Functional interrelation of the brain structures of the cat during the generation of rhythmic activity. I. The frequency characteristics of the electroencephalogram

The similarity of frequency parameters of electroencephalograms (EEG) recorded from visual, associative and sensorimotor cortical area, caudate nucleus and several thalamic nuclei have been analysed using the period analysis of EEG and cluster analysis of data obtained to clarify the functional interrelationships between these parts of the brain during generation of rhythmic activity of different types. Functional interrelationships between brain structures in freely moving cats during the states of drowsiness and slow-wave sleep have been shown to differ from "classical" thalamo-cortical pacemaker relations.     

Alpha-bursts and K-complex: phasic activation pattern during spontaneous recovery of correct psychomotor performance at difference stages of drowsiness

It is known that phasic activation processes reveal themselves by different electrophysiological patterns depending on the sleep depth. Alpha bursts are an electrophysiological manifestation of arousal at the initial stage of sleep, whereas at the II stage K-complex becomes the main arousal pattern. We have shown earlier that during light drowsiness spontaneous recovery of correct psychomotor test performance (after an error) by a sitting subject is accompanied by EEG alpha bursts. The aim of this work was to study the EEG phasic activation pattern at deeper drowsiness during test performance by a subject in a lying position. Subjects had to press sensitive button in a lying position with closed eyes with self-paced oral counting of pressings. The experiment lasted for 40 min; EEG, EOG, and button pressing were recorded. It was shown that recovery of correct performance after errors at deeper drowsiness was accompanied by two types of EEG phasic activation patterns (PAP-1 and PAP-2). The alpha frequency component was always present in both PAP-1 and PAP-2. PAP-1 were observed at early stages of drowsiness and consisted of high-amplitude alpha bursts and EEG activity of higher frequency. PAP-2 were recorded at deeper stages and consisted of K-complexes with superposition of PAP-1. At first (medium level of drowsiness) the alpha bursts were superposed on the late slow K-complex components. With further deepening of drowsiness the early fast components of K-complex were also observed. The early appearance of K-complex during test performance at drowsiness seems to be associated with the urgent run of brain arousal systems, which at spontaneous falling asleep are in operation at the II sleep stage.     

Scale-Free Music of the Brain

Background

There is growing interest in the relation between the brain and music. The appealing similarity between brainwaves and the rhythms of music has motivated many scientists to seek a connection between them. A variety of transferring rules has been utilized to convert the brainwaves into music; and most of them are mainly based on spectra feature of EEG.

Methodology/Principal Findings

In this study, audibly recognizable scale-free music was deduced from individual Electroencephalogram (EEG) waveforms. The translation rules include the direct mapping from the period of an EEG waveform to the duration of a note, the logarithmic mapping of the change of average power of EEG to music intensity according to the Fechner''s law, and a scale-free based mapping from the amplitude of EEG to music pitch according to the power law. To show the actual effect, we applied the deduced sonification rules to EEG segments recorded during rapid-eye movement sleep (REM) and slow-wave sleep (SWS). The resulting music is vivid and different between the two mental states; the melody during REM sleep sounds fast and lively, whereas that in SWS sleep is slow and tranquil. 60 volunteers evaluated 25 music pieces, 10 from REM, 10 from SWS and 5 from white noise (WN), 74.3% experienced a happy emotion from REM and felt boring and drowsy when listening to SWS, and the average accuracy for all the music pieces identification is 86.8%(κ = 0.800, P<0.001). We also applied the method to the EEG data from eyes closed, eyes open and epileptic EEG, and the results showed these mental states can be identified by listeners.

Conclusions/Significance

The sonification rules may identify the mental states of the brain, which provide a real-time strategy for monitoring brain activities and are potentially useful to neurofeedback therapy.     

