Ictal dystonia and secondary generalization in temporal lobe seizures: a video-EEG study.

PubMed

Popovic, Ljubica; Vojvodic, Nikola; Ristic, Aleksandar J; Bascarevic, Vladimir; Sokic, Dragoslav; Kostic, Vladimir S

2012-12-01

The aim of this study was to determine whether the occurrence of unilateral ictal limb dystonia (ID) during complex partial seizures (CPS) reduces the possibility of contralateral propagation (CP) and secondary generalization (SG) in patients with temporal lobe epilepsy (TLE). We assessed 216 seizures recorded in 33 patients with pharmacoresistant TLE. All patients underwent video-EEG telemetry prior to surgical treatment with good postoperative outcomes (Engel I). Ictal limb dystonia was observed in 16 of the 33 patients (48%) and 58 of the 216 seizures (26.8%). We found highly significant differences in the frequency of SG between seizures with ID and seizures without ID (2/58 vs. 41/158; 3.45% vs. 25.95%; p<0.001). Contralateral propagation was seen in 13 of the 57 analyzed seizures with ID compared to 85 of the 158 seizures without ID (22.8% vs. 53.8%; p<0.001). Among the CPS without SG, we found that the mean duration of seizures with ID was significantly longer than the duration of seizures without ID (81.66±40.10 vs. 68.88±25.01 s; p=0.011). Our findings that CP and SG occur less often in patients with ID, yet the duration of CPS without SG is longer in patients with ID, suggest that the basal ganglia might inhibit propagation to the contralateral hemisphere but not ictal activity within the unilateral epileptic network. Copyright © 2012 Elsevier Inc. All rights reserved.

Alterations of network synchrony after epileptic seizures: An analysis of post-ictal intracranial recordings in pediatric epilepsy patients.

PubMed

Tomlinson, Samuel B; Khambhati, Ankit N; Bermudez, Camilo; Kamens, Rebecca M; Heuer, Gregory G; Porter, Brenda E; Marsh, Eric D

2018-07-01

Post-ictal EEG alterations have been identified in studies of intracranial recordings, but the clinical significance of post-ictal EEG activity is undetermined. The purpose of this study was to examine the relationship between peri-ictal EEG activity, surgical outcome, and extent of seizure propagation in a sample of pediatric epilepsy patients. Intracranial EEG recordings were obtained from 19 patients (mean age = 11.4 years, range = 3-20 years) with 57 seizures used for analysis (mean = 3.0 seizures per patient). For each seizure, 3-min segments were extracted from adjacent pre-ictal and post-ictal epochs. To compare physiology of the epileptic network between epochs, we calculated the relative delta power (Δ) using discrete Fourier transformation and constructed functional networks based on broadband connectivity (conn). We investigated differences between the pre-ictal (Δ pre , conn pre ) and post-ictal (Δ post , conn post ) segments in focal-network (i.e., confined to seizure onset zone) versus distributed-network (i.e., diffuse ictal propagation) seizures. Distributed-network (DN) seizures exhibited increased post-ictal delta power and global EEG connectivity compared to focal-network (FN) seizures. Following DN seizures, patients with seizure-free outcomes exhibited a 14.7% mean increase in delta power and an 8.3% mean increase in global connectivity compared to pre-ictal baseline, which was dramatically less than values observed among seizure-persistent patients (29.6% and 47.1%, respectively). Post-ictal differences between DN and FN seizures correlate with post-operative seizure persistence. We hypothesize that post-ictal deactivation of subcortical nuclei recruited during seizure propagation may account for this result while lending insights into mechanisms of post-operative seizure recurrence. Copyright © 2018 Elsevier B.V. All rights reserved.

Finding the missing link between ictal bradyarrhythmia, ictal asystole, and sudden unexpected death in epilepsy.

PubMed

Leung, H; Kwan, P; Elger, C E

2006-08-01

Basic science studies of the human brain have supported the cortical representation of cardiovascular responses, including heart rate variability. Clinical observations of ictal bradyarrhythmia may be mechanistically explained by the influence of the central autonomic network, although the localization and lateralization issues need to be considered in the light of patterns of seizure spread, hand dominance, and presence of lesions. Ictal bradyarrhythmia also offers a mechanistic explanation of sudden unexpected death in epilepsy (SUDEP), though it may explain only some but not all cases of SUDEP. The missing links are (1) clinical evidence of common factors shared by patients with ictal bradyarrhythmia and patients who die from SUDEP, (2) evidence of arrhythmia as a risk factor for SUDEP from epidemiological studies, and, (3) determination of the importance of ictal bradyarrhythmia in SUDEP with respect to other proposed mechanisms including apnea and intrinsic cardiac abnormalities. There remains a need to review the seizure mechanisms in cases of SUDEP and to step up the amount of concurrent ECG/intracranial EEG analysis in both ictal bradyarrhythmia and SUDEP cases.

Unilateral Eye Blinking Arising From the Ictal Ipsilateral Occipital Area.

PubMed

Falsaperla, Raffaele; Perciavalle, Valentina; Pavone, Piero; Praticò, Andrea Domenico; Elia, Maurizio; Ruggieri, Martino; Caraballo, Roberto; Striano, Pasquale

2016-07-01

We report on an 18-month-old boy with unilateral left eye blinking as a single ictal manifestation without facial twitching. The clinical onset of this phenomenon was first recorded (as an occasional event) at age 3 months, and it was overlooked. By age 6 months, the child's blinking increased to almost daily occurrence in clusters: during blinking the infant showed intact awareness and occasional jerks in the upper limbs and right leg. A video-electroencephalography (video-EEG) documented clinical correlation with a focal pattern arising from the left occipital region, and brain magnetic resonance imaging (MRI) revealed severe brain damage, consisting in poroencephalic hollows and increased spaces in the convexities involving a large area of the left cerebral hemisphere. The boy was prescribed sodium valproate (30 mg/kg/d), resulting in drastic reduction of his clinical seizures. Follow-up to his current age documented good general status, with persistent partial right hemilateral seizures. The blinking progressively disappeared, and is no longer recorded. The pathogenic hypotheses of the unilateral ictal blinking include involvement of the ipsilateral cerebral hemisphere and/or the cerebellar pathways. Review of previous reports of unilateral eye blinking, arising from the ictal ipsilateral brain, revealed that different damaged regions may give rise to blinking ictal phenomena, likely via the trigeminal fibres innervating the subdural intracranial structures and the pial vessels in the ipsilateral affected brain. The eye blinking in the present child represents a further example of an ictal phenomenon, which is predictive of the damaged brain region. © EEG and Clinical Neuroscience Society (ECNS) 2014.

A system for automatic artifact removal in ictal scalp EEG based on independent component analysis and Bayesian classification.

PubMed

LeVan, P; Urrestarazu, E; Gotman, J

2006-04-01

To devise an automated system to remove artifacts from ictal scalp EEG, using independent component analysis (ICA). A Bayesian classifier was used to determine the probability that 2s epochs of seizure segments decomposed by ICA represented EEG activity, as opposed to artifact. The classifier was trained using numerous statistical, spectral, and spatial features. The system's performance was then assessed using separate validation data. The classifier identified epochs representing EEG activity in the validation dataset with a sensitivity of 82.4% and a specificity of 83.3%. An ICA component was considered to represent EEG activity if the sum of the probabilities that its epochs represented EEG exceeded a threshold predetermined using the training data. Otherwise, the component represented artifact. Using this threshold on the validation set, the identification of EEG components was performed with a sensitivity of 87.6% and a specificity of 70.2%. Most misclassified components were a mixture of EEG and artifactual activity. The automated system successfully rejected a good proportion of artifactual components extracted by ICA, while preserving almost all EEG components. The misclassification rate was comparable to the variability observed in human classification. Current ICA methods of artifact removal require a tedious visual classification of the components. The proposed system automates this process and removes simultaneously multiple types of artifacts.

Ictal connectivity in childhood absence epilepsy: Associations with outcome.

PubMed

Tenney, Jeffrey R; Kadis, Darren S; Agler, William; Rozhkov, Leonid; Altaye, Mekibib; Xiang, Jing; Vannest, Jennifer; Glauser, Tracy A

2018-05-01

The understanding of childhood absence epilepsy (CAE) has been revolutionized over the past decade, but the biological mechanisms responsible for variable treatment outcomes are unknown. Our purpose in this prospective observational study was to determine how pretreatment ictal network pathways, defined using a combined electroencephalography (EEG)-functional magnetic resonance imaging (EEG-fMRI) and magnetoencephalography (MEG) effective connectivity analysis, were related to treatment response. Sixteen children with newly diagnosed and drug-naive CAE had 31 typical absence seizures during EEG-fMRI and 74 during MEG. The spatial extent of the pretreatment ictal network was defined using fMRI hemodynamic response with an event-related independent component analysis (eICA). This spatially defined pretreatment ictal network supplied prior information for MEG-effective connectivity analysis calculated using phase slope index (PSI). Treatment outcome was assessed 2 years following diagnosis and dichotomized to ethosuximide (ETX)-treatment responders (N = 11) or nonresponders (N = 5). Effective connectivity of the pretreatment ictal network was compared to the treatment response. Patterns of pretreatment connectivity demonstrated strongest connections in the thalamus and posterior brain regions (parietal, posterior cingulate, angular gyrus, precuneus, and occipital) at delta frequencies and the frontal cortices at gamma frequencies (P < .05). ETX treatment nonresponders had pretreatment connectivity, which was decreased in the precuneus region and increased in the frontal cortex compared to ETX responders (P < .05). Pretreatment ictal connectivity differences in children with CAE were associated with response to antiepileptic treatment. This is a possible mechanism for the variable treatment response seen in patients sharing the same epilepsy syndrome. Wiley Periodicals, Inc. © 2018 International League Against Epilepsy.

Time-Varying Networks of Inter-Ictal Discharging Reveal Epileptogenic Zone.

PubMed

Zhang, Luyan; Liang, Yi; Li, Fali; Sun, Hongbin; Peng, Wenjing; Du, Peishan; Si, Yajing; Song, Limeng; Yu, Liang; Xu, Peng

2017-01-01

The neuronal synchronous discharging may cause an epileptic seizure. Currently, most of the studies conducted to investigate the mechanism of epilepsy are based on EEGs or functional magnetic resonance imaging (fMRI) recorded during the ictal discharging or the resting-state, and few studies have probed into the dynamic patterns during the inter-ictal discharging that are much easier to record in clinical applications. Here, we propose a time-varying network analysis based on adaptive directed transfer function to uncover the dynamic brain network patterns during the inter-ictal discharging. In addition, an algorithm based on the time-varying outflow of information derived from the network analysis is developed to detect the epileptogenic zone. The analysis performed revealed the time-varying network patterns during different stages of inter-ictal discharging; the epileptogenic zone was activated prior to the discharge onset then worked as the source to propagate the activity to other brain regions. Consistence between the epileptogenic zones detected by our proposed approach and the actual epileptogenic zones proved that time-varying network analysis could not only reveal the underlying neural mechanism of epilepsy, but also function as a useful tool in detecting the epileptogenic zone based on the EEGs in the inter-ictal discharging.

Ictal SPECT using an attachable automated injector: clinical usefulness in the prediction of ictal onset zone.

PubMed

Lee, Jung-Ju; Lee, Sang Kun; Choi, Jang Wuk; Kim, Dong-Wook; Park, Kyung Il; Kim, Bom Sahn; Kang, Hyejin; Lee, Dong Soo; Lee, Seo-Young; Kim, Sung Hun; Chung, Chun Kee; Nam, Hyeon Woo; Kim, Kwang Ki

2009-12-01

Ictal single-photon emission computed tomography (SPECT) is a valuable method for localizing the ictal onset zone in the presurgical evaluation of patients with intractable epilepsy. Conventional methods used to localize the ictal onset zone have problems with time lag from seizure onset to injection. To evaluate the clinical usefulness of a method that we developed, which involves an attachable automated injector (AAI), in reducing time lag and improving the ability to localize the zone of seizure onset. Patients admitted to the epilepsy monitoring unit (EMU) between January 1, 2003, and June 30, 2008, were included. The definition of ictal onset zone was made by comprehensive review of medical records, magnetic resonance imaging (MRI), data from video electroencephalography (EEG) monitoring, and invasive EEG monitoring if available. We comprehensively evaluated the time lag to injection and the image patterns of ictal SPECT using traditional visual analysis, statistical parametric mapping-assisted, and subtraction ictal SPECT coregistered to an MRI-assisted means of analysis. Image patterns were classified as localizing, lateralizing, and nonlateralizing. The whole number of patients was 99: 48 in the conventional group and 51 in the AAI group. The mean (SD) delay time to injection from seizure onset was 12.4+/-12.0 s in the group injected by our AAI method and 40.4+/-26.3 s in the group injected by the conventional method (P=0.000). The mean delay time to injection from seizure detection was 3.2+/-2.5 s in the group injected by the AAI method and 21.4+/-9.7 s in the group injected by the conventional method (P=0.000). The AAI method was superior to the conventional method in localizing the area of seizure onset (36 out of 51 with AAI method vs. 21 out of 48 with conventional method, P=0.009), especially in non-temporal lobe epilepsy (non-TLE) patients (17 out of 27 with AAI method vs. 3 out of 13 with conventional method, P=0.041), and in lateralizing the

Stimulus-Induced Rhythmic, Periodic, or Ictal Discharges (SIRPIDs).

PubMed

Johnson, Emily L; Kaplan, Peter W; Ritzl, Eva K

2018-05-01

Stimulus-induced rhythmic, periodic, or ictal discharges (SIRPIDs) are a relatively common phenomenon found on prolonged electroencephalogram (EEG) monitoring that captures state changes and stimulation of critically ill patients. Common causes include hypoxic injury, traumatic brain injury, and hemorrhage, as well as toxic-metabolic disturbances. Some studies have shown an association between SIRPIDs and the presence of spontaneous electrographic seizures. Although the degree to which SIRPIDs should be treated with antiepileptic medications is unknown, the rare cases of functional imaging obtained in patients with SIRPIDs have not shown an increase in cerebral blood flow to suggest an active ictal process. Stimulus-induced rhythmic, periodic, or ictal discharges may reflect dysregulation of thalamo-cortical projections into abnormal or hyperexcitable cortex.

Scalp EEG does not predict hemispherectomy outcome

PubMed Central

Greiner, Hansel M.; Park, Yong D.; Holland, Katherine; Horn, Paul S.; Byars, Anna W.; Mangano, Francesco T.; Smith, Joseph R.; Lee, Mark R.; Lee, Ki-Hyeong

2012-01-01

Background Functional hemispherectomy is effective in carefully selected patients, resulting in a reduction of seizure burden up to complete resolution, improvement of intellectual development, and developmental benefit despite possible additional neurological deficit. Despite apparent hemispheric pathology on brain magnetic resonance imaging (MRI) or other imaging tests, scalp electroencephalography (EEG) could be suggestive of bilateral ictal onset or even ictal onset contralateral to the dominant imaging abnormality. We aimed to investigate the role of scalp EEG lateralization pre-operatively in predicting outcome. Methods We retrospectively reviewed 54 patients who underwent hemispherectomy between 1991 and 2009 at Medical College of Georgia (1991–2006) and Cincinnati Children’s Hospital Medical Center (2006–2009) and had at least one year post-operative follow-up. All preoperative EEGs were reviewed, and classified as either lateralizing or nonlateralizing, for both ictal and interictal EEG recordings. Results Of 54 patients, 42 (78%) became seizure free. Twenty-four (44%) of 54 had a nonlateralizing ictal or interictal EEG. Further analysis was based on etiology of epilepsy, including malformation of cortical development (MCD), Rasmussen syndrome (RS), and stroke (CVA). EEG nonlateralization did not predict poor outcome in any of the etiology groups evaluated. Conclusion Scalp EEG abnormalities in contralateral or bilateral hemispheres do not, in isolation, predict a poor outcome from hemispherectomy. Results of other non-invasive and invasive evaluations should be used to determine candidacy. PMID:21813300

Interictal to Ictal Phase Transition in a Small-World Network

NASA Astrophysics Data System (ADS)

Nemzer, Louis; Cravens, Gary; Worth, Robert

Real-time detection and prediction of seizures in patients with epilepsy is essential for rapid intervention. Here, we perform a full Hodgkin-Huxley calculation using n 50 in silico neurons configured in a small-world network topology to generate simulated EEG signals. The connectivity matrix, constructed using a Watts-Strogatz algorithm, admits randomized or deterministic entries. We find that situations corresponding to interictal (non-seizure) and ictal (seizure) states are separated by a phase transition that can be influenced by congenital channelopathies, anticonvulsant drugs, and connectome plasticity. The interictal phase exhibits scale-free phenomena, as characterized by a power law form of the spectral power density, while the ictal state suffers from pathological synchronization. We compare the results with intracranial EEG data and show how these findings may be used to detect or even predict seizure onset. Along with the balance of excitatory and inhibitory factors, the network topology plays a large role in determining the overall characteristics of brain activity. We have developed a new platform for testing the conditions that contribute to the phase transition between non-seizure and seizure states.

Prediction of rhythmic and periodic EEG patterns and seizures on continuous EEG with early epileptiform discharges.

PubMed

Koren, J; Herta, J; Draschtak, S; Pötzl, G; Pirker, S; Fürbass, F; Hartmann, M; Kluge, T; Baumgartner, C

2015-08-01

Continuous EEG (cEEG) is necessary to document nonconvulsive seizures (NCS), nonconvulsive status epilepticus (NCSE), as well as rhythmic and periodic EEG patterns of 'ictal-interictal uncertainty' (RPPIIU) including periodic discharges, rhythmic delta activity, and spike-and-wave complexes in neurological intensive care patients. However, cEEG is associated with significant recording and analysis efforts. Therefore, predictors from short-term routine EEG with a reasonably high yield are urgently needed in order to select patients for evaluation with cEEG. The aim of this study was to assess the prognostic significance of early epileptiform discharges (i.e., within the first 30 min of EEG recording) on the following: (1) incidence of ictal EEG patterns and RPPIIU on subsequent cEEG, (2) occurrence of acute convulsive seizures during the ICU stay, and (3) functional outcome after 6 months of follow-up. We conducted a separate analysis of the first 30 min and the remaining segments of prospective cEEG recordings according to the ACNS Standardized Critical Care EEG Terminology as well as NCS criteria and review of clinical data of 32 neurological critical care patients. In 17 patients with epileptiform discharges within the first 30 min of EEG (group 1), electrographic seizures were observed in 23.5% (n = 4), rhythmic or periodic EEG patterns of 'ictal-interictal uncertainty' in 64.7% (n = 11), and neither electrographic seizures nor RPPIIU in 11.8% (n = 2). In 15 patients with no epileptiform discharges in the first 30 min of EEG (group 2), no electrographic seizures were recorded on subsequent cEEG, RPPIIU were seen in 26.7% (n = 4), and neither electrographic seizures nor RPPIIU in 73.3% (n = 11). The incidence of EEG patterns on cEEG was significantly different between the two groups (p = 0.008). Patients with early epileptiform discharges developed acute seizures more frequently than patients without early epileptiform discharges (p = 0.009). Finally, functional

Peri-ictal water drinking and other ictal vegetative symptoms: Localizing and lateralizing the epileptogenic zone in temporal lobe epilepsy? Two case reports and review of the literature.

PubMed

Errguig, L; Lahjouji, F; Belaidi, H; Jiddane, M; Elkhamlichi, A; Dakka, T; Ouazzani, R

2013-11-01

Peri-ictal behavior disorders can be helpful in localizing and lateralizing seizure onset in partial epilepsies, especially those originating in the temporal lobe. In this paper, we present the case of two right-handed women aged 36 and 42 years who presented with partial seizures of mesial temporal type. Both of the patients had drug resistant epilepsy and undergone presurgical evaluation tests including brain magnetic resonance imaging, video-EEG monitoring and neuropsychological testing. The two patients had hippocampal sclerosis in the right temporal lobe and exhibited PIWD behavior concomitant with right temporal lobe discharges documented during video-EEG recordings. Anterior temporal lobectomy was performed in one case with an excellent outcome after surgery. The patient was free of seizures at 3 years follow-up. We reviewed other publications of peri-ictal autonomic symptoms considered to have a lateralizing significance, such as peri-ictal vomiting, urinary urge, ictal pilo-erection. Clinicians should search for these symptoms, even if not spontaneously reported by the patient, because they are often under-estimated, both by the patients themselves and by physicians. Additionally, patients with lateralizing auras during seizures have a significantly better outcome after epilepsy surgery than those without lateralizing features. Copyright © 2013. Published by Elsevier Masson SAS.

Characterization of ictal slow waves in epileptic spasms.

PubMed

Honda, Ryoko; Saito, Yoshiaki; Okumura, Akihisa; Abe, Shinpei; Saito, Takashi; Nakagawa, Eiji; Sugai, Kenji; Sasaki, Masayuki

2015-12-01

We characterized the clinico-neurophysiological features of epileptic spasms, particularly focusing on high-voltage slow waves during ictal EEG. We studied 22 patients with epileptic spasms recorded during digital video-scalp EEG, including five individuals who still had persistent spasms after callosotomy. We analysed the duration, amplitude, latency to onset of electromyographic bursts, and distribution of the highest positive and negative peaks of slow waves in 352 spasms. High-voltage positive slow waves preceded the identifiable muscle contractions of spasms. The mean duration of these positive waves was 569±228 m, and the mean latency to electromyographic onset was 182±127 m. These parameters varied markedly even within a patient. The highest peak of the positive component was distributed in variable regions, which was not consistent with the location of lesions on MRI. The peak of the negative component following the positivity was distributed in the neighbouring or opposite areas of the positive peak distribution. No changes were evident in the pre- or post-surgical distributions of the positive peak, or in the interhemispheric delay between both hemispheres, in individuals with callosotomy. Our data imply that ictal positive slow waves are the most common EEG changes during spasms associated with a massive motor component. Plausible explanations for these widespread positive slow waves include the notion that EEG changes possibly reflect involvement of both cortical and subcortical structures.

Ictal verbal help-seeking: Occurrence and the underlying etiology.

PubMed

Asadi-Pooya, Ali A; Asadollahi, Marjan; Bujarski, Krzysztof; Rabiei, Amin H; Aminian, Narsis; Wyeth, Dale; Sperling, Michael R

2016-11-01

Ictal verbal help-seeking has never been systematically studied before. In this study, we evaluated a series of patients with ictal verbal help-seeking to characterize its frequency and underlying etiology. We retrospectively reviewed all the long-term video-EEG reports from Jefferson Comprehensive Epilepsy Center over a 12-year period (2004-2015) for the occurrence of the term "help" in the text body. All the extracted reports were reviewed and patients with at least one episode of documented ictal verbal help-seeking in epilepsy monitoring unit (EMU) were studied. For each patient, the data were reviewed from the electronic medical records, EMU report, and neuroimaging records. During the study period, 5133 patients were investigated in our EMU. Twelve patients (0.23%) had at least one episode of documented ictal verbal help-seeking. Nine patients (six women and three men) had epilepsy and three patients (two women and one man) had psychogenic nonepileptic seizures (PNES). Seven out of nine patients with epilepsy had temporal lobe epilepsy; six patients had right temporal lobe epilepsy. Ictal verbal help-seeking is a rare finding among patients evaluated in epilepsy monitoring units. Ictal verbal help-seeking may suggest that seizures arise in or propagate to the right temporal lobe. Copyright © 2016 Elsevier Inc. All rights reserved.

Muscle and eye movement artifact removal prior to EEG source localization.

PubMed

Hallez, Hans; Vergult, Anneleen; Phlypo, Ronald; Van Hese, Peter; De Clercq, Wim; D'Asseler, Yves; Van de Walle, Rik; Vanrumste, Bart; Van Paesschen, Wim; Van Huffel, Sabine; Lemahieu, Ignace

2006-01-01

Muscle and eye movement artifacts are very prominent in the ictal EEG of patients suffering from epilepsy, thus making the dipole localization of ictal activity very unreliable. Recently, two techniques (BSS-CCA and pSVD) were developed to remove those artifacts. The purpose of this study is to assess whether the removal of muscle and eye movement artifacts improves the EEG dipole source localization. We used a total of 8 EEG fragments, each from another patient, first unfiltered, then filtered by the BSS-CCA and pSVD. In both the filtered and unfiltered EEG fragments we estimated multiple dipoles using RAP-MUSIC. The resulting dipoles were subjected to a K-means clustering algorithm, to extract the most prominent cluster. We found that the removal of muscle and eye artifact results to tighter and more clear dipole clusters. Furthermore, we found that localization of the filtered EEG corresponded with the localization derived from the ictal SPECT in 7 of the 8 patients. Therefore, we can conclude that the BSS-CCA and pSVD improve localization of ictal activity, thus making the localization more reliable for the presurgical evaluation of the patient.

The promise of subtraction ictal SPECT co-registered to MRI for improved seizure localization in pediatric epilepsies: Affecting factors and relationship to the surgical outcome

PubMed Central

Stamoulis, Catherine; Verma, Nishant; Kaulas, Himanshu; Halford, Jonathan J.; Duffy, Frank H.; Pearl, Phillip L.; Treves, S. Ted

2016-01-01

Objective Ictal SPECT is promising for accurate non-invasive localization of the epileptogenic brain tissue in focal epilepsies. However, high quality ictal scans require meticulous attention to the seizure onset. In a relatively large cohort of pediatric patients, this study investigated the impact of the timing of radiotracer injection, MRI findings and seizure characteristics on ictal SPECT localizations, and the relationship between concordance of ictal SPECT, scalp EEG and resected area with seizure freedom following epilepsy surgery. Methods Scalp EEG and ictal SPECT studies from 95 patients (48 males and 47 females, median age = 11 years, (25th, 75th) quartiles = (6.0, 14.75) years) with pharmacoresistant focal epilepsy and no prior epilepsy surgery were reviewed. The ictal SPECT result was examined as a function of the radiotracer injection delay, seizure duration, epilepsy etiology, cerebral lobe of seizure onset identified by EEG and MRI findings. Thirty two patients who later underwent epilepsy surgery had postoperative seizure freedom data at <1, 6 and 12 months. Results Sixty patients (63.2%) had positive SPECT localizations - 51 with a hyperperfused region that was concordant with the cerebral lobe of seizure origin identified by EEG and 9 with discordant localizations. Of these, 35 patients (58.3%) had temporal and 25 (41.7%) had extratemporal seizures. The ictal SPECT result was significantly correlated with the injection delay (p<0.01) and cerebral lobe of seizure onset (specifically frontal versus temporal; p = 0.02) but not MRI findings (p = 0.33), epilepsy etiology (p ≥ 0.27) or seizure duration (p = 0.20). Concordance of SPECT, scalp EEG and resected area was significantly correlated with seizure freedom at 6 months after surgery (p=0.04). Significance Ictal SPECT holds promise as a powerful source imaging tool for presurgical planning in pediatric epilepsies. To optimize the SPECT result the radiotracer injection delay should be minimized to

The promise of subtraction ictal SPECT co-registered to MRI for improved seizure localization in pediatric epilepsies: Affecting factors and relationship to the surgical outcome.

PubMed

Stamoulis, Catherine; Verma, Nishant; Kaulas, Himanshu; Halford, Jonathan J; Duffy, Frank H; Pearl, Phillip L; Treves, S Ted

2017-01-01

Ictal SPECT is promising for accurate non-invasive localization of the epileptogenic brain tissue in focal epilepsies. However, high quality ictal scans require meticulous attention to the seizure onset. In a relatively large cohort of pediatric patients, this study investigated the impact of the timing of radiotracer injection, MRI findings and seizure characteristics on ictal SPECT localizations, and the relationship between concordance of ictal SPECT, scalp EEG and resected area with seizure freedom following epilepsy surgery. Scalp EEG and ictal SPECT studies from 95 patients (48 males and 47 females, median age=11years, (25th, 75th) quartiles=(6.0, 14.75) years) with pharmacoresistant focal epilepsy and no prior epilepsy surgery were reviewed. The ictal SPECT result was examined as a function of the radiotracer injection delay, seizure duration, epilepsy etiology, cerebral lobe of seizure onset identified by EEG and MRI findings. Thirty two patients who later underwent epilepsy surgery had postoperative seizure freedom data at <1, 6 and 12 months. Sixty patients (63.2%) had positive SPECT localizations - 51 with a hyperperfused region that was concordant with the cerebral lobe of seizure origin identified by EEG and 9 with discordant localizations. Of these, 35 patients (58.3%) had temporal and 25 (41.7%) had extratemporal seizures. The ictal SPECT result was significantly correlated with the injection delay (p<0.01) and cerebral lobe of seizure onset (specifically frontal versus temporal; p=0.02) but not MRI findings (p=0.33), epilepsy etiology (p≥0.27) or seizure duration (p=0.20). Concordance of SPECT, scalp EEG and resected area was significantly correlated with seizure freedom at 6 months after surgery (p=0.04). Ictal SPECT holds promise as a powerful source imaging tool for presurgical planning in pediatric epilepsies. To optimize the SPECT result the radiotracer injection delay should be minimized to≤25s, although the origin of seizure onset

Correspondence between large-scale ictal and interictal epileptic networks revealed by single photon emission computed tomography (SPECT) and electroencephalography (EEG)-functional magnetic resonance imaging (fMRI).

PubMed

Tousseyn, Simon; Dupont, Patrick; Goffin, Karolien; Sunaert, Stefan; Van Paesschen, Wim

2015-03-01

Epilepsy is increasingly recognized as a network disorder, but the spatial relationship between ictal and interictal networks is still largely unexplored. In this work, we compared hemodynamic changes related to seizures and interictal spikes on a whole brain scale. Twenty-eight patients with refractory focal epilepsy (14 temporal and 14 extratemporal lobe) underwent both subtraction ictal single photon emission computed tomography (SPECT) coregistered to magnetic resonance imaging (MRI) (SISCOM) and spike-related electroencephalography (EEG-functional MRI (fMRI). SISCOM visualized relative perfusion changes during seizures, whereas EEG-fMRI mapped blood oxygen level-dependent (BOLD) changes related to spikes. Similarity between statistical maps of both modalities was analyzed per patient using the following two measures: (1) correlation between unthresholded statistical maps (Pearson's correlation coefficient) and (2) overlap between thresholded images (Dice coefficient). Overlap was evaluated at a regional level, for hyperperfusions and activations and for hypoperfusions and deactivations separately, using different thresholds. Nonparametric permutation tests were applied to assess statistical significance (p ≤ 0.05). We found significant and positive correlations between hemodynamic changes related to seizures and spikes in 27 (96%) of 28 cases (median correlation coefficient 0.29 [range -0.12 to 0.62]). In 20 (71%) of 28 cases, spatial overlap between hyperperfusion on SISCOM and activation on EEG-fMRI was significantly larger than expected by chance. Congruent changes were not restricted to the territory of the presumed epileptogenic zone, but could be seen at distant sites (e.g., cerebellum and basal ganglia). Overlap between ictal hypoperfusion and interictal deactivation was statistically significant in 22 (79%) of 28 patients. Despite the high rate of congruence, discrepancies were observed for both modalities. We conclude that hemodynamic changes

Contralateral interictal and ictal EEG epileptiform activity accentuate memory impairment in unilateral mesial temporal sclerosis patients.

PubMed

Pinto, Lecio F; Adda, Carla C; Silva, Liliane C A; Banaskiwitz, Natalie H C; Passarelli, Valmir; Jorge, Carmen L; Valerio, Rosa M; Castro, Luiz H

2017-03-01

Memory impairment is a recognized complication of mesial temporal sclerosis (MTS). Epileptiform activity may negatively impact on cognition. We evaluated the impact of contralateral EEG involvement on memory in unilateral MTS (uMTS) patients. Retrospective review of 121 right-handed uMTS patients (69 left) evaluated with prolonged video-EEG and verbal and nonverbal memory tests (Rey Auditory Verbal Learning Test and Rey-Osterrieth Complex figure), with additional very delayed trials. Patients were classified according to ictal/interictal EEG findings and MTS side as left or right concordant or discordant. Thirty-nine normal individuals who underwent the same neuropsychological battery served as controls. Demographic, disease, and treatment features did not differ among groups. On the 7-day verbal memory free recall, left discordant performed significantly worse than controls and right concordant, recognized fewer words, and had more recognition errors than all other groups, including left concordant. For nonverbal memory, right discordant performed significantly worse than controls on delayed recall, and attained lower scores than other groups on immediate and 7-day recall, but this difference did not reach statistical significance. Left discordant had higher scores of memory complaints than controls and disclosed a trend toward accentuated memory impairment compared with the other groups over time. Our results suggest that contralateral electrographic involvement in uMTS was associated with more pronounced memory impairment for verbal material in left discordant patients, and to a lesser extent, for nonverbal material in right discordant patients. Left discordant group also had increased memory complaints. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Sensitivity and Specificity of Interictal EEG-fMRI for Detecting the Ictal Onset Zone at Different Statistical Thresholds

PubMed Central

Tousseyn, Simon; Dupont, Patrick; Goffin, Karolien; Sunaert, Stefan; Van Paesschen, Wim

2014-01-01

There is currently a lack of knowledge about electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) specificity. Our aim was to define sensitivity and specificity of blood oxygen level dependent (BOLD) responses to interictal epileptic spikes during EEG-fMRI for detecting the ictal onset zone (IOZ). We studied 21 refractory focal epilepsy patients who had a well-defined IOZ after a full presurgical evaluation and interictal spikes during EEG-fMRI. Areas of spike-related BOLD changes overlapping the IOZ in patients were considered as true positives; if no overlap was found, they were treated as false-negatives. Matched healthy case-controls had undergone similar EEG-fMRI in order to determine true-negative and false-positive fractions. The spike-related regressor of the patient was used in the design matrix of the healthy case-control. Suprathreshold BOLD changes in the brain of controls were considered as false positives, absence of these changes as true negatives. Sensitivity and specificity were calculated for different statistical thresholds at the voxel level combined with different cluster size thresholds and represented in receiver operating characteristic (ROC)-curves. Additionally, we calculated the ROC-curves based on the cluster containing the maximal significant activation. We achieved a combination of 100% specificity and 62% sensitivity, using a Z-threshold in the interval 3.4–3.5 and cluster size threshold of 350 voxels. We could obtain higher sensitivity at the expense of specificity. Similar performance was found when using the cluster containing the maximal significant activation. Our data provide a guideline for different EEG-fMRI settings with their respective sensitivity and specificity for detecting the IOZ. The unique cluster containing the maximal significant BOLD activation was a sensitive and specific marker of the IOZ. PMID:25101049

The additional lateralizing and localizing value of the postictal EEG in frontal lobe epilepsy.

PubMed

Whitehead, Kimberley; Gollwitzer, Stephanie; Millward, Helen; Wehner, Tim; Scott, Catherine; Diehl, Beate

2016-03-01

The aim of this study was to describe the additional lateralizing and localizing value of the postictal EEG in frontal lobe epilepsy (FLE). The ictal EEG in FLE is frequently challenging to localize. We identified patients investigated for epilepsy surgery with unilateral FLE based on consistent semiology, a clear lesion and/or with frontal onset on intracranial EEG. A one hour section of postictal EEG was analyzed by two raters for new or activated EEG features and it was assessed whether these features offered additional information when compared to the ictal EEG. Postictal features assessed included asymmetrical return of the posterior dominant rhythm and potentiated lateralized or regional frontal slowing, spikes or sharp waves. Thirty-eight patients were included who had a combined total of ninety-six seizures. 47/96 (49%) postictal periods contained correctly lateralizing or localizing information. The sensitivity for asymmetrical return of the posterior dominant rhythm was 24%. The sensitivity for regional frontal slow and frontal spikes was 23% and 20% respectively. Further analysis showed that in 14/38 (39%) patients, at least one seizure with an unhelpful ictal EEG was followed by postictal EEG features that added new localizing or lateralizing information. A subgroup of 11 patients who were ⩾1 year seizure-free (ILAE class 1) and thus classified as having a 'gold-standard' FLE diagnosis were analyzed separately and it was found that 14/30 of their seizures (47%) had extra postictal information. The new postictal information was always concordant with the ultimate diagnosis, except for asymmetric postictal return of background activity ipsilateral to the epileptogenic zone in three patients. This study shows that a close examination of the postictal EEG can offer additional information which can contribute to the identification of a potentially resectable epileptogenic zone. Copyright © 2015 International Federation of Clinical Neurophysiology

[Ictal Speech Manifesting as Sleep Talking: A Case Report].

PubMed

Suzuki, Takehiro; Kakisaka, Yosuke; Kitazawa, Yu; Jin, Kazutaka; Sato, Shiho; Iwasaki, Masaki; Fujikawa, Mayu; Nishio, Yoshiyuki; Kanno, Akitake; Nakasato, Nobukazu

2017-02-01

We present a 28-year-old female patient whose epilepsy started at the age of 19. MRI showed right perisylvian polymicrogyria. She exhibited various seizure symptoms, such as somatosensory aura involving the left leg, dyscognitive seizures, and amnesic seizures. Her mother indicated that the patient sometimes had "sleep talking", which was associated with presence of epileptic seizures of the next day. Long-term video electroencephalography (EEG) revealed that her episodes of "sleep talking" were epileptic events, specifically ictal speech, originating in the right hemisphere. The present case demonstrates the importance of considering "sleep talk" as an epileptic symptom. Careful history taking is fundamental to carry patients with possibly pathological "sleep talk" to the long-term video EEG, which will contribute correct diagnosis and treatment. (Received August 16, 2016; Accepted September 9, 2016; Published February 1, 2017).

Neuronal autoantibodies in epilepsy patients with peri-ictal autonomic findings.

PubMed

Baysal-Kirac, Leyla; Tuzun, Erdem; Erdag, Ece; Ulusoy, Canan; Vanli-Yavuz, Ebru Nur; Ekizoglu, Esme; Peach, Sian; Sezgin, Mine; Bebek, Nerses; Gurses, Candan; Gokyigit, Aysen; Vincent, Angela; Baykan, Betul

2016-03-01

Autonomic dysfunction has frequently been reported in autoimmune encephalitis associated with seizures and there is growing evidence that epilepsy patients may display neuronal autoantibodies (NAAb). The aim of this study was to investigate the frequency of NAAb in epilepsy patients with peri-ictal autonomic findings. Fifty-eight patients (37 women/21 men; average age of 34.2 ± 9.9 years and epilepsy duration of 19.1 ± 9.6 years) who had at least one video-EEG recorded focal or secondary generalized seizure with clear-cut documented peri-ictal autonomic findings, or consistently reported seizures with autonomic semiology, were included. NAAb were tested by RIA or cell based assays. NAAb were present in 17 of 58 (29.3%) patients. Among seropositive patients, antibodies were directed against N-methyl-D-aspartate receptor (NMDAR) in 5 (29%), contactin-associated protein-like 2 (CASPR2) in 5 (29%), uncharacterized voltage gated potassium channel (VGKC)-complex antigens in 3 (18%), glutamic acid decarboxylase (GAD) in 2 (12%), glycine receptor (GLYR) in one (6%) and type A gamma aminobutyric acid receptor (GABAAR) in one patient (6%). Peri-ictal gastrointestinal manifestations, piloerection, ictal fever, urinary urge, and cough occurred more commonly in the seropositive group. The prevalences of psychotic attacks and status epilepticus were significantly increased in the seropositive group. Seropositivity prevalence in our patient group with peri-ictal autonomic findings is higher than other previously reported epilepsy cohorts. In our study, ictal fever-VGKC-complex antibody and pilomotor seizure-GABAAR antibody associations were documented for the first time. Chronic epilepsy patients with peri-ictal autonomic semiology, history of status epilepticus and psychotic disorder may benefit from autoantibody screening.

Distribution entropy analysis of epileptic EEG signals.

PubMed

Li, Peng; Yan, Chang; Karmakar, Chandan; Liu, Changchun

2015-01-01

It is an open-ended challenge to accurately detect the epileptic seizures through electroencephalogram (EEG) signals. Recently published studies have made elaborate attempts to distinguish between the normal and epileptic EEG signals by advanced nonlinear entropy methods, such as the approximate entropy, sample entropy, fuzzy entropy, and permutation entropy, etc. Most recently, a novel distribution entropy (DistEn) has been reported to have superior performance compared with the conventional entropy methods for especially short length data. We thus aimed, in the present study, to show the potential of DistEn in the analysis of epileptic EEG signals. The publicly-accessible Bonn database which consisted of normal, interictal, and ictal EEG signals was used in this study. Three different measurement protocols were set for better understanding the performance of DistEn, which are: i) calculate the DistEn of a specific EEG signal using the full recording; ii) calculate the DistEn by averaging the results for all its possible non-overlapped 5 second segments; and iii) calculate it by averaging the DistEn values for all the possible non-overlapped segments of 1 second length, respectively. Results for all three protocols indicated a statistically significantly increased DistEn for the ictal class compared with both the normal and interictal classes. Besides, the results obtained under the third protocol, which only used very short segments (1 s) of EEG recordings showed a significantly (p <; 0.05) increased DistEn for the interictal class in compassion with the normal class, whereas both analyses using relatively long EEG signals failed in tracking this difference between them, which may be due to a nonstationarity effect on entropy algorithm. The capability of discriminating between the normal and interictal EEG signals is of great clinical relevance since it may provide helpful tools for the detection of a seizure onset. Therefore, our study suggests that the Dist

High density scalp EEG in frontal lobe epilepsy.

PubMed

Feyissa, Anteneh M; Britton, Jeffrey W; Van Gompel, Jamie; Lagerlund, Terrance L; So, Elson; Wong-Kisiel, Lilly C; Cascino, Gregory C; Brinkman, Benjamin H; Nelson, Cindy L; Watson, Robert; Worrell, Gregory A

2017-01-01

Localization of seizures in frontal lobe epilepsy using the 10-20 system scalp EEG is often challenging because neocortical seizure can spread rapidly, significant muscle artifact, and the suboptimal spatial resolution for seizure generators involving mesial frontal lobe cortex. Our aim in this study was to determine the value of visual interpretation of 76 channel high density EEG (hdEEG) monitoring (10-10 system) in patients with suspected frontal lobe epilepsy, and to evaluate concordance with MRI, subtraction ictal SPECT co-registered to MRI (SISCOM), conventional EEG, and intracranial EEG (iEEG). We performed a retrospective cohort study of 14 consecutive patients who underwent hdEEG monitoring for suspected frontal lobe seizures. The gold standard for localization was considered to be iEEG. Concordance of hdEEG findings with MRI, subtraction ictal SPECT co-registered to MRI (SISCOM), conventional 10-20 EEG, and iEEG as well as correlation of hdEEG localization with surgical outcome were examined. hdEEG localization was concordant with iEEG in 12/14 and was superior to conventional EEG 3/14 (p<0.01) and SISCOM 3/12 (p<0.01). hdEEG correctly lateralized seizure onset in 14/14 cases, compared to 9/14 (p=0.04) cases with conventional EEG. Seven patients underwent surgical resection, of whom five were seizure free. hdEEG monitoring should be considered in patients with suspected frontal epilepsy requiring localization of epileptogenic brain. hdEEG may assist in developing a hypothesis for iEEG monitoring and could potentially augment EEG source localization. Published by Elsevier B.V.

Incidence and localizing value of vertigo and dizziness in patients with epilepsy: Video-EEG monitoring study.

PubMed

Kim, Dong Wook; Sunwoo, Jun-Sang; Lee, Sang Kun

2016-10-01

Vertigo and dizziness are common neurological complaints that have long been associated with epilepsy. However, studies of patients with epileptic vertigo or dizziness with concurrent EEG monitoring are scarce. We performed the present study to investigate the incidence and localizing value of vertigo and dizziness in patients with epilepsy who had confirmation of EEG changes via video-EEG monitoring. Data of aura and clinical seizure episodes of 831 consecutive patients who underwent video-EEG monitoring were analyzed retrospectively. Out of 831 patients, 40 patients (4.8%) experienced vertigo or dizziness as aura (mean age, 32.8±11.8years), all of whom had partial seizures. Eight had mesial temporal, 20 had lateral temporal, four had frontal, one had parietal, and seven had occipital lobe onset seizures. An intracranial EEG with cortical stimulation study was performed in seven patients, and the area of stimulation-induced vertigo or dizziness coincided with the ictal onset area in only one patient. Our study showed that vertigo or dizziness is a common aura in patients with epilepsy, and that the temporal lobe is the most frequent ictal onset area in these patients. However, it can be suggested that the symptomatogenic area in patients with epileptic vertigo and dizziness may not coincide with the ictal onset area. Copyright © 2016 Elsevier B.V. All rights reserved.

Seizure threshold increases can be predicted by EEG quality in right unilateral ultrabrief ECT.

PubMed

Gálvez, Verònica; Hadzi-Pavlovic, Dusan; Waite, Susan; Loo, Colleen K

2017-12-01

Increases in seizure threshold (ST) over a course of brief pulse ECT can be predicted by decreases in EEG quality, informing ECT dose adjustment to maintain adequate supra-threshold dosing. ST increases also occur over a course of right unilateral ultrabrief (RUL UB) ECT, but no data exist on the relationship between ST increases and EEG indices. This study (n = 35) investigated if increases in ST over RUL UB ECT treatments could be predicted by a decline in seizure quality. ST titration was performed at ECT session one and seven, with treatment dosing maintained stable (at 6-8 times ST) in intervening sessions. Seizure quality indices (slow-wave onset, mid-ictal amplitude, regularity, stereotypy, and post-ictal suppression) were manually rated at the first supra-threshold treatment, and last supra-threshold treatment before re-titration, using a structured rating scale, by a single trained rater blinded to the ECT session being rated. Twenty-one subjects (60%) had a ST increase. The association between ST changes and EEG quality indices was analysed by logistic regression, yielding a significant model (p < 0.001). Initial ST (p < 0.05) and percentage change in mid-ictal amplitude (p < 0.05) were significant predictors of change in ST. Percentage change in post-ictal suppression reached trend level significance (p = 0.065). Increases in ST over a RUL UB ECT course may be predicted by decreases in seizure quality, specifically decline in mid-ictal amplitude and potentially in post-ictal suppression. Such EEG indices may be able to inform when dose adjustments are necessary to maintain adequate supra-threshold dosing in RUL UB ECT.

Functional neurotoxicity evaluation of noribogaine using video-EEG in cynomolgus monkeys.

PubMed

Authier, Simon; Accardi, Michael V; Paquette, Dominique; Pouliot, Mylène; Arezzo, Joseph; Stubbs, R John; Gerson, Ronald J; Friedhoff, Lawrence T; Weis, Holger

2016-01-01

Continuous video-electroencephalographic (EEG) monitoring remains the gold standard for seizure liability assessments in preclinical drug safety assessments. EEG monitored by telemetry was used to assess the behavioral and EEG effects of noribogaine hydrochloride (noribogaine) in cynomolgus monkeys. Noribogaine is an iboga alkaloid being studied for the treatment of opioid dependence. Six cynomolgus monkeys (3 per gender) were instrumented with EEG telemetry transmitters. Noribogaine was administered to each monkey at both doses (i.e., 160 and 320mg/kg, PO) with an interval between dosing of at least 6days, and the resulting behavioral and EEG effects were evaluated. IV pentylenetetrazol (PTZ), served as a positive control for induced seizures. The administration of noribogaine at either of the doses evaluated was not associated with EEG evidence of seizure or with EEG signals known to be premonitory signs of increased seizure risk (e.g., sharp waves, unusual synchrony, shifts to high-frequency patterns). Noribogaine was associated with a mild reduction in activity levels, increased scratching, licking and chewing, and some degree of poor coordination and related clinical signs. A single monkey exhibited brief myoclonic movements that increased in frequency at the high dose, but which did not appear to generalize, cluster or to be linked with EEG abnormalities. Noribogaine was also associated with emesis and partial anorexia. In contrast, PTZ was associated with substantial pre-ictal EEG patterns including large amplitude, repetitive sharp waves leading to generalized seizures and to typical post-ictal EEG frequency attenuation. EEG patterns were within normal limits following administration of noribogaine at doses up to 320mg/kg with concurrent clinical signs that correlated with plasma exposures and resolved by the end of the monitoring period. PTZ was invariably associated with EEG paroxysmal activity leading to ictal EEG. In the current study, a noribogaine

A self-adapting system for the automated detection of inter-ictal epileptiform discharges.

PubMed

Lodder, Shaun S; van Putten, Michel J A M

2014-01-01

Scalp EEG remains the standard clinical procedure for the diagnosis of epilepsy. Manual detection of inter-ictal epileptiform discharges (IEDs) is slow and cumbersome, and few automated methods are used to assist in practice. This is mostly due to low sensitivities, high false positive rates, or a lack of trust in the automated method. In this study we aim to find a solution that will make computer assisted detection more efficient than conventional methods, while preserving the detection certainty of a manual search. Our solution consists of two phases. First, a detection phase finds all events similar to epileptiform activity by using a large database of template waveforms. Individual template detections are combined to form "IED nominations", each with a corresponding certainty value based on the reliability of their contributing templates. The second phase uses the ten nominations with highest certainty and presents them to the reviewer one by one for confirmation. Confirmations are used to update certainty values of the remaining nominations, and another iteration is performed where ten nominations with the highest certainty are presented. This continues until the reviewer is satisfied with what has been seen. Reviewer feedback is also used to update template accuracies globally and improve future detections. Using the described method and fifteen evaluation EEGs (241 IEDs), one third of all inter-ictal events were shown after one iteration, half after two iterations, and 74%, 90%, and 95% after 5, 10 and 15 iterations respectively. Reviewing fifteen iterations for the 20-30 min recordings 1 took approximately 5 min. The proposed method shows a practical approach for combining automated detection with visual searching for inter-ictal epileptiform activity. Further evaluation is needed to verify its clinical feasibility and measure the added value it presents.

A Self-Adapting System for the Automated Detection of Inter-Ictal Epileptiform Discharges

PubMed Central

Lodder, Shaun S.; van Putten, Michel J. A. M.

2014-01-01

Purpose Scalp EEG remains the standard clinical procedure for the diagnosis of epilepsy. Manual detection of inter-ictal epileptiform discharges (IEDs) is slow and cumbersome, and few automated methods are used to assist in practice. This is mostly due to low sensitivities, high false positive rates, or a lack of trust in the automated method. In this study we aim to find a solution that will make computer assisted detection more efficient than conventional methods, while preserving the detection certainty of a manual search. Methods Our solution consists of two phases. First, a detection phase finds all events similar to epileptiform activity by using a large database of template waveforms. Individual template detections are combined to form “IED nominations”, each with a corresponding certainty value based on the reliability of their contributing templates. The second phase uses the ten nominations with highest certainty and presents them to the reviewer one by one for confirmation. Confirmations are used to update certainty values of the remaining nominations, and another iteration is performed where ten nominations with the highest certainty are presented. This continues until the reviewer is satisfied with what has been seen. Reviewer feedback is also used to update template accuracies globally and improve future detections. Key Findings Using the described method and fifteen evaluation EEGs (241 IEDs), one third of all inter-ictal events were shown after one iteration, half after two iterations, and 74%, 90%, and 95% after 5, 10 and 15 iterations respectively. Reviewing fifteen iterations for the 20–30 min recordings 1took approximately 5 min. Significance The proposed method shows a practical approach for combining automated detection with visual searching for inter-ictal epileptiform activity. Further evaluation is needed to verify its clinical feasibility and measure the added value it presents. PMID:24454813

Rhythmic EEG patterns in extremely preterm infants: Classification and association with brain injury and outcome.

PubMed

Weeke, Lauren C; van Ooijen, Inge M; Groenendaal, Floris; van Huffelen, Alexander C; van Haastert, Ingrid C; van Stam, Carolien; Benders, Manon J; Toet, Mona C; Hellström-Westas, Lena; de Vries, Linda S

2017-12-01

Classify rhythmic EEG patterns in extremely preterm infants and relate these to brain injury and outcome. Retrospective analysis of 77 infants born <28 weeks gestational age (GA) who had a 2-channel EEG during the first 72 h after birth. Patterns detected by the BrainZ seizure detection algorithm were categorized: ictal discharges, periodic epileptiform discharges (PEDs) and other waveforms. Brain injury was assessed with sequential cranial ultrasound (cUS) and MRI at term-equivalent age. Neurodevelopmental outcome was assessed with the BSITD-III (2 years) and WPPSI-III-NL (5 years). Rhythmic patterns were observed in 62.3% (ictal 1.3%, PEDs 44%, other waveforms 86.3%) with multiple patterns in 36.4%. Ictal discharges were only observed in one and excluded from further analyses. The EEG location of the other waveforms (p<0.05), but not PEDs (p=0.238), was significantly associated with head position. No relation was found between the median total duration of each pattern and injury on cUS and MRI or cognition at 2 and 5 years. Clear ictal discharges are rare in extremely preterm infants. PEDs are common but their significance is unclear. Rhythmic waveforms related to head position are likely artefacts. Rhythmic EEG patterns may have a different significance in extremely preterm infants. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Video/EEG aspects of early-infantile epileptic encephalopathy with suppression-bursts (Ohtahara syndrome).

PubMed

Fusco, L; Pachatz, C; Di Capua, M; Vigevano, F

2001-11-01

Early-infantile epileptic encephalopathy (EIEE) with suppression-bursts is a severe neonatal epileptic encephalopathy. The etiology is multiple, with cerebral malformations as the more frequent. We review the clinical and video/EEG aspects of eight infants with EIEE. These infants, aged between 4 and 70 days at the time of video/EEG recordings, were studied in relation to their clinical and video/EEG characteristics, evolution, persistence of suppression-burst pattern and etiology. Seven of the eight infants showed an ictal clinical sign correlated to the burst of the suppression-burst pattern, four of whom died within 11 months of age. The other three are alive. One, now aged 4 years, underwent surgery for hemimegalencephaly and is seizure-free, with good neurological outcome. One, now aged 9 months, was pyridoxine-dependent and she is seizure-free, and with normal neurological evolution under pyridoxine therapy. One, now aged 3 years and 9 months, is seizure-free, but with severe neurological and cognitive impairment. The only child who did not show a clinical ictal correlation of burst is also alive, now aged 3 years and 9 months, with drug-resistant epilepsy, and severe neurological and cognitive deficits. With regard to the etiology, three showed structural abnormalities, two more showed some signs of prenatal origin of neurological disease, and three had metabolic etiology. Our study confirms that EIEE is a severe age-dependent early epileptic encephalopathy. The etiology is mostly malformative. The prognosis is poor regarding motor and cognitive development, seizures, as well as life expectancies. The presence of an ictal burst of the suppression-burst pattern usually correlates with a negative outcome.

Orgasm-induced seizures: male studied with ictal electroencephalography.

PubMed

Sengupta, Anshuman; Mahmoud, Ali; Tun, Shwe Z; Goulding, Peter

2010-06-01

Reflex seizures can occur in response to a variety of stimuli, both sensory and emotional. Common triggers include light and music; however, in a growing number of case reports, the phenomenon of sexual activity triggering epileptic seizures is described. The majority of these case reports have been in women so far, and most have been found to localise to the right cerebral hemisphere on interictal electroencephalography (EEG). We report the case of a 34-year-old male with orgasm-induced seizures, recorded on ictal EEG. This gentleman's electrophysiology localised his seizure focus to the left cerebral hemisphere, making his case atypical in comparison with the majority of previous reports. Orgasm-induced seizures are an increasingly well-described phenomenon and we suggest that this should be taken into account when assessing patients with possible reflex seizures. Copyright 2010 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Epileptic seizure detection from EEG signals with phase-amplitude cross-frequency coupling and support vector machine

NASA Astrophysics Data System (ADS)

Liu, Yang; Wang, Jiang; Cai, Lihui; Chen, Yingyuan; Qin, Yingmei

2018-03-01

As a pattern of cross-frequency coupling (CFC), phase-amplitude coupling (PAC) depicts the interaction between the phase and amplitude of distinct frequency bands from the same signal, and has been proved to be closely related to the brain’s cognitive and memory activities. This work utilized PAC and support vector machine (SVM) classifier to identify the epileptic seizures from electroencephalogram (EEG) data. The entropy-based modulation index (MI) matrixes are used to express the strength of PAC, from which we extracted features as the input for classifier. Based on the Bonn database, which contains five datasets of EEG segments obtained from healthy volunteers and epileptic subjects, a 100% classification accuracy is achieved for identifying seizure ictal from healthy data, and an accuracy of 97.67% is reached in the classification of ictal EEG signals from inter-ictal EEGs. Based on the CHB-MIT database which is a group of continuously recorded epileptic EEGs by scalp electrodes, a 97.50% classification accuracy is obtained and a raising sign of MI value is found at 6s before seizure onset. The classification performance in this work is effective, and PAC can be considered as a useful tool for detecting and predicting the epileptic seizures and providing reference for clinical diagnosis.

A Novel Signal Modeling Approach for Classification of Seizure and Seizure-Free EEG Signals.

PubMed

Gupta, Anubha; Singh, Pushpendra; Karlekar, Mandar

2018-05-01

This paper presents a signal modeling-based new methodology of automatic seizure detection in EEG signals. The proposed method consists of three stages. First, a multirate filterbank structure is proposed that is constructed using the basis vectors of discrete cosine transform. The proposed filterbank decomposes EEG signals into its respective brain rhythms: delta, theta, alpha, beta, and gamma. Second, these brain rhythms are statistically modeled with the class of self-similar Gaussian random processes, namely, fractional Brownian motion and fractional Gaussian noises. The statistics of these processes are modeled using a single parameter called the Hurst exponent. In the last stage, the value of Hurst exponent and autoregressive moving average parameters are used as features to design a binary support vector machine classifier to classify pre-ictal, inter-ictal (epileptic with seizure free interval), and ictal (seizure) EEG segments. The performance of the classifier is assessed via extensive analysis on two widely used data set and is observed to provide good accuracy on both the data set. Thus, this paper proposes a novel signal model for EEG data that best captures the attributes of these signals and hence, allows to boost the classification accuracy of seizure and seizure-free epochs.

