A method for the topographical identification and quantification of high frequency oscillations in intracranial electroencephalography recordings

OBJECTIVE

To develop a reliable software method using a topographic analysis of time-frequency plots to distinguish ripple (80-200 Hz) oscillations that are often associated with EEG sharp waves or spikes (RonS) from sinusoid-like waveforms that appear as ripples but correspond with digital filtering of sharp transients contained in the wide bandwidth EEG.

METHODS

A custom algorithm distinguished true from false ripples in one second intracranial EEG (iEEG) recordings using wavelet convolution, identifying contours of isopower, and categorizing these contours into sets of open or closed loop groups. The spectral and temporal features of candidate groups were used to classify the ripple, and determine its duration, frequency, and power. Verification of detector accuracy was performed on the basis of simulations, and visual inspection of the original and band-pass filtered signals.

RESULTS

The detector could distinguish simulated true from false ripple on spikes (RonS). Among 2934 visually verified trials of iEEG recordings and spectrograms exhibiting RonS the accuracy of the detector was 88.5% with a sensitivity of 81.8% and a specificity of 95.2%. The precision was 94.5% and the negative predictive value was 84.0% (N = 12). Among, 1,370 trials of iEEG recording exhibiting RonS that were reviewed blindly without spectrograms the accuracy of the detector was 68.0%, with kappa equal to 0.01 ± 0.03. The detector successfully distinguished ripple from high spectral frequency 'fast ripple' oscillations (200-600 Hz), and characterize ripple duration and spectral frequency and power. The detector was confounded by brief bursts of gamma (30-80 Hz) activity in 7.31 ± 6.09% of trials, and in 30.2 ± 14.4% of the true RonS detections ripple duration was underestimated.

CONCLUSIONS

Characterizing the topographic features of a time-frequency plot generated by wavelet convolution is useful for distinguishing true oscillations from false oscillations generated by filter ringing.

SIGNIFICANCE

Categorizing ripple oscillations and characterizing their properties can improve the clinical utility of the biomarker.

Bimodal coupling of ripples and slower oscillations during sleep in patients with focal epilepsy

OBJECTIVE

Differentiating pathologic and physiologic high-frequency oscillations (HFOs) is challenging. In patients with focal epilepsy, HFOs occur during the transitional periods between the up and down state of slow waves. The preferred phase angles of this form of phase-event amplitude coupling are bimodally distributed, and the ripples (80-150 Hz) that occur during the up-down transition more often occur in the seizure-onset zone (SOZ). We investigated if bimodal ripple coupling was also evident for faster sleep oscillations, and could identify the SOZ.

METHODS

Using an automated ripple detector, we identified ripple events in 40-60 min intracranial electroencephalography (iEEG) recordings from 23 patients with medically refractory mesial temporal lobe or neocortical epilepsy. The detector quantified epochs of sleep oscillations and computed instantaneous phase. We utilized a ripple phasor transform, ripple-triggered averaging, and circular statistics to investigate phase event-amplitude coupling.

RESULTS

We found that at some individual recording sites, ripple event amplitude was coupled with the sleep oscillatory phase and the preferred phase angles exhibited two distinct clusters (p < 0.05). The distribution of the pooled mean preferred phase angle, defined by combining the means from each cluster at each individual recording site, also exhibited two distinct clusters (p < 0.05). Based on the range of preferred phase angles defined by these two clusters, we partitioned each ripple event at each recording site into two groups: depth iEEG peak-trough and trough-peak. The mean ripple rates of the two groups in the SOZ and non-SOZ (NSOZ) were compared. We found that in the frontal (spindle, p = 0.009; theta, p = 0.006, slow, p = 0.004) and parietal lobe (theta, p = 0.007, delta, p = 0.002, slow, p = 0.001) the SOZ incidence rate for the ripples occurring during the trough-peak transition was significantly increased.

SIGNIFICANCE

Phase-event amplitude coupling between ripples and sleep oscillations may be useful to distinguish pathologic and physiologic events in patients with frontal and parietal SOZ.

Ripples on spikes show increased phase-amplitude coupling in mesial temporal lobe epilepsy seizure-onset zones

OBJECTIVE

Ripples (80-150 Hz) recorded from clinical macroelectrodes have been shown to be an accurate biomarker of epileptogenic brain tissue. We investigated coupling between epileptiform spike phase and ripple amplitude to better understand the mechanisms that generate this type of pathologic ripple (pRipple) event.

