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Object Epilepsy surgery is an effective treatment for selected patients with focal intractable epilepsy. Complete removal of the epileptogenic zone significantly increases the chances for postoperative seizure-freedom. In complex surgical candidates, delineation of the epileptogenic zone requires a long-term invasive video/EEG from intracranial electrodes. It is especially challenging to achieve a complete resection in deep brain structures such as opercular-insular cortex. We report a novel approach utilizing intraoperative visual detection of stereotactically implanted depth electrodes to inform and guide the extent of surgical resection. Methods We retrospectively reviewed data of pediatric patients operated in Motol Epilepsy Center between October 2010 and June 2020 who underwent resections guided by intraoperative visual detection of depth electrodes following SEEG. The outcome in terms of seizure- and AED-freedom was assessed individually in each patient. Results Nineteen patients (age at surgery 2.9–18.6 years, median 13 years) were included in the study. The epileptogenic zone involved opercular-insular cortex in eighteen patients. The intraoperative detection of the electrodes was successful in seventeen patients and the surgery was regarded complete in sixteen. Thirteen patients were seizure-free at final follow-up including six drug-free cases. The successful intraoperative detection of the electrodes was associated with favorable outcome in terms of achieving complete resection and seizure-freedom in most cases. On the contrary, the patients in whom the procedure failed had poor postsurgical outcome. Conclusion The reported technique helps to achieve the complete resection in challenging patients with the epileptogenic zone in deep brain structures.

Epilepsy surgery fails in 30% of patients with focal cortical dysplasia (FCD). The seizure persistence after surgery can be attributed to the inability to precisely localize the tissue with an endogenous potential to generate seizures. In this study, we aimed to identify the critical components of the epileptic network that were actively involved in seizure genesis.The directed transfer function was applied to intracranial EEG recordings and the effective connectivity was determined with a high temporal and frequency resolution. Pre-ictal network properties were compared with ictal epochs to identify regions actively generating ictal activity and discriminate them from the areas of propagation.Analysis of 276 seizures from 30 patients revealed the existence of a seizure-related network reconfiguration in the gamma-band (25-170 Hz; p 0.005) - ictogenic nodes. Unlike seizure onset zone, resecting the majority of ictogenic nodes correlated with favorable outcomes (p 0.012).The prerequisite to successful epilepsy surgery is the accurate identification of brain areas from which seizures arise. We show that in FCD-related epilepsy, gamma-band network markers can reliably identify and distinguish ictogenic areas in macroelectrode recordings, improve intracranial EEG interpretation and better delineate the epileptogenic zone.Ictogenic nodes localize the critical parts of the epileptogenic tissue and increase the diagnostic yield of intracranial evaluation.

Early implantable epilepsy therapy devices provided open-loop electrical stimulation without brain sensing, computing, or an interface for synchronized behavioural inputs from patients. Recent epilepsy stimulation devices provide brain sensing but have not yet developed analytics for accurately tracking and quantifying behaviour and seizures. Here we describe a distributed brain co-processor providing an intuitive bi-directional interface between patient, implanted neural stimulation and sensing device, and local and distributed computing resources. Automated analysis of continuous streaming electrophysiology is synchronized with patient reports using a handheld device and integrated with distributed cloud computing resources for quantifying seizures, interictal epileptiform spikes and patient symptoms during therapeutic electrical brain stimulation. The classification algorithms for interictal epileptiform spikes and seizures were developed and parameterized using long-term ambulatory data from nine humans and eight canines with epilepsy, and then implemented prospectively in out-of-sample testing in two pet canines and four humans with drug-resistant epilepsy living in their natural environments. Accurate seizure diaries are needed as the primary clinical outcome measure of epilepsy therapy and to guide brain-stimulation optimization. The brain co-processor system described here enables tracking interictal epileptiform spikes, seizures and correlation with patient behavioural reports. In the future, correlation of spikes and seizures with behaviour will allow more detailed investigation of the clinical impact of spikes and seizures on patients.

