG activity of the two sleep stages is almost indistinguishable by visual inspection. Although many efforts have been directed toward understanding the process of falling asleep, little is known about differences in EEG activity between stage 1 (S1) and REM sleep. Polysomnography of 8 healthy young adults from S1, REM sleep and wakefulness was recorded. Spectral power and spectral correlation were obtained for 1-50 Hz. Stage 1 was distinguished (ANOVAs) from REM sleep by lower power in 1-9 Hz, higher power in alpha, beta and gamma, lower interhemispheric correlation in 1-8 Hz and gamma, and higher right correlation in 30-50 Hz. It differed from wakefulness by lower power in 9-50 Hz, but not in 1-8 Hz, or in inter- and intrahemispheric correlation. EEG differences between S1 and REM sleep reside not only in changes in power but also in coherent activity. The different behavior of slow and fast frequencies suggests two different mechanisms involved in the gate into sleep, one implicated in promoting sleep, the thalamo-cortical oscillator mode and the other in reducing alertness involving activation mechanisms. Stage 1 is a mixed state, alertness is already reduced but sleep-promoting mechanisms are not yet fully installed. The EEG differences between these two sleep stages contribute to the understanding of REM sleep and S1 physiology and may be relevant for understanding disorders in falling asleep.
... Nunez and Katznelson (1981) found that a slower alpha component was generated in the anterior brain regions, while a faster one in the posterior regions. An interaction between anterior and posterior cortical circuits has been consistently supported by EEG coherence studies (Cantero et al., 1999(Cantero et al., , 2000Srinivasan, 1999;Thatcher et al., 1986). This functional relationship seems to be anatomically supported by the long fronto-occipital fasciculi (Braitenberg, 1978;Thatcher et al., 1986). ...
Article
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Recent studies suggest brain oscillations as a mechanism for cerebral integration. Such integration can exist across a number of functional domains, with different frequency rhythms associated with each domain. Here, evidence is summarized which shows that delta oscillations depend on activity of motivational systems and participate in salience detection. Theta oscillations are involved in memory and emotional regulation. Alpha oscillations participate in inhibitory processes which contribute to a variety of cognitive operations such as attention and memory. The importance of inhibitory functions associated with alpha oscillations increases during the course of evolution. In ontogenesis, these functions develop later and may be more sensitive to a variety of detrimental environmental influences. In a number of developmental stages and pathological conditions, a deficient alpha and/or increased slow-wave activity are associated with cognitive deficits and a lack of inhibitory control. It is shown that slow-wave and alpha oscillations are reciprocally related to each other. This reciprocal relationship may reflect an inhibitory control over motivational and emotional drives which is implemented by the prefrontal cortex.
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Biological sex profoundly shapes brain function, yet its precise influence on neural oscillations was poorly understood. Despite decades of research, studies investigating sex-based variations in electroencephalographic (EEG) signals have yielded inconsistent findings that obstructs what may be a potentially crucial source of inter-individual variability in brain function. To address this, we analyzed five publicly available resting-state datasets, comprising EEG data (n=445) and iEEG data (n=103). Our results revealed striking age-dependent sex differences: older adults (30-80 years) exhibited robust sex differences, with males showing heightened low alpha (8-9 Hz) activity in temporal regions and attenuated low beta (16-20 Hz) oscillations in parietal-occipital areas compared to females. Intriguingly, these sex-specific patterns were absent in younger adults (20-30 years), suggesting a complex interplay between sex and aging in shaping brain dynamics. Furthermore, we identified consistent sex-related activity in the precentral gyrus with the results of scalp EEG, potentially driving the observed scalp EEG differences. This multi-level analysis allowed us to bridge the gap between cortical and scalp- level observations, providing a more comprehensive picture of sex-related neural dynamics. To further investigate the functional implications of these oscillatory differences, we conducted correlation analyses to uncover significant associations between sex-specific oscillatory patterns and several lifestyle factors (behavioral and anthropometric measures) in older adults. This comprehensive investigation demonstrates the complex interplay between sex, age, and neural oscillations, revealing the variability in brain dynamics. And our findings highlight the importance of careful demographic consideration in EEG research design to ensure fairness in capturing the full spectrum of neurophysiological diversity. Significance statement The influence of biological sex and age on neural oscillations had been a long- standing, unresolved question in EEG research, largely unaddressed due to limited sample sizes and simplistic demographic matching. Our study leverages large-scale, open datasets to tackle this issue, analyzing hundreds of participants across five datasets. Our findings demonstrate substantial sex- based differences in even resting-state EEG baselines, particularly in low alpha and low beta bands, uncovering a significant source of variability in neural activity. By connecting these sex and age-related variations to potential neural circuit mechanisms and lifestyle factors, our findings highlight the importance of careful demographic consideration in EEG research design in EEG experimental design to accurately capture the rich spectrum of neurophysiological variability across the lifespan.
