Correspondence between the location of evoked potential generators and sites of maximal sensitivity to stimulation

The potential recorded by a set of electrodes as an action potential traverses a small axonal segment is proportional to the transmembrane potential produced during stimulation of that axon segment by the same set of recording electrodes, under certain circumstances. First, the membrane must have a constant thickness which is so small that the difference between the surface area of the inner and outer surfaces is minimal. Second, all media must be linear. Third, there must be a monotonically increasing relation between the mean transmembrane potential induced by a stimulus and the maximum transmembrane potential. Fourth, as each axon segment depolarizes, the transmembrane current and change in membrane potential during this time are same. This principle remains true for magnetic stimulation and recording as long as currents generated at the boundaries between regions of differing conductivity outside the axon contribute minimally to the field at the axon. This allows the identification of the point at which an action potential generates a maximal extracellular potential as the point that is stimulated with the lowest threshold.     

Modeling and estimation of single evoked brain potential components

Presents a novel approach to solving the single-trial evoked-potential estimation problem. Recognizing that different components of an evoked potential complex may originate from different functional brain sites and can be distinguished according to their respective latencies and amplitudes, the authors propose an estimation approach based on identification of evoked potential components on a single-trial basis. The estimation process is performed in 2 stages: first, an average evoked potential is calculated and decomposed into a set of components, with each component serving as a subtemplate for the next stage; then, the single measurement is parametrically modeled by a superposition of an emulated ongoing electroencephalographic activity and a linear combination of latency and amplitude-corrected component templates. Once optimized, the model provides the 2 assumed signal contributions, namely the ongoing brain activity and the single evoked brain response. The estimator's performance is analyzed analytically and via simulation, verifying its capability to extract single components at low signal-to-noise ratios typical of evoked potential data. Finally, 2 applications are presented, demonstrating the improved analysis capabilities gained by using the proposed approach. The first application deals with movement related brain potentials, where a change of the single evoked response due to external loading is detected. The second application involves cognitive event-related brain potentials, where a dynamic change of 2 overlapping components throughout the experimental session is detected and tracked     

Estimating regional brain activity from evoked potential fields onthe scalp

Potential fields on the surface of the brain were estimated from discretely sampled scalp fields in human subjects. Relatively simple methods of linear algebra were combined with detailed anatomical information from magnetic resonance imaging. The method was verified using a tank model of the human head that encased a fully hydrated human skull in a polymer matrix of controlled resistivity matching that of human brain and scalp. Brain surface fields evoked by checkerboard contrast reversal spread less than their scalp field counterparts, and provided information helpful in localizing brain activity     

Visual evoked potential actuated brain computer interface: a brain-actuated cursor system

Flash visual evoked potential (FVEP), induced by OFF-to-ON flash, i.e. flash onset, in a light emitting diode (LED) was used to control four cursor movements (left, right, up, down), and left- and right-button clicks on a screen menu. ON or OFF duration in each flashing sequence was designed to be random so that all flashing sequences were mutually independent. Since FVEPs are time-locked and phase-locked to flash onsets of gazed LEDs, segmenting EEG signals based on the flash onsets of each flashing sequence followed by averaging will sharpen epochs evoked by gazed LEDs. Four inexperienced subjects were asked to generate a sequence of cursor commands. Mean recognition and transfer rates were 88% and 3.74 s/command, respectively.     

Multicategory classification of body surface potential maps

A statistical classification method is suggested for body surface potential maps (BSPM). The initial data reduction utilizes the Fourier expansion and time integration, resulting in physiological-oriented features. Based on Fischer's criterion, optimal discriminant vectors are used to map the features to an optimal subdomain. Experimental criteria determine the dimensionality of the subdomain and the number of features to be mapped into it. Classification is performed in two steps. In the first, a k-nearest neighbor (k-NN) rule is used for every two-category problem, the results of which are fed into a voting rule for final classification. The method is tested with 123 patients divided into four categories: normal (NR), ischemia (IS), myocardial infarction (MI), and left bundle branch block (LB) patients. The success is between 88% (for IS) and 100% (for LB) for QRS segment integration. Departure maps were used to explain the misclassified patterns.     

