基于径向基函数神经网络的多电极阵列信号脉冲电位的分类

通过径向基函数神经网络的分析,对神经元脉冲电位信号提出了新的分类方法。对原始信号进行峰电位检测,获得脉冲电位信号样本,以主成分进行预分类,选取与类中心方差小的典型脉冲电位集合作为径向基网络的训练样本,让神经网络进行自适应学习,以实现对原始信号的分类。仿真结果表明,在对模拟的脉冲电位信号进行分类时此方法的错误率比主成分聚类法和形状聚类法小。多电极细胞外记录的海马神经元细胞电活动信号应用此方法分类也取得了较好的效果。     

Spike sorting by a minimax reduced feature set based on finite differences

Spikes are classified according to their finite differences in various orders. The fundamental idea that makes it work is that finite differences can extract and isolate features from spikes. This method showed better sorting quality and involved less labor than the methods of principal component analysis, original reduced feature set, and wavelet-based spike classifiers.     

Spike detection in biomedical signals using midprediction filter

Spikes such as QRS complex in ECG, epileptic seizures in EEG, fine crackles in vesicular sound and glottal closure instants in voiced sound are of diagnostic importance. Various methods of spike detection use the amplitude and frequency characteristics of the spikes. Because of the high frequency content, the spikes appear in the error signal when a linear prediction filtering scheme is used. The authors use the method of midprediction filtering for the detection of the spikes. In this method, the present sample is predicted as a weighted average of p recent past and p immediate future samples. The symmetrical nature of midprediction causes the spikes to appear in the error signal with their original basewidths. This can help in improving the reliability of spike detection, as both the amplitude and the duration of the spike can be considered as decision making parameters. It is observed that the high frequency gain of the midprediction filter is higher compared to the high frequency gain of the LPC or endprediction filter. As a result, this method works better than linear prediction for the detection of spikes.     

Dendritic spikes in Purkinje cells of the guinea pig cerebellum studied in vitro

Summary Extracellular spikes were recorded simultaneously from dendrites and somata of Purkinje cells in thin cerebellar sections. Spontaneously occurring dendritic spikes were biphasic with the initial phase positive. Triphasic dendritic spikes with a large negative phase appeared during electrophoretic application of glutamate. In media containing procaine, tetrodotoxin, or high concentrations of KCl, negative dendritic spikes occurred whereas soma spikes were abolished. The negative dendritic spikes were suppressed by CoCl₂ or MnCl₂. Electrical stimulation elicited climbing fibre responses in somata and large negative waves in dendrites. Spikes of dendritic origin were different from those reflecting electrotonic spread of soma spikes. The relation between soma spikes and active dendritic spikes is discussed.     

基于小波变换和非线性能量算子的神经元放电检测

微电极导向的立体定向手术中,微电极记录的神经元放电信号噪声干扰严重,信噪比变化大,影响着神经元放电脉冲的分析。利用小波变换和非线性能量算子相结合的一种新的方法能检测出神经元放电。通过对临床不同病人、不同特点的神经元放电信号处理,结果表明:该方法能成功地检测出细胞放电,提取出放电波形。     

Neural codes for perceptual discrimination in primary somatosensory cortex

We sought to determine the neural code(s) for frequency discrimination of vibrotactile stimuli. We tested five possible candidate codes by analyzing the responses of single neurons recorded in primary somatosensory cortex of trained monkeys while they discriminated between two consecutive vibrotactile stimuli. Differences in the frequency of two stimuli could be discriminated using information from (i) time intervals between spikes, (ii) average spiking rate during each stimulus, (iii) absolute number of spikes elicited by each stimulus, (iv) average rate of bursts of spikes or (v) absolute number of spike bursts elicited by each stimulus. However, only a spike count code, in which spikes are integrated over a time window that has most of its mass in the first 250 ms of each stimulus period, covaried with behavior on a trial-by-trial basis, was consistent with psychophysical biases induced by manipulation of stimulus duration, and produced neurometric discrimination thresholds similar to behavioral psychophysical thresholds.     