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Dreaming is a universal human mental state characterized by hallucinatory imagery congruent with a confabulated, temporally ordered, storylike experience. As in waking consciousness, such experiences in both rapid eye movement (REM) and non-REM (NREM) sleep are associated with activation of forebrain structures by ascending arousal systems of the brainstem, hypothalamus, and basal forebrain. Differences between forebrain activation patterns in waking and REM sleep suggest bases for their phenomenological differences. In REM compared to waking, there is relatively more activation of the brain's limbic system and relatively less activity of cortical areas involved in higher-level cognition. REM sleep dreaming may activate anterior and midline portions of the brain's "default mode," a network of structures that supports self-related cognition when the brain is unoccupied by external stimuli. A variety of neurochemical systems can influence dreaming, including the neuromodulators acetylcholine, dopamine, serotonin, and norepinephrine. Dream phenomena are strikingly similar to neuropsychiatric symptom complexes such as complex hallucinosis and spontaneous confabulation as well as delirium and misidentification syndromes. A descriptive model of dream generation links sleep imaging studies with known regional specialization in waking neurocognitive functions.
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Individual differences in attention biases for motivationally significant stimuli have been reported in clinical and normative populations. Few studies, however, have attempted to examine potential biological mechanisms underlying differences in the cognitive processing of emotional stimuli. The present study examined the extent to which two well-validated psychophysiological vulnerability markers of affective style [i.e., frontal electroencephalogram (EEG) asymmetry and cardiac vagal tone] predicted biased attention toward rapid presentations (approximately 250 ms) of angry and happy facial expressions. We found that right frontal EEG asymmetry and low cardiac vagal tone, taken together, predicted approximately 37% of the variability in attentional vigilance for angry faces. Frontal EEG asymmetry and cardiac vagal tone did not predict attention for happy faces, independently of each other. Our results provide preliminary evidence that two well established psychophysiological indicators of affective style bias early processing of motivationally salient stimuli.
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El estudio de los ritmos cerebrales puede ser abordado mediante el análisis de sus propiedades electrofisiológicas usando técnicas de EEG cuantitativo. En aquellos casos donde una misma actividad aparece espontáneamente en diferentes estados de activación cerebral, el estudio de estas propiedades ayudaría a establecer diferencias funcionales asociadas a cada uno de estos estados. El presente trabajo revisa aquellos estudios que han determinado las propiedades electrofisiológicas de las diferentes variantes normales de alfa que aparecen en el continuo vigilia-sueño, más concretamente en vigilia relajada, somnolencia y durante la fase REM del sueño. Los resultados indican que cada variante normal de alfa, aun mostrando una distribución topográfica similar en cada uno de los estados cerebrales, presenta características diferenciales atendiendo a su composición espectral, relaciones funcionales entre regiones corticales, y micro-estados cerebrales subyacentes. De acuerdo con estos hallazgos, cada variante de alfa desempeñaría diferentes funciones cerebrales. El ritmo alfa de vigilia parece ser el resultado de una máxima sincronización neuronal como consecuencia de la ausencia de procesamiento sensorial, mientras que la presencia de actividad alfa durante la somnolencia estaría más asociada al procesamiento de las imágenes hipnagógicas que ocurren al comienzo del sueño. Los brotes de alfa de REM, sin embargo, constituirían un punto de contacto entre el cerebro dormido y el ambiente externo. Esta caracterización electrofisiológica encuentra su campo de aplicación más directo en el diseño de algoritmos para clasificar el sueño de forma automática, así como en el diagnóstico y evaluación de determinadas patologías donde pudieran verse afectados los mecanismos cerebrales de generación de esta actividad a lo largo del continuo vigilia-sueño.
