Noise and coupling affect signal detection and bursting in a simulated physiological neural network

Signal detection in the CNS relies on a complex interaction between the numerous synaptic inputs to the detecting cells. Two effects, stochastic resonance (SR) and coherence resonance (CR) have been shown to affect signal detection in arrays of basic neuronal models. Here, an array of simulated hippocampal CA1 neurons was used to test the hypothesis that physiological noise and electrical coupling can interact to modulate signal detection in the CA1 region of the hippocampus. The array was tested using varying levels of coupling and noise with different input signals. Detection of a subthreshold signal in the network improved as the number of detecting cells increased and as coupling was increased as predicted by previous studies in SR; however, the response depended greatly on the noise characteristics present and varied from SR predictions at times. Careful evaluation of noise characteristics may be necessary to form conclusions about the role of SR in complex systems such as physiological neurons. The coupled array fired synchronous, periodic bursts when presented with noise alone. The synchrony of this firing changed as a function of noise and coupling as predicted by CR. The firing was very similar to certain models of epileptiform activity, leading to a discussion of CR as a possible simple model of epilepsy. A single neuron was unable to recruit its neighbors to a periodic signal unless the signal was very close to the synchronous bursting frequency. These findings, when viewed in comparison with physiological parameters in the hippocampus, suggest that both SR and CR can have significant effects on signal processing in vivo.     

生物医学领域中随机共振的理论及应用研究

随机共振是非线性动力系统中的普遍现象,它向人们展示了噪声在非线性体系中的积极作用。除了经典的随机共振理论外,还讨论了其他类型的随机共振,诸如非周期、超阈值和耦合随机共振等等;讲述了随机共振的基本机理及表征方法;介绍了随机共振在生物和医学领域中的应用及最新研究进展,并对随机共振的发展前景做了展望。     

Intra-hemispheric functional coupling of alpha rhythms is related to golfer's performance: a coherence EEG study

It has been shown that frontocentral electroencephalographic (EEG) alpha rhythms (about 10-12 Hz) were higher in amplitude in expert golfers in successful than unsuccessful putts, possibly reflecting the idea that amplitude regulation of frontocentral alpha rhythms is a physiological mechanism implied in motor control and golfer's performance (Babiloni et al., 2008). Here, we tested the ancillary hypothesis that golfer's performance is also associated to an improved coordination of cortical activity, as reflected by functional coupling of alpha rhythms across cortical regions. To this aim, between-electrodes spectral coherence was computed from spatially enhanced EEG data of the mentioned study (i.e. right handed 12 expert golfers; augmented 10-20 system; surface Laplacian estimation). Low- (about 8-10 Hz) and high-frequency (about 10-12 Hz) alpha sub-bands were considered with reference to individual alpha frequency peak. Statistical results showed that intra-hemispheric low-frequency alpha coherence in bilateral parietal-frontal (P3-F3 and P4-F4 electrodes) and parietal-central (P3-C3 and P4-C4 electrodes) was higher in amplitude in successful than unsuccessful putts (p<0.004). The same was true for intra-hemispheric high-frequency alpha coherence in bilateral parietal-frontal regions (p<0.004). These findings suggest that intra-hemispheric functional coupling of cortical alpha rhythms between "visuo-spatial" parietal area and other cortical areas is implicated in fine motor control of golfer's performance.     

Fully tuneable stochastic resonance in cutaneous receptors

Stochastic resonance describes a phenomenon whereby the addition of "noise" to the input of a nonlinear system can improve sensitivity. "Fully tuneable stochastic resonance" is a particular form of the phenomenon that requires the matching of two time scales: one being that of the subthreshold periodic stimulus of the system and the other being the noise-induced response of the system. First proposed in 1981, stochastic resonance has been reported in a wide range of biological systems; however, conclusive experimental evidence for fully tuneable stochastic resonance in biological systems is limited. Evidence of fully tuneable stochastic resonance in the response of slowly adapting type I mechanoreceptors in the toad is presented. The results are extended to include the first evidence supporting fully tuneable stochastic resonance in psychophysical experiments, namely tactile detection thresholds, indicating that the human CNS is capable of accessing the improved information available via fully tuneable stochastic resonance.     

