HFO Frequency Research Articles

Epileptic tissue localization using graph-based networks in the high frequency oscillation range of intracranial electroencephalography

PurposeHigh frequency oscillations (HFOs) are an emerging biomarker of epilepsy. However, very few studies have investigated the functional connectivity of interictal iEEG signals in the frequency range of HFOs. Here, we study the corresponding functional networks using graph theory, and we assess their predictive value for automatic electrode classification in a cohort of 20 drug resistant patients. MethodsCoherence-based connectivity analysis was performed on the iEEG recordings, and six different local graph measures were computed in both sub-bands of the HFO frequency range (80–250 Hz and 250–500 Hz). Correlation analysis was implemented between the local graph measures and the ripple and fast ripple rates. Finally, the WEKA software was employed for training and testing different predictive models on the aforementioned local graph measures. ResultsThe ripple rate was significantly correlated with five out of six local graph measures in the functional network. For fast ripples, their rate was also significantly (but negatively) correlated with most of the local metrics. The results from WEKA showed that the Logistic Regression algorithm was able to classify highly HFO-contaminated electrodes with an accuracy of 82.5 % for ripples and 75.4 % for fast ripples. ConclusionFunctional connectivity networks in the HFO band could represent an alternative to the direct use of distinct HFO events, while also providing important insights about hub epileptic areas that can represent possible surgical targets. Automatic electrode classification through FC-based classifiers can help bypass the burden of manual HFO annotation, providing at the same time similar amount of information about the epileptic tissue.

Accuracy of high-frequency oscillations recorded intraoperatively for classification of epileptogenic regions

To see whether acute intraoperative recordings using stereo EEG (SEEG) electrodes can replace prolonged interictal intracranial EEG (iEEG) recording, making the process more efficient and safer, 10 min of iEEG were recorded following electrode implantation in 16 anesthetized patients, and 1–2 days later during non-rapid eye movement (REM) sleep. Ripples on oscillations (RonO, 80–250 Hz), ripples on spikes (RonS), sharp-spikes, fast RonO (fRonO, 250–600 Hz), and fast RonS (fRonS) were semi-automatically detected. HFO power and frequency were compared between the conditions using a generalized linear mixed-effects model. HFO rates were compared using a two-way repeated measures ANOVA with anesthesia type and SOZ as factors. A receiver-operating characteristic (ROC) curve analysis quantified seizure onset zone (SOZ) classification accuracy, and the scalar product was used to assess spatial reliability. Resection of contacts with the highest rate of events was compared with outcome. During sleep, all HFOs, except fRonO, were larger in amplitude compared to intraoperatively (p < 0.01). HFO frequency was also affected (p < 0.01). Anesthesia selection affected HFO and sharp-spike rates. In both conditions combined, sharp-spikes and all HFO subtypes were increased in the SOZ (p < 0.01). However, the increases were larger during the sleep recordings (p < 0.05). The area under the ROC curves for SOZ classification were significantly smaller for intraoperative sharp-spikes, fRonO, and fRonS rates (p < 0.05). HFOs and spikes were only significantly spatially reliable for a subset of the patients (p < 0.05). A failure to resect fRonO areas in the sleep recordings trended the most sensitive and accurate for predicting failure. In summary, HFO morphology is altered by anesthesia. Intraoperative SEEG recordings exhibit increased rates of HFOs in the SOZ, but their spatial distribution can differ from sleep recordings. Recording these biomarkers during non-REM sleep offers a more accurate delineation of the SOZ and possibly the epileptogenic zone.

Laminar distribution of electrically evoked hippocampal short latency ripple activity highlights the importance of the subiculum in vivo in human epilepsy, an intraoperative study

ObjectiveThe goal of this study was to define the pathology and anesthesia dependency of single pulse electrical stimulation (SPES) dependent high-frequency oscillations (HFOs, ripples, fast ripples) in the hippocampal formation. MethodsLaminar profile of electrically evoked short latency (<100 ms) high-frequency oscillations (80−500 Hz) was examined in the hippocampus of therapy-resistant epileptic patients (6 female, 2 male) in vivo, under general anesthesia. ResultsParahippocampal SPES evoked HFOs in all recorded hippocampal subregions (Cornu Ammonis 2−3, dentate gyrus, and subiculum) were not uniform, rather the combination of ripples, fast ripples, sharp transients, and multiple unit activities. Mild and severe hippocampal sclerosis (HS) differed in the probability to evoke fast ripples: it decreased with the severity of sclerosis in CA2−3 but increased in the subiculum. Modulation in the ripple spectrum was observed only in the subiculum with increased fast HFO rate and frequency in severe HS. Inhalational anesthetics (isoflurane) suppressed the chance to evoke HFOs compared to propofol. ConclusionThe presence of early HFOs in the dentate gyrus and early fast HFOs (>250 Hz) in the other subregions indicate the pathological nature of these evoked oscillations. Subiculum was found to be active producing HFOs in parallel with the cell loss in the hippocampus proper, which emphasize the role of this region in the generation of epileptic activity.