Time-varying adaptive filters for evoked potential estimation

Adaptive implementation of an optimal time-varying filter (TVF) for evoked potential (EP) estimation is addressed here. A data-adaptive scheme is used, which converges asymptotically to the optimal TVF solution. Two basic adaptive TVF's (ATVF's) are first introduced, namely least mean square (LMS) ATVF and recursive least-squares (RLS) ATVF. The latter converges much faster than the former. Since the basic ATVF's usually require a relatively large set of response trials to get a meaningful solution, a reduced-order ATVF is further presented and the corresponding LMS and RLS (including a fast RLS) adaptive algorithms are developed. To save memory, a truncated Fourier expansion is suggested to express approximately the time-sequenced weight-vectors of the ATVF's, resulting in a simplified reduced-order ATVF. Finally, extensive simulations are provided to confirm the superior performance of the ATVF's. The present ATVF's can be used as prefilters for latency-corrected average (LCA) processing to obtain more informative estimates of EP signals     

Topographic mapping of single sweep evoked potentials in the brain

Single trial analysis of brain-evoked potentials via stochastic parametric identification and filtering is here extended to multichannel recordings, leading to the topographic mapping of the brain activity elicited by a single stimulus, instead of the usual averaged mapping. The temporal dynamics of the subsequent sweeps in the protocol of a neurophysiologic experiment can thus be recovered and quantified also on its spatial characteristic.     

The potential for Laplacian maps to solve the inverse problem ofelectrocardiography

Presents a method to solve the inverse problem of electrocardiography using the Laplacian of the body surface potentials. The method presented is studied first using trade-off curves from a concentric spheres model representing a heart-torso system. Then a more conventional study is undertaken where a limited number of current dipoles are placed within the inner sphere and noise is added to the resulting potentials and Laplacians on the surface of the outer sphere. The results indicate that measurements of the outer surface Laplacian can more accurately reconstruct epicardial potentials than measurements of the outer surface potentials. The reconstructions are more accurate in that extrema are placed very close to their correct positions and multiple extrema and high potential gradients are recovered. Identical conclusions are observed in the presence of noise and even when the Laplacians are subject to greater noise than the potentials     

Individual identification technique using visual evoked potential signals

A new individual identification technique using visual evoked potential (VEP) signals is proposed. The technique uses fuzzy ARTMAP (FA) classification of gamma band VEP response from 61 channels extracted while the individual is seeing a single picture. All ten subjects tested are classified correctly with an overall maximum classification rate of 95% across 200 test patterns. The method could be developed into a stand-alone identification system or as an addition to existing identification systems, especially for identifying a group of individuals in a company or factory.     

基于FPGA的可编程视觉、听觉诱发电位刺激器

诱发电位是神经系统接受各种外界刺激后所产生的特异性电反应。它在中枢神经系统及周围神经系统的相应部位被检出,与刺激有锁时关系的电位变化,具有能定量及定位的特点,往往较常规脑电图检查有更稳定的效果,从而在诊断及研究神经系统各部位神经电生理变化方面,有重要作用。本项目通过产生特定频率的听觉和视觉刺激信号,使人脑产生诱发电位。医护人员可从诱发脑电中获取更多信息,并帮助其更好地对病情进行确诊。本刺激器可产生音频刺激和视频刺激,其中音频刺激包括发出短声、纯音、自己录制的声音等;视频刺激包括棋盘格翻转。刺激的时长、频率都可设定。本项目主要通过FPGA与相关芯片完成。使用平台为ALTERA公司的DE2开发平台。     

Development and evaluation of the piecewise Prony method for evoked potential analysis

A new method is presented to decompose nonstationary signals into a summation of oscillatory components with time varying frequency, amplitude, and phase characteristics. This method, referred to as piecewise Prony method (PPM), is an improvement over the classical Prony method, which can only deal with signals containing components with fixed frequency, amplitude and phase, and monotonically increasing or decreasing rate of change. PPM allows the study of the temporal profile of post-stimulus signal changes in single-trial evoked potentials (EPs), which can lead to new insights in EP generation. We have evaluated this method on simulated data to test its limitations and capabilities, and also on single-trial EPs. The simulation experiments showed that the PPM can detect amplitude changes as small as 10%, rate changes as small as 10%, and 0.15 Hz of frequency changes. The capabilities of the PPM were demonstrated using single electroencephalogram/EP trials of flash visual EPs recorded from one normal subject. The trial-by-trial results confirmed that the stimulation drastically attenuates the alpha activity shortly after stimulus presentation, with the alpha activity returning about 0.5 s later. The PPM results also provided evidence that delta activity undergoes phase alignment following stimulus presentation.     

