scholarly journals ANALYSIS OF HIGH-RESOLUTION MICROELECTRODE EEG RECORDINGS IN AN ANIMAL MODEL OF SPONTANEOUS LIMBIC SEIZURES

2009 ◽  
Vol 19 (02) ◽  
pp. 605-617 ◽  
Author(s):  
C. KOMALAPRIYA ◽  
M. C. ROMANO ◽  
M. THIEL ◽  
U. SCHWARZ ◽  
J. KURTHS ◽  
...  
Keyword(s):  
Animal Model ◽  
High Resolution ◽  
High Frequency ◽  
Recurrence Time ◽  
Very High Frequency ◽  
Limbic Seizures ◽  
High Frequency Oscillations ◽  
Quantification Analysis ◽  
Eeg Recordings

We perform a systematic data analysis on high resolution (0.5–12 kHz) multiarray microelectrode recordings from an animal model of spontaneous limbic epilepsy, to investigate the role of high frequency oscillations and the occurrence of early precursors for seizures. Results of spectral analysis confirm the importance of very high frequency oscillations (even greater than 600 Hz) in normal (healthy) and abnormal (epileptic) hippocampus. Furthermore, we show that the measures of Recurrence Quantification Analysis (RQA) and Recurrence Time Statistics (RTS) are successful in indicating, rather uniquely, the onset of ictal state and the occurrence of some warnings/precursors during the pre-ictal state, in contrast to the linear measures investigated.

11. Very high frequency oscillations in medial temporal structures

2011 ◽  
Vol 122 (8) ◽  
pp. e11
Author(s):  
Miyako Yamaguchi ◽  
Kiyohito Terada ◽  
Koichi Baba ◽  
Fumihiro Nakamura ◽  
Kazumi Matsuda ◽  
...  
Keyword(s):  
High Frequency ◽  
Very High Frequency ◽  
High Frequency Oscillations ◽  
Temporal Structures ◽  
Very High

scholarly journals A Neuromorphic Spiking Neural Network Detects Epileptic High Frequency Oscillations in the Scalp EEG

2021 ◽  
Author(s):  
Karla Burelo ◽  
Georgia Ramantani ◽  
Giacomo Indiveri ◽  
Johannes Sarnthein
Keyword(s):  
Low Power ◽  
Seizure Frequency ◽  
High Frequency ◽  
Therapy Monitoring ◽  
Non Invasive ◽  
Scalp Eeg ◽  
High Frequency Oscillations ◽  
Eeg Recordings ◽  
Active Epilepsy ◽  
Wearable Electronic Devices

Abstract Background: Interictal High Frequency Oscillations (HFO) are measurable in scalp EEG. This has aroused interest in investigating their potential as biomarkers of epileptogenesis, seizure propensity, disease severity, and treatment response. The demand for therapy monitoring in epilepsy has kindled interest in compact wearable electronic devices for long- term EEG recording. Spiking neural networks (SNN) have been shown to be optimal architectures for being embedded in compact low-power signal processing hardware. Methods: We analyzed 20 scalp EEG recordings from 11 patients with pediatric focal lesional epilepsy. We designed a custom SNN to detect events of interest (EoI) in the 80-250 Hz ripple band and reject artifacts in the 500-900 Hz band. Results: We identified the optimal SNN parameters to automatically detect EoI and reject artifacts. The occurrence of HFO thus detected was associated with active epilepsy with 80% accuracy. The HFO rate mirrored the decrease in seizure frequency in 8 patients (p = 0.0047). Overall, the HFO rate correlated with seizure frequency (rho = 0.83, p < 0.0001, Spearman’s correlation).Conclusions: The fully automated SNN detected clinically relevant HFO in the scalp EEG. This is a further step towards non-invasive epilepsy monitoring with a low-power wearable device.

scholarly journals Peranan Lingkungan Sosial terhadap Pembentukan Karakter Peduli Lingkungan Mahasiswa Pendidikan Geografi di Universitas Samudra Langsa

2018 ◽  
Vol 10 (2) ◽  
pp. 235
Author(s):  
Fitria Mustika ◽  
Tengku Muhammad Sahudra
Keyword(s):  
Family Environment ◽  
High Frequency ◽  
Low Frequency ◽  
Measurement Scale ◽  
Education Student ◽  
Achievement Level ◽  
Very High Frequency ◽  
Environmental Care ◽  
The Family

This study aims to determine the role of the family, community, and tertiary environment towards the formation of caring character in the geography education student environment. The output of this study was a four-indexed indexed education journal and a UNIMED google scolar. Samples from the study population were 20 respondents with 30 items about questionnaires. The time of the study starts from May 2018 to October 2018. The measurement scale in this study is the scale of the briquette. Data collection by means of library studies, interviews, questionnaires, and documentation. This research was conducted by distributing questionnaire questionnaires and interviews. Based on the results of questionnaire data processing, the family environment has a very high frequency in the formation of character of the student's environmental care with an achievement level of a total score of 91%. Furthermore, the role of the campus environment also has a high frequency in the formation of the character of the student's environmental care with a total score of 89%. Whereas the family environment has a low frequency in the formation of character of student environmental care with a total score of 57%. It can be concluded that the family environment has the most role in forming the character of the student's environmental care.

scholarly journals Detection of High-Frequency Oscillations by Hybrid Depth Electrodes in Standard Clinical Intracranial EEG Recordings

2014 ◽  
Vol 5 ◽  
Author(s):  
Efstathios D. Kondylis ◽  
Thomas A. Wozny ◽  
Witold J. Lipski ◽  
Alexandra Popescu ◽  
Vincent J. DeStefino ◽  
...  
Keyword(s):  
High Frequency ◽  
Intracranial Eeg ◽  
High Frequency Oscillations ◽  
Depth Electrodes ◽  
Eeg Recordings

scholarly journals The Oscillatory Basis of Working Memory Function and Dysfunction in Epilepsy

2021 ◽  
Vol 14 ◽  
Author(s):  
Olivia N. Arski ◽  
Julia M. Young ◽  
Mary-Lou Smith ◽  
George M. Ibrahim
Keyword(s):  
Working Memory ◽  
High Frequency ◽  
Large Scale ◽  
Memory Function ◽  
Epileptic Activity ◽  
Functional Roles ◽  
High Frequency Oscillations ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges

Working memory (WM) deficits are pervasive co-morbidities of epilepsy. Although the pathophysiological mechanisms underpinning these impairments remain elusive, it is thought that WM depends on oscillatory interactions within and between nodes of large-scale functional networks. These include the hippocampus and default mode network as well as the prefrontal cortex and frontoparietal central executive network. Here, we review the functional roles of neural oscillations in subserving WM and the putative mechanisms by which epilepsy disrupts normative activity, leading to aberrant oscillatory signatures. We highlight the particular role of interictal epileptic activity, including interictal epileptiform discharges and high frequency oscillations (HFOs) in WM deficits. We also discuss the translational opportunities presented by greater understanding of the oscillatory basis of WM function and dysfunction in epilepsy, including potential targets for neuromodulation.

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