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Objective: The increased amplitude of ictal activity is a common feature of epileptic seizures, but the determinants of this amplitude have not been identified. Clinically, ictal amplitudes are measured electrographically (using, e.g., electroencephalography, electrocorticography, and depth electrodes), but these methods do not enable the assessment of the activity of individual neurons. Population signal may increase from three potential sources: (1) increased synchrony (i.e., more coactive neurons); (2) altered active state, from bursts of action potentials and/or paroxysmal depolarizing shifts in membrane potential; and (3) altered subthreshold state, which includes all lower levels of activity. Here, we quantify the fraction of ictal signal from each source. Methods: To identify the cellular determinants of the ictal signal, we measured single cell and population electrical activity and neuronal calcium levels via optical imaging of the genetically encoded calcium indicator (GECI) GCaMP. Spontaneous seizure activity was assessed with microendoscopy in an APP/PS1 mouse with focal cortical injury and via widefield imaging in the organotypic hippocampal slice cultures (OHSCs) model of posttraumatic epilepsy. Single cell calcium signals were linked to a range of electrical activities by performing simultaneous GECI‐based calcium imaging and whole‐cell patch‐clamp recordings in spontaneously seizing OHSCs. Neuronal resolution calcium imaging of spontaneous seizures was then used to quantify the cellular contributions to population‐level ictal signal. Results: The seizure onset signal was primarily driven by increased subthreshold activity, consistent with either barrages of excitatory postsynaptic potentials or sustained membrane depolarization. Unsurprisingly, more neurons entered the active state as seizure activity progressed. However, the increasing fraction of active cells was primarily driven by synchronous reactivation and not from continued recruitment of new populations of neurons into the seizure. Significance: This work provides a critical link between single neuron activity and population measures of seizure activity. [ABSTRACT FROM AUTHOR]

Despite extensive temporal lobe epilepsy (TLE) research, understanding the specific limbic structures' roles in seizures remains limited. This weakness can be attributed to the complex nature of TLE and the existence of various TLE subsyndromes, including non-lesional TLE. Conventional TLE models like kainate and pilocarpine hinder precise assessment of the role of individual limbic structures in TLE ictogenesis due to widespread limbic damage induced by the initial status epilepticus. In this study, we used a non-lesional TLE model characterized by the absence of initial status and cell damage to determine the spatiotemporal profile of seizure initiation and limbic structure recruitment in TLE. Epilepsy was induced by injecting a minute dose of tetanus toxin into the right dorsal hippocampus in seven animals. Following injection, animals were implanted with bipolar recording electrodes in the amygdala, dorsal hippocampus, ventral hippocampus, piriform, perirhinal, and entorhinal cortices of both hemispheres. The animals were video-EEG monitored for four weeks. In total, 140 seizures (20 seizures per animal) were analyzed. The average duration of each seizure was 53.2±3.9 s. Seizure could initiate in any limbic structure. Most seizures initiated in the ipsilateral (41 %) and contralateral (18 %) ventral hippocampi. These two structures displayed a significantly higher probability of seizure initiation than by chance. The involvement of limbic structures in seizure initiation varied between individual animals. Surprisingly, only 7 % of seizures initiated in the injected dorsal hippocampus. The limbic structure recruitment into the seizure activity wasn't random and displayed consistent patterns of early recruitment of hippocampi and entorhinal cortices. Although ventral hippocampus represented the primary seizure onset zone, the study demonstrated the involvement of multiple limbic structures in seizure initiation in a non-lesional TLE model. The study also revealed the dichotomy between the primary epileptogenic lesion and main seizure onset zones and points to the central role of ventral hippocampi in temporal lobe ictogenesis. [ABSTRACT FROM AUTHOR]