The cortical focus in childhood absence epilepsy; evidence from nonlinear analysis of scalp EEG recordings.

PubMed

Sarrigiannis, Ptolemaios G; Zhao, Yifan; He, Fei; Billings, Stephen A; Baster, Kathleen; Rittey, Chris; Yianni, John; Zis, Panagiotis; Wei, Hualiang; Hadjivassiliou, Marios; Grünewald, Richard

2018-03-01

To determine the origin and dynamic characteristics of the generalised hyper-synchronous spike and wave (SW) discharges in childhood absence epilepsy (CAE). We applied nonlinear methods, the error reduction ratio (ERR) causality test and cross-frequency analysis, with a nonlinear autoregressive exogenous (NARX) model, to electroencephalograms (EEGs) from CAE, selected with stringent electro-clinical criteria (17 cases, 42 absences). We analysed the pre-ictal and ictal strength of association between homologous and heterologous EEG derivations and estimated the direction of synchronisation and corresponding time lags. A frontal/fronto-central onset of the absences is detected in 13 of the 17 cases with the highest ictal strength of association between homologous frontal followed by centro-temporal and fronto-central areas. Delays consistently in excess of 4 ms occur at the very onset between these regions, swiftly followed by the emergence of "isochronous" (0-2 ms) synchronisation but dynamic time lag changes occur during SW discharges. In absences an initial cortico-cortical spread leads to dynamic lag changes to include periods of isochronous interhemispheric synchronisation, which we hypothesize is mediated by the thalamus. Absences from CAE show ictal epileptic network dynamics remarkably similar to those observed in WAG/Rij rats which guided the formulation of the cortical focus theory. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Peri-ictal ECG changes in childhood epilepsy: implications for detection systems.

PubMed

Jansen, Katrien; Varon, Carolina; Van Huffel, Sabine; Lagae, Lieven

2013-10-01

Early detection of seizures could reduce associated morbidity and mortality and improve the quality of life of patients with epilepsy. In this study, the aim was to investigate whether ictal tachycardia is present in focal and generalized epileptic seizures in children. We sought to predict in which type of seizures tachycardia can be identified before actual seizure onset. Electrocardiogram segments in 80 seizures were analyzed in time and frequency domains before and after the onset of epileptic seizures on EEG. These ECG parameters were analyzed to find the most informative ones that can be used for seizure detection. The algorithm of Leutmezer et al. was used to find the temporal relationship between the change in heart rate and seizure onset. In the time domain, the mean RR shows a significant difference before compared to after onset of the seizure in focal seizures. This can be observed in temporal lobe seizures as well as frontal lobe seizures. Calculation of mean RR interval has a high specificity for detection of ictal heart rate changes. Preictal heart rate changes are observed in 70% of the partial seizures. Ictal heart rate changes are present only in partial seizures in this childhood epilepsy study. The changes can be observed in temporal lobe seizures as well as in frontal lobe seizures. Heart rate changes precede seizure onset in 70% of the focal seizures, making seizure detection and closed-loop systems a possible therapeutic alternative in the population of children with refractory epilepsy. © 2013.

Peri-ictal water drinking: a rare automatic behaviour in temporal lobe epilepsy.

PubMed

Pietrafusa, Nicola; Trivisano, Marina; de Palma, Luca; Serino, Domenico; Moavero, Romina; Benvenga, Antonella; Cappelletti, Simona; Boero, Giovanni; Vigevano, Federico; La Neve, Angela; Specchio, Nicola

2015-12-01

Peri-ictal water drinking (PIWD) has been reported as the action of drinking during or within two minutes of an electroclinical seizure. It is considered a peri-ictal vegetative symptom, evident both during childhood and adulthood epilepsy. The aim of this paper was to describe the clinical and electroencephalographic features of two new adult subjects suffering from symptomatic temporal lobe epilepsy with episodes of PIWD recorded by VIDEO-EEG and to review literature data in order to better define this peculiar event during seizures, a rare and probably underestimated semiological sign. To date, 51 cases with focal epilepsy and seizures associated with PIWD have been reported. All patients presented with temporal lobe epilepsy. All cases but one had symptomatic epilepsy. Most of the patients had an involvement of the right hemisphere. Water drinking was reported as an ictal sign in the majority of patients, and less frequently was reported as postictal. We believe that PIWD might be considered a rare automatic behaviour, like other automatisms. Automatisms are more frequently described in patients with temporal lobe epilepsy. PIWD was reported also to have lateralizing significance in the non-dominant temporal lobe, however, because of its rarity, this finding remains unclear.

Ictal semiology in hippocampal versus extrahippocampal temporal lobe epilepsy.

PubMed

Gil-Nagel, A; Risinger, M W

1997-01-01

We have analysed retrospectively the clinical features and electroencephalograms in 35 patients with complex partial seizures of temporal lobe origin who were seizure-free after epilepsy surgery. Two groups were differentiated for statistical analysis: 16 patients had hippocampal temporal lobe seizures (HTS) and 19 patients had extrahippocampal temporal lobe seizures (ETS) associated with a small tumour of the lateral or inferior temporal cortex. All patients in the HTS group had ictal onset verified with intracranial recordings (depth or subdural electrodes). In the ETS group, extrahippocampal onset was verified with intracranial recordings in eight patients and assumed, because of failure of a previous amygdalohippocampectomy, in one patient. Historical information, ictal semiology and ictal EEG of typical seizures were analysed in each patient. The occurrence of early and late oral automatisms and dystonic posturing of an upper extremity was analysed separately. A prior history of febrile convulsions was obtained in 13 HTS patients (81.3%) but in none with ETS (P < 0.0001, Fisher's exact test). An epigastric aura preceded seizures in five patients with HTS (31.3%) and none with ETS (P = 0.0135, Fisher's exact test), while an aura with experiential content was recalled by nine patients with ETS (47.4%) and none with HTS (P = 0.0015), Fisher's exact test). Early oral automatisms occurred in 11 patients with HTS (68.8%) and in two with ETS (10.5%) (P = 0.0005, Fisher's exact test). Early motor involvement of the contralateral upper extremity without oral automatisms occurred in three patients with HTS (18.8%) and in 10 with ETS (52.6%) (P = 0.0298, Fisher's exact test). Arrest reaction, vocalization, speech, facial grimace, postictal cough, late oral automatisms and late motor involvement of the contralateral arm and hand occurred with similar frequency in both groups. These observations show that the early clinical features of HTS and ETS are different.

Spatiotemporal source analysis in scalp EEG vs. intracerebral EEG and SPECT: a case study in a 2-year-old child.

PubMed

Aarabi, A; Grebe, R; Berquin, P; Bourel Ponchel, E; Jalin, C; Fohlen, M; Bulteau, C; Delalande, O; Gondry, C; Héberlé, C; Moullart, V; Wallois, F

2012-06-01

This case study aims to demonstrate that spatiotemporal spike discrimination and source analysis are effective to monitor the development of sources of epileptic activity in time and space. Therefore, they can provide clinically useful information allowing a better understanding of the pathophysiology of individual seizures with time- and space-resolved characteristics of successive epileptic states, including interictal, preictal, postictal, and ictal states. High spatial resolution scalp EEGs (HR-EEG) were acquired from a 2-year-old girl with refractory central epilepsy and single-focus seizures as confirmed by intracerebral EEG recordings and ictal single-photon emission computed tomography (SPECT). Evaluation of HR-EEG consists of the following three global steps: (1) creation of the initial head model, (2) automatic spike and seizure detection, and finally (3) source localization. During the source localization phase, epileptic states are determined to allow state-based spike detection and localization of underlying sources for each spike. In a final cluster analysis, localization results are integrated to determine the possible sources of epileptic activity. The results were compared with the cerebral locations identified by intracerebral EEG recordings and SPECT. The results obtained with this approach were concordant with those of MRI, SPECT and distribution of intracerebral potentials. Dipole cluster centres found for spikes in interictal, preictal, ictal and postictal states were situated an average of 6.3mm from the intracerebral contacts with the highest voltage. Both amplitude and shape of spikes change between states. Dispersion of the dipoles was higher in the preictal state than in the postictal state. Two clusters of spikes were identified. The centres of these clusters changed position periodically during the various epileptic states. High-resolution surface EEG evaluated by an advanced algorithmic approach can be used to investigate the

A new epileptic seizure classification based exclusively on ictal semiology.

PubMed

Lüders, H; Acharya, J; Baumgartner, C; Benbadis, S; Bleasel, A; Burgess, R; Dinner, D S; Ebner, A; Foldvary, N; Geller, E; Hamer, H; Holthausen, H; Kotagal, P; Morris, H; Meencke, H J; Noachtar, S; Rosenow, F; Sakamoto, A; Steinhoff, B J; Tuxhorn, I; Wyllie, E

1999-03-01

Historically, seizure semiology was the main feature in the differential diagnosis of epileptic syndromes. With the development of clinical EEG, the definition of electroclinical complexes became an essential tool to define epileptic syndromes, particularly focal epileptic syndromes. Modern advances in diagnostic technology, particularly in neuroimaging and molecular biology, now permit better definitions of epileptic syndromes. At the same time detailed studies showed that there does not necessarily exist a one-to-one relationship between epileptic seizures or electroclinical complexes and epileptic syndromes. These developments call for the reintroduction of an epileptic seizure classification based exclusively on clinical semiology, similar to the seizure classifications which were used by neurologists before the introduction of the modern diagnostic methods. This classification of epileptic seizures should always be complemented by an epileptic syndrome classification based on all the available clinical information (clinical history, neurological exam, ictal semiology, EEG, anatomical and functional neuroimaging, etc.). Such an approach is more consistent with mainstream clinical neurology and would avoid the current confusion between the classification of epileptic seizures (which in the International Seizure Classification is actually a classification of electroclinical complexes) and the classification of epileptic syndromes.

Quantitative EEG analysis of the maturational changes associated with childhood absence epilepsy

NASA Astrophysics Data System (ADS)

Rosso, O. A.; Hyslop, W.; Gerlach, R.; Smith, R. L. L.; Rostas, J. A. P.; Hunter, M.

2005-10-01

This study aimed to examine the background electroencephalography (EEG) in children with childhood absence epilepsy, a condition whose presentation has strong developmental links. EEG hallmarks of absence seizure activity are widely accepted and there is recognition that the bulk of inter-ictal EEG in this group is normal to the naked eye. This multidisciplinary study aimed to use the normalized total wavelet entropy (NTWS) (Signal Processing 83 (2003) 1275) to examine the background EEG of those patients demonstrating absence seizure activity, and compare it with children without absence epilepsy. This calculation can be used to define the degree of order in a system, with higher levels of entropy indicating a more disordered (chaotic) system. Results were subjected to further statistical analyses of significance. Entropy values were calculated for patients versus controls. For all channels combined, patients with absence epilepsy showed (statistically significant) lower entropy values than controls. The size of the difference in entropy values was not uniform, with certain EEG electrodes consistently showing greater differences than others.

Unfavorable surgical outcomes in partial epilepsy with secondary bilateral synchrony: Intracranial electroencephalography study.

PubMed

Sunwoo, Jun-Sang; Byun, Jung-Ick; Moon, Jangsup; Lim, Jung-Ah; Kim, Tae-Joon; Lee, Soon-Tae; Jung, Keun-Hwa; Park, Kyung-Il; Chu, Kon; Kim, Manho; Chung, Chun-Kee; Jung, Ki-Young; Lee, Sang Kun

2016-05-01

Secondary bilateral synchrony (SBS) indicates bilaterally synchronous epileptiform discharges arising from a focal cortical origin. The present study aims to investigate SBS in partial epilepsy with regard to surgical outcomes and intracranial EEG findings. We retrospectively reviewed consecutive patients who underwent epilepsy surgery following extraoperative intracranial electroencephalography (EEG) study from 2008 to 2012. The presence of SBS was determined based upon the results of scalp EEG monitoring performed for presurgical evaluations. We reviewed scalp EEG, neuroimaging, intracranial EEG findings, and surgical outcomes in patients with SBS. We found 12 patients with SBS who were surgically treated for intractable partial epilepsy. Nine (75%) patients had lateralized ictal semiology and only two (16.6%) patients showed localized ictal onset in scalp EEG. Brain MRI showed epileptogenic lesion in three (25%) patients. Intracranial EEG demonstrated that ictal onset zone was widespread or non-localized in six (50%) patients. Low-voltage fast activity was the most common ictal onset EEG pattern. Rapid propagation of ictal onset was noted in 10 (83.3%) patients. Eleven patients underwent resective epilepsy surgery and only two patients (18.2%) achieved seizure-freedom (median follow-up 56 months). MRI-visible brain lesions were associated with favorable outcomes (p=0.024). Patients with SBS, compared to frontal lobe epilepsy without SBS, showed lesser localization in ictal onset EEG (p=0.029) and more rapid propagation during evolution of ictal rhythm (p=0.015). The present results suggested that resective surgery for partial epilepsy with SBS should be decided carefully, especially in case of nonlesional epilepsy. Poor localization and rapid spread of ictal onset were prominent in intracranial EEG, which might contribute to incomplete resection of the epileptogenic zone and poor surgical outcomes. Copyright © 2016 Elsevier B.V. All rights reserved.

Inter-ictal spike detection using a database of smart templates.

PubMed

Lodder, Shaun S; Askamp, Jessica; van Putten, Michel J A M

2013-12-01

Visual analysis of EEG is time consuming and suffers from inter-observer variability. Assisted automated analysis helps by summarizing key aspects for the reviewer and providing consistent feedback. Our objective is to design an accurate and robust system for the detection of inter-ictal epileptiform discharges (IEDs) in scalp EEG. IED Templates are extracted from the raw data of an EEG training set. By construction, the templates are given the ability to learn by searching for other IEDs within the training set using a time-shifted correlation. True and false detections are remembered and classifiers are trained for improving future predictions. During detection, trained templates search for IEDs in the new EEG. Overlapping detections from all templates are grouped and form one IED. Certainty values are added based on the reliability of the templates involved. For evaluation, 2160 templates were used on an evaluation dataset of 15 continuous recordings containing 241 IEDs (0.79/min). Sensitivities up to 0.99 (7.24fp/min) were reached. To reduce false detections, higher certainty thresholds led to a mean sensitivity of 0.90 with 2.36fp/min. By using many templates, this technique is less vulnerable to variations in spike morphology. A certainty value for each detection allows the system to present findings in a more efficient manner and simplifies the review process. Automated spike detection can assist in visual interpretation of the EEG which may lead to faster review times. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Ictal visual hallucinations due to frontal lobe epilepsy in a patient with bipolar disorder☆

PubMed Central

Manfioli, Valeria; Saladini, Marina; Cagnin, Annachiara

2013-01-01

In ictal psychosis with complex visual hallucinations (VHs), widespread functional changes of cortical networks have been suggested. We describe the clinical and EEG findings of a patient with bipolar disorder who manifested complex VHs associated with intense emotional symptoms caused by frontal epileptic seizures. This description highlights the challenges of diagnosing the epileptic nature of new psychotic phenomena in patients with previous psychiatric disorders and shines light into the role of the frontal cortex in the genesis of complex VHs. PMID:25667849

Information theoretic measures of network coordination in high-frequency scalp EEG reveal dynamic patterns associated with seizure termination

PubMed Central

Stamoulis, Catherine; Schomer, Donald L.; Chang, Bernard S.

2013-01-01

How a seizure terminates is still under-studied and, despite its clinical importance, remains an obscure phase of seizure evolution. Recent studies of seizure-related scalp EEGs at frequencies >100 Hz suggest that neural activity, in the form of oscillations and/or neuronal network interactions, may play an important role in preictal/ictal seizure evolution [2, 31]. However, the role of high-frequency activity in seizure termination, is unknown, if it exists at all. Using information theoretic measures of network coordination, this study investigated ictal and immediate postictal neurodynamic interactions encoded in scalp EEGs from a relatively small sample of 8 patients with focal epilepsy and multiple seizures originating in temporal and/or frontal brain regions, at frequencies ≤100 Hz and >100 Hz, respectively. Despite some heterogeneity in the dynamics of these interactions, consistent patterns were also estimated. Specifically, in several seizures, linear or non-linear increase in high-frequency neuronal coordination during ictal intervals, coincided with a corresponding decrease in coordination at frequencies <100 Hz, suggesting a potential interference role of high-frequency activity, to disrupt abnormal ictal synchrony at lower frequencies. These changes in network synchrony started at least 20–30 sec prior to seizure offset, depending on the seizure duration. Opposite patterns were estimated at frequencies ≤100 Hz in several seizures. These results raise the possibility that high-frequency interference may occur in the form of progressive network coordination during the ictal interval, which continues during the postictal interval. This may be one of several possible mechanisms that facilitate seizure termination. In fact, inhibition of pairwise interactions between EEGs by other signals in their spatial neighborhood, quantified by negative interaction information, was estimated at frequencies ≤100 Hz, at least in some seizures. PMID:23608198

Information theoretic measures of network coordination in high-frequency scalp EEG reveal dynamic patterns associated with seizure termination.

PubMed

Stamoulis, Catherine; Schomer, Donald L; Chang, Bernard S

2013-08-01

How a seizure terminates is still under-studied and, despite its clinical importance, remains an obscure phase of seizure evolution. Recent studies of seizure-related scalp EEGs at frequencies >100 Hz suggest that neural activity, in the form of oscillations and/or neuronal network interactions, may play an important role in preictal/ictal seizure evolution (Andrade-Valenca et al., 2011; Stamoulis et al., 2012). However, the role of high-frequency activity in seizure termination, is unknown, if it exists at all. Using information theoretic measures of network coordination, this study investigated ictal and immediate postictal neurodynamic interactions encoded in scalp EEGs from a relatively small sample of 8 patients with focal epilepsy and multiple seizures originating in temporal and/or frontal brain regions, at frequencies ≤ 100 Hz and >100 Hz, respectively. Despite some heterogeneity in the dynamics of these interactions, consistent patterns were also estimated. Specifically, in several seizures, linear or non-linear increase in high-frequency neuronal coordination during ictal intervals, coincided with a corresponding decrease in coordination at frequencies <100 Hz, suggesting a potential interference role of high-frequency activity, to disrupt abnormal ictal synchrony at lower frequencies. These changes in network synchrony started at least 20-30s prior to seizure offset, depending on the seizure duration. Opposite patterns were estimated at frequencies ≤ 100 Hz in several seizures. These results raise the possibility that high-frequency interference may occur in the form of progressive network coordination during the ictal interval, which continues during the postictal interval. This may be one of several possible mechanisms that facilitate seizure termination. In fact, inhibition of pairwise interactions between EEGs by other signals in their spatial neighborhood, quantified by negative interaction information, was estimated at frequencies ≤ 100 Hz

Localizing and lateralizing value of ictal flatulence.

PubMed

Strzelczyk, Adam; Nowak, Mareike; Bauer, Sebastian; Reif, Philipp S; Oertel, Wolfgang H; Knake, Susanne; Hamer, Hajo M; Rosenow, Felix

2010-02-01

Autonomic seizures have been associated with seizure onset in the temporal or insular lobe and consist of variations in blood pressure and heart rate, sweating, flushing, piloerection, hypersalivation, vomiting, spitting, and alterations in bladder and bowel functions. The aim of this study was to evaluate the localizing and lateralizing value of ictal flatulence. Medical records of patients with focal epilepsies who were monitored at the Interdisciplinary Epilepsy Center Marburg between 2006 and 2009 were reviewed for the occurrence of ictal flatulence. Clinical, electrophysiological, and imaging data were reviewed and compared with data for previously reported cases of ictal flatulence. Two patients with ictal flatulence were identified (0.6%). In both patients, ictal flatulence was associated with a seizure pattern in the temporal lobe of the dominant hemisphere. Our cases and previously reported cases point toward activation of insular cortex because of such additional autonomic symptoms as unilateral piloerection, tachycardia, profound sweating, and flushing of the face. Ictal flatulence is a rare manifestation of autonomic seizures and a localizing sign for temporal or/and insular lobe epilepsies. In general, ictal flatulence seems to have no lateralizing value. (c) 2009 Elsevier Inc. All rights reserved.

Prognostic value of electroencephalography (EEG) for brain injury after cardiopulmonary resuscitation.

PubMed

Feng, Guibo; Jiang, Guohui; Li, Zhiwei; Wang, Xuefeng

2016-06-01

Cardiac arrest (CA) patients can experience neurological sequelae or even death after successful cardiopulmonary resuscitation (CPR) due to cerebral hypoxia- and ischemia-reperfusion-mediated brain injury. Thus, it is important to perform early prognostic evaluations in CA patients. Electroencephalography (EEG) is an important tool for determining the prognosis of hypoxic-ischemic encephalopathy due to its real-time measurement of brain function. Based on EEG, burst suppression, a burst suppression ratio >0.239, periodic discharges, status epilepticus, stimulus-induced rhythmic, periodic or ictal discharges, non-reactive EEG, and the BIS value based on quantitative EEG may be associated with the prognosis of CA after successful CPR. As measures of neural network integrity, the values of small-world characteristics of the neural network derived from EEG patterns have potential applications.

Beyond the double banana: improved recognition of temporal lobe seizures in long-term EEG.

PubMed

Rosenzweig, Ivana; Fogarasi, András; Johnsen, Birger; Alving, Jørgen; Fabricius, Martin Ejler; Scherg, Michael; Neufeld, Miri Y; Pressler, Ronit; Kjaer, Troels W; van Emde Boas, Walter; Beniczky, Sándor

2014-02-01

To investigate whether extending the 10-20 array with 6 electrodes in the inferior temporal chain and constructing computed montages increases the diagnostic value of ictal EEG activity originating in the temporal lobe. In addition, the accuracy of computer-assisted spectral source analysis was investigated. Forty EEG samples were reviewed by 7 EEG experts in various montages (longitudinal and transversal bipolar, common average, source derivation, source montage, current source density, and reference-free montages) using 2 electrode arrays (10-20 and the extended one). Spectral source analysis used source montage to calculate density spectral array, defining the earliest oscillatory onset. From this, phase maps were calculated for localization. The reference standard was the decision of the multidisciplinary epilepsy surgery team on the seizure onset zone. Clinical performance was compared with the double banana (longitudinal bipolar montage, 10-20 array). Adding the inferior temporal electrode chain, computed montages (reference free, common average, and source derivation), and voltage maps significantly increased the sensitivity. Phase maps had the highest sensitivity and identified ictal activity at earlier time-point than visual inspection. There was no significant difference concerning specificity. The findings advocate for the use of these digital EEG technology-derived analysis methods in clinical practice.

Ictal autoscopic phenomena and near death experiences: a study of five patients with ictal autoscopies.

PubMed

Hoepner, Robert; Labudda, Kirsten; May, Theodor W; Schoendienst, Martin; Woermann, Friedrich G; Bien, Christian G; Brandt, Christian

2013-03-01

Autoscopic phenomena in general may-among other conditions-occur during epileptic seizures and near death experiences. We set the hypothesis that ictal autoscopic phenomena and near death experiences have a similar semiology as measured by the Near Death Experience Questionnaire. We also investigated whether patients with aura before temporal lobe seizures with or without autoscopic phenomena could be distinguished by this questionnaire. For these purposes, we examined five patients with ictal autoscopy and 12 patients with aura before temporal lobe seizures without ictal autoscopy as controls. We used a cut-off of 7 points or higher on the Near Death Experience Questionnaire for indicating the semiology of a near death experience and for distinguishing patients with ictal autoscopy from controls. This cut-off separated patients with ictal autoscopic phenomena from aura before temporal lobe seizures without autoscopy (p = 0.0002, two-sided, exact Fisher's Test; specificity: 100 % [CI95 % 77.9 and 100 %], sensitivity: 100 % [CI95 % 54.9 and 100 %]). Furthermore, all autoscopic patients (range 7-10) and none of the controls (range 0-5) had scores of 7 points or higher. Thus, the individual experiences during simple partial autoscopic seizures and near death experiences are similar, at least in some prominent aspects. These findings might be of particular interest for the pathophysiology of near death experiences, as all patients with ictal autoscopic phenomena had an epileptic dysfunction at the temporo-parietal junction or its neighboring regions. Therefore, a malfunction of this brain region might also be involved in near death experiences of other origins especially during states which could cause a near death experience and a cerebral excitability.

Interrater agreement in visual scoring of neonatal seizures based on majority voting on a web-based system: The Neoguard EEG database.

PubMed

Dereymaeker, Anneleen; Ansari, Amir H; Jansen, Katrien; Cherian, Perumpillichira J; Vervisch, Jan; Govaert, Paul; De Wispelaere, Leen; Dielman, Charlotte; Matic, Vladimir; Dorado, Alexander Caicedo; De Vos, Maarten; Van Huffel, Sabine; Naulaers, Gunnar

2017-09-01

To assess interrater agreement based on majority voting in visual scoring of neonatal seizures. An online platform was designed based on a multicentre seizure EEG-database. Consensus decision based on 'majority voting' and interrater agreement was estimated using Fleiss' Kappa. The influences of different factors on agreement were determined. 1919 Events extracted from 280h EEG of 71 neonates were reviewed by 4 raters. Majority voting was applied to assign a seizure/non-seizure classification. 44% of events were classified with high, 36% with moderate, and 20% with poor agreement, resulting in a Kappa value of 0.39. 68% of events were labelled as seizures, and in 46%, all raters were convinced about electrographic seizures. The most common seizure duration was <30s. Raters agreed best for seizures lasting 60-120s. There was a significant difference in electrographic characteristics of seizures versus dubious events, with seizures having longer duration, higher power and amplitude. There is a wide variability in identifying rhythmic ictal and non-ictal EEG events, and only the most robust ictal patterns are consistently agreed upon. Database composition and electrographic characteristics are important factors that influence interrater agreement. The use of well-described databases and input of different experts will improve neonatal EEG interpretation and help to develop uniform seizure definitions, useful for evidence-based studies of seizure recognition and management. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Application of recurrence quantification analysis for the automated identification of epileptic EEG signals.

PubMed

Acharya, U Rajendra; Sree, S Vinitha; Chattopadhyay, Subhagata; Yu, Wenwei; Ang, Peng Chuan Alvin

2011-06-01

Epilepsy is a common neurological disorder that is characterized by the recurrence of seizures. Electroencephalogram (EEG) signals are widely used to diagnose seizures. Because of the non-linear and dynamic nature of the EEG signals, it is difficult to effectively decipher the subtle changes in these signals by visual inspection and by using linear techniques. Therefore, non-linear methods are being researched to analyze the EEG signals. In this work, we use the recorded EEG signals in Recurrence Plots (RP), and extract Recurrence Quantification Analysis (RQA) parameters from the RP in order to classify the EEG signals into normal, ictal, and interictal classes. Recurrence Plot (RP) is a graph that shows all the times at which a state of the dynamical system recurs. Studies have reported significantly different RQA parameters for the three classes. However, more studies are needed to develop classifiers that use these promising features and present good classification accuracy in differentiating the three types of EEG segments. Therefore, in this work, we have used ten RQA parameters to quantify the important features in the EEG signals.These features were fed to seven different classifiers: Support vector machine (SVM), Gaussian Mixture Model (GMM), Fuzzy Sugeno Classifier, K-Nearest Neighbor (KNN), Naive Bayes Classifier (NBC), Decision Tree (DT), and Radial Basis Probabilistic Neural Network (RBPNN). Our results show that the SVM classifier was able to identify the EEG class with an average efficiency of 95.6%, sensitivity and specificity of 98.9% and 97.8%, respectively.

Ictal electroencephalograms in neonatal seizures: characteristics and associations.

PubMed

Nagarajan, Lakshmi; Ghosh, Soumya; Palumbo, Linda

2011-07-01

The characteristics of ictal electroencephalograms in 160 neonatal seizures of 43 babies were correlated with mortality and neurodevelopmental outcomes. Neonatal seizures are focal at onset, most frequently temporal, and often occur during sleep. Twenty-one percent of babies with seizures died, and 76% of survivors manifested neurodevelopmental impairment during 2-6-year follow-up. A low-amplitude ictal electroencephalogram discharge was associated with increased mortality, and a frequency of <2 Hz with increased morbidity. Status epilepticus, ictal fractions, multiple foci, and bihemispheric involvement did not influence outcomes. Of 160 seizures, 99 exhibited no associated clinical features (electrographic seizures). Neonatal seizures with clinical correlates (electroclinical seizures) exhibited a higher amplitude and frequency of ictal electroencephalogram discharge than electrographic seizures. During electroclinical seizures, the ictal electroencephalogram was more likely to involve larger areas of the brain and to cross the midline. Mortality and morbidity were similar in babies with electroclinical and electrographic seizures, emphasizing the need to diagnose and treat both types. Ictal electroencephalogram topography has implications for electrode application during limited-channel, amplitude-integrated electroencephalograms. We recommend temporal and paracentral electrodes. Video electroencephalograms are important in diagnosing neonatal seizures and providing useful information regarding ictal electroencephalogram characteristics. Copyright © 2011 Elsevier Inc. All rights reserved.

Neural network underlying ictal pouting ("chapeau de gendarme") in frontal lobe epilepsy.

PubMed

Souirti, Zouhayr; Landré, Elisabeth; Mellerio, Charles; Devaux, Bertrand; Chassoux, Francine

2014-08-01

In order to determine the anatomical neural network underlying ictal pouting (IP), with the mouth turned down like a "chapeau de gendarme", in frontal lobe epilepsy (FLE), we reviewed the video-EEG recordings of 36 patients with FLE who became seizure-free after surgery. We selected the cases presenting IP, defined as a symmetrical and sustained (>5s) lowering of labial commissures with contraction of chin, mimicking an expression of fear, disgust, or menace. Ictal pouting was identified in 11 patients (8 males; 16-48 years old). We analyzed the clinical semiology, imaging, and electrophysiological data associated with IP, including FDG-PET in 10 and SEEG in 9 cases. In 37 analyzed seizures (2-7/patient), IP was an early symptom, occurring during the first 10s in 9 cases. The main associated features consisted of fear, anguish, vegetative disturbances, behavioral disorders (sudden agitation, insults, and fighting), tonic posturing, and complex motor activities. The epileptogenic zone assessed by SEEG involved the mesial frontal areas, especially the anterior cingulate cortex (ACC) in 8 patients, whereas lateral frontal onset with an early spread to the ACC was seen in the other patient. Ictal pouting associated with emotional changes and hypermotor behavior had high localizing value for rostroventral "affective" ACC, whereas less intense facial expressions were related to the dorsal "cognitive" ACC. Fluorodeoxyglucose positron emission tomography demonstrated the involvement of both the ACC and lateral cortex including the anterior insula in all cases. We propose that IP is sustained by reciprocal mesial and lateral frontal interactions involved in emotional and cognitive processes, in which the ACC plays a pivotal role. Copyright © 2014 Elsevier Inc. All rights reserved.

Three-dimensional intracranial EEG monitoring in presurgical assessment of MRI-negative frontal lobe epilepsy

PubMed Central

Yang, Peng-Fan; Shang, Ming-Chao; Lin, Qiao; Xiao, Hui; Mei, Zhen; Jia, Yan-Zeng; Liu, Wei; Zhong, Zhong-Hui

2016-01-01

Abstract Magnetic resonance imaging (MRI)-negative epilepsy is associated with poor clinical outcomes prognosis. The present study was aimed to assess whether intracranial 3D interictal and ictal electroencephalography (EEG) findings, a combination of EEG at a different depth, in addition to clinical, scalp EEG, and positron emission tomography–computed tomography (PETCT) data help to predict outcome in a series of patients with MRI-negative frontal lobe epilepsy (FLE) after surgery. Patients with MRI-negative FLE who were presurgically evaluated by 3D-intracranial EEG (3D-iEEG) recording were included. Outcome predictors were compared in patients with seizure freedom (group 1) and those with recurrent seizures (group 2) at least 24 months after surgery. Forty-seven patients (15 female) were included in this study. MRI was found normal in 38 patients, whereas a focal or regional hypometabolism was observed in 33 cases. Twenty-three patients (48.9%) were seizure-free (Engel class I), and 24 patients (51.1%) continued to have seizures (12 were class II, 7 were class III, and 5 were class IV). Detailed analysis of intracranial EEG revealed widespread (>2 cm) (17.4%:75%; P = 0.01) in contrast to focal seizure onset as well as shorter latency to onset of seizure spread (5.9 ± 7.1 s; 1.4 ± 2.9 s; P = 0.016) and to ictal involvement of brain structures beyond the frontal lobe (21.8 ± 20.3 s; 4.9 ± 5.1 s; P = 0.025) in patients without seizure freedom. The results suggest that presurgical evaluation using 3D-iEEG monitoring lead to a better surgical outcome as seizure free in MRI-negative FLE patients. PMID:27977572

Ictal SPECT in a case of pure musicogenic epilepsy.

PubMed

Gelisse, Philippe; Thomas, Pierre; Padovani, Raymond; Hassan-Sebbag, Nathalie; Pasquier, Jacques; Genton, Pierre

2003-09-01

A 39-year-old, right-handed woman had seizures for two years which were always triggered by exposure to various types of music: the first occurred while she listened to a tune she particularly liked, Con Te Partiro, by Andrea Boccelli. Other triggering factors were various types of music such as supermarket background music and polyphonic singing or instrumental music played by family members. The seizures had a stereotyped course: she felt anxious, tearful, then occurred slight obtundation, during which she smacked her lips and moved restlessly. There was no complete loss of consciousness, but some degree of amnesia. She never experienced a generalized tonic-clonic seizure, but reported rare spontaneous feelings of déjà-vu that had begun at the same time as the induced seizures. There were no other spontaneous attacks; only one seizure was apparently provoked, not by music but by a loud background noise in her office. She was a music lover and a singer. Interictal EEG showed independent slow waves over the temporal regions. Several seizures with EEG localisation over the right temporal region were elicited after several minutes of exposure to music. Monoauricular stimulation with the same music produced a seizure when applied to the left ear but was ineffective when applied to the right ear. Ictal SPECT demonstrated right temporal hyperperfusion. MRI was normal. On high dose of carbamazepine, seizure frequency decreased. The addition of topiramate resulted in full seizure control. Musicogenic epilepsy is a rare form of reflex epilepsy. Pure cases, when patients do not experience unprovoked seizures, are exceptional. Our report confirms the implication of the right temporal lobe in this epilepsy. Copyright John Libbey Eurotext 2003

Stimulus-induced rhythmic, periodic, or ictal discharges (SIRPIDs): an intriguing EEG phenomenon.

PubMed

Silveira, Mariana Ribeiro Marcondes da; Andrade, Joaquina; Garzon, Eliana

2013-12-01

SIRPIDs, an acronym for stimulus-induced rhythmic, periodic, or ictal discharges, were first named in 2004. This is a pattern observed in continuous electroencephalogram (CEEG) consistently elicited by stimulation in comatose patients. The pathophysiology of SIRPIDs probably involves dysregulation of subcortico-cortical projections, particularly thalamocortical circuit, in a markedly abnormal brain with hyperexci-table cortex. This may explain some studies found an association of prolonged periodic epileptiform discharges (PEDs) activity and a higher incidence of concurrent electrographic seizures and SIRPIDs. An association of SIRPIDs and poor prognosis has already been described. However, it is not yet possible to assert whether these discharges can cause neuronal injury or if they are simply a marker of severe brain injury. Objective of this paper is to review clinical relevance and pathophysiology of SIRPIDs, as well as its role as a brain response in the critically ill patient.

MEG-EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy.

PubMed

Chowdhury, Rasheda Arman; Zerouali, Younes; Hedrich, Tanguy; Heers, Marcel; Kobayashi, Eliane; Lina, Jean-Marc; Grova, Christophe

2015-11-01

The purpose of this study is to develop and quantitatively assess whether fusion of EEG and MEG (MEEG) data within the maximum entropy on the mean (MEM) framework increases the spatial accuracy of source localization, by yielding better recovery of the spatial extent and propagation pathway of the underlying generators of inter-ictal epileptic discharges (IEDs). The key element in this study is the integration of the complementary information from EEG and MEG data within the MEM framework. MEEG was compared with EEG and MEG when localizing single transient IEDs. The fusion approach was evaluated using realistic simulation models involving one or two spatially extended sources mimicking propagation patterns of IEDs. We also assessed the impact of the number of EEG electrodes required for an efficient EEG-MEG fusion. MEM was compared with minimum norm estimate, dynamic statistical parametric mapping, and standardized low-resolution electromagnetic tomography. The fusion approach was finally assessed on real epileptic data recorded from two patients showing IEDs simultaneously in EEG and MEG. Overall the localization of MEEG data using MEM provided better recovery of the source spatial extent, more sensitivity to the source depth and more accurate detection of the onset and propagation of IEDs than EEG or MEG alone. MEM was more accurate than the other methods. MEEG proved more robust than EEG and MEG for single IED localization in low signal-to-noise ratio conditions. We also showed that only few EEG electrodes are required to bring additional relevant information to MEG during MEM fusion.

Magnetoencephalography and ictal SPECT in patients with failed epilepsy surgery.

PubMed

El Tahry, Riёm; Wang, Z Irene; Thandar, Aung; Podkorytova, Irina; Krishnan, Balu; Tousseyn, Simon; Guiyun, Wu; Burgess, Richard C; Alexopoulos, Andreas V

2018-06-06

Selected patients with intractable focal epilepsy who have failed a previous epilepsy surgery can become seizure-free with reoperation. Preoperative evaluation is exceedingly challenging in this cohort. We aim to investigate the diagnostic value of two noninvasive approaches, magnetoencephalography (MEG) and ictal single-photon emission computed tomography (SPECT), in patients with failed epilepsy surgery. We retrospectively included a consecutive cohort of patients who failed prior resective epilepsy surgery, underwent re-evaluation including MEG and ictal SPECT, and had another surgery after the re-evaluation. The relationship between resection and localization from each test was determined, and their association with seizure outcomes was analyzed. A total of 46 patients were included; 21 (46%) were seizure-free at 1-year followup after reoperation. Twenty-seven (58%) had a positive MEG and 31 (67%) had a positive ictal SPECT. The resection of MEG foci was significantly associated with seizure-free outcome (p = 0.002). Overlap of ictal SPECT hyperperfusion zones with resection was significantly associated with seizure-free outcome in the subgroup of patients with injection time ≤20 seconds(p = 0.03), but did not show significant association in the overall cohort (p = 0.46) although all injections were ictal. Patients whose MEG and ictal SPECT were concordant on a sublobar level had a significantly higher chance of seizure freedom (p = 0.05). MEG alone achieved successful localization in patients with failed epilepsy surgery with a statistical significance. Only ictal SPECT with early injection (≤20 seconds) had good localization value. Sublobar concordance between both tests was significantly associated with seizure freedom. SPECT can provide essential information in MEG-negative cases and vice versa. Our results emphasize the importance of considering a multimodal presurgical evaluation including MEG and SPECT in all patients with a

Intracranial EEG in predicting surgical outcome in frontal lobe epilepsy.

PubMed

Holtkamp, Martin; Sharan, Ashwini; Sperling, Michael R

2012-10-01

Surgery in frontal lobe epilepsy (FLE) has a worse prognosis regarding seizure freedom than anterior lobectomy in temporal lobe epilepsy. The current study aimed to assess whether intracranial interictal and ictal EEG findings in addition to clinical and scalp EEG data help to predict outcome in a series of patients who needed invasive recording for FLE surgery. Patients with FLE who had resective surgery after chronic intracranial EEG recording were included. Outcome predictors were compared in patients with seizure freedom (group 1) and those with recurrent seizures (group 2) at 19-24 months after surgery. Twenty-five patients (16 female) were included in this study. Mean age of patients at epilepsy surgery was 32.3 ± 15.6 years (range 12-70); mean duration of epilepsy was 16.9 ± 13.4 years (range 1-48). In each outcome group, magnetic resonance imaging revealed frontal lobe lesions in three patients. Fifteen patients (60%) were seizure-free (Engel class 1), 10 patients (40%) continued to have seizures (two were class II, three were class III, and five were class IV). Lack of seizure freedom was seen more often in patients with epilepsy surgery on the left frontal lobe (group 1, 13%; group 2, 70%; p = 0.009) and on the dominant (27%; 70%; p = 0.049) hemisphere as well as in patients without aura (29%; 80%; p = 0.036), whereas sex, age at surgery, duration of epilepsy, and presence of an MRI lesion in the frontal lobe or extrafrontal structures were not different between groups. Electroencephalographic characteristics associated with lack of seizure freedom included presence of interictal epileptiform discharges in scalp recordings (31%; 90%; p = 0.01). Detailed analysis of intracranial EEG revealed widespread (>2 cm) (13%; 70%; p = 0.01) in contrast to focal seizure onset as well as shorter latency to onset of seizure spread (5.8 ± 6.1 s; 1.5 ± 2.3 s; p = 0.016) and to ictal involvement of brain structures beyond the frontal lobe (23.5 ± 22.4 s; 5.8 ± 5.4 s

Presence of nonlinearity in intracranial EEG recordings: detected by Lyapunov exponents

NASA Astrophysics Data System (ADS)

Liu, Chang-Chia; Shiau, Deng-Shan; Chaovalitwongse, W. Art; Pardalos, Panos M.; Sackellares, J. C.

2007-11-01

In this communication, we performed nonlinearity analysis in the EEG signals recorded from patients with temporal lobe epilepsy (TLE). The largest Lyapunov exponent (Lmax) and phase randomization surrogate data technique were employed to form the statistical test. EEG recordings were acquired invasively from three patients in six brain regions (left and right temporal depth, sub-temporal and orbitofrontal) with 28-32 depth electrodes placed in depth and subdural of the brain. All three patients in this study have unilateral epileptic focus region on the right hippocampus(RH). Nonlinearity was detected by comparing the Lmax profiles of the EEG recordings to its surrogates. The nonlinearity was seen in all different states of the patient with the highest found in post-ictal state. Further our results for all patients exhibited higher degree of differences, quantified by paired t-test, in Lmax values between original and its surrogate from EEG signals recorded from epileptic focus regions. The results of this study demonstrated the Lmax is capable to capture spatio-temporal dynamics that may not be able to detect by linear measurements in the intracranial EEG recordings.

Postictal aphasia and paresis: a clinical and intracerebral EEG study.

PubMed

Adam, C; Adam, C; Rouleau, I; Saint-Hilaire, J M

2000-02-01

We examined the lateralizing value of postictal language and motor deficits and studied their underlying mechanisms. The total sample consisted of 35 patients (26 temporals, 8 frontals, 1 parietal) with a good postsurgical outcome (Engel's class I and II). Postictal examination was blindly reviewed on videotapes. In 15 cases (29 seizures), postictal language manifestations were analyzed in relation with the diffusion of the epileptic discharge recorded by intracerebral EEG. Language dominance was determined by the intracarotid amobarbital test. Postictal aphasia was observed only when (1) seizure originated in the dominant hemisphere and (2) ictal activity spread to language areas (Wernicke and/or Broca areas). When the epileptic focus was in the nondominant hemisphere, no postictal aphasia was observed even if there was secondary generalization of ictal activity affecting the language areas of the dominant hemisphere. Postictal motor deficits also had a strong lateralizing value even when seizures were secondarily generalized. Postictal aphasia in temporal epilepsies and postical motor deficits in temporal and extra temporal epilepsies provided excellent lateralizing information. Postictal deficits appear to be the result of inhibitory mechanisms induced by previous ictal activity of the structures related to these functions.

Open database of epileptic EEG with MRI and postoperational assessment of foci--a real world verification for the EEG inverse solutions.

PubMed

Zwoliński, Piotr; Roszkowski, Marcin; Zygierewicz, Jaroslaw; Haufe, Stefan; Nolte, Guido; Durka, Piotr J

2010-12-01

This paper introduces a freely accessible database http://eeg.pl/epi , containing 23 datasets from patients diagnosed with and operated on for drug-resistant epilepsy. This was collected as part of the clinical routine at the Warsaw Memorial Child Hospital. Each record contains (1) pre-surgical electroencephalography (EEG) recording (10-20 system) with inter-ictal discharges marked separately by an expert, (2) a full set of magnetic resonance imaging (MRI) scans for calculations of the realistic forward models, (3) structural placement of the epileptogenic zone, recognized by electrocorticography (ECoG) and post-surgical results, plotted on pre-surgical MRI scans in transverse, sagittal and coronal projections, (4) brief clinical description of each case. The main goal of this project is evaluation of possible improvements of localization of epileptic foci from the surface EEG recordings. These datasets offer a unique possibility for evaluating different EEG inverse solutions. We present preliminary results from a subset of these cases, including comparison of different schemes for the EEG inverse solution and preprocessing. We report also a finding which relates to the selective parametrization of single waveforms by multivariate matching pursuit, which is used in the preprocessing for the inverse solutions. It seems to offer a possibility of tracing the spatial evolution of seizures in time.

EEG-confirmed epileptic activity in a cat with VGKC-complex/LGI1 antibody-associated limbic encephalitis.

PubMed

Pakozdy, Akos; Glantschnigg, Ursula; Leschnik, Michael; Hechinger, Harald; Moloney, Teresa; Lang, Bethan; Halasz, Peter; Vincent, Angela

2014-03-01

A 5-year-old, female client-owned cat presented with acute onset of focal epileptic seizures with orofacial twitching and behavioural changes. Magnetic resonance imaging showed bilateral temporal lobe hyperintensities and the EEG was consistent with ictal epileptic seizure activity. After antiepileptic and additional corticosteroid treatment, the cat recovered and by 10 months of follow-up was seizure-free without any problem. Retrospectively, antibodies to LGI1, a component of the voltage-gated potassium channel-complex, were identified. Feline focal seizures with orofacial involvement have been increasingly recognised in client-owned cats, and autoimmune limbic encephalitis was recently suggested as a possible aetiology. This is the first report of EEG, MRI and long-term follow-up of this condition in cats which is similar to human limbic encephalitis.

The long-term course of temporal lobe epilepsy: From unilateral to bilateral interictal epileptiform discharges in repeated video-EEG monitorings.

PubMed

Gollwitzer, Stephanie; Scott, Catherine A; Farrell, Fiona; Bell, Gail S; de Tisi, Jane; Walker, Matthew C; Wehner, Tim; Sander, Josemir W; Hamer, Hajo M; Diehl, Beate

2017-03-01

Bilateral interictal epileptiform discharges (IED) and ictal patterns are common in temporal lobe epilepsy (TLE) and have been associated with decreased chances of seizure freedom after epilepsy surgery. It is unclear whether secondary epileptogenesis, although demonstrated in experimental models, exists in humans and may account for progression of epilepsy. We reviewed consecutive video-EEG recordings from 1992 to 2014 repeated at least two years apart (mean interval 6.14years) in 100 people diagnosed with TLE. Ictal EEG patterns and IED remained restricted to one hemisphere in 36 people (group 1), 46 exhibited bilateral abnormalities from the first recording (group 2), 18 progressed from unilateral to bilateral EEG pathology over time (group 3). No significant differences between the three groups were seen with respect to age at epilepsy onset, duration, or underlying pathology. Extra-temporal IED during the first EEG recording were associated with an increased risk of developing bilateral epileptiform changes over time (hazard ratio 3.67; 95% CI 1.4, 9.4). Our findings provide some support of progression in TLE and raise the possibility of secondary epileptogenesis in humans. The development of an independent contra-lateral epileptogenic focus is known to be associated with a less favorable surgical outcome. We defined reliable EEG markers for an increased risk of progression to more widespread or independent bitemporal epileptogenicity at an early stage, thus allowing for individualized pre-surgical counselling. Copyright © 2016 Elsevier Inc. All rights reserved.

Automatic Seizure Detection Based on Morphological Features Using One-Dimensional Local Binary Pattern on Long-Term EEG.

PubMed

Shanir, P P Muhammed; Khan, Kashif Ahmad; Khan, Yusuf Uzzaman; Farooq, Omar; Adeli, Hojjat

2017-12-01

Epileptic neurological disorder of the brain is widely diagnosed using the electroencephalography (EEG) technique. EEG signals are nonstationary in nature and show abnormal neural activity during the ictal period. Seizures can be identified by analyzing and obtaining features of EEG signal that can detect these abnormal activities. The present work proposes a novel morphological feature extraction technique based on the local binary pattern (LBP) operator. LBP provides a unique decimal value to a sample point by weighing the binary outcomes after thresholding the neighboring samples with the present sample point. These LBP values assist in capturing the rising and falling edges of the EEG signal, thus providing a morphologically featured discriminating pattern for epilepsy detection. In the present work, the variability in the LBP values is measured by calculating the sum of absolute difference of the consecutive LBP values. Interquartile range is calculated over the preprocessed EEG signal to provide dispersion measure in the signal. For classification purpose, K-nearest neighbor classifier is used, and the performance is evaluated on 896.9 hours of data from CHB-MIT continuous EEG database. Mean accuracy of 99.7% and mean specificity of 99.8% is obtained with average false detection rate of 0.47/h and sensitivity of 99.2% for 136 seizures.

Outcomes of patients with altered level of consciousness and abnormal electroencephalogram: A retrospective cohort study

PubMed Central

Ferrari-Marinho, Taissa; Naves, Pedro Vicente Ferreira; Ladeia-Frota, Carol; Caboclo, Luís Otávio

2017-01-01

Introduction Nonconvulsive seizures (NCS) are frequent in hospitalized patients and may further aggravate injury in the already damaged brain, potentially worsening outcomes in encephalopathic patients. Therefore, both early seizure recognition and treatment have been advocated to prevent further neurological damage. Objective Evaluate the main EEG patterns seen in patients with impaired consciousness and address the effect of treatment with antiepileptic drugs (AEDs), continuous intravenous anesthetic drugs (IVADs), or the combination of both, on outcomes. Methods This was a single center retrospective cohort study conducted in a private, tertiary care hospital. Consecutive adult patients with altered consciousness submitted to a routine EEG between January 2008 and February 2011 were included in this study. Based on EEG pattern, patients were assigned to one of three groups: Group Interictal Patterns (IP; EEG showing only interictal epileptiform discharges or triphasic waves), Group Rhythmic and Periodic Patterns (RPP; at least one EEG with rhythmic or periodic patterns), and Group Ictal (Ictal; at least one EEG showing ictal pattern). Groups were compared in terms of administered antiepileptic treatment and frequency of unfavorable outcomes (modified Rankin scale ≥3 and in-hospital mortality). Results Two hundred and six patients (475 EEGs) were included in this analysis. Interictal pattern was observed in 35.4% (73/206) of patients, RPP in 53.4% (110/206) and ictal in 11.2% (23/206) of patients. Treatment with AEDs, IVADs or a combination of both was administered in half of the patients. While all Ictal group patients received treatment (AEDs or IVADs), only 24/73 (32.9%) IP group patients and 55/108 (50.9%) RPP group patients were treated (p<0.001). Hospital length of stay (LOS) and frequency of unfavorable outcomes did not differ among the groups. In-hospital mortality was higher in IVADs treated RPP patients compared to AEDs treated RPP patients [11/19 (57

Outcomes of patients with altered level of consciousness and abnormal electroencephalogram: A retrospective cohort study.

PubMed

Sanches, Paula Rodrigues; Corrêa, Thiago Domingos; Ferrari-Marinho, Taissa; Naves, Pedro Vicente Ferreira; Ladeia-Frota, Carol; Caboclo, Luís Otávio

2017-01-01

Nonconvulsive seizures (NCS) are frequent in hospitalized patients and may further aggravate injury in the already damaged brain, potentially worsening outcomes in encephalopathic patients. Therefore, both early seizure recognition and treatment have been advocated to prevent further neurological damage. Evaluate the main EEG patterns seen in patients with impaired consciousness and address the effect of treatment with antiepileptic drugs (AEDs), continuous intravenous anesthetic drugs (IVADs), or the combination of both, on outcomes. This was a single center retrospective cohort study conducted in a private, tertiary care hospital. Consecutive adult patients with altered consciousness submitted to a routine EEG between January 2008 and February 2011 were included in this study. Based on EEG pattern, patients were assigned to one of three groups: Group Interictal Patterns (IP; EEG showing only interictal epileptiform discharges or triphasic waves), Group Rhythmic and Periodic Patterns (RPP; at least one EEG with rhythmic or periodic patterns), and Group Ictal (Ictal; at least one EEG showing ictal pattern). Groups were compared in terms of administered antiepileptic treatment and frequency of unfavorable outcomes (modified Rankin scale ≥3 and in-hospital mortality). Two hundred and six patients (475 EEGs) were included in this analysis. Interictal pattern was observed in 35.4% (73/206) of patients, RPP in 53.4% (110/206) and ictal in 11.2% (23/206) of patients. Treatment with AEDs, IVADs or a combination of both was administered in half of the patients. While all Ictal group patients received treatment (AEDs or IVADs), only 24/73 (32.9%) IP group patients and 55/108 (50.9%) RPP group patients were treated (p<0.001). Hospital length of stay (LOS) and frequency of unfavorable outcomes did not differ among the groups. In-hospital mortality was higher in IVADs treated RPP patients compared to AEDs treated RPP patients [11/19 (57.9%) vs. 11/36 (30.6%) patients

Postictal apnea as an important mechanism for SUDEP: A near-SUDEP with continuous EEG-ECG-EMG recording.

PubMed

Jin, Lang; Zhang, Ying; Wang, Xiao-Li; Zhang, Wen-Juan; Liu, Yong-Hong; Jiang, Zhao

2017-09-01

Sudden unexpected death in epilepsy (SUDEP) is one of the most frequent causes of death among patients with epilepsy. Most SUDEP or near-SUDEP are unwitnessed and not observed or recorded during video-EEG recording in epilepsy monitoring units. This report describes a young woman with post ictal apnea and generalized EEG suppression (PGES) after a secondary generalized tonic-clonic seizure (sGTCS). This was accompanied by bradycardia and then ventricular tachycardia (VT). But at the end of VT, the patient's breath recovered without any intervention, such as cardio-respiratory resuscitation. This case report with continuous EEG, EKG, EMG during near SUDEP may provide insights into the mechanism of action. Copyright © 2017 Elsevier Ltd. All rights reserved.

Severe peri-ictal respiratory dysfunction is common in Dravet syndrome

PubMed Central

Kim, YuJaung; Bravo, Eduardo; Thirnbeck, Caitlin K.; Smith-Mellecker, Lori A.; Kim, Se Hee; Gehlbach, Brian K.; Laux, Linda C.; Zhou, Xiuqiong; Nordli, Douglas R.

2018-01-01

Dravet syndrome (DS) is a severe childhood-onset epilepsy commonly due to mutations of the sodium channel gene SCN1A. Patients with DS have a high risk of sudden unexplained death in epilepsy (SUDEP), widely believed to be due to cardiac mechanisms. Here we show that patients with DS commonly have peri-ictal respiratory dysfunction. One patient had severe and prolonged postictal hypoventilation during video EEG monitoring and died later of SUDEP. Mice with an Scn1aR1407X/+ loss-of-function mutation were monitored and died after spontaneous and heat-induced seizures due to central apnea followed by progressive bradycardia. Death could be prevented with mechanical ventilation after seizures were induced by hyperthermia or maximal electroshock. Muscarinic receptor antagonists did not prevent bradycardia or death when given at doses selective for peripheral parasympathetic blockade, whereas apnea, bradycardia, and death were prevented by the same drugs given at doses high enough to cross the blood-brain barrier. When given via intracerebroventricular infusion at a very low dose, a muscarinic receptor antagonist prevented apnea, bradycardia, and death. We conclude that SUDEP in patients with DS can result from primary central apnea, which can cause bradycardia, presumably via a direct effect of hypoxemia on cardiac muscle. PMID:29329111

Hyperventilation revisited: physiological effects and efficacy on focal seizure activation in the era of video-EEG monitoring.

PubMed

Guaranha, Mirian S B; Garzon, Eliana; Buchpiguel, Carlos A; Tazima, Sérgio; Yacubian, Elza M T; Sakamoto, Américo C

2005-01-01

Hyperventilation is an activation method that provokes physiological slowing of brain rhythms, interictal discharges, and seizures, especially in generalized idiopathic epilepsies. In this study we assessed its effectiveness in inducing focal seizures during video-EEG monitoring. We analyzed the effects of hyperventilation (HV) during video-EEG monitoring (video-EEG) of patients with medically intractable focal epilepsies. We excluded children younger than 10 years, mentally retarded patients, and individuals with frequent seizures. We analyzed 97 patients; 24 had positive seizure activation (PSA), and 73 had negative seizure activation (NSA). No differences were found between groups regarding sex, age, age at epilepsy onset, duration of epilepsy, frequency of seizures, and etiology. Temporal lobe epilepsies were significantly more activated than frontal lobe epilepsies. Spontaneous and activated seizures did not differ in terms of their clinical characteristics, and the activation did not affect the performance of ictal single-photon emission computed tomography (SPECT). HV is a safe and effective method of seizure activation during monitoring. It does not modify any of the characteristics of the seizures and allows the obtaining of valuable ictal SPECTs. This observation is clinically relevant and suggests the effectiveness and the potential of HV in shortening the presurgical evaluation, especially of temporal lobe epilepsy patients, consequently reducing its costs and increasing the number of candidates for epilepsy surgery.