METHODS

We quantified phase amplitude coupling (PAC) between epileptiform electroencephalography (EEG) spike phase and ripple amplitude recorded from intracranial depth macroelectrodes during episodes of sleep in 12 patients with mesial temporal lobe epilepsy. PAC was determined by (1) a phasor transform that corresponds to the strength and rate of ripples coupled with spikes, and a (2) ripple-triggered average to measure the strength, morphology, and spectral frequency of the modulating and modulated signals. Coupling strength was evaluated in relation to recording sites within and outside the seizure-onset zone (SOZ).

RESULTS

Both the phasor transform and ripple-triggered averaging methods showed that ripple amplitude was often robustly coupled with epileptiform EEG spike phase. Coupling was found more regularly inside than outside the SOZ, and coupling strength correlated with the likelihood a macroelectrode's location was within the SOZ (p < 0.01). The ratio of the rate of ripples coupled with EEG spikes inside the SOZ to rates of coupled ripples in non-SOZ was greater than the ratio of rates of ripples on spikes detected irrespective of coupling (p < 0.05). Coupling strength correlated with an increase in mean normalized ripple amplitude (p < 0.01), and a decrease in mean ripple spectral frequency (p < 0.05).

SIGNIFICANCE

Generation of low-frequency (80-150 Hz) pRipples in the SOZ involves coupling between epileptiform spike phase and ripple amplitude. The changes in excitability reflected as epileptiform spikes may also cause clusters of pathologically interconnected bursting neurons to grow and synchronize into aberrantly large neuronal assemblies.

The progression of electrophysiologic abnormalities during epileptogenesis after experimental traumatic brain injury

OBJECTIVE

Posttraumatic epilepsy (PTE) accounts for 20% of acquired epilepsies. Experimental models are important for studying epileptogenesis. We previously reported that repetitive high-frequency oscillations with spikes (rHFOSs) occur early after lateral fluid percussion injury (FPI) and may be a biomarker for PTE. The objective of this study was to use multiple electrodes in rat hippocampal and neocortical regions to describe the long-term electroencephalographic and behavioral evolution of rHFOSs and epileptic seizures after traumatic brain injury (TBI).

METHODS

Adult male rats underwent mild, moderate, or severe FPI or sham injury followed by video-electroencephalography (EEG) recordings with a combination of 16 neocortical and hippocampal electrodes at an early, intermediate, or late time-point after injury, up to 52 weeks. Recordings were analyzed for the presence of rHFOSs and seizures.

RESULTS

Analysis was done on 28 rats with FPI and 7 shams. Perilesional rHFOSs were recorded in significantly more rats after severe (70.3%) than mild (20%) injury or shams (14.3%). Frequency of occurrence was significantly highest in the early (10.8/h) versus late group (3.2/h). Late focal seizures originating from the same electrodes were recorded in significantly more rats in the late (87.5%) versus early period (22.2%), occurring almost exclusively in injured rats. Seizure duration increased significantly over time, averaging 19 s at the beginning of the early period and 27 s at the end of the late period. Seizure frequency also increased significantly over time, from 4.4 per week in the early group to 26.4 per week in the late group. Rarely, rats displayed early seizures or generalized seizures.

SIGNIFICANCE

FPI results in early rHFOSs and later spontaneous focal seizures arising from peri-lesional neocortex, supporting its use as a model for PTE. Epilepsy severity increased over time and was related to injury severity. The association between early rHFOSs and later focal seizures suggests that rHFOSs may be a potential noninvasive biomarker of PTE.

Pathologic electrographic changes after experimental traumatic brain injury

OBJECTIVE

To investigate possible electroencephalography (EEG) correlates of epileptogenesis after traumatic brain injury (TBI) using the fluid percussion model.

METHODS

Experiments were conducted on adult 2- to 4-month-old male Sprague-Dawley rats. Two groups of animals were studied: (1) the TBI group with depth and screw electrodes implanted immediately after the fluid percussion injury (FPI) procedure, and (2) a naive age-matched control group with the same electrode implantation montage. Pairs of tungsten microelectrodes (50 μm outer diameter) and screw electrodes were implanted in neocortex inside the TBI core, areas adjacent to TBI, and remote areas. EEG activity, recorded on the day of FPI, and continuously for 2 weeks, was analyzed for possible electrographic biomarkers of epileptogenesis. Video-EEG monitoring was also performed continuously in the TBI group to capture electrographic and behavioral seizures until the caps came off (28-189 days), and for 1 week, at 2, 3, and 6 months of age, in the control group.