Objective: The significance of the onset of seizure based on the medical and social aspects of epilepsy. The aim of this study was to investigate the age of seizure onset based on the specific characteristics of each age of seizure onset in many epilepsy syndromes to make an appropriate diagnosis. Methods: The age at epilepsy was retrospectively studied in 155 women aged between 16 and 45 years with a verified diagnosis of epilepsy. The epidemiological method revealed the age at epilepsy onset, and females were divided into three groups: pre-puberty (10-11 years old), puberty (10-18 years old), and post-puberty (18+ years old). A correlation study of the frequency of onset with the periods of formation and function of the female reproductive tract was conducted. Results: A statistically significant quantitative predominance of females with epilepsy onset during puberty (p

Objective: The significance of the onset of seizure based on the medical and social aspects of epilepsy. The aim of this study was to investigate the age of seizure onset based on the specific characteristics of each age of seizure onset in many epilepsy syndromes to make an appropriate diagnosis. Methods: The age at epilepsy was retrospectively studied in 155 women aged between 16 and 45 years with a verified diagnosis of epilepsy. The epidemiological method revealed the age at epilepsy onset, and females were divided into three groups: pre-puberty (10-11 years old), puberty (10-18 years old), and postpuberty (18+ years old). A correlation study of the frequency of onset with the periods of formation and function of the female reproductive tract was conducted. Results: A statistically significant quantitative predominance of females with epilepsy onset during puberty (p<0.001) was identified. Statistically valid was the prevalence of epilepsy onset in the combined age range of 12 to16 (p<0.001). A direct link between menarche and epilepsy onset was detected in the general cohort in 13% of females, which is among the risk factors for catamenial seizure onset. Conclusion: Epilepsy onset in females of reproductive age dominates during childhood development. In more than half of the cases, the epilepsy onset occurs in the puberty period. Epilepsy onset most often occurs between the ages of 12 and 16. Seizure onset occurs at the ages of 12-16 years during menstrual bleeding and ovulatory cycle development due to the proconvulsive effects of estrogens. [ABSTRACT FROM AUTHOR]

Abstract Background Stroke had been accounted to cause almost 50% of epilepsy in the elderly and may lead to poor functional outcomes. Many studies examining the risk factors have been conducted despite showing inconsistent results and currently still difficult to predict the occurrence of post-stroke epilepsy. The study aimed to determine risk factors related to post-stroke epilepsy that influence clinical seizure, electroencephalography (EEG), and functional outcome of patients. Analytic retrospective case–control study was conducted with a total sampling of 62 samples of post-stroke epilepsy and 62 samples of control from all stroke patients in the Neurology Clinic from January 2019 to December 2021. Epilepsy was classified according to the criteria of the International League Against Epilepsy (ILAE) in 2017. The relevant demographic and clinical data were collected. Result The study involved 62 patients in the case group (average age of onset = 57.69; 42 men, 20 women; 51 ischemic stroke, 11 hemorrhagic stroke) and 62 patients in the control group (average age of onset = 56.90; 24 men, 38 women; 52 ischemic stroke, 10 hemorrhagic stroke). We found that 31 patients had focal-to-bilateral seizures, 26 patients had generalized seizures and 5 patients had focal seizures. Men (p = 0.001; OR 3.325) and NIHSS Score (p = 0.027; OR 5.094) had significant correlations with post-stroke epilepsy. Ischemic stroke had a significant correlation (p = 0.008) with seizure onset. Women also had a significant correlation (p = 0.012) with EEG abnormalities. The study found that 59 of 62 post-stroke epilepsy patients had poor functional outcomes (mRS > 2). Conclusion Our study confirmed that most patients had focal-to-bilateral seizure patterns that occurred in 1–2 years after stroke, and had poor functional outcomes. Men had 3.325 times more likely to develop post-stroke epilepsy than women. Also, NIHSS score ≥ 15 correlated and 5.094 times more likely to develop post-stroke epilepsy. Ischemic stroke had a peak of epilepsy onset at 1–2 years after stroke and women had significant showing abnormalities on EEG recording than men.