Assessment of the Utility of Ictal Magnetoencephalography in the Localization of the Epileptic Seizure Onset Zone.

PubMed

Alkawadri, Rafeed; Burgess, Richard C; Kakisaka, Yosuke; Mosher, John C; Alexopoulos, Andreas V

2018-06-11

Literature on ictal magnetoencephalography (MEG) in clinical practice and the relationship to other modalities is limited because of the brevity of routine studies. To investigate the utility and reliability of ictal MEG in the localization of the epileptogenic zone. A retrospective medical record review and prospective analysis of a novel ictal rhythm analysis method was conducted at a tertiary epilepsy center with a wide base of referrals for epilepsy surgery evaluation and included consecutive cases of patients who experienced epileptic seizures during routine MEG studies from March 2008 to February 2012. A total of 377 studies screened. Data were analyzed from November 2011 to October 2015. Presurgical workup and interictal and ictal MEG data were reviewed. The localizing value of using extended-source localization of a narrow band identified visually at onset was analyzed. Of the 44 included patients, the mean (SD) age at the time of recording was 19.3 (14.9) years, and 25 (57%) were male. The mean duration of recording was 51.2 minutes. Seizures were provoked by known triggers in 3 patients and were spontaneous otherwise. Twenty-five patients (57%) had 1 seizure, 6 (14%) had 2, and 13 (30%) had 3 or more. Magnetoencephalography single equivalent current dipole analysis was possible in 29 patients (66%), of whom 8 (28%) had no clear interictal discharges. Sublobar concordance between ictal and interictal dipoles was seen in 18 of 21 patients (86%). Three patients (7%) showed clear ictal MEG patterns without electroencephalography changes. Ictal MEG dipoles correlated with the lobe of onset in 7 of 8 patients (88%) who underwent intracranial electroencephalography evaluations. Reasons for failure to identify ictal dipoles included diffuse or poor dipolar ictal patterns, no MEG changes, and movement artifact. Resection of areas containing a minimum-norm estimate of a narrow band at onset, not single equivalent current dipole, was associated with sustained

Response Rates to Anticonvulsant Trials in Patients with Triphasic-Wave EEG Patterns of Uncertain Significance.

PubMed

O'Rourke, Deirdre; Chen, Patrick M; Gaspard, Nicolas; Foreman, Brandon; McClain, Lauren; Karakis, Ioannis; Mahulikar, Advait; Westover, M Brandon

2016-04-01

Generalized triphasic waves (TPWs) occur in both metabolic encephalopathies and non-convulsive status epilepticus (NCSE). Empiric trials of benzodiazepines (BZDs) or non-sedating AED (NSAEDs) are commonly used to differentiate the two, but the utility of such trials is debated. The goal of this study was to assess response rates of such trials and investigate whether metabolic profile differences affect the likelihood of a response. Three institutions within the Critical Care EEG Monitoring Research Consortium retrospectively identified patients with unexplained encephalopathy and TPWs who had undergone a trial of BZD and/or NSAEDs to differentiate between ictal and non-ictal patterns. We assessed responder rates and compared metabolic profiles of responders and non-responders. Response was defined as resolution of the EEG pattern and either unequivocal improvement in encephalopathy or appearance of previously absent normal EEG patterns, and further categorized as immediate (within <2 h of trial initiation) or delayed (>2 h from trial initiation). We identified 64 patients with TPWs who had an empiric trial of BZD and/or NSAED. Most patients (71.9%) were admitted with metabolic derangements and/or infection. Positive clinical responses occurred in 10/53 (18.9%) treated with BZDs. Responses to NSAEDs occurred in 19/45 (42.2%), being immediate in 6.7%, delayed but definite in 20.0%, and delayed but equivocal in 15.6%. Overall, 22/64 (34.4%) showed a definite response to either BZDs or NSAEDs, and 7/64 (10.9%) showed a possible response. Metabolic differences of responders versus non-responders were statistically insignificant, except that the 48-h low value of albumin in the BZD responder group was lower than in the non-responder group. Similar metabolic profiles in patients with encephalopathy and TPWs between responders and non-responders to anticonvulsants suggest that predicting responders a priori is difficult. The high responder rate suggests that empiric

Long-term subdural strip electrocorticographic monitoring of ictal déjà vu.

PubMed

Weinand, M E; Hermann, B; Wyler, A R; Carter, L P; Oommen, K J; Labiner, D; Ahern, G; Herring, A

1994-01-01

We report a series of 8 patients with ictal déjà vu. Subdural strip electrocorticographic (ECoG) monitoring localized the ictal epileptogenic focus as follows: right (n = 6) and left (n = 2) mesiotemporal lobe. In all 8 patients, the left hemisphere was dominant for language function based on intracarotid amytal testing. In 6 right-handed patients, ictal déjà vu was associated with a right temporal lobe focus. However, in the 2 left-handed patients, the ictal focus was left temporal lobe. Although ictal déjà vu localizes the epileptic focus to temporal lobe, this experimental phenomenon appears to lateralize to the hemisphere nondominant for handedness.

Sleep disruption increases seizure susceptibility: Behavioral and EEG evaluation of an experimental model of sleep apnea.

PubMed

Hrnčić, Dragan; Grubač, Željko; Rašić-Marković, Aleksandra; Šutulović, Nikola; Šušić, Veselinka; Bjekić-Macut, Jelica; Stanojlović, Olivera

2016-03-01

Sleep disruption accompanies sleep apnea as one of its major symptoms. Obstructive sleep apnea is particularly common in patients with refractory epilepsy, but causing factors underlying this are far from being resolved. Therefore, translational studies regarding this issue are important. Our aim was to investigate the effects of sleep disruption on seizure susceptibility of rats using experimental model of lindane-induced refractory seizures. Sleep disruption in male Wistar rats with implanted EEG electrodes was achieved by treadmill method (belt speed set on 0.02 m/s for working and 0.00 m/s for stop mode, respectively). Animals were assigned to experimental conditions lasting 6h: 1) sleep disruption (sleep interrupted, SI; 30s working and 90 s stop mode every 2 min; 180 cycles in total); 2) activity control (AC, 10 min working and 30 min stop mode, 9 cycles in total); 3) treadmill chamber control (TC, only stop mode). Afterwards, the animals were intraperitoneally treated with lindane (L, 4 mg/kg, SI+L, AC+L and TC+L groups) or dimethylsulfoxide (DMSO, SIc, ACc and TCc groups). Convulsive behavior was assessed by seizure incidence, latency time to first seizure, and its severity during 30 min after drug administration. Number and duration of ictal periods were determined in recorded EEGs. Incidence and severity of lindane-induced seizures were significantly increased, latency time significantly decreased in animals undergoing sleep disruption (SI+L group) compared with the animals from TC+L. Seizure latency was also significantly decreased in SI+L compared to AC+L groups. Number of ictal periods were increased and duration of it presented tendency to increase in SI+L comparing to AC+L. No convulsive signs were observed in TCc, ACc and SIc groups, as well as no ictal periods in EEG. These results indicate sleep disruption facilitates induction of epileptic activity in rodent model of lindane-epilepsy enabling translational research of this phenomenon. Copyright �

Seizure classification in EEG signals utilizing Hilbert-Huang transform

PubMed Central

2011-01-01

Background Classification method capable of recognizing abnormal activities of the brain functionality are either brain imaging or brain signal analysis. The abnormal activity of interest in this study is characterized by a disturbance caused by changes in neuronal electrochemical activity that results in abnormal synchronous discharges. The method aims at helping physicians discriminate between healthy and seizure electroencephalographic (EEG) signals. Method Discrimination in this work is achieved by analyzing EEG signals obtained from freely accessible databases. MATLAB has been used to implement and test the proposed classification algorithm. The analysis in question presents a classification of normal and ictal activities using a feature relied on Hilbert-Huang Transform. Through this method, information related to the intrinsic functions contained in the EEG signal has been extracted to track the local amplitude and the frequency of the signal. Based on this local information, weighted frequencies are calculated and a comparison between ictal and seizure-free determinant intrinsic functions is then performed. Methods of comparison used are the t-test and the Euclidean clustering. Results The t-test results in a P-value < 0.02 and the clustering leads to accurate (94%) and specific (96%) results. The proposed method is also contrasted against the Multivariate Empirical Mode Decomposition that reaches 80% accuracy. Comparison results strengthen the contribution of this paper not only from the accuracy point of view but also with respect to its fast response and ease to use. Conclusion An original tool for EEG signal processing giving physicians the possibility to diagnose brain functionality abnormalities is presented in this paper. The proposed system bears the potential of providing several credible benefits such as fast diagnosis, high accuracy, good sensitivity and specificity, time saving and user friendly. Furthermore, the classification of mode mixing

Seizure classification in EEG signals utilizing Hilbert-Huang transform.

PubMed

Oweis, Rami J; Abdulhay, Enas W

2011-05-24

Classification method capable of recognizing abnormal activities of the brain functionality are either brain imaging or brain signal analysis. The abnormal activity of interest in this study is characterized by a disturbance caused by changes in neuronal electrochemical activity that results in abnormal synchronous discharges. The method aims at helping physicians discriminate between healthy and seizure electroencephalographic (EEG) signals. Discrimination in this work is achieved by analyzing EEG signals obtained from freely accessible databases. MATLAB has been used to implement and test the proposed classification algorithm. The analysis in question presents a classification of normal and ictal activities using a feature relied on Hilbert-Huang Transform. Through this method, information related to the intrinsic functions contained in the EEG signal has been extracted to track the local amplitude and the frequency of the signal. Based on this local information, weighted frequencies are calculated and a comparison between ictal and seizure-free determinant intrinsic functions is then performed. Methods of comparison used are the t-test and the Euclidean clustering. The t-test results in a P-value < 0.02 and the clustering leads to accurate (94%) and specific (96%) results. The proposed method is also contrasted against the Multivariate Empirical Mode Decomposition that reaches 80% accuracy. Comparison results strengthen the contribution of this paper not only from the accuracy point of view but also with respect to its fast response and ease to use. An original tool for EEG signal processing giving physicians the possibility to diagnose brain functionality abnormalities is presented in this paper. The proposed system bears the potential of providing several credible benefits such as fast diagnosis, high accuracy, good sensitivity and specificity, time saving and user friendly. Furthermore, the classification of mode mixing can be achieved using the extracted

Ictal fear: Associations with age, gender, and other experiential phenomena.

PubMed

Chong, Derek J; Dugan, Patricia

2016-09-01

The aim of this study was to determine the relationship of fear to other auras and to gender and age using a large database. The Epilepsy Phenome/Genome Project (EPGP) is a multicenter, multicontinental cross-sectional study in which ictal symptomatology and other data were ascertained in a standardized series of questionnaires then corroborated by epilepsy specialists. Auras were classified into subgroups of symptoms, with ictal fear, panic, or anxiety as a single category. Of 536 participants with focal epilepsy, 72 were coded as having ictal fear/panic/anxiety. Reviewing raw patient responses, 12 participants were deemed not to have fear, and 24 had inadequate data, leaving 36 (7%) of 512 with definite ictal fear. In univariate analyses, fear was significantly associated with auras historically considered temporal lobe in origin, including cephalic, olfactory, and visceral complaints; déjà vu; and derealization. On both univariate and multivariate stepwise analyses, fear was associated with jamais vu and auras with cardiac symptoms, dyspnea, and chest tightening. Expressive aphasia was associated with fear on univariate analysis only, but the general category of aphasias was associated with fear only in the multivariate model. There was no age or gender relationship with fear when compared to the overall population with focal epilepsy that was studied under the EPGP. Patients with ictal fear were more likely to have a right hemisphere seizure focus. Ictal fear was strongly associated with other auras considered to originate from the limbic system. No relationship of fear with age or gender was observed. Copyright © 2016 Elsevier Inc. All rights reserved.

The Success Rate of Neurology Residents in EEG Interpretation After Formal Training.

PubMed

Dericioglu, Nese; Ozdemir, Pınar

2018-03-01

EEG is an important tool for neurologists in both diagnosis and classification of seizures. It is not uncommon in clinical practice to see patients who were erroneously diagnosed as epileptic. Most of the time incorrect interpretation of EEG contributes significantly to this problem. In this study, we aimed to investigate the success rate of neurology residents in EEG interpretation after formal training. Eleven neurology residents were included in the study. Duration of EEG training (3 vs 4 months) and time since completion of EEG education were determined. Residents were randomly presented 30 different slides of representative EEG screenshots. They received 1 point for each correct response. The effect of training duration and time since training were investigated statistically. Besides, we looked at the success rate of each question to see whether certain patterns were more readily recognized than others. EEG training duration ( P = .93) and time since completion of training ( P = .16) did not influence the results. The success rate of residents for correct responses was between 17% and 50%. On the other hand, the success rate for each question varied between 0% and 91%. Overall, benign variants and focal ictal onset patterns were the most difficult to recognize. On 13 occasions (6.5%) nonepileptiform patterns were thought to represent epileptiform abnormalities. After formal training, neurology residents could identify ≤50% of the EEG patterns correctly. The wide variation in success rate among residents and also between questions implies that both personal characteristics and inherent EEG features influence successful EEG interpretation.

NREM Arousal Parasomnias and Their Distinction from Nocturnal Frontal Lobe Epilepsy: A Video EEG Analysis

PubMed Central

Derry, Christopher P.; Harvey, A. Simon; Walker, Matthew C.; Duncan, John S.; Berkovic, Samuel F.

2009-01-01

Study Objectives. To describe the semiological features of NREM arousal parasomnias in detail and identify features that can be used to reliably distinguish parasomnias from nocturnal frontal lobe epilepsy (NFLE). Design. Systematic semiologial evaluation of parasomnias and NFLE seizures recorded on video-EEG monitoring. Patients. 120 events (57 parasomnias, 63 NFLE seizures) from 44 subjects (14 males). Interventions. The presence or absence of 68 elemental clinical features was determined in parasomnias and NFLE seizures. Qualitative analysis of behavior patterns and ictal EEG was undertaken. Statistical analysis was undertaken using established techniques. Results. Elemental clinical features strongly favoring parasomnias included: interactive behavior, failure to wake after event, and indistinct offset (all P < 0.001). Cluster analysis confirmed differences in both the frequency and combination of elemental features in parasomnias and NFLE. A diagnostic decision tree generated from these data correctly classified 94% of events. While sleep stage at onset was discriminatory (82% of seizures occurred during stage 1 or 2 sleep, with 100% of parasomnias occurring from stage 3 or 4 sleep), ictal EEG features were less useful. Video analysis of parasomnias identified three principal behavioral patterns: arousal behavior (92% of events); non-agitated motor behavior (72%); distressed emotional behavior (51%). Conclusions Our results broadly support the concept of confusion arousals, somnambulism and night terrors as prototypical behavior patterns of NREM parasomnias, but as a hierarchical continuum rather than distinct entities. Our observations provide an evidence base to assist in the clinical diagnosis of NREM parasomnias, and their distinction from NFLE seizures, on semiological grounds. Citation: Derry CP; Harvey AS; Walker MC; Duncan JS; Berkovic SF. NREM arousal parasomnias and their distinction from nocturnal frontal lobe epilepsy: a video EEG analysis. SLEEP

Dynamics of convulsive seizure termination and postictal generalized EEG suppression

PubMed Central

Bauer, Prisca R.; Thijs, Roland D.; Lamberts, Robert J.; Velis, Demetrios N.; Visser, Gerhard H.; Tolner, Else A.; Sander, Josemir W.; Lopes da Silva, Fernando H.; Kalitzin, Stiliyan N.

2017-01-01

Abstract It is not fully understood how seizures terminate and why some seizures are followed by a period of complete brain activity suppression, postictal generalized EEG suppression. This is clinically relevant as there is a potential association between postictal generalized EEG suppression, cardiorespiratory arrest and sudden death following a seizure. We combined human encephalographic seizure data with data of a computational model of seizures to elucidate the neuronal network dynamics underlying seizure termination and the postictal generalized EEG suppression state. A multi-unit computational neural mass model of epileptic seizure termination and postictal recovery was developed. The model provided three predictions that were validated in EEG recordings of 48 convulsive seizures from 48 subjects with refractory focal epilepsy (20 females, age range 15–61 years). The duration of ictal and postictal generalized EEG suppression periods in human EEG followed a gamma probability distribution indicative of a deterministic process (shape parameter 2.6 and 1.5, respectively) as predicted by the model. In the model and in humans, the time between two clonic bursts increased exponentially from the start of the clonic phase of the seizure. The terminal interclonic interval, calculated using the projected terminal value of the log-linear fit of the clonic frequency decrease was correlated with the presence and duration of postictal suppression. The projected terminal interclonic interval explained 41% of the variation in postictal generalized EEG suppression duration (P < 0.02). Conversely, postictal generalized EEG suppression duration explained 34% of the variation in the last interclonic interval duration. Our findings suggest that postictal generalized EEG suppression is a separate brain state and that seizure termination is a plastic and autonomous process, reflected in increased duration of interclonic intervals that determine the duration of postictal

Palilalia, echolalia, and echopraxia-palipraxia as ictal manifestations in a patient with left frontal lobe epilepsy.

PubMed

Cho, Yang-Je; Han, Sang-Don; Song, Sook Keun; Lee, Byung In; Heo, Kyoung

2009-06-01

Palilalia is a relatively rare pathologic speech behavior and has been reported in various neurologic and psychiatric disorders. We encountered a case of palilalia, echolalia, and echopraxia-palipraxia as ictal phenomena of left frontal lobe epilepsy. A 55-year-old, right-handed man was admitted because of frequent episodes of rapid reiteration of syllables. Video-electroencephalography monitoring revealed stereotypical episodes of palilalia accompanied by rhythmic head nodding and right-arm posturing with ictal discharges over the left frontocentral area. He also displayed echolalia or echopraxia-palipraxia, partially responding to an examiner's stimulus. Magnetic resonance imaging revealed encephalomalacia on the left superior frontal gyrus and ictal single photon emission computed tomography showed hyperperfusion just above the lesion, corresponding to the left supplementary motor area (SMA), and subcortical nuclei. This result suggests that the neuroanatomic substrate involved in the generation of these behaviors as ictal phenomena might exist in the SMA of the left frontal lobe.

Ictal high frequency oscillations distinguish two types of seizure territories in humans

PubMed Central

Weiss, Shennan A.; Banks, Garrett P.; McKhann, Guy M.; Goodman, Robert R.; Emerson, Ronald G.; Trevelyan, Andrew J.

2013-01-01

High frequency oscillations have been proposed as a clinically useful biomarker of seizure generating sites. We used a unique set of human microelectrode array recordings (four patients, 10 seizures), in which propagating seizure wavefronts could be readily identified, to investigate the basis of ictal high frequency activity at the cortical (subdural) surface. Sustained, repetitive transient increases in high gamma (80–150 Hz) amplitude, phase-locked to the low-frequency (1–25 Hz) ictal rhythm, correlated with strong multi-unit firing bursts synchronized across the core territory of the seizure. These repetitive high frequency oscillations were seen in recordings from subdural electrodes adjacent to the microelectrode array several seconds after seizure onset, following ictal wavefront passage. Conversely, microelectrode recordings demonstrating only low-level, heterogeneous neural firing correlated with a lack of high frequency oscillations in adjacent subdural recording sites, despite the presence of a strong low-frequency signature. Previously, we reported that this pattern indicates a failure of the seizure to invade the area, because of a feedforward inhibitory veto mechanism. Because multi-unit firing rate and high gamma amplitude are closely related, high frequency oscillations can be used as a surrogate marker to distinguish the core seizure territory from the surrounding penumbra. We developed an efficient measure to detect delayed-onset, sustained ictal high frequency oscillations based on cross-frequency coupling between high gamma amplitude and the low-frequency (1–25 Hz) ictal rhythm. When applied to the broader subdural recording, this measure consistently predicted the timing or failure of ictal invasion, and revealed a surprisingly small and slowly spreading seizure core surrounded by a far larger penumbral territory. Our findings thus establish an underlying neural mechanism for delayed-onset, sustained ictal high frequency oscillations, and

Response Rates to Anticonvulsant Trials in Patients with Triphasic-Wave EEG Patterns of Uncertain Significance

PubMed Central

O’Rourke, Deirdre; Chen, Patrick M.; Gaspard, Nicolas; Foreman, Brandon; McClain, Lauren; Karakis, Ioannis; Mahulikar, Advait

2016-01-01

Background Generalized triphasic waves (TPWs) occur in both metabolic encephalopathies and non-convulsive status epilepticus (NCSE). Empiric trials of benzodiazepines (BZDs) or non-sedating AED (NSAEDs) are commonly used to differentiate the two, but the utility of such trials is debated. The goal of this study was to assess response rates of such trials and investigate whether metabolic profile differences affect the likelihood of a response. Methods Three institutions within the Critical Care EEG Monitoring Research Consortium retrospectively identified patients with unexplained encephalopathy and TPWs who had undergone a trial of BZD and/or NSAEDs to differentiate between ictal and non-ictal patterns. We assessed responder rates and compared metabolic profiles of responders and non-responders. Response was defined as resolution of the EEG pattern and either unequivocal improvement in encephalopathy or appearance of previously absent normal EEG patterns, and further categorized as immediate (within <2 h of trial initiation) or delayed (>2 h from trial initiation). Results We identified 64 patients with TPWs who had an empiric trial of BZD and/or NSAED. Most patients (71.9 %) were admitted with metabolic derangements and/or infection. Positive clinical responses occurred in 10/53 (18.9 %) treated with BZDs. Responses to NSAEDs occurred in 19/45 (42.2 %), being immediate in 6.7 %, delayed but definite in 20.0 %, and delayed but equivocal in 15.6 %. Overall, 22/64 (34.4 %) showed a definite response to either BZDs or NSAEDs, and 7/64 (10.9 %) showed a possible response. Metabolic differences of responders versus non-responders were statistically insignificant, except that the 48-h low value of albumin in the BZD responder group was lower than in the non-responder group. Conclusions Similar metabolic profiles in patients with encephalopathy and TPWs between responders and non-responders to anticonvulsants suggest that predicting responders a priori is difficult. The

Neuronal network model of interictal and recurrent ictal activity

NASA Astrophysics Data System (ADS)

Lopes, M. A.; Lee, K.-E.; Goltsev, A. V.

2017-12-01

We propose a neuronal network model which undergoes a saddle node on an invariant circle bifurcation as the mechanism of the transition from the interictal to the ictal (seizure) state. In the vicinity of this transition, the model captures important dynamical features of both interictal and ictal states. We study the nature of interictal spikes and early warnings of the transition predicted by this model. We further demonstrate that recurrent seizures emerge due to the interaction between two networks.

Epileptic peri-ictal psychosis, a reversible cause of psychosis.

PubMed

González Mingot, C; Gil Villar, M P; Calvo Medel, D; Corbalán Sevilla, T; Martínez Martínez, L; Iñiguez Martínez, C; Santos Lasaosa, S; Mauri Llerda, J A

2013-03-01

Epileptic psychoses are categorised as peri-ictal and interictal according to their relationship with the occurrence of seizures. There is a close temporal relationship between peri-ictal psychosis and seizures, and psychosis may present before (preictal), during (ictal) or after seizures (postictal). Epileptic psychoses usually have acute initial and final phases, with a short symptom duration and complete remission with a risk of recurrence. There is no temporal relationship between interictal or chronic psychosis and epileptic seizures. Another type of epileptic psychosis is related to the response to epilepsy treatment: epileptic psychosis caused by the phenomenon of forced normalisation (alternative psychosis), which includes epileptic psychosis secondary to epilepsy surgery. Although combination treatment with antiepileptic and neuroleptic drugs is now widely used to manage this condition, there are no standard treatment guidelines for epileptic psychosis. We present 5 cases of peri-ictal epileptic psychosis in which we observed an excellent response to treatment with levetiracetam. Good control was achieved over both seizures and psychotic episodes. Levetiracetam was used in association with neuroleptic drugs with no adverse effects, and our patients did not require high doses of the latter. Categorising psychotic states associated with epilepsy according to their temporal relationship with seizures is clinically and prognostically useful because it provides important information regarding disease treatment and progression. The treatment of peri-ictal or acute mental disorders is based on epileptic seizure control, while the treatment of interictal or chronic disorders has more in common with managing disorders which are purely psychiatric in origin. In addition to improving the patient's quality of life and reducing disability, achieving strict control over seizures may also prevent the development of interictal psychosis. For this reason, we believe that

Interictal EEG spikes identify the region of seizure onset in some, but not all pediatric epilepsy patients

PubMed Central

Marsh, Eric D.; Peltzer, Bradley; Brown, Merritt W.; Wusthoff, Courtney; Storm, Phillip B.; Litt, Brian; Porter, Brenda E.

2010-01-01

Purpose The role of sharps and spikes, interictal epileptiform discharges (IEDs), in guiding epilepsy surgery in children remains controversial, particularly with intracranial EEG (IEEG). While ictal recording is the mainstay of localizing epileptic networks for surgical resection, current practice dictates removing regions generating frequent IEDs if they are near the ictal onset zone. Indeed, past studies suggest an inconsistent relationship between IED and seizure onset location, though these studies were based upon relatively short EEG epochs. Methods We employ a previously validated, computerized spike detector, to measure and localize IED activity over prolonged, representative segments of IEEG recorded from 19 children with intractable, mostly extra temporal lobe epilepsy. Approximately 8 hours of IEEG, randomly selected thirty-minute segments of continuous interictal IEEG per patient were analyzed over all intracranial electrode contacts. Results When spike frequency was averaged over the 16-time segments, electrodes with the highest mean spike frequency were found to be within the seizure onset region in 11 of 19 patients. There was significant variability between individual 30-minute segments in these patients, indicating that large statistical samples of interictal activity were required for improved localization. Low voltage fast EEG at seizure onset was the only clinical factor predicting IED localization to the seizure onset region. Conclusions Our data suggest that automated IED detection over multiple representative samples of IEEG may be of utility in planning epilepsy surgery for children with intractable epilepsy. Further research is required to better determine which patients may benefit from this technique a priori. PMID:19780794

Daytime outpatient versus inpatient video-EEG monitoring for presurgical evaluation in temporal lobe epilepsy.

PubMed

Guerreiro, Carlos A M; Montenegro, Maria Augusta; Kobayashi, Eliane; Noronha, Ana Lúcia A; Guerreiro, Marilisa M; Cendes, Fernando

2002-06-01

Video-EEG monitoring documentation of seizure localization is one of the most important aspects of a presurgical investigation in refractory temporal lobe epilepsy (TLE) patients. The objective of this study was to evaluate the efficacy of inpatient versus daytime outpatient telemetry. The authors evaluated prospectively 73 patients with medically intractable TLE. Ninety-one telemetry sessions were performed: 35 as inpatients and 56 as outpatients. Outpatient monitoring was performed in the EEG laboratory. They used 18-channel digital EEG. Medications were not changed in the outpatient group. For analysis of the data, time was counted in periods (12 hours = 1 period). Statistical analyses were performed using Student's t-test and the chi2 test. There were no differences between the two groups (outpatient versus inpatient) with respect to age and mean seizure frequency before monitoring, mean time to record the first seizure (1.1 versus 1.4 periods), mean number of seizures per period (0.6 for both groups), lateralization by interictal spiking (46% versus 57%), and lateralization by ictal EEG (59% versus 77%). Daytime outpatient video-EEG monitoring for presurgical evaluation is efficient and comparable with inpatient monitoring. Therefore, the improved cost benefit of outpatient monitoring may increase the access to surgery for individuals with intractable TLE.

Presurgical EEG-fMRI in a complex clinical case with seizure recurrence after epilepsy surgery

PubMed Central

Zhang, Jing; Liu, Qingzhu; Mei, Shanshan; Zhang, Xiaoming; Wang, Xiaofei; Liu, Weifang; Chen, Hui; Xia, Hong; Zhou, Zhen; Li, Yunlin

2013-01-01

Epilepsy surgery has improved over the last decade, but non-seizure-free outcome remains at 10%–40% in temporal lobe epilepsy (TLE) and 40%–60% in extratemporal lobe epilepsy (ETLE). This paper reports a complex multifocal case. With a normal magnetic resonance imaging (MRI) result and nonlocalizing electroencephalography (EEG) findings (bilateral TLE and ETLE, with more interictal epileptiform discharges [IEDs] in the right frontal and temporal regions), a presurgical EEG-functional MRI (fMRI) was performed before the intraoperative intracranial EEG (icEEG) monitoring (icEEG with right hemispheric coverage). Our previous EEG-fMRI analysis results (IEDs in the left hemisphere alone) were contradictory to the EEG and icEEG findings (IEDs in the right frontal and temporal regions). Thus, the EEG-fMRI data were reanalyzed with newly identified IED onsets and different fMRI model options. The reanalyzed EEG-fMRI findings were largely concordant with those of EEG and icEEG, and the failure of our previous EEG-fMRI analysis may lie in the inaccurate identification of IEDs and wrong usage of model options. The right frontal and temporal regions were resected in surgery, and dual pathology (hippocampus sclerosis and focal cortical dysplasia in the extrahippocampal region) was found. The patient became seizure-free for 3 months, but his seizures restarted after antiepileptic drugs (AEDs) were stopped. The seizures were not well controlled after resuming AEDs. Postsurgical EEGs indicated that ictal spikes in the right frontal and temporal regions reduced, while those in the left hemisphere became prominent. This case suggested that (1) EEG-fMRI is valuable in presurgical evaluation, but requires caution; and (2) the intact seizure focus in the remaining brain may cause the non-seizure-free outcome. PMID:23926432

[The role of ambulatory electroencephalogram monitoring: experience and results in 264 records].

PubMed

González de la Aleja, J; Saiz Díaz, R A; Martín García, H; Juntas, R; Pérez-Martínez, D; de la Peña, P

2008-11-01

Ambulatory electroencephalogram (EEG) monitoring allows for long-term, mobile electroencephalographic recordings of patients. This study aims to describe and analyze the results obtained with ambulatory EEG in our clinical practice. We have analyzed the results of 264 ambulatory EEG records, grouped according to the reason for the request: a) group 1: diagnostic evaluation of episodes of epileptic nature; b) group 2: diagnostic evaluation of paroxysmal episodes, and c) group 3: evaluation of the risk of relapse during anti-seizure treatment withdrawal in certain epileptic patients. a) Group 1 (n=137): normal results were found in 54 records (39.4%). There was generalized epileptic activity in 20 (14.6%) of them (5 with ictal activity) and focal epileptic activity was detected in 57 cases (42%) (8 with ictal activity). No EEG diagnosis could be reached in 6 (4%) recordings due to the presence of artefacts; b) group 2 (n=99): in 47 records (47.5 %), there were no episodes and the Holter-EEG was normal. There was a clinically documented episode without anomalies during Holter-EEG registration in 14 cases (14.2%). In 29 records (29.3%), focal epileptic activity was recorded (ictal 4) and generalized epileptic activity (ictal in 1) was recorded in 4 patients (4%). No EEG diagnosis could be reached in 5 cases (5%), and c) group 3 (n=28): the study was normal in 15 cases (53.6%) and showed focal interictal epileptic activity in 8 (28.6 %) and generalized interictal epileptic activity in 5 of them (17.8%). We believe that the ambulatory EEG recordings in correctly selected cases can provide important additional information regarding global assessment of patients with epilepsy.

Post-ictal psychosis in adolescent Niemann-Pick disease type C.

PubMed

Walterfang, Mark; Kornberg, Andrew; Adams, Sophia; Fietz, Michael; Velakoulis, Dennis

2010-12-01

We describe the presentation of an adolescent with juvenile-onset Niemann-Pick disease type C (NPC) who presented with post-ictal psychosis in the context of a developing seizure disorder. After demonstrating mild gait disturbance beginning at the age of 4 years, he was diagnosed with NPC at age 12 on the basis of 95% of cultured fibroblasts staining positive for filipin and a reduced fibroblast cholesterol esterification rate. He then developed a seizure disorder at age 15, where clusters of seizures produced typical psychotic symptoms, including hallucinations and delusions. His seizure disorder responded to valproate, which resulted in a settling of his psychotic symptoms. Whilst post-ictal psychosis is rarely reported prior to the age of 16, NPC in adolescents and adults is particularly psychotogenic and may increase the risk for post-ictal psychosis in the pediatric population.

Postictal psychosis and its electrophysiological correlates in invasive EEG: a case report study and literature review.

PubMed

Kuba, Robert; Brázdil, Milan; Rektor, Ivan

2012-04-01

We identified two patients with medically refractory temporal lobe epilepsy, from whom intracranial EEG recordings were obtained at the time of postictal psychosis. Both patients had mesial temporal epilepsy associated with hippocampal sclerosis. In both patients, the postictal psychosis was associated with a continual "epileptiform" EEG pattern that differed from their interictal and ictal EEG findings (rhythmical slow wave and "abortive" spike-slow wave complex activity in the right hippocampus and lateral temporal cortex in case 1 and a periodic pattern of triphasic waves in the contacts recording activity from the left anterior cingulate gyrus). Some cases of postictal psychosis might be caused by the transient impairment of several limbic system structures due to the "continual epileptiform discharge" in some brain regions. Case 2 is the first report of a patient with TLE in whom psychotic symptoms were associated with the epileptiform impairment of the anterior cingulate gyrus. Copyright © 2012 Elsevier Inc. All rights reserved.

Non ictal onset zone: A window to ictal dynamics.

PubMed

Afra, Pegah; Hanrahan, Sara J; Kellis, Spencer Sterling; House, Paul

2017-01-01

The focal and network concepts of epilepsy present different aspects of electroclinical phenomenon of seizures. Here, we present a 23-year-old man undergoing surgical evaluation with left fronto-temporal electrocorticography (ECoG) and microelectrode-array (MEA) in the middle temporal gyrus (MTG). We compare action-potential (AP) and local field potentials (LFP) recorded from MEA with ECoG. Seizure onset in the mesial-temporal lobe was characterized by changes in the pattern of AP-firing without clear changes in LFP or ECoG in MTG. This suggests simultaneous analysis of neuronal activity in differing spatial scales and frequency ranges provide complementary insights into how focal and network neurophysiological activity contribute to ictal activity.

Infantile ictal apneas in a child with williams-beuren syndrome.

PubMed

Myers, Kenneth A; McLeod, D Ross; Bello-Espinosa, Luis

2013-02-01

Williams-Beuren syndrome is a genetic disorder rarely associated with seizures. The few described cases of Williams-Beuren syndrome and epilepsy have primarily involved infantile spasms and deletions extending beyond the common deletion region for this disorder. We present the case of a 5-week-old child with ictal apneas and typical Williams-Beuren syndrome deletion. Diagnosis was challenging, because the child had cardiac, respiratory, and gastrointestinal abnormalities typically associated with Williams-Beuren syndrome, which are also associated with cyanotic episodes. The results of interictal electroencephalography were normal, illustrating that prolonged electroencephalography is often essential in evaluation of suspected ictal apneas. Seizure freedom was achieved with carbamazepine. Sudden death is seen in Williams-Beuren syndrome, and this case raises the question whether some of these cases may be related to ictal apneas and could potentially be preventable with appropriate pharmaceutical intervention. Copyright © 2013 Elsevier Inc. All rights reserved.

Ictal 18F-FDG PET/MRI in a Patient With Cortical Heterotopia and Focal Epilepsy.

PubMed

Calabria, Ferdinando F; Cascini, Giuseppe Lucio; Gambardella, Antonio; Labate, Angelo; Cherubini, Andrea; Gullà, Domenico; Tafuri, Benedetta; Sabatini, Umberto; Vescio, Virginia; Quattrone, Aldo

2017-10-01

A 19-year-old man with epilepsy underwent ictal F-FDG PET/MRI, showing a 5 mm heterotopic nodule in the periventricular white matter, adjacent to the frontal horn of the left lateral ventricle (SUVmax, 5.5; glucidic cerebral metabolic rate, 0.317 μmol/mL). A repeated F-FDG PET/MRI, during seizure freedom, showed, at visual analysis, subtle decrease of the nodule metabolism. SUVmax and glucidic cerebral metabolic rate were clearly reduced to 3.7 and 0.226, respectively. Ictal F-FDG PET/MRI could be useful in epilepsy because of the added value of SUVmax and cerebral metabolic rate of glucose analysis to understand the relationship between heterotopy and epilepsy.

Multivariate regression methods for estimating velocity of ictal discharges from human microelectrode recordings

NASA Astrophysics Data System (ADS)

Liou, Jyun-you; Smith, Elliot H.; Bateman, Lisa M.; McKhann, Guy M., II; Goodman, Robert R.; Greger, Bradley; Davis, Tyler S.; Kellis, Spencer S.; House, Paul A.; Schevon, Catherine A.

2017-08-01

-observable EEG data, with a variety of straightforward computation methods available. This opens possibilities for systematic assessments of ictal discharge propagation in clinical and research settings.

Cerebral perfusion alterations in epileptic patients during peri-ictal and post-ictal phase: PASL vs DSC-MRI.

PubMed

Pizzini, Francesca B; Farace, Paolo; Manganotti, Paolo; Zoccatelli, Giada; Bongiovanni, Luigi G; Golay, Xavier; Beltramello, Alberto; Osculati, Antonio; Bertini, Giuseppe; Fabene, Paolo F

2013-07-01

Non-invasive pulsed arterial spin labeling (PASL) MRI is a method to study brain perfusion that does not require the administration of a contrast agent, which makes it a valuable diagnostic tool as it reduces cost and side effects. The purpose of the present study was to establish the viability of PASL as an alternative to dynamic susceptibility contrast (DSC-MRI) and other perfusion imaging methods in characterizing changes in perfusion patterns caused by seizures in epileptic patients. We evaluated 19 patients with PASL. Of these, the 9 affected by high-frequency seizures were observed during the peri-ictal period (within 5hours since the last seizure), while the 10 patients affected by low-frequency seizures were observed in the post-ictal period. For comparison, 17/19 patients were also evaluated with DSC-MRI and CBF/CBV. PASL imaging showed focal vascular changes, which allowed the classification of patients in three categories: 8 patients characterized by increased perfusion, 4 patients with normal perfusion and 7 patients with decreased perfusion. PASL perfusion imaging findings were comparable to those obtained by DSC-MRI. Since PASL is a) sensitive to vascular alterations induced by epileptic seizures, b) comparable to DSC-MRI for detecting perfusion asymmetries, c) potentially capable of detecting time-related perfusion changes, it can be recommended for repeated evaluations, to identify the epileptic focus, and in follow-up and/or therapy-response assessment. Copyright © 2013 Elsevier Inc. All rights reserved.

Ictal and interictal electric source imaging in presurgical evaluation: a prospective study.

PubMed

Sharma, Praveen; Scherg, Michael; Pinborg, Lars H; Fabricius, Martin; Rubboli, Guido; Pedersen, Birthe; Leffers, Anne-Mette; Uldall, Peter; Jespersen, Bo; Brennum, Jannick; Mølby Henriksen, Otto; Beniczky, Sándor

2018-05-11

Accurate localization of the epileptic focus is essential for surgical treatment of patients with drug- resistant epilepsy. EEG source imaging (ESI) is increasingly used in presurgical evaluation. However, most previous studies analysed interictal discharges. Prospective studies comparing feasibility and accuracy of interictal (II) and ictal (IC) ESI are lacking. We prospectively analysed long-term video EEG recordings (LTM) of patients admitted for presurgical evaluation. We performed ESI of II and IC signals, using two methods: equivalent current dipole (ECD) and distributed source model (DSM). LTM recordings employed the standard 25-electrode array (including inferior temporal electrodes). An age-matched template head-model was used for source analysis. Results were compared with intracranial recordings (ICR), conventional neuroimaging methods (MRI, PET, SPECT) and outcome one year after surgery. Eighty-seven consecutive patients were analysed. ECD gave a significantly higher proportion of patients with localised focal abnormalities (94%) compared to MRI (70%), PET (66%) and SPECT (64%). Agreement between the ESI methods and ICR was moderate to substantial (k=0.56-0.79). Fifty-four patients were operated (47 for more than one year ago) and 62% of them became seizure-free. Localization accuracy of II-ESI was 51% for DSM and 57% for ECD; for IC-ESI this was 51% (DSM) and 62% (ECD). The differences between the ESI methods were not significant. Differences in localization accuracy between ESI and MRI (55%), PET (33%) and SPECT (40%) were not significant. II and IC ESI of LTM-data have high feasibility and their localisation accuracy is similar to the conventional neuroimaging methods. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Differential neurophysiological effects of magnetic seizure therapy (MST) and electroconvulsive shock (ECS) in non-human primates.

PubMed

Cycowicz, Yael M; Luber, Bruce; Spellman, Timothy; Lisanby, Sarah H

2008-07-01

Magnetic seizure therapy (MST) is under development as a means of reducing the side effects of electroconvulsive therapy (ECT) through enhanced control over patterns of seizure induction and spread. We previously reported that chronic treatment with MST resulted in less impairment in cognitive function than electroconvulsive shock (ECS) in a non-human primate model of convulsive therapy. Here we present quantitative analyses of ictal expression and post-ictal suppression following ECS, MST, and anesthesia-alone sham in the same model to test whether differential neurophysiological characteristics of the seizures could be identified. Rhesus monkeys received 4 weeks of daily treatment with ECS, MST, and anesthesia-alone sham in a counterbalanced order separated by a recovery period. Both ECS and MST were given bilaterally at 2.5 x seizure threshold. Neurophysiological characteristics were derived from two scalp EEG electrode recording sites during and immediately following the ictal period, and were compared to sham treatment. EEG power within four frequencies (delta, theta, alpha and beta) was calculated. Our results support earlier findings from intracerebral electrode recordings demonstrating that MST- and ECS- induced seizures elicit differential patterns of EEG activation. Specifically, we found that ECS shows significantly more marked ictal expression, and more intense post-ictal suppression than MST in the theta, alpha, and beta frequency bands (Ps < .05). However, the ECS and MST were indistinguishable in the delta frequency band during both ictal and post-ictal periods. These results demonstrate that magnetic seizure induction can result in seizures that differ in some neurophysiological respects compared with ECS, but that these modalities share some aspects of seizure expression. The clinical significance of these similarities and differences awaits clinical correlation.

Differentiating ictal panic with low-grade temporal lobe tumors from psychogenic panic attacks.

PubMed

Ghods, Ali J; Ruban, Dmitry S; Wallace, David; Byrne, Richard W

2013-11-01

Indolent low-grade temporal lobe tumors may present with ictal panic that may be difficult to differentiate from psychogenic panic attacks. The current study aims to demonstrate the differences between the two disorders and help physicians generate a diagnostic paradigm. This was a retrospective study of 43 patients who underwent a temporal lobectomy between 1981 and 2008 for the treatment of intractable temporal lobe epilepsy secondary to low-grade neoplasms at Rush University Medical Center. A total of 10 patients in this group presented with ictal panic who were previously being treated for psychogenic panic attacks. Medical records were reviewed for age at seizure onset, duration of symptoms, lateralization of the epileptogenic zone, pathological diagnosis, and postsurgical seizure outcome according to the modified Engel classification. Neuropathologic findings of the 10 tumors were pleomorphic xanthoastrocytoma, ganglioglioma, oligodendroglioma, and dysembryoplastic neuroepithelial. The mean age of the patients undergoing surgery was 28 years (range, 15-49). The mean duration of panic symptoms prior to surgery was 9.8 years (range, 3-23). All patients had unprovoked ictal panic. None had symptoms suggestive of a brain tumor, such as signs of increased intracranial pressure or any focal neurologic deficit. In 5 of the patients, other symptoms associated with the ictal panic, including unusual sounds, nausea, automatism, uprising gastric sensation, and déjà vu were identified. Gross total resection of the lesion resulted in improved seizure outcome in all patients undergoing surgery. Patient follow-up was, on average, 7.4 years (range, 2-14) from time of surgery. Although similar, ictal panic from epilepsy and classic panic attacks are clinically distinguishable entities with different modalities of treatment. A careful history may help differentiate patients with ictal panic from those with psychogenic panic attacks and determine for which patients to obtain

Spatial and Temporal EEG-fMRI Changes During Preictal and Postictal Phases in a Patient With Posttraumatic Epilepsy.

PubMed

Storti, Silvia F; Del Felice, Alessandra; Formaggio, Emanuela; Boscolo Galazzo, Ilaria; Bongiovanni, Luigi G; Cerini, Roberto; Fiaschi, Antonio; Manganotti, Paolo

2015-07-01

The combined use of electroencephalography (EEG) and functional magnetic resonance imaging (EEG-fMRI) in epilepsy allows the noninvasive hemodynamic characterization of epileptic discharge-related neuronal activations. The aim of this study was to investigate pathophysiologic mechanisms underlying epileptic activity by exploring the spatial and temporal distribution of fMRI signal modifications during seizure in a single patient with posttraumatic epilepsy. EEG and fMRI data were acquired during two scanning sessions: a spontaneous critical episode was observed during the first, and interictal events were recorded during the second. The EEG-fMRI data were analyzed using the general linear model (GLM). Blood oxygenation level-dependent (BOLD) localization derived from the preictal and artifact-free postictal phase was concordant with the BOLD localization of the interictal epileptiform discharges identified in the second session, pointing to a left perilesional mesiofrontal area. Of note, BOLD signal modifications were already visible several seconds before seizure onset. In brief, BOLD activations from the preictal, postictal, and interictal epileptiform discharge analysis appear to be concordant with the clinically driven localization hypothesis, whereas a widespread network of activations is detected during the ictal phase in a partial seizure. © EEG and Clinical Neuroscience Society (ECNS) 2014.

Measuring the level and content of consciousness during epileptic seizures: the Ictal Consciousness Inventory.

PubMed

Cavanna, A E; Mula, M; Servo, S; Strigaro, G; Tota, G; Barbagli, D; Collimedaglia, L; Viana, M; Cantello, R; Monaco, F

2008-07-01

Ictal alterations of the level of general awareness and subjective content of consciousness play a pivotal role in the clinical phenomenology of epilepsy, and reflect the pathological involvement of different neurobiological substrates. However, no self-reported measures have been proposed for patients experiencing altered conscious states during seizures. This study describes the development and validation of a new scale for the quantitative assessment of the level and content of ictal consciousness, the Ictal Consciousness Inventory (ICI). The ICI is a 20-item questionnaire generated on the basis of interviews with patients, literature review, and consultation with experts. It was tested on a sample of 110 patients attending three different epilepsy clinics in Northern Italy, who also completed standardized clinical scales. Standard psychometric methods were used to demonstrate that this scale satisfies criteria for acceptability, reliability, and validity. The ICI is proposed as a user-friendly and clinically sound instrument for the measurement of ictal alterations of consciousness in patients with epilepsy.

Age-related gender differences in reporting ictal fear: analysis of case histories and review of the literature.

PubMed

Chiesa, Valentina; Gardella, Elena; Tassi, Laura; Canger, Raffaele; Lo Russo, Giorgio; Piazzini, Ada; Turner, Katherine; Canevini, Maria Paola

2007-12-01

To determine if there are age or gender-related differences in reporting fear as a symptom of epileptic seizure, all clinical charts of patients evaluated at the "C. Munari - Epilepsy Surgery Center" of Milan from 1990 to June 2005 were analyzed, looking for patients with ictal fear. Among the 2,530 clinical charts examined (1,330 male and 1,200 female), 265 patients were found with ictal fear (100 men, 165 women). The gender difference in reporting ictal fear was not so marked in the pediatric age group (98 girls, 74 boys), whereas in adult patients the difference was significant (158 women, 83 men). Interestingly, more men than women (14:3) had ictal fear during childhood that disappeared during adulthood. The literature review confirmed that ictal fear is significantly more common in women, though there is no gender difference in the pediatric age group.

Automatic and remote controlled ictal SPECT injection for seizure focus localization by use of a commercial contrast agent application pump.

PubMed

Feichtinger, Michael; Eder, Hans; Holl, Alexander; Körner, Eva; Zmugg, Gerda; Aigner, Reingard; Fazekas, Franz; Ott, Erwin

2007-07-01

In the presurgical evaluation of patients with partial epilepsy, the ictal single photon emission computed tomography (SPECT) is a useful noninvasive diagnostic tool for seizure focus localization. To achieve optimal SPECT scan quality, ictal tracer injection should be carried out as quickly as possible after the seizure onset and under highest safety conditions possible. Compared to the commonly used manual injection, an automatic administration of the radioactive tracer may provide higher quality standards for this procedure. In this study, therefore, we retrospectively analyzed efficiency and safety of an automatic injection system for ictal SPECT tracer application. Over a 31-month period, 26 patients underwent ictal SPECT by use of an automatic remote-controlled injection pump originally designed for CT-contrast agent application. Various factors were reviewed, including latency of ictal injection, radiation safety parameters, and ictal seizure onset localizing value. Times between seizure onset and tracer injection ranged between 3 and 48 s. In 21 of 26 patients ictal SPECT supported the localization of the epileptogenic focus in the course of the presurgical evaluation. In all cases ictal SPECT tracer injection was performed with a high degree of safety to patients and staff. Ictal SPECT by use of a remote-controlled CT-contrast agent injection system provides a high scan quality and is a safe and confirmatory presurgical evaluation technique in the epilepsy-monitoring unit.

Recurrence risk of ictal asystole in epilepsy.

PubMed

Hampel, Kevin G; Thijs, Roland D; Elger, Christian E; Surges, Rainer

2017-08-22

To determine the recurrence risk of ictal asystole (IA) and its determining factors in people with epilepsy. We performed a systematic review of published cases with IA in 3 databases and additionally searched our local database for patients with multiple seizures simultaneously recorded with ECG and EEG and at least one IA. IA recurrence risk was estimated by including all seizures without knowledge of the chronological order. Various clinical features were assessed by an individual patient data meta-analysis. A random mixed effect logistic regression model was applied to estimate the average recurrence risk of IA. Plausibility of the calculated IA recurrence risk was checked by analyzing the local dataset with available information in chronological order. Eighty patients with 182 IA in 537 seizures were included. Recurrence risk of IA amounted to 40% (95% confidence interval [CI] 32%-50%). None of the clinical factors (age, sex, type and duration of epilepsy, hemispheric lateralization, duration of IA per patient) appeared to have a significant effect on the short-term recurrence risk of IA. When considering the local dataset only, IA recurrence risk was estimated to 30% (95% CI 14%-53%). Information whether IA coincided with symptoms (i.e., syncope) or not was given in 60 patients: 100 out of 142 IAs were symptomatic. Our data suggest that in case of clinically suspected IA, the recording of 1 or 2 seizures is not sufficient to rule out IA. Furthermore, the high short-term recurrence risk favors aggressive treatment, including pacemaker implantation if seizure freedom cannot be achieved. Copyright © 2017 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.

Which EEG patterns in coma are nonconvulsive status epilepticus?

PubMed

Trinka, Eugen; Leitinger, Markus

2015-08-01

Nonconvulsive status epilepticus (NCSE) is common in patients with coma with a prevalence between 5% and 48%. Patients in deep coma may exhibit epileptiform EEG patterns, such as generalized periodic spikes, and there is an ongoing debate about the relationship of these patterns and NCSE. The purposes of this review are (i) to discuss the various EEG patterns found in coma, its fluctuations, and transitions and (ii) to propose modified criteria for NCSE in coma. Classical coma patterns such as diffuse polymorphic delta activity, spindle coma, alpha/theta coma, low output voltage, or burst suppression do not reflect NCSE. Any ictal patterns with a typical spatiotemporal evolution or epileptiform discharges faster than 2.5 Hz in a comatose patient reflect nonconvulsive seizures or NCSE and should be treated. Generalized periodic diacharges or lateralized periodic discharges (GPDs/LPDs) with a frequency of less than 2.5 Hz or rhythmic discharges (RDs) faster than 0.5 Hz are the borderland of NCSE in coma. In these cases, at least one of the additional criteria is needed to diagnose NCSE (a) subtle clinical ictal phenomena, (b) typical spatiotemporal evolution, or (c) response to antiepileptic drug treatment. There is currently no consensus about how long these patterns must be present to qualify for NCSE, and the distinction from nonconvulsive seizures in patients with critical illness or in comatose patients seems arbitrary. The Salzburg Consensus Criteria for NCSE [1] have been modified according to the Standardized Terminology of the American Clinical Neurophysiology Society [2] and validated in three different cohorts, with a sensitivity of 97.2%, a specificity of 95.9%, and a diagnostic accuracy of 96.3% in patients with clinical signs of NCSE. Their diagnostic utility in different cohorts with patients in deep coma has to be studied in the future. This article is part of a Special Issue entitled "Status Epilepticus". Copyright © 2015. Published by Elsevier Inc.

Influence of Time-Series Normalization, Number of Nodes, Connectivity and Graph Measure Selection on Seizure-Onset Zone Localization from Intracranial EEG.

PubMed

van Mierlo, Pieter; Lie, Octavian; Staljanssens, Willeke; Coito, Ana; Vulliémoz, Serge

2018-04-26

We investigated the influence of processing steps in the estimation of multivariate directed functional connectivity during seizures recorded with intracranial EEG (iEEG) on seizure-onset zone (SOZ) localization. We studied the effect of (i) the number of nodes, (ii) time-series normalization, (iii) the choice of multivariate time-varying connectivity measure: Adaptive Directed Transfer Function (ADTF) or Adaptive Partial Directed Coherence (APDC) and (iv) graph theory measure: outdegree or shortest path length. First, simulations were performed to quantify the influence of the various processing steps on the accuracy to localize the SOZ. Afterwards, the SOZ was estimated from a 113-electrodes iEEG seizure recording and compared with the resection that rendered the patient seizure-free. The simulations revealed that ADTF is preferred over APDC to localize the SOZ from ictal iEEG recordings. Normalizing the time series before analysis resulted in an increase of 25-35% of correctly localized SOZ, while adding more nodes to the connectivity analysis led to a moderate decrease of 10%, when comparing 128 with 32 input nodes. The real-seizure connectivity estimates localized the SOZ inside the resection area using the ADTF coupled to outdegree or shortest path length. Our study showed that normalizing the time-series is an important pre-processing step, while adding nodes to the analysis did only marginally affect the SOZ localization. The study shows that directed multivariate Granger-based connectivity analysis is feasible with many input nodes (> 100) and that normalization of the time-series before connectivity analysis is preferred.

Interictal EEG spikes identify the region of electrographic seizure onset in some, but not all, pediatric epilepsy patients.

PubMed

Marsh, Eric D; Peltzer, Bradley; Brown, Merritt W; Wusthoff, Courtney; Storm, Phillip B; Litt, Brian; Porter, Brenda E

2010-04-01

The role of sharps and spikes, interictal epileptiform discharges (IEDs), in guiding epilepsy surgery in children remains controversial, particularly with intracranial electroencephalography (IEEG). Although ictal recording is the mainstay of localizing epileptic networks for surgical resection, current practice dictates removing regions generating frequent IEDs if they are near the ictal onset zone. Indeed, past studies suggest an inconsistent relationship between IED and seizure-onset location, although these studies were based upon relatively short EEG epochs. We employ a previously validated, computerized spike detector to measure and localize IED activity over prolonged, representative segments of IEEG recorded from 19 children with intractable, mostly extratemporal lobe epilepsy. Approximately 8 h of IEEG, randomly selected 30-min segments of continuous interictal IEEG per patient, were analyzed over all intracranial electrode contacts. When spike frequency was averaged over the 16-time segments, electrodes with the highest mean spike frequency were found to be within the seizure-onset region in 11 of 19 patients. There was significant variability between individual 30-min segments in these patients, indicating that large statistical samples of interictal activity were required for improved localization. Low-voltage fast EEG at seizure onset was the only clinical factor predicting IED localization to the seizure-onset region. Our data suggest that automated IED detection over multiple representative samples of IEEG may be of utility in planning epilepsy surgery for children with intractable epilepsy. Further research is required to better determine which patients may benefit from this technique a priori.

SPECT measurements with /sup 99m/Tc-HM-PAO in focal epilepsy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ryding, E.; Rosen, I.; Elmqvist, D.

1988-12-01

The ability of SPECT measurements with (/sup 99m/Tc)-HM-PAO (Ceretec) to find the location of the epileptic focus was studied in patients under consideration for neurosurgical treatment for therapy-resistant focal epilepsy. The location of low (/sup 99m/Tc)-HM-PAO uptake regions found at interictal measurements, and of high (/sup 99m/Tc)-HM-PAO uptake regions found at ictal measurements, was compared to the findings of extensive ictal and interictal EEG examinations, and to the results of CT and MRT. While EEG revealed focal epileptic activity in all of the 14 patients, SPECT showed regional abnormalities in 13 (93%). CT and MRT showed abnormal findings in 30%.

Acute confusional state of unknown cause in the elderly: a study with continuous EEG monitoring.

