Characterizing Alzheimer’s Disease Severity via Resting-Awake EEG Amplitude Modulation Analysis

Changes in electroencephalography (EEG) amplitude modulations have recently been linked with early-stage Alzheimer’s disease (AD). Existing tools available to perform such analysis (e.g., detrended fluctuation analysis), however, provide limited gains in discriminability power over traditional spectral based EEG analysis. In this paper, we explore the use of an innovative EEG amplitude modulation analysis technique based on spectro-temporal signal processing. More specifically, full-band EEG signals are first decomposed into the five well-known frequency bands and the envelopes are then extracted via a Hilbert transform. Each of the five envelopes are further decomposed into four so-called modulation bands, which were chosen to coincide with the delta, theta, alpha and beta frequency bands. Experiments on a resting-awake EEG dataset collected from 76 participants (27 healthy controls, 27 diagnosed with mild-AD, and 22 with moderate-AD) showed significant differences in amplitude modulations between the three groups. Most notably, i) delta modulation of the beta frequency band disappeared with an increase in disease severity (from mild to moderate AD), ii) delta modulation of the theta band appeared with an increase in severity, and iii) delta modulation of the beta frequency band showed to be a reliable discriminant feature between healthy controls and mild-AD patients. Taken together, it is hoped that the developed tool can be used to assist clinicians not only with early detection of Alzheimer’s disease, but also to monitor its progression.     

Dissociable Neural Response Signatures for Slow Amplitude and Frequency Modulation in Human Auditory Cortex

Natural auditory stimuli are characterized by slow fluctuations in amplitude and frequency. However, the degree to which the neural responses to slow amplitude modulation (AM) and frequency modulation (FM) are capable of conveying independent time-varying information, particularly with respect to speech communication, is unclear. In the current electroencephalography (EEG) study, participants listened to amplitude- and frequency-modulated narrow-band noises with a 3-Hz modulation rate, and the resulting neural responses were compared. Spectral analyses revealed similar spectral amplitude peaks for AM and FM at the stimulation frequency (3 Hz), but amplitude at the second harmonic frequency (6 Hz) was much higher for FM than for AM. Moreover, the phase delay of neural responses with respect to the full-band stimulus envelope was shorter for FM than for AM. Finally, the critical analysis involved classification of single trials as being in response to either AM or FM based on either phase or amplitude information. Time-varying phase, but not amplitude, was sufficient to accurately classify AM and FM stimuli based on single-trial neural responses. Taken together, the current results support the dissociable nature of cortical signatures of slow AM and FM. These cortical signatures potentially provide an efficient means to dissect simultaneously communicated slow temporal and spectral information in acoustic communication signals.     

Quantification of transient quadratic phase couplings within EEG burst patterns in sedated patients during electroencephalic burst-suppression period

The time dynamics of the quadratic phase coupling within burst patterns during electroencephalic burst-suppression has been quantified. It can be shown that a transient quadratic phase coupling (QPC) exists between the frequency ranges 0 to 2.5 and 3 to 7.5 Hz and between the frequency ranges 0 to 2.5 and 8 to 12 Hz. The QPC can be explained by an amplitude modulation, where the slow rhythm modulates the rhythmic activities with a higher frequency. By means of time-variant bicoherence analysis, a strong phase-locking between the modulating and the modulated component can be identified. The phase-locking is demonstrable within the first 250 ms after the burst onset and comes up to the maximum between 750 and 1250 ms. The effect is maintained over the whole first part of the burst (2 s) with a decreasing tendency after 1250 ms. All these effects cannot be found in the EEG before entering the burst suppression period (BSP). The transient coupling phenomena in the EEG bursts during BSP can be regarded as indicators for short-term interrelations between the underlying electrophysiologic processes.     

Electrical Brain Responses to an Auditory Illusion and the Impact of Musical Expertise