Mobile phone emission increases inter-hemispheric functional coupling of electroencephalographic alpha rhythms in epileptic patients

It has been reported that GSM electromagnetic fields (GSM-EMFs) of mobile phones modulate - after a prolonged exposure - inter-hemispheric synchronization of temporal and frontal resting electroencephalographic (EEG) rhythms in normal young and elderly subjects (Vecchio et al., 2007, 2010). Here we tested the hypothesis that this can be even more evident in epileptic patients, who typically suffer from abnormal mechanisms governing synchronization of rhythmic firing of cortical neurons. Eyes-closed resting EEG data were recorded in ten patients affected by focal epilepsy in real and sham exposure conditions. These data were compared with those obtained from 15 age-matched normal subjects of the previous reference studies. The GSM device was turned on (45 min) in the "GSM" condition and was turned off (45 min) in the other condition ("sham"). The mobile phone was always positioned on the left side in both patients and control subjects. Spectral coherence evaluated the inter-hemispheric synchronization of EEG rhythms at the following frequency bands: delta (about 2-4 Hz), theta (about 4-6 Hz), alpha1 (about 6-8 Hz), alpha2 (about 8-10 Hz), and alpha3 (about 10-12 Hz). The effects on the patients were investigated comparing the inter-hemispheric EEG coherence in the epileptic patients with the control group of subjects evaluated in the previous reference studies. Compared with the control subjects, epileptic patients showed a statistically significant higher inter-hemispheric coherence of temporal and frontal alpha rhythms (about 8-12 Hz) in the GSM than "Sham" condition. These results suggest that GSM-EMFs of mobile phone may affect inter-hemispheric synchronization of the dominant (alpha) EEG rhythms in epileptic patients. If confirmed by future studies on a larger group of epilepsy patients, the modulation of the inter-hemispheric alpha coherence due to the GSM-EMFs could have clinical implications and be related to changes in cognitive-motor function.     

Network recruitment to coherent oscillations in a hippocampal computer model

Coherent neural oscillations represent transient synchronization of local neuronal populations in both normal and pathological brain activity. These oscillations occur at or above gamma frequencies (>30 Hz) and often are propagated to neighboring tissue under circumstances that are both normal and abnormal, such as gamma binding or seizures. The mechanisms that generate and propagate these oscillations are poorly understood. In the present study we demonstrate, via a detailed computational model, a mechanism whereby physiological noise and coupling initiate oscillations and then recruit neighboring tissue, in a manner well described by a combination of stochastic resonance and coherence resonance. We develop a novel statistical method to quantify recruitment using several measures of network synchrony. This measurement demonstrates that oscillations spread via preexisting network connections such as interneuronal connections, recurrent synapses, and gap junctions, provided that neighboring cells also receive sufficient inputs in the form of random synaptic noise. "Epileptic" high-frequency oscillations (HFOs), produced by pathologies such as increased synaptic activity and recurrent connections, were superior at recruiting neighboring tissue. "Normal" HFOs, associated with fast firing of inhibitory cells and sparse pyramidal cell firing, tended to suppress surrounding cells and showed very limited ability to recruit. These findings point to synaptic noise and physiological coupling as important targets for understanding the generation and propagation of both normal and pathological HFOs, suggesting potential new diagnostic and therapeutic approaches to human disorders such as epilepsy.     