Epileptic seizure prediction based on EEG spikes detection of ictal-preictal states

Epileptic seizures are known for their unpredictable nature. However, recent research provides that the transition to seizure event is not random but the result of evidence accumulations. Therefore, a reliable method capable to detect these indications can predict seizures and improve the life quality of epileptic patients. Seizures periods are generally characterized by epileptiform discharges with different changes including spike rate variation according to the shapes, spikes, and the amplitude. In this study, spike rate is used as the indicator to anticipate seizures in electroencephalogram (EEG) signal. Spikes detection step is used in EEG signal during interictal, preictal, and ictal periods followed by a mean filter to smooth the spike number. The maximum spike rate in interictal periods is used as an indicator to predict seizures. When the spike number in the preictal period exceeds the threshold, an alarm is triggered. Using the CHB-MIT database, the proposed approach has ensured 92% accuracy in seizure prediction for all patients.     

帕金森病人苍白球神经元放电的自适应阈值检测

自动选取合适的阈值以适应不同信噪比的信号,达到检测神经元放电的目的。依据微电极记录的信号,采用闭环方式自动递归调整阈值,逐次检测神经元放电。对合成的模拟神经放电信号及临床手术中微电极记录的112个病人的神经元放电信号处理,检测出了不同信噪比信号中的神经元放电脉冲,这些放电脉冲反映了神经核团的电生理特征。根据检测的神经元放电,可以对不同神经核团放电特征进行客观定量的分析,准确识别手术中微电极所在的神经核团,对于指导靶点定位具有重要的意义。     

基于人工神经网络的癫痫棘波检测方法

脑电癫痫特征波的自动提取对于患者的诊断具有重要的意义。提出一种时频分析与Jensen函数相结合的方法进行棘波检测，然后提取出棘波的波形特征，并通过人工神经网络进行进一步的判决，从而降低棘波检测的误检率。在对真实的癫痫脑电信号（EEG）的仿真实验中，该方法取得了较好的结果。     

Ventral hippocampus spikes during sleep, wakefulness, and arousal in the cat

The relationship between high amplitude (100--300- micro V) spike potentials (50--100 msec duration) in the ventral hippocampus (VH) and sleep-wakefulness stages was investigated. Forty-eight hours of continuous recordings taken from 5 chronically implanted cats were quantitatively scored for stage by digitized outputs of integrated EEG and electromyographic signals and for VH spikes by automatic devices. (1) A very strong relationship was observed between VH spike rates and EEG stage. Spikes were rare during wakefulness and paradoxical sleep (PS). They were always most frequent during nonrapid eye movement (NREM) sleep stages, progressively increasing through drowsiness, moderate amplitude slow wave activity, and high amplitude slow wave activity. (2) VH spike rates varied inversely with level of behavioral arousal within wakefulness. Rates were lowest during the presentation of novel experimental stimuli, higher during spontaneous movement, and highest during quiet wakefulness. (3) VH spikes anticipated stage changes independent of the quantified EEG. Spike rates increased from previous baseline levels in the 30 sec epoch of waking immediately preceding NREM sleep onset and in the transition period between PS and NREM sleep. They decreased significantly from previous base-line levels in the 30 sec epoch of NREM sleep preceding either waking or PS. These results show that the VH spike is a potentially useful noncortical indicator of NREM sleep. Within wakefulness and in the anticipation of stage changes it can be a more sensitive indicator of sleep processes or arousal level than the EEG.     

Spike-timing precision underlies the coding efficiency of auditory receptor neurons

Sensory systems must translate incoming signals quickly and reliably so that an animal can act successfully in its environment. Even at the level of receptor neurons, however, functional aspects of the sensory encoding process are not yet fully understood. Specifically, this concerns the question how stimulus features and neural response characteristics lead to an efficient transmission of sensory information. To address this issue, we have recorded and analyzed spike trains from grasshopper auditory receptors, while systematically varying the stimulus statistics. The stimulus variations profoundly influenced the efficiency of neural encoding. This influence was largely attributable to the presence of specific stimulus features that triggered remarkably precise spikes whose trial-to-trial timing variability was as low as 0.15 ms--one order of magnitude shorter than typical stimulus time scales. Precise spikes decreased the noise entropy of the spike trains, thereby increasing the rate of information transmission. In contrast, the total spike train entropy, which quantifies the variety of different spike train patterns, hardly changed when stimulus conditions were altered, as long as the neural firing rate remained the same. This finding shows that stimulus distributions that were transmitted with high information rates did not invoke additional response patterns, but instead displayed exceptional temporal precision in their neural representation. The acoustic stimuli that led to the highest information rates and smallest spike-time jitter feature pronounced sound-pressure deflections lasting for 2-3 ms. These upstrokes are reminiscent of salient structures found in natural grasshopper communication signals, suggesting that precise spikes selectively encode particularly important aspects of the natural stimulus environment.     

