Predictability of EEG interictal spikes.

To determine whether EEG spikes are predictable, time series of EEG spike intervals were generated from subdural and depth electrode recordings from four patients. The intervals between EEG spikes were hand edited to ensure high accuracy and eliminate false positive and negative spikes. Spike rates (per minute) were generated from longer time series, but for these data hand editing was usually not feasible. Linear and nonlinear models were fit to both types of data. One patient had no linear or nonlinear predictability, two had predictability that could be well accounted for with a linear stochastic model, and one had a degree of nonlinear predictability for both interval and rate data that no linear model could adequately account for.     

An alternative method for Plasmodium culture synchronization

Since the synchronization of Plasmodium falciparum has become an essential tool in research, we have investigated the use of a commercial gelatine solution, Plasmion, to replace Plasmagel, which is now difficult to obtain. This method also avoids the use of techniques based on Percoll-glucose gradients. The Plasmion-based technique proved to be a good method and could become an alternative to Plasmagel.     

Nonlinear autoregressive analysis of the 3/s ictal electroencephalogram: implications for underlying dynamics

 In a previous study, nonlinear autoregressive (NLAR) models applied to ictal electroencephalogram (EEG) recordings in six patients revealed nonlinear signal interactions that correlated with seizure type and clinical diagnosis. Here we interpret these models from a theoretical viewpoint. Extended models with multiple nonlinear terms are employed to demonstrate the independence of nonlinear dynamical interactions identified in the ‘NLAR fingerprint’ of patients with 3/s seizure discharges. Analysis of the role of periodicity in the EEG signal reveals that the fingerprints reflect the dynamics not only of the periodic discharge itself, but also of the fluctuations of each cycle about an average waveform. A stability analysis is used to make qualitative inferences concerning the network properties of the ictal generators. Finally, the NLAR fingerprint is analyzed in the context of Volterra-Weiner theory. Received: 6 April 1994/Accepted in revised form: 18 November 1994     

A study on the best order for autoregressive EEG modelling

The autoregressive (AR) model is a widely used tool in electroencephalogram (EEG) analysis. The dependence of the AR model on both the segment length and several characteristic EEG patterns is addressed. The best AR model order is computed with three different criteria. The results show that the Rissanen criteria provides the more consistent order estimate for the EEG patterns considered. This study shows that for our data set, a 5th order AR model represents adequately 1- or 2-s EEG segments with the exception of featureless background, where higher order models are necessary.     

Characteristic nonlinearities of the 3/s ictal electroencephalogram identified by nonlinear autoregressive analysis

We describe a method for the characterization of electroencephalographic (EEG) signals based on a model which features nonlinear feedback. The characteristic EEG fingerprints obtained through this approach display the time-course of nonlinear interactions, rather than aspects susceptible to standard spectral analysis. Fingerprints of seizure discharges in six patients (five with typical absence seizures, one with complex partial seizures) revealed significant nonlinear interactions. The timing and pattern of these interactions correlated closely with the seizure type. Nonlinear autoregressive (NLAR) analysis is compared with other nonlinear dynamical measures that have been applied to the EEG.     

Classification methods for ongoing EEG and MEG signals

Classification algorithms help predict the qualitative properties of a subject's mental state by extracting useful information from the highly multivariate non-invasive recordings of his brain activity. In particular, applying them to Magneto-encephalography (MEG) and electro-encephalography (EEG) is a challenging and promising task with prominent practical applications to e.g. Brain Computer Interface (BCI). In this paper, we first review the principles of the major classification techniques and discuss their application to MEG and EEG data classification. Next, we investigate the behavior of classification methods using real data recorded during a MEG visuomotor experiment. In particular, we study the influence of the classification algorithm, of the quantitative functional variables used in this classifier, and of the validation method. In addition, our findings suggest that by investigating the distribution of classifier coefficients, it is possible to infer knowledge and construct functional interpretations of the underlying neural mechanisms of the performed tasks. Finally, the promising results reported here (up to 97% classification accuracy on 1-second time windows) reflect the considerable potential of MEG for the continuous classification of mental states.     