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Evidence suggests that an important contribution of spectral power in the alpha range is characteristic of human REM sleep. This contribution is, in part, due to the appearance of well-defined bursts of alpha activity not associated with arousals during both tonic and phasic REM fragments. The present study aims at determining if the REM-alpha bursts constitute a different alpha variant from the REM background alpha activity. Since previous findings showed a selective suppression of background alpha activity over occipital regions during phasic REM fragments and, on the other hand, the density of alpha bursts seem to be independent of the presence or absence of rapid eye movements, one expects to find the same spectral power contribution of alpha bursts in tonic and phasic REM fragments. The results indicated that REM-alpha bursts showed a similar power contribution and topographic distribution (maximum energy over occipital regions) both in tonic and phasic REM fragments. This suggests that two variants of alpha activity with different functional roles are present during the human REM sleep: i) background alpha activity, modulated over occipital regions by the presence of rapid eye movements, which may be an electrophysiological correlate of the visual dream contents; and ii) REM-alpha bursts, independent of the presence of rapid eye movements, which could be facilitating the connection between the dreaming brain and the external world, working as a micro-arousal in this brain state.
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Cortical oscillations in the range of alpha activity (8-13 Hz) are one of the fundamental electrophysiological phenomena of the human electroencephalogram (EEG). Evidence from quantitative EEG data has shown that their electrophysiological features, cortical generation mechanisms, and therefore, their functional correlates vary along the sleep-wake continuum. Specifically, spectral microstructure and EEG coherence levels between anterior and posterior cortical regions permit to differentiate among alpha activity spontaneously appearing in relaxed wakefulness with eyes closed, drowsiness period, and REM sleep, by reflecting distinct properties of neural networks involved in its cortical generation as well as a different interplay between cortical generators, respectively. Besides, the dissimilar spatiotemporal features of brain electrical microstates within the alpha range reveals a different geometry of active neural structures underlying each alpha variant or, simply, changes in the stability level of neural networks during each brain state. Studies reviewed in this paper support the hypothesis that two different alpha variants occur during human REM sleep: 'background responsive alpha activity', blocked over occipital regions when rapid eye movements are present, and 'REM-alpha bursts', non modulated by the alteration of tonic and phasic periods. Altogether, evidence suggests that electrophysiological features of human cortical oscillations in the alpha frequency range vary across different behavioural states, as well as within state, reflecting different cerebral phenomena with probably dissimilar functional meaning.
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Only a small number of studies have used quantitative electroencephalography (qEEG) in research of the post-traumatic stress disorder (PTSD). The results are not consistent. The aim of the present investigation was to compare qEEG in combat veterans with and without PTSD. The hypothesis is that differences among qEEG characteristics will be found regarding the presence/absence of PTSD. Seventy-nine combat veterans with PTSD comprised the experimental group and 37 veterans without PTSD were included as controls. After the informed consent, they were investigated by the resting EEG recordings. The results demonstrate that PTSD veterans had decreased alpha power and increased beta power. These results suggest an altered neurobiology in PTSD. Various explanations have been offered for alpha activity decrease observed in PTSD veterans. Increased beta rhythm may play a role as a potential marker in differentiating subtypes of PTSD.
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To clarify the physiological significance of task-related change of the regional electroencephalogram (EEG) rhythm, we quantitatively evaluated the correlation between regional cerebral blood flow (rCBF) and EEG power. Eight subjects underwent H2 15O positron emission tomography scans simultaneously with EEG recording during the following tasks: rest condition with eyes closed and open, self-paced movements of the right and left thumb and right ankle. EEG signals were recorded from the occipital and bilateral sensorimotor areas. Cortical activation associated with EEG rhythm generation was studied by the correlation between rCBF and EEG power. There were significant negative correlations between the sensorimotor EEG rhythm at 10-20 Hz on each side and the ipsilateral sensorimotor rCBF and between the occipital EEG rhythm at 10-20 Hz and the occipital rCBF. The occipital EEG rhythm showed a positive correlation with the bilateral medial prefrontal rCBF, while the right sensorimotor EEG rhythm showed a positive correlation with the left prefrontal rCBF. In conclusion, decrease in the regional EEG rhythm at 10-20 Hz might represent the neuronal activation of the cortex underlying the electrodes, at least for the visual and sensorimotor areas. The neural network including the prefrontal cortex could play an important role to generate the EEG rhythm.
