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Journal ArticleDOI

High-Frequency Oscillations in Epilepsy: What Have We Learned and What Needs to be Addressed.

02 Mar 2021-Neurology (Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology)-Vol. 96, Iss: 9, pp 439-448
TL;DR: For the past 2 decades, highfrequency oscillations (HFOs) have been enthusiastically studied by the epilepsy community as discussed by the authors and they have shown great promise to delineate epileptogenic brain areas and possibly predict the likelihood of seizures.
Abstract: For the past 2 decades, high-frequency oscillations (HFOs) have been enthusiastically studied by the epilepsy community. Emerging evidence shows that HFOs harbor great promise to delineate epileptogenic brain areas and possibly predict the likelihood of seizures. Investigations into HFOs in clinical epilepsy have advanced from small retrospective studies relying on visual identification and correlation analysis to larger prospective assessments using automatic detection and prediction strategies. Although most studies have yielded promising results, some have revealed significant obstacles to clinical application of HFOs, thus raising debate about the reliability and practicality of HFOs as clinical biomarkers. In this review, we give an overview of the current state of HFO research and pinpoint the conceptual and methodological issues that have hampered HFO translation. We highlight recent insights gained from long-term data, high-density recordings, and multicenter collaborations and discuss the open questions that need to be addressed in future research.
Citations
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Journal ArticleDOI
TL;DR: In this article, the authors presented a neuromorphic system that combines a neural recording headstage with a spiking neural network (SNN) processing core on the same die for processing intracranial EEG (iEEG) from epilepsy patients for the detection of high frequency oscillations (HFO), which are a biomarker for epileptogenic brain tissue.
Abstract: The analysis of biomedical signals for clinical studies and therapeutic applications can benefit from embedded devices that can process these signals locally and in real-time An example is the analysis of intracranial EEG (iEEG) from epilepsy patients for the detection of High Frequency Oscillations (HFO), which are a biomarker for epileptogenic brain tissue Mixed-signal neuromorphic circuits offer the possibility of building compact and low-power neural network processing systems that can analyze data on-line in real-time Here we present a neuromorphic system that combines a neural recording headstage with a spiking neural network (SNN) processing core on the same die for processing iEEG, and show how it can reliably detect HFO, thereby achieving state-of-the-art accuracy, sensitivity, and specificity This is a first feasibility study towards identifying relevant features in iEEG in real-time using mixed-signal neuromorphic computing technologies

52 citations

Journal ArticleDOI
TL;DR: A neuromorphic system that combines for the first time a neural recording headstage with a signal-to-spike conversion circuit and a multi-core spiking neural network architecture on the same die for recording, processing, and detecting High Frequency Oscillations (HFO), which are biomarkers for the epileptogenic zone is presented.
Abstract: In this work, we present a neuromorphic system that combines for the first time a neural recording headstage with a signal-to-spike conversion circuit and a multi-core spiking neural network (SNN) architecture on the same die for recording, processing, and detecting High Frequency Oscillations (HFO), which are biomarkers for the epileptogenic zone. The device was fabricated using a standard 0.18$\mu$m CMOS technology node and has a total area of 99mm$^{2}$. We demonstrate its application to HFO detection in the iEEG recorded from 9 patients with temporal lobe epilepsy who subsequently underwent epilepsy surgery. The total average power consumption of the chip during the detection task was 614.3$\mu$W. We show how the neuromorphic system can reliably detect HFOs: the system predicts postsurgical seizure outcome with state-of-the-art accuracy, specificity and sensitivity (78%, 100%, and 33% respectively). This is the first feasibility study towards identifying relevant features in intracranial human data in real-time, on-chip, using event-based processors and spiking neural networks. By providing "neuromorphic intelligence" to neural recording circuits the approach proposed will pave the way for the development of systems that can detect HFO areas directly in the operation room and improve the seizure outcome of epilepsy surgery.