The presentation of two sinusoidal tones, one to each ear, with a slight frequency mismatch yields an auditory illusion of a beating frequency equal to the frequency difference between the two tones; this is known as binaural beat (BB). The effect of brief BB stimulation on scalp EEG is not conclusively demonstrated. Further, no studies have examined the impact of musical training associated with BB stimulation, yet musicians'' brains are often associated with enhanced auditory processing. In this study, we analysed EEG brain responses from two groups, musicians and non-musicians, when stimulated by short presentation (1 min) of binaural beats with beat frequency varying from 1 Hz to 48 Hz. We focused our analysis on alpha and gamma band EEG signals, and they were analysed in terms of spectral power, and functional connectivity as measured by two phase synchrony based measures, phase locking value and phase lag index. Finally, these measures were used to characterize the degree of centrality, segregation and integration of the functional brain network. We found that beat frequencies belonging to alpha band produced the most significant steady-state responses across groups. Further, processing of low frequency (delta, theta, alpha) binaural beats had significant impact on cortical network patterns in the alpha band oscillations. Altogether these results provide a neurophysiological account of cortical responses to BB stimulation at varying frequencies, and demonstrate a modulation of cortico-cortical connectivity in musicians'' brains, and further suggest a kind of neuronal entrainment of a linear and nonlinear relationship to the beating frequencies.     

突触功能障碍大鼠模型EE G 频域特征

本文旨在探讨突触功能障碍大鼠模型在额叶、颞叶和海马这些与认知功能有关的脑区EEG频域特征。先用海马CA1区Aβ1-40加微量注射法制备突触功能障碍模型,用Morris水迷宫行为学测试系统检测其学习记忆能力;然后记录上述脑区的EEG并做频谱分析。结果显示：（1）模型组在第3,4、5、6训练时间段的平均逃避潜伏期较正常组明显延长,和第2训练时间段的相比较,正常组第5训练时间段平均逃避潜伏期明显缩短,模型组到第7训练时间段平均逃避潜伏期开始明显缩短（P〈0．05）;撤去平台后,模型组在原平台所在象限的时间百分比明显降低（P〈0．05）。（2）模型组的EEG表现为α节律慢化,功率下降,其主峰频率左移2Hz,并且额叶、颞叶和海马的δ波和θ波功率不同程度地增高。由此Aβ1-40微量注射法成功制备了突触功能障碍大鼠模型。该模型大鼠的学习记忆能力降低,其频谱特征表现为α节律慢化,功率下降或消失,慢波（δ波和θ波）活动增多,功率不同程度地增高。这些与阿尔茨海默病（Alzheimer’s disease,AD）的EEG一致,可为以后对突触功能障碍时受累皮层进行深入的可塑性和神经再生的研究提供电生理基础。     

Morning and evening-type differences in slow waves during NREM sleep reveal both trait and state-dependent phenotypes

Brain recovery after prolonged wakefulness is characterized by increased density, amplitude and slope of slow waves (SW, <4 Hz) during non-rapid eye movement (NREM) sleep. These SW comprise a negative phase, during which cortical neurons are mostly silent, and a positive phase, in which most neurons fire intensively. Previous work showed, using EEG spectral analysis as an index of cortical synchrony, that Morning-types (M-types) present faster dynamics of sleep pressure than Evening-types (E-types). We thus hypothesized that single SW properties will also show larger changes in M-types than in E-types in response to increased sleep pressure. SW density (number per minute) and characteristics (amplitude, slope between negative and positive peaks, frequency and duration of negative and positive phases) were compared between chronotypes for a baseline sleep episode (BL) and for recovery sleep (REC) after two nights of sleep fragmentation. While SW density did not differ between chronotypes, M-types showed higher SW amplitude and steeper slope than E-types, especially during REC. SW properties were also averaged for 3 NREM sleep periods selected for their decreasing level of sleep pressure (first cycle of REC [REC1], first cycle of BL [BL1] and fourth cycle of BL [BL4]). Slope was significantly steeper in M-types than in E-types in REC1 and BL1. SW frequency was consistently higher and duration of positive and negative phases constantly shorter in M-types than in E-types. Our data reveal that specific properties of cortical synchrony during sleep differ between M-types and E-types, although chronotypes show a similar capacity to generate SW. These differences may involve 1) stable trait characteristics independent of sleep pressure (i.e., frequency and durations) likely linked to the length of silent and burst-firing phases of individual neurons, and 2) specific responses to increased sleep pressure (i.e., slope and amplitude) expected to depend on the synchrony between neurons.     

Increase of slow periodic modulation of EEG in a patient with Alzheimer's disease.