Gamma->alpha linkage and persistent firing of Ia fibers by pudendal nerve stimulation in the decerebrate cat

The sensory pudendal nerve (SPN) was stimulated in decerebrate female cats. Spikes of single Ia muscle spindle afferents from the medial gastrocnemius (MG) muscle were recorded in dorsal root filaments. Electroneurography (ENG) was recorded in a cut nerve filament to the MG muscle; MG electromyography (EMG) was also recorded. Single shock to SPN induced discharges of small ENG spikes (SS) with similar amplitude to that of gamma spikes elicited by ventral root stimulation. Thus SS were identified as gamma spikes. The latency of the gamma discharge was approximately 15 ms. As expected, the onset of the gamma discharge preceded a discharge of Ia spikes; the time difference between both discharges was approximately 5 ms. After the initial bursts, the Ia and the gamma activities paused during 20-30 ms but later increased again to last approximately 1 s. After the shock, the EMG activity was depressed during approximately 50 ms; later, motor-unit spikes may show transient activation. Thus the onset of the gamma activation preceded the activation of motor units (gamma-->alpha link). Trains of shocks (1 or 100 Hz) to SPN induced a sustained increase in the frequency of gamma spikes, Ia spikes, and motor units that outlasted the train by 20-120 s. The sustained firing of Ia fibers might trigger or help to trigger and maintain the response of alpha-motoneurons.     

Biochemical genetics of the pentose phosphate cycle: human ribose 5-phosphate isomerase (RPI) and ribulose 5-phosphate 3-epimerase (RPE)

1. Staining procedures are described for the detection after starch-gel electrophoresis of ribose-5-phosphate isomerase (RPI) and ribulose 5-phosphate 3-epimerase (RPE). 2. Both RPI and RPE were detected in all human tissues including red cells, lymphocytes and fibroblasts. 3. No evidence was found for more than one structural gene locus for either enzyme. 4. NO allelic variants of either enzyme were found in erythrocyte lysates from over 200 unrelated individuals. 5. Preliminary data are presented which suggest that differences in tissue RPE isozyme patterns may be due to endogenous proteolytic activity. 6. Electrophoretic analysis of RPE and RPI isozyme patterns in extracts of man/mouse hybrid cells indicates that RPE is probably a dimer and RPI may also be polymeric.     

The neuronal encoding of information in the brain

We describe the results of quantitative information theoretic analyses of neural encoding, particularly in the primate visual, olfactory, taste, hippocampal, and orbitofrontal cortex. Most of the information turns out to be encoded by the firing rates of the neurons, that is by the number of spikes in a short time window. This has been shown to be a robust code, for the firing rate representations of different neurons are close to independent for small populations of neurons. Moreover, the information can be read fast from such encoding, in as little as 20 ms. In quantitative information theoretic studies, only a little additional information is available in temporal encoding involving stimulus-dependent synchronization of different neurons, or the timing of spikes within the spike train of a single neuron. Feature binding appears to be solved by feature combination neurons rather than by temporal synchrony. The code is sparse distributed, with the spike firing rate distributions close to exponential or gamma. A feature of the code is that it can be read by neurons that take a synaptically weighted sum of their inputs. This dot product decoding is biologically plausible. Understanding the neural code is fundamental to understanding not only how the cortex represents, but also processes, information.     

Three types of sympathetic preganglionic neurones with different electrophysiological properties are identified by intracellular recordings in the cat

Intracellular recordings were obtained from sympathetic preganglionic neurones (SPN) of the third thoracic segment in cats. Based on differences in their active and passive electrophysiological properties, three different types of SPNs were discerned: Type A neurones had a high resting membrane potential (RMP) (-60 to -86 mV) and a low input resistance (RN) 12-23 M omega). Action potentials of these neurones had a pronounced IS-SD inflexion and a prominent shoulder in their falling phase. Spikes were rarely generated from the on-going synaptic activity. Type B neurones had a lower RMP (-48 to -65 mV) and a higher RN (21-37 M omega). Their action potentials were characterized by an after-depolarization; they showed a slight IS-SD inflexion and a less pronounced shoulder in their falling phase. The after-depolarization was abolished by membrane hyperpolarization in a time dependent way. A hyperpolarization of at least 50 ms duration was required for its abolition. The after-depolarization was also abolished during repetitive discharges. In most of these neurones spikes were generated at irregular intervals and low rates (0.06-4.6 spikes/s) from the synaptic activity. Type C neurones were similar to type B neurones, but their action potentials did not show the after-depolarization. Additionally, spikes were generated at fairly regular intervals and rather high rates (0.8-6.5 spikes/s). The rate of spike repolarization of all neurones was markedly increased by hyperpolarization and decreased by membrane depolarization. Current-voltage curves of some type B and C neurones showed a marked rectification upon membrane hyperpolarization.(ABSTRACT TRUNCATED AT 250 WORDS)     