38 citations

Journal ArticleDOI
01 Nov 2022
TL;DR: Suerman et al. as discussed by the authors evaluated the non-inferiority of HFO-guided and spike-guided tailoring on seizure freedom at 1 year in the HFO trial.
Abstract: Intraoperative electrocorticography is used to tailor epilepsy surgery by analysing interictal spikes or spike patterns that can delineate epileptogenic tissue. High-frequency oscillations (HFOs) on intraoperative electrocorticography have been proposed as a new biomarker of epileptogenic tissue, with higher specificity than spikes. We prospectively tested the non-inferiority of HFO-guided tailoring of epilepsy surgery to spike-guided tailoring on seizure freedom at 1 year.The HFO trial was a randomised, single-blind, adaptive non-inferiority trial at an epilepsy surgery centre (UMC Utrecht) in the Netherlands. We recruited children and adults (no age limits) who had been referred for intraoperative electrocorticography-tailored epilepsy surgery. Participants were randomly allocated (1:1) to either HFO-guided or spike-guided tailoring, using an online randomisation scheme with permuted blocks generated by an independent data manager, stratified by epilepsy type. Treatment allocation was masked to participants and clinicians who documented seizure outcome, but not to the study team or neurosurgeon. Ictiform spike patterns were always considered in surgical decision making. The primary endpoint was seizure outcome after 1 year (dichotomised as seizure freedom [defined as Engel 1A-B] vs seizure recurrence [Engel 1C-4]). We predefined a non-inferiority margin of 10% risk difference. Analysis was by intention to treat, with prespecified subgroup analyses by epilepsy type and for confounders. This completed trial is registered with the Dutch Trial Register, Toetsingonline ABR.NL44527.041.13, and ClinicalTrials.gov, NCT02207673.Between Oct 10, 2014, and Jan 31, 2020, 78 individuals were enrolled to the study and randomly assigned (39 to HFO-guided tailoring and 39 to spike-guided tailoring). There was no loss to follow-up. Seizure freedom at 1 year occurred in 26 (67%) of 39 participants in the HFO-guided group and 35 (90%) of 39 in the spike-guided group (risk difference -23·5%, 90% CI -39·1 to -7·9; for the 48 patients with temporal lobe epilepsy, the risk difference was -25·5%, -45·1 to -6·0, and for the 30 patients with extratemporal lobe epilepsy it was -20·3%, -46·0 to 5·4). Pathology associated with poor prognosis was identified as a confounding factor, with an adjusted risk difference of -7·9% (90% CI -20·7 to 4·9; adjusted risk difference -12·5%, -31·0 to 5·9, for temporal lobe epilepsy and 5·8%, -7·7 to 19·5, for extratemporal lobe epilepsy). We recorded eight serious adverse events (five in the HFO-guided group and three in the spike-guided group) requiring hospitalisation. No patients died.HFO-guided tailoring of epilepsy surgery was not non-inferior to spike-guided tailoring on intraoperative electrocorticography. After adjustment for confounders, HFOs show non-inferiority in extratemporal lobe epilepsy. This trial challenges the clinical value of HFOs as an epilepsy biomarker, especially in temporal lobe epilepsy. Further research is needed to establish whether HFO-guided intraoperative electrocorticography holds promise in extratemporal lobe epilepsy.UMCU Alexandre Suerman, EpilepsieNL, RMI Talent Fellowship, European Research Council, and MING Fund.

17 citations

Journal ArticleDOI
24 Jan 2022-Brain
TL;DR: In this paper , a normative map of brain dynamics, in terms of relative band power, from interictal intracranial recordings from 234 participants (21 598 electrode contacts) was constructed and compared to the normative map to identify abnormal regions.
Abstract: The identification of abnormal electrographic activity is important in a wide range of neurological disorders, including epilepsy for localizing epileptogenic tissue. However, this identification may be challenging during non-seizure (interictal) periods, especially if abnormalities are subtle compared to the repertoire of possible healthy brain dynamics. Here, we investigate if such interictal abnormalities become more salient by quantitatively accounting for the range of healthy brain dynamics in a location-specific manner. To this end, we constructed a normative map of brain dynamics, in terms of relative band power, from interictal intracranial recordings from 234 participants (21 598 electrode contacts). We then compared interictal recordings from 62 patients with epilepsy to the normative map to identify abnormal regions. We proposed that if the most abnormal regions were spared by surgery, then patients would be more likely to experience continued seizures postoperatively. We first confirmed that the spatial variations of band power in the normative map across brain regions were consistent with healthy variations reported in the literature. Second, when accounting for the normative variations, regions that were spared by surgery were more abnormal than those resected only in patients with persistent postoperative seizures (t = -3.6, P = 0.0003), confirming our hypothesis. Third, we found that this effect discriminated patient outcomes (area under curve 0.75 P = 0.0003). Normative mapping is a well-established practice in neuroscientific research. Our study suggests that this approach is feasible to detect interictal abnormalities in intracranial EEG, and of potential clinical value to identify pathological tissue in epilepsy. Finally, we make our normative intracranial map publicly available to facilitate future investigations in epilepsy and beyond.