RESULTS

Pathologic high-frequency oscillations (pHFOs) with a central frequency between 100 and 600 Hz, were recorded from microelectrodes, beginning during the first two post-FPI weeks, in 7 of 12 animals in the TBI group (58%) and never in the controls. pHFOs only occurred in cortical areas within or adjacent to the TBI core. These were associated with synchronous multiunit discharges and popSpikes, duration 15-40 msec. Repetitive pHFOs and EEG spikes (rHFOSs) formed paroxysmal activity, with a unique arcuate pattern, in the frequency band 10-16 Hz in the same areas as isolated pHFOs, and these events were also recorded by screw electrodes. Although loss of caps prevented long-term recordings from all rats, pHFOs and rHFOSs occurred during the first 2 weeks in all four animals that later developed seizures, and none of the rats without these events developed late seizures.

SIGNIFICANCE

pHFOs, similar to those associated with epileptogenesis in the status rat model of epilepsy, may also reflect epileptogenesis after FPI. rHFOSs could be noninvasive biomarkers of epileptogenesis.

Ictal onset patterns of local field potentials, high frequency oscillations, and unit activity in human mesial temporal lobe epilepsy

OBJECTIVE

To characterize local field potentials, high frequency oscillations, and single unit firing patterns in microelectrode recordings of human limbic onset seizures.

METHODS

Wide bandwidth local field potential recordings were acquired from microelectrodes implanted in mesial temporal structures during spontaneous seizures from six patients with mesial temporal lobe epilepsy.

RESULTS

In the seizure onset zone, distinct epileptiform discharges were evident in the local field potential prior to the time of seizure onset in the intracranial EEG. In all three seizures with hypersynchronous (HYP) seizure onset, fast ripples with incrementally increasing power accompanied epileptiform discharges during the transition to the ictal state (p < 0.01). In a single low voltage fast (LVF) onset seizure a triad of evolving HYP LFP discharges, increased single unit activity, and fast ripples of incrementally increasing power were identified ~20 s prior to seizure onset (p < 0.01). In addition, incrementally increasing fast ripples occurred after seizure onset just prior to the transition to LVF activity (p < 0.01). HYP onset was associated with an increase in fast ripple and ripple rate (p < 0.05) and commonly each HYP discharge had a superimposed ripple followed by a fast ripple. Putative excitatory and inhibitory single units could be distinguished during limbic seizure onset, and heterogeneous shifts in firing rate were observed during LVF activity.

SIGNIFICANCE

Epileptiform activity is detected by microelectrodes before it is detected by depth macroelectrodes, and the one clinically identified LVF ictal onset was a HYP onset at the local level. Patterns of incrementally increasing fast ripple power are consistent with observations in rats with experimental hippocampal epilepsy, suggesting that limbic seizures arise when small clusters of synchronously bursting neurons increase in size, coalesce, and reach a critical mass for propagation.

Variants of Porphyromonas gingivalis lipopolysaccharide alter lipidation of autophagic protein, microtubule-associated protein 1 light chain 3, LC3

Porphyromonas gingivalis often subverts host cell autophagic processes for its own survival. Our previous studies document the association of the cargo sorting protein, melanoregulin (MREG), with its binding partner, the autophagic protein, microtubule-associated protein 1 light chain 3 (LC3) in macrophages incubated with P. gingivalis (strain 33277). Differences in the lipid A moiety of lipopolysaccharide (LPS) affect the virulence of P. gingivalis; penta-acylated LPS₁₆₉₀ is a weak Toll-like receptor 4 agonist compared with Escherichia coli LPS, whereas tetra-acylated LPS_1435/1449 acts as an LPS₁₆₉₀ antagonist. To determine how P. gingivalis LPS₁₆₉₀ affects autophagy we assessed LC3-dependent and MREG-dependent processes in green fluorescent protein (GFP)-LC3-expressing Saos-2 cells. LPS₁₆₉₀ stimulated the formation of very large LC3-positive vacuoles and MREG puncta. This LPS₁₆₉₀ -mediated LC3 lipidation decreased in the presence of LPS_1435/1449 . When Saos-2 cells were incubated with P. gingivalis the bacteria internalized but did not traffic to GFP-LC3-positive structures. Nevertheless, increases in LC3 lipidation and MREG puncta were observed. Collectively, these results suggest that P. gingivalis internalization is not necessary for LC3 lipidation. Primary human gingival epithelial cells isolated from patients with periodontitis showed both LC3II and MREG puncta whereas cells from disease-free individuals exhibited little co-localization of these two proteins. These results suggest that the prevalence of a particular LPS moiety may modulate the degradative capacity of host cells, so influencing bacterial survival.