Background: Stroke had been accounted to cause almost 50% of epilepsy in the elderly and may lead to poor functional outcomes. Many studies examining the risk factors have been conducted despite showing inconsistent results and currently still difficult to predict the occurrence of post-stroke epilepsy. The study aimed to determine risk factors related to post-stroke epilepsy that influence clinical seizure, electroencephalography (EEG), and functional outcome of patients. Analytic retrospective case–control study was conducted with a total sampling of 62 samples of post-stroke epilepsy and 62 samples of control from all stroke patients in the Neurology Clinic from January 2019 to December 2021. Epilepsy was classified according to the criteria of the International League Against Epilepsy (ILAE) in 2017. The relevant demographic and clinical data were collected. Result: The study involved 62 patients in the case group (average age of onset = 57.69; 42 men, 20 women; 51 ischemic stroke, 11 hemorrhagic stroke) and 62 patients in the control group (average age of onset = 56.90; 24 men, 38 women; 52 ischemic stroke, 10 hemorrhagic stroke). We found that 31 patients had focal-to-bilateral seizures, 26 patients had generalized seizures and 5 patients had focal seizures. Men (p = 0.001; OR 3.325) and NIHSS Score (p = 0.027; OR 5.094) had significant correlations with post-stroke epilepsy. Ischemic stroke had a significant correlation (p = 0.008) with seizure onset. Women also had a significant correlation (p = 0.012) with EEG abnormalities. The study found that 59 of 62 post-stroke epilepsy patients had poor functional outcomes (mRS > 2). Conclusion: Our study confirmed that most patients had focal-to-bilateral seizure patterns that occurred in 1–2 years after stroke, and had poor functional outcomes. Men had 3.325 times more likely to develop post-stroke epilepsy than women. Also, NIHSS score ≥ 15 correlated and 5.094 times more likely to develop post-stroke epilepsy. Ischemic stroke had a peak of epilepsy onset at 1–2 years after stroke and women had significant showing abnormalities on EEG recording than men. [ABSTRACT FROM AUTHOR]

The implications of combining structural and functional connectivity to quantify the most active brain regions in seizure onset remain unclear. This study tested a new model that may facilitate the incorporation of diffusion MRI (dMRI) in clinical practice. We obtained structural connectomes from dMRI and functional connectomes from electroencephalography (EEG) to assess whether high structure-function coupling corresponded with the seizure onset region. We mapped individual electrodes to their nearest cortical region to allow for a one-to-one comparison between the structural and functional connectomes. A seizure laterality score and expected onset zone were defined. The patients with well-lateralised seizures revealed high structure-function coupling consistent with the seizure onset zone. However, a lower seizure lateralisation score translated to reduced alignment between the high structure-function coupling regions and the seizure onset zone. We illustrate that dMRI, in combination with EEG, can improve the identification of the seizure onset zone. Our model may be valuable in enhancing ultra-long-term monitoring by indicating optimal, individualised electrode placement. [ABSTRACT FROM AUTHOR]

