小儿先心病中EEG和RAEP的临床评价

目的 :评价先心病儿脑电图 (EEG)、脑干听觉诱发电位 (BAEP)的变化。方法 :对 3 0例先心病儿童EEG、BAEP的变化进行对比观察 ,并以 3 0名健康儿童为对照组。结果 :1.EEG :发绀组 (CCHD)异常率为 80 %( 8/ 10 ) ,非发绀组 (NCCHD)异常率为 3 0 %( 6/ 2 0 ) ,差异显著 (P <0 .0 5 )。2 .BAEP :CCHD组异常率为 10 0 %( 10 / 10 ) ,NCCHD异常率为 65 %( 13 / 2 0 ) ,差异显著 (P<0 .0 5 ) ,Ⅴ波潜伏期 (PL)、Ⅲ -Ⅴ、Ⅰ -Ⅴ波峰间潜伏期 (IPL)先心病患儿与对照组比较 ,CCHD组显著延长 (P <0 .0 5 )。 3 .EEG与BAEP :EEG异常者BAEP均异常 ( 10 0 %) ,EEG正常者BAEP有 5 6.3 %异常。结论 :1、先心病患儿伴有脑功能异常 ,CCHD较NCCHD显著。 2、EEG与BAEP均可反映脑功能异常改变 ,但非完全同步 ,BAEP似乎较为敏感。     

Error-related EEG potentials generated during simulated brain-computer interaction.

Brain-computer interfaces (BCIs) are prone to errors in the recognition of subject's intent. An elegant approach to improve the accuracy of BCIs consists in a verification procedure directly based on the presence of error-related potentials (ErrP) in the electroencephalogram (EEG) recorded right after the occurrence of an error. Several studies show the presence of ErrP in typical choice reaction tasks. However, in the context of a BCI, the central question is: "Are ErrP also elicited when the error is made by the interface during the recognition of the subject's intent?"; We have thus explored whether ErrP also follow a feedback indicating incorrect responses of the simulated BCI interface. Five healthy volunteer subjects participated in a new human-robot interaction experiment, which seem to confirm the previously reported presence of a new kind of ErrP. However, in order to exploit these ErrP, we need to detect them in each single trial using a short window following the feedback associated to the response of the BCI. We have achieved an average recognition rate of correct and erroneous single trials of 83.5% and 79.2%, respectively, using a classifier built with data recorded up to three months earlier.     

Quasi-reflectionless potentials in semiconductor nanoheterostructures

A new class of reflectionless potentials associated with low-energy scattering is considered. Using the expansion of the transmittance of the system in terms of wave vectors in the region of parameters corresponding to the transition of localized states to the continuous spectrum, the effective parameters of low-energy scattering are determined. For heterostructures formed by a stepwise distribution of the components, the parameters providing the conditions for the lack of reflection in the low-energy region are determined.     

Combining wavelet analysis and Bayesian networks for the classification of auditory brainstem response.

The auditory brainstem response (ABR) has become a routine clinical tool for hearing and neurological assessment. In order to pick out the ABR from the background EEG activity that obscures it, stimulus-synchronized averaging of many repeated trials is necessary, typically requiring up to 2000 repetitions. This number of repetitions can be very difficult, time consuming and uncomfortable for some subjects. In this study, a method combining wavelet analysis and Bayesian networks is introduced to reduce the required number of repetitions, which could offer a great advantage in the clinical situation. 314 ABRs with 64 repetitions and 155 ABRs with 128 repetitions recorded from eight subjects are used here. A wavelet transform is applied to each of the ABRs, and the important features of the ABRs are extracted by thresholding and matching the wavelet coefficients. The significant wavelet coefficients that represent the extracted features of the ABRs are then used as the variables to build the Bayesian network for classification of the ABRs. In order to estimate the performance of this approach, stratified ten-fold cross-validation is used.     

Insights into channel potentials and electron quasi-Fermi potentials for DGtunnel FETs

A detailed investigation carried out, with the help of extensive simulations using the TCAD device simulator Sentaurus, with the aim of achieving an understanding of the effects of variations in gate and drain potentials on the device characteristics of a silicon double-gate tunnel field effect transistor (Si-DG TFET) is reported in this paper. The investigation is mainly aimed at studying electrical properties such as the electric potential, the electron density, and the electron quasi-Fermi potential in a channel. From the simulation results, it is found that the electrical properties in the channel region of the DG TFET are different from those for a DG MOSFET. It is observed that the central channel potential of the DG TFET is not pinned to a fixed potential even after the threshold is passed (as in the case of the DG MOSFET); instead, it initially increases and later on decreases with increasing gate voltage, and this is also the behavior exhibited by the surface potential of the device. However, the drain current always increases with the applied gate voltage. It is also observed that the electron quasi-Fermi potential (eQFP) decreases as the channel potential starts to decrease, and there are hiphops in the channel eQFP for higher applied drain voltages. The channel regime resistance is also observed for higher gate length, which has a great effect on the I-V characteristics of the DG TFET device. These channel regime electrical properties will be very useful for determining the tunneling current; thus these results may have further uses in developing analytical current models.     