Molecular alterations in areas generating fast ripples in an animal model of temporal lobe epilepsy

The molecular basis of epileptogenesis is poorly characterized. Studies in humans and animal models have identified an electrophysiological signature that precedes the onset of epilepsy, which has been termed fast ripples (FRs) based on its frequency. Multiple lines of evidence implicate regions generating FRs in epileptogenesis, and FRs appear to demarcate the seizure onset zone, suggesting a role in ictogenesis as well. We performed gene expression analysis comparing areas of the dentate gyrus that generate FRs to those that do not generate FRs in a well-characterized rat model of epilepsy. We identified a small cohort of genes that are differentially expressed in FR versus non-FR brain tissue and used quantitative PCR to validate some of those that modulate neuronal excitability. Gene expression network analysis demonstrated conservation of gene co-expression between non-FR and FR samples, but examination of gene connectivity revealed changes that were most pronounced in the cm-40 module, which contains several genes associated with synaptic function and the differentially expressed genes Kcna4, Kcnv1, and Npy1r that are down-regulated in FRs. We then demonstrate that the genes within the cm-40 module are regulated by seizure activity and enriched for the targets of the RNA binding protein Elavl4. Our data suggest that seizure activity induces co-expression of genes associated with synaptic transmission and that this pattern is attenuated in areas displaying FRs, implicating the failure of this mechanism in the generation of FRs.

Single-unit activities during epileptic discharges in the human hippocampal formation

Between seizures the brain of patients with epilepsy generates pathological patterns of synchronous activity, designated as interictal epileptiform discharges (ID). Using microelectrodes in the hippocampal formations of 8 patients with drug-resistant temporal lobe epilepsy, we studied ID by simultaneously analyzing action potentials from individual neurons and the local field potentials (LFPs) generated by the surrounding neuronal network. We found that ~30% of the units increased their firing rate during ID and 40% showed a decrease during the post-ID period. Surprisingly, 30% of units showed either an increase or decrease in firing rates several hundred of milliseconds before the ID. In 4 patients, this pre-ID neuronal firing was correlated with field high-frequency oscillations at 40-120 Hz. Finally, we observed that only a very small subset of cells showed significant coincident firing before or during ID. Taken together, we suggested that, in contrast to traditional views, ID are generated by a sparse neuronal network and followed a heterogeneous synchronization process initiated over several hundreds of milliseconds before the paroxysmal discharges.

Functional connectivity between brain areas estimated by analysis of gamma waves

The goal of this study is to investigate functional connectivity between different brain regions by analyzing the temporal relationship of the maxima of gamma waves recorded in multiple brain areas. Local field potentials were recorded from motor cortex, hippocampus, entorhinal cortex and piriform cortex of rats. Gamma activity was filtered and separated into two bands; high (65-90Hz) and low (30-55Hz) gamma. Maxima for gamma activity waves were detected and functional connectivity between different brain regions was determined using Shannon entropy for perievent histograms for each pair channels. Significant Shannon entropy values were reported as connectivity factors. We defined a connectivity matrix based the connectivity factors between different regions. We found that maxima of low and high frequency gamma occur in strong temporal relationship between some brain areas, indicating the existence of functional connections between these areas. The spatial pattern of functional connections between brain areas was different for slow wave sleep and waking states. However for each behavioral state in the same animal the pattern of functional connections was stable over time within 30min of continuous analysis and over a 5 day period. With the same electrode montage the pattern of functional connectivity varied from one subject to another. Analysis of the temporal relationship of maxima of gamma waves between various brain areas could be a useful tool for investigation of functional connections between these brain areas. This approach could be applied for analysis of functional alterations occurring in these connections during different behavioral tasks and during processes related to learning and memory. The specificity in the connectivity pattern from one subject to another can be explained by the existence of unique functional networks for each subject.