快速老化小鼠海马脑片CA1区神经元放电特征模式研究

目的研究快速老化对记忆脑区海马CA1神经元电活动兴奋性的影响。方法应用脑片和细胞外记录技术,记录快速老化（sAM．P／8）组和正常对照组小鼠在海马脑片CA1区的锥体神经元自发放电序列,通过计算2组神经元自发放电频率和神经元放电间隔（ISI）研究快速老化对海马CA1区神经元兴奋性的影响。结果快速老化组小鼠海马CA1区神经元自发放电频率为（1．052±0．364）Hz（样本数n1=14）,正常对照组为4．416＋1．306Hz（样本数n1=22）,前者比后者显著降低（P〈0．05）;快速老化组ISI≥1s,占80．5％,正常对照组ISI均≤1S,其中95．6％≤0．5S,前者比后者显著延长。结论快速老化组小鼠海马脑片CA1区神经元的发放频率降低,ISI延长。提示快速老化对小鼠海马区神经元兴奋性电活动起到了明显的抑制作用。     

Synaptic noise improves detection of subthreshold signals in hippocampal CA1 neurons

Stochastic resonance (SR) is a phenomenon whereby the detection of a low-level signal is enhanced in a nonlinear system by the introduction of noise. Studies of the effects of SR in neurons have suggested that noise could play a prominent role in improving detection of small signals. Most experimental SR research has focused on the role of noise in sensory neurons using physiological stimuli. Computer simulations show that signal detection in hippocampal neurons is improved by the addition of physiological levels of noise applied extracellularly to synaptic inputs. These results were confirmed experimentally. We now report that endogenous noise sources can also improve signal detection. The noise source was generated by modulating the random synaptic activity on the apical dendrites of CA1 cells in rat hippocampal slices using subthreshold cathodic current. Intracellular recordings of CA1 cells showed that even small increases of synaptic noise are able to greatly improve the detection of an independent, synaptic, subthreshold stimulus as predicted by the simulations. The noise variance in the CA1 cell was compared with the resting variance and with variance changes caused by several endogenous noise sources. In all cases, the increased noise variance was well within the physiological range. These results were supplemented and analyzed with a CA1 computer model. The improved signal detection with small amounts of endogenous noise suggests that the diverse inputs to CA1 are able to improve detection of subthreshold synaptic signals and could provide a means to modulate detection of specific inputs in the hippocampus.     

EEG Correlates of Action Observation in Humans

To investigate electrophysiological correlates of action observation electroencephalogram (EEG) was recorded while participants observed repetitive biological (human) or non-biological movements (at a rate of 2 Hz). Steady-state evoked potentials were analyzed and their neural sources were investigated using low resolution electromagnetic tomography analysis (LORETA). Results revealed significantly higher activation in the primary motor and premotor cortex, supplementary motor area as well as the posterior parietal cortices during observation of biological movements, supporting mirror properties of cortical motor neurons. In addition interregional communication was analyzed. Increased coherence for distributed networks at delta (0.5–4 Hz) and lower alpha (8–10 Hz) frequencies were obtained suggesting integration and functional coupling between the activated cortical regions during human action observation.     

Control of human locomotion under various task constraints

The goal of this study was to identify the control mechanism used for locomotion pointing regulation under different external temporal constraints. Subjects ( n=8) had to walk on a treadmill through a number of virtual hallways and cross a pair of gliding doors that opened and closed at a constant preset frequency (0.5 Hz or 1 Hz). Crossing performance, step durations, and step lengths were used as dependent measures. The results revealed the regulation of locomotion occurred earlier and was more pronounced at 0.5 Hz than at 1 Hz, making performance better at 0.5 Hz. Nevertheless at the two frequencies the control mechanism appears similar; it is grounded on information movement coupling. This control mechanism allows for the production of specific behavior according to the task constraints.     

