scholarly journals Relationship between high-frequency activity in the sensory and the motor hand areas, and regional myelin content

2021 ◽  
Author(s):  
Leo Tomasevic ◽  
Hartwig Roman Siebner ◽  
Axel Thielscher ◽  
Fiore Manganelli ◽  
Giuseppe Pontillo ◽  
...  
Keyword(s):  
High Frequency ◽  
Motor Evoked Potentials ◽  
Short Interval ◽  
Neuronal Responses ◽  
Electrical Nerve Stimulation ◽  
Frequency Responses ◽  
High Frequency Oscillations ◽  
Contralateral Hand ◽  
High Frequency Activity ◽  
The Individual

AbstractBackgroundThe human primary sensory (S1) and primary motor (M1) hand areas feature high-frequency neuronal responses. Electrical nerve stimulation evokes high-frequency oscillations (HFO) at around 650 Hz in the contralateral S1. Likewise, paired-pulse transcranial magnetic stimulation of M1 produces short interval intracortical facilitation (SICF) of motor evoked potentials in contralateral hand muscles. SICF features several peaks of facilitation which are separated by inter-peak intervals resembling HFO rhythmicity.HypothesisIn this study, we tested the hypothesis that the individual expressions of HFO and SICF are tightly related to each other and to the regional myelin content in the sensorimotor cortex.MethodsIn 24 healthy volunteers, we recorded HFO and SICF, and, in a subgroup of 20 participants, we mapped the cortical myelin content using the ratio between the T1- and T2-weighted MRI signal as read-out.ResultsThe individual frequencies and magnitudes of HFO and SICF were tightly correlated: the intervals between the first and second peak of cortical HFO and SICF showed a positive linear relationship (r= 0.703, p< 0.001), while their amplitudes were inversely related (r= −0.613, p= 0.001). The rhythmicity, but not the magnitude of the high-frequency responses, was related to the cortical myelin content: the higher the cortical myelin content, the shorter the inter-peak intervals of HFO and SICF.ConclusionThe results confirm a tight functional relationship between high-frequency responses in S1 (i.e., HFO) and M1 (i.e., SICF). They also establish a link between the degree of regional cortical myelination and the expression of high-frequency responses in the human cortex, giving further the opportunity to infer their possible generators.

FV20 Prospectively defined high frequency oscillations to predict seizure outcome in the individual patient

2020 ◽  
Vol 131 (4) ◽  
pp. e233
Author(s):  
E. Boran ◽  
P. Mégevand ◽  
A. Steenkamp ◽  
V. Dimakopoulos ◽  
M. Seeck ◽  
...  
Keyword(s):  
High Frequency ◽  
Seizure Outcome ◽  
High Frequency Oscillations ◽  
The Individual

scholarly journals Tracking multi-site seizure propagation using ictal high frequency activity

2020 ◽  
Author(s):  
Steven Tobochnik ◽  
Lisa M. Bateman ◽  
Cigdem I. Akman ◽  
Deepti Anbarasan ◽  
Carl W. Bazil ◽  
...  
Keyword(s):  
High Frequency ◽  
Spatial Clustering ◽  
Spatial Clusters ◽  
Prognostic Information ◽  
Spatial Overlap ◽  
High Frequency Oscillations ◽  
Depth Electrodes ◽  
Seizure Termination ◽  
High Frequency Activity

Objective: Characterization of progressive multi-site seizure recruitment using high frequency oscillations. Methods: Ictal and interictal high frequency oscillations were identified in a series of 13 patients with 72 seizures recorded by stereotactic depth electrodes, using previously validated methods. Channels with ictal high frequency oscillations were assigned to distinct spatial clusters, and seizure hubs were identified by stereotypically recruited non-overlapping clusters. Clusters were correlated with asynchronous seizure terminations to provide supportive evidence for independent seizure activity at these sites. The spatial overlap of ictal and interictal high frequency oscillations were compared. Results: Ictal high frequency oscillations were detected in 71% of seizures and 10% of implanted contacts, enabling tracking of contiguous and noncontiguous seizure recruitment. Multiple seizure hubs were identified in 54% of cases, including 43% of patients thought preoperatively to have unifocal epilepsy. Noncontiguous recruitment was associated with asynchronous seizure termination (Odds Ratio=10, 95% CI 2.9-41, p<0.001). Interictal high frequency oscillations demonstrated greater spatial overlap with ictal high frequency oscillations in cases with single seizure hubs than in those with multiple hubs (100% vs 66% per patient, p=0.03). Significance: Analysis of ictal high frequency oscillations can serve as a useful adjunctive technique to distinguish contiguous seizure spread from propagation to remote seizure sites. This study demonstrated that multiple seizure hubs were commonly identified by spatial clustering of ictal high frequency oscillations, including in cases that were considered unifocal. The distinction between initially activated and delayed seizure hubs was not evident based on interictal high frequency analysis, but may provide important prognostic information.

scholarly journals High-frequency bioelectrical activity of the brain in the diagnosis of epilepsy