Exploring Age-Related Changes in Dynamical Non-Stationarity in Electroencephalographic Signals during Early Adolescence

Dynamics of brain signals such as electroencephalogram (EEG) can be characterized as a sequence of quasi-stable patterns. Such patterns in the brain signals can be associated with coordinated neural oscillations, which can be modeled by non-linear systems. Further, these patterns can be quantified through dynamical non-stationarity based on detection of qualitative changes in the state of the systems underlying the observed brain signals. This study explored age-related changes in dynamical non-stationarity of the brain signals recorded at rest, longitudinally with 128-channel EEG during early adolescence (10 to 13 years of age, 56 participants). Dynamical non-stationarity was analyzed based on segmentation of the time series with subsequent grouping of the segments into clusters with similar dynamics. Age-related changes in dynamical non-stationarity were described in terms of the number of stationary states and the duration of the stationary segments. We found that the EEG signal became more non-stationary with age. Specifically, the number of states increased whereas the mean duration of the stationary segment decreased with age. These two effects had global and parieto-occipital distribution, respectively, with the later effect being most dominant in the alpha (around 10 Hz) frequency band.     

Changes in EEG power, acoustic evoked potentials and heart rate after mildly arousing non-acoustic priming stimuli in carp (Cyprinus carpio).

1. Changes in EEG power spectrum of carp to a priming non-acoustic stimulus followed by acoustic clicks were compared to those due to acoustic clicks delivered alone. Recordings were made from the telencephalon, midbrain and medulla. Acoustic evoked potentials (AEPs) to the clicks were also recorded. 2. EEG power changes to non-acoustic stimuli occurred over the whole 1-40 Hz frequency range and were regionally specific and consistent. 3. The changes in the EEG midfrequency 12-24 Hz power spectrum to non-acoustic stimuli were significantly correlated with changes in the AEP to subsequent clicks. An elevated medullary AEP amplitude and reduced duration were correlated with increased medullary EEG power and increased midbrain AEP duration. 4. Telencephalic EEG power changes were inversely related to changes in medullary and midbrain AEP amplitude.     

Modeling EEG fractal dimension changes in wake and drowsy states in humans—a preliminary study

Aim of this preliminary study was to examine and compare topographic distribution of Higuchi's fractal dimension (FD, measure of signal complexity) of EEG signals between states of relaxed wakefulness and drowsiness, as well as their FD differences. The experiments were performed on 10 healthy individuals using a fourteen-channel montage. An explanation is offered on the causes of the detected FD changes. FD values of 60 s records belonging to wake (Hori's stage 1) and drowsy (Hori's stages 2-4) states were calculated for each channel and each subject. In 136 out of 140 epochs an increase in FD was obtained. Relationship between signal FD and its relative alpha amplitude was mathematically modeled and we quantitatively demonstrated that the increase in FD was predominantly due to a reduction in alpha activity. The model was generalized to include other EEG oscillations. By averaging FD values for each channel across 10 subjects, four clusters (O2O1; T6P4T5P3; C3F3F4C4F8F7; T4T3) for the wake and two clusters (O2O1P3T6P4T5; C3C4F4F3F8T4T3F7) for the drowsy state were statistically verified. Topographic distribution of FD values in wakefulness showed a lateral symmetry and a partial fronto-occipital gradient. In drowsiness, a reduction in the number of clusters was detected, due to regrouping of channels T3, T4, O1 and O2. Topographic distribution of absolute FD differences revealed largest values at F7, O1 and F3. Reorganization of channel clusters showed that regionalized brain activity, specific for wakefulness, became more global by entering into drowsiness. Since the global increase in FD during wake-to-drowsy transition correlated with the decrease of alpha power, we inferred that increase of EEG complexity may not necessarily be an index of brain activation.     