Stochastic resonance improves signal detection in hippocampal CA1 neurons

Stochastic resonance (SR) is a phenomenon observed in nonlinear systems whereby the introduction of noise enhances the detection of a subthreshold signal for a certain range of noise intensity. The nonlinear threshold detection mechanism that neurons employ and the noisy environment in which they reside makes it likely that SR plays a role in neural signal detection. Although the role of SR in sensory neural systems has been studied extensively, its role in central neurons is unknown. In many central neurons, such as the hippocampal CA1 cell, very large dendritic trees are responsible for detecting neural input in a noisy environment. Attenuation due to the electrotonic length of these trees is significant, suggesting that a method other than passive summation is necessary if signals at the distal ends of the tree are to be detected. The hypothesis that SR plays an important role in the detection of distal synaptic inputs first was tested in a computer simulation of a CA1 cell and then verified with in vitro rat hippocampal slices. The results clearly showed that SR can enhance signal detection in CA1 hippocampal cells. Moreover, high levels of noise were found to equalize detection of synaptic signals received at varying positions on the dendritic tree. The amount of noise needed to evoke the effect is compared with physiological noise in slices and in vivo.     

Noninvasive Epileptic Seizure Localization from Stochastic Behavior of Short Duration Interictal High Density Scalp EEG Data

The stochastic behavior of the phase synchronization index (SI) in different EEG bands was examined for noninvasive localization of the epileptogenic areas from the short duration (30–60 s), seizure-free and spike-free high density (256 channel) scalp EEG data. We also examined the cross-frequency and cross-electrode coupling in different EEG bands. EEG data of four subjects was used. The seizure areas were localized with subdural recordings with an 8×8 grid electrode array. It was found that the stochastic behavior of the SI in low gamma band (30–50 Hz) was higher in epileptogenic areas. The beta (12–30 Hz) band also showed similar tendencies. The stochastic behavior in theta (3–7 Hz) band was depressed in the seizure area while it was widespread in large areas over the scalp in the alpha (7–12 Hz) band. The stochastic behavior of the cross-frequency and cross-electrode couplings in theta–gamma, alpha–gamma and beta–gamma bands were decreased in the seizure areas for all four subjects. These findings suggest that it is possible to localize the epileptogenic areas from the short duration seizure-free and spike-free high density scalp EEG data.     

Movement rate effect on activation and functional coupling of motor cortical areas

We investigated changes in the activation and functional coupling of bilateral primary sensorimotor (SM1) and supplementary motor (SMA) areas with different movement rates in eight normal volunteers. An auditory-cued repetitive right-thumb movement was performed at rates of 0.5, 0.75, 1, 2, 3, and 4 Hz. As a control condition, subjects listened to pacing tones with no movements. Electroencephalogram (EEG) was recorded from 28 scalp electrodes and electromyogram was obtained from the hand muscles. The event-related changes in EEG band-power (ERpow: activation of each area) and correlation (ERcor: functional coupling between each pair of cortical areas) were computed every 32 ms. Modulations of ERpow and ERcor were inspected in alpha (8-12 Hz) and beta (16-20 Hz) bands. Motor cortical activation and coupling was greater for faster movements. With increasing movement rate, the timing relationship between movement and tone switched from synchronization (for 0.5-1 Hz) to syncopation (for 3-4 Hz). The results suggested that for slow repetitive movements (0.5-1 Hz), each individual movement is separately controlled, and EEG activation and coupling of the motor cortical areas were immediately followed by transient deactivation and decoupling, having clear temporal modulation locked to each movement. In contrast, for fast repetitive movements (3-4 Hz), it appears that the rhythm is controlled and the motor cortices showed sustained EEG activation and continuous coupling.     