15 citations

References
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Journal ArticleDOI
TL;DR: The phylogenetic analysis complemented with synteny analyses suggests that Bmp2, -4 and -16 are remnants of a gene quartet that originated during the two rounds of whole-genome duplication (2R-WGD) early in vertebrate evolution.
Abstract: The vertebrate gene repertoire is characterized by “cryptic” genes whose identification has been hampered by their absence from the genomes of well-studied species. One example is the Bmp16 gene, a paralog of the developmental key genes Bmp2 and -4. We focus on the Bmp2/4/16 group of genes to study the evolutionary dynamics following gen(om)e duplications with special emphasis on the poorly studied Bmp16 gene. We reveal the presence of Bmp16 in chondrichthyans in addition to previously reported teleost fishes and reptiles. Using comprehensive, vertebrate-wide gene sampling, our phylogenetic analysis complemented with synteny analyses suggests that Bmp2, -4 and -16 are remnants of a gene quartet that originated during the two rounds of whole-genome duplication (2R-WGD) early in vertebrate evolution. We confirm that Bmp16 genes were lost independently in at least three lineages (mammals, archelosaurs and amphibians) and report that they have elevated rates of sequence evolution. This finding agrees with their more “flexible” deployment during development; while Bmp16 has limited embryonic expression domains in the cloudy catshark, it is broadly expressed in the green anole lizard. Our study illustrates the dynamics of gene family evolution by integrating insights from sequence diversification, gene repertoire changes, and shuffling of expression domains.

1,376 citations

Journal ArticleDOI
TL;DR: To estimate the burden of lifetime epilepsy (LTE) and active epilepsy (AE) and examine the influence of study characteristics on prevalence estimates.
Abstract: SUMMARY Purpose: To estimate the burden of lifetime epilepsy (LTE) and active epilepsy (AE) and examine the influence of study characteristics on prevalence estimates. Methods: We searched online databases and identified articles using prespecified criteria. Random-effects metaanalyses were used to estimate the median prevalence in developed countries and in urban and rural settings in developing countries. The impact of study characteristics on prevalence estimates was determined using metaregression models. Results: The median LTE prevalence for developed countries was 5.8 per 1,000 (5th–95th percentile range 2.7– 12.4) compared to 15.4 per 1,000 (4.8–49.6) for rural and 10.3 (2.8–37.7) for urban studies in developing countries. The median prevalence of AE was 4.9 per 1,000 (2.3–10.3) for developed countries and 12.7 per 1,000 (3.5–45.5) and 5.9 (3.4–10.2) in rural and urban studies in developing countries. The estimates of burden for LTE and AE in developed countries were 6.8 million (5th–95th percentile range 3.2–14.7) and 5.7 million (2.7–12.2), respectively. In developing countries these were 45 (14–145) million LTE and 17 (10–133) million AE in rural areas and 17 (5–61) million LTE and 10 (5–17) million AE in urban areas. Studies involving all ages or only adults showed higher estimates than pediatric studies. Higher prevalence estimates were also associated with rural location and small study size. Conclusions: This study estimates the global burden of epilepsy and the proportions with AE, which may benefit from treatment. There are systematic differences in reported prevalence estimates, which are only partially

1,112 citations

Journal ArticleDOI
TL;DR: Property of oscillations with frequencies >100 Hz were studied in kainic acid (KA)‐treated rats and compared with those recorded in normal and kindled rats as well as in patients with epilepsy to determine differences associated with epilepsy.
Abstract: Summary: Purpose: Properties of oscillations with frequencies >100 Hz were studied in kainic acid (KA)-treated rats and compared with those recorded in normal and kindled rats as well as in patients with epilepsy to determine differences associated with epilepsy. Methods: Prolonged in vivo wideband recordings of electrical activity were made in hippocampus and entorhinal cortex (EC) of (a) normal rats, (b) kindled rats, (c) rats having chronic recurrent spontaneous seizures after intrahippocampal KA injections, and (d) patients with epilepsy undergoing depth electrode evaluation in preparation for surgical treatment. Results: Intermittent oscillatory activity ranging from 100 to 200 Hz in frequency and 50–150 ms in duration was recorded in CA1 and EC of all three animal groups, and in epileptic human hippocampus and EC. This activity had the same characteristics in all groups, resembled previously observed “ripples” described by Buzsaki et al., and appeared to represent field potentials of inhibitory postsynaptic potentials (IPSPs) on principal cells. Unexpectedly, higher frequency intermittent oscillatory activity ranging from 200 to 500 Hz and 10–100 ms in duration was encountered only in KA-treated rats and patients with epilepsy. These oscillations, termed fast ripples (FRs), were found only adjacent to the epileptogenic lesion in hippocampus, EC, and dentate gyrus, and appeared to represent field potential population spikes. Their local origin was indicated by correspondence with the negative phase of burst discharges of putative pyramidal cells. Conclusions: The persistence of normal-appearing ripples in epileptic brain support the view that inhibitory processes are preserved. FRs appear to be field potentials reflecting hypersynchronous bursting of excitatory neurons and provide an opportunity to study the role of this pathophysiologic phenomenon in epilepsy and seizure initiation. Furthermore, if FR activity is unique to brain areas capable of generating spontaneous seizures, its identification could be a powerful functional indicator of the epileptic region in patients evaluated for surgical treatment.