Nasal respiration is necessary for ketamine-dependent high frequency network oscillations and behavioral hyperactivity in rats

Changes in oscillatory activity are widely reported after subanesthetic ketamine, however their mechanisms of generation are unclear. Here, we tested the hypothesis that nasal respiration underlies the emergence of high-frequency oscillations (130–180 Hz, HFO) and behavioral activation after ketamine in freely moving rats. We found ketamine 20 mg/kg provoked “fast” theta sniffing in rodents which correlated with increased locomotor activity and HFO power in the OB. Bursts of ketamine-dependent HFO were coupled to “fast” theta frequency sniffing. Theta coupling of HFO bursts were also found in the prefrontal cortex and ventral striatum which, although of smaller amplitude, were coherent with OB activity. Haloperidol 1 mg/kg pretreatment prevented ketamine-dependent increases in fast sniffing and instead HFO coupling to slower basal respiration. Consistent with ketamine-dependent HFO being driven by nasal respiration, unilateral naris blockade led to an ipsilateral reduction in ketamine-dependent HFO power compared to the control side. Bilateral nares blockade reduced ketamine-induced hyperactivity and HFO power and frequency. These findings suggest that nasal airflow entrains ketamine-dependent HFO in diverse brain regions, and that the OB plays an important role in the broadcast of this rhythm.

F92. Dense array EEG utilization in outpatient clinic: 788 Cases

Dense array EEG (dEEG) covers entire scalp surface by 128 or 256 leads, with shorter inter-electrode distance, making a better spatial resolution. It has been utilized only in selected cases for intractable seizure and a part of the presurgical evaluation. It is time-consuming to analyze EEG because of exceeding number of channels beyond the space of LCD monitor. There was no study that dEEG was applied for routine outpatient EEG evaluation. This result may be compared with routine outpatient EEG by 10–20 recording. We utilized dense array EEG system (dEEG) for patients visiting neurology clinic for mental status change in recent past 2 years. Electrodes were applied by the cap system. EEG was recorded using high-impedance DC amplification system by EGI (Eugene, OR, USA), 128 channels with a sampling frequency of 1000 Hz. We developed “double-banana” based convenient montage so that all relevant leads information can be seen by one monitor size without moving the EEG images up and down, that enabled us to review a large number of dEEG quickly. A recording sensitivity was 7 uV/mm, HFF 120 Hz, LFF 1.0 Hz. Recording duration was 30 min for all the patients. 788 dEEG recordings were accumulated in our outpatient clinic. Among them, diffuse background slowing was seen in 117 cases (14.8%), focal slowing in 197 (25%), interictal epileptiform discharges were seen in 285 (36.1%). Among the IID cases, 157 (55.1% of IID cases: 19.9% of total) were electrographic seizure pattern. Moreover, scalp permeating HFO (frequency 50–120 Hz) were seen in 46 (5.8%) Infra-slow delta (Defined as frequency <1 Hz) was seen in 39 (4.9%). 128 channel dEEG is sufficiently increased the special resolution and higher yield of inter-ictal abnormalities including IID and focal slowing. Moreover, it would increase the detecting yield of focal abnormalities, i.e., electrographic rhythmic pattern, Infra-slow delta activities, and scalp permeating HFO. Routine outpatient utilization of dEEG may potentially be more efficient in detection of abnormality than routine 10–20 system recording.

Effects of NMDA receptor antagonists and antipsychotics on high frequency oscillations recorded in the nucleus accumbens of freely moving mice.

RationaleAbnormal oscillatory activity associated with N-methyl-D-aspartate (NMDA) receptor hypofunction is widely considered to contribute to the symptoms of schizophrenia.ObjectiveThis study aims to characterise the changes produced by NMDA receptor antagonists and antipsychotics on accumbal high-frequency oscillations (HFO; 130–180 Hz) in mice.MethodsLocal field potentials were recorded from the nucleus accumbens of freely moving mice.ResultsSystemic injection of ketamine and MK801 both dose-dependently increased the power of HFO and produced small increases in HFO frequency. The atypical antipsychotic drug, clozapine, produced a robust dose-dependent reduction in the frequency of MK801-enhanced HFO, whilst haloperidol, a typical antipsychotic drug, had little effect. Stimulation of NMDA receptors (directly or through the glycine site) as well as activation of 5-HT1A receptors, reduced the frequency of MK801-enhanced HFO, but other receptors known to be targets for clozapine, namely 5-HT2A, 5-HT7 and histamine H3 receptors had no effect.ConclusionsNMDA receptor antagonists and antipsychotics produce broadly similar fundamental effects on HFO, as reported previously for rats, but we did observe several notable differences. In mice, HFO at baseline were weak or not detectable unlike rats. Post-injection of NMDA receptor antagonists HFO was also weaker but significantly faster. Additionally, we found that atypical antipsychotic drugs may reduce the frequency of HFO by interacting with NMDA and/or 5-HT1A receptors.Electronic supplementary materialThe online version of this article (doi:10.1007/s00213-015-4073-0) contains supplementary material, which is available to authorized users.