PubMed

Naeije, Gilles; Gaspard, Nicolas; Depondt, Chantal; Pepersack, Thierry; Legros, Benjamin

2012-03-01

Acute confusional state (ACS) is a frequent cause of emergency consultation in the elderly. Many causes of ACS are also risk factors for seizures. Both non-convulsive seizures and status epilepticus can cause acute confusion. The yield of routine EEG may not be optimal in case of prolonged post-ictal confusion. We thus, sought to evaluate the yield of CEEG in identifying seizures in elderly patients with ACS of unknown origin. We reviewed our CEEG database for patients over 75 years with ACS and collected EEG, CEEG and clinical information. Thirty-one percent (15/48) of the CEEG performed in elderly patients were done for ACS. Routine EEG did not reveal any epileptic anomalies in 7/15 patients. Among those, CEEG identified interictal epileptiform discharges (IED) in 2 and NCSE in 1. In 8/15 patients, routine EEG revealed epileptiform abnormalities: 3 with IED (including 1 with periodic lateralized discharges), 3 with non-convulsive seizures (NCSz) and 2 with non-convulsive status epilepticus (NCSE). Among patients with only IED, CEEG revealed NCSz in 1 and NCSE in 2. This retrospective study suggests that NCSz and NCSE may account for more cases of ACS than what was previously thought. A single negative routine EEG does not exclude this diagnosis. Continuous EEG (CEEG) monitoring is more revealing than routine EEG for the detection of NCSE and NCSz in confused elderly. The presence of IED in the first routine EEG strongly suggests concomitant NCSz or NCSE. Prospective studies are required to further determine the role of CEEG monitoring in the assessment of ACS in the elderly and to establish the incidence of NCSz and NCSE in this setting. Copyright © 2012 Elsevier Inc. All rights reserved.

Paramedic Checklists do not Accurately Identify Post-ictal or Hypoglycaemic Patients Suitable for Discharge at the Scene.

PubMed

Tohira, Hideo; Fatovich, Daniel; Williams, Teresa A; Bremner, Alexandra; Arendts, Glenn; Rogers, Ian R; Celenza, Antonio; Mountain, David; Cameron, Peter; Sprivulis, Peter; Ahern, Tony; Finn, Judith

2016-06-01

to hypoglycemia. The checklists did not accurately identify patients suitable for discharge at the scene within the Emergency Medical Service. Patients who fulfilled the post-ictal checklist made more subsequent health care service requests within three days than those who did not. Both checklists showed similar occurrence of subsequent events to paramedics' decision, but the hypoglycemia checklist identified fewer patients who could be discharged at the scene than paramedics actually discharged. Reliance on these checklists may increase transportations to ED and delay initiation of appropriate treatment at a hospital. Tohira H , Fatovich D , Williams TA , Bremner A , Arendts G , Rogers IR , Celenza A , Mountain D , Cameron P , Sprivulis P , Ahern T , Finn J . Paramedic checklists do not accurately identify post-ictal or hypoglycaemic patients suitable for discharge at the scene. Prehosp Disaster Med. 2016;31(3):282-293.

Endorphin mediation of post-ictal effects of kindled seizures in rats.

PubMed

Kelsey, J E; Belluzzi, J D

1982-12-16

Brief electrical stimulation of the enkephalin-rich globus pallidus at 1-h intervals produced kindled, clonic seizures in rats as rapidly as similar stimulation of the amygdala. Massing the kindling trials at 10-min intervals inhibited the occurrence of subsequent seizures, especially following globus pallidus stimulation. Naloxone (20 mg/kg), an opiate receptor antagonist, reversed this post-ictal inhibition of seizures following massed trials, but had no effect on seizures kindled at 1-h intervals. Thus, endorphin-released during seizures do not appear to mediate the production of kindled seizures, but do appear to mediate the transient posts ictal inhibition of seizures.

Maternal care affects EEG properties of spike-wave seizures (including pre- and post ictal periods) in adult WAG/Rij rats with genetic predisposition to absence epilepsy.

PubMed

Sitnikova, Evgenia; Rutskova, Elizaveta M; Raevsky, Vladimir V

2016-10-01

WAG/Rij rats have a genetic predisposition to absence epilepsy and develop spontaneous spike-wave discharges in EEG during late ontogenesis (SWD, EEG manifestation of absence epilepsy). Changes in an environment during early postnatal ontogenesis can influence the genetically predetermined absence epilepsy. Here we examined the effect of maternal environment during weaning period on the EEG manifestation of absence epilepsy in adulthood. Experiments were performed in the offspring of WAG/Rij and Wistar rats. The newborn pups were fostered to dams of the same (in-fostering) or another strain (cross-fostering). Age-matched control WAG/Rij and Wistar rats were reared by their biological mothers. Absence seizures were uncommon in Wistar and were not aggravated in both in- and cross-fostered groups. In WAG/Rij rats, fewer SWD were found in the cross-fostered as compared to the in-fostered group. The cross-fostered WAG/Rij rats showed higher percentage of short-lasting SWD with duration <2s. The mean frequency of EEG at the beginning of SWD in the cross-fostered WAG/Rij rats was lower than in control (8.82 vs 9.25Hz), but it was higher in a period of 1.5s before and after SWD. It was concluded that a healthier maternal environment is able to alleviate genetically predetermined absence seizures in adulthood through changes in EEG rhythmic activity. Copyright © 2016 Elsevier Inc. All rights reserved.

Intrinsic connections within the pedunculopontine tegmental nucleus are critical to the elaboration of post-ictal antinociception.

PubMed

Mazzei-Silva, Elaine Cristina; de Oliveira, Rithiele Cristina; dos Anjos Garcia, Tayllon; Falconi-Sobrinho, Luiz Luciano; Almada, Rafael Carvalho; Coimbra, Norberto Cysne

2014-08-01

This study investigated the intrinsic connections of a key-structure of the endogenous pain inhibitory system, the pedunculopontine tegmental nucleus (PPTN), in post-ictal antinociceptive process through synaptic inactivation of the PPTN with cobalt chloride. Male Wistar rats (n = 6 or 7 per group), weighing 250-280 g, had the tail-flick baseline recorded and were submitted to a stereotaxic surgery for the introduction of a guide-cannula aiming at the PPTN. After 5 days of postoperative recovery, cobalt chloride (1 mM/0.2 µL) or physiological saline (0.2 µL) were microinjected into the PPTN and after 5 min, the tail-withdrawal latency was measured again at 0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, and 120 min after seizures evoked by intraperitoneal injection of pentylenetetrazole (64 mg/kg). The synaptic inactivation of PPTN decreased the post-ictal antinociceptive phenomenon, suggesting the involvement of PPTN intrinsic connections in the modulation of pain, during tonic-clonic seizures. These results showed that the PPTN may be crucially involved in the neural network that organizes the post-ictal analgesia. © 2014 Wiley Periodicals, Inc.

Ictal affective symptoms in temporal lobe epilepsy are related to gender and age.

PubMed

Toth, Vanda; Fogarasi, Andras; Karadi, Kazmer; Kovacs, Norbert; Ebner, Alois; Janszky, Jozsef

2010-07-01

We systematically analyzed the video-recorded and patient-reported, as well as positive and negative ictal affective symptoms (IAS) in temporal lobe epilepsy (TLE). Our aim was to assess (1) frequency, (2) gender effect, (3) lateralizing significance, (4) localizing value, and (5) prognostic significance in epilepsy surgery of IAS in patients with video-registered seizures. We reviewed ictal video recordings of 184 patients (99 women, aged 16-63). All patients had surgery for intractable TLE with video-recorded complex partial seizures (CPS) due to temporal lobe lesions visualized by high-resolution magnetic resonance imaging (MRI). Affective auras (AAs) were categorized into two groups: positive or negative. We registered AAs in 18% of patients: positive in 3%, negative in 15%. We saw ictal affective behavior (IAB) in 22% of patients; 10% had positive, whereas 14% had negative IAB. Two patients had both positive and negative IAB. AAs showed an association with IAB in case of fear expression versus fear auras (p = 0.018). IAB, especially negative IAB, occurred more often in women than in men. Patients with negative IAB were younger than others. We could not demonstrate an association between IAS and the localization, lateralization, or hemispheric dominance. Surgical outcome did not associate with IAS. Patient-reported and video-recorded negative-but not positive-affective signs are related to each other. Video-recorded negative AAs occur more often in women and young patients.

Recurrent epileptic Wernicke aphasia.

PubMed

Sahaya, Kinshuk; Dhand, Upinder K; Goyal, Munish K; Soni, Chetan R; Sahota, Pradeep K

2010-04-15

We report a patient with recurrent epileptic Wernicke aphasia who prior to this presentation, had been misdiagnosed as transient ischemic attacks for several years. This case report emphasizes the consideration of epileptic nature of aphasia when a clear alternate etiology is unavailable, even when EEG fails to show a clear ictal pattern. We also present a brief discussion of previously reported ictal aphasias. Copyright 2010 Elsevier B.V. All rights reserved.

Status gelasticus after temporal lobectomy: ictal FDG-PET findings and the question of dual pathology involving hypothalamic hamartomas.

PubMed

Palmini, Andre; Van Paesschen, Wim; Dupont, Patrick; Van Laere, Koen; Van Driel, Guido

2005-08-01

To present the first ictal fluorodeoxyglucose-positron emission tomography (FDG-PET) evidence of the hypothalamic origin of gelastic seizures in a patient with a hypothalamic hamartoma (HH) and to raise the issue of true dual pathology related to this entity. Ictal FDG-PET was acquired during an episode of status gelasticus with preserved consciousness, in a patient previously operated on for complex partial seizures (CPSs) due to a temporal lobe epileptogenic cyst. Ictal hypermetabolism was localized to the region of the HH during the status gelasticus. CPSs had been completely eliminated after temporal lobe surgery. Ictal FDG-PET independently confirmed that gelastic seizures in patients with HH do originate in the diencephalic lesion. An HH may coexist with another epileptogenic lesion, in a context of dual pathology.

In patients suffering from major depressive disorders, quantitative EEG showed favorable changes in left and right prefrontal cortex.

PubMed

Haghighi, Mohammad; Ludyga, Sebastian; Rahimi, Boshra; Jahangard, Leila; Ahmadpanah, Mohammad; Torabian, Saadat; Esnaashari, Farzaneh; Nazaribadie, Marzieh; Bajoghli, Hafez; Sadeghi Bahmani, Dena; Holsboer-Trachsler, Edith; Brand, Serge

2017-05-01

Patients suffering from major depressive disorders (MDD) report anhedonia, low concentration and lack of goal-oriented behavior. Data from imaging and quantitative EEG (QEEG) studies show an asymmetry in the prefrontal cortex (PFC), with lower left as compared to right PFC-activity, associated with specific depression-related behavior. Cordance is a QEEG measurement, which combines absolute and relative power of EEG-spectra with strong correlations with regional perfusion. The aim of the present study was to investigate to what extent a four weeks lasting treatment with a standard SSRI had an influence on neuronal activation and MDD-related symptoms. Twenty patients suffering from severe MDD were treated with citalopram (40mg) for four consecutive weeks. At baseline and at the end of the treatment, patients underwent QEEG. Experts rated the degree of depression with the Hamilton Depression Rating Scale (HDRS). Over time, theta cordance increased over right ventromedial and left dorsolateral PFC, whereas alpha cordance decreased over dorsolateral PFC. Improvement in MDD-related symptoms was higher in patients showing decreased EEG theta cordance over right dorsal PFC and increased EEG alpha cordance over left dorsolateral PFC. In patients suffering from MDD, treatment response was associated with favorable changes in neuronal activity. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Nursing benefits of using an automated injection system for ictal brain single photon emission computed tomography.

PubMed

Vonhofen, Geraldine; Evangelista, Tonya; Lordeon, Patricia

2012-04-01

The traditional method of administering radioactive isotopes to pediatric patients undergoing ictal brain single photon emission computed tomography testing has been by manual injections. This method presents certain challenges for nursing, including time requirements and safety risks. This quality improvement project discusses the implementation of an automated injection system for isotope administration and its impact on staffing, safety, and nursing satisfaction. It was conducted in an epilepsy monitoring unit at a large urban pediatric facility. Results of this project showed a decrease in the number of nurses exposed to radiation and improved nursing satisfaction with the use of the automated injection system. In addition, there was a decrease in the number of nursing hours required during ictal brain single photon emission computed tomography testing.

On Quantitative Biomarkers of VNS Therapy Using EEG and ECG Signals.

PubMed

Ravan, Maryam; Sabesan, Shivkumar; D'Cruz, O'Neill

2017-02-01

The goal of this work is to objectively evaluate the effectiveness of neuromodulation therapies, specifically, Vagus nerve stimulation (VNS) in reducing the severity of seizures in patients with medically refractory epilepsy. Using novel quantitative features obtained from combination of electroencephalographic (EEG) and electrocardiographic (ECG) signals around seizure events in 16 patients who underwent implantation of closed-loop VNS therapy system, namely AspireSR, we evaluated if automated delivery of VNS at the time of seizure onset reduces the severity of seizures by reducing EEG spatial synchronization as well as the duration and magnitude of heart rate increase. Unsupervised classification was subsequently applied to test the discriminative ability and validity of these features to measure responsiveness to VNS therapy. Results of application of this methodology to compare 105 pre-VNS treatment and 107 post-VNS treatment seizures revealed that seizures that were acutely stimulated using VNS had a reduced ictal spread as well as reduced impact on cardiovascular function compared to the ones that occurred prior to any treatment. Furthermore, application of an unsupervised fuzzy-c-mean classifier to evaluate the ability of the combined EEG-ECG based features to classify pre and post-treatment seizures achieved a classification accuracy of 85.85%. These results indicate the importance of timely delivery of VNS to reduce seizure severity and thus help achieve better seizure control for patients with epilepsy. The proposed set of quantitative features could be used as potential biomarkers for predicting long-term response to VNS therapy.

Hippocampal effective synchronization values are not pre-seizure indicator without considering the state of the onset channels

PubMed Central

Shayegh, Farzaneh; Sadri, Saeed; Amirfattahi, Rassoul; Ansari-Asl, Karim; Bellanger, Jean-Jacques; Senhadji, Lotfi

2014-01-01

In this paper, a model-based approach is presented to quantify the effective synchrony between hippocampal areas from depth-EEG signals. This approach is based on the parameter identification procedure of a realistic Multi-Source/Multi-Channel (MSMC) hippocampal model that simulates the function of different areas of hippocampus. In the model it is supposed that the observed signals recorded using intracranial electrodes are generated by some hidden neuronal sources, according to some parameters. An algorithm is proposed to extract the intrinsic (solely relative to one hippocampal area) and extrinsic (coupling coefficients between two areas) model parameters, simultaneously, by a Maximum Likelihood (ML) method. Coupling coefficients are considered as the measure of effective synchronization. This work can be considered as an application of Dynamic Causal Modeling (DCM) that enables us to understand effective synchronization changes during transition from inter-ictal to pre -ictal state. The algorithm is first validated by using some synthetic datasets. Then by extracting the coupling coefficients of real depth-EEG signals by the proposed approach, it is observed that the coupling values show no significant difference between ictal, pre-ictal and inter-ictal states, i.e., either the increase or decrease of coupling coefficients has been observed in all states. However, taking the value of intrinsic parameters into account, pre-seizure state can be distinguished from inter-ictal state. It is claimed that seizures start to appear when there are seizure-related physiological parameters on the onset channel, and its coupling coefficient toward other channels increases simultaneously. As a result of considering both intrinsic and extrinsic parameters as the feature vector, inter-ictal, pre-ictal and ictal activities are discriminated from each other with an accuracy of 91.33% accuracy. PMID:25061815

Classification of ictal and seizure-free HRV signals with focus on lateralization of epilepsy.

PubMed

Behbahani, Soroor; Dabanloo, Nader Jafarnia; Nasrabadi, Ali Motie; Dourado, Antonio

2016-01-01

Epileptic onsets often affect the autonomic function of the body during a seizure, whether it is in ictal, interictal or post-ictal periods. The different effects of localization and lateralization of seizures on heart rate variability (HRV) emphasize the importance of autonomic function changes in epileptic patients. On the other hand, the detection of seizures is of primary interests in evaluating the epileptic patients. In the current paper, we analyzed the HRV signal to develop a reliable offline seizure-detection algorithm to focus on the effects of lateralization on HRV. We assessed the HRV during 5-min segments of continuous electrocardiogram (ECG) recording with a total number of 170 seizures occurred in 16 patients, composed of 86 left-sided and 84 right-sided focus seizures. Relatively high and low-frequency components of the HRV were computed using spectral analysis. Poincaré parameters of each heart rate time series considered as non-linear features. We fed these features to the Support Vector Machines (SVMs) to find a robust classification method to classify epileptic and non-epileptic signals. Leave One Out Cross-Validation (LOOCV) approach was used to demonstrate the consistency of the classification results. Our obtained classification accuracy confirms that the proposed scheme has a potential in classifying HRV signals to epileptic and non-epileptic classes. The accuracy rates for right-sided and left-sided focus seizures were obtained as 86.74% and 79.41%, respectively. The main finding of our study is that the patients with right-sided focus epilepsy showed more reduction in parasympathetic activity and more increase in sympathetic activity. It can be a marker of impaired vagal activity associated with increased cardiovascular risk and arrhythmias. Our results suggest that lateralization of the seizure onset zone could exert different influences on heart rate changes. A right-sided seizure would cause an ictal tachycardia whereas a left

A case study on Discrete Wavelet Transform based Hurst exponent for epilepsy detection.

PubMed

Madan, Saiby; Srivastava, Kajri; Sharmila, A; Mahalakshmi, P

2018-01-01

Epileptic seizures are manifestations of epilepsy. Careful analysis of EEG records can provide valuable insight and improved understanding of the mechanism causing epileptic disorders. The detection of epileptic form discharges in EEG is an important component in the diagnosis of epilepsy. As EEG signals are non-stationary, the conventional frequency and time domain analysis does not provide better accuracy. So, in this work an attempt has been made to provide an overview of the determination of epilepsy by implementation of Hurst exponent (HE)-based discrete wavelet transform techniques for feature extraction from EEG data sets obtained during ictal and pre ictal stages of affected person and finally classifying EEG signals using SVM and KNN Classifiers. The The highest accuracy of 99% is obtained using SVM.

Neural Connectivity in Epilepsy as Measured by Granger Causality.

PubMed

Coben, Robert; Mohammad-Rezazadeh, Iman

2015-01-01

Epilepsy is a chronic neurological disorder characterized by repeated seizures or excessive electrical discharges in a group of brain cells. Prevalence rates include about 50 million people worldwide and 10% of all people have at least one seizure at one time in their lives. Connectivity models of epilepsy serve to provide a deeper understanding of the processes that control and regulate seizure activity. These models have received initial support and have included measures of EEG, MEG, and MRI connectivity. Preliminary findings have shown regions of increased connectivity in the immediate regions surrounding the seizure foci and associated low connectivity in nearby regions and pathways. There is also early evidence to suggest that these patterns change during ictal events and that these changes may even by related to the occurrence or triggering of seizure events. We present data showing how Granger causality can be used with EEG data to measure connectivity across brain regions involved in ictal events and their resolution. We have provided two case examples as a demonstration of how to obtain and interpret such data. EEG data of ictal events are processed, converted to independent components and their dipole localizations, and these are used to measure causality and connectivity between these locations. Both examples have shown hypercoupling near the seizure foci and low causality across nearby and associated neuronal pathways. This technique also allows us to track how these measures change over time and during the ictal and post-ictal periods. Areas for further research into this technique, its application to epilepsy, and the formation of more effective therapeutic interventions are recommended.

Resected Brain Tissue, Seizure Onset Zone and Quantitative EEG Measures: Towards Prediction of Post-Surgical Seizure Control

PubMed Central

Andrzejak, Ralph G.; Hauf, Martinus; Pollo, Claudio; Müller, Markus; Weisstanner, Christian; Wiest, Roland; Schindler, Kaspar

2015-01-01

Background Epilepsy surgery is a potentially curative treatment option for pharmacoresistent patients. If non-invasive methods alone do not allow to delineate the epileptogenic brain areas the surgical candidates undergo long-term monitoring with intracranial EEG. Visual EEG analysis is then used to identify the seizure onset zone for targeted resection as a standard procedure. Methods Despite of its great potential to assess the epileptogenicty of brain tissue, quantitative EEG analysis has not yet found its way into routine clinical practice. To demonstrate that quantitative EEG may yield clinically highly relevant information we retrospectively investigated how post-operative seizure control is associated with four selected EEG measures evaluated in the resected brain tissue and the seizure onset zone. Importantly, the exact spatial location of the intracranial electrodes was determined by coregistration of pre-operative MRI and post-implantation CT and coregistration with post-resection MRI was used to delineate the extent of tissue resection. Using data-driven thresholding, quantitative EEG results were separated into normally contributing and salient channels. Results In patients with favorable post-surgical seizure control a significantly larger fraction of salient channels in three of the four quantitative EEG measures was resected than in patients with unfavorable outcome in terms of seizure control (median over the whole peri-ictal recordings). The same statistics revealed no association with post-operative seizure control when EEG channels contributing to the seizure onset zone were studied. Conclusions We conclude that quantitative EEG measures provide clinically relevant and objective markers of target tissue, which may be used to optimize epilepsy surgery. The finding that differentiation between favorable and unfavorable outcome was better for the fraction of salient values in the resected brain tissue than in the seizure onset zone is consistent

Spatio-temporal coupling of EEG signals in epilepsy

NASA Astrophysics Data System (ADS)

Senger, Vanessa; Müller, Jens; Tetzlaff, Ronald

2011-05-01

Approximately 1% of the world's population suffer from epileptic seizures throughout their lives that mostly come without sign or warning. Thus, epilepsy is the most common chronical disorder of the neurological system. In the past decades, the problem of detecting a pre-seizure state in epilepsy using EEG signals has been addressed in many contributions by various authors over the past two decades. Up to now, the goal of identifying an impending epileptic seizure with sufficient specificity and reliability has not yet been achieved. Cellular Nonlinear Networks (CNN) are characterized by local couplings of dynamical systems of comparably low complexity. Thus, they are well suited for an implementation as highly parallel analogue processors. Programmable sensor-processor realizations of CNN combine high computational power comparable to tera ops of digital processors with low power consumption. An algorithm allowing an automated and reliable detection of epileptic seizure precursors would be a"huge step" towards the vision of an implantable seizure warning device that could provide information to patients and for a time/event specific treatment directly in the brain. Recent contributions have shown that modeling of brain electrical activity by solutions of Reaction-Diffusion-CNN as well as the application of a CNN predictor taking into account values of neighboring electrodes may contribute to the realization of a seizure warning device. In this paper, a CNN based predictor corresponding to a spatio-temporal filter is applied to multi channel EEG data in order to identify mutual couplings for different channels which lead to a enhanced prediction quality. Long term EEG recordings of different patients are considered. Results calculated for these recordings with inter-ictal phases as well as phases with seizures will be discussed in detail.

Coprolalia as a manifestation of epileptic seizures.

PubMed

Massot-Tarrús, Andreu; Mousavi, Seyed Reza; Dove, Carin; Hayman-Abello S, Susan; Hayman-Abello, Brent; Derry, Paul A; Diosy, David C; McLachlan, Richard S; Burneo, Jorge G; Steven, David A; Mirsattari, Seyed M

2016-07-01

The aim of this study was to investigate the lateralizing and localizing value of ictal coprolalia and brain areas involved in its production. A retrospective search for patients manifesting ictal coprolalia was conducted in our EMU database. Continuous video-EEG recordings were reviewed, and EEG activity before and during coprolalia was analyzed using independent component analysis (ICA) technique and was compared to the seizures without coprolalia among the same patients. Nine patients were evaluated (five women), eight with intracranial video-EEG recordings (icVEEG). Four had frontal or temporal lesions, and five had normal MRIs. Six patients showed impairment in the language functions and five in the frontal executive tasks. Two hundred six seizures were reviewed (60.7% from icVEEG). Ictal coprolalia occurred in 46.6% of them, always associated with limbic auras or automatisms. They arose from the nondominant hemisphere in five patients, dominant hemisphere in three, and independently from the right and left hippocampus-parahippocampus in one. Electroencephalographic activity always involved orbitofrontal and/or mesial temporal regions of the nondominant hemisphere when coprolalia occurred. Independent component analysis of 31 seizures in seven patients showed a higher number of independent components in the nondominant hippocampus-parahippocampus before and during coprolalia and in the dominant lateral temporal region in those seizures without coprolalia (p=0.009). Five patients underwent surgery, and all five had an ILAE class 1 outcome. Ictal coprolalia occurs in both males and females with temporal or orbitofrontal epilepsy and has a limited lateralizing value to the nondominant hemisphere but can be triggered by seizures from either hemisphere. It involves activation of the paralimbic temporal-orbitofrontal network. Copyright © 2016 Elsevier Inc. All rights reserved.

Focal BOLD-fMRI changes in bicuculline-induced tonic-clonic seizures in the rat

PubMed Central

DeSalvo, Matthew N.; Schridde, Ulrich; Mishra, Asht M.; Motelow, Joshua E.; Purcaro, Michael J.; Danielson, Nathan; Bai, Xiaoxiao; Hyder, Fahmeed; Blumenfeld, Hal

2010-01-01

Generalized tonic-clonic seizures cause widespread physiological changes throughout the cerebral cortex and subcortical structures in the brain. Using combined blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) at 9.4 T and electroencephalography (EEG) these changes can be characterized with high spatiotemporal resolution. We studied BOLD changes in anesthetized Wistar rats during bicuculline-induced tonic-clonic seizures. Bicuculline, a GABAA receptor antagonist, was injected systemically and seizure activity was observed on EEG as high amplitude, high-frequency polyspike discharges followed by clonic paroxysmal activity of lower frequency, with mean electrographic seizure duration of 349 s. Our aim was to characterize the spatial localization, direction, and timing of BOLD signal changes during the pre-ictal, ictal and post-ictal periods. Group analysis was performed across seizures using paired t-maps of BOLD signal superimposed on high resolution anatomical images. Regional analysis was then performed using volumes of interest to quantify BOLD timecourses. In the pre-ictal period we found focal BOLD increases in specific areas of somatosensory cortex (S1, S2) and thalamus several seconds before seizure onset. During seizures we observed BOLD increases in cortex, brainstem and thalamus and BOLD decreases in the hippocampus. The largest ictal BOLD increases remained in the focal regions of somatosensory cortex showing pre-ictal increases. During the post-ictal period we observed widespread BOLD decreases. These findings support a model in which “generalized” tonic-clonic seizures begin with focal changes before electrographic seizure onset, which progress to non-uniform changes during seizures, possibly shedding light on the etiology and pathophysiology of similar seizures in humans. PMID:20079442

Infraslow status epilepticus: A new form of subclinical status epilepticus recorded in a child with Sturge-Weber syndrome.

PubMed

Bello-Espinosa, Luis E

2015-08-01

Analysis of infraslow EEG activity (ISA) has shown potential in the evaluation of patients with epilepsy and in the differentiation between focal and generalized epilepsies. Infraslow EEG activity analysis may also provide insights into the pathophysiology of refractory clinical and subclinical status epilepticus. The purpose of this report is to describe a girl with Sturge-Weber syndrome (SWS) who presented with a 96-h refractory encephalopathy and nonischemic hemiparesis and who was identified to have infraslow status epilepticus (ISSE), which successfully resolved after midazolam administration. The continuous EEG recording of a 5-year-old girl with known structural epilepsy due to Sturge-Weber syndrome is presented. The patient presented to the ED with acute confusion, eye deviation, and right hemiparesis similar to two previous admissions. Despite administration of lorazepam, fosphenytoin, phenobarbital, and valproic loads, the patient showed no improvement in the clinical condition after 48 h. The continuous video-EEG monitoring (VEM) showed continuous severe diffuse nonrhythmic asymmetric slowing but no apparent ictal activity on continuous conventional EEG recording settings. As brain CT, CTA, CTV, and complete MRI scans including DWI obtained within 72 h of presentation failed to demonstrate any ischemic changes, analysis of the EEG infraslow (ISA) activity was undertaken using LFF: 0.01 Hz and HFF: of 0.1 Hz, respectively. Continuous subclinical unilateral rhythmic ictal ISA was identified. This was only evident on the left hemisphere which correlated with the structural changes due to SWS. A trial of continuous 120 to 240 μg/kg/h of IV midazolam resulted in immediate resolution of the contralateral hemiparesis and encephalopathy. Continuous prolonged rhythmic ictal infraslow activity (ISA) can cause super-refractory subclinical focal status epilepticus. This has not been previously reported, and we propose that this be called infraslow status

De novo status epilepticus with isolated aphasia.

PubMed

Flügel, Dominique; Kim, Olaf Chan-Hi; Felbecker, Ansgar; Tettenborn, Barbara

2015-08-01

Sudden onset of aphasia is usually due to stroke. Rapid diagnostic workup is necessary if reperfusion therapy is considered. Ictal aphasia is a rare condition but has to be excluded. Perfusion imaging may differentiate acute ischemia from other causes. In dubious cases, EEG is required but is time-consuming and laborious. We report a case where we considered de novo status epilepticus as a cause of aphasia without any lesion even at follow-up. A 62-year-old right-handed woman presented to the emergency department after nurses found her aphasic. She had undergone operative treatment of varicosis 3 days earlier. Apart from hypertension and obesity, no cardiovascular risk factors and no intake of medication other than paracetamol were reported. Neurological examination revealed global aphasia and right pronation in the upper extremity position test. Computed tomography with angiography and perfusion showed no abnormalities. Electroencephalogram performed after the CT scan showed left-sided slowing with high-voltage rhythmic 2/s delta waves but no clear ictal pattern. Intravenous lorazepam did improve EEG slightly, while aphasia did not change. Lumbar puncture was performed which likely excluded encephalitis. Magnetic resonance imaging showed cortical pathological diffusion imaging (restriction) and cortical hyperperfusion in the left parietal region. Intravenous anticonvulsant therapy under continuous EEG resolved neurological symptoms. The patient was kept on anticonvulsant therapy. Magnetic resonance imaging after 6 months showed no abnormalities along with no clinical abnormalities. Magnetic resonance imaging findings were only subtle, and EEG was without clear ictal pattern, so the diagnosis of aphasic status remains with some uncertainty. However, status epilepticus can mimic stroke symptoms and has to be considered in patients with aphasia even when no previous stroke or structural lesions are detectable and EEG shows no epileptic discharges. Epileptic origin is

A comparison of continuous video-EEG monitoring and 30-minute EEG in an ICU.

PubMed

Khan, Omar I; Azevedo, Christina J; Hartshorn, Alendia L; Montanye, Justin T; Gonzalez, Juan C; Natola, Mark A; Surgenor, Stephen D; Morse, Richard P; Nordgren, Richard E; Bujarski, Krzysztof A; Holmes, Gregory L; Jobst, Barbara C; Scott, Rod C; Thadani, Vijay M

2014-12-01

To determine whether there is added benefit in detecting electrographic abnormalities from 16-24 hours of continuous video-EEG in adult medical/surgical ICU patients, compared to a 30-minute EEG. This was a prospectively enroled non-randomized study of 130 consecutive ICU patients for whom EEG was requested. For 117 patients, a 30-minute EEG was requested for altered mental state and/or suspected seizures; 83 patients continued with continuous video-EEG for 16-24 hours and 34 patients had only the 30-minute EEG. For 13 patients with prior seizures, continuous video-EEG was requested and was carried out for 16-24 hours. We gathered EEG data prospectively, and reviewed the medical records retrospectively to assess the impact of continuous video-EEG. A total of 83 continuous video-EEG recordings were performed for 16-24 hours beyond 30 minutes of routine EEG. All were slow, and 34% showed epileptiform findings in the first 30 minutes, including 2% with seizures. Over 16-24 hours, 14% developed new or additional epileptiform abnormalities, including 6% with seizures. In 8%, treatment was changed based on continuous video-EEG. Among the 34 EEGs limited to 30 minutes, almost all were slow and 18% showed epileptiform activity, including 3% with seizures. Among the 13 patients with known seizures, continuous video-EEG was slow in all and 69% had epileptiform abnormalities in the first 30 minutes, including 31% with seizures. An additional 8% developed epileptiform abnormalities over 16-24 hours. In 46%, treatment was changed based on continuous video-EEG. This study indicates that if continuous video-EEG is not available, a 30-minute EEG in the ICU has a substantial diagnostic yield and will lead to the detection of the majority of epileptiform abnormalities. In a small percentage of patients, continuous video-EEG will lead to the detection of additional epileptiform abnormalities. In a sub-population, with a history of seizures prior to the initiation of EEG recording

Concealed, Unobtrusive Ear-Centered EEG Acquisition: cEEGrids for Transparent EEG

PubMed Central

Bleichner, Martin G.; Debener, Stefan

2017-01-01

Electroencephalography (EEG) is an important clinical tool and frequently used to study the brain-behavior relationship in humans noninvasively. Traditionally, EEG signals are recorded by positioning electrodes on the scalp and keeping them in place with glue, rubber bands, or elastic caps. This setup provides good coverage of the head, but is impractical for EEG acquisition in natural daily-life situations. Here, we propose the transparent EEG concept. Transparent EEG aims for motion tolerant, highly portable, unobtrusive, and near invisible data acquisition with minimum disturbance of a user's daily activities. In recent years several ear-centered EEG solutions that are compatible with the transparent EEG concept have been presented. We discuss work showing that miniature electrodes placed in and around the human ear are a feasible solution, as they are sensitive enough to pick up electrical signals stemming from various brain and non-brain sources. We also describe the cEEGrid flex-printed sensor array, which enables unobtrusive multi-channel EEG acquisition from around the ear. In a number of validation studies we found that the cEEGrid enables the recording of meaningful continuous EEG, event-related potentials and neural oscillations. Here, we explain the rationale underlying the cEEGrid ear-EEG solution, present possible use cases and identify open issues that need to be solved on the way toward transparent EEG. PMID:28439233

Impact of Transient Acute Hypoxia on the Developing Mouse EEG

PubMed Central

Zanelli, S.; Goodkin, H.P.; Kowalski, S.; Kapur, J.

2015-01-01

Hypoxemic events are common in sick preterm and term infants and represent the most common cause of seizures in the newborn period. Neonatal seizures often lack clinical correlates and are only recognized by electroencephalogram (EEG). The mechanisms leading from a hypoxic/ischemic insult to acute seizures in neonates remain poorly understood. Further, the effects of hypoxia on EEG at various developmental stages have not been fully characterized in neonatal animals, in part due to technical challenges. We evaluated the impact of hypoxia on neonatal mouse EEG to define periods of increased susceptibility to seizures during postnatal development. Hippocampal and cortical electrodes were implanted stereotaxically in C57BL/6 mice from postnatal age 3 (P3) to P15. Following recovery, EEG recording were obtained during baseline, acute hypoxia (4% FiO2 for 4 min) and reoxygenation. In baseline recordings, maturation of EEG was characterized by the appearance of a more continuous background pattern that replaced alternating high and low amplitude activity. Clinical seizures during hypoxia were observed more frequently in younger animals (100% P3-4, 87.5% P5-6, 93% P7-8, 83% P9-10, 33% P11-12, 17% P15, r2=0.81) and also occurred at higher FiO2 in younger animals (11.2±1.1% P3-P6 vs. 8.9±0.8% P7-12, p<0.05). Background attenuation followed the initial hypoxemic seizure; progressive return to baseline during reoxygenation was observed in survivors. Electrographic seizures without clinical manifestations were observed during reoxygenation, again more commonly in younger animals (83% P3-4, 86% P5-6, 75% P7-8, 71% P9-10, 20% P11-12, r2=0.82). All P15 animals died with this duration and degree of hypoxia. Post-ictal abnormalities included burst attenuation and post-anoxic myoclonus and were more commonly seen in older animals. In summary, neonatal mice exposed to brief and severe hypoxia followed by rapid reoxygenation reliably develop seizures and the response to hypoxia

What can be found in scalp EEG spectrum beyond common frequency bands. EEG-fMRI study

NASA Astrophysics Data System (ADS)

Marecek, R.; Lamos, M.; Mikl, M.; Barton, M.; Fajkus, J.; I, Rektor; Brazdil, M.

2016-08-01

Objective. The scalp EEG spectrum is a frequently used marker of neural activity. Commonly, the preprocessing of EEG utilizes constraints, e.g. dealing with a predefined subset of electrodes or a predefined frequency band of interest. Such treatment of the EEG spectrum neglects the fact that particular neural processes may be reflected in several frequency bands and/or several electrodes concurrently, and can overlook the complexity of the structure of the EEG spectrum. Approach. We showed that the EEG spectrum structure can be described by parallel factor analysis (PARAFAC), a method which blindly uncovers the spatial-temporal-spectral patterns of EEG. We used an algorithm based on variational Bayesian statistics to reveal nine patterns from the EEG of 38 healthy subjects, acquired during a semantic decision task. The patterns reflected neural activity synchronized across theta, alpha, beta and gamma bands and spread over many electrodes, as well as various EEG artifacts. Main results. Specifically, one of the patterns showed significant correlation with the stimuli timing. The correlation was higher when compared to commonly used models of neural activity (power fluctuations in distinct frequency band averaged across a subset of electrodes) and we found significantly correlated hemodynamic fluctuations in simultaneously acquired fMRI data in regions known to be involved in speech processing. Further, we show that the pattern also occurs in EEG data which were acquired outside the MR machine. Two other patterns reflected brain rhythms linked to the attentional and basal ganglia large scale networks. The other patterns were related to various EEG artifacts. Significance. These results show that PARAFAC blindly identifies neural activity in the EEG spectrum and that it naturally handles the correlations among frequency bands and electrodes. We conclude that PARAFAC seems to be a powerful tool for analysis of the EEG spectrum and might bring novel insight to the

Relationship of number of seizures recorded on video-EEG to surgical outcome in refractory medial temporal lobe epilepsy

PubMed Central

Sainju, Rup Kamal; Wolf, Bethany Jacobs; Bonilha, Leonardo; Martz, Gabriel

2014-01-01

Introduction Surgical planning for refractory medial temporal lobe epilepsy (rMTLE) relies on seizure localization by ictal electroencephalography (EEG). Multiple factors impact the number of seizures recorded. We evaluated whether seizure freedom correlated to the number of seizures recorded, and the related factors. Methods We collected data for 32 patients with rMTLE who underwent anterior temporal lobectomy. Primary analysis evaluated number of seizures captured as a predictor of surgical outcome. Subsequent analyses explored factors that may seizure number. Results Number of seizures recorded did not predict seizure freedom. More seizures were recorded with more days of seizure occurrence (p<0.001), seizure clusters (p≤0.011) and poorly localized seizures (PLSz) (p=0.004). Regression modeling showed a trend for subjects with fewer recorded poorly localized seizures to have better surgical outcome (p=0.052). Conclusions Total number of recorded seizures does not predict surgical outcome. Patients with more PLSz may have worse outcome. PMID:22990726

Application of high-frequency Granger causality to analysis of epileptic seizures and surgical decision making.

PubMed

Epstein, Charles M; Adhikari, Bhim M; Gross, Robert; Willie, Jon; Dhamala, Mukesh

2014-12-01

In recent decades intracranial EEG (iEEG) recordings using increasing numbers of electrodes, higher sampling rates, and a variety of visual and quantitative analyses have indicated the presence of widespread, high frequency ictal and preictal oscillations (HFOs) associated with regions of seizure onset. Seizure freedom has been correlated with removal of brain regions generating pathologic HFOs. However, quantitative analysis of preictal HFOs has seldom been applied to the clinical problem of planning the surgical resection. We performed Granger causality (GC) analysis of iEEG recordings to analyze features of preictal seizure networks and to aid in surgical decision making. Ten retrospective and two prospective patients were chosen on the basis of individually stereotyped seizure patterns by visual criteria. Prospective patients were selected, additionally, for failure of those criteria to resolve apparent multilobar ictal onsets. iEEG was recorded at 500 or 1,000 Hz, using up to 128 surface and depth electrodes. Preictal and early ictal GC from individual electrodes was characterized by the strength of causal outflow, spatial distribution, and hierarchical causal relationships. In all patients we found significant, widespread preictal GC network activity at peak frequencies from 80 to 250 Hz, beginning 2-42 s before visible electrographic onset. In the two prospective patients, GC source/sink comparisons supported the exclusion of early ictal regions that were not the dominant causal sources, and contributed to planning of more limited surgical resections. Both patients have a class 1 outcome at 1 year. GC analysis of iEEG has the potential to increase understanding of preictal network activity, and to help improve surgical outcomes in cases of otherwise ambiguous iEEG onset. Wiley Periodicals, Inc. © 2014 International League Against Epilepsy.

Ictal Cardiac Ryhthym Abnormalities.

PubMed

Ali, Rushna

2016-01-01

Cardiac rhythm abnormalities in the context of epilepsy are a well-known phenomenon. However, they are under-recognized and often missed. The pathophysiology of these events is unclear. Bradycardia and asystole are preceded by seizure onset suggesting ictal propagation into the cortex impacting cardiac autonomic function, and the insula and amygdala being possible culprits. Sudden unexpected death in epilepsy (SUDEP) refers to the unanticipated death of a patient with epilepsy not related to status epilepticus, trauma, drowning, or suicide. Frequent refractory generalized tonic-clonic seizures, anti-epileptic polytherapy, and prolonged duration of epilepsy are some of the commonly identified risk factors for SUDEP. However, the most consistent risk factor out of these is an increased frequency of generalized tonic-clonic seizures (GTC). Prevention of SUDEP is extremely important in patients with chronic, generalized epilepsy. Since increased frequency of GTCS is the most consistently reported risk factor for SUDEP, effective seizure control is the most important preventive strategy.

Simultaneous trimodal PET-MR-EEG imaging: Do EEG caps generate artefacts in PET images?

PubMed

Rajkumar, Ravichandran; Rota Kops, Elena; Mauler, Jörg; Tellmann, Lutz; Lerche, Christoph; Herzog, Hans; Shah, N Jon; Neuner, Irene

2017-01-01

Trimodal simultaneous acquisition of positron emission tomography (PET), magnetic resonance imaging (MRI), and electroencephalography (EEG) has become feasible due to the development of hybrid PET-MR scanners. To capture the temporal dynamics of neuronal activation on a millisecond-by-millisecond basis, an EEG system is appended to the quantitative high resolution PET-MR imaging modality already established in our institute. One of the major difficulties associated with the development of simultaneous trimodal acquisition is that the components traditionally used in each modality can cause interferences in its counterpart. The mutual interferences of MRI components and PET components on PET and MR images, and the influence of EEG electrodes on functional MRI images have been studied and reported on. Building on this, this study aims to investigate the influence of the EEG cap on the quality and quantification of PET images acquired during simultaneous PET-MR measurements. A preliminary transmission scan study on the ECAT HR+ scanner, using an Iida phantom, showed visible attenuation effect due to the EEG cap. The BrainPET-MR emission images of the Iida phantom with [18F]Fluordeoxyglucose, as well as of human subjects with the EEG cap, did not show significant effects of the EEG cap, even though the applied attenuation correction did not take into account the attenuation of the EEG cap itself.

EEG in children with spelling disabilities.

PubMed

Byring, R F; Salmi, T K; Sainio, K O; Orn, H P

1991-10-01

A total of 23 13-year-old boys with spelling disabilities and 21 matched controls were studied. EEG was recorded for visual and quantitative analysis, including FFT band powers and normalized slope descriptors (NSD). Visual analysis showed general excess of slow activity, as well as an excess of temporal slow wave activity in the index group. Quantitative analysis showed low alpha and beta powers, and low "activity" and high "complexity" (NSD) in parieto-occipital derivations in the index group. Quantitative EEG (qEEG) parameter ratios between temporal and parieto-occipital derivations were increased in the index group, implying a lack of spatial differentiation in these EEGs. In covariance analysis the qEEG parameter differences between the index group and controls were partly explained by the neurotic traits made evident in psychological tests. This implies that psychopathological artifacts should be considered in qEEG examinations of children with cognitive handicaps. Differences in anterior/posterior qEEG ratios were, however, little affected by any confounding factors. Thus these qEEG ratios seem potentially useful in clinical assessments of children with learning disabilities.

Physiological artifacts in scalp EEG and ear-EEG.

PubMed

Kappel, Simon L; Looney, David; Mandic, Danilo P; Kidmose, Preben

2017-08-11

A problem inherent to recording EEG is the interference arising from noise and artifacts. While in a laboratory environment, artifacts and interference can, to a large extent, be avoided or controlled, in real-life scenarios this is a challenge. Ear-EEG is a concept where EEG is acquired from electrodes in the ear. We present a characterization of physiological artifacts generated in a controlled environment for nine subjects. The influence of the artifacts was quantified in terms of the signal-to-noise ratio (SNR) deterioration of the auditory steady-state response. Alpha band modulation was also studied in an open/closed eyes paradigm. Artifacts related to jaw muscle contractions were present all over the scalp and in the ear, with the highest SNR deteriorations in the gamma band. The SNR deterioration for jaw artifacts were in general higher in the ear compared to the scalp. Whereas eye-blinking did not influence the SNR in the ear, it was significant for all groups of scalps electrodes in the delta and theta bands. Eye movements resulted in statistical significant SNR deterioration in both frontal, temporal and ear electrodes. Recordings of alpha band modulation showed increased power and coherence of the EEG for ear and scalp electrodes in the closed-eyes periods. Ear-EEG is a method developed for unobtrusive and discreet recording over long periods of time and in real-life environments. This study investigated the influence of the most important types of physiological artifacts, and demonstrated that spontaneous activity, in terms of alpha band oscillations, could be recorded from the ear-EEG platform. In its present form ear-EEG was more prone to jaw related artifacts and less prone to eye-blinking artifacts compared to state-of-the-art scalp based systems.

Risk factors of postictal generalized EEG suppression in generalized convulsive seizures.

PubMed

Alexandre, Veriano; Mercedes, Blanca; Valton, Luc; Maillard, Louis; Bartolomei, Fabrice; Szurhaj, William; Hirsch, Edouard; Marchal, Cécile; Chassoux, Francine; Petit, Jérôme; Crespel, Arielle; Nica, Anca; Navarro, Vincent; Kahane, Philippe; De Toffol, Bertrand; Thomas, Pierre; Rosenberg, Sarah; Denuelle, Marie; Jonas, Jacques; Ryvlin, Philippe; Rheims, Sylvain

2015-11-03

To identify the clinical determinants of occurrence of postictal generalized EEG suppression (PGES) after generalized convulsive seizures (GCS). We reviewed the video-EEG recordings of 417 patients included in the REPO2MSE study, a multicenter prospective cohort study of patients with drug-resistant focal epilepsy. According to ictal semiology, we classified GCS into 3 types: tonic-clonic GCS with bilateral and symmetric tonic arm extension (type 1), clonic GCS without tonic arm extension or flexion (type 2), and GCS with unilateral or asymmetric tonic arm extension or flexion (type 3). Association between PGES and person-specific or seizure-specific variables was analyzed after correction for individual effects and the varying number of seizures. A total of 99 GCS in 69 patients were included. Occurrence of PGES was independently associated with GCS type (p < 0.001) and lack of early administration of oxygen (p < 0.001). Odds ratio (OR) for GCS type 1 in comparison with GCS type 2 was 66.0 (95% confidence interval [CI 5.4-801.6]). In GCS type 1, risk of PGES was significantly increased when the seizure occurred during sleep (OR 5.0, 95% CI 1.2-20.9) and when oxygen was not administered early (OR 13.4, 95% CI 3.2-55.9). The risk of PGES dramatically varied as a function of GCS semiologic characteristics. Whatever the type of GCS, occurrence of PGES was prevented by early administration of oxygen. © 2015 American Academy of Neurology.

A study of 43 patients with panayiotopoulos syndrome, a common and benign childhood seizure susceptibility.

PubMed

Lada, Christina; Skiadas, Konstantinos; Theodorou, Virginia; Loli, Nomiki; Covanis, Athanasios

2003-01-01

To determine prevalence, clinical, EEG features, and prognosis of Panayiotopoulos syndrome and to examine the proposition that clinical manifestations are more important than EEG findings. We analyzed retrospectively the clinical and EEG records of 1,340 children with one or more focal seizures seen in the last 18 years, supplemented with a prospective study from 1998. Panayiotopoulos syndrome was defined by clinical criteria, mainly ictal emesis, irrespective of EEG findings. We analyzed 43 of 90 patients with Panayiotopoulos syndrome who were seizure free >2 years. Girls predominated. Mean age at first seizure was 5 years. Seizures consisted mainly of autonomic manifestations; ictal emesis was often the first symptom, culminating in vomiting in 86%. Of nonautonomic manifestations, lateral eye deviation was the most common; visual symptoms were exceptional. Impairment of consciousness ensued in all seizures, half of which ended with hemi or generalized convulsions. Nearly 46.5% of cases had at least one seizure >30 min, constituting autonomic status epilepticus. Seizures during sleep (84%) were more common than those in wakefulness. EEG showed occipital spikes in 29 patients. Of the other 14 cases, five had extraoccipital abnormalities or brief generalized discharges, and nine had normal awake and sleep EEG. Prognosis was excellent. All 43 children have been free of seizures for > or =2 years, 53% having a single seizure, and 47%, an average two to three seizures. Panayiotopoulos syndrome is common and needs wider recognition. EEG shows occipital or extraoccipital abnormalities, is normal in one third of patients, and does not determine clinical manifestations or prognosis, which is excellent despite the high prevalence of lengthy seizures.

Seizure outcomes of temporal lobe epilepsy surgery in patients with normal MRI and without specific histopathology.

PubMed

Ivanovic, Jugoslav; Larsson, Pål G; Østby, Ylva; Hald, John; Krossnes, Bård K; Fjeld, Jan G; Pripp, Are H; Alfstad, Kristin Å; Egge, Arild; Stanisic, Milo

2017-05-01

Seizure outcome following surgery in pharmacoresistant temporal lobe epilepsy patients with normal magnetic resonance imaging and normal or non-specific histopathology is not sufficiently presented in the literature. In a retrospective design, we reviewed data of 263 patients who had undergone temporal lobe epilepsy surgery and identified 26 (9.9%) who met the inclusion criteria. Seizure outcomes were determined at 2-year follow-up. Potential predictors of Engel class I (satisfactory outcome) were identified by logistic regression analyses. Engel class I outcome was achieved in 61.5% of patients, 50% being completely seizure free (Engel class IA outcome). The strongest predictors of satisfactory outcome were typical ictal seizure semiology (p = 0.048) and localised ictal discharges on scalp EEG (p = 0.036). Surgery might be an effective treatment choice for the majority of these patients, although outcomes are less favourable than in patients with magnetic resonance imaging-defined lesional temporal lobe epilepsy. Typical ictal seizure semiology and localised ictal discharges on scalp EEG were predictors of Engel class I outcome.

Intracranial investigation of a patient with nodular heterotopia and hippocampal sclerosis: dealing with a dual pathology.

PubMed

Ladino, Lady Diana; Dash, Chelsea; Wu, Adam; Tellez-Zenteno, Jose Francisco

2017-06-01

The pre-operative assessment and surgical management of patients with dual pathology is challenging. We describe a patient with drug-resistant focal epilepsy with hippocampal sclerosis and extensive periventricular nodular heterotopia in the same hemisphere. The semiology, scalp EEG, and imaging were divergent, but the presence of focal interictal and ictal epileptic discharges of the putative ictal onset zone resulted in successful localization of the epileptogenic zone. A less aggressive resection was performed based on intracranial EEG recording. The patient has been seizure-free for three years since resection. Electroclinical hypotheses and challenges in defining the epileptogenic network are discussed.

Video electroencephalogram telemetry in temporal lobe epilepsy

PubMed Central

Mani, Jayanti

2014-01-01

Temporal lobe epilepsy (TLE) is the most commonly encountered medically refractory epilepsy. It is also the substrate of refractory epilepsy that gives the most gratifying results in any epilepsy surgery program, with a minimum use of resources. Correlation of clinical behavior and the ictal patterns during ictal behavior is mandatory for success at epilepsy surgery. Video electroencephalogram (EEG) telemetry achieves this goal and hence plays a pivotal role in pre-surgical assessment. The role of telemetry is continuously evolving with the advent of digital EEG technology, of high-resolution volumetric magnetic resonance imaging and other functional imaging techniques. Most of surgical selection in patients with TLE can be done with a scalp video EEG monitoring. However, the limitations of the scalp EEG technique demand invasive recordings in a selected group of TLE patients. This subset of the patients can be a challenge to the epileptologist. PMID:24791089

Ordinal patterns in epileptic brains: Analysis of intracranial EEG and simultaneous EEG-fMRI

NASA Astrophysics Data System (ADS)

Rummel, C.; Abela, E.; Hauf, M.; Wiest, R.; Schindler, K.

2013-06-01

Epileptic seizures are associated with high behavioral stereotypy of the patients. In the EEG of epilepsy patients characteristic signal patterns can be found during and between seizures. Here we use ordinal patterns to analyze EEGs of epilepsy patients and quantify the degree of signal determinism. Besides relative signal redundancy and the fraction of forbidden patterns we introduce the fraction of under-represented patterns as a new measure. Using the logistic map, parameter scans are performed to explore the sensitivity of the measures to signal determinism. Thereafter, application is made to two types of EEGs recorded in two epilepsy patients. Intracranial EEG shows pronounced determinism peaks during seizures. Finally, we demonstrate that ordinal patterns may be useful for improving analysis of non-invasive simultaneous EEG-fMRI.

Classification of epileptic seizures using wavelet packet log energy and norm entropies with recurrent Elman neural network classifier.

PubMed

Raghu, S; Sriraam, N; Kumar, G Pradeep

2017-02-01

Electroencephalogram shortly termed as EEG is considered as the fundamental segment for the assessment of the neural activities in the brain. In cognitive neuroscience domain, EEG-based assessment method is found to be superior due to its non-invasive ability to detect deep brain structure while exhibiting superior spatial resolutions. Especially for studying the neurodynamic behavior of epileptic seizures, EEG recordings reflect the neuronal activity of the brain and thus provide required clinical diagnostic information for the neurologist. This specific proposed study makes use of wavelet packet based log and norm entropies with a recurrent Elman neural network (REN) for the automated detection of epileptic seizures. Three conditions, normal, pre-ictal and epileptic EEG recordings were considered for the proposed study. An adaptive Weiner filter was initially applied to remove the power line noise of 50 Hz from raw EEG recordings. Raw EEGs were segmented into 1 s patterns to ensure stationarity of the signal. Then wavelet packet using Haar wavelet with a five level decomposition was introduced and two entropies, log and norm were estimated and were applied to REN classifier to perform binary classification. The non-linear Wilcoxon statistical test was applied to observe the variation in the features under these conditions. The effect of log energy entropy (without wavelets) was also studied. It was found from the simulation results that the wavelet packet log entropy with REN classifier yielded a classification accuracy of 99.70 % for normal-pre-ictal, 99.70 % for normal-epileptic and 99.85 % for pre-ictal-epileptic.

Intravenous Levetiracetam in the Rat Pilocarpine-Induced Status Epilepticus Model: Behavioral, Physiological and Histological Studies

PubMed Central

Zheng, Yi; Moussally, Jon; Cash, Sydney S.; Karnam, Havisha B.; Cole, Andrew J.

2010-01-01

Purpose Status epilepticus is a neurological emergency associated with neuronal injury, lasting behavioral disturbance, and a high rate of mortality. Intravenous levetiracetam (LEV), an antiepileptic drug approved to treat partial seizures, has recently been introduced. We sought to determine the effect of LEV administered intravenously in a chemoconvulsant model of status epilepticus. Methods We examined the effect of intravenous LEV in the rat lithium-pilocarpine model of status epilepticus. Ten or 30 minutes after the onset of behavioral status epilepticus, animals were treated with LEV (200–1200 mg/kg i.v.) administered in a single bolus. Behavioral responses were recorded. Selected animals had continuous EEG recording before, during and after the administration of LEV. Some animals were sacrificed 24 h after the experiment and processed for histochemical assessment of neuronal injury. Results When administered 30 minutes after the onset of behavioral epileptic seizures, transient attenuation of ictal behavior was observed in animals treated with 800 mg/kg or more of LEV. The duration of behavioral attenuation increased sharply as the dose rose to 1000 mg/kg or higher, from a mean of 4 minutes to 23.6 minutes. When administered 10 minutes after seizure onset, 400 mg/kg of LEV resulted in transient ictal behavioral attenuation, and higher doses caused relatively longer periods of attenuation. Pretreatment with LEV prior to pilocarpine also delayed the onset of seizures. EEG recordings, however, showed no significant attenuation of ictal discharge. By contrast, TUNEL staining demonstrated less neuronal injury in hippocampii and other limbic structures in animals that responded behaviorally to LEV. Conclusions Intravenous administration of LEV in a chemoconvulsant model of status epilepticus results in attenuation of behavioral manifestations of seizure discharge and in reduction of neuronal injury but does not significantly alter ictal discharge recorded by EEG

Intravenous levetiracetam in the rat pilocarpine-induced status epilepticus model: behavioral, physiological and histological studies.