An ischemic stroke is a local lesion that disrupts the large-scale structural and functional connectivity of the brain. Although local, the ischemic stroke often leads to deficits in cognitive functions which can’t be explained by local brain damage. It is believed that stroke-induced large-scale network alteration represents the mechanisms responsible for a decline in cognitive functions which are dependent on large-scale integration. To gain insight into the pathophysiological principles of how a local lesion results in a global cognitive decline requires a reliable and robust algorithm that can quantify the relationship between cognitive functions and network properties. In this study, we have developed, optimized, and tested a processing pipeline to parameterize complex neuropsychological evaluation and determine the functional connectivity from high-density EEG recordings. The developed algorithm was applied on a cohort of 27 patients who suffered a stroke and who were underwent cognitive examinations and high-density EEG monitoring one and two years after the stroke. The developed automatic algorithm demonstrated that it can reliably estimate functional connectivity and that it is robust against the physiological and technical artifacts. The proposed processing pipeline allows an unbiased and quantitative characterization of cognitive performance and its comparison with functional connectivity alterations.

Early implantable epilepsy therapy devices provided open-loop electrical stimulation without brain sensing, computing, or an interface for synchronized behavioral inputs from patients. Recent epilepsy stimulation devices provide brain sensing but have not yet developed analytics for accurately tracking and quantifying behavior and seizures. Here we describe a distributed brain co-processor providing an intuitive bi-directional interface between patient, implanted neural stimulation and sensing device, and local and distributed computing resources. Automated analysis of continuous streaming electrophysiology is synchronized with patient reports using a hand-held device and integrated with distributed cloud computing resources for quantifying seizures, interictal epileptiform spikes, and patient symptoms during therapeutic electrical brain stimulation. The classification algorithms for interictal epileptiform spikes and seizures were developed and parameterized using long-term ambulatory data from 9 humans and 8 canines with epilepsy, and then implemented prospectively in out-of-sample testing in 2 pet canines and 4 humans with drug resistant epilepsy living in their natural environments.

Networked optical wireless communication, also denoted as LiFi, is expected to play an important role in so-called smart hospitals. In this paper, we present the first experimental study of LiFi in an operating room at Motol University Hospital in Prague, Czech Republic. First, we perform one-to-one measurements using an optical transmitter (Tx) and receiver (Rx) and observe that channels with a free LOS provide sufficient signal strength for mobile communication inside the operating room. Then we combine the individual LOS links into a multiple-input multiple-output (MIMO) link using four distributed transmitters representing a wireless infrastructure, and six distributed receivers representing medical devices. In this configuration, at least two strong singular values of the MIMO channel matrix are observed which allow spatial multiplexing. By appropriately clustering the transmitters and selecting the users, mobile devices can be served in parallel. For data transmission, several multiplexing schemes such as time-division multiple access (TDMA) with one and two best links, TDMA with spatial reuse, space-division multiple access (SDMA) with two best links with and without zero forcing (ZF) are considered. Results show that SDMA with ZF increases the data rate by 2.7 times compared to baseline TDMA, resulting in a total data rate of 600 Mbit/s.

The thermal effect of a novel effective electrical stimulation mapping (ESM) technique using an Ojemann's stimulation electrode in open craniotomy areas causes a nondestructive local increase in temperature. Another type of stimulating electrode is a subdural strip, routinely used in intraoperative electrocorticography (ECoG), which applies ESM in a covered subdural area over the motor cortex. ECoG electrode geometry produces a different electrical field, causing a different Joule heat distribution in tissue, one that is impossible to measure in subdural space. Therefore, the previous safety control study of the novel ESM technique needed to be extended to include an assessment of the thermal effect of ECoG strip electrodes. We adapted a previously well-validated numerical model and performed coupled complex electro-thermal transient simulations for short-time (28.4 ms) high-frequency (500 Hz) and hyperintense (peak 100 mA) ESM paradigm. The risk of heat-induced cellular damage was assessed by applying the Arrhenius equation integral on the computed time-dependent spatial distribution of temperature in the brain tissue during ESM stimulation and during the cooldown period. The results showed increases in temperature in the proximity around ECoG electrode discs in a safe range without destructive effects. As opposed to open craniotomy, subdural space is not cooled by the air; hence a higher - but still safe - induced temperature was observed. The presented simulation agrees with the previously published histopathological examination of the stimulated brain tissue, and confirms the safety of the novel ESM technique when applied using ECoG strip electrodes.