Emerging evidence supports that brain dysfunction may be attributable to environmental factors. This study aims to examine associations of ambient temperature and temperature variability (TV) with seizure incidence in children, which has not been explored. Data on 2718 outpatient visits due to seizure were collected in Shanghai, China, from 2018 to 2023. Exposure to ambient temperature was estimated at children's residential addresses using spatial-temporal models. A time-stratified case-crossover design with a distributed lag non-linear model (DLNM) was conducted to assess the association between seizure incidence and daily average of ambient temperature over a period of 21 days prior to a case date of disease onset. For a given case date, we selected all dates falling on the same day of the week within the same month as control dates. We calculated a composite index of intra-day and inter-day TV, which was the standard deviation of the daily minimum and maximum temperatures, respectively, over 7 days preceding a case date. We then assessed the association between TV and seizure incidence. Stratified analyses were conducted by age (73.51% < 5 years old and 26.49 % ≥ 5 years old), sex (41.83% female), presence of fever (69.72%), and diagnosis of epilepsy (27.63%). We observed inversed J-shaped temperature-response curves. Lower temperatures had a significant and prolonged effect than higher temperatures. Using 20 °C (with the minimum effect) as the reference, the cumulative odds ratios (ORs) for over 0–21 days preceding the onset at the 5th percentile of the temperature (3 °C) and at the 95th percentile (29 °C) were 3.17 (95% CI: 1.77, 5.68) and 1.54 (95% CI: 0.97, 2.44), respectively. In addition, per 1 °C increases in TV 0 – 7 was associated with OR of 1.08 (95% CI: 1.01, 1.15). Older children and those experiencing seizure with fever exhibited a higher risk of seizure onset at both lower and higher ambient temperatures. Both low and high temperatures can contribute to the morbidity related to pediatric seizure. Lower temperatures, however, exerted a longer period of effect prior to seizure onset than higher temperatures. An increased risk for incident seizure was significantly associated with temperature variability during preceding 7 days. • The associations between temperature and pediatric incident seizure were inverted J-shaped pattern. • Both low and high temperatures might be important risk factors for seizure onset. • Lower temperatures exert a greater effect size on seizure onset compared to higher temperatures. [ABSTRACT FROM AUTHOR]

Data fusion refers to the joint analysis of multiple datasets that provide different (e.g., complementary) views of the same task. In general, it can extract more information than separate analyses can. Jointly analyzing electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) measurements has been proved to be highly beneficial to the study of the brain function, mainly because these neuroimaging modalities have complementary spatiotemporal resolution: EEG offers good temporal resolution while fMRI is better in its spatial resolution. The EEG–fMRI fusion methods that have been reported so far ignore the underlying multiway nature of the data in at least one of the modalities and/or rely on very strong assumptions concerning the relation of the respective datasets. For example, in multisubject analysis, it is commonly assumed that the hemodynamic response function is a priori known for all subjects and/or the coupling across corresponding modes is assumed to be exact (hard). In this article, these two limitations are overcome by adopting tensor models for both modalities and by following soft and flexible coupling approaches to implement the multimodal fusion. The obtained results are compared against those of parallel independent component analysis and hard coupling alternatives, with both synthetic and real data (epilepsy and visual oddball paradigm). Our results demonstrate the clear advantage of using soft and flexible coupled tensor decompositions in scenarios that do not conform with the hard coupling assumption. [ABSTRACT FROM AUTHOR]

Seizure initiation is the least understood and most disabling element of epilepsy. Studies of ictogenesis require high speed recordings at cellular resolution in the area of seizure onset. However, in vivo seizure onset areas cannot be determined at the level of resolution necessary to enable such studies. To circumvent these challenges, we used novel GCaMP7-based calcium imaging in the organotypic hippocampal slice culture model of post-traumatic epilepsy in mice. Organotypic hippocampal slice cultures generate spontaneous, recurrent seizures in a preparation in which it is feasible to image the activity of the entire network (with no unseen inputs existing). Chronic calcium imaging of the entire hippocampal network, with paired electrophysiology, revealed three patterns of seizure onset: (i) low amplitude fast activity; (ii) sentinel spike; and (iii) spike burst and low amplitude fast activity onset. These patterns recapitulate common features of human seizure onset, including low voltage fast activity and spike discharges. Weeks-long imaging of seizure activity showed a characteristic evolution in onset type and a refinement of the seizure onset zone. Longitudinal tracking of individual neurons revealed that seizure onset is stochastic at the single neuron level, suggesting that seizure initiation activates neurons in non-stereotyped sequences seizure to seizure. This study demonstrates for the first time that transitions to seizure are not initiated by a small number of neuronal 'bad actors' (such as overly connected hub cells), but rather by network changes which enable the onset of pathology among large populations of neurons. [ABSTRACT FROM AUTHOR]

