A database of EEG information was collected from EEG recordings performed in epileptic patients with diffuse spike-wave complex discharges. Normal activity, spike-waves, slow waves and artefacts were mixed up in these recordings. The analysis of EEGs stored in the database was performed, channel by channel, through a 2.56 s moving window. For each so defined EEG sequence, a set of 22 variables chosen for their discriminatory power was computed. A subset of 8 highly discriminating variables was selected by the means of a stepwise discriminant analysis. Each class of the learning set contained 40 up to 100 EEG sequences. A classifying algorithm that takes into account zones of uncertainty is proposed. It has been evaluated on a test set which was composed of 1981 EEG sequences issued from 15 different patients. The results have been checked by two neurologists. The agreement rate between each of them and the proposed algorithm was more than 92%; this result is comparable to the agreement rate between the two neurologists (94%). A contextual analysis algorithm, using bi-dimensional smoothing techniques, allowed to improve the agreement rates which exceeded 94%.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/0020-7101(82)90042-3 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Beta oscillations predict the envelope sharpness in a rhythmic beat sequence.
Sci Rep
January 2025
RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Forskningsveien 3A, Oslo, 0373, Norway.
Periodic sensory inputs entrain oscillatory brain activity, reflecting a neural mechanism that might be fundamental to temporal prediction and perception. Most environmental rhythms and patterns in human behavior, such as walking, dancing, and speech do not, however, display strict isochrony but are instead quasi-periodic. Research has shown that neural tracking of speech is driven by modulations of the amplitude envelope, especially via sharp acoustic edges, which serve as prominent temporal landmarks.
View Article and Find Full Text PDFA multi-domain feature fusion epilepsy seizure detection method based on spike matching and PLV functional networks.
J Neural Eng
January 2025
Hangzhou Dianzi University, School of Automation, Hangzhou Dianzi University, Hangzhou 310052, China, Hangzhou, Zhejiang, 310018, CHINA.
The identification of spikes, as a typical characteristic wave of epilepsy, is crucial for diagnosing and locating the epileptogenic region. The traditional seizure detection methods lack spike features and have low sample richness. This paper proposes a seizure detection method with spike-based phase locking value (PLV) functional brain networks and multi-domain fused features.
View Article and Find Full Text PDFA randomized, placebo-controlled, cross-over trial of ketamine in Rett syndrome.
J Neurodev Disord
January 2025
Rett Syndrome Research Trust, Trumbull, CT, USA.
Background: Preclinical studies and anecdotal case reports support the potential therapeutic benefit of low-dose oral ketamine as a treatment of clinical symptoms in Rett syndrome (RTT); however, no controlled studies have been conducted in RTT to evaluate safety, tolerability and efficacy.
Design: This was a sequentially initiated, dose-escalating cohort, placebo-controlled, double blind, randomized sequence, cross-over study of oral ketamine in 6-12-year-old girls with RTT to evaluate short-term safety and tolerability and explore efficacy.
Methods: Participants were randomized to either five days treatment with oral ketamine or matched placebo, followed by a nine-day wash-out period and then crossed-over to the opposite treatment.
Predicting the Irrelevant: Neural Effects of Distractor Predictability Depend on Load.
Eur J Neurosci
January 2025
Department of Psychology, University of Lübeck, Lübeck, Germany.
Distraction is ubiquitous in human environments. Distracting input is often predictable, but we do not understand when or how humans can exploit this predictability. Here, we ask whether predictable distractors are able to reduce uncertainty in updating the internal predictive model.
View Article and Find Full Text PDFCirculating microRNAs as Biomarkers of Various Forms of Epilepsy.
Med Sci (Basel)
January 2025
Department of Medical Genetics, Clinical Neurophysiology of Postgraduate Education, V.F. Voyno-Yasenetsky Krasnoyarsk State Medical University, Russian National Research, Krasnoyarsk 660022, Russia.
: Epilepsy is a group of disorders characterized by a cluster of clinical and EEG signs leading to the formation of abnormal synchronous excitation of neurons in the brain. It is one of the most common neurological disorders worldwide; and is characterized by aberrant expression patterns; both at the level of matrix transcripts and at the level of regulatory RNA sequences. Aberrant expression of a number of microRNAs can mark a particular epileptic syndrome; which will improve the quality of differential diagnosis.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!