OBJECTIVEResective epilepsy surgery is an established treatment method for children with focal intractable epilepsy, but the use of this method introduces the risk of postsurgical motor deficits. Electrical stimulation mapping (ESM), used to define motor areas and pathways, frequently fails in children. The authors developed and tested a novel ESM protocol in children of all age categories.METHODSThe ESM protocol utilizes high-frequency electric cortical stimulation combined with continuous intraoperative motor-evoked potential (MEP) monitoring. The relationships between stimulation current intensity and selected presurgical and surgery-associated variables were analyzed in 66 children (aged 7 months to 18 years) undergoing 70 resective epilepsy surgeries in proximity to the motor cortex or corticospinal tracts.RESULTSESM elicited MEP responses in all children. Stimulation current intensity was associated with patient age at surgery and date of surgery (F value = 6.81, p < 0.001). Increase in stimulation current intensity predicted postsurgical motor deficits (F value = 44.5, p < 0.001) without effects on patient postsurgical seizure freedom (p > 0.05).CONCLUSIONSThe proposed ESM paradigm developed in our center represents a reliable method for preventing and predicting postsurgical motor deficits in all age groups of children. This novel ESM protocol may increase the safety and possibly also the completeness of epilepsy surgery. It could be adopted in pediatric epilepsy surgery centers.

This paper aims to employ the numerical simulations to assess the risk of cellular damage during the application of a novel paradigm of electrical stimulation mapping (ESM) used in neurosurgery. The core principle of the paradigm is the use of short, high-intensity and high-frequency stimulation pulses. We developed a complex numerical model and performed coupled electro-thermal transient simulations. The model was optimized by incorporating ESM electrodes’ resistance obtained during multiple intraoperative measurements and validated by comparing them with the results of temperature distribution measurement acquired by thermal imaging. The risk of heat-induced cellular damage was assessed by applying the Arrhenius equation integral on the computed time-dependent spatial distribution of temperature in the brain tissue. Our results suggest that the impact of the temperature increase during our novel ESM paradigm is thermally non-destructive. The presented simulation results match the previously published thermographic measurement and histopathological examination of the stimulated brain tissue and confirm the safety of the novel ESM.

Between seizures, irritative network generates frequent brief synchronous activity, which manifests on the EEG as interictal epileptiform discharges (IEDs). Recent insights into the mechanism of IEDs at the microscopic level have demonstrated a high variance in the recruitment of neuronal populations generating IEDs and a high variability in the trajectories through which IEDs propagate across the brain. These phenomena represent one of the major constraints for precise characterization of network organization and for the utilization of IEDs during presurgical evaluations. We have developed a new approach to dissect human neocortical irritative networks and quantify their properties. We have demonstrated that irritative network has modular nature and it is composed of multiple independent sub-regions, each with specific IED propagation trajectories and differing in the extent of IED activity generated. The global activity of the irritative network is determined by long-term and circadian fluctuations in sub-region spatiotemporal properties. Also, the most active sub-region co-localizes with the seizure onset zone in 12/14 cases. This study demonstrates that principles of recruitment variability and propagation are conserved at the macroscopic level and that they determine irritative network properties in humans. Functional stratification of the irritative network increases the diagnostic yield of intracranial investigations with the potential to improve the outcomes of surgical treatment of neocortical epilepsy.

The cortical Electric Stimulation Mapping (ESM) procedure is used as a standard approach to localize and continuously monitor function of the eloquent cortex and corticospinal tract during neurosurgical intervention. However, eliciting motor responses using standard ESM paradigm is frequently difficult to young children. We have thus developed and tested a novel EMS protocol, which uses intense, high frequency and short stimulation pulses. However, the intense stimulation peak-peak current (up to 100 mA) possess the potential risk of tissue damage.