The recently described slow oscillations of amplitude of theta and alpha waves of the EEG (with a frequency below 0.08 Hz) in healthy subjects are attributed to the autonomic nervous system with control at the brain stem level. In the present pilot study, the slow brain rhythms were analyzed in a patient with Alzheimer's disease and were compared to a healthy subject. Dynamic analysis of the EEG was performed using time-frequency mapping which gives simultaneous time and frequency representation of the brain signal. This method comprises a transform of the filtered EEG signal into its analytic form and application of the Wigner distribution modified by time and frequency smoothing. It has been shown that the envelope of both theta and alpha activities oscillates at 0.04 Hz and 0.07 Hz in the healthy subject and at 0.03 Hz and 0.06 Hz in a patient with Alzheimer's disease. The amplitude of the slow oscillations of theta activity was substantially higher in the patient with Alzheimer's disease as compared with the healthy subject. It is being proposed that the increase of slow brain rhythms in the patient with Alzheimer's disease reflects an abnormal activity of the autonomic nervous system. However, the underlying pathophysiological mechanisms need to be further studied.     

Factors affecting central inspiratory modulation of hypoglossal motoneuron activity in newborn pigs

In newborn pigs (4-6 days old), recordings of efferent whole hypoglossal and phrenic nerve discharges were obtained during hyperoxia (or normoxia) and during hypoxia, before and after bilateral vagotomy. With intact vagi, spontaneous hypoglossal inspiratory activity was not observed and was not elicited by either spontaneous changes of electroencephalogram (EEG) or hypoxic stimulation (15% O2 in N2). After bilateral vagotomy, some animals had episodes of spontaneous hypoglossal inspiratory activity; power spectral analysis of EEG demonstrated that this inspiratory activity appeared synchronously with shifts of major peaks in EEG spectra from the delta band (0.5-3.5 Hz) to the theta band (3.5-7.0 Hz). Hypoglossal inspiratory discharges were also elicited by hypoxic stimulation and usually had a decrementing discharge pattern; in some cases, this activity had an augmenting discharge pattern. Our results suggest that hypoglossal motoneurons are poorly modulated by central inspiratory drive, requiring additional facilitatory influences, i.e. corticobulbar, intra-bulbar, chemical drive, before such modulation is observed.     

不同部位梗死后痴呆的脑电图表现差异分析

目的:探讨不同部位脑梗死导致血管性痴呆的脑电图表现差异,为血管性痴呆的诊断分类提供客观依据。方法:80例诊断血管性痴呆的患者根据影像学表现分为多灶梗死后痴呆和关键部位梗死后痴呆。入选患者均于饱餐后2小时给予常规18导脑电图检查,记录时间为30分钟以上。结果:1多灶梗死后痴呆多表现为α节律减慢,6-8Hz为主;波幅低,以20-25Uv为主,α波频率调节差、节律不规则。低波幅θ波出现者27例,占71.1%,出现于各导联,出现δ波者17例,占44.7%。2关键部位梗死后痴呆的患者中,正常为6例,占13%。异常者39例,占87%。EEG改变主要表现为α指数减少,节律以7-9Hz为主的患者28例,占71.8%。低波幅θ波出现者17例,以前额为主,占43.6%。39例患者未出现δ波。结论:不同部位梗死后血管性痴呆的脑电图表现不尽相同,可以为血管性痴呆的分类诊断提供客观依据。     

Low-frequency rhythmic electrocutaneous hand stimulation during slow-wave night sleep: Physiological and therapeutic effects

Neocortical EEG slow wave activity (SWA) in the delta frequency band (0.5–4.0 Hz) is a hallmark of slow wave sleep (SWS) and its power is a function of prior wake duration and an indicator of a sleep need. SWS is considered the most important stage for realization of recovery functions of sleep. Possibility of impact on characteristics of a night sleep by rhythmic (0.8–1.2 Hz) subthreshold electocutaneous stimulation of a hand during SWS is shown: 1st night—adaptation, 2nd night—control, 3d and 4th nights—with stimulation during SWA stages of a SWS. Stimulation caused significant increase in average duration of SWS and EEG SWA power (in 11 of 16 subjects), and also well-being and mood improvement in subjects with lowered emotional tone. It is supposed that the received result is caused by functioning of a hypothetical mechanism directed on maintenance and deepening of SWS and counteracting activating, awakening influences of the afferent stimulation. The results can be of value both for understanding the physiological mechanisms of sleep homeostasis and for development of non-pharmacological therapy of sleep disorders.     