Different mechanisms of ripple‐like oscillations in the human epileptic subiculum

Transient high-frequency oscillations (HFOs; 150-600Hz) in local field potentials generated by human hippocampal and parahippocampal areas have been related to both physiological and pathological processes. The cellular basis and effects of normal and abnormal forms of HFOs have been controversial. This lack of agreement is clinically significant, because HFOs may be good markers of epileptogenic areas. Better defining the neuronal correlate of specific HFO frequency bands could improve electroencephalographic analyses made before epilepsy surgery. Here, we recorded HFOs in slices of the subiculum prepared from human hippocampal tissue resected for treatment of pharmacoresistant epilepsy. With combined intra- or juxtacellular and extracellular recordings, we examined the cellular correlates of interictal and ictal HFO events. HFOs occurred spontaneously in extracellular field potentials during interictal discharges (IIDs) and also during pharmacologically induced preictal discharges (PIDs) preceding ictal-like events. Many of these events included frequencies >250Hz and so might be considered pathological, but a significant proportion were spectrally similar to physiological ripples (150-250Hz). We found that IID ripples were associated with rhythmic γ-aminobutyric acidergic and glutamatergic synaptic potentials with moderate neuronal firing. In contrast, PID ripples were associated with depolarizing synaptic inputs frequently reaching the threshold for bursting in most pyramidal cells. Our data suggest that IID and PID ripple-like oscillations (150-250Hz) in human epileptic hippocampus are associated with 2 distinct population activities that rely on different cellular and synaptic mechanisms. Thus, the ripple band could not help to disambiguate the underlying cellular processes.

Antipsychotic compounds differentially modulate high-frequency oscillations in the rat nucleus accumbens: a comparison of first- and second-generation drugs

Improved understanding of the actions of antipsychotic compounds is critical for a better treatment of schizophrenia. Abnormal oscillatory activity has been found in schizophrenia and in rat models of the disease. N-Methyl-D-aspartic acid receptor (NMDAR) antagonists, used to model certain features of schizophrenia, increase the frequency and power of high-frequency oscillations (HFO, 130-180 Hz) in the rat nucleus accumbens, a brain region implicated in schizophrenia pathology. Antipsychotics can be classified as first- and second-generation drugs, the latter often reported to have wider benefit in humans and experimental models. This prompted the authors to examine the pre- and post-treatment effects of clozapine, risperidone (second-generation drugs) and sulpiride and haloperidol (first-generation drugs) on ketamine and MK801-enhanced accumbal HFO. Both NMDAR antagonists increased HFO frequency. In contrast, clozapine and risperidone markedly and dose-dependently reduced the frequency of spontaneous and NMDAR-antagonist-enhanced HFO, whilst a moderate effect was found for sulpiride and a much weaker effect for haloperidol. Unexpectedly, we found reductions in HFO frequency were associated with an increase in its power. These findings indicate that modulation of accumbal HFO frequency may be a fundamental effect produced by antipsychotic compounds. Of the drugs investigated, first- and second-generation compounds could be dissociated by their potency on this measure. This effect may partially explain the differences in the clinical profile of these drugs.

Network interactions in inspiratory (I) and expiratory (E) neuron populations as indicated by high-frequency oscillations

Fast rhythms are present in neural discharges of many motor systems. In the decerebrate cat, high-frequency oscillations (HFO, range 50–100 Hz) are ubiquitous in the discharges of Imotoneurons (phrenic, recurrent laryngeal, external intercostal) and of medullary Ineurons. The amplitude and frequency of HFO are greater when respiratory drive is increased. Coherence spectral analysis shows that the various discharges (population and unit) are significantly correlated at the HFO frequency. This indicates that the common rhythm arises in the brainstem and is transmitted to cranial motoneurons via propriobulbar projections and to spinal motoneurons via bulbospinal projections.

High-frequency oscillations in membrane potentials of medullary inspiratory and expiratory neurons (including laryngeal motoneurons).