PubMed

Zheng, Yi; Moussally, Jon; Cash, Sydney S; Karnam, Havisha B; Cole, Andrew J

2010-01-01

Status epilepticus is a neurological emergency associated with neuronal injury, lasting behavioral disturbance, and a high rate of mortality. Intravenous levetiracetam (LEV), an anti-epileptic drug approved to treat partial seizures, has recently been introduced. We sought to determine the effect of LEV administered intravenously in a chemoconvulsant model of status epilepticus. We examined the effect of intravenous LEV in the rat lithium-pilocarpine model of status epilepticus. Ten or 30 min after the onset of behavioral status epilepticus, animals were treated with LEV (200-1200 mg/kg i.v.) administered in a single bolus. Behavioral responses were recorded. Selected animals had continuous EEG recording before, during and after the administration of LEV. Some animals were sacrificed 24 h after the experiment and processed for histochemical assessment of neuronal injury. When administered 30 min after the onset of behavioral epileptic seizures, transient attenuation of ictal behavior was observed in animals treated with 800 mg/kg or more of LEV. The duration of behavioral attenuation increased sharply as the dose rose to 1000 mg/kg or higher, from a mean of 4-23.6 min. When administered 10 min after seizure onset, 400 mg/kg of LEV resulted in transient ictal behavioral attenuation, and higher doses caused relatively longer periods of attenuation. Pretreatment with LEV prior to pilocarpine also delayed the onset of seizures. EEG recordings, however, showed no significant attenuation of ictal discharge. By contrast, TUNEL staining demonstrated less neuronal injury in hippocampii and other limbic structures in animals that responded behaviorally to LEV. Intravenous administration of LEV in a chemoconvulsant model of status epilepticus results in attenuation of behavioral manifestations of seizure discharge and in reduction of neuronal injury but does not significantly alter ictal discharge recorded by EEG. Copyright 2009 Elsevier Ltd. All rights reserved.

Abnormal EEG Power Spectra in Acute Transient Global Amnesia: A Quantitative EEG Study.

PubMed

Imperatori, Claudio; Farina, Benedetto; Todini, Federico; Di Blasi, Chiara; Mazzucchi, Edoardo; Brunetti, Valerio; Della Marca, Giacomo

2018-06-01

Transient global amnesia (TGA) is a clinical syndrome characterized by retrograde and anterograde amnesia without other neurological deficits. Although electroencephalography (EEG) methods are commonly used in both clinical and research setting with TGA patients, few studies have investigated neurophysiological pattern in TGA using quantitative EEG (qEEG). The main aim of the present study was to extend these previous findings by exploring EEG power spectra differences between patients with acute TGA and healthy controls using the exact low-resolution brain electromagnetic tomography software (eLORETA). EEG was recorded during 5 minutes of resting state. Sixteen patients (mean age: 66.81 ± 7.94 years) during acute TGA and 16 healthy subjects were enrolled. All patients showed hippocampal or parahippocampal signal abnormalities in diffusion-weighted magnetic resonance imaging performed from 2 to 5 days after the onset of TGA. Compared with healthy controls, TGA patients showed a decrease of theta power localized in the temporal lobe (Brodmann areas, BAs 21-22-38) and frontal lobe (BAs 8-9-44-45). A decrease of EEG beta power in the bilateral precuneus (BA 7) and in the bilateral postcentral gyrus (BAs 3-4-5) was also observed in TGA individuals. Taken together, our results could reflect the neurophysiological substrate of the severe impairment of both episodic memory and autobiographical memory which affect TGA patients during the acute phase.

Reliability of quantitative EEG (qEEG) measures and LORETA current source density at 30 days.

PubMed

Cannon, Rex L; Baldwin, Debora R; Shaw, Tiffany L; Diloreto, Dominic J; Phillips, Sherman M; Scruggs, Annie M; Riehl, Timothy C

2012-06-14

There is a growing interest for using quantitative EEG and LORETA current source density in clinical and research settings. Importantly, if these indices are to be employed in clinical settings then the reliability of these measures is of great concern. Neuroguide (Applied Neurosciences) is sophisticated software developed for the analyses of power, and connectivity measures of the EEG as well as LORETA current source density. To date there are relatively few data evaluating topographical EEG reliability contrasts for all 19 channels and no studies have evaluated reliability for LORETA calculations. We obtained 4 min eyes-closed and eyes-opened EEG recordings at 30-day intervals. The EEG was analyzed in Neuroguide and FFT power, coherence and phase was computed for traditional frequency bands (delta, theta, alpha and beta) and LORETA current source density was calculated in 1 Hz increments and summed for total power in eight regions of interest (ROI). In order to obtain a robust measure of reliability we utilized a random effects model with an absolute agreement definition. The results show very good reproducibility for total absolute power and coherence. Phase shows lower reliability coefficients. LORETA current source density shows very good reliability with an average 0.81 for ECB and 0.82 for EOB. Similarly, the eight regions of interest show good to very good agreement across time. Implications for future directions and use of qEEG and LORETA in clinical populations are discussed. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

DTI-based response-driven modeling of mTLE laterality.

PubMed

Nazem-Zadeh, Mohammad-Reza; Elisevich, Kost; Air, Ellen L; Schwalb, Jason M; Divine, George; Kaur, Manpreet; Wasade, Vibhangini S; Mahmoudi, Fariborz; Shokri, Saeed; Bagher-Ebadian, Hassan; Soltanian-Zadeh, Hamid

2016-01-01

To develop lateralization models for distinguishing between unilateral and bilateral mesial temporal lobe epilepsy (mTLE) and determining laterality in cases of unilateral mTLE. mTLE is the most common form of medically refractory focal epilepsy. Many mTLE patients fail to demonstrate an unambiguous unilateral ictal onset. Intracranial EEG (icEEG) monitoring can be performed to establish whether the ictal origin is unilateral or truly bilateral with independent bitemporal ictal origin. However, because of the expense and risk of intracranial electrode placement, much research has been done to determine if the need for icEEG can be obviated with noninvasive neuroimaging methods, such as diffusion tensor imaging (DTI). Fractional anisotropy (FA) was used to quantify microstructural changes reflected in the diffusivity properties of the corpus callosum, cingulum, and fornix, in a retrospective cohort of 31 patients confirmed to have unilateral (n = 24) or bilateral (n = 7) mTLE. All unilateral mTLE patients underwent resection with an Engel class I outcome. Eleven were reported to have hippocampal sclerosis on pathological analysis; nine had undergone prior icEEG. The bilateral mTLE patients had undergone icEEG demonstrating independent epileptiform activity in both right and left hemispheres. Twenty-three nonepileptic subjects were included as controls. In cases of right mTLE, FA showed significant differences from control in all callosal subregions, in both left and right superior cingulate subregions, and in forniceal crura. Comparison of right and left mTLE cases showed significant differences in FA of callosal genu, rostral body, and splenium and the right posteroinferior and superior cingulate subregions. In cases of left mTLE, FA showed significant differences from control only in the callosal isthmus. Significant differences in FA were identified when cases of right mTLE were compared with bilateral mTLE cases in the rostral and midbody callosal subregions

Somatosensory-evoked spikes on electroencephalography (EEG): longitudinal clinical and EEG aspects in 313 children.

PubMed

Fonseca, Lineu Corrêa; Tedrus, Gloria M A S

2012-01-01

Somatosensory-evoked spikes (ESp) are high-voltage potentials registered on the EEG, which accompany each of the percussions on the feet or hands. The objective of this research was to study the longitudinal clinical and EEG aspects of children with ESp. A total of 313 children, 53.7% male, showing ESp on the EEG and with an average initial age of 6.82 (range from 2 to 14 years) were followed for a mean period of 35.7 months. In the initial evaluation, 118 (37.7%) had a history of nonfebrile epileptic seizures (ES). Epileptiform activity (EA) was observed on the EEG in 61% and showed a significantly greater occurrence in children with ES than in those without (P = .000). Of the 118 showing seizures from the start, 53 (44.9%) continued to have seizures; of the 195 without seizures at the start, only 13 (6.67%) developed them. Thus, only 66 (21.1%) children showed ES during the follow-up. ESp disappeared in 237 (75.7%) cases and EA in 221 (70.6%). In the children with ES, it was found that the presence of EA on the first EEG did not indicate continuation of the ES throughout the remaining period, while the 13 children who presented their first ES in a later period showed a greater occurrence of EA on the initial EEG than those who did not develop ES (P = .001). Evidence of brain injury was observed in 43 (13.7%) children and was associated with a greater continuity of the ES during the study (P = .018). ESp, EA, and ES tend to disappear, suggesting an age-dependent phenomenon. The finding of ESp, particularly in the absence of any evidence of brain injury, indicates a low association with ES and benign outcome.

Evaluation of acute ischemic stroke using quantitative EEG: a comparison with conventional EEG and CT scan.

PubMed

Murri, L; Gori, S; Massetani, R; Bonanni, E; Marcella, F; Milani, S

1998-06-01

The sensitivity of quantitative electroencephalogram (EEG) was compared with that of conventional EEG in patients with acute ischaemic stroke. In addition, a correlation between quantitative EEG data and computerized tomography (CT) scan findings was carried out for all the areas of lesion in order to reassess the actual role of EEG in the evaluation of stroke. Sixty-five patients were tested with conventional and quantitative EEG within 24 h from the onset of neurological symptoms, whereas CT scan was performed within 4 days from the onset of stroke. EEG was recorded from 19 electrodes placed upon the scalp according to the International 10-20 System. Spectral analysis was carried out on 30 artefact-free 4-sec epochs. For each channel absolute and relative power were calculated for the delta, theta, alpha and beta frequency bands and such data were successively represented in colour-coded maps. Ten patients with extensive lesions documented by CT scan were excluded. The results indicated that conventional EEG revealed abnormalities in 40 of 55 cases, while EEG mapping showed abnormalities in 46 of 55 cases: it showed focal abnormalities in five cases and nonfocal abnormalities in one of six cases which had appeared to be normal according to visual inspection of EEG. In a further 11 cases, where the conventional EEG revealed abnormalities in one hemisphere, the quantitative EEG and maps allowed to further localize abnormal activity in a more localized way. The sensitivity of both methods was higher for frontocentral, temporal and parieto-occipital cortical-subcortical infarctions than for basal ganglia and internal capsule lesions; however, quantitative EEG was more efficient for all areas of lesion in detecting cases that had appeared normal by visual inspection and was clearly superior in revealing focal abnormalities. When we considered the electrode related to which the maximum power of the delta frequency band is recorded, a fairly close correlation was found

Building an EEG-fMRI Multi-Modal Brain Graph: A Concurrent EEG-fMRI Study

PubMed Central

Yu, Qingbao; Wu, Lei; Bridwell, David A.; Erhardt, Erik B.; Du, Yuhui; He, Hao; Chen, Jiayu; Liu, Peng; Sui, Jing; Pearlson, Godfrey; Calhoun, Vince D.

2016-01-01

The topological architecture of brain connectivity has been well-characterized by graph theory based analysis. However, previous studies have primarily built brain graphs based on a single modality of brain imaging data. Here we develop a framework to construct multi-modal brain graphs using concurrent EEG-fMRI data which are simultaneously collected during eyes open (EO) and eyes closed (EC) resting states. FMRI data are decomposed into independent components with associated time courses by group independent component analysis (ICA). EEG time series are segmented, and then spectral power time courses are computed and averaged within 5 frequency bands (delta; theta; alpha; beta; low gamma). EEG-fMRI brain graphs, with EEG electrodes and fMRI brain components serving as nodes, are built by computing correlations within and between fMRI ICA time courses and EEG spectral power time courses. Dynamic EEG-fMRI graphs are built using a sliding window method, versus static ones treating the entire time course as stationary. In global level, static graph measures and properties of dynamic graph measures are different across frequency bands and are mainly showing higher values in eyes closed than eyes open. Nodal level graph measures of a few brain components are also showing higher values during eyes closed in specific frequency bands. Overall, these findings incorporate fMRI spatial localization and EEG frequency information which could not be obtained by examining only one modality. This work provides a new approach to examine EEG-fMRI associations within a graph theoretic framework with potential application to many topics. PMID:27733821

Uppermost synchronized generators of spike-wave activity are localized in limbic cortical areas in late-onset absence status epilepticus.

PubMed

Piros, Palma; Puskas, Szilvia; Emri, Miklos; Opposits, Gabor; Spisak, Tamas; Fekete, Istvan; Clemens, Bela

2014-03-01

Absence status (AS) epilepticus with generalized spike-wave pattern is frequently found in severely ill patients in whom several disease states co-exist. The cortical generators of the ictal EEG pattern and EEG functional connectivity (EEGfC) of this condition are unknown. The present study investigated the localization of the uppermost synchronized generators of spike-wave activity in AS. Seven patients with late-onset AS were investigated by EEG spectral analysis, LORETA (Low Resolution Electromagnetic Tomography) source imaging, and LSC (LORETA Source Correlation) analysis, which estimates cortico-cortical EEGfC among 23 ROIs (regions of interest) in each hemisphere. All the patients showed generalized ictal EEG activity. Maximum Z-scored spectral power was found in the 1-6 Hz and 12-14 Hz frequency bands. LORETA showed that the uppermost synchronized generators of 1-6 Hz band activity were localized in frontal and temporal cortical areas that are parts of the limbic system. For the 12-14 Hz band, abnormally synchronized generators were found in the antero-medial frontal cortex. Unlike the rather stereotyped spectral and LORETA findings, the individual EEGfC patterns were very dissimilar. The findings are discussed in the context of nonconvulsive seizure types and the role of the underlying cortical areas in late-onset AS. The diversity of the EEGfC patterns remains an enigma. Localizing the cortical generators of the EEG patterns contributes to understanding the neurophysiology of the condition. Copyright © 2013 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Focal epilepsy recruiting a generalised network of juvenile myoclonic epilepsy: a case report.

PubMed

Khaing, Myo; Lim, Kheng-Seang; Tan, Chong-Tin

2014-09-01

We report a patient with juvenile myoclonic epilepsy who subsequently developed temporal lobe epilepsy, which gradually became clinically dominant. Video telemetry revealed both myoclonic seizures and temporal lobe seizures. The temporal lobe seizures were accompanied by a focal recruiting rhythm with rapid generalisation on EEG, in which the ictal EEG pattern during the secondary generalised phase was morphologically similar to the ictal pattern during myoclonic seizures. The secondary generalised seizures of the focal epilepsy responded to sodium valproate, similar to the myoclonic epilepsy. In this rare case of coexistent Juvenile Myoclonic Epilepsy and Temporal lobe epilepsy, the possibility of focal epilepsy recruiting a generalised epileptic network was proposed and discussed.

Acute behavioral symptomatology at disappearance of epileptiform EEG abnormality. Paradoxical or "forced" normalization.

PubMed

Wolf, P

1991-01-01

Paradoxical or "forced" normalization of the EEG of patients with epilepsy was first described by Landolt in 1953. It refers to conditions where disappearance of epileptiform discharge from the routine scalp EEG is accompanied by some kind of behavioral disorder. The best known of these is a paranoid psychotic state in clear consciousness, which is also known as "alternative" psychosis. Thus, the issue is related to much older observations which indicated a "biological antagonism" between productive psychotic symptomatology and epileptic seizures, which led to the therapy of psychoses with artificially induced convulsions. Apart from psychotic episodes, the clinical manifestations of PN comprise dysphoric states, hysterical and hypochondriacal syndromes, affective disorders, and miscellanea. PN can be observed in both generalized and localization-related epilepsies as a rare complication. A subset where it is more frequently seen are in adults with persistent absence seizures when the latter become finally controlled by succinimide therapy. These seem to be the drugs with the highest hazard of precipitation of PN, but all other AEDs have also been suspected. Sleep disturbance by succinimide treatment may play a crucial role, but a variety of other factors are also involved, including psychosocial factors. The pathogenesis of this condition has given rise to some debate but remains still unresolved. Eleven of the most important hypotheses have been discussed and seem to converge into a more comprehensive hypothesis which basically assumes that, during PN, the epilepsy is still active subcortically, perhaps with spread of discharge along unusual pathways. This activity is supposed to provide energy and, possibly, some of the symptoms included in the psychotic syndrome. A critical clinical condition results, usually with a dysphoric symptomatology, where a development towards psychosis is impending but still depends on the presence or absence of a variety of risk

EEG activity during estral cycle in the rat.

PubMed

Corsi-Cabrera, M; Juárez, J; Ponce-de-León, M; Ramos, J; Velázquez, P N

1992-10-01

EEG activity was recorded from right and left parietal cortex in adult female rats daily during 6 days. Immediately after EEG recording vaginal smears were taken and were microscopically analyzed to determine the estral stage. Absolute and relative powers and interhemispheric correlation of EEG activity were calculated and compared between estral stages. Interhemispheric correlation was significantly lower during diestrous as compared to proestrous and estrous. Absolute and relative powers did not show significant differences between estral stages. Absolute powers of alpha1, alpha2, beta1 and beta2 bands were significantly higher at the right parietal cortex. Comparisons of the same EEG records with estral stages randomly grouped showed no significant differences for any of the EEG parameters. EEG activity is a sensitive tool to study functional changes related to the estral cycle.

Vigabatrin therapy implicates neocortical high frequency oscillations in an animal model of infantile spasms.

PubMed

Frost, James D; Le, John T; Lee, Chong L; Ballester-Rosado, Carlos; Hrachovy, Richard A; Swann, John W

2015-10-01

Abnormal high frequency oscillations (HFOs) in EEG recordings are thought to be reflections of mechanisms responsible for focal seizure generation in the temporal lobe and neocortex. HFOs have also been recorded in patients and animal models of infantile spasms. If HFOs are important contributors to infantile spasms then anticonvulsant drugs that suppress these seizures should decrease the occurrence of HFOs. In experiments reported here, we used long-term video/EEG recordings with digital sampling rates capable of capturing HFOs. We tested the effectiveness of vigabatrin (VGB) in the TTX animal model of infantile spasms. VGB was found to be quite effective in suppressing spasms. In 3 of 5 animals, spasms ceased after a daily two week treatment. In the other 2 rats, spasm frequency dramatically decreased but gradually increased following treatment cessation. In all animals, hypsarrhythmia was abolished by the last treatment day. As VGB suppressed the frequency of spasms, there was a decrease in the intensity of the behavioral spasms and the duration of the ictal EEG event. Analysis showed that there was a burst of high frequency activity at ictal onset, followed by a later burst of HFOs. VGB was found to selectively suppress the late HFOs of ictal complexes. VGB also suppressed abnormal HFOs recorded during the interictal periods. Thus VGB was found to be effective in suppressing both the generation of spasms and hypsarrhythmia in the TTX model. Vigabatrin also appears to preferentially suppress the generation of abnormal HFOs, thus implicating neocortical HFOs in the infantile spasms disease state. Copyright © 2015 Elsevier Inc. All rights reserved.

Vigabatrin Therapy Implicates Neocortical High Frequency Oscillations in an Animal Model of Infantile Spasms

PubMed Central

Frost, James D.; Le, John T.; Lee, Chong L.; Ballester-Rosado, Carlos; Hrachovy, Richard A.; Swann, John W.

2015-01-01

Abnormal high frequency oscillations (HFOs) in EEG recordings are thought to be reflections of mechanisms responsible for focal seizure generation in the temporal lobe and neocortex. HFOs have also been recorded in patients and animal models of infantile spasms. If HFOs are important contributors to infantile spasms then anticonvulsant drugs that suppress these seizures should decrease the occurrence of HFOs. In experiments reported here, we used long-term video/EEG recordings with digital sampling rates capable of capturing HFOs. We tested the effectiveness of vigabatrin (VGB) in the TTX animal model of infantile spasms. VGB was found to be quite effective in suppressing spasms. In 3 of 5 animals, spasms ceased after a daily two week treatment. In the other 2 rats, spasm frequency dramatically decreased but gradually increased following treatment cessation. In all animals, hypsarrhythmia was abolished by the last treatment day. As VGB suppressed the frequency of spasms, there was a decrease in the intensity of the behavioral spasms and the duration of the ictal EEG event. Analysis showed that there was a burst of high frequency activity at ictal onset, followed by a later burst of HFOs. VGB was found to selectively suppress the late HFOs of ictal complexes. VGB also suppressed abnormal HFOs recorded during the interictal periods. Thus VGB was found to be effective in suppressing both the generation of spasms and hypsarrhythmia in the TTX model. Vigabatrin also appears to preferentially suppress the generation of abnormal HFOs, thus implicating neocortical HFOs in the infantile spasms disease state. PMID:26026423

Comparison between Scalp EEG and Behind-the-Ear EEG for Development of a Wearable Seizure Detection System for Patients with Focal Epilepsy

PubMed Central

Gu, Ying; Cleeren, Evy; Dan, Jonathan; Claes, Kasper; Hunyadi, Borbála

2017-01-01

A wearable electroencephalogram (EEG) device for continuous monitoring of patients suffering from epilepsy would provide valuable information for the management of the disease. Currently no EEG setup is small and unobtrusive enough to be used in daily life. Recording behind the ear could prove to be a solution to a wearable EEG setup. This article examines the feasibility of recording epileptic EEG from behind the ear. It is achieved by comparison with scalp EEG recordings. Traditional scalp EEG and behind-the-ear EEG were simultaneously acquired from 12 patients with temporal, parietal, or occipital lobe epilepsy. Behind-the-ear EEG consisted of cross-head channels and unilateral channels. The analysis on Electrooculography (EOG) artifacts resulting from eye blinking showed that EOG artifacts were absent on cross-head channels and had significantly small amplitudes on unilateral channels. Temporal waveform and frequency content during seizures from behind-the-ear EEG visually resembled that from scalp EEG. Further, coherence analysis confirmed that behind-the-ear EEG acquired meaningful epileptic discharges similarly to scalp EEG. Moreover, automatic seizure detection based on support vector machine (SVM) showed that comparable seizure detection performance can be achieved using these two recordings. With scalp EEG, detection had a median sensitivity of 100% and a false detection rate of 1.14 per hour, while, with behind-the-ear EEG, it had a median sensitivity of 94.5% and a false detection rate of 0.52 per hour. These findings demonstrate the feasibility of detecting seizures from EEG recordings behind the ear for patients with focal epilepsy. PMID:29295522

Correlation of invasive EEG and scalp EEG.

PubMed

Ramantani, Georgia; Maillard, Louis; Koessler, Laurent

2016-10-01

Ever since the implementation of invasive EEG recordings in the clinical setting, it has been perceived that a considerable proportion of epileptic discharges present at a cortical level are missed by routine scalp EEG recordings. Several in vitro, in vivo, and simulation studies have been performed in the past decades aiming to clarify the interrelations of cortical sources with their scalp and invasive EEG correlates. The amplitude ratio of cortical potentials to their scalp EEG correlates, the extent of the cortical area involved in the discharge, as well as the localization of the cortical source and its geometry have been each independently linked to the recording of the cortical discharge with scalp electrodes. The need to elucidate these interrelations has been particularly imperative in the field of epilepsy surgery with its rapidly growing EEG-based localization technologies. Simultaneous multiscale EEG recordings with scalp, subdural and/or depth electrodes, applied in presurgical epilepsy workup, offer an excellent opportunity to shed some light to this fundamental issue. Whereas past studies have considered predominantly neocortical sources in the context of temporal lobe epilepsy, current investigations have included deep sources, as in mesial temporal epilepsy, as well as extratemporal sources. Novel computational tools may serve to provide surrogates for the shortcomings of EEG recording methodology and facilitate further developments in modern electrophysiology. Copyright © 2016 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Test-retest reliability of cognitive EEG

NASA Technical Reports Server (NTRS)

McEvoy, L. K.; Smith, M. E.; Gevins, A.

2000-01-01

OBJECTIVE: Task-related EEG is sensitive to changes in cognitive state produced by increased task difficulty and by transient impairment. If task-related EEG has high test-retest reliability, it could be used as part of a clinical test to assess changes in cognitive function. The aim of this study was to determine the reliability of the EEG recorded during the performance of a working memory (WM) task and a psychomotor vigilance task (PVT). METHODS: EEG was recorded while subjects rested quietly and while they performed the tasks. Within session (test-retest interval of approximately 1 h) and between session (test-retest interval of approximately 7 days) reliability was calculated for four EEG components: frontal midline theta at Fz, posterior theta at Pz, and slow and fast alpha at Pz. RESULTS: Task-related EEG was highly reliable within and between sessions (r0.9 for all components in WM task, and r0.8 for all components in the PVT). Resting EEG also showed high reliability, although the magnitude of the correlation was somewhat smaller than that of the task-related EEG (r0.7 for all 4 components). CONCLUSIONS: These results suggest that under appropriate conditions, task-related EEG has sufficient retest reliability for use in assessing clinical changes in cognitive status.

Is 'burned-out hippocampus' syndrome a distinct electro-clinical variant of MTLE-HS syndrome?

PubMed

Nair, Pradeep P; Menon, Ramshekhar N; Radhakrishnan, Ashalatha; Cherian, Ajit; Abraham, Mathew; Vilanilam, George; Kesavadas, C; Thomas, Bejoy; Alexander, Aley; Thomas, Sanjeev V

2017-04-01

To study the clinical, electrophysiological and imaging characteristics of patients with unilateral mesial temporal lobe epilepsy (MTLE) with contralateral ictal onset on scalp EEG, viz. 'burned-out hippocampus' syndrome (MTLE-BHS). MTLE-BHS was defined as TLE with unilateral hippocampal sclerosis (HS) without any dual pathology on MRI and contralateral ictal onset on scalp EEG, unlike in classical hippocampal sclerosis (HS). Consecutive "MTLE-BHS" patients evaluated at our Centre for Comprehensive Epilepsy Care from January 2005 to July 2014 were studied. Twenty-five cases of classic MTLE-HS operated during the same period were also analyzed for comparison. Seventeen patients were diagnosed to have MTLE-BHS. Mean age of seizure onset was 9.5±7.7years and the mean duration of epilepsy was18.2±7.3years. Epigastric aura was more common in MTLE-HS and fear, secondary generalized seizures and temporal polar changes on MRI were more prevalent in the MTLE-BHS subgroup. In the latter group, five (29%) exhibited seizure semiology and 2 (12%) had interictal discharges discordant to the side of MTS. Eight (47%) patients in the MTLE-BHS sub-group had normal medial temporal volume on Scheltens scale. Eight patients among MTLE-BHS underwent surgery (4 following intracranial monitoring that localized to the side of HS) with Engel class I outcome at 1year follow-up in 6 and Engel class II outcome in 2. Attenuation of ipsilateral fast ictal rhythms on scalp EEG as well as neocortical changes are likely to be deterministic factors for MTLE-BHS as opposed to the severity of hippocampal atrophy. Considering good post-operative outcomes, intracranial monitoring for surgical selection is not mandatory in MTLE-BHS despite discordant semiology and ictal onset, in the presence of inter-ictal, functional imaging and neuropsychology data concordant to the side of HS. Copyright © 2017 Elsevier Inc. All rights reserved.

The diagnostic value of EEGs in patients with syncope.

PubMed

Abubakr, Abuhuziefa; Wambacq, Ilse

2005-05-01

We retrospectively reviewed reports of all EEGs performed at the New Jersey Neuroscience Institute at JFK Hospital between January 1999 and December 2003. Of 9234 EEGs performed, 1094 were of patients with syncope. Among patients with syncope, 67.18% of the EEGs were normal and 28.15% showed diffuse and focal slowing. Only 1.46% of the EEGs showed epileptiform discharges (EDs). This is similar to the incidence of EDs in healthy adults. The presence of EDs did not change the management of these patients. Therefore, EEGs have very low yield and should not be routinely obtained in patients with syncope.

Technical and clinical analysis of microEEG: a miniature wireless EEG device designed to record high-quality EEG in the emergency department

PubMed Central

2012-01-01

Background We describe and characterize the performance of microEEG compared to that of a commercially available and widely used clinical EEG machine. microEEG is a portable, battery-operated, wireless EEG device, developed by Bio-Signal Group to overcome the obstacles to routine use of EEG in emergency departments (EDs). Methods The microEEG was used to obtain EEGs from healthy volunteers in the EEG laboratory and ED. The standard system was used to obtain EEGs from healthy volunteers in the EEG laboratory, and studies recorded from patients in the ED or ICU were also used for comparison. In one experiment, a signal splitter was used to record simultaneous microEEG and standard EEG from the same electrodes. Results EEG signal analysis techniques indicated good agreement between microEEG and the standard system in 66 EEGs recorded in the EEG laboratory and the ED. In the simultaneous recording the microEEG and standard system signals differed only in a smaller amount of 60 Hz noise in the microEEG signal. In a blinded review by a board-certified clinical neurophysiologist, differences in technical quality or interpretability were insignificant between standard recordings in the EEG laboratory and microEEG recordings from standard or electrode cap electrodes in the ED or EEG laboratory. The microEEG data recording characteristics such as analog-to-digital conversion resolution (16 bits), input impedance (>100MΩ), and common-mode rejection ratio (85 dB) are similar to those of commercially available systems, although the microEEG is many times smaller (88 g and 9.4 × 4.4 × 3.8 cm). Conclusions Our results suggest that the technical qualities of microEEG are non-inferior to a standard commercially available EEG recording device. EEG in the ED is an unmet medical need due to space and time constraints, high levels of ambient electrical noise, and the cost of 24/7 EEG technologist availability. This study suggests that using microEEG with an electrode cap

Comparison of Amplitude-Integrated EEG and Conventional EEG in a Cohort of Premature Infants.

PubMed

Meledin, Irina; Abu Tailakh, Muhammad; Gilat, Shlomo; Yogev, Hagai; Golan, Agneta; Novack, Victor; Shany, Eilon

2017-03-01

To compare amplitude-integrated EEG (aEEG) and conventional EEG (EEG) activity in premature neonates. Biweekly aEEG and EEG were simultaneously recorded in a cohort of infants born less than 34 weeks gestation. aEEG recordings were visually assessed for lower and upper border amplitude and bandwidth. EEG recordings were compressed for visual evaluation of continuity and assessed using a signal processing software for interburst intervals (IBI) and frequencies' amplitude. Ten-minute segments of aEEG and EEG indices were compared using regression analysis. A total of 189 recordings from 67 infants were made, from which 1697 aEEG/EEG pairs of 10-minute segments were assessed. Good concordance was found for visual assessment of continuity between the 2 methods. EEG IBI, alpha and theta frequencies' amplitudes were negatively correlated to the aEEG lower border while conceptional age (CA) was positively correlated to aEEG lower border ( P < .001). IBI and all frequencies' amplitude were positively correlated to the upper aEEG border ( P ≤ .001). CA was negatively correlated to aEEG span while IBI, alpha, beta, and theta frequencies' amplitude were positively correlated to the aEEG span. Important information is retained and integrated in the transformation of premature neonatal EEG to aEEG. aEEG recordings in high-risk premature neonates reflect reliably EEG background information related to continuity and amplitude.

Estimating short-run and long-run interaction mechanisms in interictal state.

PubMed

Ozkaya, Ata; Korürek, Mehmet

2010-04-01

We address the issue of analyzing electroencephalogram (EEG) from seizure patients in order to test, model and determine the statistical properties that distinguish between EEG states (interictal, pre-ictal, ictal) by introducing a new class of time series analysis methods. In the present study: firstly, we employ statistical methods to determine the non-stationary behavior of focal interictal epileptiform series within very short time intervals; secondly, for such intervals that are deemed non-stationary we suggest the concept of Autoregressive Integrated Moving Average (ARIMA) process modelling, well known in time series analysis. We finally address the queries of causal relationships between epileptic states and between brain areas during epileptiform activity. We estimate the interaction between different EEG series (channels) in short time intervals by performing Granger-causality analysis and also estimate such interaction in long time intervals by employing Cointegration analysis, both analysis methods are well-known in econometrics. Here we find: first, that the causal relationship between neuronal assemblies can be identified according to the duration and the direction of their possible mutual influences; second, that although the estimated bidirectional causality in short time intervals yields that the neuronal ensembles positively affect each other, in long time intervals neither of them is affected (increasing amplitudes) from this relationship. Moreover, Cointegration analysis of the EEG series enables us to identify whether there is a causal link from the interictal state to ictal state.

Lateralized hyperkinetic motor behavior.

PubMed

Krishnaiah, Balaji; Acharya, Jayant; Ahmed, Aiesha

2018-01-01

Seizures are followed by a post-ictal period, which is characterized by usual slowing of brain activity. This case report describes a 68-year old woman who presented with right-sided rhythmic, non-voluntary, semi-purposeful motor behavior that started 2 days after an episode of generalized seizure. Her initial electroencephalogram (EEG) showed beta activity with no evidence of epileptiform discharges. Computed tomography scan showed hypodensity in the left parieto-occipital region. Magnetic resonance imaging (MRI) showed restricted diffusion/fluid-attenuated inversion recovery hyperintensities in the left precentral and post-central gyrus. Unilateral compulsive motor behavior during the post-ictal state should be considered, and not confused with partial status epilepticus to avoid unnecessary treatment. Abnormal magnetic resonance imaging (MRI) findings, which are reversible, can help with the diagnostic and therapeutic approach.

Identifying auditory attention with ear-EEG: cEEGrid versus high-density cap-EEG comparison

NASA Astrophysics Data System (ADS)

Bleichner, Martin G.; Mirkovic, Bojana; Debener, Stefan

2016-12-01

Objective. This study presents a direct comparison of a classical EEG cap setup with a new around-the-ear electrode array (cEEGrid) to gain a better understanding of the potential of ear-centered EEG. Approach. Concurrent EEG was recorded from a classical scalp EEG cap and two cEEGrids that were placed around the left and the right ear. Twenty participants performed a spatial auditory attention task in which three sound streams were presented simultaneously. The sound streams were three seconds long and differed in the direction of origin (front, left, right) and the number of beats (3, 4, 5 respectively), as well as the timbre and pitch. The participants had to attend to either the left or the right sound stream. Main results. We found clear attention modulated ERP effects reflecting the attended sound stream for both electrode setups, which agreed in morphology and effect size. A single-trial template matching classification showed that the direction of attention could be decoded significantly above chance (50%) for at least 16 out of 20 participants for both systems. The comparably high classification results of the single trial analysis underline the quality of the signal recorded with the cEEGrids. Significance. These findings are further evidence for the feasibility of around the-ear EEG recordings and demonstrate that well described ERPs can be measured. We conclude that concealed behind-the-ear EEG recordings can be an alternative to classical cap EEG acquisition for auditory attention monitoring.

Identifying auditory attention with ear-EEG: cEEGrid versus high-density cap-EEG comparison.

PubMed

Bleichner, Martin G; Mirkovic, Bojana; Debener, Stefan

2016-12-01

This study presents a direct comparison of a classical EEG cap setup with a new around-the-ear electrode array (cEEGrid) to gain a better understanding of the potential of ear-centered EEG. Concurrent EEG was recorded from a classical scalp EEG cap and two cEEGrids that were placed around the left and the right ear. Twenty participants performed a spatial auditory attention task in which three sound streams were presented simultaneously. The sound streams were three seconds long and differed in the direction of origin (front, left, right) and the number of beats (3, 4, 5 respectively), as well as the timbre and pitch. The participants had to attend to either the left or the right sound stream. We found clear attention modulated ERP effects reflecting the attended sound stream for both electrode setups, which agreed in morphology and effect size. A single-trial template matching classification showed that the direction of attention could be decoded significantly above chance (50%) for at least 16 out of 20 participants for both systems. The comparably high classification results of the single trial analysis underline the quality of the signal recorded with the cEEGrids. These findings are further evidence for the feasibility of around the-ear EEG recordings and demonstrate that well described ERPs can be measured. We conclude that concealed behind-the-ear EEG recordings can be an alternative to classical cap EEG acquisition for auditory attention monitoring.

Ictal SPECT in patients with rapid eye movement sleep behaviour disorder.

PubMed

Mayer, Geert; Bitterlich, Marion; Kuwert, Torsten; Ritt, Philipp; Stefan, Hermann

2015-05-01

Rapid eye movement sleep behaviour disorder is a rapid eye movement parasomnia clinically characterized by acting out dreams due to disinhibition of muscle tone in rapid eye movement sleep. Up to 80-90% of the patients with rapid eye movement sleep behaviour disorder develop neurodegenerative disorders within 10-15 years after symptom onset. The disorder is reported in 45-60% of all narcoleptic patients. Whether rapid eye movement sleep behaviour disorder is also a predictor for neurodegeneration in narcolepsy is not known. Although the pathophysiology causing the disinhibition of muscle tone in rapid eye movement sleep behaviour disorder has been studied extensively in animals, little is known about the mechanisms in humans. Most of the human data are from imaging or post-mortem studies. Recent studies show altered functional connectivity between substantia nigra and striatum in patients with rapid eye movement sleep behaviour disorder. We were interested to study which regions are activated in rapid eye movement sleep behaviour disorder during actual episodes by performing ictal single photon emission tomography. We studied one patient with idiopathic rapid eye movement sleep behaviour disorder, one with Parkinson's disease and rapid eye movement sleep behaviour disorder, and two patients with narcolepsy and rapid eye movement sleep behaviour disorder. All patients underwent extended video polysomnography. The tracer was injected after at least 10 s of consecutive rapid eye movement sleep and 10 s of disinhibited muscle tone accompanied by movements registered by an experienced sleep technician. Ictal single photon emission tomography displayed the same activation in the bilateral premotor areas, the interhemispheric cleft, the periaqueductal area, the dorsal and ventral pons and the anterior lobe of the cerebellum in all patients. Our study shows that in patients with Parkinson's disease and rapid eye movement sleep behaviour disorder-in contrast to wakefulness

Nicotinic and muscarinic cholinergic receptors are recruited by acetylcholine-mediated neurotransmission within the locus coeruleus during the organisation of post-ictal antinociception.

PubMed

de Oliveira, Rithiele Cristina; de Oliveira, Ricardo; Biagioni, Audrey Franceschi; Falconi-Sobrinho, Luiz Luciano; Dos Anjos-Garcia, Tayllon; Coimbra, Norberto Cysne

2016-10-01

Post-ictal antinociception is characterised by an increase in the nociceptive threshold that accompanies tonic and tonic-clonic seizures (TCS). The locus coeruleus (LC) receives profuse cholinergic inputs from the pedunculopontine tegmental nucleus. Different concentrations (1μg, 3μg and 5μg/0.2μL) of the muscarinic cholinergic receptor antagonist atropine and the nicotinic cholinergic receptor antagonist mecamylamine were microinjected into the LC of Wistar rats to investigate the role of cholinergic mechanisms in the severity of TCS and the post-ictal antinociceptive response. Five minutes later, TCS were induced by systemic administration of pentylenetetrazole (PTZ) (64mg/kg). Seizures were recorded inside the open field apparatus for an average of 10min. Immediately after seizures, the nociceptive threshold was recorded for 130min using the tail-flick test. Pre-treatment of the LC with 1μg, 3μg and 5μg/0.2μL concentrations of both atropine and mecamylamine did not cause a significant effect on seizure severity. However, the same treatments decreased the post-ictal antinociceptive phenomenon. In addition, mecamylamine caused an earlier decrease in the post-ictal antinociception compared to atropine. These results suggest that muscarinic and mainly nicotinic cholinergic receptors of the LC are recruited to organise tonic-clonic seizure-induced antinociception. Copyright © 2016 Elsevier Inc. All rights reserved.

Combined EEG/MEG Can Outperform Single Modality EEG or MEG Source Reconstruction in Presurgical Epilepsy Diagnosis

PubMed Central

Aydin, Ümit; Vorwerk, Johannes; Dümpelmann, Matthias; Küpper, Philipp; Kugel, Harald; Heers, Marcel; Wellmer, Jörg; Kellinghaus, Christoph; Haueisen, Jens; Rampp, Stefan; Stefan, Hermann; Wolters, Carsten H.

2015-01-01

We investigated two important means for improving source reconstruction in presurgical epilepsy diagnosis. The first investigation is about the optimal choice of the number of epileptic spikes in averaging to (1) sufficiently reduce the noise bias for an accurate determination of the center of gravity of the epileptic activity and (2) still get an estimation of the extent of the irritative zone. The second study focuses on the differences in single modality EEG (80-electrodes) or MEG (275-gradiometers) and especially on the benefits of combined EEG/MEG (EMEG) source analysis. Both investigations were validated with simultaneous stereo-EEG (sEEG) (167-contacts) and low-density EEG (ldEEG) (21-electrodes). To account for the different sensitivity profiles of EEG and MEG, we constructed a six-compartment finite element head model with anisotropic white matter conductivity, and calibrated the skull conductivity via somatosensory evoked responses. Our results show that, unlike single modality EEG or MEG, combined EMEG uses the complementary information of both modalities and thereby allows accurate source reconstructions also at early instants in time (epileptic spike onset), i.e., time points with low SNR, which are not yet subject to propagation and thus supposed to be closer to the origin of the epileptic activity. EMEG is furthermore able to reveal the propagation pathway at later time points in agreement with sEEG, while EEG or MEG alone reconstructed only parts of it. Subaveraging provides important and accurate information about both the center of gravity and the extent of the epileptogenic tissue that neither single nor grand-averaged spike localizations can supply. PMID:25761059

Involvement of 5-HT(2) serotonergic receptors of the nucleus raphe magnus and nucleus reticularis gigantocellularis/paragigantocellularis complex neural networks in the antinociceptive phenomenon that follows the post-ictal immobility syndrome.

PubMed

de Oliveira, Rithiele Cristina; de Oliveira, Ricardo; Ferreira, Célio Marcos Dos Reis; Coimbra, Norberto Cysne

2006-09-01

The post-ictal immobility syndrome is followed by a significant increase in the nociceptive thresholds in animals and men. In this interesting post-ictal behavioral response, endogenous opioid peptides-mediated mechanisms, as well as cholinergic-mediated antinociceptive processes, have been suggested. However, considering that many serotonergic descending pathways have been implicated in antinociceptive reactions, the aim of the present work is to investigate the involvement of 5-HT(2)-serotonergic receptor subfamily in the post-ictal antinociception. The analgesia was measured by the tail-flick test in seven or eight Wistar rats per group. Convulsions were followed by statistically significant increase in the tail-flick latencies (TFL), at least for 120 min of the post-ictal period. Male Wistar rats were submitted to stereotaxic surgery for introduction of a guide-cannula in the rhombencephalon, aiming either the nucleus raphe magnus (NRM) or the gigantocellularis complex. In independent groups of animals, these nuclei were neurochemically lesioned with a unilateral microinjection of ibotenic acid (1.0 microg/0.2 microL). The neuronal damage of either the NRM or nucleus reticularis gigantocellularis/paragigantocellularis complex decreased the post-ictal analgesia. Also, in other independent groups, central administration of ritanserin (5.0 microg/0.2 microL) or physiological saline into each of the reticular formation nuclei studied caused a statistically significant decrease in the TFL of seizing animals, as compared to controls, in all post-ictal periods studied. These results indicate that serotonin input-connected neurons of the pontine and medullarly reticular nuclei may be involved in the post-ictal analgesia.

EEG in Sarcoidosis Patients Without Neurological Findings.

PubMed

Bilgin Topçuoğlu, Özgür; Kavas, Murat; Öztaş, Selahattin; Arınç, Sibel; Afşar, Gülgün; Saraç, Sema; Midi, İpek

2017-01-01

Sarcoidosis is a multisystem granulomatous disease affecting nervous system in 5% to 10% of patients. Magnetic resonance imaging (MRI) is accepted as the most sensitive method for detecting neurosarcoidosis. However, the most common findings in MRI are the nonspecific white matter lesions, which may be unrelated to sarcoidosis and can occur because of hypertension, diabetes mellitus, smoking, and other inflammatory or infectious disorders, as well. Autopsy studies report more frequent neurological involvement than the ante mortem studies. The aim of this study is to assess electroencephalography (EEG) in sarcoidosis patients without neurological findings in order to display asymptomatic neurological dysfunction. We performed EEG on 30 sarcoidosis patients without diagnosis of neurosarcoidosis or prior neurological comorbidities. Fourteen patients (46.7%) showed intermittant focal and/or generalized slowings while awake and not mentally activated. Seven (50%) of these 14 patients with EEG slowings had nonspecific white matter changes while the other half showed EEG slowings in the absence of MRI changes. We conclude that EEG slowings, when normal variants (psychomotor variant, temporal theta of elderly, frontal theta waves) are eliminated, may be an indicator of dysfunction in brain activity even in the absence of MRI findings. Hence, EEG may contribute toward detecting asymptomatic neurological dysfunction or probable future neurological involvement in sarcoidosis patients. © EEG and Clinical Neuroscience Society (ECNS) 2016.

Frequent sleep-related bitemporal focal seizures in transient epileptic amnesia syndrome: Evidence from ictal video-EEG.

PubMed

Burkholder, David B; Jones, Amy L; Jones, David T; Fabris, Rachel R; Britton, Jeffrey W; Lagerlund, Terrence D; So, Elson L; Cascino, Gregory D; Worrell, Gregory A; Shin, Cheolsu; St Louis, Erik K

2017-06-01

Two patients who shared similar presenting clinical features of anterograde and retrograde autobiographical amnesia typical of transient epileptic amnesia (TEA) underwent prolonged video electroencephalogram (VEEG) monitoring and were found to have sleep-activated epileptiform activity and frequent subclinical bitemporal seizures predominantly during sleep. Case 1 is a 59-year-old woman whose presenting complaint was memory impairment. Over 18 months, she had three distinct 8-h-long episodes of confusion and disorientation with persistent anterograde and retrograde autobiographical amnesia. VEEG recorded frequent interictal bitemporal sharp waves confined to sleep, and 14 subclinical seizures, also mostly during sleep. Case 2 is a 50-year-old woman with known focal epilepsy also presented with memory complaints. Over the course of 1 year, she had two discrete 2-h-long episodes of amnesia, with ongoing anterograde and retrograde autobiographical amnesia. VEEG recorded independent bitemporal sharp waves, and 14 subclinical seizures during sleep and drowsiness. Memory impairment improved in both patients with successful treatment of their seizures. Although the etiology of accelerated long-term forgetting (ALF) and remote memory impairment (RMI) in transient epileptic amnesia (TEA) is unknown, these cases suggest frequent sleep-related seizures may contribute, and they highlight the importance of video-EEG monitoring.

[EEG changes in symptomatic headache caused by bruxism].

PubMed

Wieselmann, G; Grabmair, W; Logar, C; Permann, R; Moser, F

1987-02-20

EEG recordings were carried out on 36 patients with the verified diagnosis of bruxism and unilateral headache. Occlusal splints were applied in the long-term management of these patients. Initial EEG recordings showed pathological changes in 56% of the patients. The EEG recordings were repeated two and six weeks later in these patients and following improvement in the clinical symptomatology pathological EEG patterns were detected in only 22% of all cases. This decrease is of statistical significance.

Preterm EEG: a multimodal neurophysiological protocol.

PubMed

Stjerna, Susanna; Voipio, Juha; Metsäranta, Marjo; Kaila, Kai; Vanhatalo, Sampsa

2012-02-18

Since its introduction in early 1950s, electroencephalography (EEG) has been widely used in the neonatal intensive care units (NICU) for assessment and monitoring of brain function in preterm and term babies. Most common indications are the diagnosis of epileptic seizures, assessment of brain maturity, and recovery from hypoxic-ischemic events. EEG recording techniques and the understanding of neonatal EEG signals have dramatically improved, but these advances have been slow to penetrate through the clinical traditions. The aim of this presentation is to bring theory and practice of advanced EEG recording available for neonatal units. In the theoretical part, we will present animations to illustrate how a preterm brain gives rise to spontaneous and evoked EEG activities, both of which are unique to this developmental phase, as well as crucial for a proper brain maturation. Recent animal work has shown that the structural brain development is clearly reflected in early EEG activity. Most important structures in this regard are the growing long range connections and the transient cortical structure, subplate. Sensory stimuli in a preterm baby will generate responses that are seen at a single trial level, and they have underpinnings in the subplate-cortex interaction. This brings neonatal EEG readily into a multimodal study, where EEG is not only recording cortical function, but it also tests subplate function via different sensory modalities. Finally, introduction of clinically suitable dense array EEG caps, as well as amplifiers capable of recording low frequencies, have disclosed multitude of brain activities that have as yet been overlooked. In the practical part of this video, we show how a multimodal, dense array EEG study is performed in neonatal intensive care unit from a preterm baby in the incubator. The video demonstrates preparation of the baby and incubator, application of the EEG cap, and performance of the sensory stimulations.

A method for classification of transient events in EEG recordings: application to epilepsy diagnosis.

PubMed

Tzallas, A T; Karvelis, P S; Katsis, C D; Fotiadis, D I; Giannopoulos, S; Konitsiotis, S

2006-01-01

The aim of the paper is to analyze transient events in inter-ictal EEG recordings, and classify epileptic activity into focal or generalized epilepsy using an automated method. A two-stage approach is proposed. In the first stage the observed transient events of a single channel are classified into four categories: epileptic spike (ES), muscle activity (EMG), eye blinking activity (EOG), and sharp alpha activity (SAA). The process is based on an artificial neural network. Different artificial neural network architectures have been tried and the network having the lowest error has been selected using the hold out approach. In the second stage a knowledge-based system is used to produce diagnosis for focal or generalized epileptic activity. The classification of transient events reported high overall accuracy (84.48%), while the knowledge-based system for epilepsy diagnosis correctly classified nine out of ten cases. The proposed method is advantageous since it effectively detects and classifies the undesirable activity into appropriate categories and produces a final outcome related to the existence of epilepsy.

Classification of EEG abnormalities in partial epilepsy with simultaneous EEG-fMRI recordings.

PubMed

Pedreira, C; Vaudano, A E; Thornton, R C; Chaudhary, U J; Vulliemoz, S; Laufs, H; Rodionov, R; Carmichael, D W; Lhatoo, S D; Guye, M; Quian Quiroga, R; Lemieux, L

2014-10-01

Scalp EEG recordings and the classification of interictal epileptiform discharges (IED) in patients with epilepsy provide valuable information about the epileptogenic network, particularly by defining the boundaries of the "irritative zone" (IZ), and hence are helpful during pre-surgical evaluation of patients with severe refractory epilepsies. The current detection and classification of epileptiform signals essentially rely on expert observers. This is a very time-consuming procedure, which also leads to inter-observer variability. Here, we propose a novel approach to automatically classify epileptic activity and show how this method provides critical and reliable information related to the IZ localization beyond the one provided by previous approaches. We applied Wave_clus, an automatic spike sorting algorithm, for the classification of IED visually identified from pre-surgical simultaneous Electroencephalogram-functional Magnetic Resonance Imagining (EEG-fMRI) recordings in 8 patients affected by refractory partial epilepsy candidate for surgery. For each patient, two fMRI analyses were performed: one based on the visual classification and one based on the algorithmic sorting. This novel approach successfully identified a total of 29 IED classes (compared to 26 for visual identification). The general concordance between methods was good, providing a full match of EEG patterns in 2 cases, additional EEG information in 2 other cases and, in general, covering EEG patterns of the same areas as expert classification in 7 of the 8 cases. Most notably, evaluation of the method with EEG-fMRI data analysis showed hemodynamic maps related to the majority of IED classes representing improved performance than the visual IED classification-based analysis (72% versus 50%). Furthermore, the IED-related BOLD changes revealed by using the algorithm were localized within the presumed IZ for a larger number of IED classes (9) in a greater number of patients than the expert

Two magneto-encephalographic epileptic foci did not coincide with the electrocorticographic ictal onset zone in a patient with temporal lobe epilepsy.

PubMed

Hisada, K; Morioka, T; Nishio, S; Yamamoto, T; Fukui, M

2001-12-01

To evaluate the usefulness and limitations of magneto-encephalography (MEG) for epilepsy surgery, we compared 'interictal' epileptic spike fields on MEG with ictal electrocorticography (ECoG) using invasive chronic subdural electrodes in a patient with intractable medial temporal lobe epilepsy (MTLE) associated with vitamin K deficiency intracerebral hemorrhage. A 19-year-old male with an 8-year history of refractory complex partial seizures, secondarily generalized, and right hemispheric atrophy and porencephaly in the right frontal lobe on MRI, was studied with MEG to define the interictal paroxysmal sources based on the single-dipole model. This was followed by invasive ECoG monitoring to delineate the epileptogenic zone. MEG demonstrated two paroxysmal foci, one each on the right lateral temporal and frontal lobes. Ictal ECoG recordings revealed an ictal onset zone on the right medial temporal lobe, which was different from that defined by MEG. Anterior temporal lobectomy with hippocampectomy was performed and the patient has been seizure free for two years. Our results indicate that interictal MEG does not always define the epileptogenic zone in patients with MTLE.

Instantaneous frequency based newborn EEG seizure characterisation

NASA Astrophysics Data System (ADS)

Mesbah, Mostefa; O'Toole, John M.; Colditz, Paul B.; Boashash, Boualem

2012-12-01

The electroencephalogram (EEG), used to noninvasively monitor brain activity, remains the most reliable tool in the diagnosis of neonatal seizures. Due to their nonstationary and multi-component nature, newborn EEG seizures are better represented in the joint time-frequency domain than in either the time domain or the frequency domain. Characterising newborn EEG seizure nonstationarities helps to better understand their time-varying nature and, therefore, allow developing efficient signal processing methods for both modelling and seizure detection and classification. In this article, we used the instantaneous frequency (IF) extracted from a time-frequency distribution to characterise newborn EEG seizures. We fitted four frequency modulated (FM) models to the extracted IFs, namely a linear FM, a piecewise-linear FM, a sinusoidal FM, and a hyperbolic FM. Using a database of 30-s EEG seizure epochs acquired from 35 newborns, we were able to show that, depending on EEG channel, the sinusoidal and piecewise-linear FM models best fitted 80-98% of seizure epochs. To further characterise the EEG seizures, we calculated the mean frequency and frequency span of the extracted IFs. We showed that in the majority of the cases (>95%), the mean frequency resides in the 0.6-3 Hz band with a frequency span of 0.2-1 Hz. In terms of the frequency of occurrence of the four seizure models, the statistical analysis showed that there is no significant difference( p = 0.332) between the two hemispheres. The results also indicate that there is no significant differences between the two hemispheres in terms of the mean frequency ( p = 0.186) and the frequency span ( p = 0.302).

High-resolution EEG (HR-EEG) and magnetoencephalography (MEG).

PubMed

Gavaret, M; Maillard, L; Jung, J

2015-03-01

High-resolution EEG (HR-EEG) and magnetoencephalography (MEG) allow the recording of spontaneous or evoked electromagnetic brain activity with excellent temporal resolution. Data must be recorded with high temporal resolution (sampling rate) and high spatial resolution (number of channels). Data analyses are based on several steps with selection of electromagnetic signals, elaboration of a head model and use of algorithms in order to solve the inverse problem. Due to considerable technical advances in spatial resolution, these tools now represent real methods of ElectroMagnetic Source Imaging. HR-EEG and MEG constitute non-invasive and complementary examinations, characterized by distinct sensitivities according to the location and orientation of intracerebral generators. In the presurgical assessment of drug-resistant partial epilepsies, HR-EEG and MEG can characterize and localize interictal activities and thus the irritative zone. HR-EEG and MEG often yield significant additional data that are complementary to other presurgical investigations and particularly relevant in MRI-negative cases. Currently, the determination of the epileptogenic zone and functional brain mapping remain rather less well-validated indications. In France, in 2014, HR-EEG is now part of standard clinical investigation of epilepsy, while MEG remains a research technique. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Directed differential connectivity graph of interictal epileptiform discharges

PubMed Central

Amini, Ladan; Jutten, Christian; Achard, Sophie; David, Olivier; Soltanian-Zadeh, Hamid; Hossein-Zadeh, Gh. Ali; Kahane, Philippe; Minotti, Lorella; Vercueil, Laurent

2011-01-01

In this paper, we study temporal couplings between interictal events of spatially remote regions in order to localize the leading epileptic regions from intracerebral electroencephalogram (iEEG). We aim to assess whether quantitative epileptic graph analysis during interictal period may be helpful to predict the seizure onset zone of ictal iEEG. Using wavelet transform, cross-correlation coefficient, and multiple hypothesis test, we propose a differential connectivity graph (DCG) to represent the connections that change significantly between epileptic and non-epileptic states as defined by the interictal events. Post-processings based on mutual information and multi-objective optimization are proposed to localize the leading epileptic regions through DCG. The suggested approach is applied on iEEG recordings of five patients suffering from focal epilepsy. Quantitative comparisons of the proposed epileptic regions within ictal onset zones detected by visual inspection and using electrically stimulated seizures, reveal good performance of the present method. PMID:21156385

Temporal lobe deficits in murderers: EEG findings undetected by PET.

PubMed

Gatzke-Kopp, L M; Raine, A; Buchsbaum, M; LaCasse, L

2001-01-01

This study evaluates electroencephalography (EEG) and positron emission tomography (PET) in the same subjects. Fourteen murderers were assessed by using both PET (while they were performing the continuous performance task) and EEG during a resting state. EEG revealed significant increases in slow-wave activity in the temporal, but not frontal, lobe in murderers, in contrast to prior PET findings that showed reduced prefrontal, but not temporal, glucose metabolism. Results suggest that resting EEG shows empirical utility distinct from PET activation findings.

The changes of HRV in refractory epilepsy: The potential index to predict the onset of epilepsy in children.

PubMed

Gong, Xuehao; Mao, Xuhua; Chen, Yan; Huang, Leidan; Liu, Weizong; Huang, Xian; Tan, Zheng; Wang, Xianming; Wu, Wanqing; Chen, Qian; Li, Rong

2016-01-01

In this study, we examine the potential of heart rate variability (HRV) as an efficient tool for predicting the onset of epilepsy in children. We totally collected 53 seizures EEG and ECG data using Video - EEG - ECG monitoring system. We then separated the ECG data into three segments: ten-minute before onset of each seizure, five-minute before onset of each seizure, and five-minute from the onset of each seizure. After the HRV parameters in all segments were calculated, we compared the differences between pre-ictal period and ictal period. We found that the values of meanHR, LF and LF/HF were greater in onset period. And the values of meanRR and the HF were less in ictal period. And it presented the similar changes when seizures occurred in the daytime and seizures occurred in the nighttime. In brief, we found that the sympathetic nervous system was under a more active status during onset period. We speculated that the HRV parameters such as the LF, HF or LF/HF could have potential to predict the seizures in children with epilepsy.