The transmission of reflexes in the spinal cord of cats during direct irradiation with microwaves.

The spinal of cats was directly exposed to 2450 CW microwave radiation in order to study the effect on reflex response and synaptic function. A small but statistically significant increase in the reflex response was detected in the first series of experiment, which indicates enhancement of the synaptic transmission. However, this effect was not observed in a second series of experiments in which the incident power density was increased from 10 mW/cm(2) to 20 mW/cm(2) and a more rigorous experimental design was employed. The slight changes that were observed in the second series could be attributed to small temperature variations during the experiment.     

Time-dependent scalar Beltrami-Hertz potentials in free space

We have solved the Beltrami-Maxwell equations for free space in terms of time-dependent scalar functions, the so-called scalar Beltrami-Hertz potentials. The two Beltrami fields have been represented in terms of scalar Beltrami-Hertz potentials. While the method is formulated for general sources, it is at its most powerful when the impressed source current densities are unidirectional: each Beltrami field, a complex-valued vector, can then be derived from a single scalar Beltrami-Hertz potential. We have calculated the corresponding scalar Green function explicity and given closed-form solutions for dipolar sources. Finally, the connection between the Beltrami-Maxwell formalism and conventional electromagnetic theory has been re-affirmed.     

Adaptive estimation of latency changes in evoked potentials

Changes in latency of evoked potentials (EP) may indicate clinically and diagnostically important changes in the status of the nervous system. A low signal-to-noise ratio of the EP signal makes it difficult to estimate small, transient, time-varying changes in latency, or delays. Here, the authors present an adaptive algorithm that estimates small delay (latency change) values even when EP signal amplitudes are time-varying. When the delay is time invariant, the adaptive algorithm produces an unbiased estimate with delay estimation error less than half of the sampling interval. A lower estimation error variance is obtained when, in a pair of signals, the adaptive algorithm delays the signal with the higher SNR. The adaptive delay estimation algorithm was tested on intra-operative recordings of somatosensory EP, and analysis of those recordings reveals that the anesthetic etomidate produces a step change in the amplitude and latency of the EP signals     

Simulation of action potentials in a one-dimensional bidomain

An approximate method of calculating action potentials in a nerve fiber within a coaxial sheath is presented. The method is of the implicit type, but it avoids any large matrix inversion and is adapted to run conveniently on a small PC/AT. It produces traces of the extracellular voltage V_out, which is not calculated by other methods, as well as the intracellular potentials V_in. For homogeneous fibers with small sheath resistance, V_out is proportional to d² V_in/dz², as expected. In more complex cases, V_out remains small, but its shape is hard to predict. One such example is presented in which an extracellular voltage trace of novel shape is calculated     

Noninvasive detection of fibrillation potentials in skeletal muscle

The presence of spontaneous muscle activity was determined by analysis of the power spectra of computer-model-generated sequences of spontaneous activity and additive noise. The modeling results identified the frequency band of 100-300 Hz as the band of peak signal-to-noise ratio for the detection of fibrillation potentials. Animal experiments were conducted in which the left sciatic nerves of three rats were transected. Measurements were taken 14 days following surgery with Ag/AgCl gel electrodes on the skin surface. Data was recorded from the gastrocnemius muscle on both the normal and denervated side for all three rats. The normal data and the denervated data yielded no discernible difference in the time-domain. Spectral analysis, however, demonstrated a clear and quantifiable difference between denervated and normal muscle signals. The average difference between the denervated and normal power spectral densities for the frequency band from 100 Hz to 300 Hz was 3.43, 1.90, and 3.02 dB for the three rats. The additional energy observed in the signals recorded from denervated muscles suggests that the single fiber spontaneous muscle activity that occurs in denervated muscle can be noninvasively detected. The potential diagnostic utility of noninvasive fibrillation potential detection is discussed and suggestions for future experiments are made.     

Weighted averaging of evoked potentials

Weighted averages of brain evoked potentials (EP's) are obtained by weighting each single EP sweep prior to averaging. These weights are shown to maximize the signal-to-noise ratio (SNR) of the resulting average if they satisfy a generalized eigenvalue problem involving the correlation matrices of the underlying signal and noise components. The signal and noise correlation matrices are difficult to estimate and the solution of the generalized eigenvalue problem is often computationally impractical for real-time processing. Correspondingly, a number of simplifying assumptions about the signal and noise correlation matrices are made which allow an efficient method of approximating the maximum SNR weights. Experimental results are given using actual auditory EP data which demonstrate that the resulting weighted average has estimated SNR's that are up to 21% greater than the conventional ensemble average SNR.     