基于关联维数的神经元动作电位特征提取与分类研究

神经元动作电位模式分类是动作电位序列分析和解码的基础.由于神经元动作电位信号波形隐藏着动作电位的特征信息,而关联维数是度量波形不规则程度的一种手段,因此基于神经元动作电位信号的波形差异,提出一种基于关联维数对神经元动作电位进行特征提取的新方法.首先,对采集到的神经元动作电位信号进行相空间重构;然后,在重构的相空间中,以关联维数作为对非同源动作电位信号的特征进行描述;最终,结合K均值算法,对神经元动作电位实现无监督模式分类.仿真和真实数据实验结果表明:该方法分类的准确率较高,且稳定性较好,仿真数据分类错分率基本稳定在4.9％以内,真实数据的分类能较大程度地贴近人工分类的结果,因此用来代替人工分类具有一定的可行性.     

Electrophysiological properties of hypoglossal motoneurons of guinea-pigs studied in vitro

Intracellular recordings were made from the hypoglossal nuclear complex in brain slices from guinea-pigs. Retrograde transport of horseradish peroxidase from the tongue confirmed the identity of the visually identified hypoglossal nucleus. Eighteen neurons were stained by intracellular electrophoresis of Lucifer Yellow through the recording pipette. Two types of neurons were encountered, motoneurons with maximal discharge rates of 90 Hz and another type with maximal discharge rates of 250 Hz. Motoneurons were prevalent in the hypoglossal nucleus and the other type prevailed in the adjoining nucleus prepositus hypoglossi. In both nuclei the two types were mixed. Antidromic spikes elicited from hypoglossal root fibres had initial segment and somatodendritic components. Electrical stimulation of the reticular matter dorsolateral to the hypoglossal nucleus elicited excitatory postsynaptic potentials and strychnine sensitive inhibitory postsynaptic potentials. Motoneurons responded to depolarizing current pulses with a train of spikes. The initial spike interval was much shorter than the rest and fast adaptation occurred over three to four intervals. Slow adaptation was most prominent when the neuron was depolarized and discharged at a high rate. High threshold calcium spikes were evoked by depolarizing pulses when sodium spikes were blocked by tetrodotoxin and the potassium conductance reduced by tetraethylammonium bromide. Motoneurons discharged in a single range, inflections on the frequency-current plot being absent. Spikes and spike trains evoked by depolarizing pulses were followed by afterhyperpolarizations with fast and slow parts. The fast phase was eliminated by tetraethyl-ammonium bromide, possibly because the delayed rectifier was involved. A calcium dependent potassium conductance was probably involved in the slow phase, because it was sensitive to inorganic calcium blockers. The amplitude of the afterhyperpolarization following trains of spikes depended on the frequency of the preceding spikes. At constant frequency, the amplitude depended, in addition, on the strength of stimuli arising from different hyperpolarized potentials. Afterdepolarizing potentials were absent. Lissajous plots of double ramp current stimulation showed anomalous rectification between resting potential and spike threshold. The rectification was sensitive to inorganic calcium blockers. Subthreshold responses showed initial sags and rebound responses in all healthy cells and these were eliminated by caesium. Barium, substituted for calcium, unleashed a depolarizing plateau potential sensitive to tetrodotoxin, indicating the presence of a persistent sodium conductance.

The membrane of hypoglossal motoneurons contains voltage dependent conductances in the voltage range around resting potential and spike threshold. These conductances provide for effective switching between the discharging and the non-discharging state of the motoneuron.     