Clozapine-induced EEG abnormalities and clinical response to clozapine.

PubMed

Risby, E D; Epstein, C M; Jewart, R D; Nguyen, B V; Morgan, W N; Risch, S C; Thrivikraman, K V; Lewine, R L

1995-01-01

The authors hypothesized that patients who develop gross EEG abnormalities during clozapine treatment would have a less favorable outcome than patients who did not develop abnormal EEGs. The clinical EEGs and the Brief Psychiatric Rating Scale (BPRS) scores of 12 patients with schizophrenia and 4 patients with schizoaffective disorder were compared before and during treatment with clozapine. Eight patients developed significant EEG abnormalities on clozapine; 1 showed worsening of an abnormal pre-clozapine EEG; none of these subjects had clinical seizures. BPRS scores improved significantly in the group of patients who developed abnormal EEGs but not in the group who did not. Findings are consistent with previous reports of a high incidence of clozapine-induced EEG abnormalities and a positive association between these abnormalities and clinical improvement.

Inhibition of adenosine metabolism induces changes in post-ictal depression, respiration, and mortality in genetically epilepsy prone rats.

PubMed

Kommajosyula, Srinivasa P; Randall, Marcus E; Faingold, Carl L

2016-01-01

A major cause of mortality in epilepsy patients is sudden unexpected death in epilepsy (SUDEP). Post-ictal respiratory dysfunction following generalized convulsive seizures is most commonly observed in witnessed cases of human SUDEP. DBA mouse models of SUDEP are induced by audiogenic seizures (AGSz) and show high incidences of seizure-induced death due to respiratory depression. The relatively low incidence of human SUDEP suggests that it may be useful to examine seizure-associated death in an AGSz model that rarely exhibits sudden death, such as genetically epilepsy-prone rats (GEPR-9s). Adenosine is released extensively during seizures and depresses respiration, which may contribute to seizure-induced death. The present study examined the effects of inhibiting adenosine metabolism on the durations of post-ictal depression (PID) and respiratory distress (RD), changes in blood oxygen saturation (% SpO2), and the incidence of post-seizure mortality in GEPR-9s. Systemic administration of adenosine metabolism inhibitors, erythro-9-(2-hydroxy-3-nonyl) adenine (EHNA, 30 mg/kg) with 5-Iodotubericidin (5-ITU, 3mg/kg) in GEPR-9s resulted in significant changes in the duration of AGSz-induced PID as compared to vehicle in both genders. These agents also significantly increased the duration of post-seizure RD and significantly decreased the mean% SpO2 after AGSz, as compared to vehicle but only in females. Subsequently, we observed that the incidences of death in both genders 12-48 h post-seizure were significantly greater in drug vs. vehicle treatment. The incidence of death in females was also significantly higher than in males, which is consistent with the elevated seizure sensitivity of female GEPR-9s developmentally. These results support a potentially important role of elevated adenosine levels following generalized seizures in the increased incidence of death in GEPR-9s induced by adenosine metabolism inhibitors. These findings may also be relevant to human SUDEP, in

PyEEG: an open source Python module for EEG/MEG feature extraction.

PubMed

Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

2011-01-01

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction.

PyEEG: An Open Source Python Module for EEG/MEG Feature Extraction

PubMed Central

Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

2011-01-01

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction. PMID:21512582

Artifact removal from EEG data with empirical mode decomposition

NASA Astrophysics Data System (ADS)

Grubov, Vadim V.; Runnova, Anastasiya E.; Efremova, Tatyana Yu.; Hramov, Alexander E.

2017-03-01

In the paper we propose the novel method for dealing with the physiological artifacts caused by intensive activity of facial and neck muscles and other movements in experimental human EEG recordings. The method is based on analysis of EEG signals with empirical mode decomposition (Hilbert-Huang transform). We introduce the mathematical algorithm of the method with following steps: empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing empirical modes with artifacts, reconstruction of the initial EEG signal. We test the method on filtration of experimental human EEG signals from movement artifacts and show high efficiency of the method.

Identifying the effects of microsaccades in tripolar EEG signals.

PubMed

Bellisle, Rachel; Steele, Preston; Bartels, Rachel; Lei Ding; Sunderam, Sridhar; Besio, Walter

2017-07-01

Microsaccades are tiny, involuntary eye movements that occur during fixation, and they are necessary to human sight to maintain a sharp image and correct the effects of other fixational movements. Researchers have theorized and studied the effects of microsaccades on electroencephalography (EEG) signals to understand and eliminate the unwanted artifacts from EEG. The tripolar concentric ring electrode (TCRE) sensors are used to acquire TCRE EEG (tEEG). The tEEG detects extremely focal signals from directly below the TCRE sensor. We have noticed a slow wave frequency found in some tEEG recordings. Therefore, we conducted the current work to determine if there was a correlation between the slow wave in the tEEG and the microsaccades. This was done by analyzing the coherence of the frequency spectrums of both tEEG and eye movement in recordings where microsaccades are present. Our preliminary findings show that there is a correlation between the two.

Causality within the Epileptic Network: An EEG-fMRI Study Validated by Intracranial EEG.

PubMed

Vaudano, Anna Elisabetta; Avanzini, Pietro; Tassi, Laura; Ruggieri, Andrea; Cantalupo, Gaetano; Benuzzi, Francesca; Nichelli, Paolo; Lemieux, Louis; Meletti, Stefano

2013-01-01

Accurate localization of the Seizure Onset Zone (SOZ) is crucial in patients with drug-resistance focal epilepsy. EEG with fMRI recording (EEG-fMRI) has been proposed as a complementary non-invasive tool, which can give useful additional information in the pre-surgical work-up. However, fMRI maps related to interictal epileptiform activities (IED) often show multiple regions of signal change, or "networks," rather than highly focal ones. Effective connectivity approaches like Dynamic Causal Modeling (DCM) applied to fMRI data potentially offers a framework to address which brain regions drives the generation of seizures and IED within an epileptic network. Here, we present a first attempt to validate DCM on EEG-fMRI data in one patient affected by frontal lobe epilepsy. Pre-surgical EEG-fMRI demonstrated two distinct clusters of blood oxygenation level dependent (BOLD) signal increases linked to IED, one located in the left frontal pole and the other in the ipsilateral dorso-lateral frontal cortex. DCM of the IED-related BOLD signal favored a model corresponding to the left dorso-lateral frontal cortex as driver of changes in the fronto-polar region. The validity of DCM was supported by: (a) the results of two different non-invasive analysis obtained on the same dataset: EEG source imaging (ESI), and "psycho-physiological interaction" analysis; (b) the failure of a first surgical intervention limited to the fronto-polar region; (c) the results of the intracranial EEG monitoring performed after the first surgical intervention confirming a SOZ located over the dorso-lateral frontal cortex. These results add evidence that EEG-fMRI together with advanced methods of BOLD signal analysis is a promising tool that can give relevant information within the epilepsy surgery diagnostic work-up.

Trends in pediatric epilepsy surgery.

PubMed

Shah, Ritesh; Botre, Abhijit; Udani, Vrajesh

2015-03-01

Epilepsy surgery has become an accepted treatment for drug resistant epilepsy in infants and children. It has gained ground in India over the last decade. Certain epilepsy surgically remediable syndromes have been delineated and should be offered surgery earlier rather than later, especially if cognitive/behavioral development is being compromised. Advances in imaging, particularly in MRI has helped identify surgical candidates. Pre-surgical evaluation includes clinical assessment, structural and functional imaging, inter-ictal EEG, simultaneous video -EEG, with analysis of seizure semiology and ictal EEG and other optional investigations like neuropsychology and other newer imaging techniques. If data are concordant resective surgery is offered, keeping in mind preservation of eloquent cortical areas subserving motor, language and visual functions. In case of discordant data or non-lesional MRI, invasive EEG maybe useful using a two-stage approach. With multi-focal / generalized disease, palliative surgery like corpus callosotomy and vagal nerve stimulation maybe useful. A good outcome is seen in about 2/3rd of patients undergoing resective surgery with a low morbidity and mortality. This review outlines important learning aspects of pediatric epilepsy surgery for the general pediatrician.

Cardiac arrhythmias during or after epileptic seizures

PubMed Central

van der Lende, Marije; Surges, Rainer; Sander, Josemir W; Thijs, Roland D

2016-01-01

Seizure-related cardiac arrhythmias are frequently reported and have been implicated as potential pathomechanisms of Sudden Unexpected Death in Epilepsy (SUDEP). We attempted to identify clinical profiles associated with various (post)ictal cardiac arrhythmias. We conducted a systematic search from the first date available to July 2013 on the combination of two terms: ‘cardiac arrhythmias’ and ‘epilepsy’. The databases searched were PubMed, Embase (OVID version), Web of Science and COCHRANE Library. We attempted to identify all case reports and case series. We identified seven distinct patterns of (post)ictal cardiac arrhythmias: ictal asystole (103 cases), postictal asystole (13 cases), ictal bradycardia (25 cases), ictal atrioventricular (AV)-conduction block (11 cases), postictal AV-conduction block (2 cases), (post)ictal atrial flutter/atrial fibrillation (14 cases) and postictal ventricular fibrillation (3 cases). Ictal asystole had a mean prevalence of 0.318% (95% CI 0.316% to 0.320%) in people with refractory epilepsy who underwent video-EEG monitoring. Ictal asystole, bradycardia and AV-conduction block were self-limiting in all but one of the cases and seen during focal dyscognitive seizures. Seizure onset was mostly temporal (91%) without consistent lateralisation. Postictal arrhythmias were mostly found following convulsive seizures and often associated with (near) SUDEP. The contrasting clinical profiles of ictal and postictal arrhythmias suggest different pathomechanisms. Postictal rather than ictal arrhythmias seem of greater importance to the pathophysiology of SUDEP. PMID:26038597

EEG and Coma.

PubMed

Ardeshna, Nikesh I

2016-03-01

Coma is defined as a state of extreme unresponsiveness, in which a person exhibits no voluntary movement or behavior even to painful stimuli. The utilization of EEG for patients in coma has increased dramatically over the last few years. In fact, many institutions have set protocols for continuous EEG (cEEG) monitoring for patients in coma due to potential causes such as subarachnoid hemorrhage or cardiac arrest. Consequently, EEG plays an important role in diagnosis, managenent, and in some cases even prognosis of coma patients.

Aberrant EEG functional connectivity and EEG power spectra in resting state post-traumatic stress disorder: a sLORETA study.

PubMed

Imperatori, Claudio; Farina, Benedetto; Quintiliani, Maria Isabella; Onofri, Antonio; Castelli Gattinara, Paola; Lepore, Marta; Gnoni, Valentina; Mazzucchi, Edoardo; Contardi, Anna; Della Marca, Giacomo

2014-10-01

The aim of the present study was to explore the modifications of EEG power spectra and EEG connectivity of resting state (RS) condition in patients with post-traumatic stress disorder (PTSD). Seventeen patients and seventeen healthy subjects matched for age and gender were enrolled. EEG was recorded during 5min of RS. EEG analysis was conducted by means of the standardized Low Resolution Electric Tomography software (sLORETA). In power spectra analysis PTSD patients showed a widespread increase of theta activity (4.5-7.5Hz) in parietal lobes (Brodmann Area, BA 7, 4, 5, 40) and in frontal lobes (BA 6). In the connectivity analysis PTSD patients also showed increase of alpha connectivity (8-12.5Hz) between the cortical areas explored by Pz-P4 electrode. Our results could reflect the alteration of memory systems and emotional processing consistently altered in PTSD patients. Copyright © 2014 Elsevier B.V. All rights reserved.

Short-Term EEG Spectral Pattern as a Single Event in EEG Phenomenology

PubMed Central

Fingelkurts, Al. A; Fingelkurts, An. A

2010-01-01

Spectral decomposition, to this day, still remains the main analytical paradigm for the analysis of EEG oscillations. However, conventional spectral analysis assesses the mean characteristics of the EEG power spectra averaged out over extended periods of time and/or broad frequency bands, thus resulting in a “static” picture which cannot reflect adequately the underlying neurodynamic. A relatively new promising area in the study of EEG is based on reducing the signal to elementary short-term spectra of various types in accordance with the number of types of EEG stationary segments instead of using averaged power spectrum for the whole EEG. It is suggested that the various perceptual and cognitive operations associated with a mental or behavioural condition constitute a single distinguishable neurophysiological state with a distinct and reliable spectral pattern. In this case, one type of short-term spectral pattern may be considered as a single event in EEG phenomenology. To support this assumption the following issues are considered in detail: (a) the relations between local EEG short-term spectral pattern of particular type and the actual state of the neurons in underlying network and a volume conduction; (b) relationship between morphology of EEG short-term spectral pattern and the state of the underlying neurodynamical system i.e. neuronal assembly; (c) relation of different spectral pattern components to a distinct physiological mechanism; (d) relation of different spectral pattern components to different functional significance; (e) developmental changes of spectral pattern components; (f) heredity of the variance in the individual spectral pattern and its components; (g) intra-individual stability of the sets of EEG short-term spectral patterns and their percent ratio; (h) discrete dynamics of EEG short-term spectral patterns. Functional relevance (consistency) of EEG short-term spectral patterns in accordance with the changes of brain functional state

Reference layer adaptive filtering (RLAF) for EEG artifact reduction in simultaneous EEG-fMRI.

PubMed

Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R

2017-04-01

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) combines advantages of both methods, namely high temporal resolution of EEG and high spatial resolution of fMRI. However, EEG quality is limited due to severe artifacts caused by fMRI scanners. To improve EEG data quality substantially, we introduce methods that use a reusable reference layer EEG cap prototype in combination with adaptive filtering. The first method, reference layer adaptive filtering (RLAF), uses adaptive filtering with reference layer artifact data to optimize artifact subtraction from EEG. In the second method, multi band reference layer adaptive filtering (MBRLAF), adaptive filtering is performed on bandwidth limited sub-bands of the EEG and the reference channels. The results suggests that RLAF outperforms the baseline method, average artifact subtraction, in all settings and also its direct predecessor, reference layer artifact subtraction (RLAS), in lower (<35 Hz) frequency ranges. MBRLAF is computationally more demanding than RLAF, but highly effective in all EEG frequency ranges. Effectivity is determined by visual inspection, as well as root-mean-square voltage reduction and power reduction of EEG provided that physiological EEG components such as occipital EEG alpha power and visual evoked potentials (VEP) are preserved. We demonstrate that both, RLAF and MBRLAF, improve VEP quality. For that, we calculate the mean-squared-distance of single trial VEP to the mean VEP and estimate single trial VEP classification accuracies. We found that the average mean-squared-distance is lowest and the average classification accuracy is highest after MBLAF. RLAF was second best. In conclusion, the results suggests that RLAF and MBRLAF are potentially very effective in improving EEG quality of simultaneous EEG-fMRI. Highlights We present a new and reusable reference layer cap prototype for simultaneous EEG-fMRI We introduce new algorithms for reducing EEG

Reference layer adaptive filtering (RLAF) for EEG artifact reduction in simultaneous EEG-fMRI

NASA Astrophysics Data System (ADS)

Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R.

2017-04-01

Objective. Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) combines advantages of both methods, namely high temporal resolution of EEG and high spatial resolution of fMRI. However, EEG quality is limited due to severe artifacts caused by fMRI scanners. Approach. To improve EEG data quality substantially, we introduce methods that use a reusable reference layer EEG cap prototype in combination with adaptive filtering. The first method, reference layer adaptive filtering (RLAF), uses adaptive filtering with reference layer artifact data to optimize artifact subtraction from EEG. In the second method, multi band reference layer adaptive filtering (MBRLAF), adaptive filtering is performed on bandwidth limited sub-bands of the EEG and the reference channels. Main results. The results suggests that RLAF outperforms the baseline method, average artifact subtraction, in all settings and also its direct predecessor, reference layer artifact subtraction (RLAS), in lower (<35 Hz) frequency ranges. MBRLAF is computationally more demanding than RLAF, but highly effective in all EEG frequency ranges. Effectivity is determined by visual inspection, as well as root-mean-square voltage reduction and power reduction of EEG provided that physiological EEG components such as occipital EEG alpha power and visual evoked potentials (VEP) are preserved. We demonstrate that both, RLAF and MBRLAF, improve VEP quality. For that, we calculate the mean-squared-distance of single trial VEP to the mean VEP and estimate single trial VEP classification accuracies. We found that the average mean-squared-distance is lowest and the average classification accuracy is highest after MBLAF. RLAF was second best. Significance. In conclusion, the results suggests that RLAF and MBRLAF are potentially very effective in improving EEG quality of simultaneous EEG-fMRI. Highlights We present a new and reusable reference layer cap prototype for simultaneous EEG-fMRI We

A testbed to explore the optimal electrical stimulation parameters for suppressing inter-ictal spikes in human hippocampal slices.

PubMed

Min-Chi Hsiao; Pen-Ning Yu; Dong Song; Liu, Charles Y; Heck, Christi N; Millett, David; Berger, Theodore W

2014-01-01

New interventions using neuromodulatory devices such as vagus nerve stimulation, deep brain stimulation and responsive neurostimulation are available or under study for the treatment of refractory epilepsy. Since the actual mechanisms of the onset and termination of the seizure are still unclear, most researchers or clinicians determine the optimal stimulation parameters through trial-and-error procedures. It is necessary to further explore what types of electrical stimulation parameters (these may include stimulation frequency, amplitude, duration, interval pattern, and location) constitute a set of optimal stimulation paradigms to suppress seizures. In a previous study, we developed an in vitro epilepsy model using hippocampal slices from patients suffering from mesial temporal lobe epilepsy. Using a planar multi-electrode array system, inter-ictal activity from human hippocampal slices was consistently recorded. In this study, we have further transferred this in vitro seizure model to a testbed for exploring the possible neurostimulation paradigms to inhibit inter-ictal spikes. The methodology used to collect the electrophysiological data, the approach to apply different electrical stimulation parameters to the slices are provided in this paper. The results show that this experimental testbed will provide a platform for testing the optimal stimulation parameters of seizure cessation. We expect this testbed will expedite the process for identifying the most effective parameters, and may ultimately be used to guide programming of new stimulating paradigms for neuromodulatory devices.

Headache Following Occipital Brain Lesion: A Case of Migraine Triggered by Occipital Spikes?

PubMed

Vollono, Catello; Mariotti, Paolo; Losurdo, Anna; Giannantoni, Nadia Mariagrazia; Mazzucchi, Edoardo; Valentini, Piero; De Rose, Paola; Della Marca, Giacomo

2015-10-01

This study describes the case of an 8-year-old boy who developed a genuine migraine after the surgical excision, from the right occipital lobe, of brain abscesses due to selective infestation of the cerebrum by Entamoeba histolytica. After the surgical treatment, the boy presented daily headaches with typical migraine features, including right-side parieto-temporal pain, nausea, vomiting, and photophobia. Electroencephalography (EEG) showed epileptiform discharges in the right occipital lobe, although he never presented seizures. Clinical and neurophysiological observations were performed, including video-EEG and polygraphic recordings. EEG showed "interictal" epileptiform discharges in the right occipital lobe. A prolonged video-EEG recording performed before, during, and after an acute attack ruled out ictal or postictal migraine. In this boy, an occipital lesion caused occipital epileptiform EEG discharges without seizures, probably prevented by the treatment. We speculate that occipital spikes, in turn, could have caused a chronic headache with features of migraine without aura. Occipital epileptiform discharges, even in absence of seizures, may trigger a genuine migraine, probably by means of either the trigeminovascular or brainstem system. © EEG and Clinical Neuroscience Society (ECNS) 2014.

On the optimal z-score threshold for SISCOM analysis to localize the ictal onset zone.

PubMed

De Coster, Liesbeth; Van Laere, Koen; Cleeren, Evy; Baete, Kristof; Dupont, Patrick; Van Paesschen, Wim; Goffin, Karolien E

2018-04-17

In epilepsy patients, SISCOM or subtraction ictal single photon emission computed tomography co-registered to magnetic resonance imaging has become a routinely used, non-invasive technique to localize the ictal onset zone (IOZ). Thresholding of clusters with a predefined number of standard deviations from normality (z-score) is generally accepted to localize the IOZ. In this study, we aimed to assess the robustness of this parameter in a group of patients with well-characterized drug-resistant epilepsy in whom the exact location of the IOZ was known after successful epilepsy surgery. Eighty patients underwent preoperative SISCOM and were seizure free in a postoperative period of minimum 1 year. SISCOMs with z-threshold 2 and 1.5 were analyzed by two experienced readers separately, blinded from the clinical ground truth data. Their reported location of the IOZ was compared with the operative resection zone. Furthermore, confidence scores of the SISCOM IOZ were compared for the two thresholds. Visual reporting with a z-score threshold of 1.5 and 2 showed no statistically significant difference in localizing correspondence with the ground truth (70 vs. 72% respectively, p = 0.17). Interrater agreement was moderate (κ = 0.65) at the threshold of 1.5, but high (κ = 0.84) at a threshold of 2, where also reviewers were significantly more confident (p < 0.01). SISCOM is a clinically useful, routinely used modality in the preoperative work-up in many epilepsy surgery centers. We found no significant differences in localizing value of the IOZ using a threshold of 1.5 or 2, but interrater agreement and reader confidence were higher using a z-score threshold of 2.

EEG datasets for motor imagery brain-computer interface.

PubMed

Cho, Hohyun; Ahn, Minkyu; Ahn, Sangtae; Kwon, Moonyoung; Jun, Sung Chan

2017-07-01

Most investigators of brain-computer interface (BCI) research believe that BCI can be achieved through induced neuronal activity from the cortex, but not by evoked neuronal activity. Motor imagery (MI)-based BCI is one of the standard concepts of BCI, in that the user can generate induced activity by imagining motor movements. However, variations in performance over sessions and subjects are too severe to overcome easily; therefore, a basic understanding and investigation of BCI performance variation is necessary to find critical evidence of performance variation. Here we present not only EEG datasets for MI BCI from 52 subjects, but also the results of a psychological and physiological questionnaire, EMG datasets, the locations of 3D EEG electrodes, and EEGs for non-task-related states. We validated our EEG datasets by using the percentage of bad trials, event-related desynchronization/synchronization (ERD/ERS) analysis, and classification analysis. After conventional rejection of bad trials, we showed contralateral ERD and ipsilateral ERS in the somatosensory area, which are well-known patterns of MI. Finally, we showed that 73.08% of datasets (38 subjects) included reasonably discriminative information. Our EEG datasets included the information necessary to determine statistical significance; they consisted of well-discriminated datasets (38 subjects) and less-discriminative datasets. These may provide researchers with opportunities to investigate human factors related to MI BCI performance variation, and may also achieve subject-to-subject transfer by using metadata, including a questionnaire, EEG coordinates, and EEGs for non-task-related states. © The Authors 2017. Published by Oxford University Press.

Cerebrospinal fluid findings after epileptic seizures.

PubMed

Chatzikonstantinou, Anastasios; Ebert, Anne D; Hennerici, Michael G

2015-12-01

We aimed to evaluate ictally-induced CSF parameter changes after seizures in adult patients without acute inflammatory diseases or infectious diseases associated with the central nervous system. In total, 151 patients were included in the study. All patients were admitted to our department of neurology following acute seizures and received an extensive work-up including EEG, cerebral imaging, and CSF examinations. CSF protein elevation was found in most patients (92; 60.9%) and was significantly associated with older age, male sex, and generalized seizures. Abnormal CSF-to-serum glucose ratio was found in only nine patients (5.9%) and did not show any significant associations. CSF lactate was elevated in 34 patients (22.5%) and showed a significant association with focal seizures with impaired consciousness, status epilepticus, the presence of EEG abnormalities in general and epileptiform potentials in particular, as well as epileptogenic lesions on cerebral imaging. Our results indicate that non-inflammatory CSF elevation of protein and lactate after epileptic seizures is relatively common, in contrast to changes in CSF-to-serum glucose ratio, and further suggest that these changes are caused by ictal activity and are related to seizure type and intensity. We found no indication that these changes may have further-reaching pathological implications besides their postictal character.

EEG spectral analysis in primary insomnia: NREM period effects and sex differences.

PubMed

Buysse, Daniel J; Germain, Anne; Hall, Martica L; Moul, Douglas E; Nofzinger, Eric A; Begley, Amy; Ehlers, Cindy L; Thompson, Wesley; Kupfer, David J

2008-12-01

To compare NREM EEG power in primary insomnia (PI) and good sleeper controls (GSC), examining both sex and NREM period effects; to examine relationships between EEG power, clinical characteristics, and self-reports of sleep. Overnight polysomnographic study. Sleep laboratory. PI (n=48; 29 women) and GSC (n=25; 15 women). None. EEG power from 1-50 Hz was computed for artifact-free sleep epochs across four NREM periods. Repeated measures mixed effect models contrasted differences between groups, EEG frequency bands, and NREM periods. EEG power-frequency curves were modeled using regressions with fixed knot splines. Mixed models showed no significant group (PI vs. GSC) differences; marginal sex differences (delta and theta bands); significant differences across NREM periods; and group*sex and group*NREM period interactions, particularly in beta and gamma bands. Modeled power-frequency curves showed no group difference in whole-night NREM, but PI had higher power than GSC from 18-40 Hz in the first NREM period. Among women, PI had higher 16 to 44-Hz power than GSC in the first 3 NREM periods, and higher 3 to 5-Hz power across all NREM periods. PI and GSC men showed no consistent differences in EEG power. High-frequency EEG power was not related to clinical or subjective sleep ratings in PI. Women with PI, but not men, showed increased high-frequency and low-frequency EEG activity during NREM sleep compared to GSC, particularly in early NREM periods. Sex and NREM period may moderate quantitative EEG differences between PI and GSC.

Generalized Hurst exponent estimates differentiate EEG signals of healthy and epileptic patients

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

2018-01-01

The aim of our current study is to check whether multifractal patterns of the electroencephalographic (EEG) signals of normal and epileptic patients are statistically similar or different. In this regard, the generalized Hurst exponent (GHE) method is used for robust estimation of the multifractals in each type of EEG signals, and three powerful statistical tests are performed to check existence of differences between estimated GHEs from healthy control subjects and epileptic patients. The obtained results show that multifractals exist in both types of EEG signals. Particularly, it was found that the degree of fractal is more pronounced in short variations of normal EEG signals than in short variations of EEG signals with seizure free intervals. In contrary, it is more pronounced in long variations of EEG signals with seizure free intervals than in normal EEG signals. Importantly, both parametric and nonparametric statistical tests show strong evidence that estimated GHEs of normal EEG signals are statistically and significantly different from those with seizure free intervals. Therefore, GHEs can be efficiently used to distinguish between healthy and patients suffering from epilepsy.

Periictal activity in cooled asphyxiated neonates with seizures.

PubMed

Major, Philippe; Lortie, Anne; Dehaes, Mathieu; Lodygensky, Gregory Anton; Gallagher, Anne; Carmant, Lionel; Birca, Ala

2017-04-01

Seizures are common in critically ill neonates. Both seizures and antiepileptic treatments may lead to short term complications and worsen the outcomes. Predicting the risks of seizure reoccurrence could enable individual treatment regimens and better outcomes. We aimed to identify EEG signatures of seizure reoccurrence by investigating periictal electrographic features and spectral power characteristics in hypothermic neonates with hypoxic-ischemic encephalopathy (HIE) with or without reoccurrence of seizures on rewarming. We recruited five consecutive HIE neonates, submitted to continuous EEG monitoring, with high seizure burden (>20% per hour) while undergoing therapeutic hypothermia. Two of them had reoccurrence of seizures on rewarming. We performed quantitative analysis of fifteen artifact-free consecutive seizures to appreciate spectral power changes between the interictal, preictal and ictal periods, separately for each patient. Visual analysis allowed description of electrographic features associated with ictal events. Every patient demonstrated a significant increase in overall spectral power from the interictal to preictal and ictal periods (p<0.01). Alpha power increase was more pronounced in the two patients with reoccurrence of seizures on rewarming and significant when comparing both interictal-to-preictal and interictal-to-ictal periods. This alpha activity increase could be also appreciated using visual analysis and distinguished neonates with and without seizure reoccurrence. This distinct alpha activity preceding ictal onset could represent a biomarker of propensity for seizure reoccurrence in neonates. Future studies should be performed to confirm whether quantitative periictal characteristics and electrographic features allow predicting the risks of seizure reoccurrence in HIE neonates and other critically ill patients. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Interpretation of the auto-mutual information rate of decrease in the context of biomedical signal analysis. Application to electroencephalogram recordings.

PubMed

Escudero, Javier; Hornero, Roberto; Abásolo, Daniel

2009-02-01

The mutual information (MI) is a measure of both linear and nonlinear dependences. It can be applied to a time series and a time-delayed version of the same sequence to compute the auto-mutual information function (AMIF). Moreover, the AMIF rate of decrease (AMIFRD) with increasing time delay in a signal is correlated with its entropy and has been used to characterize biomedical data. In this paper, we aimed at gaining insight into the dependence of the AMIFRD on several signal processing concepts and at illustrating its application to biomedical time series analysis. Thus, we have analysed a set of synthetic sequences with the AMIFRD. The results show that the AMIF decreases more quickly as bandwidth increases and that the AMIFRD becomes more negative as there is more white noise contaminating the time series. Additionally, this metric detected changes in the nonlinear dynamics of a signal. Finally, in order to illustrate the analysis of real biomedical signals with the AMIFRD, this metric was applied to electroencephalogram (EEG) signals acquired with eyes open and closed and to ictal and non-ictal intracranial EEG recordings.

Visual brain activity patterns classification with simultaneous EEG-fMRI: A multimodal approach.

PubMed

Ahmad, Rana Fayyaz; Malik, Aamir Saeed; Kamel, Nidal; Reza, Faruque; Amin, Hafeez Ullah; Hussain, Muhammad

2017-01-01

Classification of the visual information from the brain activity data is a challenging task. Many studies reported in the literature are based on the brain activity patterns using either fMRI or EEG/MEG only. EEG and fMRI considered as two complementary neuroimaging modalities in terms of their temporal and spatial resolution to map the brain activity. For getting a high spatial and temporal resolution of the brain at the same time, simultaneous EEG-fMRI seems to be fruitful. In this article, we propose a new method based on simultaneous EEG-fMRI data and machine learning approach to classify the visual brain activity patterns. We acquired EEG-fMRI data simultaneously on the ten healthy human participants by showing them visual stimuli. Data fusion approach is used to merge EEG and fMRI data. Machine learning classifier is used for the classification purposes. Results showed that superior classification performance has been achieved with simultaneous EEG-fMRI data as compared to the EEG and fMRI data standalone. This shows that multimodal approach improved the classification accuracy results as compared with other approaches reported in the literature. The proposed simultaneous EEG-fMRI approach for classifying the brain activity patterns can be helpful to predict or fully decode the brain activity patterns.

Continuous EEG source imaging enhances analysis of EEG-fMRI in focal epilepsy.

PubMed

Vulliemoz, S; Rodionov, R; Carmichael, D W; Thornton, R; Guye, M; Lhatoo, S D; Michel, C M; Duncan, J S; Lemieux, L

2010-02-15

EEG-correlated fMRI (EEG-fMRI) studies can reveal haemodynamic changes associated with Interictal Epileptic Discharges (IED). Methodological improvements are needed to increase sensitivity and specificity for localising the epileptogenic zone. We investigated whether the estimated EEG source activity improved models of the BOLD changes in EEG-fMRI data, compared to conventional < event-related > designs based solely on the visual identification of IED. Ten patients with pharmaco-resistant focal epilepsy underwent EEG-fMRI. EEG Source Imaging (ESI) was performed on intra-fMRI averaged IED to identify the irritative zone. The continuous activity of this estimated IED source (cESI) over the entire recording was used for fMRI analysis (cESI model). The maps of BOLD signal changes explained by cESI were compared to results of the conventional IED-related model. ESI was concordant with non-invasive data in 13/15 different types of IED. The cESI model explained significant additional BOLD variance in regions concordant with video-EEG, structural MRI or, when available, intracranial EEG in 10/15 IED. The cESI model allowed better detection of the BOLD cluster, concordant with intracranial EEG in 4/7 IED, compared to the IED model. In 4 IED types, cESI-related BOLD signal changes were diffuse with a pattern suggestive of contamination of the source signal by artefacts, notably incompletely corrected motion and pulse artefact. In one IED type, there was no significant BOLD change with either model. Continuous EEG source imaging can improve the modelling of BOLD changes related to interictal epileptic activity and this may enhance the localisation of the irritative zone. Copyright 2009 Elsevier Inc. All rights reserved.

PET MRI Coregistration in Intractable Epilepsy and Gray Matter Heterotopia.

PubMed

Seniaray, Nikhil; Jain, Anuj

2017-03-01

A 25-year-old woman with intractable seizures underwent FDG PET/MRI for seizure focus localization. MRI demonstrated bilateral carpetlike nodular subependymal gray matter and asymmetrical focal dilatation in the right temporal horn. PET/MRI showed increased FDG within subependymal gray matter with significant hypometabolism in right anterior temporal lobe. EEG and ictal semiology confirmed the right temporal seizure origin. This case highlights the importance of identification of gray matter heterotopia on FDG PET/MRI.

Quantification of EEG reactivity in comatose patients.

PubMed

Hermans, Mathilde C; Westover, M Brandon; van Putten, Michel J A M; Hirsch, Lawrence J; Gaspard, Nicolas

2016-01-01

EEG reactivity is an important predictor of outcome in comatose patients. However, visual analysis of reactivity is prone to subjectivity and may benefit from quantitative approaches. In EEG segments recorded during reactivity testing in 59 comatose patients, 13 quantitative EEG parameters were used to compare the spectral characteristics of 1-minute segments before and after the onset of stimulation (spectral temporal symmetry). Reactivity was quantified with probability values estimated using combinations of these parameters. The accuracy of probability values as a reactivity classifier was evaluated against the consensus assessment of three expert clinical electroencephalographers using visual analysis. The binary classifier assessing spectral temporal symmetry in four frequency bands (delta, theta, alpha and beta) showed best accuracy (Median AUC: 0.95) and was accompanied by substantial agreement with the individual opinion of experts (Gwet's AC1: 65-70%), at least as good as inter-expert agreement (AC1: 55%). Probability values also reflected the degree of reactivity, as measured by the inter-experts' agreement regarding reactivity for each individual case. Automated quantitative EEG approaches based on probabilistic description of spectral temporal symmetry reliably quantify EEG reactivity. Quantitative EEG may be useful for evaluating reactivity in comatose patients, offering increased objectivity. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Quantification of EEG reactivity in comatose patients

PubMed Central

Hermans, Mathilde C.; Westover, M. Brandon; van Putten, Michel J.A.M.; Hirsch, Lawrence J.; Gaspard, Nicolas

2016-01-01

Objective EEG reactivity is an important predictor of outcome in comatose patients. However, visual analysis of reactivity is prone to subjectivity and may benefit from quantitative approaches. Methods In EEG segments recorded during reactivity testing in 59 comatose patients, 13 quantitative EEG parameters were used to compare the spectral characteristics of 1-minute segments before and after the onset of stimulation (spectral temporal symmetry). Reactivity was quantified with probability values estimated using combinations of these parameters. The accuracy of probability values as a reactivity classifier was evaluated against the consensus assessment of three expert clinical electroencephalographers using visual analysis. Results The binary classifier assessing spectral temporal symmetry in four frequency bands (delta, theta, alpha and beta) showed best accuracy (Median AUC: 0.95) and was accompanied by substantial agreement with the individual opinion of experts (Gwet’s AC1: 65–70%), at least as good as inter-expert agreement (AC1: 55%). Probability values also reflected the degree of reactivity, as measured by the inter-experts’ agreement regarding reactivity for each individual case. Conclusion Automated quantitative EEG approaches based on probabilistic description of spectral temporal symmetry reliably quantify EEG reactivity. Significance Quantitative EEG may be useful for evaluating reactivity in comatose patients, offering increased objectivity. PMID:26183757

Temporal structure of neuronal population oscillations with empirical model decomposition

NASA Astrophysics Data System (ADS)

Li, Xiaoli

2006-08-01

Frequency analysis of neuronal oscillation is very important for understanding the neural information processing and mechanism of disorder in the brain. This Letter addresses a new method to analyze the neuronal population oscillations with empirical mode decomposition (EMD). Following EMD of neuronal oscillation, a series of intrinsic mode functions (IMFs) are obtained, then Hilbert transform of IMFs can be used to extract the instantaneous time frequency structure of neuronal oscillation. The method is applied to analyze the neuronal oscillation in the hippocampus of epileptic rats in vivo, the results show the neuronal oscillations have different descriptions during the pre-ictal, seizure onset and ictal periods of the epileptic EEG at the different frequency band. This new method is very helpful to provide a view for the temporal structure of neural oscillation.

Filtration of human EEG recordings from physiological artifacts with empirical mode method

NASA Astrophysics Data System (ADS)

Grubov, Vadim V.; Runnova, Anastasiya E.; Khramova, Marina V.

2017-03-01

In the paper we propose the new method for dealing with noise and physiological artifacts in experimental human EEG recordings. The method is based on analysis of EEG signals with empirical mode decomposition (Hilbert-Huang transform). We consider noises and physiological artifacts on EEG as specific oscillatory patterns that cause problems during EEG analysis and can be detected with additional signals recorded simultaneously with EEG (ECG, EMG, EOG, etc.) We introduce the algorithm of the method with following steps: empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing empirical modes with artifacts, reconstruction of the initial EEG signal. We test the method on filtration of experimental human EEG signals from eye-moving artifacts and show high efficiency of the method.

Discovering EEG resting state alterations of semantic dementia.

PubMed

Grieder, Matthias; Koenig, Thomas; Kinoshita, Toshihiko; Utsunomiya, Keita; Wahlund, Lars-Olof; Dierks, Thomas; Nishida, Keiichiro

2016-05-01

Diagnosis of semantic dementia relies on cost-intensive MRI or PET, although resting EEG markers of other dementias have been reported. Yet the view still holds that resting EEG in patients with semantic dementia is normal. However, studies using increasingly sophisticated EEG analysis methods have demonstrated that slightest alterations of functional brain states can be detected. We analyzed the common four resting EEG microstates (A, B, C, and D) of 8 patients with semantic dementia in comparison with 8 healthy controls and 8 patients with Alzheimer's disease. Topographical differences between the groups were found in microstate classes B and C, while microstate classes A and D were comparable. The data showed that the semantic dementia group had a peculiar microstate E, but the commonly found microstate C was lacking. Furthermore, the presence of microstate E was significantly correlated with lower MMSE and language scores. Alterations in resting EEG can be found in semantic dementia. Topographical shifts in microstate C might be related to semantic memory deficits. This is the first study that discovered resting state EEG abnormality in semantic dementia. The notion that resting EEG in this dementia subtype is normal has to be revised. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

EEG power during waking and NREM sleep in primary insomnia.

PubMed

Wu, You Meme; Pietrone, Regina; Cashmere, J David; Begley, Amy; Miewald, Jean M; Germain, Anne; Buysse, Daniel J

2013-10-15

Pathophysiological models of insomnia invoke the concept of 24-hour hyperarousal, which could lead to symptoms and physiological findings during waking and sleep. We hypothesized that this arousal could be seen in the waking electroencephalogram (EEG) of individuals with primary insomnia (PI), and that waking EEG power would correlate with non-REM (NREM) EEG. Subjects included 50 PI and 32 good sleeper controls (GSC). Five minutes of eyes closed waking EEG were collected at subjects' usual bedtimes, followed by polysomnography (PSG) at habitual sleep times. An automated algorithm and visual editing were used to remove artifacts from waking and sleep EEGs, followed by power spectral analysis to estimate power from 0.5-32 Hz. We did not find significant differences in waking or NREM EEG spectral power of PI and GSC. Significant correlations between waking and NREM sleep power were observed across all frequency bands in the PI group and in most frequency bands in the GSC group. The absence of significant differences between groups in waking or NREM EEG power suggests that our sample was not characterized by a high degree of cortical arousal. The consistent correlations between waking and NREM EEG power suggest that, in samples with elevated NREM EEG beta activity, waking EEG power may show a similar pattern.

Towards the utilization of EEG as a brain imaging tool.

PubMed

Michel, Christoph M; Murray, Micah M

2012-06-01

Recent advances in signal analysis have engendered EEG with the status of a true brain mapping and brain imaging method capable of providing spatio-temporal information regarding brain (dys)function. Because of the increasing interest in the temporal dynamics of brain networks, and because of the straightforward compatibility of the EEG with other brain imaging techniques, EEG is increasingly used in the neuroimaging community. However, the full capability of EEG is highly underestimated. Many combined EEG-fMRI studies use the EEG only as a spike-counter or an oscilloscope. Many cognitive and clinical EEG studies use the EEG still in its traditional way and analyze grapho-elements at certain electrodes and latencies. We here show that this way of using the EEG is not only dangerous because it leads to misinterpretations, but it is also largely ignoring the spatial aspects of the signals. In fact, EEG primarily measures the electric potential field at the scalp surface in the same way as MEG measures the magnetic field. By properly sampling and correctly analyzing this electric field, EEG can provide reliable information about the neuronal activity in the brain and the temporal dynamics of this activity in the millisecond range. This review explains some of these analysis methods and illustrates their potential in clinical and experimental applications. Copyright © 2011 Elsevier Inc. All rights reserved.

Comparison of a single-channel EEG sleep study to polysomnography

PubMed Central

Lucey, Brendan P.; McLeland, Jennifer S.; Toedebusch, Cristina D.; Boyd, Jill; Morris, John C.; Landsness, Eric C.; Yamada, Kelvin; Holtzman, David M.

2016-01-01

Summary An accurate home sleep study to assess electroencephalography (EEG)-based sleep stages and EEG power would be advantageous for both clinical and research purposes, such as for longitudinal studies measuring changes in sleep stages over time. The purpose of this study was to compare sleep scoring of a single-channel EEG recorded simultaneously on the forehead against attended polysomnography. Participants were recruited from both a clinical sleep center and a longitudinal research study investigating cognitively-normal aging and Alzheimer's disease. Analysis for overall epoch-by-epoch agreement found strong and substantial agreement between the single-channel EEG compared to polysomnography (kappa=0.67). Slow wave activity in the frontal regions was also similar when comparing the single-channel EEG device to polysomnography. As expected, stage N1 showed poor agreement (sensitivity 0.2) due to lack of occipital electrodes. Other sleep parameters such as sleep latency and REM onset latency had decreased agreement. Participants with disrupted sleep consolidation, such as from obstructive sleep apnea, also had poor agreement. We suspect that disagreement in sleep parameters between the single-channel EEG and polysomnography is partially due to altered waveform morphology and/or poorer signal quality in the single-channel derivation. Our results show that single-channel EEG provides comparable results to polysomnography in assessing REM, combined stages N2 and N3 sleep, and several other parameters including frontal slow wave activity. The data establish that single-channel EEG can be a useful research tool. PMID:27252090

EEG feature selection method based on decision tree.

PubMed

Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

EEG Artifact Removal Using a Wavelet Neural Network

NASA Technical Reports Server (NTRS)

Nguyen, Hoang-Anh T.; Musson, John; Li, Jiang; McKenzie, Frederick; Zhang, Guangfan; Xu, Roger; Richey, Carl; Schnell, Tom

2011-01-01

!n this paper we developed a wavelet neural network. (WNN) algorithm for Electroencephalogram (EEG) artifact removal without electrooculographic (EOG) recordings. The algorithm combines the universal approximation characteristics of neural network and the time/frequency property of wavelet. We. compared the WNN algorithm with .the ICA technique ,and a wavelet thresholding method, which was realized by using the Stein's unbiased risk estimate (SURE) with an adaptive gradient-based optimal threshold. Experimental results on a driving test data set show that WNN can remove EEG artifacts effectively without diminishing useful EEG information even for very noisy data.

Lateralizing value of unilateral relative ictal immobility in patients with refractory focal seizures--Looking beyond unilateral automatisms.

PubMed

Agarwal, Priya; Kaul, Bhavna; Shukla, Garima; Srivastava, Achal; Singh, Mamta Bhushan; Goyal, Vinay; Behari, Madhuri; Suri, Ashish; Gupta, Aditya; Garg, Ajay; Gaikwad, Shailesh; Bal, C S

2015-12-01

Ictal motor phenomena play a crucial role in the localization of seizure focus in the management of refractory focal epilepsy. While the importance of unilateral automatisms is well established, little attention is paid to the contralateral relatively immobile limb. In cases where automatisms mimic clonic or dystonic movements and in the absence of previously well-established signs, unilateral relative ictal immobility (RII) is potentially useful as a lateralizing sign. This study was carried out to examine the lateralizing value of this sign and to define its characteristics among patients of refractory focal epilepsy. VEEGs of 69 consecutive patients of refractory focal epilepsy who had undergone epilepsy surgery at our center over last four years were reviewed and analyzed for the presence of RII. Unilateral RII was defined as a paucity of movement in one limb lasting for at least 10s while the contralateral limb showed purposive or semi-purposive movements (in the absence of tonic or dystonic posturing or clonic movements in the involved limb). The findings were seen in the light of VEEG, radiological and nuclear imaging data, and with post-surgical outcome. Unilateral RII as a lateralizing sign was found in 24 of 69 patients (34.78%), consisting of both temporal and extra temporal epilepsy, with 100% concordance with VEEG and MRI data. All patients demonstrating this sign had a good post-surgical outcome. RII, when well characterized is a frequent and reliable lateralizing sign in patients of refractory focal epilepsy. Copyright © 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Rett syndrome: EEG presentation.

PubMed

Robertson, R; Langill, L; Wong, P K; Ho, H H

1988-11-01

Rett syndrome, a degenerative neurological disorder of girls, has a classical presentation and typical EEG findings. The electroencephalograms (EEGs) of 7 girls whose records have been followed from the onset of symptoms to the age of 5 or more are presented. These findings are tabulated with the Clinical Staging System of Hagberg and Witt-Engerström (1986). The records show a progressive deterioration in background rhythms in waking and sleep. The abnormalities of the background activity may only become evident at 4-5 years of age or during stage 2--the Rapid Destructive Stage. The marked contrast between waking and sleep background may not occur until stage 3--the Pseudostationary Stage. In essence EEG changes appear to lag behind clinical symptomatology by 1-3 years. An unexpected, but frequent, abnormality was central spikes seen in 5 of 7 girls. They appeared to be age related and could be evoked by tactile stimulation in 2 patients. We hypothesize that the prominent 'hand washing' mannerism may be self-stimulating and related to the appearance of central spike discharges.

Engagement Assessment Using EEG Signals

NASA Technical Reports Server (NTRS)

Li, Feng; Li, Jiang; McKenzie, Frederic; Zhang, Guangfan; Wang, Wei; Pepe, Aaron; Xu, Roger; Schnell, Thomas; Anderson, Nick; Heitkamp, Dean

2012-01-01

In this paper, we present methods to analyze and improve an EEG-based engagement assessment approach, consisting of data preprocessing, feature extraction and engagement state classification. During data preprocessing, spikes, baseline drift and saturation caused by recording devices in EEG signals are identified and eliminated, and a wavelet based method is utilized to remove ocular and muscular artifacts in the EEG recordings. In feature extraction, power spectrum densities with 1 Hz bin are calculated as features, and these features are analyzed using the Fisher score and the one way ANOVA method. In the classification step, a committee classifier is trained based on the extracted features to assess engagement status. Finally, experiment results showed that there exist significant differences in the extracted features among different subjects, and we have implemented a feature normalization procedure to mitigate the differences and significantly improved the engagement assessment performance.

Functional connectivity analysis in EEG source space: The choice of method

PubMed Central

Knyazeva, Maria G.

2017-01-01

Functional connectivity (FC) is among the most informative features derived from EEG. However, the most straightforward sensor-space analysis of FC is unreliable owing to volume conductance effects. An alternative—source-space analysis of FC—is optimal for high- and mid-density EEG (hdEEG, mdEEG); however, it is questionable for widely used low-density EEG (ldEEG) because of inadequate surface sampling. Here, using simulations, we investigate the performance of the two source FC methods, the inverse-based source FC (ISFC) and the cortical partial coherence (CPC). To examine the effects of localization errors of the inverse method on the FC estimation, we simulated an oscillatory source with varying locations and SNRs. To compare the FC estimations by the two methods, we simulated two synchronized sources with varying between-source distance and SNR. The simulations were implemented for hdEEG, mdEEG, and ldEEG. We showed that the performance of both methods deteriorates for deep sources owing to their inaccurate localization and smoothing. The accuracy of both methods improves with the increasing between-source distance. The best ISFC performance was achieved using hd/mdEEG, while the best CPC performance was observed with ldEEG. In conclusion, with hdEEG, ISFC outperforms CPC and therefore should be the preferred method. In the studies based on ldEEG, the CPC is a method of choice. PMID:28727750

Amplitude-Integrated EEG and Range-EEG Modulation Associated with Pneumatic Orocutaneous Stimulation in Preterm Infants

PubMed Central

Barlow, Steven M; Jegatheesan, Priya; Weiss, Sunshine; Govindaswami, Balaji; Wang, Jingyan; Lee, Jaehoon; Oder, Austin; Song, Dongli

2013-01-01

Background Controlled somatosensory stimulation strategies have demonstrated merit in developing oral feeding skills in premature infants who lack a functional suck, however, the effects of orosensory entrainment stimulation on electrocortical dynamics is unknown. Objective To determine the effects of servo-controlled pneumatic orocutaneous stimulation presented during gavage feedings on the modulation of aEEG and rEEG activity. Methods Two-channel EEG recordings were collected during 180 sessions that included orocutaneous stimulation and non-stimulation epochs among 22 preterm infants (mean gestational age = 28.56 weeks) who were randomized to treatment and control ‘sham’ conditions. The study was initiated at around 32 weeks post-menstrual age (PMA). The raw EEG was transformed into amplitude-integrated EEG (aEEG) margins, and range-EEG (rEEG) amplitude bands measured at 1-minute intervals and subjected to a mixed models statistical analysis. Results Multiple significant effects were observed in the processed EEG during and immediately following 3-minute periods of orocutaneous stimulation, including modulation of the upper and lower margins of the aEEG, and a reorganization of rEEG with an apparent shift from amplitude bands D and E to band C throughout the 23-minute recording period that followed the first stimulus block when compared to the sham condition. Cortical asymmetry also was apparent in both EEG measures. Conclusions Orocutaneous stimulation represents a salient trigeminal input which has both short- and long-term effects in modulating electrocortical activity, and thus, is hypothesized to represent a form of neural adaptation or plasticity that may benefit the preterm infant during this critical period of brain maturation. PMID:24310443

Memories of attachment hamper EEG cortical connectivity in dissociative patients.

PubMed

Farina, Benedetto; Speranza, Anna Maria; Dittoni, Serena; Gnoni, Valentina; Trentini, Cristina; Vergano, Carola Maggiora; Liotti, Giovanni; Brunetti, Riccardo; Testani, Elisa; Della Marca, Giacomo

2014-08-01

In this study, we evaluated cortical connectivity modifications by electroencephalography (EEG) lagged coherence analysis, in subjects with dissociative disorders and in controls, after retrieval of attachment memories. We asked thirteen patients with dissociative disorders and thirteen age- and sex-matched healthy controls to retrieve personal attachment-related autobiographical memories through adult attachment interviews (AAI). EEG was recorded in the closed eyes resting state before and after the AAI. EEG lagged coherence before and after AAI was compared in all subjects. In the control group, memories of attachment promoted a widespread increase in EEG connectivity, in particular in the high-frequency EEG bands. Compared to controls, dissociative patients did not show an increase in EEG connectivity after the AAI. Conclusions: These results shed light on the neurophysiology of the disintegrative effect of retrieval of traumatic attachment memories in dissociative patients.

Modulation of EEG Theta Band Signal Complexity by Music Therapy

NASA Astrophysics Data System (ADS)

Bhattacharya, Joydeep; Lee, Eun-Jeong

The primary goal of this study was to investigate the impact of monochord (MC) sounds, a type of archaic sounds used in music therapy, on the neural complexity of EEG signals obtained from patients undergoing chemotherapy. The secondary goal was to compare the EEG signal complexity values for monochords with those for progressive muscle relaxation (PMR), an alternative therapy for relaxation. Forty cancer patients were randomly allocated to one of the two relaxation groups, MC and PMR, over a period of six months; continuous EEG signals were recorded during the first and last sessions. EEG signals were analyzed by applying signal mode complexity, a measure of complexity of neuronal oscillations. Across sessions, both groups showed a modulation of complexity of beta-2 band (20-29Hz) at midfrontal regions, but only MC group showed a modulation of complexity of theta band (3.5-7.5Hz) at posterior regions. Therefore, the neuronal complexity patterns showed different changes in EEG frequency band specific complexity resulting in two different types of interventions. Moreover, the different neural responses to listening to monochords and PMR were observed after regular relaxation interventions over a short time span.

How to write an EEG report

PubMed Central

Benbadis, Selim R.

2013-01-01

The EEG report is structured to include demographics of the patient studied and reason for the EEG; specifics of the EEG techniques used; a description of the patterns, frequencies, voltages, and progression of the EEG pattern that were recorded; and finally a clinical impression of the EEG significance. The interpretation should be concise, clear and to the point, avoid jargon and EEG specifics, and should be understandable by any health care practitioner. PMID:23267044

Mouse EEG spike detection based on the adapted continuous wavelet transform

NASA Astrophysics Data System (ADS)

Tieng, Quang M.; Kharatishvili, Irina; Chen, Min; Reutens, David C.

2016-04-01

Objective. Electroencephalography (EEG) is an important tool in the diagnosis of epilepsy. Interictal spikes on EEG are used to monitor the development of epilepsy and the effects of drug therapy. EEG recordings are generally long and the data voluminous. Thus developing a sensitive and reliable automated algorithm for analyzing EEG data is necessary. Approach. A new algorithm for detecting and classifying interictal spikes in mouse EEG recordings is proposed, based on the adapted continuous wavelet transform (CWT). The construction of the adapted mother wavelet is founded on a template obtained from a sample comprising the first few minutes of an EEG data set. Main Result. The algorithm was tested with EEG data from a mouse model of epilepsy and experimental results showed that the algorithm could distinguish EEG spikes from other transient waveforms with a high degree of sensitivity and specificity. Significance. Differing from existing approaches, the proposed approach combines wavelet denoising, to isolate transient signals, with adapted CWT-based template matching, to detect true interictal spikes. Using the adapted wavelet constructed from a predefined template, the adapted CWT is calculated on small EEG segments to fit dynamical changes in the EEG recording.

Sensor Level Functional Connectivity Topography Comparison Between Different References Based EEG and MEG.

PubMed

Huang, Yunzhi; Zhang, Junpeng; Cui, Yuan; Yang, Gang; Liu, Qi; Yin, Guangfu

2018-01-01

Sensor-level functional connectivity topography (sFCT) contributes significantly to our understanding of brain networks. sFCT can be constructed using either electroencephalography (EEG) or magnetoencephalography (MEG). Here, we compared sFCT within the EEG modality and between EEG and MEG modalities. We first used simulations to look at how different EEG references-including the Reference Electrode Standardization Technique (REST), average reference (AR), linked mastoids (LM), and left mastoid references (LR)-affect EEG-based sFCT. The results showed that REST decreased the reference effects on scalp EEG recordings, making REST-based sFCT closer to the ground truth (sFCT based on ideal recordings). For the inter-modality simulation comparisons, we compared each type of EEG-sFCT with MEG-sFCT using three metrics to quantize the differences: Relative Error (RE), Overlap Rate (OR), and Hamming Distance (HD). When two sFCTs are similar, RE and HD are low, while OR is high. Results showed that among all reference schemes, EEG-and MEG-sFCT were most similar when the EEG was REST-based and the EEG and MEG were recorded simultaneously. Next, we analyzed simultaneously recorded MEG and EEG data from publicly available face-recognition experiments using a similar procedure as in the simulations. The results showed (1) if MEG-sFCT is the standard, REST-and LM-based sFCT provided results closer to this standard in the terms of HD; (2) REST-based sFCT and MEG-sFCT had the highest similarity in terms of RE; (3) REST-based sFCT had the most overlapping edges with MEG-sFCT in terms of OR. This study thus provides new insights into the effect of different reference schemes on sFCT and the similarity between MEG and EEG in terms of sFCT.

Sensor Level Functional Connectivity Topography Comparison Between Different References Based EEG and MEG

PubMed Central

Huang, Yunzhi; Zhang, Junpeng; Cui, Yuan; Yang, Gang; Liu, Qi; Yin, Guangfu

2018-01-01

Sensor-level functional connectivity topography (sFCT) contributes significantly to our understanding of brain networks. sFCT can be constructed using either electroencephalography (EEG) or magnetoencephalography (MEG). Here, we compared sFCT within the EEG modality and between EEG and MEG modalities. We first used simulations to look at how different EEG references—including the Reference Electrode Standardization Technique (REST), average reference (AR), linked mastoids (LM), and left mastoid references (LR)—affect EEG-based sFCT. The results showed that REST decreased the reference effects on scalp EEG recordings, making REST-based sFCT closer to the ground truth (sFCT based on ideal recordings). For the inter-modality simulation comparisons, we compared each type of EEG-sFCT with MEG-sFCT using three metrics to quantize the differences: Relative Error (RE), Overlap Rate (OR), and Hamming Distance (HD). When two sFCTs are similar, RE and HD are low, while OR is high. Results showed that among all reference schemes, EEG-and MEG-sFCT were most similar when the EEG was REST-based and the EEG and MEG were recorded simultaneously. Next, we analyzed simultaneously recorded MEG and EEG data from publicly available face-recognition experiments using a similar procedure as in the simulations. The results showed (1) if MEG-sFCT is the standard, REST—and LM-based sFCT provided results closer to this standard in the terms of HD; (2) REST-based sFCT and MEG-sFCT had the highest similarity in terms of RE; (3) REST-based sFCT had the most overlapping edges with MEG-sFCT in terms of OR. This study thus provides new insights into the effect of different reference schemes on sFCT and the similarity between MEG and EEG in terms of sFCT. PMID:29867395

Symptomatic complex partial status epilepticus manifesting as utilization behavior of a mobile phone.