Action potentials of curved nerves in finite limbs

Previous simulations of volume-conducted nerve-fiber action-potentials have modeled the limb as semi-infinite or circularly cylindrical, and the fibers as straight lines parallel to the limb surface. The geometry of actual nerves and limbs, however, can be considerably more complicated. Here, the authors present a general method for computing the potentials of fibers with arbitrary paths in arbitrary finite limbs. It involves computing the propagating point-source response (PPSR), which is the potential arising from a single point source (dipole or tripole) travelling along the fiber. The PPSR can be applied to fibers of different conduction velocities by simple dilation or compression. The method is illustrated for oblique and spiralling nerve fibers. Potentials from oblique fibers are shown to be different for orthodromic and antidromic propagation. Such results show that the straight-line models are not always adequate for nerves with anatomical amounts of curvature     

Derivation of the Lorentz potentials

The article [Schwab et al., 1996] on semantics of the irrotational component of the magnetic vector potential inspired the following alternative derivation of the expressions for the magnetic field, H, and the electric field, E, in terms of the Lorentz potentials. The artifice of the Lorentz gauge is not used in this derivation. Instead, the Lorentz potentials are required to satisfy differential equations akin to those satisfied by the Coulomb potentials. The Lorentz vector potential, A_L, is constructed by adding what turns out to be an irrotational vector, A_irr, to the Coulomb vector potential, A_C. The Lorentz scalar potential, φ_L, is constructed by adding a scalar, φ, to the Coulomb scalar potential, φ_C     

Nonstationary time-series analysis applied to investigation of brainstem system dynamics

Previous investigations of the dynamic organization of the lower brainstem and its relation to peripheral and other central nervous systems were predominantly performed by linear methods. These are based on time-averaging algorithms, which merely can be applied to stationary signal intervals. Thus, the current concept of the common brainstem system (CBS) in the reticular formation (RF) of the lower brainstem and basic types of its functional organization have been developed. Here, we present experiments where neuronal activities of the RF and the nucleus tractus solitarii (NTS, first relay station of baroreceptor afferents) were recorded together with related parameters of electroencephalogram (EEG), respiration, and cardiovascular system. The RF neurons are part of the CBS, which participates in regulation and coordination of cardiovascular, respiratory, and motor systems, and vigilance. The physiological time series, thus acquired, yield information about the internal dynamic coordination of the participating regulation processes. The major problem in evaluating these data is the nonlinearity and nonstationarity of the signals. We used a set of especially designed time resolving methods to evaluate nonlinear dynamic couplings in the interaction between CBS neurons and cardiovascular signals, respiration and the EEG, and between NTS neurons (influenced by baroreceptor afferents) and CBS neurons.     

Recovery of the auditory brainstem response by sign-bit andconventional averaging

In evoked potential studies, such as measurement of the auditory brainstem response (ABR), the signal of interest is recovered from the noise background by averaging at least 1000 EEG segments, recorded in phase, with a repeated auditory signal. The possibility is examined that information about whether each sample point was positive or negative relative to a baseline (i.e., averaging the sign bit) would allow recovery of the ABR for clinical purposes. A demonstration is presented in which auditory brainstem responses based on the full 12 bits of a typical analog-to-digital converter (TA or true amplitude procedure) are compared to those based on a single bit (SB procedure). For the signal-to-noise (S/N) ratios associated with an ABR signal in EEG noise (i.e., in the range 0.01⩾S/N⩾0.5), the recovery of the ABR signal using the SB procedure is quite satisfactory. Since the SB procedure is much less demanding computationally than the TA procedure, and thus faster and less expensive, it could be useful for practical ABR recovery     

Membrane current from transmembrane potentials in complex core-conductor models

Core-conductor models, used to integrate the behavior of the longitudinal currents with the distributed voltages of electrically active tissue, have evolved for over a century. A critical step in the use of such models is the computation of membrane current from the set of distributed transmembrane potential values that exist at a given moment, where the potentials are obtained either experimentally or computationally. Over time, interest has developed in a number of substantial extensions of the original model to include such features as nonuniform spatial resistances, loop instead of linear structure, and multiple sites of extracellular stimulation. This paper concisely restates and extends the equations for calculation of transmembrane currents with the systematic inclusion of alternative cases, noting how they reduce to the standard forms. An important issue is how complex the calculation of membrane current has to be. Thus, the paper goes on to show criteria (based on the uniformity of resistance and the presence of stimulation) for deciding when membrane currents can be obtained with a relatively simple calculation with a single equation involving local variables versus with a more complex calculation involving the simultaneous solution of a (possibly large) set of equations.