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ObjectivesCerebral hemispherectomy, a surgical procedure undergone to control intractable seizures, is becoming a standard procedure with more cases identified and treated early in life [33]. While the effect of the dominant hemisphere resection on spoken language has been extensively researched, little is known about reading abilities in individuals after left-sided resection. Left-lateralized phonological abilities are the key components of reading, i.e., grapheme-phoneme conversion skills [1]. These skills are critical for the acquisition of word-specific orthographic knowledge and have been shown to predict reading levels in average readers as well as in readers with mild cognitive disability [26]. Furthermore, impaired phonological processing has been implicated as the cognitive basis in struggling readers. Here, we explored the reading skills in participants who have undergone left cerebral hemispherectomy.MethodsSeven individuals who have undergone left cerebral hemispherectomy to control intractable seizures associated with perinatal infarct have been recruited for this study. We examined if components of phonological processing that are shown to reliably separate average readers from struggling readers, i.e., phonological awareness, verbal memory, speed of retrieval, and size of vocabulary, show the same relationship to reading levels when they are mediated by the right hemisphere [2].ResultsWe found that about 60% of our group developed both word reading and paragraph reading in the average range. Phonological processing measured by both phonological awareness and nonword reading was unexpectedly spared in the majority of participants. Phonological awareness levels strongly correlated with word reading. Verbal memory, a component of phonological processing skills, together with receptive vocabulary size, positively correlated with reading levels similar to those reported in average readers. Receptive vocabulary, a bilateral function, was preserved to a certain degree similar to that of strongly left-lateralized phonological skills [3]. Later seizure onset was associated with better reading levels.ConclusionsWhen cerebral hemispherectomy is performed to control seizures associated with very early (in utero) insult, it has been found that the remaining right hemisphere is still able to support reading and phonological processing skills that are normally mediated by the left hemisphere. Our results also suggest the existence of variability in individuals after hemispherectomy, even within groups having the same etiology and similar timing of insult.

The implications of combining structural and functional connectivity to quantify the most active brain regions in seizure onset remain unclear. This study tested a new model that may facilitate the incorporation of diffusion MRI (dMRI) in clinical practice. We obtained structural connectomes from dMRI and functional connectomes from electroencephalography (EEG) to assess whether high structure-function coupling corresponded with the seizure onset region. We mapped individual electrodes to their nearest cortical region to allow for a one-to-one comparison between the structural and functional connectomes. A seizure laterality score and expected onset zone were defined. The patients with well-lateralised seizures revealed high structure-function coupling consistent with the seizure onset zone. However, a lower seizure lateralisation score translated to reduced alignment between the high structure-function coupling regions and the seizure onset zone. We illustrate that dMRI, in combination with EEG, can improve the identification of the seizure onset zone. Our model may be valuable in enhancing ultra-long-term monitoring by indicating optimal, individualised electrode placement.

Electroencephalography (EEG) was widely investigated in brain status detection and disease diagnosis, in which the fractal analysis played an important role. In this paper, the roughness scaling extraction (RSE) algorithm proposed in our previous study on surface morphologies was applied to calculate the fractal dimensions (FDs) of artificial profiles and EEG signals. Fractal profiles with ideal FDs ranging from 1.01 to 1.99 were generated through the Weierstrass-Mandelbrot function. The RSE algorithm and the traditional algorithms, including the Higuchi algorithm, the Katz algorithm, and the box counting algorithm, were compared by analyzing the artificial profiles. Based on the mean relative errors and mean square errors, it was found that the RSE algorithm was more accurate than the traditional algorithms. To investigate the influence of noise on FD calculation, noise with different levels was added to the fractal profiles. The RSE and Higuchi algorithms were found reliable at signal-to-noise ratios of 50 and 40 dB, while the accuracy of RSE was also superior to that of the Higuchi. The RSE, Higuchi, and Katz algorithms were utilized to analyze the EEG signals of epilepsy events. The significant FD increasing, which corresponded to the seizure onset, could be detected, and the overlapping between the seizure and non-seizure statuses was small by using the RSE algorithm, indicating its feasibility for the EEG fractal analysis.

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.