Patterns of the UP-Down state in normal and epileptic mice

Goal of this manuscript is to investigate whether changes that exist in epileptic brain generating spontaneous seizures are reflected in the pattern of the UP-Down state (UDS) recorded from the neocortex and dentate gyrus. Experiments were carried out on naive and epileptic mice under urethane anesthesia. Local field potentials were recorded with chronically implanted microelectrodes and single unit activity was recorded with glass microelectrodes. Recorded neurons were labeled by neurobiotin and identified later as granular cells or interneurons in histological sections. The following major features differentiate the pattern of UDS in epilepsy from normal. (1) The duration of UP and Down phases is significantly longer. (2) Recovery of network excitability after termination of the UP phase is longer. (3) UP-spikes occur during the UP phase, which transiently interrupt the development of the normal electrographic pattern of UP phase. Our data provide evidence that UP-spikes result from gigantic EPSPs generated in response to afferent activity. UP-spikes in the neocortex and dentate gyrus occur in close temporal relationship indicating the existence of direct or indirect pathological functional connections between these areas. Changes in the duration of UP and Down phases as well increased time of recovery of excitability of epileptic brain after termination of UP phase suggest alterations in the homeostatic properties of neuronal network in epileptic brain. We suggest that the existence of UP-spikes in epileptic brain may be an additional electrographic pattern indicating epileptogenicity. Unraveling the neuronal substrates of UP-spikes may further improve our understanding of the mechanisms of epilepsy.

Novel Cell and Tissue Acquisition System (CTAS): microdissection of live and frozen brain tissues

We developed a novel, highly accurate, capillary based vacuum-assisted microdissection device CTAS - Cell and Tissue Acquisition System, for efficient isolation of enriched cell populations from live and freshly frozen tissues, which can be successfully used in a variety of molecular studies, including genomics and proteomics. Specific diameter of the disposable capillary unit (DCU) and precisely regulated short vacuum impulse ensure collection of the desired tissue regions and even individual cells. We demonstrated that CTAS is capable of dissecting specific regions of live and frozen mouse and rat brain tissues at the cellular resolution with high accuracy. CTAS based microdissection avoids potentially harmful physical treatment of tissues such as chemical treatment, laser irradiation, excessive heat or mechanical cell damage, thus preserving primary functions and activities of the dissected cells and tissues. High quality DNA, RNA, and protein can be isolated from CTAS-dissected samples, which are suitable for sequencing, microarray, 2D gel-based proteomic analyses, and Western blotting. We also demonstrated that CTAS can be used to isolate cells from native living tissues for subsequent recultivation of primary cultures without affecting cellular viability, making it a simple and cost-effective alternative for laser-assisted microdissection.

Inhibition of aminoacylase 3 protects rat brain cortex neuronal cells from the toxicity of 4-hydroxy-2-nonenal mercapturate and 4-hydroxy-2-nonenal

4-Hydroxy-2-nonenal (4HNE) and acrolein (ACR) are highly reactive neurotoxic products of lipid peroxidation that are implicated in the pathogenesis and progression of Alzheimer's and Parkinson's diseases. Conjugation with glutathione (GSH) initiates the 4HNE and ACR detoxification pathway, which generates the mercapturates of 4HNE and ACR that can be excreted. Prior work has shown that the efficiency of the GSH-dependent renal detoxification of haloalkene derived mercapturates is significantly decreased upon their deacetylation because of rapid transformation of the deacetylated products into toxic compounds mediated by β-lyase. The enzymes of the GSH-conjugation pathway and β-lyases are expressed in the brain, and we hypothesized that a similar toxicity mechanism may be initiated in the brain by the deacetylation of 4HNE- and ACR-mercapturate. The present study was performed to identify an enzyme(s) involved in 4HNE- and ACR-mercapturate deacetylation, characterize the brain expression of this enzyme and determine whether its inhibition decreases 4HNE and 4HNE-mercapturate neurotoxicity. We demonstrated that of two candidate deacetylases, aminoacylases 1 (AA1) and 3 (AA3), only AA3 efficiently deacetylates both 4HNE- and ACR-mercapturate. AA3 was further localized to neurons and blood vessels. Using a small molecule screen we generated high-affinity AA3 inhibitors. Two of them completely protected rat brain cortex neurons expressing AA3 from the toxicity of 4HNE-mercapturate. 4HNE-cysteine (4HNE-Cys) was also neurotoxic and its toxicity was mostly prevented by a β-lyase inhibitor, aminooxyacetate. The results suggest that the AA3 mediated deacetylation of 4HNE-mercapturate may be involved in the neurotoxicity of 4HNE.

Non-linear classification of heart rate parameters as a biomarker for epileptogenesis

PURPOSE

To characterize a biomarker for epileptogenesis based on cardiac interbeat interval characteristics.