Frequency response of human vestibular reflexes characterized by stochastic stimuli

Stochastic vestibular stimulation (SVS) can be used to study the postural responses to unpredictable vestibular perturbations. The present study seeks to determine if stochastic vestibular stimulation elicits lower limb muscular responses and to estimate the frequency characteristics of these vestibulo-motor responses in humans. Fourteen healthy subjects were exposed to unpredictable galvanic currents applied on their mastoid processes while quietly standing (±3 mA, 0–50 Hz). The current amplitude and stimulation configuration as well as the subject's head position relative to their feet were manipulated in order to determine that: (1) the muscle responses evoked by stochastic currents are dependent on the amplitude of the current, (2) the muscle responses evoked by stochastic currents are specific to the percutaneous stimulation of vestibular afferents and (3) the lower limb muscle responses exhibit polarity changes with different head positions as previously described for square-wave galvanic vestibular stimulation (GVS) pulses. Our results revealed significant coherence (between 0 and 20 Hz) and cumulant density functions (peak responses at 65 and 103 ms) between SVS and the lower limbs' postural muscle activity. The polarity of the cumulant density functions corresponded to that of the reflexes elicited by square-wave GVS pulses. The SVS–muscle activity coherence and time cumulant functions were modulated by current amplitude, electrode position and head orientation with respect to the subject's feet. These findings strongly support the vestibular origin of the lower limb muscles evoked by SVS. In addition, specific frequency bandwidths in the stochastic vestibular signal contributed to the early (12–20 Hz) and late components (2–10 Hz) of the SVS-evoked muscular responses. These frequency-dependent SVS-evoked muscle responses support the view that the biphasic muscle response is conveyed by two distinct physiological processes.     

Cortico-cortical coupling patterns during dual task performance

We investigated the neural correlates of dual task performance using EEG coherence as a measure of the functional coupling between cortical regions. Nine healthy participants performed a rhythmical movement with the right hand and an isometric contraction with the left hand, either initiated simultaneously or successively. EEG data revealed that dual task performance was associated with stronger coherence in left hemispheric and mesial areas than the sum of the tasks performed separately in the beta (>12–30 Hz), but not alpha (8–12 Hz), band. This effect was more pronounced when the two assignments were initiated simultaneously, as opposed to successively. The data demonstrate that the pattern of cortico-cortical coupling during bimanual actions is not just the sum of that associated with its component parts, but is increased according to coordinative demands and processing load.     

Hippocampal network patterns of activity in the mouse

Genetic engineering of the mouse brain allows investigators to address novel hypotheses in vivo. Because of the paucity of information on the network patterns of the mouse hippocampus, we investigated the electrical patterns in the behaving animal using multisite silicon probes and wire tetrodes. Theta (6-9 Hz) and gamma (40-100 Hz) oscillations were present during exploration and rapid eye movement sleep. Gamma power and theta power were comodulated and gamma power varied as a function of the theta cycle. Pyramidal cells and putative interneurons were phase-locked to theta oscillations. During immobility, consummatory behaviors and slow-wave sleep, sharp waves were present in cornu ammonis region CA1 of the hippocampus stratum radiatum associated with 140-200-Hz "ripples" in the pyramidal cell layer and population burst of CA1 neurons. In the hilus, large-amplitude "dentate spikes" occurred in association with increased discharge of hilar neurons. The amplitude of field patterns was larger in the mouse than in the rat, likely reflecting the higher neuron density in a smaller brain. We suggest that the main hippocampal network patterns are mediated by similar pathways and mechanisms in mouse and rat.     

Functional cortico-muscular coupling during upright standing in athletes and nonathletes: a coherence electroencephalographic-electromyographic study

We tested the hypothesis that functional cortico-muscular coupling of brain rhythms is implied in the control of lower limb muscles for upright standing. Electroencephalographic (EEG; Be-plus Eb-Neuro) and electromyographic (EMG) data were recorded in 18 fencing and 19 karate elite athletes, 14 karate amateurs, and 9 non-athletes, during quiet upright standing with open and closed eyes conditions. Cortico-muscular coupling was evaluated by computing EEG-EMG spectral coherence and directed transfer function (DTF). Body sway area did not differ among the groups. In non-athletes, the EEG-EMG coherence (gastrocnemius lateralis) at centro-parietal and parasylvian alpha rhythms (about 8-12 Hz) was higher during the open than closed eyes condition. This was not true in the elite athletes. At the same alpha rhythms, the sport amateurs presented values halfway between the non-athletes and elite athletes. Finally, the DTF was higher for cortico-muscular than muscular-cortical direction. These results suggest that visual information affects cortico-muscular coherence at 8-12 Hz in non-athletes and amateur athletes but not in elite athletes. In elite athletes, this might be due to a long training for the control of equilibrium based on proprioceptive and tactile inputs.     