A digital signal processing system for EEG frequency analysis

This paper describes the digital signal processing work of a research project for studying children's cognitive processes by analyzing EEG signals during school-related tasks. The EEG being analyzed involves two homologous channels (left and right parietal area), and is recorded on magnetic tapes. The objective of the analysis is to determine if, by examining the alpha band of the ongoing EEG, different school tasks and correct vs incorrect responses can be detected. Analysis of alpha-band calls for the determination of signal power in the 7-12 Hz frequency band (adjusted for the age of the subjects) for each channel as well as correlation between the channels. A digital signal processing scheme implemented on an Apple II microcomputer was developed for such an analysis. The results obtained are discussed.     

Involvement of Ventral Periaqueductal Gray Dopaminergic Neurons in Propofol Anesthesia

It has been reported that central dopaminergic system is implicated in the mechanism underlying general anesthesia. Whether dopamine (DA) neurons in midbrain ventral periaqueductal gray (vPAG) are involved in general anesthesia and how general anesthetics affect these neurons remain sparsely documented. To determine the role of vPAG DA neurons in propofol-induced anesthesia, we performed microinjection of 6-hydroxydopamine (6-OHDA) into vPAG to damage DA neurons and investigated the alteration in somatosensory electroencephalogram (EEG), as well as the induction and recovery time of propofol anesthesia. Subsequently, we examined the effect of propofol on the electrophysiological activity of DA neurons in vPAG using whole-cell patch clamp. Two weeks after 6-OHDA microinfusion, DA neurons in the vPAG were markedly reduced by 63.6% in the 6-OHDA-treated rats compared with vehicle rats. This lesion significantly shortened the induction time (7.15?±?3.97 s vs. 11.18?±?2.83 s, P?<?0.05) and prolonged the recovery time of propofol anesthesia (780.26?±?150.86 s vs. 590.68?±?107.97 s, P?<?0.05). Meanwhile, EEG in somatosensory cortex revealed that delta power (0–4 Hz) was significantly higher in 6-OHDA-treated rats than vehicle rats. In the electrophysiological experiment, propofol decreased the frequency of spontaneous excitatory postsynaptic currents rather than the amplitude and decay time. In addition, propofol preferentially increased the frequency and prolonged the decay time of spontaneous inhibitory postsynaptic currents without affecting the amplitude. Significance: Propofol can promote presynaptic GABA release, inhibit presynaptic glutamate release and increase postsynaptic GABA_A receptor sensitivity, which eventually inhibits the activity of vPAG DA neurons and thereby influences the state of consciousness.     

Differential Entrainment of Neuroelectric Delta Oscillations in Developmental Dyslexia

Oscillatory entrainment to the speech signal is important for language processing, but has not yet been studied in developmental disorders of language. Developmental dyslexia, a difficulty in acquiring efficient reading skills linked to difficulties with phonology (the sound structure of language), has been associated with behavioural entrainment deficits. It has been proposed that the phonological ‘deficit’ that characterises dyslexia across languages is related to impaired auditory entrainment to speech at lower frequencies via neuroelectric oscillations (<10 Hz, ‘temporal sampling theory’). Impaired entrainment to temporal modulations at lower frequencies would affect the recovery of the prosodic and syllabic structure of speech. Here we investigated event-related oscillatory EEG activity and contingent negative variation (CNV) to auditory rhythmic tone streams delivered at frequencies within the delta band (2 Hz, 1.5 Hz), relevant to sampling stressed syllables in speech. Given prior behavioural entrainment findings at these rates, we predicted functionally atypical entrainment of delta oscillations in dyslexia. Participants performed a rhythmic expectancy task, detecting occasional white noise targets interspersed with tones occurring regularly at rates of 2 Hz or 1.5 Hz. Both groups showed significant entrainment of delta oscillations to the rhythmic stimulus stream, however the strength of inter-trial delta phase coherence (ITC, ‘phase locking’) and the CNV were both significantly weaker in dyslexics, suggestive of weaker entrainment and less preparatory brain activity. Both ITC strength and CNV amplitude were significantly related to individual differences in language processing and reading. Additionally, the instantaneous phase of prestimulus delta oscillation predicted behavioural responding (response time) for control participants only.     

Regional slow waves and spindles in human sleep

The most prominent EEG events in sleep are slow waves, reflecting a slow (<1 Hz) oscillation between up and down states in cortical neurons. It is unknown whether slow oscillations are synchronous across the majority or the minority of brain regions--are they a global or local phenomenon? To examine this, we recorded simultaneously scalp EEG, intracerebral EEG, and unit firing in multiple brain regions of neurosurgical patients. We find that most sleep slow waves and the underlying active and inactive neuronal states occur locally. Thus, especially in late sleep, some regions can be active while others are silent. We also find that slow waves can propagate, usually from medial prefrontal cortex to the medial temporal lobe and hippocampus. Sleep spindles, the other hallmark of NREM sleep EEG, are likewise predominantly local. Thus, intracerebral communication during sleep is constrained because slow and spindle oscillations often occur out-of-phase in different brain regions.     

