Richard N. Harner

Patient-specific Early Seizure Detection From Scalp Electroencephalogram

The objective of this study is to develop a method for automatic detection of seizures before or immediately after clinical onset using features derived from scalp electroencephalogram. This detection method is patient specific. It uses recurrent neural networks and a variety of input features. For each patient, we trained and optimized the detection algorithm for two cases: (1) during the period immediately preceding seizure onset and (2) during the period immediately after seizure onset. Continuous scalp electroencephalogram recordings (duration 15–62 hours, median 25 hours) from 25 patients, including a total of 86 seizures, were used in this study. Preonset detection was successful in 14 of the 25 patients. For these 14 patients, all of the testing seizures were detected before seizure onset with a median preonset time of 51 seconds and false-positive (FP) rate was 0.06/hour. Postonset detection had 100% sensitivity, 0.023/hour FP rate, and median delay of 4 seconds after onset. The unique results of this study relate to preonset detection. Our results suggest that reliable preonset seizure detection may be achievable for a significant subset of patients with epilepsy without use of invasive electrodes.

Singular value decomposition--a general linear model for analysis of multivariate structure in the electroencephalogram.

SummaryThe application of Singular Value Decomposition (SVD)to analysis of EEG and evoked potential data has led to a hypothesis concerning the underlying structure of the EEG recorded from multiple channels. Based on the SVD algorithm the EEG is considered to be the linear combination of a sufficient number of features, each of which is defined in terms of its spatial distribution, temporal distribution, and amplitude. Use of this model leads to clear concepts concerning sampling, data reduction, normalization, and calculation of statistical significance, some of which are less evident when analysis is restricted to a single domain of interest.

Application of singular value cecomposition to topographic analysis of flash-evoked potentials

SummarySingular value decomposition is a robust numerical method for decomposing a matrix of multichannel EEG or EP data into a sharply reduced set of features with corresponding waveform, amplitude, and spatial vectors. In 19 normal subjects aged 19 to 40 years, the three largest features computed by the SVD algorithm accounted for 93–98 percent of the total variance of the averaged flash-evoked potential. There was good separation of major brain areas as well as clustering of related electrode sites. Orthogonal rotation of the three spatial vectors is essential to see clustering of brain areas across subjects. Three-dimensional display showed the regular presence of orthonormal occipital, frontopolar, and vertex spatial vectors. Since the spatial feature vectors cluster tightly and yet are orthonormal, statistical comparison of patients with normal control groups will be facilitated.

Bicycling movements as a manifestation of complex partial seizures of temporal lobe origin.

Summary: Alternating movements of the limbs during a seizure, especially bicycling movements of the legs, are often taken as strong evidence for the psychogenic origin of seizure activity in an adult population. A recent review of pseudoseizure manifestations concluded that alternating limb movements were “highly characteristic of pseudoseizures.” We report two adult patients with complex partial seizures of temporal lobe origin, confirmed by ictal video EEG recording, in whom bicycling movements were the prominent ictal manifestation. Bicycling occurred 5–30 s after ictal onset and lasted 15–30 s. Use of video EEG recording continues to increase our understanding of the wide range of behaviors which may occur in the course of an epileptic seizure, particularly complex partial seizures. Few absolute clinical criteria remain to distinguish epileptic seizures from pseudoseizures. These two cases and one other reported case clearly remove bicycling movements from that category.

Bedside clinical and electrophysiological assessment: assessment of change in vulnerable patients.

Current approaches to the diagnosis of delirium are based upon the recognition of symptoms that emerge in the pathological state. As an alternative, we propose an approach to case identification for research purposes based on the recognition of significant changes in the cognitive or cerebral state of the individual patient. Categorical change can be defined using prediction intervals calculated from repeated measures on a population of medically stable subjects. Data from subjects enrolled in a prospective study of delirium in a long-term care population were utilized to calculate prediction intervals for the Mini-Mental Status Examination and for measures of the electroencephalographic background frequency as obtained with a two-channel microprocessor-based EEG device. Preliminary findings support the validity of this quantitative approach for defining changes in brain state. Future research should evaluate both cognitive and electrophysiological techniques for monitoring vulnerable patients.

Utilization of a Two-Channel, Microprocessor-Based EEG Device for Monitoring Cognitively Vulnerable Patients

Several experiments were conducted to validate the use of a two-channel microprocessor-based electroencephalographic (EEG) device for detecting changes in EEG background rhythm in the clinic or at the bedside. The reliability of background measures in healthy individuals was evaluated by obtaining EEG data on 20 control subjects on two occasions separated by at least 1 day. The sensitivity to an experimental toxic encephalopathy was evaluated using measures of EEG and the Buschke Memory Selective Reminding Test after the administration of scopolamine hydrobromide, 0.86 mg subcutaneously, to three healthy volunteers. Postdrug measures of the EEG showed significant group differences from controls at 1 and 2 hours for relative alpha and relative theta power. The drug-induced change for each individual exceeded the predicted range calculated from data on control subjects. These findings suggest the feasibility and the potential utility of this method. This approach was extended to the elderly with measures on 102 subjects (average age, 85 years) living in an institutional setting. EEG measures in the population were of acceptable reliability and were significantly correlated with Mini-Mental State Examination (MMSE) scores (r = -.375 for theta and .357 for beta). Preliminary findings suggest that this method may detect metabolic encephalopathies in the elderly. The study demonstrates the potential value of this approach and suggests the need for further research. (J Geriatr Psychiatry Neurol 1990;3:155-162) .

The saint Vincent conference in Valle d'Aosta

The idea for a high level technical workshop that would bring together leading experts in the field of topographic EEG analysis came from an informal meeting of Richard Harner, Dietrich Lehmann and Peter Wong in 1987. The possibility of holding the workshop in the superb conference and hotel facilities of St. Vincent was suggested and converted into reality by Silvana Riggio in 1988. Subsequently a basic course in topographic EEG analysis, originally conceived by Frank Duffy, Roy John and Richard Harner, was organized to precede and introduce the workshop.