PubMed

Carota, Antonio; Novy, Jan; Rossetti, Andrea O

2009-03-01

Utilization behavior (UB) consists of reaching out and using objects in the environment in an automatic manner and out of context. This behavior has been correlated to frontal lobe dysfunction, especially of the right hemisphere. We describe a 60-year-old woman, affected by a glioblastoma located in the right frontal region, who presented with intermittent UB of the mobile phone as the main clinical manifestation of partial complex status epilepticus. Video/EEG studies showed a striking correlation between mobile phone utilization and ictal epileptic activity. Clinical and EEG findings were markedly reduced after the introduction of antiepileptic drugs. This case study suggests that UB may be added to the symptoms described for partial seizures originating from frontal areas.

Earlier tachycardia onset in right than left mesial temporal lobe seizures.

PubMed

Kato, Kazuhiro; Jin, Kazutaka; Itabashi, Hisashi; Iwasaki, Masaki; Kakisaka, Yosuke; Aoki, Masashi; Nakasato, Nobukazu

2014-10-07

To clarify whether the presence and timing of peri-ictal heart rate (HR) change is a seizure lateralizing sign in patients with mesial temporal lobe epilepsy (mTLE). Long-term video EEGs were retrospectively reviewed in 21 patients, 7 men and 14 women aged 13 to 67 years, diagnosed as mTLE with MRI lesions in the mesial temporal structures (hippocampal sclerosis in 20 cases, amygdala hypertrophy in 1 case). Seventy-seven partial seizures without secondary generalization were extracted. Peri-ictal HR change was compared between 29 right seizures (9 patients) and 48 left seizures (12 patients). HR abruptly increased in all 29 right seizures and 42 of 48 left seizures. Onset time of HR increase in relation to ictal EEG onset was significantly earlier in right seizures than in left seizures (mean ± SD, -11.5 ± 14.8 vs 9.2 ± 21.7 seconds; p < 0.0001). Time of maximum HR was also significantly earlier in right seizures than in left seizures (36.0 ± 18.1 vs 58.0 ± 28.7 seconds; p < 0.0001). Maximum HR changes from baseline showed no significant difference between right and left seizures (47.5 ± 19.1 vs 40.8 ± 20.0/min). Significantly earlier tachycardia in right than left mTLE seizures supports previous hypotheses that the right cerebral hemisphere is dominant in the sympathetic network. No HR change, or delayed tachycardia possibly due to seizure propagation to the right hemisphere, may be a useful lateralizing sign of left mTLE seizures. © 2014 American Academy of Neurology.

Characterizing the EEG correlates of exploratory behavior.

PubMed

Bourdaud, Nicolas; Chavarriaga, Ricardo; Galan, Ferran; Millan, José Del R

2008-12-01

This study aims to characterize the electroencephalography (EEG) correlates of exploratory behavior. Decision making in an uncertain environment raises a conflict between two opposing needs: gathering information about the environment and exploiting this knowledge in order to optimize the decision. Exploratory behavior has already been studied using functional magnetic resonance imaging (fMRI). Based on a usual paradigm in reinforcement learning, this study has shown bilateral activation in the frontal and parietal cortex. To our knowledge, no previous study has been done on it using EEG. The study of the exploratory behavior using EEG signals raises two difficulties. First, the labels of trial as exploitation or exploration cannot be directly derived from the subject action. In order to access this information, a model of how the subject makes his decision must be built. The exploration related information can be then derived from it. Second, because of the complexity of the task, its EEG correlates are not necessarily time locked with the action. So the EEG processing methods used should be designed in order to handle signals that shift in time across trials. Using the same experimental protocol as the fMRI study, results show that the bilateral frontal and parietal areas are also the most discriminant. This strongly suggests that the EEG signal also conveys information about the exploratory behavior.

Highly Efficient Compression Algorithms for Multichannel EEG.

PubMed

Shaw, Laxmi; Rahman, Daleef; Routray, Aurobinda

2018-05-01

The difficulty associated with processing and understanding the high dimensionality of electroencephalogram (EEG) data requires developing efficient and robust compression algorithms. In this paper, different lossless compression techniques of single and multichannel EEG data, including Huffman coding, arithmetic coding, Markov predictor, linear predictor, context-based error modeling, multivariate autoregression (MVAR), and a low complexity bivariate model have been examined and their performances have been compared. Furthermore, a high compression algorithm named general MVAR and a modified context-based error modeling for multichannel EEG have been proposed. The resulting compression algorithm produces a higher relative compression ratio of 70.64% on average compared with the existing methods, and in some cases, it goes up to 83.06%. The proposed methods are designed to compress a large amount of multichannel EEG data efficiently so that the data storage and transmission bandwidth can be effectively used. These methods have been validated using several experimental multichannel EEG recordings of different subjects and publicly available standard databases. The satisfactory parametric measures of these methods, namely percent-root-mean square distortion, peak signal-to-noise ratio, root-mean-square error, and cross correlation, show their superiority over the state-of-the-art compression methods.

Evaluation of Dry Sensors for Neonatal EEG recordings

PubMed Central

Fridman, Igor; Cordeiro, Malaika; Rais-Bahrami, Khodayar; McDonald, Neil J.; Reese, James J.; Massaro, An N.; Conry, Joan A.; Chang, Taeun; Soussou, Walid; Tsuchida, Tammy N.

2015-01-01

Introduction Neonatal seizures are a common neurologic diagnosis in Neonatal Intensive Care Units (NICUs), occurring in approximately 14,000 newborns annually in the US. While the only reliable means of detecting and treating neonatal seizures is with an EEG recording, many neonates do not get an EEG or experience delays in getting them. Barriers to obtaining neonatal EEGs include: 1) lack of skilled EEG technologists to apply conventional wet electrodes to delicate neonatal skin, 2) poor signal quality due to improper skin preparation and artifact, 3) extensive time needed to apply electrodes. Dry sensors have the potential to overcome these obstacles but have not been previously evaluated on neonates. Methods Sequential and simultaneous recordings with wet and dry sensors were performed for one hour on 27 neonates from 35-42.5 weeks postmenstrual age. Recordings were analyzed for correlation and amplitude, and were reviewed by neurophysiologists. Performance of dry sensors on simulated vernix was examined. Results Analysis of dry and wet signals showed good time-domain correlation (reaching >0.8) given the non-superimposed sensor positions, and similar power spectral density curves. Neurophysiologist reviews showed no statistically significant difference between dry and wet data on most clinically-relevant EEG background and seizure patterns. There was no skin injury after 1 hr of dry sensor recordings. In contrast to wet electrodes, impedance and electrical artifact of dry sensors were largely unaffected by simulated vernix. Conclusions Dry sensors evaluated in this study have the potential to provide high-quality, timely EEG recordings on neonates with less risk of skin injury. PMID:26562208

Evaluation of Dry Sensors for Neonatal EEG Recordings.

PubMed

Fridman, Igor; Cordeiro, Malaika; Rais-Bahrami, Khodayar; McDonald, Neil J; Reese, James J; Massaro, An N; Conry, Joan A; Chang, Taeun; Soussou, Walid; Tsuchida, Tammy N

2016-04-01

Neonatal seizures are a common neurologic diagnosis in neonatal intensive care units, occurring in approximately 14,000 newborns annually in the United States. Although the only reliable means of detecting and treating neonatal seizures is with an electroencephalography (EEG) recording, many neonates do not receive an EEG or experience delays in getting them. Barriers to obtaining neonatal EEGs include (1) lack of skilled EEG technologists to apply conventional wet electrodes to delicate neonatal skin, (2) poor signal quality because of improper skin preparation and artifact, and (3) extensive time needed to apply electrodes. Dry sensors have the potential to overcome these obstacles but have not previously been evaluated on neonates. Sequential and simultaneous recordings with wet and dry sensors were performed for 1 hour on 27 neonates from 35 to 42.5 weeks postmenstrual age. Recordings were analyzed for correlation and amplitude and were reviewed by neurophysiologists. Performance of dry sensors on simulated vernix was examined. Analysis of dry and wet signals showed good time-domain correlation (reaching >0.8), given the nonsuperimposed sensor positions and similar power spectral density curves. Neurophysiologist reviews showed no statistically significant difference between dry and wet data on most clinically relevant EEG background and seizure patterns. There was no skin injury after 1 hour of dry sensor recordings. In contrast to wet electrodes, impedance and electrical artifact of dry sensors were largely unaffected by simulated vernix. Dry sensors evaluated in this study have the potential to provide high-quality, timely EEG recordings on neonates with less risk of skin injury.

EEG in connection with coma.

PubMed

Wilson, John A; Nordal, Helge J

2013-01-08

Coma is a dynamic condition that may have various causes. Important changes may take place rapidly, often with consequences for treatment. The purpose of this article is to provide a brief overview of EEG patterns in comas with various causes, and indicate how EEG contributes in an assessment of the prognosis for coma patients. The article is based on many years of clinical and research-based experience of EEG used for patients in coma. A self-built reference database was supplemented by searches for relevant articles in PubMed. EEG reveals immediate changes in coma, and can provide early information on cause and prognosis. It is the only diagnostic tool for detecting a non-convulsive epileptic status. Locked-in- syndrome may be overseen without EEG. Repeated EEG scans increase diagnostic certainty and make it possible to monitor the development of coma. EEG reflects brain function continuously and therefore holds a key place in the assessment and treatment of coma.

Tele-transmission of EEG recordings.

PubMed

Lemesle, M; Kubis, N; Sauleau, P; N'Guyen The Tich, S; Touzery-de Villepin, A

2015-03-01

EEG recordings can be sent for remote interpretation. This article aims to define the tele-EEG procedures and technical guidelines. Tele-EEG is a complete medical act that needs to be carried out with the same quality requirements as a local one in terms of indications, formulation of the medical request and medical interpretation. It adheres to the same quality requirements for its human resources and materials. It must be part of a medical organization (technical and medical network) and follow all rules and guidelines of good medical practices. The financial model of this organization must include costs related to performing the EEG recording, operating and maintenance of the tele-EEG network and medical fees of the physician interpreting the EEG recording. Implementing this organization must be detailed in a convention between all parties involved: physicians, management of the healthcare structure, and the company providing the tele-EEG service. This convention will set rules for network operation and finance, and also the continuous training of all staff members. The tele-EEG system must respect all rules for safety and confidentiality, and ensure the traceability and storing of all requests and reports. Under these conditions, tele-EEG can optimize the use of human resources and competencies in its zone of utilization and enhance the organization of care management. Copyright © 2015. Published by Elsevier SAS.

[EEG-markers of vertical postural organization in healthy persons].

PubMed

Zhavoronkova, L A; Zharikova, A V; Kushnir, E M; Mikhalkova, A A

2012-01-01

In 10 healthy persons (22.8 +/- 0.67 years) spectral-coherence parameters of EEG were analyzed in different steps of verticalizations--from gorizontal position to seat and stand one. Maximal changes of all EEG parameters were observed in state with absence of visual control. We observed an increase of power for fast spectral bands of EEG (beta- and gamma-bands) in all conditions and additional increase of these EEG parameters was observed at situation of complication of conditions of vertical pose supporting. Results of EEG coherent analysis in conditions of human verticalization showed specific increase of coherence for the majority of rhythm ranges in the right hemisphere especially in the central-frontal and in occipital-parietal areas and for interhemispheric pairs for these leads. This fact can reflect participation of cortical as well as subcortical structures in these processes. In conditions of complicate conditions of vertical pose supporting the additional increase of EEG coherence in fast bands (beta-rhythm) was observed at the frontal areas. This fact can testify about increasing of executive functions in this conditions.

Length matters: Improved high field EEG-fMRI recordings using shorter EEG cables.

PubMed

Assecondi, Sara; Lavallee, Christina; Ferrari, Paolo; Jovicich, Jorge

2016-08-30

The use of concurrent EEG-fMRI recordings has increased in recent years, allowing new avenues of medical and cognitive neuroscience research; however, currently used setups present problems with data quality and reproducibility. We propose a compact experimental setup for concurrent EEG-fMRI at 4T and compare it to a more standard reference setup. The compact setup uses short EEG cables connecting to the amplifiers, which are placed right at the back of the head RF coil on a form-fitting extension force-locked to the patient MR bed. We compare the two setups in terms of sensitivity to MR-room environmental noise, interferences between measuring devices (EEG or fMRI), and sensitivity to functional responses in a visual stimulation paradigm. The compact setup reduces the system sensitivity to both external noise and MR-induced artefacts by at least 60%, with negligible EEG noise induced from the mechanical vibrations of the cryogenic cooling compression pump. The compact setup improved EEG data quality and the overall performance of MR-artifact correction techniques. Both setups were similar in terms of the fMRI data, with higher reproducibility for cable placement within the scanner in the compact setup. This improved compact setup may be relevant to MR laboratories interested in reducing the sensitivity of their EEG-fMRI experimental setup to external noise sources, setting up an EEG-fMRI workplace for the first time, or for creating a more reproducible configuration of equipment and cables. Implications for safety and ergonomics are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

EEG source imaging during two Qigong meditations.

PubMed

Faber, Pascal L; Lehmann, Dietrich; Tei, Shisei; Tsujiuchi, Takuya; Kumano, Hiroaki; Pascual-Marqui, Roberto D; Kochi, Kieko

2012-08-01

Experienced Qigong meditators who regularly perform the exercises "Thinking of Nothing" and "Qigong" were studied with multichannel EEG source imaging during their meditations. The intracerebral localization of brain electric activity during the two meditation conditions was compared using sLORETA functional EEG tomography. Differences between conditions were assessed using t statistics (corrected for multiple testing) on the normalized and log-transformed current density values of the sLORETA images. In the EEG alpha-2 frequency, 125 voxels differed significantly; all were more active during "Qigong" than "Thinking of Nothing," forming a single cluster in parietal Brodmann areas 5, 7, 31, and 40, all in the right hemisphere. In the EEG beta-1 frequency, 37 voxels differed significantly; all were more active during "Thinking of Nothing" than "Qigong," forming a single cluster in prefrontal Brodmann areas 6, 8, and 9, all in the left hemisphere. Compared to combined initial-final no-task resting, "Qigong" showed activation in posterior areas whereas "Thinking of Nothing" showed activation in anterior areas. The stronger activity of posterior (right) parietal areas during "Qigong" and anterior (left) prefrontal areas during "Thinking of Nothing" may reflect a predominance of self-reference, attention and input-centered processing in the "Qigong" meditation, and of control-centered processing in the "Thinking of Nothing" meditation.

Epileptogenic developmental venous anomaly: insights from simultaneous EEG/fMRI.

PubMed

Scheidegger, Olivier; Wiest, Roland; Jann, Kay; König, Thomas; Meyer, Klaus; Hauf, Martinus

2013-04-01

Developmental venous anomalies (DVAs) are associated with epileptic seizures; however, the role of DVA in the epileptogenesis is still not established. Simultaneous interictal electroencephalogram/functional magnetic resonance imaging (EEG/fMRI) recordings provide supplementary information to electroclinical data about the epileptic generators, and thus aid in the differentiation of clinically equivocal epilepsy syndromes. The main objective of our study was to characterize the epileptic network in a patient with DVA and epilepsy by simultaneous EEG/fMRI recordings. A 17-year-old woman with recently emerging generalized tonic-clonic seizures, and atypical generalized discharges, was investigated using simultaneous EEG/fMRI at the university hospital. Previous high-resolution MRI showed no structural abnormalities, except a DVA in the right frontal operculum. Interictal EEG recordings showed atypical generalized discharges, corresponding to positive focal blood oxygen level dependent (BOLD) correlates in the right frontal operculum, a region drained by the DVA. Additionally, widespread cortical bilateral negative BOLD correlates in the frontal and parietal lobes were delineated, resembling a generalized epileptic network. The EEG/fMRI recordings support a right frontal lobe epilepsy, originating in the vicinity of the DVA, propagating rapidly to both frontal and parietal lobes, as expressed on the scalp EEG by secondary bilateral synchrony. The DVA may be causative of focal epilepsies in cases where no concomitant epileptogenic lesions can be detected. Advanced imaging techniques, such as simultaneous EEG/fMRI, may thus aid in the differentiation of clinically equivocal epilepsy syndromes.

Singular spectrum analysis of sleep EEG in insomnia.

PubMed

Aydın, Serap; Saraoǧlu, Hamdi Melih; Kara, Sadık

2011-08-01

In the present study, the Singular Spectrum Analysis (SSA) is applied to sleep EEG segments collected from healthy volunteers and patients diagnosed by either psycho physiological insomnia or paradoxical insomnia. Then, the resulting singular spectra computed for both C3 and C4 recordings are assigned as the features to the Artificial Neural Network (ANN) architectures for EEG classification in diagnose. In tests, singular spectrum of particular sleep stages such as awake, REM, stage1 and stage2, are considered. Three clinical groups are successfully classified by using one hidden layer ANN architecture with respect to their singular spectra. The results show that the SSA can be applied to sleep EEG series to support the clinical findings in insomnia if ten trials are available for the specific sleep stages. In conclusion, the SSA can detect the oscillatory variations on sleep EEG. Therefore, different sleep stages meet different singular spectra. In addition, different healthy conditions generate different singular spectra for each sleep stage. In summary, the SSA can be proposed for EEG discrimination to support the clinical findings for psycho-psychological disorders.

Surface EEG Shows that Functional Segregation via Phase Coupling Contributes to the Neural Substrate of Mental Calculations

ERIC Educational Resources Information Center

Dimitriadis, Stavros I.; Kanatsouli, Kassiani; Laskaris, Nikolaos A.; Tsirka, Vasso; Vourkas, Michael; Micheloyannis, Sifis

2012-01-01

Multichannel EEG traces from healthy subjects are used to investigate the brain's self-organisation tendencies during two different mental arithmetic tasks. By making a comparison with a control-state in the form of a classification problem, we can detect and quantify the changes in coordinated brain activity in terms of functional connectivity.…

EEG slow waves in traumatic brain injury: Convergent findings in mouse and man

PubMed Central

Modarres, Mo; Kuzma, Nicholas N.; Kretzmer, Tracy; Pack, Allan I.; Lim, Miranda M.

2016-01-01

Objective Evidence from previous studies suggests that greater sleep pressure, in the form of EEG-based slow waves, accumulates in specific brain regions that are more active during prior waking experience. We sought to quantify the number and coherence of EEG slow waves in subjects with mild traumatic brain injury (mTBI). Methods We developed a method to automatically detect individual slow waves in each EEG channel, and validated this method using simulated EEG data. We then used this method to quantify EEG-based slow waves during sleep and wake states in both mouse and human subjects with mTBI. A modified coherence index that accounts for information from multiple channels was calculated as a measure of slow wave synchrony. Results Brain-injured mice showed significantly higher theta:alpha amplitude ratios and significantly more slow waves during spontaneous wakefulness and during prolonged sleep deprivation, compared to sham-injured control mice. Human subjects with mTBI showed significantly higher theta:beta amplitude ratios and significantly more EEG slow waves while awake compared to age-matched control subjects. We then quantified the global coherence index of slow waves across several EEG channels in human subjects. Individuals with mTBI showed significantly less EEG global coherence compared to control subjects while awake, but not during sleep. EEG global coherence was significantly correlated with severity of post-concussive symptoms (as assessed by the Neurobehavioral Symptom Inventory scale). Conclusion and implications Taken together, our data from both mouse and human studies suggest that EEG slow wave quantity and the global coherence index of slow waves may represent a sensitive marker for the diagnosis and prognosis of mTBI and post-concussive symptoms. PMID:28018987

EEG slow waves in traumatic brain injury: Convergent findings in mouse and man.

PubMed

Modarres, Mo; Kuzma, Nicholas N; Kretzmer, Tracy; Pack, Allan I; Lim, Miranda M

2016-07-01

Evidence from previous studies suggests that greater sleep pressure, in the form of EEG-based slow waves, accumulates in specific brain regions that are more active during prior waking experience. We sought to quantify the number and coherence of EEG slow waves in subjects with mild traumatic brain injury (mTBI). We developed a method to automatically detect individual slow waves in each EEG channel, and validated this method using simulated EEG data. We then used this method to quantify EEG-based slow waves during sleep and wake states in both mouse and human subjects with mTBI. A modified coherence index that accounts for information from multiple channels was calculated as a measure of slow wave synchrony. Brain-injured mice showed significantly higher theta:alpha amplitude ratios and significantly more slow waves during spontaneous wakefulness and during prolonged sleep deprivation, compared to sham-injured control mice. Human subjects with mTBI showed significantly higher theta:beta amplitude ratios and significantly more EEG slow waves while awake compared to age-matched control subjects. We then quantified the global coherence index of slow waves across several EEG channels in human subjects. Individuals with mTBI showed significantly less EEG global coherence compared to control subjects while awake, but not during sleep. EEG global coherence was significantly correlated with severity of post-concussive symptoms (as assessed by the Neurobehavioral Symptom Inventory scale). Taken together, our data from both mouse and human studies suggest that EEG slow wave quantity and the global coherence index of slow waves may represent a sensitive marker for the diagnosis and prognosis of mTBI and post-concussive symptoms.

A Discriminative Approach to EEG Seizure Detection

PubMed Central

Johnson, Ashley N.; Sow, Daby; Biem, Alain

2011-01-01

Seizures are abnormal sudden discharges in the brain with signatures represented in electroencephalograms (EEG). The efficacy of the application of speech processing techniques to discriminate between seizure and non-seizure states in EEGs is reported. The approach accounts for the challenges of unbalanced datasets (seizure and non-seizure), while also showing a system capable of real-time seizure detection. The Minimum Classification Error (MCE) algorithm, which is a discriminative learning algorithm with wide-use in speech processing, is applied and compared with conventional classification techniques that have already been applied to the discrimination between seizure and non-seizure states in the literature. The system is evaluated on 22 pediatric patients multi-channel EEG recordings. Experimental results show that the application of speech processing techniques and MCE compare favorably with conventional classification techniques in terms of classification performance, while requiring less computational overhead. The results strongly suggests the possibility of deploying the designed system at the bedside. PMID:22195192

Statistical features of hypnagogic EEG measured by a new scoring system.

PubMed

Tanaka, H; Hayashi, M; Hori, T

1996-11-01

The purpose of this study was to examine the durations of individual occurrences of each of nine hypnagogic electroencephalographic (EEG) stages and the interchange relationship among these stages. Most of the alpha patterns (stages 1, 2, and 3), ripples (stage 5), and spindles (stage 9) tended to last > 2 minutes. On the other hand, histograms of the durations of time in EEG flattening (stage 4) and vertex sharp wave (stages 6, 7, and 8) patterns had peaks that lasted < 30 seconds. Analysis of the sequences of EEG stage changes demonstrated that shifts to adjacent stages were most common for all stages. A smooth change in EEG stage occurred in the downward or upward direction in the hypnagogic state. This was especially true for the first five stages. EEG stages with vertex sharp waves (stages 6, 7, and 8), however, showed less-smooth changes, with approximately 20% of all changes involving a jump of more than one stage. These results show that the basic EEG activities in the sleep onset period are the alpha, theta, and sleep spindles activities, whereas the activities of vertex sharp waves seem to have a secondary or enhancing role, instead of independent characteristics.

Mental Task Evaluation for Hybrid NIRS-EEG Brain-Computer Interfaces

PubMed Central

Gupta, Rishabh; Falk, Tiago H.

2017-01-01

Based on recent electroencephalography (EEG) and near-infrared spectroscopy (NIRS) studies that showed that tasks such as motor imagery and mental arithmetic induce specific neural response patterns, we propose a hybrid brain-computer interface (hBCI) paradigm in which EEG and NIRS data are fused to improve binary classification performance. We recorded simultaneous NIRS-EEG data from nine participants performing seven mental tasks (word generation, mental rotation, subtraction, singing and navigation, and motor and face imagery). Classifiers were trained for each possible pair of tasks using (1) EEG features alone, (2) NIRS features alone, and (3) EEG and NIRS features combined, to identify the best task pairs and assess the usefulness of a multimodal approach. The NIRS-EEG approach led to an average increase in peak kappa of 0.03 when using features extracted from one-second windows (equivalent to an increase of 1.5% in classification accuracy for balanced classes). The increase was much stronger (0.20, corresponding to an 10% accuracy increase) when focusing on time windows of high NIRS performance. The EEG and NIRS analyses further unveiled relevant brain regions and important feature types. This work provides a basis for future NIRS-EEG hBCI studies aiming to improve classification performance toward more efficient and flexible BCIs. PMID:29181021

Spatio-Temporal EEG Models for Brain Interfaces

PubMed Central

Gonzalez-Navarro, P.; Moghadamfalahi, M.; Akcakaya, M.; Erdogmus, D.

2016-01-01

Multichannel electroencephalography (EEG) is widely used in non-invasive brain computer interfaces (BCIs) for user intent inference. EEG can be assumed to be a Gaussian process with unknown mean and autocovariance, and the estimation of parameters is required for BCI inference. However, the relatively high dimensionality of the EEG feature vectors with respect to the number of labeled observations lead to rank deficient covariance matrix estimates. In this manuscript, to overcome ill-conditioned covariance estimation, we propose a structure for the covariance matrices of the multichannel EEG signals. Specifically, we assume that these covariances can be modeled as a Kronecker product of temporal and spatial covariances. Our results over the experimental data collected from the users of a letter-by-letter typing BCI show that with less number of parameter estimations, the system can achieve higher classification accuracies compared to a method that uses full unstructured covariance estimation. Moreover, in order to illustrate that the proposed Kronecker product structure could enable shortening the BCI calibration data collection sessions, using Cramer-Rao bound analysis on simulated data, we demonstrate that a model with structured covariance matrices will achieve the same estimation error as a model with no covariance structure using fewer labeled EEG observations. PMID:27713590

Analysis of intracerebral EEG recordings of epileptic spikes: insights from a neural network model

PubMed Central

Demont-Guignard, Sophie; Benquet, Pascal; Gerber, Urs; Wendling, Fabrice

2009-01-01

The pathophysiological interpretation of EEG signals recorded with depth electrodes (i.e. local field potentials, LFPs) during interictal (between seizures) or ictal (during seizures) periods is fundamental in the pre-surgical evaluation of patients with drug-resistant epilepsy. Our objective was to explain specific shape features of interictal spikes in the hippocampus (observed in LFPs) in terms of cell and network-related parameters of neuronal circuits that generate these events. We developed a neural network model based on “minimal” but biologically-relevant neuron models interconnected through GABAergic and glutamatergic synapses that reproduces the main physiological features of the CA1 subfield. Simulated LFPs were obtained by solving the forward problem (dipole theory) from networks including a large number (~3000) of cells. Insertion of appropriate parameters allowed the model to simulate events that closely resemble actual epileptic spikes. Moreover, the shape of the early fast component (‘spike’) and the late slow component (‘negative wave’) was linked to the relative contribution of glutamatergic and GABAergic synaptic currents in pyramidal cells. In addition, the model provides insights about the sensitivity of electrode localization with respect to recorded tissue volume and about the relationship between the LFP and the intracellular activity of principal cells and interneurons represented in the network. PMID:19651549

EEG analysis of seizure patterns using visibility graphs for detection of generalized seizures.

PubMed

Wang, Lei; Long, Xi; Arends, Johan B A M; Aarts, Ronald M

2017-10-01

The traditional EEG features in the time and frequency domain show limited seizure detection performance in the epileptic population with intellectual disability (ID). In addition, the influence of EEG seizure patterns on detection performance was less studied. A single-channel EEG signal can be mapped into visibility graphs (VGS), including basic visibility graph (VG), horizontal VG (HVG), and difference VG (DVG). These graphs were used to characterize different EEG seizure patterns. To demonstrate its effectiveness in identifying EEG seizure patterns and detecting generalized seizures, EEG recordings of 615h on one EEG channel from 29 epileptic patients with ID were analyzed. A novel feature set with discriminative power for seizure detection was obtained by using the VGS method. The degree distributions (DDs) of DVG can clearly distinguish EEG of each seizure pattern. The degree entropy and power-law degree power in DVG were proposed here for the first time, and they show significant difference between seizure and non-seizure EEG. The connecting structure measured by HVG can better distinguish seizure EEG from background than those by VG and DVG. A traditional EEG feature set based on frequency analysis was used here as a benchmark feature set. With a support vector machine (SVM) classifier, the seizure detection performance of the benchmark feature set (sensitivity of 24%, FD t /h of 1.8s) can be improved by combining our proposed VGS features extracted from one EEG channel (sensitivity of 38%, FD t /h of 1.4s). The proposed VGS-based features can help improve seizure detection for ID patients. Copyright © 2017 Elsevier B.V. All rights reserved.

EEG-fMRI evaluation of patients with mesial temporal lobe sclerosis.

PubMed

Avesani, Mirko; Giacopuzzi, Silvia; Bongiovanni, Luigi Giuseppe; Borelli, Paolo; Cerini, Roberto; Pozzi Mucelli, Roberto; Fiaschi, Antonio

2014-02-01

This preliminary study sought more information on blood oxygen level dependent (BOLD) activation, especially contralateral temporal/extratemporal spread, during continuous EEG-fMRI recordings in four patients with mesial temporal sclerosis (MTS). In two patients, EEG showed unilateral focal activity during the EEG-fMRI session concordant with the interictal focus previously identified with standard and video-poly EEG. In the other two patients EEG demonstrated a contralateral diffusion of the irritative focus. In the third patient (with the most drug-resistant form and also extratemporal clinical signs), there was an extratemporal diffusion over frontal regions, ipsilateral to the irritative focus. fMRI analysis confirmed a single activation in the mesial temporal region in two patients whose EEG showed unilateral focal activity, while it demonstrated a bilateral activation in the mesial temporal regions in the other two patients. In the third patient, fMRI demonstrated an activation in the supplementary motxor area. This study confirms the most significant activation with a high firing rate of the irritative focus, but also suggests the importance of using new techniques (such as EEG-fMRI to examine cerebral blood flow) to identify the controlateral limbic activation, and any other extratemporal activations, possible causes of drug resistance in MTS that may require a more precise pre-surgical evaluation with invasive techniques.

EEG-fMRI Evaluation of Patients with Mesial Temporal Lobe Sclerosis

PubMed Central

Avesani, Mirko; Giacopuzzi, Silvia; Bongiovanni, Luigi Giuseppe; Borelli, Paolo; Cerini, Roberto; Pozzi Mucelli, Roberto; Fiaschi, Antonio

2014-01-01

Summary This preliminary study sought more information on blood oxygen level dependent (BOLD) activation, especially contralateral temporal/extratemporal spread, during continuous EEG-fMRI recordings in four patients with mesial temporal sclerosis (MTS). In two patients, EEG showed unilateral focal activity during the EEG-fMRI session concordant with the interictal focus previously identified with standard and video-poly EEG. In the other two patients EEG demonstrated a contralateral diffusion of the irritative focus. In the third patient (with the most drug-resistant form and also extratemporal clinical signs), there was an extratemporal diffusion over frontal regions, ipsilateral to the irritative focus. fMRI analysis confirmed a single activation in the mesial temporal region in two patients whose EEG showed unilateral focal activity, while it demonstrated a bilateral activation in the mesial temporal regions in the other two patients. In the third patient, fMRI demonstrated an activation in the supplementary motxor area. This study confirms the most significant activation with a high firing rate of the irritative focus, but also suggests the importance of using new techniques (such as EEG-fMRI to examine cerebral blood flow) to identify the controlateral limbic activation, and any other extratemporal activations, possible causes of drug resistance in MTS that may require a more precise pre-surgical evaluation with invasive techniques. PMID:24571833

EEG Patterns Related to Cognitive Tasks of Varying Complexity.

ERIC Educational Resources Information Center

Dunn, Denise A.; And Others

A study was conducted that attempted to show changes in electroencephalographic (EEG) patterns (identified using topographic EEG mapping) when children were required to perform the relatively simple task of button pressing during an eyes-open baseline session of low cognitive demand and a complex reaction time (RT) task of high cognitive demand.…

Preoperative EEG predicts memory and selective cognitive functions after temporal lobe surgery.

PubMed Central

Tuunainen, A; Nousiainen, U; Hurskainen, H; Leinonen, E; Pilke, A; Mervaala, E; Vapalahti, M; Partanen, J; Riekkinen, P

1995-01-01

Preoperative and postoperative cognitive and memory functions, psychiatric outcome, and EEGs were evaluated in 32 epileptic patients who underwent temporal lobe surgery. The presence and location of preoperative slow wave focus in routine EEG predicted memory functions of the non-resected side after surgery. Neuropsychological tests of the function of the frontal lobes also showed improvement. Moreover, psychiatric ratings showed that seizure free patients had significantly less affective symptoms postoperatively than those who were still exhibiting seizures. After temporal lobectomies, successful outcome in postoperative memory functions can be achieved in patients with unilateral slow wave activity in preoperative EEGs. This study suggests a new role for routine EEG in preoperative evaluation of patients with temporal lobe epilepsy. PMID:7608663

Non-restraining EEG Radiotelemetry: Epidural and Deep Intracerebral Stereotaxic EEG Electrode Placement.

PubMed

Papazoglou, Anna; Lundt, Andreas; Wormuth, Carola; Ehninger, Dan; Henseler, Christina; Soós, Julien; Broich, Karl; Weiergräber, Marco

2016-06-25

Implantable EEG radiotelemetry is of central relevance in the neurological characterization of transgenic mouse models of neuropsychiatric and neurodegenerative diseases as well as epilepsies. This powerful technique does not only provide valuable insights into the underlying pathophysiological mechanisms, i.e., the etiopathogenesis of CNS related diseases, it also facilitates the development of new translational, i.e., therapeutic approaches. Whereas competing techniques that make use of recorder systems used in jackets or tethered systems suffer from their unphysiological restraining to semi-restraining character, radiotelemetric EEG recordings overcome these disadvantages. Technically, implantable EEG radiotelemetry allows for precise and highly sensitive measurement of epidural and deep, intracerebral EEGs under various physiological and pathophysiological conditions. First, we present a detailed protocol of a straight forward, successful, quick and efficient technique for epidural (surface) EEG recordings resulting in high-quality electrocorticograms. Second, we demonstrate how to implant deep, intracerebral EEG electrodes, e.g., in the hippocampus (electrohippocampogram). For both approaches, a computerized 3D stereotaxic electrode implantation system is used. The radiofrequency transmitter itself is implanted into a subcutaneous pouch in both mice and rats. Special attention also has to be paid to pre-, peri- and postoperative treatment of the experimental animals. Preoperative preparation of mice and rats, suitable anesthesia as well as postoperative treatment and pain management are described in detail.

Electroencephalography as a tool for evidence-based diagnosis and improved outcomes in children with epilepsy in a resource-poor setting.

PubMed

Lagunju, Ike Oluwa Abiola; Oyinlade, Alexander Opebiyi; Atalabi, Omolola Mojisola; Ogbole, Godwin; Tedimola, Olushola; Famosaya, Abimbola; Ogunniyi, Adesola; Ogunseyinde, Ayotunde Oluremi; Ragin, Ann

2015-01-01

Electroencephalography (EEG) remains the most important investigative modality in the diagnostic evaluation of individuals with epilepsy. Children living with epilepsy in the developing world are faced with challenges of lack of access to appropriate diagnostic evaluation and a high risk of misdiagnosis and inappropriate therapy. We appraised EEG studies in a cohort of Nigerian children with epilepsy seen in a tertiary center in order to evaluate access to and the impact of EEG in the diagnostic evaluation of the cases. Inter-ictal EEG was requested in all cases of pediatric epilepsy seen at the pediatric neurology clinic of the University College Hospital, Ibadan, Nigeria over a period of 18 months. Clinical diagnosis without EEG evaluation was compared with the final diagnosis post- EEG evaluation. A total of 329 EEGs were recorded in 329 children, aged 3 months to 16 years, median 61.0 months. Clinical evaluation pre-EEG classified 69.3% of the epilepsies as generalized. The a posteriori EEG evaluations showed a considerably higher proportion of localization-related epilepsies (33.6%). The final evaluation post EEG showed a 21% reduction in the proportion of cases labeled as generalized epilepsy and a 55% increase in cases of localization-related epilepsy(p<0.001). Here we show that there is a high risk of misdiagnosis and therefore the use of inappropriate therapies in children with epilepsy in the absence of EEG evaluation. The implications of our findings in the resource-poor country scenario are key for reducing the burden of care and cost of epilepsy treatment on both the caregivers and the already overloaded tertiary care services.

Dealing with noise and physiological artifacts in human EEG recordings: empirical mode methods

NASA Astrophysics Data System (ADS)

Runnova, Anastasiya E.; Grubov, Vadim V.; Khramova, Marina V.; Hramov, Alexander E.

2017-04-01

In the paper we propose the new method for removing noise and physiological artifacts in human EEG recordings based on empirical mode decomposition (Hilbert-Huang transform). As physiological artifacts we consider specific oscillatory patterns that cause problems during EEG analysis and can be detected with additional signals recorded simultaneously with EEG (ECG, EMG, EOG, etc.) We introduce the algorithm of the proposed method with steps including empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing these empirical modes and reconstructing of initial EEG signal. We show the efficiency of the method on the example of filtration of human EEG signal from eye-moving artifacts.

EEG-fMRI Bayesian framework for neural activity estimation: a simulation study.

PubMed

Croce, Pierpaolo; Basti, Alessio; Marzetti, Laura; Zappasodi, Filippo; Gratta, Cosimo Del

2016-12-01

Due to the complementary nature of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), and given the possibility of simultaneous acquisition, the joint data analysis can afford a better understanding of the underlying neural activity estimation. In this simulation study we want to show the benefit of the joint EEG-fMRI neural activity estimation in a Bayesian framework. We built a dynamic Bayesian framework in order to perform joint EEG-fMRI neural activity time course estimation. The neural activity is originated by a given brain area and detected by means of both measurement techniques. We have chosen a resting state neural activity situation to address the worst case in terms of the signal-to-noise ratio. To infer information by EEG and fMRI concurrently we used a tool belonging to the sequential Monte Carlo (SMC) methods: the particle filter (PF). First, despite a high computational cost, we showed the feasibility of such an approach. Second, we obtained an improvement in neural activity reconstruction when using both EEG and fMRI measurements. The proposed simulation shows the improvements in neural activity reconstruction with EEG-fMRI simultaneous data. The application of such an approach to real data allows a better comprehension of the neural dynamics.

EEG-fMRI Bayesian framework for neural activity estimation: a simulation study

NASA Astrophysics Data System (ADS)

Croce, Pierpaolo; Basti, Alessio; Marzetti, Laura; Zappasodi, Filippo; Del Gratta, Cosimo

2016-12-01

Objective. Due to the complementary nature of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), and given the possibility of simultaneous acquisition, the joint data analysis can afford a better understanding of the underlying neural activity estimation. In this simulation study we want to show the benefit of the joint EEG-fMRI neural activity estimation in a Bayesian framework. Approach. We built a dynamic Bayesian framework in order to perform joint EEG-fMRI neural activity time course estimation. The neural activity is originated by a given brain area and detected by means of both measurement techniques. We have chosen a resting state neural activity situation to address the worst case in terms of the signal-to-noise ratio. To infer information by EEG and fMRI concurrently we used a tool belonging to the sequential Monte Carlo (SMC) methods: the particle filter (PF). Main results. First, despite a high computational cost, we showed the feasibility of such an approach. Second, we obtained an improvement in neural activity reconstruction when using both EEG and fMRI measurements. Significance. The proposed simulation shows the improvements in neural activity reconstruction with EEG-fMRI simultaneous data. The application of such an approach to real data allows a better comprehension of the neural dynamics.

Safety and EEG data quality of concurrent high-density EEG and high-speed fMRI at 3 Tesla

PubMed Central

Foged, Mette Thrane; Lindberg, Ulrich; Vakamudi, Kishore; Larsson, Henrik B. W.; Pinborg, Lars H.; Kjær, Troels W.; Fabricius, Martin; Svarer, Claus; Ozenne, Brice; Thomsen, Carsten; Beniczky, Sándor; Posse, Stefan

2017-01-01

Purpose Concurrent EEG and fMRI is increasingly used to characterize the spatial-temporal dynamics of brain activity. However, most studies to date have been limited to conventional echo-planar imaging (EPI). There is considerable interest in integrating recently developed high-speed fMRI methods with high-density EEG to increase temporal resolution and sensitivity for task-based and resting state fMRI, and for detecting interictal spikes in epilepsy. In the present study using concurrent high-density EEG and recently developed high-speed fMRI methods, we investigate safety of radiofrequency (RF) related heating, the effect of EEG on cortical signal-to-noise ratio (SNR) in fMRI, and assess EEG data quality. Materials and methods The study compared EPI, multi-echo EPI, multi-band EPI and multi-slab echo-volumar imaging pulse sequences, using clinical 3 Tesla MR scanners from two different vendors that were equipped with 64- and 256-channel MR-compatible EEG systems, respectively, and receive only array head coils. Data were collected in 11 healthy controls (3 males, age range 18–70 years) and 13 patients with epilepsy (8 males, age range 21–67 years). Three of the healthy controls were scanned with the 256-channel EEG system, the other subjects were scanned with the 64-channel EEG system. Scalp surface temperature, SNR in occipital cortex and head movement were measured with and without the EEG cap. The degree of artifacts and the ability to identify background activity was assessed by visual analysis by a trained expert in the 64 channel EEG data (7 healthy controls, 13 patients). Results RF induced heating at the surface of the EEG electrodes during a 30-minute scan period with stable temperature prior to scanning did not exceed 1.0° C with either EEG system and any of the pulse sequences used in this study. There was no significant decrease in cortical SNR due to the presence of the EEG cap (p > 0.05). No significant differences in the visually analyzed EEG

Safety and EEG data quality of concurrent high-density EEG and high-speed fMRI at 3 Tesla.

PubMed

Foged, Mette Thrane; Lindberg, Ulrich; Vakamudi, Kishore; Larsson, Henrik B W; Pinborg, Lars H; Kjær, Troels W; Fabricius, Martin; Svarer, Claus; Ozenne, Brice; Thomsen, Carsten; Beniczky, Sándor; Paulson, Olaf B; Posse, Stefan

2017-01-01

Concurrent EEG and fMRI is increasingly used to characterize the spatial-temporal dynamics of brain activity. However, most studies to date have been limited to conventional echo-planar imaging (EPI). There is considerable interest in integrating recently developed high-speed fMRI methods with high-density EEG to increase temporal resolution and sensitivity for task-based and resting state fMRI, and for detecting interictal spikes in epilepsy. In the present study using concurrent high-density EEG and recently developed high-speed fMRI methods, we investigate safety of radiofrequency (RF) related heating, the effect of EEG on cortical signal-to-noise ratio (SNR) in fMRI, and assess EEG data quality. The study compared EPI, multi-echo EPI, multi-band EPI and multi-slab echo-volumar imaging pulse sequences, using clinical 3 Tesla MR scanners from two different vendors that were equipped with 64- and 256-channel MR-compatible EEG systems, respectively, and receive only array head coils. Data were collected in 11 healthy controls (3 males, age range 18-70 years) and 13 patients with epilepsy (8 males, age range 21-67 years). Three of the healthy controls were scanned with the 256-channel EEG system, the other subjects were scanned with the 64-channel EEG system. Scalp surface temperature, SNR in occipital cortex and head movement were measured with and without the EEG cap. The degree of artifacts and the ability to identify background activity was assessed by visual analysis by a trained expert in the 64 channel EEG data (7 healthy controls, 13 patients). RF induced heating at the surface of the EEG electrodes during a 30-minute scan period with stable temperature prior to scanning did not exceed 1.0° C with either EEG system and any of the pulse sequences used in this study. There was no significant decrease in cortical SNR due to the presence of the EEG cap (p > 0.05). No significant differences in the visually analyzed EEG data quality were found between EEG

Music effects on EEG in intrusive and withdrawn mothers with depressive symptoms.

PubMed

Tornek, Alexandra; Field, Tiffany; Hernandez-Reif, Maria; Diego, Miguel; Jones, Nancy

2003-01-01

The EEG patterns of 48 intrusive and withdrawn mothers with depressive symptoms were assessed following a 20-minute music session to determine if the music had mood-altering effects. Half the mothers listened to classical music while half listened to rock music. Intrusive mothers were expected to have more positive responses and more symmetrical EEG following the calming classical music, while withdrawn mothers were expected to have a more positive response and symmetrical EEG following the energizing rock music. Although more positive EEGs were noted for rock music in both groups, only the withdrawn mothers showed a significant change in EEG toward symmetry following rock music, and only the intrusive mothers showed a decrease in cortisol levels following the rock music. Their State Anxiety Inventory (STAI) anxiety levels also decreased, while the Profile of Mood States (POMS) depressed mood levels decreased significantly for all four groups following music.

Noninvasive EEG correlates of overground and stair walking.

PubMed

Brantley, Justin A; Luu, Trieu Phat; Ozdemir, Recep; Zhu, Fangshi; Winslow, Anna T; Huang, Helen; Contreras-Vidal, Jose L

2016-08-01

Automated walking intention detection remains a challenge in lower-limb neuroprosthetic systems. Here, we assess the feasibility of extracting motor intent from scalp electroencephalography (EEG). First, we evaluated the corticomuscular coherence between central EEG electrodes (C1, Cz, C2) and muscles of the shank and thigh during walking on level ground and stairs. Second, we trained decoders to predict the linear envelope of the surface electromyogram (EMG). We observed significant EEG-led corticomuscular coupling between electrodes and sEMG (tibialis anterior) in the high delta (3-4 Hz) and low theta (4-5 Hz) frequency bands during level walking, indicating efferent signaling from the cortex to peripheral motor neurons. The coherence was increased between EEG and vastus lateralis and tibialis anterior in the delta band (<; 2 Hz) during stair ascent, indicating a task specific modulation in corticomuscular coupling. However, EMG was the leading signal for biceps femoris and gastrocnemius coherence during stair ascent, possibly representing afferent feedback loops from periphery to the motor cortex. Decoder validation showed that EEG signals contained information about the sEMG patterns during over ground walking, however, the accuracy of the predicted sEMG patterns decreased during the stair condition. Overall, these initial findings support the feasibility of integrating sEMG and EEG into a hybrid decoder for volitional control of lower limb neuroprostheses.

Is There a Relation between EEG-Slow Waves and Memory Dysfunction in Epilepsy? A Critical Appraisal

PubMed Central

Höller, Yvonne; Trinka, Eugen

2015-01-01

Is there a relationship between peri-ictal slow waves, loss of consciousness, memory, and slow-wave sleep, in patients with different forms of epilepsy? We hypothesize that mechanisms, which result in peri-ictal slow-wave activity as detected by the electroencephalogram, could negatively affect memory processes. Slow waves (≤4 Hz) can be found in seizures with impairment of consciousness and also occur in focal seizures without impairment of consciousness but with inhibited access to memory functions. Peri-ictal slow waves are regarded as dysfunctional and are probably caused by mechanisms, which are essential to disturb the consolidation of memory entries in these patients. This is in strong contrast to physiological slow-wave activity during deep sleep, which is thought to group memory-consolidating fast oscillatory activity. In patients with epilepsy, slow waves may not only correlate with the peri-ictal clouding of consciousness, but could be the epiphenomenon of mechanisms, which interfere with normal brain function in a wider range. These mechanisms may have transient impacts on memory, such as temporary inhibition of memory systems, altered patterns of hippocampal–neocortical interactions during slow-wave sleep, or disturbed cross-frequency coupling of slow and fast oscillations. In addition, repeated tonic–clonic seizures over the years in uncontrolled chronic epilepsy may cause a progressive cognitive decline. This hypothesis can only be assessed in long-term prospective studies. These studies could disentangle the reversible short-term impacts of seizures, and the impacts of chronic uncontrolled seizures. Chronic uncontrolled seizures lead to irreversible memory impairment. By contrast, short-term impacts do not necessarily lead to a progressive cognitive decline but result in significantly impaired peri-ictal memory performance. PMID:26124717

Intracranial EEG potentials estimated from MEG sources: A new approach to correlate MEG and iEEG data in epilepsy.

PubMed

Grova, Christophe; Aiguabella, Maria; Zelmann, Rina; Lina, Jean-Marc; Hall, Jeffery A; Kobayashi, Eliane

2016-05-01

Detection of epileptic spikes in MagnetoEncephaloGraphy (MEG) requires synchronized neuronal activity over a minimum of 4cm2. We previously validated the Maximum Entropy on the Mean (MEM) as a source localization able to recover the spatial extent of the epileptic spike generators. The purpose of this study was to evaluate quantitatively, using intracranial EEG (iEEG), the spatial extent recovered from MEG sources by estimating iEEG potentials generated by these MEG sources. We evaluated five patients with focal epilepsy who had a pre-operative MEG acquisition and iEEG with MRI-compatible electrodes. Individual MEG epileptic spikes were localized along the cortical surface segmented from a pre-operative MRI, which was co-registered with the MRI obtained with iEEG electrodes in place for identification of iEEG contacts. An iEEG forward model estimated the influence of every dipolar source of the cortical surface on each iEEG contact. This iEEG forward model was applied to MEG sources to estimate iEEG potentials that would have been generated by these sources. MEG-estimated iEEG potentials were compared with measured iEEG potentials using four source localization methods: two variants of MEM and two standard methods equivalent to minimum norm and LORETA estimates. Our results demonstrated an excellent MEG/iEEG correspondence in the presumed focus for four out of five patients. In one patient, the deep generator identified in iEEG could not be localized in MEG. MEG-estimated iEEG potentials is a promising method to evaluate which MEG sources could be retrieved and validated with iEEG data, providing accurate results especially when applied to MEM localizations. Hum Brain Mapp 37:1661-1683, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Ictal alterations of consciousness during ecstatic seizures.

PubMed

Picard, Fabienne; Kurth, Florian

2014-01-01

Patients with ecstatic epileptic seizures report an altered consciousness, which they describe as a sense of heightened perception of themselves – they “feel very present” – and an increased vividness of sensory perceptions. Recently, the anterior insula has been proposed as the region where these seizures originate, based on the results of ictal nuclear imaging in three patients, the first induction of ecstatic auras by electrical stimulation, and the functional characteristics of the anterior insula in neuroimaging literature. Specifically, the anterior insula is thought to play a key role in integrating information from within the body, the external world, as well as the emotional states. In addition, the anterior insula is thought to convert this integrated information into successive global emotional moments, thus enabling both the construct of a sentient self as well as a mechanism for predictive coding. As part of the salience network, this region is also involved in switching from mind wandering toward attentional and executive processing. In this review, we will summarize previous patient reports and recap how insular functioning may be involved in the phenomenon of ecstatic seizures. Furthermore, we will relate these hypotheses to the results from research on meditation and effects of drug abuse.

Separation and reconstruction of BCG and EEG signals during continuous EEG and fMRI recordings

PubMed Central

Xia, Hongjing; Ruan, Dan; Cohen, Mark S.

2014-01-01

Despite considerable effort to remove it, the ballistocardiogram (BCG) remains a major artifact in electroencephalographic data (EEG) acquired inside magnetic resonance imaging (MRI) scanners, particularly in continuous (as opposed to event-related) recordings. In this study, we have developed a new Direct Recording Prior Encoding (DRPE) method to extract and separate the BCG and EEG components from contaminated signals, and have demonstrated its performance by comparing it quantitatively to the popular Optimal Basis Set (OBS) method. Our modified recording configuration allows us to obtain representative bases of the BCG- and EEG-only signals. Further, we have developed an optimization-based reconstruction approach to maximally incorporate prior knowledge of the BCG/EEG subspaces, and of the signal characteristics within them. Both OBS and DRPE methods were tested with experimental data, and compared quantitatively using cross-validation. In the challenging continuous EEG studies, DRPE outperforms the OBS method by nearly sevenfold in separating the continuous BCG and EEG signals. PMID:25002836

Analyze the dynamic features of rat EEG using wavelet entropy.

PubMed

Feng, Zhouyan; Chen, Hang

2005-01-01

Wavelet entropy (WE), a new method of complexity measure for non-stationary signals, was used to investigate the dynamic features of rat EEGs under three vigilance states. The EEGs of the freely moving rats were recorded with implanted electrodes and were decomposed into four components of delta, theta, alpha and beta by using multi-resolution wavelet transform. Then, the wavelet entropy curves were calculated as a function of time. The results showed that there were significant differences among the average WEs of EEGs recorded under the vigilance states of waking, slow wave sleep (SWS) and rapid eye movement (REM) sleep. The changes of WE had different relationships with the four power components under different states. Moreover, there was evident rhythm in EEG WEs of SWS sleep for most experimental rats, which indicated a reciprocal relationship between slow waves and sleep spindles in the micro-states of SWS sleep. Therefore, WE can be used not only to distinguish the long-term changes in EEG complexity, but also to reveal the short-term changes in EEG micro-state.

Hypoglycemia-Associated EEG Changes in Prepubertal Children With Type 1 Diabetes.

PubMed

Hansen, Grith Lærkholm; Foli-Andersen, Pia; Fredheim, Siri; Juhl, Claus; Remvig, Line Sofie; Rose, Martin H; Rosenzweig, Ivana; Beniczky, Sándor; Olsen, Birthe; Pilgaard, Kasper; Johannesen, Jesper

2016-11-01

The purpose of this study was to explore the possible difference in the electroencephalogram (EEG) pattern between euglycemia and hypoglycemia in children with type 1 diabetes (T1D) during daytime and during sleep. The aim is to develop a hypoglycemia alarm based on continuous EEG measurement and real-time signal processing. Eight T1D patients aged 6-12 years were included. A hyperinsulinemic hypoglycemic clamp was performed to induce hypoglycemia both during daytime and during sleep. Continuous EEG monitoring was performed. For each patient, quantitative EEG (qEEG) measures were calculated. A within-patient analysis was conducted comparing hypoglycemia versus euglycemia changes in the qEEG. The nonparametric Wilcoxon signed rank test was performed. A real-time analyzing algorithm developed for adults was applied. The qEEG showed significant differences in specific bands comparing hypoglycemia to euglycemia both during daytime and during sleep. In daytime the EEG-based algorithm identified hypoglycemia in all children on average at a blood glucose (BG) level of 2.5 ± 0.5 mmol/l and 18.4 (ranging from 0 to 55) minutes prior to blood glucose nadir. During sleep the nighttime algorithm did not perform. We found significant differences in the qEEG in euglycemia and hypoglycemia both during daytime and during sleep. The algorithm developed for adults detected hypoglycemia in all children during daytime. The algorithm had too many false alarms during the night because it was more sensitive to deep sleep EEG patterns than hypoglycemia-related EEG changes. An algorithm for nighttime EEG is needed for accurate detection of nocturnal hypoglycemic episodes in children. This study indicates that a hypoglycemia alarm may be developed using real-time continuous EEG monitoring. © 2016 Diabetes Technology Society.

Assessing the depth of hypnosis of xenon anaesthesia with the EEG.

PubMed

Stuttmann, Ralph; Schultz, Arthur; Kneif, Thomas; Krauss, Terence; Schultz, Barbara

2010-04-01

Xenon was approved as an inhaled anaesthetic in Germany in 2005 and in other countries of the European Union in 2007. Owing to its low blood/gas partition coefficient, xenons effects on the central nervous system show a fast onset and offset and, even after long xenon anaesthetics, the wake-up times are very short. The aim of this study was to examine which electroencephalogram (EEG) stages are reached during xenon application and whether these stages can be identified by an automatic EEG classification. Therefore, EEG recordings were performed during xenon anaesthetics (EEG monitor: Narcotrend®). A total of 300 EEG epochs were assessed visually with regard to the EEG stages. These epochs were also classified automatically by the EEG monitor Narcotrend® using multivariate algorithms. There was a high correlation between visual and automatic classification (Spearman's rank correlation coefficient r=0.957, prediction probability Pk=0.949). Furthermore, it was observed that very deep stages of hypnosis were reached which are characterised by EEG activity in the low frequency range (delta waves). The burst suppression pattern was not seen. In deep hypnosis, in contrast to the xenon EEG, the propofol EEG was characterised by a marked superimposed higher frequency activity. To ensure an optimised dosage for the single patient, anaesthetic machines for xenon should be combined with EEG monitoring. To date, only a few anaesthetic machines for xenon are available. Because of the high price of xenon, new and further developments of machines focus on optimizing xenon consumption.

A Comparative Study of Different EEG Reference Choices for Diagnosing Unipolar Depression.