Interictal epileptiform discharges (spikes, IEDs) are electrographic markers of epileptic tissue and their quantification is utilized in planning of surgical resection. Visual analysis of long-term multi-channel intracranial recordings is extremely laborious and prone to bias. Development of new and reliable techniques of automatic spike detection represents a crucial step towards increasing the information yield of intracranial recordings and to improve surgical outcome. In this study, we designed a novel and robust detection algorithm that adaptively models statistical distributions of signal envelopes and enables discrimination of signals containing IEDs from signals with background activity. This detector demonstrates performance superior both to human readers and to an established detector. It is even capable of identifying low-amplitude IEDs which are often missed by experts and which may represent an important source of clinical information. Application of the detector to non-epileptic intracranial data from patients with intractable facial pain revealed the existence of sharp transients with waveforms reminiscent of interictal discharges that can represent biological sources of false positive detections. Identification of these transients enabled us to develop and propose secondary processing steps, which may exclude these transients, improving the detector's specificity and having important implications for future development of spike detectors in general.

Loss of Neuronal Network Resilience Precedes Seizures and Determines the Ictogenic Nature of Interictal Synaptic Perturbations Chang WC, Kudlacek J, Hlinka J, et al. Nat Neurosci. 2018; 21(12):1742-1752. doi:10.1038/s41593-018-0278-y. PMID: 30482946.The mechanism of seizure emergence and the role of brief interictal epileptiform discharges (IEDs) in seizure generation are 2 of the most important unresolved issues in modern epilepsy research. We found that the transition to seizure is not a sudden phenomenon, but is instead a slow process that is characterized by the progressive loss of neuronal network resilience. From a dynamical perspective, the slow transition is governed by the principles of critical slowing, a robust natural phenomenon that is observable in systems characterized by transitions between dynamical regimes. In epilepsy, this process is modulated by synchronous synaptic input from IEDs. The IEDs are external perturbations that produce phasic changes in the slow transition process and exert opposing effects on the dynamics of a seizure-generating network, causing either antiseizure or proseizure effects. We found that the multifaceted nature of IEDs is defined by the dynamical state of the network at the moment of the discharge occurrence.

High frequency oscillations (HFOs) are novel biomarker of epileptogenic tissue. HFOs are currently used to localize the seizure generating areas of the brain, delineate the resection and to monitor the disease activity. It is well established that spatiotemporal dynamics of HFOs can be modified by sleep-wake cycle. In this study we aimed to evaluate in detail circadian and ultradian changes in HFO dynamics using techniques of automatic HFO detection. For this purpose we have developed and implemented novel algorithm to automatic detection and analysis of HFOs in long-term intracranial recordings of six patients. In 5/6 patients HFO rates significantly increased during NREM sleep. The largest NREM related increase in HFO rates were observed in brain areas which spatially overlapped with seizure onset zone. Analysis of long-term recording revealed existence of ultradian changes in HFO dynamics. This study demonstrated reliability of automatic HFO detection in the analysis of long-term intracranial recordings in humans. Obtained results can foster practical implementation of automatic HFO detecting algorithms into presurgical examination, dramatically decrease human labour and increase the information yield of HFOs.

Interictal epileptiform discharges (spikes) represent electrographic marker of epileptogenic brain tissue. Besides ictal onsets, localization of interictal epileptiform discharges provides additional information to plan resective epilepsy surgery. The main goals of this study were: 1) to develop a reliable automatic algorithm to detect high and low amplitude interictal epileptiform discharges in intracranial EEG recordings and 2) to design a clustering method to extract spatial patterns of their propagation. For detection, we used a signal envelope modeling technique which adaptively identifies statistical parameters of signals containing spikes. Application of this technique to human intracranial EEG data demonstrated that it was superior to expert labeling and it was able to detect even small amplitude interictal epileptiform discharges. In the second task, detected spikes were clustered by principal component analysis according to their spatial distribution. Preliminary results showed that this unsupervised approach is able to identify distinct sources of interictal epileptiform discharges and has the potential to increase the yield of presurgical examination by improved delineation of the irritative zone.