仙琴蛙对不同类型声音的感知差异研究

既往研究发现听觉感知包括对声音信号的觉察、感觉、注意和知觉等多个认知过程,但依然不清楚大脑如何对不同类型的复杂声音信号(如同种鸣声和其他声音)进行解码和处理,以及在感知不同类型声音信号时大脑活动的动态特征.本研究记录了在随机播放白噪声和洞内鸣叫声音刺激时仙琴蛙Nidirana daunchina的左右端脑、间脑和中脑的...     

Life or death: prognostic value of a resting EEG with regards to survival in patients in vegetative and minimally conscious States

Objective

To investigate the potentially prognostic value of a resting state electroencephalogram (EEG) with regards to the clinical outcome from vegetative and minimally conscious states (VS and MCS) in terms of survival six months after a brain injury.

Methods

We quantified a dynamic repertoire of EEG oscillations in resting condition with eyes closed in patients in VS and MCS. The exact composition of EEG oscillations was assessed by analysing the probability-classification of short-term EEG spectral patterns.

Results

Results demonstrated that (a) the diversity and the variability of EEG for Non-Survivors were significantly lower than for Survivors; and (b) a higher probability of mostly delta and slow-theta oscillations occurring either alone or in combination were found during the first assessment for patients with a bad outcome (i.e., those who died) within six months of an injury compared to patients who survived. At the same time, patients with a good outcome (i.e., those who survived) after six months post-injury had a higher probability of mostly fast-theta and alpha oscillations occurring either alone or in combination during the first assessment when compared to patients who died within six months of an injury.

Conclusions

Resting state EEGs properly analysed may have a potentially prognostic value with regards to the outcome from VS or MCS in terms of survival six months after a brain injury.

Significance

This work may have implications for clinical care, rehabilitative programmes and medical–legal decisions for patients with impaired consciousness states after being in a coma due to acute brain injuries.     

Attention and regulation of EEG alpha-attenuation responses

Two experiments with 16 normal adults of both sexes tested the hypothesis that inattention to a biofeedback display is associated with increased variability of those physiological processes that had been regulated by the biofeedback. Each experiment was a repeated-measures-on-independent-subjects-design. Dependent variables were the time durations and the mean rms power of two mutually exclusive segments of the parietal-occipital EEG: alpha and not-alpha segments. Independent variables were combination of counting tasks and instructions to look at, listen to, and count visual and auditory flashes and clicks. The durations of alpha and not-alpha segments were controlled or regulated by means of an alpha-contingent visual feedback stimulus, Attention to the feedback stimulus was challenged by instructions to count other, noncontingent stimuli. Control of alpha and not-alpha segments was least for conditions of (1) “sham” feedback, and (2) feedback with instructions to count noncontingent auditory clicks, which were presented 3/sec while the feedback visual stimuli were occurring. A new EEG test of attention and distraction was suggested.     

急性高原低氧环境对不同情绪状态脑电功率的影响*

目的: 探讨急性高原低氧环境对不同情绪状态脑电功率的影响。方法:本研究为双因素多水平试验设计(氧气环境2个水平×情绪类型4个水平)。通过编写情绪图片诱导12名年龄在20～25岁之间的男性被试产生四类不同情绪:低效价低唤醒(LVLA)、高效价低唤醒(HVLA)、低效价高唤醒(LVHA)、高效价高唤醒(HVHA) ,分别近似于沮丧、轻松、恐惧、快乐四类情绪,并使用Brain Products 32导脑电采集设备采集不同情绪状态下的脑电信号;次日,采用常压低氧舱模拟4 300 m的高原低氧环境,同一批被试在低氧10 h 后使用相同试验范式采集脑电信号。对采集来的脑电信号进行功率谱分析(FFT),同时对额叶(F3\Fz\F4)脑电的五个频段(delta、theta、alpha、beta、gamma)进行两因素重复测量方差分析。结果:功率谱分析发现:急性低氧前后,四类情绪状态下alpha波的全脑分布差异主要集中在额叶、顶叶及部分颞叶;HVLA情绪状态下alpha波全脑分布差异最小。两因素重复测量方差分析结果发现:①delta、beta频段功率受氧气环境影响显著(P＜0.05),低氧环境下功率增强。②theta、alpha频段功率指标上,氧气环境和情绪类型交互作用显著(P＜0.05),低氧环境下除HVLA情绪状态外,theta、alpha频段功率皆出现了显著增强。③两因素对gamma频段影响都不显著(P＞0.05)。结论:在四类情绪状态下,氧气环境的变化对大脑活动的影响差异区域主要集中在额叶、顶叶及部分颞叶;低氧环境对沮丧、恐惧、快乐情绪状态有明显影响,低氧与情绪类型对于theta及alpha频段功率的改变具有协同作用。     