2018 ◽  
Vol 10 (3) ◽  
pp. 6-13 ◽  
Author(s):  
N. D. Sorokina ◽  
S. S. Pertsov ◽  
G. V. Selitsky
Keyword(s):  
High Frequency ◽  
Epileptiform Activity ◽  
Gamma Activity ◽  
Epileptic Focus ◽  
Bioelectrical Activity ◽  
Seizure Onset ◽  
High Frequency Oscillations ◽  
Gamma Rhythm ◽  
High Frequency Activity ◽  
The Brain

Recent studies show that the brain gamma activity includes both the gamma rhythm (standard EEG) and high frequency (100-1000 Hz) as well as super-high (>1000 Hz) frequency oscillations, as recorded by electrocorticography. As reported in the literature, the high-frequency oscillations (80-500 Hz) are highly informative markers of an epileptic focus. In this review, we analyze features of high-frequency activity associated with the epileptiform activity, and its relation to the seizure onset range. Further study of high-frequency bioelectric activity of the brain is of interest to researchers and clinicians, and may improve the EEG differential diagnosis of epilepsy.

scholarly journals Spatiotemporal patterns of high-frequency activity (80-170 Hz) in long-term intracranial EEG

2020 ◽  
Author(s):  
Zhuying Chen ◽  
David B. Grayden ◽  
Anthony N. Burkitt ◽  
Udaya Seneviratne ◽  
Wendyl J. D’Souza ◽  
...  
Keyword(s):  
Circadian Rhythms ◽  
High Frequency ◽  
Focal Epilepsy ◽  
Patient Specific ◽  
Intracranial Eeg ◽  
Electrode Implantation ◽  
High Frequency Oscillations ◽  
Total Data ◽  
High Frequency Activity

AbstractObjectiveTo assess the variability in the rates and locations of high-frequency activity (HFA) and epileptiform spikes after electrode implantation, and to examine the long-term patterns of HFA using ambulatory intracranial EEG (iEEG) recordings.MethodsContinuous iEEG recordings obtained over an average of 1.4 years from 15 patients with drug-resistant focal epilepsy were used in this study. HFA was defined as high-frequency events with amplitudes clearly larger than the background, which was automatically detected using a custom algorithm. High-frequency oscillations (HFOs) were also visually annotated by three neurologists in randomly sampled segments of the total data. The automatically detected HFA was compared with the visually marked HFOs. The variations of HFA rates were compared with spikes and seizures on patient-specific and electrode-specific bases.ResultsHFA was a more general event that encompassed HFOs manually annotated by different reviewers. HFA and spike rates had high amounts of intra- and inter-patient variability. The rates and locations of HFA and spikes took up to weeks to stabilize after electrode implantation in some patients. Both HFA and spike rates showed strong circadian rhythms in all patients and some also showed multiday cycles. Furthermore, the circadian patterns of HFA and spike rates had patient-specific correlations with seizures, which tended to vary across electrodes.ConclusionsAnalysis of HFA and epileptiform spikes should account for post-implantation variability. Like seizures, HFA and epileptiform spikes show circadian rhythms. However, the circadian profiles can vary spatially within patients and their correlations to seizures are patient-specific.

P57 High Frequency Oscillations in scalp EEG to monitor therapy in the individual patient

2019 ◽  
Vol 130 (8) ◽  
pp. e169
Author(s):  
E. Boran ◽  
G. Ramantani ◽  
N. Krayenbühl ◽  
J. Sarnthein ◽  
T. Fedele
Keyword(s):  
High Frequency ◽  
Scalp Eeg ◽  
High Frequency Oscillations ◽  
The Individual

scholarly journals Resection of high frequency oscillations predicts seizure outcome in the individual patient

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Tommaso Fedele ◽  
Sergey Burnos ◽  
Ece Boran ◽  
Niklaus Krayenbühl ◽  
Peter Hilfiker ◽  
...  
Keyword(s):  
High Frequency ◽  
Seizure Outcome ◽  
High Frequency Oscillations ◽  
The Individual

Real Ear Sound Pressure Levels Developed by Three Portable Stereo System Earphones

1992 ◽  
Vol 1 (4) ◽  
pp. 52-55 ◽  
Author(s):  
Gail L. MacLean ◽  
Andrew Stuart ◽  
Robert Stenstrom
Keyword(s):  
High Frequency ◽  
Sound Pressure ◽  
Low Frequency ◽  
Test System ◽  
Output Frequency ◽  
Frequency Effects ◽  
Adult Men ◽  
Frequency Responses ◽  
Significant Difference ◽  
Sound Pressure Levels

Differences in real ear sound pressure levels (SPLs) with three portable stereo system (PSS) earphones (supraaural [Sony Model MDR-44], semiaural [Sony Model MDR-A15L], and insert [Sony Model MDR-E225]) were investigated. Twelve adult men served as subjects. Frequency response, high frequency average (HFA) output, peak output, peak output frequency, and overall RMS output for each PSS earphone were obtained with a probe tube microphone system (Fonix 6500 Hearing Aid Test System). Results indicated a significant difference in mean RMS outputs with nonsignificant differences in mean HFA outputs, peak outputs, and peak output frequencies among PSS earphones. Differences in mean overall RMS outputs were attributed to differences in low-frequency effects that were observed among the frequency responses of the three PSS earphones. It is suggested that one cannot assume equivalent real ear SPLs, with equivalent inputs, among different styles of PSS earphones.

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