High-frequency oscillations (HFOs) represent relatively new electrographic marker of epileptogenic tissue. It is starting to be used in presurgical examination to better plan surgical resection and to improve outcome of epilepsy surgery. Development of new techniques of unsupervised HFOs detection is required to further investigate the role of HFO in the pathophysiology of epilepsy and to increase the yield of presurgical examination. In this study we applied an envelope distribution modelling technique on experimental and human invasive data to detect HFOs. Application to experimental microelectrode recordings demonstrated satisfactory results with sensitivity 89.9% and false positive rate 2.1 per minute. Application of this algorithm to human invasive recordings achieved sensitivity 80%. High numbers of false positive detections required utilization of postprocessing steps to eliminate the majority of them. This study shows that envelope distribution modelling represents a promising approach to detect HFOs in intracranial recordings. Advantages of this approach are quick adjustments to changes in background activity and resistance to signal nonstationarities. However, successful application to clinical practice requires development of secondary processing steps that will decrease the rate of false positive detections.

This paper presents the possibility of early detection and localization of epileptogenic focus in the iEEG (intracranial Electroencephalography) signal using a method based on multidimensional autoregressive models. The work provides the first results of the method in the iEEG signal, and discusses technical aspects in terms of the suitability of the sampling frequency, AR model order and segmentation step.

Objective To assess whether available algorithms of quantitative EEG (qEEG) could practically help in localizing epileptogenic zone (EZ) and modify surgical planning in patients with focal intractable epilepsy. Methods We will present a case report of a 7-year-old boy with catastrophic epilepsy caused by focal cortical dysplasia located in the operculo-insular region of the right hemisphere. Due to the challenging localization of the presumed EZ, uncertain surgical borders and expected significant risks of the resection, the patient was stereotactically implanted with oblique depth electrodes. Intracranial EEG (iEEG) signal was analyzed using different qEEG methods. Our originally developed interictal epileptiform discharges (IED) detecting algorithm, which also extracts repetitive propagation patterns, was applied to localize sources of IED. We also used own network connectivity algorithm to analyze ictal (seizure) iEEG activity in detail. Employing results of qEEG analyses, 2D and 3D dynamic reconstructions of both interictal and ictal iEEG epileptiform changes were created and used to guide surgical approach. Results Both qEEG algorithms clearly proved the EZ localization in the dorso-caudal insular cortex of the right hemisphere and demonstrated sparing of initially suspected frontal opercular area. The dorso-caudal insular cortex generated 89% of IED; remaining 11% IED originated from the primary motor cortex. Surgical approach was adjusted to this qEEG-based hypothesis. Oblique depth electrodes were preserved intraoperatively to help precise targeting of the lesion. Continuous intraoperative motor-evoked potential monitoring was used to preserve motor functions. The boy has been followed for more than one year postoperatively. He is seizure-free with no motor deficit; with normal cognitive functions. Conclusions The case report demonstrates that currently available qEEG methods could help in guiding resective epilepsy surgery in complicated patients indicated for iEEG studies. We suggest our approach could increase patients’ chance to obtain seizure-free outcomes without new deficits and thus ultimately improve their quality of life. Supported by MH CZ–DRO, University Hospital Motol, Prague, Czech Republic 00064203 and IGA NT/11460-4.