METHODS

Electrocardiograph (ECG) and electroencephalogram (EEG) signals were recorded from freely moving rats (n = 23) before status epilepticus (SE) induced by i.p. pilocarpine (PILO) injection as baseline, and on days 1, 3 and 7 after SE. We assessed several features from cardiac interbeat intervals, including linear, non-linear and frequency parameters of interbeat intervals, and power spectra of interpolated intervals during epileptogenesis. After thresholding, the altered values were applied to a non-linear classifier. The non-linear classifier divided animals into two groups; with and without epilepsy, based on all collected data.

RESULTS

We found that none of the single altered parameters in cardiac activity emerged as a sole biomarker for epileptogenesis. However, the non-linear classifier distinguished animals that later developed from those and did not develop epilepsy. The non-linear classification was performed on preliminary findings from 23 animals; six did not develop epilepsy and the rest did. The average positive predictive value (precision rate) was 78%. This was calculated based on the average sensitivity and specificity, which were 80.6% and 35.2% respectively, for the 100 classification passes. We also showed that these numbers would have increased as the number of subjects increased.

CONCLUSION

Changes to the brain caused by status epilepticus that lead to epileptogenesis have systemic effects, and alter cardiac activity. A non-linear classifier performed on several extracted features of cardiac interbeat intervals may be useful as a biomarker to identify animals with low and high probability of developing epilepsy after status epilepticus.

Imaging brain neuronal activity using functionalized magnetonanoparticles and MRI

This study explored the use of non-radioactive 2-deoxy glucose (2DG)-labeled magnetonanoparticles (MNP) and magnetic resonance imaging (MRI) to detect functional activity during rest, peripheral stimulation, and epileptic seizures, in animal models. Non-radioactive 2DG was covalently attached to magnetonanoparticles composed of iron oxide and dextran and intravenous (tail) injections were performed. 2DG-MNP was injected in resting and stimulated naïve rodents and the subsequent MRI was compared to published (14)C-2DG autoradiography data. Reproducibility and statistical significance was established in one studied model. Negative contrast enhancement (NCE) in acute seizures and chronic models of epilepsy were investigated. MRI NCE due to 2DG-MNP particles was compared to that of plain (unconjugated) MNP in one animal. NCE due to 2DG-MNP particles at 3 T, which is approved for human use, was also investigated. Histology showed presence of MNP (following intravenous injection) in the brain tissues of resting naïve animal. 2DG-MNP intraparenchymal uptake was visible on MRI and histology. The locations of NCE agreed with published results of 2DG autoradiography in resting and stimulated animals and epileptic rats. Localization of epileptogenicity was confirmed by subsequent depth-electrode EEG (iEEG). Non-radioactive 2DG-MNP can cross the blood-brain barrier (BBB) and may accurately localize areas of increased activity. Although, this proof-of-principle study involves only a limited number of animals, and much more research and quantification are necessary to demonstrate that 2DG-MNP, or MNPs conjugated with other ligands, could eventually be used to image localized cerebral function with MRI in humans, this MNP-MRI approach is potentially applicable to the use of many bioactive molecules as ligands for imaging normal and abnormal localized cerebral functions.

Mechanisms of physiological and epileptic HFO generation

High frequency oscillations (HFO) have a variety of characteristics: band-limited or broad-band, transient burst-like phenomenon or steady-state. HFOs may be encountered under physiological or under pathological conditions (pHFO). Here we review the underlying mechanisms of oscillations, at the level of cells and networks, investigated in a variety of experimental in vitro and in vivo models. Diverse mechanisms are described, from intrinsic membrane oscillations to network processes involving different types of synaptic interactions, gap junctions and ephaptic coupling. HFOs with similar frequency ranges can differ considerably in their physiological mechanisms. The fact that in most cases the combination of intrinsic neuronal membrane oscillations and synaptic circuits are necessary to sustain network oscillations is emphasized. Evidence for pathological HFOs, particularly fast ripples, in experimental models of epilepsy and in human epileptic patients is scrutinized. The underlying mechanisms of fast ripples are examined both in the light of animal observations, in vivo and in vitro, and in epileptic patients, with emphasis on single cell dynamics. Experimental observations and computational modeling have led to hypotheses for these mechanisms, several of which are considered here, namely the role of out-of-phase firing in neuronal clusters, the importance of strong excitatory AMPA-synaptic currents and recurrent inhibitory connectivity in combination with the fast time scales of IPSPs, ephaptic coupling and the contribution of interneuronal coupling through gap junctions. The statistical behaviour of fast ripple events can provide useful information on the underlying mechanism and can help to further improve classification of the diverse forms of HFOs.