Abstract Background Autism spectrum disorder and epilepsy often co-occur; however, the extent to which the association between autism symptoms and epilepsy is due to shared aetiology or to the direct effects of seizures is a topic of ongoing debate. Angelman syndrome (AS) is presented as a suitable disease model to explore this association. Methods Data from medical records and questionnaires were used to examine the association between age of epilepsy onset, autism symptoms, genetic aberration and communication level. Forty-eight participants had genetically verified AS (median age 14.5 years; range 1–57 years). A measure of autism symptoms (the Social Communication Questionnaire; SCQ) was completed for 38 individuals aged ≥ 4 years. Genetic cause was subgrouped into deletion and other genetic aberrations of the 15q11-q13 area. The number of signs used to communicate (

We obtained field, K+ selective and “sharp” intracellular recordings from the rat entorhinal (EC) and perirhinal (PC) cortices in an in vitro brain slice preparation to identify the events occurring at interictal-to-ictal transition during 4-aminopyridine application. Field recordings revealed interictal- (duration: 1.1 to 2.2 s) and ictal-like (duration: 31 to 103 s) activity occurring synchronously in EC and PC; in addition, interictal spiking in PC increased in frequency shortly before the onset of ictal oscillatory activity thus resembling the hypersynchronous seizure onset seen in epileptic patients and in in vivo animal models. Intracellular recordings with K-acetate + QX314-filled pipettes in PC principal cells showed that spikes at ictal onset had post-burst hyperpolarizations (presumably mediated by postsynaptic GABAA receptors), which gradually decreased in amplitude. This trend was associated with a progressive positive shift of the post-burst hyperpolarization reversal potential. Finally, the transient elevations in [K+]o (up to 4.4 mM from a base line of 3.2 mM) – which occurred with the interictal events in PC – progressively increased (up to 7.3 mM) with the spike immediately preceding ictal onset. Our findings indicate that hypersynchronous seizure onset in rat PC is caused by dynamic weakening of GABAA receptor signaling presumably resulting from [K+]o accumulation.

Summary: Objective: In this study, we seek to analyze the determinants of the intracranial electroencephalography seizure onset pattern (SOP) and the impact of the SOP in predicting postsurgical seizure outcome. Methods: To this end, we analyzed 820 seizures from 252 consecutive patients explored by stereo‐electroencephalography (total of 2148 electrodes), including various forms of focal refractory epilepsies. We used a reproducible method combining visual and time‐frequency analyses. Results: We described eight SOPs: low‐voltage fast activity (LVFA), preictal spiking followed by LVFA, burst of polyspikes followed by LVFA, slow wave/DC shift followed by LVFA, sharp theta/alpha waves, beta sharp waves, rhythmic spikes/spike‐waves, and delta‐brush. LVFA occurred in 79% of patients. The seizure onset pattern was significantly associated with (1) underlying etiology (burst of polyspikes followed by LVFA with the presence of a focal cortical dysplasia, LVFA with malformation of cortical development, postvascular and undetermined epilepsies), (2) spatial organization of the epileptogenic zone (EZ; burst of polyspikes followed by LVFA with focal organization, slow wave/DC shift followed by LVFA with network organization), and (3) postsurgical seizure outcome (better outcome when LVFA present). Significance: This study demonstrates that the main determinants of the SOP are the underlying etiology and the spatial organization of the EZ. Concerning the postsurgical seizure outcome, the main determinant factor is the spatial organization of the EZ, but the SOP plays also a role, conferring better prognosis when LVFA is present. [ABSTRACT FROM AUTHOR]