Objective Interictal epileptiform discharges (IEDs) are electrographic hallmark of epilepsy. Information about the spatiotemporal distribution of IEDs in intracranial EEG is utilized to localize epileptogenic zone during the presurgical evaluation and plan the resection. Visual evaluation of long-term multi-channel intracranial recordings is extremely difficult and prone to bias. Clinicians usually assess only high-amplitude (high signal to noise ratio) discharge and low-amplitude IEDs can be overlooked or considered clinically insignificant. The goal of our study was to develop reliable automatic IED detectors to facilitate analysis of long-term recordings and increase the information yield of intracranial recordings. Methods Seven intracranial EEG recordings were randomly selected from our database. Samples of five minutes duration from fifteen high-rate IED channels (525 min in total) were presented to three experienced EEG specialists for spike labelling. The readers independently reviewed the data and classified IEDs into two groups: obvious and ambiguous. The inter-reader agreement was evaluated and IEDs labelled by at least two readers were considered as a gold standard (GS). We have developed, tested and optimized novel IED detector using GS datasets and compared its performance with published detectors. Our detecting approach estimates the signal envelope distribution to discriminate IEDs from background activity. Results Readers together labelled 6518 IEDs (53 ± 21% obvious, 47 ± 21% ambiguous). The reader’s maximal match was 58% in pair and agreement of all three readers was only 30% (Cohen’s kappa 0.14 ± 0.11). Detector’s performance was characterized by sensitivity 91 ± 12% and 8 ± 7 false positives per min and per channel. Its performance was 1.4× better than published detector. Examination of false positives revealed that substantial proportion had shape of reminiscent of IEDs, but with lower amplitude. More than 50% false positives were reclassified by readers as IEDs. In addition, regression analysis showed positive relationship between IEDs marked by readers and number of false positives. Conclusion The inter-reader agreement in visual IED evaluation is poor. Even experienced readers can identify approximately 40% of IED, especially those with high signal-to-noise ratio. In contrast, automatic detector is 2.5× more sensitive and can identify also low-amplitude IEDs. Areas generating not only high- but also low-amplitude IEDs can be crucial for epileptogenic zone localization. Supported by grants from IGA NT11460, NT13357, NT14489, GACR 14-02634S and Neuron Fund (NFKJ 001/2012).

Novel and quantitative methods EEG signal analysis are being developed by close multidisciplinary collaborations between epilepsy specialists, biomedical engineers and mathematicians. Quantitative analysis of the long-term monitoring from intracranial electrodes is expected to provide precise and objective results. High performance computational algorithms will be presented, not only from technical point of view, but also to demonstrate that output of these techniques can provide quantitative and clinically relevant diagnostic information. Three types of automatic and semi-automatic algorithms of quantitative EEG analysis will be presented and their benefits for epilepsy surgery planning discussed. Interictal epileptiform discharges and high-frequency oscillations represent electrographic markers of epileptic tissue. Methods of their automatic detection can substantially facilitate analysis of multi-channel long-term intracranial recordings and extract unbiased meaningful information about spatiotemporal and morphological properties of these markers. Visual identification of seizure onset zone in intracranial recordings is challenging and prone to bias. Methods of seizure onset identification represent one of the main research directions of intracranial signal processing. It has been demonstrated that introduction of causality measures and network analysis can provide useful information about epileptic network organization. These techniques are capable to identify the seizure onset zone in both ictal and interictal recordings. Application of average Directed Transfer Function and Granger’s causality to intracranial recordings demonstrate that seizure onset zone is characterized by the disconnection from the rest of the epileptic network. Increased information yield and quantitative results lead to increased integration of the above mentioned methods into presurgical diagnosis. These methods of intracranial signal analysis can improve guiding of resective surgery in difficult-to-treat cases and offer surgery to patients formerly classified as not suitable for surgery. Supported by grants from IGA NT11460, NT13357, NT14489, GACR 14-02634S and Neuron Fund (NFKJ 001/2012).

Background High frequency oscillations (HFOs) represent new electrographic marker of epileptogenic tissue and they are considered as a surrogate marker of seizure onset and epileptogenic zones. HFOs are recorded mainly in intracranial recordings. Visual analysis of HFOs in long-term recordings is extremely difficult due to the low signal-to-noise ratio of HFOs. Successful integration of HFOs into presurgical evaluation requires development of reliable methods of automatic HFO detection and quantification. We aimed to examine performance of three new HFO detecting algorithms and compared their performance with published detectors. Methods We implemented three published detectors which utilize RMS, line length or Hilbert transform approach to detect HFOs. We have developed additional three types of detectors which utilize short time energy estimation, Hilbert envelope and Bayesian evidence. All HFO detecting algorithms were applied to gold standard datasets and their performance quantified. Results Line length and Hilbert detectors detected the highest number of HFOs. The lowest number of the detections was achieved by RMS and energy estimating detectors. According to the results, the detectors can be divided into two groups. One group is characterized by high sensitivity. These algorithms detect nearly all the labeled HFOs events, but suffer from the high false positive detection rate. Second group of detectors have high positive prediction value but lower sensitivity. Our Hilbert envelope detector demonstrated the best performance of all evaluated detectors. Conclusions To improve the performance of detectors with high sensitivity will require to develop additional post-processing steps to remove the majority of false detections. Meanwhile detectors with low sensitivity will detect only high-amplitude HFOs. Future selection of the most appropriate algorithm for HFO detection in intracranial recordings will require detail understanding of the clinical significance of low-amplitude HFOs and major sources of false positive detections. Supported by Grants from IGA NT11460, NT13357, NT14489, GACR 14-02634S and Neuron Fund (NFKJ 001/2012).