Spatial synchronization of the segmental EEG in humans

Topographic features of spatial synchronization of sharp changes, or rapid transition processes (RTP), were studied in human EEG recorded from longitudinal and transversal electrode arrays. A new algorithm, the EEG Threshold Scanning, was proposed for the detection of the RTP. Synchronization of the RTP was estimated by Operational Synchrony Index (OSI) based on the difference between the actual and stochastic frequency of RTP coincidence in a pair of EEG channels. The relationship between the OSI and interelectrode distance was not monotonous. The OSI depended also on the extent of morpho-functional similarity between two cortical areas. Similar results were obtained for crosscorrelation calculated for the same pairs of the EEG derivations. The existence of dynamic spatial modules which incorporate different brain areas by complementary stabilization of their functional states is discussed.     

Segmentation of EEG during sleep using time-varying autoregressive modeling

Time-varying AR modeling is applied to sleep EEG signal, in order to perform parameter estimation and detect changes in the signal characteristics (segmentation). Several types of basis functions have been analyzed to determine how closely they can approximate parameter changes characteristics of the EEG signal. The TV-AR model was applied to a large number of simulated signal segments, in order to examine the behaviour of the estimation under various conditions such as variations in the EEG parameters and in the location of segment boundaries, and different orders of the basis functions. The set of functions that is the basis for the Discrete Cosine Transform (DCT), and the Walsh functions were found to be the most efficient in the estimation of the model parameters. A segmentation algorithm based on an “Identification function” calculated from the estimated model parameters is suggested.     

An accurate method for measurement of aldosterone production

A method is described for isolation of the acid-hydrolysable metabolite of aldosterone in sufficient purity to measure accurately the daily production rate. Values obtained with six hospital patients were 84-131mug./day on a daily intake of 100m-equiv. of Na(+) and 227-464mug./day on a daily intake of 10m-equiv. of Na(+). Corresponding values for aldosterone excretion were also recorded, but these are a poor index of production rate since they represent from 1.6 to 9.8% of the total daily output of aldosterone.     

An investigation of the phase locking index for measuring of interdependency of cortical source signals recorded in the EEG

The phase locking index (PLI) was introduced to quantify in a statistical sense the phase synchronization of two signals. It has been commonly used to process biosignals. In this article, we investigate the PLI for measuring the interdependency of cortical source signals (CSSs) recorded in the Electroencephalogram (EEG). To this end, we consider simple analytical models for the mapping of simulated CSSs into the EEG. For these models, the PLI is investigated analytically and through numerical simulations. An evaluation is made of the sensitivity of the PLI to the amount of crosstalk between the sources through biological tissues of the head. It is found that the PLI is a useful interdependency measure for CSSs, especially when the amount of crosstalk is small. Another common interdependency measure is the coherence. A direct comparison of both measures has not been made in the literature so far. We assess the performance of the PLI and coherence for estimation and detection purposes based on, respectively, a normalized variance and a novel statistical measure termed contrast. Based on these performance measures, it is found that the PLI is similar or better than the CM in most cases. This result is also confirmed through analysis of EEGs recorded from epileptic patients.

An automated colorimetric method for the measurement of 3-hydroxybutyrate concentration

An automated colorimetric method is presented for analysis of dl-3-hydroxybutyrate concentration using the Technicon AutoAnalyzer. The method is capable of measuring dl-3-hydroxybutyrate concentration in hemolyzed “blood” or plasma, with greater sensitivity and less enzyme than a previous automated method applicable only to serum.     

An interictal measurement of cerebral oxygen extraction fraction in MRI-negative refractory epilepsy using quantitative susceptibility mapping

PurposeOxygen extraction fraction (OEF) can be a factor to identify brain tissue’s disability in epileptic patients. This study aimed to assess the OEF’s level measurement in refractory epileptic patients (REPs) using a quantitative susceptibility mapping (QSM) method and to determine whether the OEF parameters change.MethodsQSM-OEF maps of 26 REPs and 16 healthy subjects were acquired using 3T MRI with a 64-channel coil. Eighteen regions-of-interest (ROIs) were chosen around the cortex in one appropriate slice of the brain and the mean QSM-OEF for each ROI was obtained. The correlations of QSM-OEF among different clinical characteristics of the disease, as well as between the patients and normal subjects, were also investigated.ResultsQSM-OEF was shown to be significantly higher in REPs (44.9 ± 5.8) than that in HS (41.9 ± 6.2) (p < 0.05). Mean QSM-OEF was statistically lower in the ipsilateral side (44.5 ± 6.6) compared to the contralateral side (46.4 ± 6.8) (P < 0.01). QSM-OEF was illustrated to have a strong positive correlation with the attack duration (r = 0.6), and a moderate negative correlation with the attack frequency (r = −0.3). Using an optimized support vector machine algorithm, we could predict the disease in subjects having abnormal OEF values in the brain-selected-ROIs with sensitivity, specificity, AUC, and the precision of 0.96, 1, 0.98, and 1, respectively.ConclusionsThe results of this study revealed that QSM-OEF of the REPs’ brain is higher than that of HS, which indicates that QSM-OEF is associated with disease activity.     