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Clinical and neuropathological evaluation of elderly subjects with dementia has traditionally concentrated upon the focal distribution of brain disease, ignoring changes in the complex connections that link brain areas and that are crucial for cognition. We examined subjects with the two most common forms of dementia in the elderly (dementia of the Alzheimer type or DAT, and multi-infarct dementia or MID); and used electroencephalographic (EEG) coherence to examine the effects of these illnesses on the functional connections between brain areas. We studied coherence between brain areas known to be linked by two different types of connections: (i) dense narrow bands of long corticocortical fibres; (ii) broad complex networks of corticocortical and corticosubcortical fibres. Areas that were linked by dense narrow bands of long corticocortical fibres showed greatly diminished coherence in subjects with DAT; among MID subjects, this coherence was not significantly affected. Areas that were linked by broad connective networks showed the largest decreases in coherence among MID subjects. These findings are consistent with neuropathological evidence that Alzheimer's disease is a neocortical 'disconnection syndrome' in which there is a loss of structural and functional integrity of long corticocortical tracts. The findings further suggest that the vascular disease of MID most prominently affects broad fibre networks that may be more vulnerable to diffuse subcortical vascular damage. A ratio of coherence from complex corticocortical-corticosubcortical networks divided by coherence from long corticocortical tracts correctly classified 76% of subjects into DAT and MID categories. Overall, these results indicate that EEG coherence detects basic pathophysiological differences between subjects with DAT and MID, and that these differences may be clinically useful.
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EEG coherence analysis was used to study aspects of the synchronisation of electrical processes in the left and right cerebral hemispheres of right-handed and left-handed healthy subjects in a state of calm wakefulness. Right-handed subjects showed a greater coherence in the left hemisphere and left-handed subjects in the right hemisphere. There were also differences between right-handed and left-handed subjects in the regional profiles of interhemispheric asymmetry and in the interhemispheric asymmetry of individual spectral bands. These differences may reflect variations in the involvement of cortical and subcortical cerebral structures in the formation of the hemispheric specificity. Changes in interhemispheric coherence with the onset of drowsiness were also observed. This suggests that changes in the interconnections of neural networks are also involved in changes in arousal. Certain characteristic regional interhemispheric asymmetry patterns and asymmetries in the spectral bands appear to be necessary for normal human brain function.
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The development of the cerebral hemispheres was assessed by using measures of electroencephalographic coherence and phase in 577 children ranging in age from 2 months to early adulthood. Two categories of age-dependent change in electroencephalographic coherence and phase were noted: continuous growth processes that were described best by an exponential growth function, and discrete growth spurts that appeared in specific anatomical locations at specific postnatal periods. The left and right hemispheres developed at different rates and with different postnatal onset times with the timing of growth spurts overlapping the timing of the major developmental stages described by Piaget.
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Periventricular white matter hyperintensities (PVHs) seen on T2 weighted MRI studies are common in elderly people and often represent demyelination of fibres. Damage to these fibres could lead to functional disconnection between brain regions. Electroencephalographic coherence, a measure of shared electrical activity between regions, was examined to determine if there was evidence for such disconnection. Twenty two subjects with clinically diagnosed dementia of the Alzheimer's type, 16 with multi-infarct dementia, and 18 normal controls were studied. It was hypothesised that coherence between areas presumably linked by fibres that traverse the periventricular region would be decreased in subjects with PVHs, and that PVHs would have a stronger association with decreased coherence than clinical diagnosis. It was also hypothesised that coherence between areas presumably connected by long corticocortical tracts that are neuroanatomically separated from the ventricles would be low in patients with Alzheimer's disease because of pyramidal cell death in this group, but would not be affected by the presence of PVHs. Patients with PVHs in fact had lower coherence than those without PVHs in the pre-Rolandic and post-Rolandic areas, where connecting fibres traverse the periventricular region. There was no effect of PVHs, however, on coherence between areas separated by the Rolandic fissure that were connected by long corticocortical tracts; this coherence was lowest among the patients with Alzheimer's disease. These patterns of association suggest that coherence may detect different types of neurophysiological "disconnection," and may be sensitive to selective damage to different fibre pathways.