Dynamics of local maxima chains in spectra of human electroencephalogram

The continuous wavelet transform was applied to the human EEG signals recorded in different states of brain activity. The dynamics of local maxima chains in the matrices of the continuous wavelet transform coefficients was studied. The typologization method was developed for local maxima chains to separate by their drift in the frequency space as well as by dynamics of their signal “energy.” The method proved to be highly informative. It was shown that it was highly sensitive to a selection of one of two responses to the test question. It is determined that local maxima chains in most cases are gradually increasing and decreasing in the frequency space and by changes in the values of their continuous wavelet transform coefficients. The functional asymmetry in local maxima chains types’ distribution is determined. The results obtained allow us to consider the types of the local maxima chains dynamics as a new phenomenon of EEG activity.     

Cognitive network interactions and beta 2 coherence in processing non-target stimuli in visual oddball task

Spatiotemporal dynamics of event-related potentials (ERP) evoked by non-target stimuli in a visual oddball experiment and the presence of coherent oscillations in beta 2 frequency band of decomposed EEG records from peristimulus period were investigated by means of intracranial electrodes in humans. Twenty-one patients with medically intractable epilepsy participated in the study. The EEG signal was recorded using platinum electrodes implanted in several cortical and subcortical sites. Averaged 2 s EEG records were analyzed. Task-specific EEG changes were found in each patient, ERPs were derived from 92 electrodes used (96 % of possible cases). In the majority of analysed cases, ERPs were composed of several distinct components, and their duration was mostly longer than 1 s. The mean onset of the first ERP component was 158+/-132 ms after the stimulus (median 112 ms, minimum value 42 ms, maximum value 755 ms), and large variability of these onset times was found in all the investigated structures. Possible coherence between neural activities of remote brain sites was investigated by calculating running correlations between pairs of decomposed EEG records (alpha, beta 1, beta 2 frequency bands were used, total number of correlated pairs was 662 in each frequency band). The record pairs exhibiting highly correlated time segments represented 23 % of all the investigated pairs in alpha band, 7 % in beta 1 band, and 59 % in beta 2 band. In investigated 2 s record windows, such segments were distributed evenly, i.e. they were also found before the stimulus onset. In conclusion, the results have implicated the idea that a lot of recorded ERPs was more or less by-products of chance in spreading a signal within the neuronal network, and that their functional relevance was somewhat linked with the phenomenon of activity synchronization.     

Locus of Psychological Control and Peculiarities of Event-Related EEG Potentials

In a group including 74 adults of both sexes, we examined interrelations between the locus of psychological control (diagnosed using the Rotter questionnaire) and parameters of event-related EEG potentials, ERPs, recorded in the course of performance of two behavioral test acts with a motor component. Task A corresponded to maximally fast pushing on the button after a signal with warning; the time of the sensorimotor reaction was measured. Task B included internal counting of a definite time interval limited by two pushings on the button. Under these conditions, we recorded the contingent negative variation (CNV), the P300 potential, and, in task B, the readiness potential (RP). EEG leads C3 and C4, according to the 10-20 system, were used. Internals (estimates by the questionnaire, 6 stens or higher) were characterized by higher amplitudes of the terminal CNV (CNV-T), integral CNV, and P300 in task A, by greater RP and CNV amplitudes in task B, and also by shorter reaction times and their smaller dispersion. It should be supposed that the corresponding peculiarities of the neurodynamic constitution of an individual are determined, to a considerable extent, by the specificity of organization and functioning of a few neurotransmitter (aminergic in particular) and neurohumoral systems.     