High-frequency oscillations and other electrophysiological biomarkers of epilepsy: underlying mechanisms

In the normal mammalian brain, neuronal synchrony occurs on a spatial scale of submillimeters to centimeters and temporal scale of submilliseconds to seconds that is reflected in the occurrence of high-frequency oscillations, physiological sharp waves and slow wave sleep oscillations referred to as Up-Down states. In the epileptic brain, the well-studied pathologic counterparts to these physiological events are pathological high-frequency oscillations and interictal spikes that could be electrophysiological biomarkers of epilepsy. Establishing these abnormal events as biomarkers of epilepsy will largely depend on a better understanding of the mechanisms underlying their generation, which will not only help distinguish pathological from physiological events, but will also determine what roles these pathological events play in epileptogenesis and epileptogenicity. This article focuses on the properties and neuronal mechanisms supporting the generation of high-frequency oscillations and interictal spikes, and introduces a new phenomenon called Up-spikes.

Absence of CNTNAP2 leads to epilepsy, neuronal migration abnormalities, and core autism-related deficits

Although many genes predisposing to autism spectrum disorders (ASD) have been identified, the biological mechanism(s) remain unclear. Mouse models based on human disease-causing mutations provide the potential for understanding gene function and novel treatment development. Here, we characterize a mouse knockout of the Cntnap2 gene, which is strongly associated with ASD and allied neurodevelopmental disorders. Cntnap2(-/-) mice show deficits in the three core ASD behavioral domains, as well as hyperactivity and epileptic seizures, as have been reported in humans with CNTNAP2 mutations. Neuropathological and physiological analyses of these mice before the onset of seizures reveal neuronal migration abnormalities, reduced number of interneurons, and abnormal neuronal network activity. In addition, treatment with the FDA-approved drug risperidone ameliorates the targeted repetitive behaviors in the mutant mice. These data demonstrate a functional role for CNTNAP2 in brain development and provide a new tool for mechanistic and therapeutic research in ASD.

High-frequency activity in experimental and clinical epileptic foci

Pathological high-frequency electrographic activity (pHFA, >80Hz) represents one of the major discoveries in epilepsy research over the past few decades. In this review we focus on the high-frequency activity recorded in vivo in chronic models of epilepsy. The presence of HFA particularly of fast ripples (250-600Hz)reflects epileptogenic reorganization of brain tissue, endogenous epileptogenicity and ability to generate spontaneous seizures. The spatial distribution of epileptic HFA can be used to localize epileptic foci. In some regions of brain the localizing value of epileptic HFA is weakened by frequency overlap with physiological HFA. In this situation, only detailed knowledge of the regional physiological activity may provide relevant information which frequencies provide localizing information. In the epileptic hippocampus, the activity from 250Hz to 600Hz frequency band (fast ripples) is always epileptic and can be used as reliable marker of epileptic tissue in all hippocampal subregions. The localizing value of HFA in the identification of the epileptic focus is discussed from an experimental and clinical perspective; as the information provided by HFA can improve presurgical diagnosis and surgical outcome. Finally, research into HFA has contributed to improved understanding and new insights into the cellular and network organization of epileptic foci and the pathophysiology of epilepsy.

A systems level, functional genomics analysis of chronic epilepsy

Neither the molecular basis of the pathologic tendency of neuronal circuits to generate spontaneous seizures (epileptogenicity) nor anti-epileptogenic mechanisms that maintain a seizure-free state are well understood. Here, we performed transcriptomic analysis in the intrahippocampal kainate model of temporal lobe epilepsy in rats using both Agilent and Codelink microarray platforms to characterize the epileptic processes. The experimental design allowed subtraction of the confounding effects of the lesion, identification of expression changes associated with epileptogenicity, and genes upregulated by seizures with potential homeostatic anti-epileptogenic effects. Using differential expression analysis, we identified several hundred expression changes in chronic epilepsy, including candidate genes associated with epileptogenicity such as Bdnf and Kcnj13. To analyze these data from a systems perspective, we applied weighted gene co-expression network analysis (WGCNA) to identify groups of co-expressed genes (modules) and their central (hub) genes. One such module contained genes upregulated in the epileptogenic region, including multiple epileptogenicity candidate genes, and was found to be involved the protection of glial cells against oxidative stress, implicating glial oxidative stress in epileptogenicity. Another distinct module corresponded to the effects of chronic seizures and represented changes in neuronal synaptic vesicle trafficking. We found that the network structure and connectivity of one hub gene, Sv2a, showed significant changes between normal and epileptogenic tissue, becoming more highly connected in epileptic brain. Since Sv2a is a target of the antiepileptic levetiracetam, this module may be important in controlling seizure activity. Bioinformatic analysis of this module also revealed a potential mechanism for the observed transcriptional changes via generation of longer alternatively polyadenlyated transcripts through the upregulation of the RNA binding protein HuD. In summary, combining conventional statistical methods and network analysis allowed us to interpret the differentially regulated genes from a systems perspective, yielding new insight into several biological pathways underlying homeostatic anti-epileptogenic effects and epileptogenicity.