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Topographic aspects of EEG development of normal children and adolescents from 6 to 17 years are investigated with respect to various spectral parameters. The topographic distribution of spectral band power does not change between hemispheres across age. Changes take place, however, in the antero-posterior dimension. For the bands theta, alpha1 and alpha2 (and less so for delta) maturation starts at posterior derivations and ends at anterior derivations. For the band beta2 (and to some extent also for beta1), development progresses from Cz to Pz and further to occipital, lateral, central and frontal derivations. Principal component analysis (PCA) leads to a more parsimonious and better interpretable description of broad-band power and of its topographic distribution. Broad-band coherences increase with age, though to a modest degree. The different magnitudes of coherence between different regions can be largely accounted for by the interelectrode distances. Coherences, too, can be described in a more parsimonious and better interpretable way via PCA. The 3 components extracted reflect firstly the overall level of coherence, secondly the coherences of the occipital regions with all other regions and thirdly antero-posterior versus left-right coherences.
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Source determination of alpha activity was studied using the relative power contribution analysis (RPCA) method which allows determination of the relative contributions of different areas to the power of a certain area at different frequencies. In 20 normal subjects, EEGs were recorded from F3, F4, C3, C4, P3, P4, O1 and O2, each referenced to a linked ear. An 8-dimensional autoregressive model was fitted to the EEGs of 10.24 sec. Based on the model, RPCA was performed. For each area, alpha activity was divided into two parts: one originating in its own area (endogenous) and another in the other areas (exogenous). Endogenous alpha activity increased as the area was more posterior. In the anterior regions (frontal and central), endogenous alpha power (power of endogenous alpha activity) was small, while exogenous alpha power was large. In the posterior regions (parietal and occipital), the amount of endogenous alpha power did not differ markedly from that of exogenous alpha power. The posterior regions, which generate more endogenous alpha activity, can be considered to play a dominant role in alpha generating mechanisms. In some subjects, alpha generators with a different frequency from that of the occipital areas were observed.
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EEG coherence was computed from 19 scalp locations from 189 children ranging in age from 5 to 16 years. Tests of spatial homogeneity of EEG coherence were conducted by comparing EEG coherence as a function of different interelectrode distances in the anterior-to-posterior versus posterior-to-anterior directions. Highly significant inhomogeneities were observed since greater coherence was present in the anterior-to-posterior direction than in the posterior-to-anterior directions. Greater coherence was also present in frontal derivations than in posterior derivations and from the right hemisphere in comparison to the left hemisphere. These data indicate that at least two separate sources of EEG coherence were present (1) coherence produced through the action of short length axonal connections, and (2) coherence produced through the action of long distance connections. Measures of phase delays as a function of interelectrode distance supported the development of a 'two-compartmental' model of EEG coherence in which different features of coherence are produced by different length fiber systems. Based on this model a number of hypotheses were developed to explain differences in connectivity between left and right hemispheres and frontal versus occipital cortex.
Article
Using auto- and cross-spectral analyses on data of 3 normal adult subjects, two components of rhythmic alpha activity were distinguished with respect to their spatial distribution and spatial relationships on the scalp. Derivations from 21 scalp points vs. linked ears were analyzed. The alpha activity with power maxima in the bilateral occipital areas (component A) showed high coherence with activity in the anterior areas and somewhat lower coherence with activity in the central/parietal areas. The other component (B) appeared dominantly in the central areas, showing extremely low values of coherence between the anterior and posterior regions, and an unstable phase relation among recording points. Components A and B appear to correspond to the 'generalized' and 'localized' alpha components described earlier. It is suggested that these two components account for the major properties of the rhythmic alpha activity.