Hearing sensation levels of emitted biosonar clicks in an echolocating Atlantic bottlenose dolphin

Emitted biosonar clicks and auditory evoked potential (AEP) responses triggered by the clicks were synchronously recorded during echolocation in an Atlantic bottlenose dolphin (Tursiops truncatus) trained to wear suction-cup EEG electrodes and to detect targets by echolocation. Three targets with target strengths of -34, -28, and -22 dB were used at distances of 2 to 6.5 m for each target. The AEP responses were sorted according to the corresponding emitted click source levels in 5-dB bins and averaged within each bin to extract biosonar click-related AEPs from noise. The AEP amplitudes were measured peak-to-peak and plotted as a function of click source levels for each target type, distance, and target-present or target-absent condition. Hearing sensation levels of the biosonar clicks were evaluated by comparing the functions of the biosonar click-related AEP amplitude-versus-click source level to a function of external (in free field) click-related AEP amplitude-versus-click sound pressure level. The results indicated that the dolphin's hearing sensation levels to her own biosonar clicks were equal to that of external clicks with sound pressure levels 16 to 36 dB lower than the biosonar click source levels, varying with target type, distance, and condition. These data may be assumed to indicate that the bottlenose dolphin possesses effective protection mechanisms to isolate the self-produced intense biosonar beam from the animal's ears during echolocation.     

Dynamics of spectral characteristics of theta- and alpha-range EEG during negative emotional reactions]

Power characteristics of the EEG theta and alpha rhythms were studied in a human in neutral state and during a conditioned negative emotional reaction (Fp1, Fp2, F3, F4, C3, C4, P3, P4, O1, O2, F7, F8, T3, T4, T5, and T6 derivations). A significant increase in the relative spectral power in the narrow theta band of 7.4-8.1 Hz in the frontocentral and temporal brain regions was observed during the development of the negative emotional reaction. The alpha-rhythm dynamics during the negative reaction was substantially individual and could be expressed in either an increase, or decrease in relative spectral power of different alpha-frequencies. No pronounced changes in their dynamics could also be observed. In some subjects the spectral power of the medium-frequency alpha-rhythm significantly decreased, that of the high-frequency rhythm increased, and changes in the spectral power of the low-frequency alpha range varied.     

Measures of entropy and complexity in altered states of consciousness

Quantification of complexity in neurophysiological signals has been studied using different methods, especially those from information or dynamical system theory. These studies have revealed a dependence on different states of consciousness, and in particular that wakefulness is characterized by a greater complexity of brain signals, perhaps due to the necessity for the brain to handle varied sensorimotor information. Thus, these frameworks are very useful in attempts to quantify cognitive states. We set out to analyze different types of signals obtained from scalp electroencephalography (EEG), intracranial EEG and magnetoencephalography recording in subjects during different states of consciousness: resting wakefulness, different sleep stages and epileptic seizures. The signals were analyzed using a statistical (permutation entropy) and a deterministic (permutation Lempel–Ziv complexity) analytical method. The results are presented in complexity versus entropy graphs, showing that the values of entropy and complexity of the signals tend to be greatest when the subjects are in fully alert states, falling in states with loss of awareness or consciousness. These findings were robust for all three types of recordings. We propose that the investigation of the structure of cognition using the frameworks of complexity will reveal mechanistic aspects of brain dynamics associated not only with altered states of consciousness but also with normal and pathological conditions.     

