New-Onset Alzheimer's Disease and Normal Subjects 100% Differentiated by P300.

Previous work has suggested that evoked potential analysis might allow the detection of subjects with new-onset Alzheimer's disease, which would be useful clinically and personally. Here, it is described how subjects with new-onset Alzheimer's disease have been differentiated from healthy, normal subjects to 100% accuracy, based on the back-projected independent components (BICs) of the P300 peak at the electroencephalogram electrodes in the response to an oddball, auditory-evoked potential paradigm. After artifact removal, clustering, selection, and normalization processes, the BICs were classified using a neural network, a Bayes classifier, and a voting strategy. The technique is general and might be applied for presymptomatic detection and to other conditions and evoked potentials, although further validation with more subjects, preferably in multicenter studies is recommended.

Waveform analysis of non-oscillatory independent components in single-trial auditory event-related activity in healthy subjects and Alzheimer's disease patients.

The objective was to characterize the non-oscillatory independent components (ICs) of the auditory event-related potential (ERP) waveform of an oddball task for normal and newly diagnosed Alzheimer's disease (AD) subjects, and to seek biomarkers for AD. Single trial ERP waveforms were analysed using independent components analysis (ICA) and k-means clustering. Two stages of clustering depended upon the magnitudes and latencies, and the scalp topographies of the non-oscillatory back-projected ICs (BICs) at electrode Cz. The electrical current dipole sources of the BICs were located using Low Resolution Electromagnetic Tomography (LORETA). Generally 3-10 BICs, of different latencies and polarities, occurred in each trial. Each peak was associated with positive and negative BICs. The trial-to-trial variations in their relative numbers and magnitudes may explain the variations in the averaged ERP reported, and the delay in the averaged P300 for AD patients. The BIC latencies, topographies and electrical current density maximum locations varied from trial-to-trial. Voltage foci in the BIC topographies identify the BIC source locations. Since statistical differences were found between the BICs in healthy and AD subjects, the method might provide reliable biomarkers for AD, if these findings are reproduced in a larger study, independently of other factors influencing the comparison of the two populations. The method can extract artefact- and EEG-free single trial ERP waveforms, offers improved ERP averages by selecting the trials on the basis of their BICs, and is applicable to other evoked potentials, conditions and diseases.

Comparison of two methods for correcting ocular artefacts in EEGs.

A major problem in the study of brain potentials is the occurrence of ocular artefacts in electro-encephalograms. OAs can be monitored by placing electrodes near the eyes and recording electro-oculograms. In the paper, two OA correction methods based on simulations are compared; the Jervis method and the vandenBerg method. In most simulations, the residual (the difference between the original EEG and the EEG after correction) is smaller in amplitude and variance for the vandenBerg method than for the Jervis method. When eye movements and blinks are given different factors, the blinks are not removed completely. For both methods, the residual of the blinks increases with the differences between the model parameters for the blinks and for eye movements. The occurrence of a slow negative wave greatly disturbs the estimated parameters and thus the residuals of the Jervis method. For the vandenBerg method, there is only a very small effect. The conclusion from correcting a recorded data set, which does not contain a slow negative wave, is that, for these data, there is no evidence that one method is better than the other.

The contingent negative variation in positive and negative types of schizophrenia.

The authors analyzed the contingent negative variations of 20 medicated patients with schizophrenia diagnosed according to DSM-III-R and 20 age- and sex-matched normal comparison subjects. For the patients with schizophrenia, there were significant correlations between contingent negative variation amplitude and two items on the Scale for the Assessment of Negative Symptoms (affective flattening and avolition-apathy) and the total score on this scale. These findings have implications regarding the underlying pathology of negative and positive symptoms of schizophrenia.

Pilot study of computerised differentiation of Huntington's disease, schizophrenic, and Parkinson's disease patients using the contingent negative variation.

In this study a potential known as the contingent negative variation was used to differentiate between schizophrenic, Parkinson's disease (PD), Huntington's disease (HD) patients and normal control subjects. The aim was to assist diagnosis and the avoidance of false diagnosis. 20 schizophrenic, 16 PD, 11 HD and 43 normal control subjects were enrolled for this study. The discriminatory variables were generated by applying spectral analysis to pre- and post-stimulus sections of the CNV responses. The patient differentiation was achieved by using the measured variables in a discriminant analysis program. It was possible to accurately differentiate between HD, schizophrenic, PD patients and normal control subjects. It was also attempted to differentiate between HD and schizophrenic patients, HD and PD patients, and schizophrenic and PD patients. The test results indicated that the method is useful in differentiating between these patients. This study had a number of limitations. It was based on a limited number of individuals, and an analysis of medication effects on the test results and the test-retest reliability assessment could not be carried out.

Effect on EEG responses of removing ocular artefacts by proportional EOG subtraction.

Work undertaken to investigate the effect on EEG responses of ocular artefact removal by proportional electro-oculogram subtraction using the least-squares method is reported. The ocular artefact model and the least-squares approach to estimation of the model parameters and hence of the EEG waveform, including the response, are described. Results are presented to show that the response shapes become modified if ocular artefact removal is implemented recursively. This happens because the response is incorrectly treated as part of the random background EEG. The solution is to incorporate a model of the response within the ocular artefact removal algorithm. The results of tests on simulated data confirm these conclusions. The results of the incorporation of response models in removing ocular artefacts from CNV recordings are presented. Even with modelling recursive ocular artefact removal is found to modify the shape of the CNV, and so reliable results can only be obtained if the removal is implemented nonrecursively. Evidence is given that it is advisable to remove DC levels from the recorded data.

Spectral analysis of EEG responses.

The techniques used and the results obtained in a spectral analysis of two specific responses in the human electroencephalogram are presented in this paper. The purposes are to show how the techniques may be applied to the necessarily short lengths of EEG data and to illustrate these techniques and the useful results obtained by relevant examples. The necessary data-processing procedures and precautions for transforming from the time to frequency domain are presented in a tutorial fashion. The importance of augmenting zeros, choice of the most appropriate data window and pretransformation of the data to avoid the combined effects of energy loss and low frequency content biasing caused by windowing is explained. The pros and cons of the tapered-cosine (Tukey) and Kaiser-Bessel windows are illustrated. The usefulness of applying certain statistical tests, which are based on a physical model of the responses, to the harmonic components of the responses is demonstrated. Thus a comparison is made between the features of auditory evoked responses and of the contingent negative variation, and the usefulness of predictive statistical diagnosis in differentiating between subject groups is illustrated by application to normal subjects and Huntington's chorea patients.

The assessment of two methods for removing eye movement artefact from the EEG.

A quantitative assessment of both computerised correlation and analogue techniques for the removal of eye movement artefact from the electroencephalogram was undertaken. In both methods a fraction of the measured EOGs was subtracted from the measured EEG to leave the corrected EEG. In the correlation method the correction factors were computed from the cross-correlations of the EOGs and measured EEGs. In the analogue method the fraction subtracted was derived using a potential divider arrangement. The relative effectiveness of the two methods was determined by comparing the autocorrelation functions of the corrected EEGs at a lag of 2 sec. It was found that the computerised correlation technique was superior. A 3-channel EOG correlation correction procedure was found adequate in which two horizontal and one vertical EOGs were used. The analogue technique was very time consuming and possibly erroneous.