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The topographic EEG features of drowsiness and sleep onset are much less well documented than are their temporal aspects. A commercial topographical mapping system was used to assess the main EEG features employing all 19 international 10/20 system electrode sites referenced to linked ears during wakefulness, stages 1A and 1B drowsiness, stage 2 sleep, and sleep onset REM periods in 19 patients. All patients had been referred for a diagnostic EEG or a Multiple Sleep Latency Test and had essentially normal EEGs. Anterior alpha of drowsiness seldom represented frontal spread of the occipital alpha rhythm but usually was a distinct activity of apparent separate origin. Theta activities of drowsiness were maximum at CZ and FZ. Vertex sharp waves and sawtooth waves of rapid eye movement (REM) sleep had similar fields maximum at the midline with a steep decrease laterally. Isolated anterior mainly negative waves were identified. Sleep spindles were usually maximal in fronto central, occasionally centro parietal, or even parietal areas.
Article
Inter- and intrahemispheric EEG coherence was studied in 4 subjects with agenesis of the corpus callosum (ACC) and in 4 matched controls through different states of the sleep/wakefulness cycle. Interhemispheric coherence was calculated between homologous prefrontal, frontal, central, parietal and occipital electrode pairs whereas intrahemispheric coherence was calculated between all adjacent, unihemispheric electrode pairs. EEG samples were recorded from stage 2, stages 3 + 4 and stage REM sleep and the eyes closed waking state. Interhemispheric coherence measures indicated lower values for ACC subjects than for control subjects for most brain regions; the occipital cortex was least affected. These results further validate the interhemispheric coherence function as a measure of activity in the corpus callosum and suggest that occipital measures may index activity localized in the posterior commissure. Intrahemispheric coherence measures indicated very few differences between the two groups, a result consistent with the suggestion that there is no specialized intrahemispheric compensation in ACC.
Article
Resting EEG interhemispheric and intrahemispheric coherences (ICoh and HCoh) in the theta, alpha and beta bands were studied in 7 patients with agenesis of the corpus callosum (5 children, aged 10-14 years, and 2 adults) and 2 groups of sex- and age-matched normal children and adults (42 subjects). In patients the ICohs (F3/F4, C3/C4, P3/P4, O1/O2) were lower than in the normal sample. The ICoh decrease, corresponding with the completeness of commissural agenesis, showed the essential role of the corpus callosum in interhemispheric EEG synchronization. A remarkable new fact was found, namely lower right hemisphere HCoh in the acallosal patients in comparison to the normals, suggesting reduced connectivity of the right hemisphere. It is assumed that the deviant HCoh patterns in the patients, most pronounced in the beta band, are indicative of compensatory left hemisphere mechanisms, accounting for a specific brain plasticity phenomenon in acallosal subjects.
Article
The present study was conducted to examine inter- and intrahemispheric EEG coherence in 14 healthy, right-handed adults during wakefulness and light drowsiness as assessed by eye movement and EEG activity. Interhemispheric coherence was significantly lower during light drowsiness than during wakefulness for O1-O2 in the alpha-1 band and for F3-F4 in the beta-1 band. Intrahemispheric EEG coherence was significantly higher during light drowsiness for C4-O2 in the theta-1 and beta-1 bands. These findings indicate that light drowsiness can alter both inter- and intrahemispheric EEG coherence when compared with wakefulness, suggesting that cerebral functional organization changes during light drowsiness. It is important, therefore, to control arousal level of subjects in future studies dealing with the relationship between EEG coherence and various pathological conditions.
Article
In a study with 10 young, healthy subjects, alpha activities were studied in three different arousal states: eyes closed in relaxed wakefulness (EC), drowsiness (DR), and REM sleep. The alpha band was divided into three subdivisions (slow, middle, and fast) which were analyzed separately for each state. The results showed a different spectral composition of alpha band according to the physiological state of the subject. Slow alpha seemed to be independent of the arousal state, whereas middle alpha showed a difference between REM and the other states. The fast-alpha subdivision appears mainly as a waking EEG component because of the increased power displayed only in wakefulness and lower and highly stable values for DR and REM. Scalp distribution of alpha activity was slightly different in each state: from occipital to central regions in EC, this topography was extended to fronto-polar areas in DR, with a contribution from occipital to frontal regions in REM sleep. These results provide evidence for an alpha power modulation and a different scalp distribution according to the cerebral arousal state.