第一和第二语言Stroop任务中EEG同步化分析

采用基于多元自回归的瞬时EEG相干方法研究了十位汉英双语者执行Stroop任务时脑神经电活动及其功能皮层区的协同作用。结果显示：在β1(13-18Hz)频段,无论是汉语(第一语言,L1)还是英语(第二语言,L2)呈现的刺激,不一致条件的EEG相干值明显大于一致条件的EEG相干值,表明β1频段对刺激类型敏感;与L2相比,L1的Stroop任务中,额一顶区的相干值显著增强。EEG相干值反映了不同脑皮层间的相互作用强度。因此研究结果表明：判断和处理冲突信息(如Stroop的不一致条件)时脑功能皮层区之间的协同作用增强;相对于第二语言,第一语言处理过程中额一顶区之间的通信协作增加。     

An algorithm for automated detection,localization and measurement of local calcium signals from camera-based imaging

Local Ca²⁺ transients such as puffs and sparks form the building blocks of cellular Ca²⁺ signaling in numerous cell types. They have traditionally been studied by linescan confocal microscopy, but advances in TIRF microscopy together with improved electron-multiplied CCD (EMCCD) cameras now enable rapid (>500 frames s⁻¹) imaging of subcellular Ca²⁺ signals with high spatial resolution in two dimensions. This approach yields vastly more information (ca. 1 Gb min⁻¹) than linescan imaging, rendering visual identification and analysis of local events imaged both laborious and subject to user bias. Here we describe a routine to rapidly automate identification and analysis of local Ca²⁺ events. This features an intuitive graphical user-interfaces and runs under Matlab and the open-source Python software. The underlying algorithm features spatial and temporal noise filtering to reliably detect even small events in the presence of noisy and fluctuating baselines; localizes sites of Ca²⁺ release with sub-pixel resolution; facilitates user review and editing of data; and outputs time-sequences of fluorescence ratio signals for identified event sites along with Excel-compatible tables listing amplitudes and kinetics of events.     

An indirect bioluminescence method for the quantitative measurement of polymorphonuclear cell chemotaxis

A method is presented which allows the quantification of the effects of chemotactic factors on polymorphonuclear leukocytes on the basis of a sensitive ATP measurement using bioluminescence. The assay measures those cells which have migrated through a commercial 3 μm filter system (Transwell?). The assay was tested under standardized conditions with different chemotactic agents (leukotriene B4 [LTB4], N-formyl-methionyl-leucyl-phenylalanine [FMLP], N-formyl-methionyl-leucyl-phenylalanine-methyl ester [M-FMLP]). Under appropriate conditions the migration of PMN-cells is time-dependent and linear for 60 minutes. Spontaneous migration of PMN cells is simultaneously quantified in a simple way, and the value obtained allows a determination of the actual chemotactic stiuation of the PMN cells. In healthy humans the spontaneous migration varied between 4.2% and 14.4% of the total number of PMN cells. An optimal chemotactic activity was detected at 10^?8/mol/I for FMLP and 10^?7 mol/l for M-FMLP in PMN leukocytes, which correlates with literature values. It was also found that in contrast to EDTA blood, heparinized blood lowers the ATP level of PMN cells (by about 50%) and therefore heparinized blood is not recommended for chemotactic experiments. This assay is a simple tool for quantification of the spontaneous migration, and the chemotactic response to specific factors and their inhibitors in particular for pharmacological experiments. In contrast to the ‘classical’ chemotactic assays this method also permits the simultaneous testing of the influence of chemotactic substances on cellular ATP levels.