Further evidence that pathologic high-frequency oscillations are bursts of population spikes derived from recordings of identified cells in dentate gyrus

PURPOSE

To analyze activity of identified dentate gyrus granular cells and interneurons during pathologic high-frequency oscillations (pHFOs).

METHODS

Pilocarpine-treated epileptic mice were anesthetized with urethane and ketamine. Their heads were fixed in a stereotaxic frame. Extracellular unit activity was recoded with glass micropipettes, whereas multiunit and local field activity was simultaneously recorded with attached tungsten microelectrodes. After electrophysiologic experiments, recorded cells were labeled by neurobiotin and visualized by immunohistochemical methods. KEY FINDINGS AND SIGNIFICANCES: pHFOs containing more than three waves were recorded in our experiments, but pathologic single-population spikes also occurred. Identified granular cells discharged preferentially in synchrony with pHFOs and single population spikes, whereas interneurons decreased their discharge frequency during this time. These experiments provide additional confirmation that pHFOs in the dentate gyrus represent single or recurrent population spikes, which in turn reflect summated hypersynchronous discharges of principal cells.

Large-scale microelectrode recordings of high-frequency gamma oscillations in human cortex during sleep

Gamma oscillations (40-120 Hz), usually associated with waking functions, can be recorded in the deepest stages of sleep in animals. The full details of their large-scale coordination across multiple cortical networks are still unknown. Furthermore, it is not known whether oscillations with similar characteristics are also present in the human brain. In this study, we examined the existence of gamma oscillations during polysomnographically defined sleep-wake states using large-scale microelectrode recordings (up to 56 channels), with single-cell and spike-time precision, in epilepsy patients. We report that low (40-80 Hz) and high (80-120 Hz) gamma oscillations recurrently emerged over time windows of several hundreds of milliseconds in all investigated cortical areas during slow-wave sleep. These patterns were correlated with positive peaks of EEG slow oscillations and marked increases in local cellular discharges, suggesting that they were associated with cortical UP states. These gamma oscillations frequently appeared at approximately the same time in many different cortical areas, including homotopic regions, forming large spatial patterns. Coincident firings with millisecond precision were strongly enhanced during gamma oscillations but only between cells within the same cortical area. Furthermore, in a significant number of cases, cortical gamma oscillations tended to occur within 100 ms after hippocampal ripple/sharp wave complexes. These data confirm and extend earlier animal studies reporting that gamma oscillations are transiently expressed during UP states during sleep. We speculate that these high-frequency patterns briefly restore "microwake" activity and are important for consolidation of memory traces acquired during previous awake periods.

High-frequency oscillations in epileptic brain

PURPOSE OF REVIEW

It has been 10 years since pathological high-frequency oscillations (pHFOs) were described in the brain of epileptic animals and patients. This review summarizes progress in research on mechanisms of their generation and potential clinical applications over that period.

RECENT FINDINGS

Initially, pHFOs were recorded with microelectrodes in the hippocampus of rodents and patients with mesial temporal lobe epilepsy (MTLE), but recently pHFOs have also been recorded with clinical depth and grid electrodes in multiple brain areas including the hippocampus and neocortex of patients with different types of epilepsy. One hypothesis is that pHFOs reflect fields of hypersynchronized action potentials (bursts of population spikes) within small discrete neuronal clusters responsible for seizure generation. Studies suggest that pHFOs can be used as a reliable biomarker for epileptogenesis, epileptogenicity, and the delineation of the epileptogenic region.

SUMMARY

Recording of pHFOs with clinical electrodes provides a means for further investigation of their functional role in the epileptic brain and as a potential biomarker of epileptogenesis and epileptogenicity and for presurgical mapping.