Excess synchrony in motor cortical neurons provides redundant direction information with that from coarse temporal measures

Previous studies have shown that measures of fine temporal correlation, such as synchronous spikes, across responses of motor cortical neurons carries more directional information than that predicted from statistically independent neurons. It is also known, however, that the coarse temporal measures of responses, such as spike count, are not independent. We therefore examined whether the information carried by coincident firing was related to that of coarsely defined spike counts and their correlation. Synchronous spikes were counted in the responses from 94 pairs of simultaneously recorded neurons in primary motor cortex (MI) while monkeys performed arm movement tasks. Direct measurement of the movement-related information indicated that the coincident spikes (1- to 5-ms precision) carry approximately 10% of the information carried by a code of the two spike counts. Inclusion of the numbers of synchronous spikes did not add information to that available from the spike counts and their coarse temporal correlation. To assess the significance of the numbers of coincident spikes, we extended the stochastic spike count matched (SCM) model to include correlations between spike counts of the individual neural responses and slow temporal dependencies within neural responses (approximately 30 Hz bandwidth). The extended SCM model underestimated the numbers of synchronous spikes. Therefore as with previous studies, we found that there were more synchronous spikes in the neural data than could be accounted for by this stochastic model. However, the SCM model accounts for most (R(2) = 0.93 +/- 0.05, mean +/- SE) of the differences in the observed number of synchronous spikes to different directions of arm movement, indicating that synchronous spiking is directly related to spike counts and their broad correlation. Further, this model supports the information theoretic analysis that the synchronous spikes do not provide directional information beyond that available from the firing rates of the same pool of directionally tuned MI neurons. These results show that detection of precisely timed spike patterns above chance levels does not imply that those spike patterns carry information unavailable from coarser population codes but leaves open the possibility that excess synchrony carries other forms of information or serves other roles in cortical information processing not studied here.     

Wiener filtering of surface EMG with a priori SNR estimation toward myoelectric control for neurological injury patients

Voluntary surface electromyogram (EMG) signals from neurological injury patients are often corrupted by involuntary background interference or spikes, imposing difficulties for myoelectric control. We present a novel framework to suppress involuntary background spikes during voluntary surface EMG recordings. The framework applies a Wiener filter to restore voluntary surface EMG signals based on tracking a priori signal to noise ratio (SNR) by using the decision-directed method. Semi-synthetic surface EMG signals contaminated by different levels of involuntary background spikes were constructed from a database of surface EMG recordings in a group of spinal cord injury subjects. After the processing, the onset detection of voluntary muscle activity was significantly improved against involuntary background spikes. The magnitude of voluntary surface EMG signals can also be reliably estimated for myoelectric control purpose. Compared with the previous sample entropy analysis for suppressing involuntary background spikes, the proposed framework is characterized by quick and simple implementation, making it more suitable for application in a myoelectric control system toward neurological injury rehabilitation.     

SADE3: an effective system for automated detection of epileptiform events in long-term EEG based on context information

Interictal spike detection is a time-consuming, low-efficiency task, but is important to epilepsy diagnosis. Automated systems reported to date usually have their practical efficacy compromised by elevated rates of false-positive detections per minute, which are caused mainly by the influence of artifacts (such as noise activity and ocular movements) and by the adoption of single or simple approaches. This work describes the development of a hybrid system for automatic detection of spikes in long-term electroencephalogram (EEG), named System for Automatic Detection of Epileptiform Events in EEG (SADE(3)), which uses wavelet transform, neural networks and artificial intelligence procedures to recognize epileptic and to reject non-epileptic activity. The system's pre-processing stage filters the EEG epochs with the Coiflet wavelet function, which showed the closest correlation to epileptogenic (EPG) activity, in opposition to some other wavelet functions that did not correlate with these events. In contrast to current attempts using continuous wavelet transform, we chose to work with fast wavelet transform to reduce processing time and data volume. Detail components at appropriate decomposition levels were used to accentuate spikes, sharp waves, high-frequency noise activity and ocular artifacts. These four detailed components were used to train four specialized neural networks, designed to detect and classify the EPG and non-EPG events. An expert module analyzes the networks' outputs, together with multichannel and context information and concludes the detection. The system was evaluated with 126,000 EEG epochs, obtained from seven different patients during long-term monitoring, under diverse behavior and mental states. More than 6,721 spikes and sharp waves were previously identified by three experienced human electroencephalographers. In these tests, the SADE(3) system simultaneously achieved 70.9% sensitivity, 99.9% specificity and a rate of 0.13 false-positives per minute, indicating its usefulness and low vulnerability to artifact influence. After tests, the SADE(3) system showed itself to be able to process bipolar cortical EEG records, from long-term monitoring, up to 32 channels, without any data preparation or event positioning. At the same time, SADE(3) revealed a high capacity to reject non-epileptic paroxysms, robustness in relation to a variety of spike morphologies, flexibility in adjustment of performance rates and the capacity to actually save time during EEG reading. Furthermore, it can be adapted to other applications for pattern recognition, with simple adjustments.