EZ-USB FX2接口在诱发电位仪系统中的应用

随着外围设备的多样化和大量数据传输的需要,USB接口应用范围越来越广泛。介绍EZ-USB FX2接口在诱发电位仪系统中的应用。首先给出了整个诱发电位仪的总体设计,讨论了FPGA作为主芯片与EZ-USB FX2的硬件连接,在此基础上重点论述了基于Slave FIFO模式的EZ-USB FX2接口设计及相应固件程序开发。该应用实现了大脑诱发电位仪传输的高可靠性、高速化、小型化,具有良好的市场前景。     

Evaluating the noise in electrically evoked compound action potential measurements in cochlear implants

Electrically evoked compound action potentials (ECAPs) are widely used to study the excitability of the auditory nerve and stimulation properties in cochlear implant (CI) users. However, ECAP detection can be difficult and very subjective at near-threshold stimulation levels or in spread of excitation measurements. In this study, we evaluated the statistical properties of the background noise (BN) and the postaverage residual noise (RN) in ECAP measurements in order to determine an objective detection criterion. For the estimation of the BN and the RN, a method currently used in auditory brainstem response measurements was applied. The potential benefit of using weighted (Bayesian) averages was also examined. All estimations were performed with a set of approximately 360 ECAP measurements recorded from five human CI users of the CII or HiRes90K device (advanced bionics). Results demonstrated that the BN was normally distributed and the RN decreased according to the square root of the number of averages. No additional benefit was observed by using weighted averaging. The noise was not significantly different either at different stimulation intensities or across recording electrodes along the cochlea. The analysis of the statistical properties of the noise indicated that a signal-to-noise ratio of 1.7 dB as a detection criterion corresponds to a false positive detection rate of 1% with the used measurement setup.     

Noise reduction in brain evoked potentials based on third-order correlations

In this paper, we use third-order correlations (TOC) in developing a filtering technique for the recovery of brain evoked potentials (EPs). The main idea behind the presented technique is to pass the noisy signal through a finite impulse response filter whose impulse response is matched with the shape of the noise-free signal. It is shown that it is possible to estimate the filter impulse response on basis of a selected third-order correlation slice (TOCS) of the input noisy signal. This is justified by two facts. The first one is that the noise-free EPs can be modeled as a sum of damped sinusoidal signals and the selected TOCS preserve the signal structure. The second fact is that the TOCS is insensitive to both Gaussian noise and other symmetrically distributed non-Gaussian noise, (white or colored). Furthermore, the approach can be applied to either nonaveraged or averaged EP observation data. In the nonaveraged data case, the approach therefore preserves information about amplitude and latency changes. Both fixed and adaptive versions of the proposed filtering technique are described. Extensive simulation results are provided to show the validity and effectiveness of the proposed cumulant-based filtering technique in comparison with the conventional correlation-based counterpart.     

Multi-resolution dyadic wavelet denoising approach for extraction of visual evoked potentials in the brain

More powerful techniques need to be developed to extract small and weak visual evoked potentials (VEPs) from the spontaneous cerebral electric activity EEG. The authors present a wavelet decomposition algorithm suitable for identification and detection of very weak VEPs. The cross-correlation analysis between Daubechies wavelet (i.e. dbN) functions /spl psi//sub N/(t), for N=4, 5 ,...,10 and a representative noiseless VEP signal is performed to choose the proper wavelet function, say that with maximum correlation coefficient (highest resemblance) with respect to the representative VEP signal sequence. In this way, the specific choice of the best wavelet prototype function is no longer arbitrary for the application of obtaining pattern reversal VEPs. Extensive clinical experiments have demonstrated that the multiresolution wavelet analysis method can identify and estimate the peak latency of VEP signal well, with only a much reduced trial of ensemble averaging (EA) required. The major advantages of the wavelet transform are that it can 'zoom-in' to time discontinuities, and that orthonormal bases, localised in time and frequency, can be constructed. With this zoom-in property of the wavelet analysis, the irregularities or abnormalities of signals can easily be detected. Also the characteristics of EP signals can be captured by means of wavelet analysis, which can be further used for the detection and recognition of the abnormalities in the brain.     

脉冲发生器的评价

最近几年,人们研制出了新的测试技术,以迎接业界新标准快速发展所带来的挑战,例如半导体和通信技术。脉冲测试就是其中一种技术。     

Deterioration of average evoked potential waveform due toasynchronous averaging and its compensation

In order to improve the signal-to-noise ratio of evoked potentials, the responses to repetitive stimuli are usually recorded, and the averaging method is applied to them. If each starting point of the averaging varies with respect to the response because of asynchronous sampling of the measurement data, the average waveform of the evoked potential signal is distorted by the averaging. We analyzed the asynchronous averaging in the frequency domain and derived a relationship between the fluctuating time and the degree of the deterioration. By using this relationship, a required sampling rate was derived to ensure the accuracy of the averaging. Furthermore, we also deduced a compensation procedure for the asynchronous averaging in case of coarse sampling.