Article
Spontaneous alpha activity clearly present in relaxed wakefulness with closed eyes, drowsiness period at sleep onset, and REM sleep was studied with spatial segmentation methods in order to determine if the brain activation state would be modulating the alpha spatial microstates composition and duration. These methods of spatial segmentation show some advantages: i) they extract topographic descriptors independent of the chosen reference (reference-free methods), and ii) they achieve spatial data reduction that are more data-driven than dipole source analysis. The results obtained with this study revealed that alpha activity presented a different spatio-temporal pattern of brain electric fields in each arousal state used in this study. These differences were reflected in a) the mean duration of alpha microstates (longer in relaxed wakefulness than in drowsy period and REM sleep), b) the number of brain microstates contained in one second (drowsiness showed more different microstates than did relaxed wakefulness and REM state), and c) the number of different classes (more abundant in drowsiness than in the rest of brain states). If we assume that longer segments of stable brain activity imply a lesser amount of different information to process (as reflected by a higher stability of the brain generator), whereas shorter segments imply a higher number of brain microstates caused by more different steps of information processing, it is possible that the alpha activity appearing in the sleep onset period could be indexing the hypnagogic imagery self-generated by the sleeping brain, and a phasic event in the case of REM sleep. Probably, REM-alpha bursts are associated with a brain microstate change (such as sleep spindles), as demonstrated by its phasic intrusion in a desynchronized background of brain activity. On the other hand, alpha rhythm could be the "baseline" of brain activity when the sensory inputs are minimum and the state is relaxed wakefulness.
Article
The maturation of the neocortex during childhood and adolescence involves dramatic increases in white-matter volume. EEG recordings from children and adults were examined to determine whether there are associated changes in spatial properties of dynamic processes in the neocortex. Spontaneous eyes-closed and eyes-open EEG were recorded at 128 electrodes in 20 children aged 6-11 years and 23 adults aged 18-23 years. The surface Laplacian algorithm was applied to improve the spatial resolution of each electrode. Power and coherence were used to characterize the spatial structure of the alpha rhythm. A stochastic field model was used to eliminate coherences that are inflated due to volume conduction. In adults, the alpha rhythm is characterized by very high coherence between distant electrodes. The children demonstrated reduced anterior power and coherence between anterior and posterior electrodes at the peak alpha frequency in comparison to the adults. The Laplacian alpha rhythm demonstrated much higher power in the children at both anterior and posterior electrodes, but was weakly correlated between electrodes. The maturation of neocortex in late childhood involves increased global correlation by long-range corticocortical connections. The local correlation that contributes power to each electrode, independent of other electrodes, is reduced as the global correlation increases.
Article
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.
Article
Spectral power contribution in the range of alpha activity is a well-known electrophysiological feature of human REM sleep, which could be caused by the spontaneous bursts of alpha activity not associated with arousals that usually appear during this brain state. The present study was undertaken to determine the density of alpha bursts during tonic and phasic (oculomotor) REM periods for each REM cycle. In addition, this phasic brain event was also described from a spectral and topographical point of view. Ten healthy right-handed subjects (5 females) aged 19-25 years (mean 22.9 years, SD 2.6) participated in the present study. Each selected subject filled in a daily sleep log for 2 weeks before the experimental night to provide information on all 3 salient aspects of sleep pattern, sleep experience and sleep effects. The results revealed that transient REM-alpha bursts, which lasted about 3 s and were accompanied by no increase in the EMG amplitude, appeared in all subjects who participated in this study, showing a higher density in the third and fourth REM cycle during phasic in comparison with tonic periods. The bandpass filtered signals showed the highest spectral contribution for the slower alpha components (8-9 Hz), the occipital scalp regions being the main generator source of this brain activity. The authors hypothesize that REM-alpha bursts may work as micro-arousals (or incomplete arousals) facilitating the brain connection with the external world in this cerebral state, whereas REM-alpha arousals - usually longer and accompanied by changes in the EMG amplitude - generate a shift of brain state associated with sleep fragmentation (complete arousal).
The EEG of drowsiness
  • J Santamaria
  • Chiappa
  • Kh
Santamaria J, Chiappa KH. The EEG of drowsiness. New York: De-mos, 1987.