An index of signal mode complexity based on orthogonal transformation

Irregular and complex signals are ubiquitous in nature. The principal aim of this paper is to develop an index, quantifying the complexity of such signals, which is based on the distribution of the strengths of its orthogonal oscillatory modes estimated by singular value decomposition. The index is first tested with simulated chaotic and/or stochastic maps and flows. Among neural data analysis, the index is first applied to a cognitive EEG data set recorded from two groups, musicians and non-musicians, during listening to music and resting state. In the gamma band (30–50 Hz), musicians showed robust changes in complexity, consistent over various scalp regions, during listening to music from resting condition, whereas such changes were minimal for non-musicians. Then the index is used to separate healthy participants from epileptic and manic patients based on spontaneous EEG analysis. Finally, it is used to track a tonic-clonic seizure EEG signal, and a conspicuous change was found in the complexity profiles of delta band (1–3.5 Hz) oscillations at the onset of seizure. We conclude that this index would be useful for quantification of a wide range of time series including neural oscillations.     

EEG Source Reconstruction Reveals Frontal-Parietal Dynamics of Spatial Conflict Processing

Cognitive control requires the suppression of distracting information in order to focus on task-relevant information. We applied EEG source reconstruction via time-frequency linear constrained minimum variance beamforming to help elucidate the neural mechanisms involved in spatial conflict processing. Human subjects performed a Simon task, in which conflict was induced by incongruence between spatial location and response hand. We found an early (∼200 ms post-stimulus) conflict modulation in stimulus-contralateral parietal gamma (30–50 Hz), followed by a later alpha-band (8–12 Hz) conflict modulation, suggesting an early detection of spatial conflict and inhibition of spatial location processing. Inter-regional connectivity analyses assessed via cross-frequency coupling of theta (4–8 Hz), alpha, and gamma power revealed conflict-induced shifts in cortical network interactions: Congruent trials (relative to incongruent trials) had stronger coupling between frontal theta and stimulus-contrahemifield parietal alpha/gamma power, whereas incongruent trials had increased theta coupling between medial frontal and lateral frontal regions. These findings shed new light into the large-scale network dynamics of spatial conflict processing, and how those networks are shaped by oscillatory interactions.     

Application of a dissimilarity index of EEG and its sub-bands on prediction of induced epileptic seizures from rat's EEG signals

ObjectiveEpileptic seizures are defined as manifest of excessive and hyper-synchronous activity of neurons in the cerebral cortex that cause frequent malfunction of the human central nervous system. Therefore, finding precursors and predictors of epileptic seizure is of utmost clinical relevance to reduce the epileptic seizure induced nervous system malfunction consequences. Researchers for this purpose may even guide us to a deep understanding of the seizure generating mechanisms. The goal of this paper is to predict epileptic seizures in epileptic rats.MethodsSeizures were induced in rats using pentylenetetrazole (PTZ) model. EEG signals in interictal, preictal, ictal and postictal periods were then recorded and analyzed to predict epileptic seizures. Epileptic seizures were predicted by calculating an index in consecutive windows of EEG signal and comparing the index with a threshold. In this work, a newly proposed dissimilarity index called Bhattacharyya Based Dissimilarity Index (BBDI), dynamical similarity index and fuzzy similarity index were investigated.ResultsBBDI, dynamical similarity index and fuzzy similarity index were examined on case and control groups and compared to each other. The results show that BBDI outperforms dynamical and fuzzy similarity indices. In order to improve the results, EEG sub-bands were also analyzed. The best result achieved when the proposed dissimilarity index was applied on Delta sub-band that predicts epileptic seizures in all rats with a mean of 299.5 s.ConclusionThe dissimilarity of neural network activity between reference window and present window of EEG signal has a significant increase prior to an epileptic seizure and the proposed dissimilarity index (BBDI) can reveal this variation to predict epileptic seizures. In addition, analyzing EEG sub-bands results in more accurate information about constituent neuronal activities underlying the EEG since certain changes in EEG signal may be amplified when each sub-band is analyzed separately.SignificanceThis paper presents application of a dissimilarity index (BBDI) on EEG signals and its sub-bands to predict PTZ-induced epileptic seizures in rats. Based on the results of this work, BBDI will predict epileptic seizures more accurately and more reliably compared to current indices that increases epileptic patient comfort and improves patient outcomes.     