681 citations

Journal ArticleDOI
TL;DR: This work investigated whether HFOs can delineate epileptogenic areas even outside the SOZ by correlating the resection of HFO‐generating areas with surgical outcome.
Abstract: Thirty percent to 40% of patients with focal epilepsy are medically intractable,1 and for some, surgical removal of epileptogenic areas is the best option to gain seizure freedom. Intracranial electroencephalographic (iEEG) investigations are indicated for patients in whom noninvasive methods fail to identify a single focal seizure generator.2 iEEG is used to define the seizure onset zone (SOZ).3 Removal of the SOZ alone, however, does not always predict the surgical benefit.4,5 It is uncertain whether the outcome can be improved by removing areas of interictal spiking, often more widespread than the SOZ.6,7 Intracranial studies also have limitations, as their results depend on electrode location and type of implantation (intracortical vs subdural). For instance, iEEG electrodes only record neuronal activity in their direct vicinity and are blind for other areas,8 making it hard to judge whether the activity at seizure onset really represents the seizure generator or is the result of propagation from else-where. Thus the actual focus and its extent may be missed, leading to unsuccessful surgery. Microelectrode-recorded high-frequency oscillations (HFOs), ripples (80 –250Hz), and fast ripples (FRs, 250 –500Hz), were found predominantly in epileptogenic tissue.9 –11 They can also be recorded with macroelectrodes during clinical iEEG investigation.12,13 HFOs were more specific in indicating the SOZ than spikes.14 Additionally, they were linked to the SOZ independently of the underlying lesion and were infrequent in lesional areas outside the SOZ.15 Evidence therefore suggests that HFOs are good markers of epileptic tissue and may help to identify epileptogenic areas. We hypothesize that removing areas generating HFOs results in good surgical outcome. The correlation between removal of HFO-generating areas and seizure outcome was compared to that coming from spikes and to the current gold standard, removing the SOZ.

584 citations

Journal ArticleDOI
01 Apr 2008-Brain
TL;DR: R ripple and fast-ripple HFO recorded from both microwires and clinical macroelectrodes were increased in seizure generating brain regions compared to control regions, supporting the hypothesis that fast- Ripple HFO are primarily generated by highly localized, sub-millimeter scale neuronal assemblies that are most effectively sampled by microwire electrodes.
Abstract: Neuronal oscillations span a wide range of spatial and temporal scales that extend beyond traditional clinical EEG. Recent research suggests that high-frequency oscillations (HFO), in the ripple (80-250 Hz) and fast ripple (250-1000 Hz) frequency range, may be signatures of epileptogenic brain and involved in the generation of seizures. However, most research investigating HFO in humans comes from microwire recordings, whose relationship to standard clinical intracranial EEG (iEEG) has not been explored. In this study iEEG recordings (DC - 9000 Hz) were obtained from human medial temporal lobe using custom depth electrodes containing both microwires and clinical macroelectrodes. Ripple and fast-ripple HFO recorded from both microwires and clinical macroelectrodes were increased in seizure generating brain regions compared to control regions. The distribution of HFO frequencies recorded from the macroelectrodes was concentrated in the ripple frequency range, compared to a broad distribution of HFO frequencies recorded from microwires. The average frequency of ripple HFO recorded from macroelectrodes was lower than that recorded from microwires (143.3 +/- 49.3 Hz versus 116.3 +/- 38.4, Wilcoxon rank sum P<0.0001). Fast-ripple HFO were most often recorded on a single microwire, supporting the hypothesis that fast-ripple HFO are primarily generated by highly localized, sub-millimeter scale neuronal assemblies that are most effectively sampled by microwire electrodes. Future research will address the clinical utility of these recordings for localizing epileptogenic networks and understanding seizure generation.

437 citations

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