Spatial synchronization of the segmental EEG in humans

Topographic features of spatial synchronization of sharp changes, or rapid transition processes (RTP), were studied in human EEG recorded from longitudinal and transversal electrode arrays. A new algorithm, the EEG Threshold Scanning, was proposed for the detection of the RTP. Synchronization of the RTP was estimated by Operational Synchrony Index (OSI) based on the difference between the actual and stochastic frequency of RTP coincidence in a pair of EEG channels. The relationship between the OSI and interelectrode distance was not monotonous. The OSI depended also on the extent of morpho-functional similarity between two cortical areas. Similar results were obtained for crosscorrelation calculated for the same pairs of the EEG derivations. The existence of dynamic spatial modules which incorporate different brain areas by complementary stabilization of their functional states is discussed.     

Classifying Different Emotional States by Means of EEG-Based Functional Connectivity Patterns

This study aimed to classify different emotional states by means of EEG-based functional connectivity patterns. Forty young participants viewed film clips that evoked the following emotional states: neutral, positive, or negative. Three connectivity indices, including correlation, coherence, and phase synchronization, were used to estimate brain functional connectivity in EEG signals. Following each film clip, participants were asked to report on their subjective affect. The results indicated that the EEG-based functional connectivity change was significantly different among emotional states. Furthermore, the connectivity pattern was detected by pattern classification analysis using Quadratic Discriminant Analysis. The results indicated that the classification rate was better than chance. We conclude that estimating EEG-based functional connectivity provides a useful tool for studying the relationship between brain activity and emotional states.     

Explore the Functional Connectivity between Brain Regions during a Chemistry Working Memory Task

Previous studies have rarely examined how temporal dynamic patterns, event-related coherence, and phase-locking are related to each other. This study assessed reaction-time-sorted spectral perturbation and event-related spectral perturbation in order to examine the temporal dynamic patterns in the frontal midline (F), central parietal (CP), and occipital (O) regions during a chemistry working memory task at theta, alpha, and beta frequencies. Furthermore, the functional connectivity between F-CP, CP-O, and F-O were assessed by component event-related coherence (ERCoh) and component phase-locking (PL) at different frequency bands. In addition, this study examined whether the temporal dynamic patterns are consistent with the functional connectivity patterns across different frequencies and time courses. Component ERCoh/PL measured the interactions between different independent components decomposed from the scalp EEG, mixtures of time courses of activities arising from different brain, and artifactual sources. The results indicate that the O and CP regions’ temporal dynamic patterns are similar to each other. Furthermore, pronounced component ERCoh/PL patterns were found to exist between the O and CP regions across each stimulus and probe presentation, in both theta and alpha frequencies. The consistent theta component ERCoh/PL between the F and O regions was found at the first stimulus and after probe presentation. These findings demonstrate that temporal dynamic patterns at different regions are in accordance with the functional connectivity patterns. Such coordinated and robust EEG temporal dynamics and component ERCoh/PL patterns suggest that these brain regions’ neurons work together both to induce similar event-related spectral perturbation and to synchronize or desynchronize simultaneously in order to swiftly accomplish a particular goal. The possible mechanisms for such distinct component phase-locking and coherence patterns were also further discussed.     

Resolving the dynamics of EEG generators by multichannel recordings

The voltage recorded over the cortex (ECoG) or over the scalp (EEG) is generated by currents derived from many sources called “generators”. Different patterns and amplitudes are observed in aroused, sleepy, epileptic or other brain states. Differences in amplitude are generally attributed to differences in synchrony among generators. The degree of EEG synchrony is measured by the correlation between electrodes placed over different cortical regions. We present a new way to quantitatively assess the degree of synchronization of these generators via multichannel recordings. We illustrate how situations where there are several groups of generators with different inter-group and intra-group synchronies can be analyzed. Finally, we present a way to identify the organization of groups exhibiting topographic organization. Although the model presented here is highly simplified, several methods are based on averaging activity over increasingly larger areas. These types of measurements may be applied as well to EEG and ECoG recordings.