Rationale The irritative zone is an area of the brain generating interictal epileptiform discharges (IEDs) that is used together with other results when planning epilepsy surgery. This zone possesses relatively low diagnostic value due to lack of a specific marker that would identify IEDs generated within the epileptogenic tissue. To increase diagnostic yield of irritative zone, we examined its functional organization. Methods Intracranial EEG recordings from 14 patients with refractory neocortical epilepsy were analysed using an algorithm that separates IEDs according to their spatial distribution into clusters. Analysis of cluster properties enabled to determine: (1) activity – percentage contribution to all IEDs in the given recording; (2) origins – the contacts where cluster initiates and (3) active region – the area of the most common propagation. Results On average 16,868 ± 16,813 IEDs per patient were analysed. The results demonstrated that in all patients the irritative zone was composed of multiple clusters with an average number of 12.5 ± 4.7 clusters per patient. The strongest cluster generated 43.5 ± 18.9% of all IEDs Average size of active region was 4.5 ± 4.5 contacts and contained 2.2 ± 1.7 origins. Evaluation of the cluster resection with the outcome suggested that the topology of the irritative zone may determine the success of the resection. Conclusion This study demonstrates the complex organization and modular nature of the neocortical irritative zone in epilepsy patients. It can be stratified into functional components, each with distinct pathophysiological and clinical significance. The ability to identify the key components of this network and its topology has potential to improve the results of epilepsy surgery. Supported by grants from IGA NT11460, NT13357, NT14489, GACR 14-02634S and Neuron Fund (NFKJ 10/2012).

Purpose Patients with hippocampal sclerosis associated with focal cortical dysplasia can have a higher risk of seizure recurrence if both of these pathologies are not removed. The aim of our study was to determine the role of intraoperative electrocorticography in detection of this dual pathology. Methods Intraoperative electrocorticography recordings were obtained in patients who underwent anteromedial temporal lobe resection. Patients with histopathologically proven hippocampal sclerosis and temporal pole available for analysis were included and were divided into two groups according to histopathology: isolated hippocampal sclerosis ( n = 23) and hippocampal sclerosis associated with focal cortical dysplasia – FCD IIIa ( n = 23).Cortical activity was measured prior to the resection using two six-contact strips (sampling from latero-basal and temporo-polar regions respectively) and one four contact strip sampling from mesio-basal temporal cortex. Occurrence of isolated mesial and independent neocortical (basal or lateral) spike activity was evaluated. Data analysis was performed by raters blinded to histopathology. Results Independent neocortical spikes were identified more frequently in patients with dual pathology (sixteen patients with FCD IIIa vs. four patients with isolated hippocampal sclerosis; p = 0.01). On the contrary, isolated mesial spikes occurred more often in patients with isolated hippocampal sclerosis (19 patients vs. six patients with FCD IIIa). In one patient with FCD IIIa no spikes were recorded. Conclusion Independent latero-basal temporal spikes recorded during intraoperative electrocorticography in patients with hippocampal sclerosis suggest associated dysplastic tissue in neocortex, i.e. dual pathology. Support: IGA MZ CR NT14489–3.

This paper deals with data analysis of electrodynamic activity of two mutants of yeast cells, cell cycle of which is synchronized and non-synchronized, respectively. We used data already published by Jelinek et al. and treat them with data mining method based on the multilayer neural network. Intersection of data mining and statistical distribution of the noise shows significant difference between synchronized and non-synchronized yeasts not only in total power, but also discrete frequencies.