Highlights • Scalp high frequency oscillations (HFO) localize the seizure onset zone in refractory epilepsy. • Widespread scalp HFO are indicative of large epileptic network. • Scalp HFO analysis might help predict postsurgical seizure outcome. Abstract Objective High frequency oscillations (HFO) between 80–500 Hz are markers of epileptic areas in intracranial and maybe also scalp EEG. We investigate simultaneous recordings of scalp and intracranial EEG and hypothesize that scalp HFOs provide important additional clinical information in the presurgical setting. Methods Spikes and HFOs were visually identified in all intracranial scalp EEG channels. Analysis of correlation of event location between intracranial and scalp EEG as well as relationship between events and the SOZ and zone of surgical removal was performed. Results 24 patients could be included, 23 showed spikes and 19 HFOs on scalp recordings. In 15/19 patients highest scalp HFO rate was located over the implantation side, with 13 patients having the highest scalp and intracranial HFO rate over the same region. 17 patients underwent surgery, 7 became seizure free. Patients with poor post-operative outcome showed significantly more regions with HFO than those with seizure free outcome. Conclusions Scalp HFOs are mostly located over the SOZ. Widespread scalp HFOs are indicative of a larger epileptic network and associated with poor postsurgical outcome. Significance Analysis of scalp HFO add clinically important information about the extent of epileptic areas during presurgical simultaneous scalp and intracranial EEG recordings. [ABSTRACT FROM AUTHOR]

High frequency oscillations (HFO) are known as markers of epileptic areas in intracranial EEG and possibly scalp EEG. We compared distributions of HFO in the ripple band (80-250 Hz) in intracranial and scalp EEG with either a conventional 10-20-montage (10-20-EEG) or a high density recording using 128 electrodes (HD-EEG). HFO were visually identified, in all intracranial EEG channels (80-500 Hz) and all channels of the 10-20-EEG (scalp EEG 80-250 Hz). For the HD-EEG, HFO were analyzed in regions of interest using areas with HFO as seen on the 10-20-EEG as well as areas in the clinically-defined seizure onset zone (SOZ). 13 patients were included in the study, of whom 12 showed HFO in the ripple band. In 8 patients HD-EEG revealed additional regions of ripples compared to the 10-20-EEG. With HD-EEG, areas of highest ripple rates were corresponding between scalp and intracranial EEG in 7 patients (58%) and 8 (67%) patients showed highest ripple rates over the SOZ. In contrast, with 10-20-EEG only 2 patients (17%) had corresponding areas of highest ripple rates and only 3 patients (23%) showed highest ripple rates over the SOZ. HD-EEG proved to be better to identify scalp HFO in the ripple band compared to standard 10-20-EEG. Moreover, ripples in 10-20-EEG seem to lead to false localization of epileptic areas. In contrast ripples detected with HD-EEG were located over the seizure onset zone and maybe a promising tool to localize epileptic tissue in the future. [ABSTRACT FROM AUTHOR]

The use of automatic electrical stimulation in response to early seizure detection has been introduced as a new treatment for intractable epilepsy. For the effective application of this method as a successful treatment, improving the accuracy of the early seizure detection is crucial. In this paper, we proposed the application of a frequency-based algorithm derived from principal component analysis (PCA), and demonstrated improved efficacy for early seizure detection in a pilocarpine-induced epilepsy rat model. A total of 100 ictal electroencephalographs (EEG) during spontaneous recurrent seizures from 11 epileptic rats were finally included for the analysis. PCA was applied to the covariance matrix of a conventional EEG frequency band signal. Two PCA results were compared: one from the initial segment of seizures (5 sec of seizure onset) and the other from the whole segment of seizures. In order to compare the accuracy, we obtained the specific threshold satisfying the target performance from the training set, and compared the False Positive (FP), False Negative (FN), and Latency (Lat) of the PCA based feature derived from the initial segment of seizures to the other six features in the testing set. The PCA based feature derived from the initial segment of seizures performed significantly better than other features with a 1.40% FP, zero FN, and 0.14 s Lat. These results demonstrated that the proposed frequency-based feature from PCA that captures the characteristics of the initial phase of seizure was effective for early detection of seizures. Experiments with rat ictal EEGs showed an improved early seizure detection rate with PCA applied to the covariance of the initial 5 s segment of visual seizure onset instead of using the whole seizure segment or other conventional frequency bands.