Membrane capacitance of cortical neurons and glia during sleep oscillations and spike-wave seizures

Dual intracellular recordings in vivo were used to disclose relationships between cortical neurons and glia during spontaneous slow (<1 Hz) sleep oscillations and spike-wave (SW) seizures in cat. Glial cells displayed a slow membrane potential oscillation (<1 Hz), in close synchrony with cortical neurons. In glia, each cycle of this oscillation was made of a round depolarizing potential of 1.5-3 mV. The depolarizing slope corresponded to a steady depolarization and sustained synaptic activity in neurons (duration, 0.5-0.8 s). The repolarization of the glial membrane (duration, 0.5-0.8 s) coincided with neuronal hyperpolarization, associated with disfacilitation, and suppressed synaptic activity in cortical networks. SW seizures in glial cells displayed phasic events, synchronized with neuronal paroxysmal potentials, superimposed on a plateau of depolarization, that lasted for the duration of the seizure. Measurements of the neuronal membrane capacitance during slow oscillating patterns showed small fluctuations around the resting values in relation to the phases of the slow oscillation. In contrast, the glial capacitance displayed a small-amplitude oscillation of 1-2 Hz, independent of phasic sleep and seizure activity. Additionally, in both cell types, SW seizures were associated with a modulatory, slower oscillation ( approximately 0.2 Hz) and a persistent increase of capacitance, developing in parallel with the progression of the seizure. These capacitance variations were dependent on the severity of the seizure and the distance between the presumed seizure focus and the recording site. We suggest that the capacitance variations may reflect changes in the membrane surface area (swelling) and/or of the interglial communication via gap junctions, which may affect the synchronization and propagation of paroxysmal activities.     

基于表面肌电非负矩阵分解与一致性的肌间协同耦合关系研究

肌肉协同模型是神经产生并控制运动的低维度结构,探讨不同动作任务下的表面肌电信号(sEMG)间的相干性分析,可以体现相应肌群的协同耦合关系,进而能从神经控制运动与肌肉相互配合协调的角度揭示运动产生与执行规律。组织8名年轻健康受试者(男女均半、20～24岁)进行上肢腕部屈、伸实验,采集动作时相应肌群的sEMG数据,引入非负矩阵分解(NMF)方法分析肌间协同性,并进一步对协同性较高的肌群采用一致性分析方法,研究信号beta(15~35 Hz)和gamma(35～60 Hz)频段的耦合强度关系,探讨腕部伸屈动作下不同受试者之间的协同耦合性差异。结果表明:腕伸动作下,主动肌桡侧腕短伸肌(ECR)、指伸肌(ED)、尺侧腕伸肌(ECU)、肱桡肌(B)在协同模块W₅中具有协同关系,且肌间耦合强度显著(P<0.05),beta频段与gamma频段一致性显著面积相差较大(1.261±0.966);腕屈动作下,分别在协同模块公式中存在具有协同关系的肌肉对,且肌肉间耦合强度显著(P<0.001),在beta和gamma频段一致性显著面积相差较小(0.412±0.163),但主动肌桡侧腕屈肌、指浅屈肌间不具有协同性,耦合关系较弱。以上说明:神经控制运动的方式不同,体现为肌肉协同耦合关系有所差异;在同一协同模块中,协同性较高的肌肉间耦合关系较强,揭示神经控制运动规律与肌肉相互配合方式;运用此方法进行肌间协同耦合联合分析,可望深入揭示中枢神经模块化协同控制运动机制,进一步为运动障碍患者功能分析和评价提供科学依据。