石灰土演替过程中颗粒态有机质和矿物结合态有机质的微生物群落特征

碳酸盐岩经风化作用并在地形、植被、气候、时间及生物等因素的影响下逐渐演替出黑色石灰土、棕色石灰土、黄色石灰土和红色石灰土。【目的】研究不同演替阶段石灰土颗粒态有机质(particulate organic matter, POM)和矿物结合态有机质(mineral-associated organic matter, MAOM)的微生物群落特征,为岩溶土壤有机质稳定机制研究提供理论依据。【方法】以广西弄岗国家级自然保护区的黑色石灰土、棕色石灰土、黄色石灰土和红色石灰土为研究对象,运用湿筛法将土壤有机质(soil organic matter, SOM)分为POM和MAOM,分析其理化性质以及微生物群落特征。【结果】石灰土演替过程中POM和MAOM的有机碳、总氮、交换性钙含量均呈下降趋势,且MAOM的C/N均大于POM,POM的C/P均大于MAOM。细菌α多样性在黑色石灰土POM和MAOM中最高,且四类石灰土MAOM的真菌多样性比POM要高。Acidobacteria、Proteobacteria、Ascomycota均为石灰土演替过程中POM和MAOM的优势菌门。总磷是影响石灰土演替过...     

A hidden Markov model reliably characterizes ketamine-induced spectral dynamics in macaque local field potentials and human electroencephalograms

Ketamine is an NMDA receptor antagonist commonly used to maintain general anesthesia. At anesthetic doses, ketamine causes high power gamma (25-50 Hz) oscillations alternating with slow-delta (0.1-4 Hz) oscillations. These dynamics are readily observed in local field potentials (LFPs) of non-human primates (NHPs) and electroencephalogram (EEG) recordings from human subjects. However, a detailed statistical analysis of these dynamics has not been reported. We characterize ketamine’s neural dynamics using a hidden Markov model (HMM). The HMM observations are sequences of spectral power in seven canonical frequency bands between 0 to 50 Hz, where power is averaged within each band and scaled between 0 and 1. We model the observations as realizations of multivariate beta probability distributions that depend on a discrete-valued latent state process whose state transitions obey Markov dynamics. Using an expectation-maximization algorithm, we fit this beta-HMM to LFP recordings from 2 NHPs, and separately, to EEG recordings from 9 human subjects who received anesthetic doses of ketamine. Our beta-HMM framework provides a useful tool for experimental data analysis. Together, the estimated beta-HMM parameters and optimal state trajectory revealed an alternating pattern of states characterized primarily by gamma and slow-delta activities. The mean duration of the gamma activity was 2.2s([1.7,2.8]s) and 1.2s([0.9,1.5]s) for the two NHPs, and 2.5s([1.7,3.6]s) for the human subjects. The mean duration of the slow-delta activity was 1.6s([1.2,2.0]s) and 1.0s([0.8,1.2]s) for the two NHPs, and 1.8s([1.3,2.4]s) for the human subjects. Our characterizations of the alternating gamma slow-delta activities revealed five sub-states that show regular sequential transitions. These quantitative insights can inform the development of rhythm-generating neuronal circuit models that give mechanistic insights into this phenomenon and how ketamine produces altered states of arousal.     

睡眠2期脑电信号产生的生理机制模型仿真研究

目前慢波睡眠生理机制研究已有的理论及动物实验结果显示,慢波睡眠中,皮层-丘脑系统神经元存在三种不同节律的振荡:慢振荡(<1 HZ)、δ振荡(1-4Hz)和纺锤振荡(7-14Hz)。这些神经元电活动在皮层水平广泛同步化,产生慢波睡眠脑电。提出了能分别产生这三种节律的三种神经元环路模型,并将之组合简化成一个七细胞环路模型。由这样的大量环路组成的网络模型在合适的突触连接参数范围内,能在皮层处产生人类慢波睡眠脑电2期的完整波形。这一结果说明了如何将动物实验观察到的睡眠生理机制的结果与人自然睡眠活动的脑电结果联系起来,并提示脑信息处理中由微观神经元群放电特征整合为脑的宏观功能状态的主要环节。