1. In midcollicular decerebrate, unanesthetized, paralyzed cats ventilated with a cycle-triggered pump system, the properties of high-frequency oscillations (HFOs, 50-100 Hz) in membrane potentials (MPs) of medullary inspiratory (I) and expiratory (E) cells were studied. Simultaneous recordings were taken from bilateral phrenic and recurrent laryngeal (RL) nerves and from cells in the intermediate ventral respiratory group (intVRG, 0-1 mm rostral to the obex) or the caudal ventral respiratory group (cVRG, 2-4 mm caudal to the obex). 2. Spectral coherence analyses were used to detect the presence of HFOs during I in I and E cell MPs. Cross-correlation histograms (CCHs) between the cell and phrenic signals were used to ascertain cell-nerve HFO phase relations and to identify cells as RL motoneurons. Of the 103 cells that had significant HFOs (cell-phrenic coherences > or = 0.1), measurable HFO peak lags in the CCH were seen in 53 cells: 1) RL cells (9 I cells and 7 E cells); and 2) other types of cell (8 intVRG I cells, 18 intVRG E cells, and 11 cVRG E cells). These cells had high HFO correlations; the cell-phrenic coherence range was 0.35-0.94, with a mean HFO frequency of 58 Hz. 3. The cell-phrenic HFO lag (in ms) was measured in the CCH as the lag of the primary peak (peak located nearest to 0 lag). The phase lag was defined as (lag of primary peak in ms)/(HFO period in ms). The phase lags differed markedly between two subsets of cells: 1) RL I cells had HFO depolarization peaks that lagged the phrenic HFO peaks (average cell-phrenic phase lag = -0.18); and 2) the non-RL cells, regardless of location (intVRG or cVRG) and type (I or E), had HFO depolarization peaks leading (preceding) the phrenic HFO peaks (average cell-phrenic phase lag = 0.28). In addition, the cVRG E cells had significantly shorter cell-phrenic phase lags than the intVRG E cells (0.23 vs. 0.31, respectively). 4. These lags can be compared with the (I unit)-phrenic phase lags (average approximately 0.3) found in earlier extracellular studies. 1) There is a transmission delay of about one half HFO cycle from excitatory I cells to RL I cells. 2) Because a depolarization peak in the MP of an E cell corresponds to the start of a hyperpolarizing wave, the excitatory bulbospinal pathways from I cells have transmission times comparable with those of the inhibitory intramedullary pathways from I cells to E cells. 5. These results indicate that study of HFO phase relations can furnish useful information on functional connectivity of medullary respiratory neurons during the I phase.

Analysis of recurrent laryngeal inspiratory discharges in relation to fast rhythms.

1. Inspiratory (I) activities of recurrent laryngeal (RL) motoneurons and efferent nerves were studied by autospectral, interval, and coherence analyses, with emphasis on fast rhythms of two types: medium-frequency oscillations (MFO, usual range 20-50 Hz for nerve autospectral peaks) and high-frequency oscillations (HFO, usual range 50-100 Hz). 2. In decerebrate, paralyzed, and artificially ventilated cats, recordings were taken from 27 isolated single RL fibers (14 cats) and 8 identified RL motoneurons in the medulla (6 cats), together with recordings of phrenic (PHR) and RL whole-nerve activities. In another 50 cats, RL and PHR nerve discharges were recorded simultaneously. 3. The autospectra of RL units showed prominent MFO peaks with frequencies close to that of the RL nerve MFO spectral peak, indicating presence of this type of fast rhythm in the units' discharges. Spectral analysis of RL unit activity in different segments of the I phase showed that the frequency of a unit's MFO was very close to the peak (maintained) firing rate of the unit during the portion of I analyzed. Thus a motoneuron's MFO spectral peak reflected its rhythmic discharge arising from the cell's refractoriness (and possibly with the rate changing in the course of I). 4. The coherences of motoneurons' MFOs to nerve MFOs were very low or 0, indicating that correlations between unitary MFOs of the RL population were rare and/or weak. 5. In those cats (19/20) that had discernible PHR nerve HFO autospectral peaks, about half of the recorded RL motoneurons (16/34) had HFO. For these motoneurons, the unit-nerve HFO coherences were substantial, indicating widespread correlations between unitary HFOs. 6. In a fraction of cats, coherence peaks in the MFO frequency range were observed between bilateral RL nerves, and between RL and PHR nerves, at frequencies that were subharmonics of the HFO frequency. 7. In light of theoretical considerations on the generation of aggregate rhythms from superposition of unitary rhythms, these observations indicate that, similarly, to the case of PHR motoneurons and nerves. 1) RL nerve MFO arises from superposition of uncorrelated, or at most partially correlated, MFOs of RL units, representing the rhythmic discharges of the cells. It is manifested therefore as a spectral deflection with a maximum in the band of peak firing rates of the units. 2) RL nerve HFO arises from correlated, common-frequency HFOs in a subpopulation of RL units, caused by HFO inputs from antecedent medullary I neurons.(ABSTRACT TRUNCATED AT 400 WORDS)