PubMed

Mumtaz, Wajid; Malik, Aamir Saeed

2018-06-02

The choice of an electroencephalogram (EEG) reference has fundamental importance and could be critical during clinical decision-making because an impure EEG reference could falsify the clinical measurements and subsequent inferences. In this research, the suitability of three EEG references was compared while classifying depressed and healthy brains using a machine-learning (ML)-based validation method. In this research, the EEG data of 30 unipolar depressed subjects and 30 age-matched healthy controls were recorded. The EEG data were analyzed in three different EEG references, the link-ear reference (LE), average reference (AR), and reference electrode standardization technique (REST). The EEG-based functional connectivity (FC) was computed. Also, the graph-based measures, such as the distances between nodes, minimum spanning tree, and maximum flow between the nodes for each channel pair, were calculated. An ML scheme provided a mechanism to compare the performances of the extracted features that involved a general framework such as the feature extraction (graph-based theoretic measures), feature selection, classification, and validation. For comparison purposes, the performance metrics such as the classification accuracies, sensitivities, specificities, and F scores were computed. When comparing the three references, the diagnostic accuracy showed better performances during the REST, while the LE and AR showed less discrimination between the two groups. Based on the results, it can be concluded that the choice of appropriate reference is critical during the clinical scenario. The REST reference is recommended for future applications of EEG-based diagnosis of mental illnesses.

Amplitude-integrated EEG and the newborn infant.

PubMed

Shah, Divyen K; Mathur, Amit

2014-01-01

There is emerging recognition of the need for continuous long term electrographic monitoring of the encephalopathic neonate. While full-montage EEG with video remains the gold standard for monitoring, it is limited in application due to the complexity of lead application and specialized interpretation of results. Amplitude integrated EEG (aEEG) is derived from limited channels (usually C3-P3, C4-P4) and is filtered, rectified and time-compressed to serve as a bedside electrographic trend monitor. Its simple application and interpretation has resulted in increasing use in neonatal units across the world. Validation studies with full montage EEG have shown reliable results in interpretation of EEG background and electrographic seizures, especially when used with the simultaneously displayed raw EEG trace. Several aEEG monitors are commercially available and seizure algorithms are being developed for use on these monitors. These aEEG monitors, complement conventional EEG and offer a significant advance in the feasibility of long term electrographic monitoring of the encephalopathic neonate.

Temporal lobe epilepsy is a predisposing factor for sleep apnea: A questionnaire study in video-EEG monitoring unit.

PubMed

Yildiz, F Gokcem; Tezer, F Irsel; Saygi, Serap

2015-07-01

The interaction between epilepsy and sleep is known. It has been shown that patients with epilepsy have more sleep problems than the general population. However, there is no recent study that compares the frequency of sleep disorders in groups with medically refractory temporal lobe epilepsy (TLE) and extratemporal lobe epilepsy (ETLE). The main purpose of this study was to investigate the occurrence of sleep disorders in two subtypes of epilepsy by using sleep questionnaire forms. One hundred and eighty-nine patients, out of 215 who were monitored for refractory epilepsy and were followed by the video-EEG monitoring unit, were divided into a group with TLE and a group with ETLE. The medical outcome study-sleep scale (MOS-SS), Epworth sleepiness scale (ESS), and sleep apnea scale of the sleep disorders questionnaire (SD-SDQ) were completed after admission to the video-EEG monitoring unit. The total scores in the group with TLE and group with ETLE were compared. Of the patients, TLE was diagnosed in 101 (53.4%) (45 females), and ETLE was diagnosed in 88 (46.6%) (44 females). Comparison of MOS-SS and Epworth sleepiness scale scores in the two subgroups did not reveal significant differences. In the group with TLE, SD-SDQ scores were significantly higher compared to that in the group with ETLE. Patients with temporal lobe epilepsy have higher risk of obstructive sleep apnea (OSA) according to their reported symptoms. Detection of OSA in patients with epilepsy by using questionnaire forms may decrease the risk of ictal or postictal respiratory-related 'Sudden Unexpected Death in Epilepsy'. Copyright © 2015 Elsevier Inc. All rights reserved.

Hypnagogic imagery and EEG activity.

PubMed

Hayashi, M; Katoh, K; Hori, T

1999-04-01

The relationships between hypnagogic imagery and EEG activity were studied. 7 subjects (4 women and 3 men) reported the content of hypnagogic imagery every minute and the hypnagogic EEGs were classified into 5 stages according to Hori's modified criteria. The content of the hypnagogic imagery changed as a function of the hypnagogic EEG stages.

Performance-informed EEG analysis reveals mixed evidence for EEG signatures unique to the processing of time.

PubMed

Schlichting, Nadine; de Jong, Ritske; van Rijn, Hedderik

2018-06-20

Certain EEG components (e.g., the contingent negative variation, CNV, or beta oscillations) have been linked to the perception of temporal magnitudes specifically. However, it is as of yet unclear whether these EEG components are really unique to time perception or reflect the perception of magnitudes in general. In the current study we recorded EEG while participants had to make judgments about duration (time condition) or numerosity (number condition) in a comparison task. This design allowed us to directly compare EEG signals between the processing of time and number. Stimuli consisted of a series of blue dots appearing and disappearing dynamically on a black screen. Each stimulus was characterized by its duration and the total number of dots that it consisted of. Because it is known that tasks like these elicit perceptual interference effects that we used a maximum-likelihood estimation (MLE) procedure to determine, for each participant and dimension separately, to what extent time and numerosity information were taken into account when making a judgement in an extensive post hoc analysis. This approach enabled us to capture individual differences in behavioral performance and, based on the MLE estimates, to select a subset of participants who suppressed task-irrelevant information. Even for this subset of participants, who showed no or only small interference effects and thus were thought to truly process temporal information in the time condition and numerosity information in the number condition, we found CNV patterns in the time-domain EEG signals for both tasks that was more pronounced in the time-task. We found no substantial evidence for differences between the processing of temporal and numerical information in the time-frequency domain.

Dynamic Neurovascular Coupling and Uncoupling during Ictal Onset, Propagation, and Termination Revealed by Simultaneous In Vivo Optical Imaging of Neural Activity and Local Blood Volume

PubMed Central

Zhao, Mingrui; Schwartz, Theodore H.

2013-01-01

Traditional models of ictal propagation involve the concept of an initiation site and a progressive outward march of activation. The process of neurovascular coupling, whereby the brain supplies oxygenated blood to metabolically active neurons presumably results in a similar outward cascade of hyperemia. However, ictal neurovascular coupling has never been assessed in vivo using simultaneous measurements of membrane potential change and hyperemia with wide spatial sampling. In an acute rat ictal model, using simultaneous intrinsic optical signal (IOS) and voltage-sensitive dye (VSD) imaging of cerebral blood volume and membrane potential changes, we demonstrate that seizures consist of multiple dynamic multidirectional waves of membrane potential change with variable onset sites that spread through a widespread network. Local blood volume evolves on a much slower spatiotemporal scale. At seizure onset, the VSD waves extend beyond the IOS signal. During evolution, spatial correlation with hemodynamic signal only exists briefly at the maximal spread of the VSD signal. At termination, the IOS signal extends spatially and temporally beyond the VSD waves. Hence, vascular reactivity evolves in a separate but parallel fashion to membrane potential changes resulting in a mechanism of neurovascular coupling and uncoupling, which is as dynamic as the seizure itself. PMID:22499798

Sort entropy-based for the analysis of EEG during anesthesia

NASA Astrophysics Data System (ADS)

Ma, Liang; Huang, Wei-Zhi

2010-08-01

The monitoring of anesthetic depth is an absolutely necessary procedure in the process of surgical operation. To judge and control the depth of anesthesia has become a clinical issue which should be resolved urgently. EEG collected wiil be processed by sort entrop in this paper. Signal response of the surface of the cerebral cortex is determined for different stages of patients in the course of anesthesia. EEG is simulated and analyzed through the fast algorithm of sort entropy. The results show that discipline of phasic changes for EEG is very detected accurately,and it has better noise immunity in detecting the EEG anaesthetized than approximate entropy. In conclusion,the computing of Sort entropy algorithm requires shorter time. It has high efficiency and strong anti-interference.

Use of EEG to Diagnose ADHD

PubMed Central

Lenartowicz, Agatha; Loo, Sandra K.

2015-01-01

Electroencephalography (EEG) has, historically, played a focal role in the assessment of neural function in children with attention deficit hyperactivity disorder (ADHD). We review here the most recent developments in the utility of EEG in the diagnosis of ADHD, with emphasis on the most commonly used and emerging EEG metrics and their reliability in diagnostic classification. Considering the clinical heterogeneity of ADHD and the complexity of information available from the EEG signals, we suggest that considerable benefits are to be gained from multivariate analyses and a focus towards understanding of the neural generators of EEG. We conclude that while EEG cannot currently be used as a diagnostic tool, vast developments in analytical and technological tools in its domain anticipate future progress in its utility in the clinical setting. PMID:25234074

A channel differential EZW coding scheme for EEG data compression.

PubMed

Dehkordi, Vahid R; Daou, Hoda; Labeau, Fabrice

2011-11-01

In this paper, a method is proposed to compress multichannel electroencephalographic (EEG) signals in a scalable fashion. Correlation between EEG channels is exploited through clustering using a k-means method. Representative channels for each of the clusters are encoded individually while other channels are encoded differentially, i.e., with respect to their respective cluster representatives. The compression is performed using the embedded zero-tree wavelet encoding adapted to 1-D signals. Simulations show that the scalable features of the scheme lead to a flexible quality/rate tradeoff, without requiring detailed EEG signal modeling.

Electroencephalogram (EEG) (For Parents)

MedlinePlus

... Most EEGs are done to diagnose and monitor seizure disorders. EEGs also can identify causes of other problems, ... are very safe. If your child has a seizure disorder, your doctor might want to stimulate and record ...

Online Reduction of Artifacts in EEG of Simultaneous EEG-fMRI Using Reference Layer Adaptive Filtering (RLAF).

PubMed

Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R

2018-01-01

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) allow us to study the active human brain from two perspectives concurrently. Signal processing based artifact reduction techniques are mandatory for this, however, to obtain reasonable EEG quality in simultaneous EEG-fMRI. Current artifact reduction techniques like average artifact subtraction (AAS), typically become less effective when artifact reduction has to be performed on-the-fly. We thus present and evaluate a new technique to improve EEG quality online. This technique adds up with online AAS and combines a prototype EEG-cap for reference recordings of artifacts, with online adaptive filtering and is named reference layer adaptive filtering (RLAF). We found online AAS + RLAF to be highly effective in improving EEG quality. Online AAS + RLAF outperformed online AAS and did so in particular online in terms of the chosen performance metrics, these being specifically alpha rhythm amplitude ratio between closed and opened eyes (3-45% improvement), signal-to-noise-ratio of visual evoked potentials (VEP) (25-63% improvement), and VEPs variability (16-44% improvement). Further, we found that EEG quality after online AAS + RLAF is occasionally even comparable with the offline variant of AAS at a 3T MRI scanner. In conclusion RLAF is a very effective add-on tool to enable high quality EEG in simultaneous EEG-fMRI experiments, even when online artifact reduction is necessary.

Corrected Four-Sphere Head Model for EEG Signals.

PubMed

Næss, Solveig; Chintaluri, Chaitanya; Ness, Torbjørn V; Dale, Anders M; Einevoll, Gaute T; Wójcik, Daniel K

2017-01-01

The EEG signal is generated by electrical brain cell activity, often described in terms of current dipoles. By applying EEG forward models we can compute the contribution from such dipoles to the electrical potential recorded by EEG electrodes. Forward models are key both for generating understanding and intuition about the neural origin of EEG signals as well as inverse modeling, i.e., the estimation of the underlying dipole sources from recorded EEG signals. Different models of varying complexity and biological detail are used in the field. One such analytical model is the four-sphere model which assumes a four-layered spherical head where the layers represent brain tissue, cerebrospinal fluid (CSF), skull, and scalp, respectively. While conceptually clear, the mathematical expression for the electric potentials in the four-sphere model is cumbersome, and we observed that the formulas presented in the literature contain errors. Here, we derive and present the correct analytical formulas with a detailed derivation. A useful application of the analytical four-sphere model is that it can serve as ground truth to test the accuracy of numerical schemes such as the Finite Element Method (FEM). We performed FEM simulations of the four-sphere head model and showed that they were consistent with the corrected analytical formulas. For future reference we provide scripts for computing EEG potentials with the four-sphere model, both by means of the correct analytical formulas and numerical FEM simulations.

Corrected Four-Sphere Head Model for EEG Signals

PubMed Central

Næss, Solveig; Chintaluri, Chaitanya; Ness, Torbjørn V.; Dale, Anders M.; Einevoll, Gaute T.; Wójcik, Daniel K.

2017-01-01

The EEG signal is generated by electrical brain cell activity, often described in terms of current dipoles. By applying EEG forward models we can compute the contribution from such dipoles to the electrical potential recorded by EEG electrodes. Forward models are key both for generating understanding and intuition about the neural origin of EEG signals as well as inverse modeling, i.e., the estimation of the underlying dipole sources from recorded EEG signals. Different models of varying complexity and biological detail are used in the field. One such analytical model is the four-sphere model which assumes a four-layered spherical head where the layers represent brain tissue, cerebrospinal fluid (CSF), skull, and scalp, respectively. While conceptually clear, the mathematical expression for the electric potentials in the four-sphere model is cumbersome, and we observed that the formulas presented in the literature contain errors. Here, we derive and present the correct analytical formulas with a detailed derivation. A useful application of the analytical four-sphere model is that it can serve as ground truth to test the accuracy of numerical schemes such as the Finite Element Method (FEM). We performed FEM simulations of the four-sphere head model and showed that they were consistent with the corrected analytical formulas. For future reference we provide scripts for computing EEG potentials with the four-sphere model, both by means of the correct analytical formulas and numerical FEM simulations. PMID:29093671

High-accuracy user identification using EEG biometrics.

PubMed

Koike-Akino, Toshiaki; Mahajan, Ruhi; Marks, Tim K; Ye Wang; Watanabe, Shinji; Tuzel, Oncel; Orlik, Philip

2016-08-01

We analyze brain waves acquired through a consumer-grade EEG device to investigate its capabilities for user identification and authentication. First, we show the statistical significance of the P300 component in event-related potential (ERP) data from 14-channel EEGs across 25 subjects. We then apply a variety of machine learning techniques, comparing the user identification performance of various different combinations of a dimensionality reduction technique followed by a classification algorithm. Experimental results show that an identification accuracy of 72% can be achieved using only a single 800 ms ERP epoch. In addition, we demonstrate that the user identification accuracy can be significantly improved to more than 96.7% by joint classification of multiple epochs.

Multireference adaptive noise canceling applied to the EEG.

PubMed

James, C J; Hagan, M T; Jones, R D; Bones, P J; Carroll, G J

1997-08-01

The technique of multireference adaptive noise canceling (MRANC) is applied to enhance transient nonstationarities in the electroeancephalogram (EEG), with the adaptation implemented by means of a multilayer-perception artificial neural network (ANN). The method was applied to recorded EEG segments and the performance on documented nonstationarities recorded. The results show that the neural network (nonlinear) gives an improvement in performance (i.e., signal-to-noise ratio (SNR) of the nonstationarities) compared to a linear implementation of MRANC. In both cases an improvement in the SNR was obtained. The advantage of the spatial filtering aspect of MRANC is highlighted when the performance of MRANC is compared to that of the inverse auto-regressive filtering of the EEG, a purely temporal filter.

Retained energy-based coding for EEG signals.

PubMed

Bazán-Prieto, Carlos; Blanco-Velasco, Manuel; Cárdenas-Barrera, Julián; Cruz-Roldán, Fernando

2012-09-01

The recent use of long-term records in electroencephalography is becoming more frequent due to its diagnostic potential and the growth of novel signal processing methods that deal with these types of recordings. In these cases, the considerable volume of data to be managed makes compression necessary to reduce the bit rate for transmission and storage applications. In this paper, a new compression algorithm specifically designed to encode electroencephalographic (EEG) signals is proposed. Cosine modulated filter banks are used to decompose the EEG signal into a set of subbands well adapted to the frequency bands characteristic of the EEG. Given that no regular pattern may be easily extracted from the signal in time domain, a thresholding-based method is applied for quantizing samples. The method of retained energy is designed for efficiently computing the threshold in the decomposition domain which, at the same time, allows the quality of the reconstructed EEG to be controlled. The experiments are conducted over a large set of signals taken from two public databases available at Physionet and the results show that the compression scheme yields better compression than other reported methods. Copyright © 2011 IPEM. Published by Elsevier Ltd. All rights reserved.

Distinctive time-lagged resting-state networks revealed by simultaneous EEG-fMRI.

PubMed

Feige, Bernd; Spiegelhalder, Kai; Kiemen, Andrea; Bosch, Oliver G; Tebartz van Elst, Ludger; Hennig, Jürgen; Seifritz, Erich; Riemann, Dieter

2017-01-15

Functional activation as evidenced by blood oxygen level-dependent (BOLD) functional MRI changes or event-related EEG is known to closely follow patterns of stimulation or self-paced action. Any lags are compatible with axonal conduction velocities and neural integration times. The important analysis of resting state networks is generally based on the assumption that these principles also hold for spontaneous fluctuations in brain activity. Previous observations using simultaneous EEG and fMRI indicate that slower processes, with delays in the seconds range, determine at least part of the relationship between spontaneous EEG and fMRI. To assess this relationship systematically, we used deconvolution analysis of EEG-fMRI during the resting state, assessing the relationship between EEG frequency bands and fMRI BOLD across the whole brain while allowing for time lags of up to 10.5s. Cluster analysis, identifying similar BOLD time courses in relation to EEG band power peaks, showed a clear segregation of functional subsystems of the brain. Our analysis shows that fMRI BOLD increases commonly precede EEG power increases by seconds. Most zero-lag correlations, on the other hand, were negative. This indicates two main distinct neuromodulatory mechanisms: an "idling" mechanism of simultaneous electric and metabolic network anticorrelation and a "regulatory" mechanism in which metabolic network activity precedes increased EEG power by some seconds. This has to be taken into consideration in further studies which address the causal and functional relationship of metabolic and electric brain activity patterns. Copyright © 2016 Elsevier Inc. All rights reserved.

Differences in Seizure Expression Between Magnetic Seizure Therapy and Electroconvulsive Shock.

PubMed

Cycowicz, Yael M; Rowny, Stefan B; Luber, Bruce; Lisanby, Sarah H

2018-06-01

Evidence suggests that magnetic seizure therapy (MST) results in fewer side effects than electroconvulsive treatment, both in humans treated with electroconvulsive therapy (ECT) as well as in the animal preclinical model that uses electroconvulsive shock (ECS). Evidence suggests that MST results in fewer cognitive side effects than ECT. Although MST offers enhanced control over seizure induction and spread, little is known about how MST and ECT seizures differ. Seizure characteristics are associated with treatment effect. This study presents quantitative analyses of electroencephalogram (EEG) power after electrical and magnetic seizure induction and anesthesia-alone sham in an animal model. The aim was to test whether differential neurophysiological characteristics of the seizures could be identified that support earlier observations that the powers of theta, alpha, and beta but not delta frequency bands were lower after MST when compared with those after ECS. In a randomized, sham-controlled trial, 24 macaca mulatte received 6 weeks of daily sessions while scalp EEG was recorded. Electroencephalogram power was quantified within delta, theta, alpha, and beta frequency bands. Magnetic seizure therapy induced lower ictal expression in the theta, alpha and beta frequencies than ECS, but MST and ECS were indistinguishable in the delta band. Magnetic seizure therapy showed less postictal suppression than ECS. Increasing electrical dosage increased ictal power, whereas increasing MST dosage had no effect on EEG expression. Magnetic seizure therapy seizures have less robust electrophysiological expression than ECS, and these differences are largest in the alpha and beta bands. The relevance of these differences in higher frequency bands to clinical outcomes deserves further exploration. Contrasting EEG in ECS and MST may lead to insights on the physiological underpinnings of seizure-induced amnesia and to finding ways to reduce cognitive side effects.

The Effect of Electroencephalogram (EEG) Reference Choice on Information-Theoretic Measures of the Complexity and Integration of EEG Signals

PubMed Central

Trujillo, Logan T.; Stanfield, Candice T.; Vela, Ruben D.

2017-01-01

Converging evidence suggests that human cognition and behavior emerge from functional brain networks interacting on local and global scales. We investigated two information-theoretic measures of functional brain segregation and integration—interaction complexity CI(X), and integration I(X)—as applied to electroencephalographic (EEG) signals and how these measures are affected by choice of EEG reference. CI(X) is a statistical measure of the system entropy accounted for by interactions among its elements, whereas I(X) indexes the overall deviation from statistical independence of the individual elements of a system. We recorded 72 channels of scalp EEG from human participants who sat in a wakeful resting state (interleaved counterbalanced eyes-open and eyes-closed blocks). CI(X) and I(X) of the EEG signals were computed using four different EEG references: linked-mastoids (LM) reference, average (AVG) reference, a Laplacian (LAP) “reference-free” transformation, and an infinity (INF) reference estimated via the Reference Electrode Standardization Technique (REST). Fourier-based power spectral density (PSD), a standard measure of resting state activity, was computed for comparison and as a check of data integrity and quality. We also performed dipole source modeling in order to assess the accuracy of neural source CI(X) and I(X) estimates obtained from scalp-level EEG signals. CI(X) was largest for the LAP transformation, smallest for the LM reference, and at intermediate values for the AVG and INF references. I(X) was smallest for the LAP transformation, largest for the LM reference, and at intermediate values for the AVG and INF references. Furthermore, across all references, CI(X) and I(X) reliably distinguished between resting-state conditions (larger values for eyes-open vs. eyes-closed). These findings occurred in the context of the overall expected pattern of resting state PSD. Dipole modeling showed that simulated scalp EEG-level CI(X) and I

Serial EEG findings in anti-NMDA receptor encephalitis: correlation between clinical course and EEG.

PubMed

Ueda, Jun; Kawamoto, Michi; Hikiami, Ryota; Ishii, Junko; Yoshimura, Hajime; Matsumoto, Riki; Kohara, Nobuo

2017-12-01

Anti-NMDA receptor encephalitis is a paraneoplastic encephalitis characterised by psychiatric features, involuntary movement, and autonomic instability. Various EEG findings in patients with anti-NMDA receptor encephalitis have been reported, however, the correlation between the EEG findings and clinical course of anti-NMDA receptor encephalitis remains unclear. We describe a patient with anti-NMDA receptor encephalitis with a focus on EEG findings, which included: status epilepticus, generalised rhythmic delta activity, excess beta activity, extreme delta brush, and paroxysmal alpha activity upon arousal from sleep, which we term"arousal alpha pattern". Initially, status epilepticus was observed on the EEG when the patient was comatose with conjugate deviation. The EEG then indicated excess beta activity, followed by the emergence of continuous slow activity, including generalised rhythmic delta activity and extreme delta brush, in the most severe phase. Slow activity gradually faded in parallel with clinical amelioration. Excess beta activity persisted, even after the patient became almost independent in daily activities, and finally disappeared with full recovery. In summary, our patient with anti-NMDA receptor encephalitis demonstrated slow activity on the EEG, including extreme delta brush during the most severe phase, which gradually faded in parallel with clinical amelioration, with excess beta activity persisting into the recovery phase.

EEG synchronization and migraine

NASA Astrophysics Data System (ADS)

Stramaglia, Sebastiano; Angelini, Leonardo; Pellicoro, Mario; Hu, Kun; Ivanov, Plamen Ch.

2004-03-01

We investigate phase synchronization in EEG recordings from migraine patients. We use the analytic signal technique, based on the Hilbert transform, and find that migraine brains are characterized by enhanced alpha band phase synchronization in presence of visual stimuli. Our findings show that migraine patients have an overactive regulatory mechanism that renders them more sensitive to external stimuli.

Working memory training using EEG neurofeedback in normal young adults.

PubMed

Xiong, Shi; Cheng, Chen; Wu, Xia; Guo, Xiaojuan; Yao, Li; Zhang, Jiacai

2014-01-01

Recent studies have shown that working memory (WM) performance can be improved by intensive and adaptive computerized training. Here, we explored the WM training effect using Electroencephalography (EEG) neurofeedback (NF) in normal young adults. In the first study, we identified the EEG features related to WM in normal young adults. The receiver operating characteristic (ROC) curve showed that the power ratio of the theta-to-alpha rhythms in the anterior-parietal region, accurately classified a high percentage of the EEG trials recorded during WM and fixation control (FC) tasks. Based on these results, a second study aimed to assess the training effects of the theta-to-alpha ratio and tested the hypothesis that up-regulating the power ratio can improve working memory behavior. Our results demonstrated that these normal young adults succeeded in improving their WM performance with EEG NF, and the pre- and post-test evaluations also indicated that WM performance increase in experimental group was significantly greater than control groups. In summary, our findings provided preliminarily evidence that WM performance can be improved through learned regulation of the EEG power ratio using EEG NF.

Going local: insights from EEG and stereo-EEG studies of the human sleep-wake cycle.

PubMed

Ferrara, Michele; De Gennaro, Luigi

2011-01-01

In the present paper, we reviewed a large body of evidence, mainly from quantitative EEG studies of our laboratory, supporting the notion that sleep is a local and use-dependent process. Quantitative analyses of sleep EEG recorded from multiple cortical derivations clearly indicate that every sleep phenomenon, from sleep onset to the awakening, is strictly local in nature. Sleep onset first occurs in frontal areas, and a frontal predominance of low-frequency power persists in the first part of the night, when the homeostatic processes mainly occur, and then it vanishes. Upon awakening, we showed an asynchronous EEG activation of different cortical areas, the more anterior ones being the first to wake up. During extended periods of wakefulness, the increase of sleepiness-related low-EEG frequencies is again evident over the frontal derivations. Similarly, experimental manipulations of sleep length by total sleep deprivation, partial sleep curtailment or even selective slow-wave sleep deprivation lead to a slow-wave activity rebound localized especially on the anterior derivations. Thus, frontal areas are crucially involved in sleep homeostasis. According to the local use-dependent theory, this would derive from a higher sleep need of the frontal cortex, which in turn is due to its higher levels of activity during wakefulness. The fact that different brain regions can simultaneously exhibit different sleep intensities indicates that sleep is not a spatially global and uniform state, as hypothesized in the theory. We have also reviewed recent evidence of localized effects of learning and plasticity on EEG sleep measures. These studies provide crucial support to a key concept in the theory, the one claiming that local sleep characteristics should be use-dependent. Finally, we have reported data corroborating the notion that sleep is not necessarily present simultaneously in the entire brain. Our stereo-EEG recordings clearly indicate that sleep and wakefulness can co

Wireless recording systems: from noninvasive EEG-NIRS to invasive EEG devices.

PubMed

Sawan, Mohamad; Salam, Muhammad T; Le Lan, Jérôme; Kassab, Amal; Gelinas, Sébastien; Vannasing, Phetsamone; Lesage, Frédéric; Lassonde, Maryse; Nguyen, Dang K

2013-04-01

In this paper, we present the design and implementation of a wireless wearable electronic system dedicated to remote data recording for brain monitoring. The reported wireless recording system is used for a) simultaneous near-infrared spectrometry (NIRS) and scalp electro-encephalography (EEG) for noninvasive monitoring and b) intracerebral EEG (icEEG) for invasive monitoring. Bluetooth and dual radio links were introduced for these recordings. The Bluetooth-based device was embedded in a noninvasive multichannel EEG-NIRS system for easy portability and long-term monitoring. On the other hand, the 32-channel implantable recording device offers 24-bit resolution, tunable features, and a sampling frequency up to 2 kHz per channel. The analog front-end preamplifier presents low input-referred noise of 5 μ VRMS and a signal-to-noise ratio of 112 dB. The communication link is implemented using a dual-band radio frequency transceiver offering a half-duplex 800 kb/s data rate, 16.5 mW power consumption and less than 10(-10) post-correction Bit-Error Rate (BER). The designed system can be accessed and controlled by a computer with a user-friendly graphical interface. The proposed wireless implantable recording device was tested in vitro using real icEEG signals from two patients with refractory epilepsy. The wirelessly recorded signals were compared to the original signals recorded using wired-connection, and measured normalized root-mean square deviation was under 2%.

The Utility of EEG in Attention Deficit Hyperactivity Disorder: A Replication Study.

PubMed

Swatzyna, Ronald J; Tarnow, Jay D; Roark, Alexandra; Mardick, Jacob

2017-07-01

The routine use of stimulants in pediatrics has increased dramatically over the past 3 decades and the long-term consequences have yet to be fully studied. Since 1978 there have been 7 articles identifying electroencephalogram (EEG) abnormalities, particularly epileptiform discharges in children with attention deficit hyperactivity disorder (ADHD). Many have studied the prevalence of these discharges in this population with varying results. An article published in 2011 suggests that EEG technology should be considered prior to prescribing stimulants to children diagnosed with ADHD due to a high prevalence of epileptiform discharges. The 2011 study found a higher prevalence (26%) of epileptiform discharges when using 23-hour and sleep-deprived EEGs in comparison with other methods of activation (hyperventilation or photostimulation) and conventional EEG. We sought to replicate the 2011 results using conventional EEG with the added qEEG technologies of automatic spike detection and low-resolution electromagnetic tomography analysis (LORETA) brain mapping. Our results showed 32% prevalence of epileptiform discharges, which suggests that an EEG should be considered prior to prescribing stimulant medications.

Long-term EEG in patients with the ring chromosome 20 epilepsy syndrome.

PubMed

Freire de Moura, Maria; Flores-Guevara, Roberto; Gueguen, Bernard; Biraben, Arnaud; Renault, Francis

2016-05-01

The recognizable electroencephalography (EEG) pattern of ring chromosome 20 epilepsy syndrome can be missing in patients with r(20) chromosomal anomaly, and may be found in patients with frontal lobe epilepsy of other origin. This study aims to search for more specific EEG signs by using long-term recordings and measuring the duration of paroxysmal anomalies. The series included 12 adult patients with r(20) anomaly, and 12 controls without any chromosomal aberration. We measured the duration of every paroxysmal burst and calculated the sum of their durations for each long-term EEG recording. We compared patients to controls using the Mann-Whitney U-test. Every patient showed long-lasting paroxysmal EEG bursts, up to 60 min; controls did not show any bursts longer than 60 s (p < 0.0001). The total duration of paroxysmal anomalies was significantly longer in patients (31-692 min) compared to controls (0-48 min) (p < 0.0001). Thus, long-term recordings enhance the contribution of EEG methods for characterizing the ring 20 chromosome epilepsy syndrome. Wiley Periodicals, Inc. © 2016 International League Against Epilepsy.

A Realistic Seizure Prediction Study Based on Multiclass SVM.

PubMed

Direito, Bruno; Teixeira, César A; Sales, Francisco; Castelo-Branco, Miguel; Dourado, António

2017-05-01

A patient-specific algorithm, for epileptic seizure prediction, based on multiclass support-vector machines (SVM) and using multi-channel high-dimensional feature sets, is presented. The feature sets, combined with multiclass classification and post-processing schemes aim at the generation of alarms and reduced influence of false positives. This study considers 216 patients from the European Epilepsy Database, and includes 185 patients with scalp EEG recordings and 31 with intracranial data. The strategy was tested over a total of 16,729.80[Formula: see text]h of inter-ictal data, including 1206 seizures. We found an overall sensitivity of 38.47% and a false positive rate per hour of 0.20. The performance of the method achieved statistical significance in 24 patients (11% of the patients). Despite the encouraging results previously reported in specific datasets, the prospective demonstration on long-term EEG recording has been limited. Our study presents a prospective analysis of a large heterogeneous, multicentric dataset. The statistical framework based on conservative assumptions, reflects a realistic approach compared to constrained datasets, and/or in-sample evaluations. The improvement of these results, with the definition of an appropriate set of features able to improve the distinction between the pre-ictal and nonpre-ictal states, hence minimizing the effect of confounding variables, remains a key aspect.

Simultaneous recording of EEG and electromyographic polygraphy increases the diagnostic yield of video-EEG monitoring.

PubMed

Hill, Aron T; Briggs, Belinda A; Seneviratne, Udaya

2014-06-01

To investigate the usefulness of adjunctive electromyographic (EMG) polygraphy in the diagnosis of clinical events captured during long-term video-EEG monitoring. A total of 40 patients (21 women, 19 men) aged between 19 and 72 years (mean 43) investigated using video-EEG monitoring were studied. Electromyographic activity was simultaneously recorded with EEG in four patients selected on clinical grounds. In these patients, surface EMG electrodes were placed over muscles suspected to be activated during a typical clinical event. Of the 40 patients investigated, 24 (60%) were given a diagnosis, whereas 16 (40%) remained undiagnosed. All four patients receiving adjunctive EMG polygraphy obtained a diagnosis, with three of these diagnoses being exclusively reliant on the EMG recordings. Specifically, one patient was diagnosed with propriospinal myoclonus, another patient was diagnosed with facio-mandibular myoclonus, and a third patient was found to have bruxism and periodic leg movements of sleep. The information obtained from surface EMG recordings aided the diagnosis of clinical events captured during video-EEG monitoring in 7.5% of the total cohort. This study suggests that EEG-EMG polygraphy may be used as a technique of improving the diagnostic yield of video-EEG monitoring in selected cases.

Embedding Dimension Selection for Adaptive Singular Spectrum Analysis of EEG Signal.

PubMed

Xu, Shanzhi; Hu, Hai; Ji, Linhong; Wang, Peng

2018-02-26

The recorded electroencephalography (EEG) signal is often contaminated with different kinds of artifacts and noise. Singular spectrum analysis (SSA) is a powerful tool for extracting the brain rhythm from a noisy EEG signal. By analyzing the frequency characteristics of the reconstructed component (RC) and the change rate in the trace of the Toeplitz matrix, it is demonstrated that the embedding dimension is related to the frequency bandwidth of each reconstructed component, in consistence with the component mixing in the singular value decomposition step. A method for selecting the embedding dimension is thereby proposed and verified by simulated EEG signal based on the Markov Process Amplitude (MPA) EEG Model. Real EEG signal is also collected from the experimental subjects under both eyes-open and eyes-closed conditions. The experimental results show that based on the embedding dimension selection method, the alpha rhythm can be extracted from the real EEG signal by the adaptive SSA, which can be effectively utilized to distinguish between the eyes-open and eyes-closed states.

Multi-scale symbolic transfer entropy analysis of EEG

NASA Astrophysics Data System (ADS)

Yao, Wenpo; Wang, Jun

2017-10-01

From both global and local perspectives, we symbolize two kinds of EEG and analyze their dynamic and asymmetrical information using multi-scale transfer entropy. Multi-scale process with scale factor from 1 to 199 and step size of 2 is applied to EEG of healthy people and epileptic patients, and then the permutation with embedding dimension of 3 and global approach are used to symbolize the sequences. The forward and reverse symbol sequences are taken as the inputs of transfer entropy. Scale factor intervals of permutation and global way are (37, 57) and (65, 85) where the two kinds of EEG have satisfied entropy distinctions. When scale factor is 67, transfer entropy of the healthy and epileptic subjects of permutation, 0.1137 and 0.1028, have biggest difference. And the corresponding values of the global symbolization is 0.0641 and 0.0601 which lies in the scale factor of 165. Research results show that permutation which takes contribution of local information has better distinction and is more effectively applied to our multi-scale transfer entropy analysis of EEG.

The effects of increased fluid viscosity on stationary characteristics of EEG signal in healthy adults

PubMed Central

Jestrović, I.; Coyle, J. L.

2014-01-01

Electroencephalography (EEG) systems can enable us to study cerebral activation patterns during performance of swallowing tasks and possibly infer about the nature of abnormal neurological conditions causing swallowing difficulties. While it is well known that EEG signals are non-stationary, there are still open questions regarding the stationarity of EEG during swallowing activities and how the EEG stationarity is affected by different viscosities of the fluids that are swallowed by subjects during these swallowing activities. In the present study, we investigated the EEG signal collected during swallowing tasks by collecting data from 55 healthy adults (ages 18–65). Each task involved the deliberate swallowing of boluses of fluids of different viscosities. Using time-frequency tests with surrogates, we showed that the EEG during swallowing tasks could be considered non-stationary. Furthermore, the statistical tests and linear regression showed that the parameters of fluid viscosity, sex, and different brain regions significantly influenced the index of non-stationarity values. Therefore, these parameters should be considered in future investigations which use EEG during swallowing activities. PMID:25245522

Kohlbergian Cosmic Perspective Responses, EEG Coherence and the TM and TM-Sidhi Programme.

ERIC Educational Resources Information Center

Nidich, Sanford I.; And Others

1983-01-01

This study compared the brain wave activity (EEG) of people who responded to the question "Why be moral?" with answers indicating a belief in the wholeness of man and nature with respondents who did not show a cosmic orientation. Results showed differences in EEG scores between groups. (Author/IS)

Understanding the pathophysiology of reflex epilepsy using simultaneous EEG-fMRI.

PubMed

Sandhya, Manglore; Bharath, Rose Dawn; Panda, Rajanikant; Chandra, S R; Kumar, Naveen; George, Lija; Thamodharan, A; Gupta, Arun Kumar; Satishchandra, P

2014-03-01

Measuring neuro-haemodynamic correlates in the brain of epilepsy patients using EEG-fMRI has opened new avenues in clinical neuroscience, as these are two complementary methods for understanding brain function. In this study, we investigated three patients with drug-resistant reflex epilepsy using EEG-fMRI. Different types of reflex epilepsy such as eating, startle myoclonus, and hot water epilepsy were included in the study. The analysis of EEG-fMRI data was based on the visual identification of interictal epileptiform discharges on scalp EEG. The convolution of onset time and duration of these epilepsy spikes was estimated, and using these condition-specific effects in a general linear model approach, we evaluated activation of fMRI. Patients with startle myoclonus epilepsy experienced epilepsy in response to sudden sound or touch, in association with increased delta and theta activity with a spike-and-slow-wave pattern of interictal epileptiform discharges on EEG and fronto-parietal network activation pattern on SPECT and EEG-fMRI. Eating epilepsy was triggered by sight or smell of food and fronto-temporal discharges were noted on video-EEG (VEEG). Similarly, fronto-temporo-parietal involvement was noted on SPECT and EEG-fMRI. Hot water epilepsy was triggered by contact with hot water either in the bath or by hand immersion, and VEEG showed fronto-parietal involvement. SPECT and EEG fMRI revealed a similar fronto-parietal-occipital involvement. From these results, we conclude that continuous EEG recording can improve the modelling of BOLD changes related to interictal epileptic activity and this can thus be used to understand the neuro-haemodynamic substrates involved in reflex epilepsy.

Focal Electrically Administered Seizure Therapy (FEAST): A novel form of ECT illustrates the roles of current directionality, polarity, and electrode configuration in seizure induction

PubMed Central

Spellman, Timothy; Peterchev, Angel V.; Lisanby, Sarah H.

2009-01-01

Electroconvulsive therapy (ECT) is a mainstay in the treatment of severe, medication resistant depression. The antidepressant efficacy and cognitive side effects of ECT are influenced by the position of the electrodes on the head and by the degree to which the electrical stimulus exceeds the threshold for seizure induction. However, surprisingly little is known about the effects of other key electrical parameters such as current directionality, polarity, and electrode configuration. Understanding these relationships may inform the optimization of therapeutic interventions to improve their risk/benefit ratio. To elucidate these relationships, we evaluated a novel form of ECT (focal electrically administered seizure therapy, FEAST) that combines unidirectional stimulation, control of polarity, and an asymmetrical electrode configuration, and contrasted it with conventional ECT in a nonhuman primate model. Rhesus monkeys had their seizure thresholds determined on separate days with ECT conditions that crossed the factors of current directionality (unidirectional or bidirectional), electrode configuration (standard bilateral or FEAST (small anterior and large posterior electrode)), and polarity (assignment of anode and cathode in unidirectional stimulation). Ictal expression and post-ictal suppression were quantified via scalp EEG. Findings were replicated and extended in a second experiment with the same subjects. Seizures were induced in each of 75 trials, including 42 FEAST procedures. Seizure thresholds were lower with unidirectional than with bidirectional stimulation (p<0.0001), and lower in FEAST than in bilateral ECS (p=0.0294). Ictal power was greatest in posterior-anode unidirectional FEAST, and post-ictal suppression was strongest in anterior-anode FEAST (p=0.0008 and p=0.0024, respectively). EEG power was higher in the stimulated hemisphere in posterior-anode FEAST (p=0.0246), consistent with the anode being the site of strongest activation. These findings

Focal electrically administered seizure therapy: a novel form of ECT illustrates the roles of current directionality, polarity, and electrode configuration in seizure induction.

PubMed

Spellman, Timothy; Peterchev, Angel V; Lisanby, Sarah H

2009-07-01

Electroconvulsive therapy (ECT) is a mainstay in the treatment of severe, medication-resistant depression. The antidepressant efficacy and cognitive side effects of ECT are influenced by the position of the electrodes on the head and by the degree to which the electrical stimulus exceeds the threshold for seizure induction. However, surprisingly little is known about the effects of other key electrical parameters such as current directionality, polarity, and electrode configuration. Understanding these relationships may inform the optimization of therapeutic interventions to improve their risk/benefit ratio. To elucidate these relationships, we evaluated a novel form of ECT (focal electrically administered seizure therapy, FEAST) that combines unidirectional stimulation, control of polarity, and an asymmetrical electrode configuration, and contrasted it with conventional ECT in a nonhuman primate model. Rhesus monkeys had their seizure thresholds determined on separate days with ECT conditions that crossed the factors of current directionality (unidirectional or bidirectional), electrode configuration (standard bilateral or FEAST (small anterior and large posterior electrode)), and polarity (assignment of anode and cathode in unidirectional stimulation). Ictal expression and post-ictal suppression were quantified through scalp EEG. Findings were replicated and extended in a second experiment with the same subjects. Seizures were induced in each of the 75 trials, including 42 FEAST procedures. Seizure thresholds were lower with unidirectional than with bidirectional stimulation (p<0.0001), and lower in FEAST than in bilateral ECS (p=0.0294). Ictal power was greatest in posterior-anode unidirectional FEAST, and post-ictal suppression was strongest in anterior-anode FEAST (p=0.0008 and p=0.0024, respectively). EEG power was higher in the stimulated hemisphere in posterior-anode FEAST (p=0.0246), consistent with the anode being the site of strongest activation. These

MEG predicts outcome following surgery for intractable epilepsy in children with normal or nonfocal MRI findings.

PubMed

RamachandranNair, Rajesh; Otsubo, Hiroshi; Shroff, Manohar M; Ochi, Ayako; Weiss, Shelly K; Rutka, James T; Snead, O Carter

2007-01-01

To identify the predictors of postsurgical seizure freedom in children with refractory epilepsy and normal or nonfocal MRI findings. We analyzed 22 children with normal or subtle and nonfocal MRI findings, who underwent surgery for intractable epilepsy following extraoperative intracranial EEG. We compared clinical profiles, neurophysiological data (scalp EEG, magnetoencephalography (MEG) and intracranial EEG), completeness of surgical resection and pathology to postoperative seizure outcomes. Seventeen children (77%) had a good postsurgical outcome (defined as Engel class IIIA or better), which included eight (36%) seizure-free children. All children with postsurgical seizure freedom had an MEG cluster in the final resection area. Postsurgical seizure freedom was obtained in none of the children who had bilateral MEG dipole clusters (3) or only scattered dipoles (1). All five children in whom ictal onset zones were confined to < or = 5 adjacent intracranial electrodes achieved seizure freedom compared to three of 17 children with ictal onset zones that extended over >5 electrodes (p = 0.002). None of six children with more than one type of seizure became seizure-free, compared to eight of 16 children with a single seizure type (p = 0.04). Complete resection of the preoperatively localized epileptogenic zone resulted in seizure remission in 63% (5/8) and incomplete resections, in 21% (3/14) (p = 0.06). Age of onset, duration of epilepsy, number of lobes involved in resection, and pathology failed to correlate with seizure freedom. Surgery for intractable epilepsy in children with normal MRI findings provided good postsurgical outcomes in the majority of our patients. As well, restricted ictal onset zone predicted postoperative seizure freedom. Postoperative seizure freedom was less likely to occur in children with bilateral MEG dipole clusters or only scattered dipoles, multiple seizure types and incomplete resection of the proposed epileptogenic zone. Seizure

EEG microstates of wakefulness and NREM sleep.

PubMed

Brodbeck, Verena; Kuhn, Alena; von Wegner, Frederic; Morzelewski, Astrid; Tagliazucchi, Enzo; Borisov, Sergey; Michel, Christoph M; Laufs, Helmut

2012-09-01

EEG-microstates exploit spatio-temporal EEG features to characterize the spontaneous EEG as a sequence of a finite number of quasi-stable scalp potential field maps. So far, EEG-microstates have been studied mainly in wakeful rest and are thought to correspond to functionally relevant brain-states. Four typical microstate maps have been identified and labeled arbitrarily with the letters A, B, C and D. We addressed the question whether EEG-microstate features are altered in different stages of NREM sleep compared to wakefulness. 32-channel EEG of 32 subjects in relaxed wakefulness and NREM sleep was analyzed using a clustering algorithm, identifying the most dominant amplitude topography maps typical of each vigilance state. Fitting back these maps into the sleep-scored EEG resulted in a temporal sequence of maps for each sleep stage. All 32 subjects reached sleep stage N2, 19 also N3, for at least 1 min and 45 s. As in wakeful rest we found four microstate maps to be optimal in all NREM sleep stages. The wake maps were highly similar to those described in the literature for wakefulness. The sleep stage specific map topographies of N1 and N3 sleep showed a variable but overall relatively high degree of spatial correlation to the wake maps (Mean: N1 92%; N3 87%). The N2 maps were the least similar to wake (mean: 83%). Mean duration, total time covered, global explained variance and transition probabilities per subject, map and sleep stage were very similar in wake and N1. In wake, N1 and N3, microstate map C was most dominant w.r.t. global explained variance and temporal presence (ratio total time), whereas in N2 microstate map B was most prominent. In N3, the mean duration of all microstate maps increased significantly, expressed also as an increase in transition probabilities of all maps to themselves in N3. This duration increase was partly--but not entirely--explained by the occurrence of slow waves in the EEG. The persistence of exactly four main microstate

Real time workload classification from an ambulatory wireless EEG system using hybrid EEG electrodes.

PubMed

Matthews, R; Turner, P J; McDonald, N J; Ermolaev, K; Manus, T; Shelby, R A; Steindorf, M

2008-01-01

This paper describes a compact, lightweight and ultra-low power ambulatory wireless EEG system based upon QUASAR's innovative noninvasive bioelectric sensor technologies. The sensors operate through hair without skin preparation or conductive gels. Mechanical isolation built into the harness permits the recording of high quality EEG data during ambulation. Advanced algorithms developed for this system permit real time classification of workload during subject motion. Measurements made using the EEG system during ambulation are presented, including results for real time classification of subject workload.

Modification of EEG power spectra and EEG connectivity in autobiographical memory: a sLORETA study.

PubMed

Imperatori, Claudio; Brunetti, Riccardo; Farina, Benedetto; Speranza, Anna Maria; Losurdo, Anna; Testani, Elisa; Contardi, Anna; Della Marca, Giacomo

2014-08-01

The aim of the present study was to explore the modifications of scalp EEG power spectra and EEG connectivity during the autobiographical memory test (AM-T) and during the retrieval of an autobiographical event (the high school final examination, Task 2). Seventeen healthy volunteers were enrolled (9 women and 8 men, mean age 23.4 ± 2.8 years, range 19-30). EEG was recorded at baseline and while performing the autobiographical memory (AM) tasks, by means of 19 surface electrodes and a nasopharyngeal electrode. EEG analysis was conducted by means of the standardized LOw Resolution Electric Tomography (sLORETA) software. Power spectra and lagged EEG coherence were compared between EEG acquired during the memory tasks and baseline recording. The frequency bands considered were as follows: delta (0.5-4 Hz); theta (4.5-7.5 Hz); alpha (8-12.5 Hz); beta1 (13-17.5 Hz); beta2 (18-30 Hz); gamma (30.5-60 Hz). During AM-T, we observed a significant delta power increase in left frontal and midline cortices (T = 3.554; p < 0.05) and increased EEG connectivity in delta band in prefrontal, temporal, parietal, and occipital areas, and for gamma bands in the left temporo-parietal regions (T = 4.154; p < 0.05). In Task 2, we measured an increased power in the gamma band located in the left posterior midline areas (T = 3.960; p < 0.05) and a significant increase in delta band connectivity in the prefrontal, temporal, parietal, and occipital areas, and in the gamma band involving right temporo-parietal areas (T = 4.579; p < 0.05). These results indicate that AM retrieval engages in a complex network which is mediated by both low- (delta) and high-frequency (gamma) EEG bands.

Quantitative change of EEG and respiration signals during mindfulness meditation.

PubMed

Ahani, Asieh; Wahbeh, Helane; Nezamfar, Hooman; Miller, Meghan; Erdogmus, Deniz; Oken, Barry

2014-05-14

This study investigates measures of mindfulness meditation (MM) as a mental practice, in which a resting but alert state of mind is maintained. A population of older people with high stress level participated in this study, while electroencephalographic (EEG) and respiration signals were recorded during a MM intervention. The physiological signals during meditation and control conditions were analyzed with signal processing. EEG and respiration data were collected and analyzed on 34 novice meditators after a 6-week meditation intervention. Collected data were analyzed with spectral analysis, phase analysis and classification to evaluate an objective marker for meditation. Different frequency bands showed differences in meditation and control conditions. Furthermore, we established a classifier using EEG and respiration signals with a higher accuracy (85%) at discriminating between meditation and control conditions than a classifier using the EEG signal only (78%). Support vector machine (SVM) classifier with EEG and respiration feature vector is a viable objective marker for meditation ability. This classifier should be able to quantify different levels of meditation depth and meditation experience in future studies.

Automatic detection and classification of artifacts in single-channel EEG.

PubMed

Olund, Thomas; Duun-Henriksen, Jonas; Kjaer, Troels W; Sorensen, Helge B D

2014-01-01

Ambulatory EEG monitoring can provide medical doctors important diagnostic information, without hospitalizing the patient. These recordings are however more exposed to noise and artifacts compared to clinically recorded EEG. An automatic artifact detection and classification algorithm for single-channel EEG is proposed to help identifying these artifacts. Features are extracted from the EEG signal and wavelet subbands. Subsequently a selection algorithm is applied in order to identify the best discriminating features. A non-linear support vector machine is used to discriminate among different artifact classes using the selected features. Single-channel (Fp1-F7) EEG recordings are obtained from experiments with 12 healthy subjects performing artifact inducing movements. The dataset was used to construct and validate the model. Both subject-specific and generic implementation, are investigated. The detection algorithm yield an average sensitivity and specificity above 95% for both the subject-specific and generic models. The classification algorithm show a mean accuracy of 78 and 64% for the subject-specific and generic model, respectively. The classification model was additionally validated on a reference dataset with similar results.

EEG abnormalities and two year outcome in first episode psychosis.

PubMed

Manchanda, R; Norman, R; Malla, A; Harricharan, R; Takhar, J; Northcott, S

2005-03-01

This study examines the relationship of EEG to 2 year symptomatic outcome, duration of illness and untreated psychosis and gender. A total of 122 patients presenting for treatment of first episode psychosis had their baseline EEG classified by modified Mayo Clinic system criteria as normal, essentially normal or dysrhythmia. Positive and negative symptoms of psychoses were rated on entry and after 2 years of treatment. The socio-demographic variables and duration of illness and of untreated psychosis were also recorded. Patients with a normal EEG showed significantly more reduction in both positive and negative symptoms of psychoses over 2 years and were more likely to be in 'remission' as compared with the essentially normal or dysrhythmia group. The dysrhythmic group had significantly higher duration of illness than either the normal or essentially normal groups. There were no gender differences in the distribution of EEGs. An abnormal EEG in patients with first episode psychosis is associated with a poorer prognosis and a longer duration of untreated illness. Copyright (c) Blackwell Munksgaard 2005

Nonlinear dimensionality reduction of electroencephalogram (EEG) for Brain Computer interfaces.

PubMed

Teli, Mohammad Nayeem; Anderson, Charles

2009-01-01

Patterns in electroencephalogram (EEG) signals are analyzed for a Brain Computer Interface (BCI). An important aspect of this analysis is the work on transformations of high dimensional EEG data to low dimensional spaces in which we can classify the data according to mental tasks being performed. In this research we investigate how a Neural Network (NN) in an auto-encoder with bottleneck configuration can find such a transformation. We implemented two approximate second-order methods to optimize the weights of these networks, because the more common first-order methods are very slow to converge for networks like these with more than three layers of computational units. The resulting non-linear projections of time embedded EEG signals show interesting separations that are related to tasks. The bottleneck networks do indeed discover nonlinear transformations to low-dimensional spaces that capture much of the information present in EEG signals. However, the resulting low-dimensional representations do not improve classification rates beyond what is possible using Quadratic Discriminant Analysis (QDA) on the original time-lagged EEG.

Quantitative change of EEG and respiration signals during mindfulness meditation

PubMed Central

2014-01-01

Background This study investigates measures of mindfulness meditation (MM) as a mental practice, in which a resting but alert state of mind is maintained. A population of older people with high stress level participated in this study, while electroencephalographic (EEG) and respiration signals were recorded during a MM intervention. The physiological signals during meditation and control conditions were analyzed with signal processing. Methods EEG and respiration data were collected and analyzed on 34 novice meditators after a 6-week meditation intervention. Collected data were analyzed with spectral analysis, phase analysis and classification to evaluate an objective marker for meditation. Results Different frequency bands showed differences in meditation and control conditions. Furthermore, we established a classifier using EEG and respiration signals with a higher accuracy (85%) at discriminating between meditation and control conditions than a classifier using the EEG signal only (78%). Conclusion Support vector machine (SVM) classifier with EEG and respiration feature vector is a viable objective marker for meditation ability. This classifier should be able to quantify different levels of meditation depth and meditation experience in future studies. PMID:24939519

Conductive polymer foam surface improves the performance of a capacitive EEG electrode.

PubMed

Baek, Hyun Jae; Lee, Hong Ji; Lim, Yong Gyu; Park, Kwang Suk

2012-12-01

In this paper, a new conductive polymer foam-surfaced electrode was proposed for use as a capacitive EEG electrode for nonintrusive EEG measurements in out-of-hospital environments. The current capacitive electrode has a rigid surface that produces an undefined contact area due to its stiffness, which renders it unable to conform to head curvature and locally isolates hairs between the electrode surface and scalp skin, making EEG measurement through hair difficult. In order to overcome this issue, a conductive polymer foam was applied to the capacitive electrode surface to provide a cushioning effect. This enabled EEG measurement through hair without any conductive contact with bare scalp skin. Experimental results showed that the new electrode provided lower electrode-skin impedance and higher voltage gains, signal-to-noise ratios, signal-to-error ratios, and correlation coefficients between EEGs measured by capacitive and conventional resistive methods compared to a conventional capacitive electrode. In addition, the new electrode could measure EEG signals, while the conventional capacitive electrode could not. We expect that the new electrode presented here can be easily installed in a hat or helmet to create a nonintrusive wearable EEG apparatus that does not make users look strange for real-world EEG applications.

Predicting epileptic seizures from scalp EEG based on attractor state analysis.

PubMed

Chu, Hyunho; Chung, Chun Kee; Jeong, Woorim; Cho, Kwang-Hyun

2017-05-01

Epilepsy is the second most common disease of the brain. Epilepsy makes it difficult for patients to live a normal life because it is difficult to predict when seizures will occur. In this regard, if seizures could be predicted a reasonable period of time before their occurrence, epilepsy patients could take precautions against them and improve their safety and quality of life. In this paper, we investigate a novel seizure precursor based on attractor state analysis for seizure prediction. We analyze the transition process from normal to seizure attractor state and investigate a precursor phenomenon seen before reaching the seizure attractor state. From the result of an analysis, we define a quantified spectral measure in scalp EEG for seizure prediction. From scalp EEG recordings, the Fourier coefficients of six EEG frequency bands are extracted, and the defined spectral measure is computed based on the coefficients for each half-overlapped 20-second-long window. The computed spectral measure is applied to seizure prediction using a low-complexity methodology. Within scalp EEG, we identified an early-warning indicator before an epileptic seizure occurs. Getting closer to the bifurcation point that triggers the transition from normal to seizure state, the power spectral density of low frequency bands of the perturbation of an attractor in the EEG, showed a relative increase. A low-complexity seizure prediction algorithm using this feature was evaluated, using ∼583h of scalp EEG in which 143 seizures in 16 patients were recorded. With the test dataset, the proposed method showed high sensitivity (86.67%) with a false prediction rate of 0.367h -1 and average prediction time of 45.3min. A novel seizure prediction method using scalp EEG, based on attractor state analysis, shows potential for application with real epilepsy patients. This is the first study in which the seizure-precursor phenomenon of an epileptic seizure is investigated based on attractor

Beamforming applied to surface EEG improves ripple visibility.

PubMed

van Klink, Nicole; Mol, Arjen; Ferrier, Cyrille; Hillebrand, Arjan; Huiskamp, Geertjan; Zijlmans, Maeike

2018-01-01

Surface EEG can show epileptiform ripples in people with focal epilepsy, but identification is impeded by the low signal-to-noise ratio of the electrode recordings. We used beamformer-based virtual electrodes to improve ripple identification. We analyzed ten minutes of interictal EEG of nine patients with refractory focal epilepsy. EEGs with more than 60 channels and 20 spikes were included. We computed ∼79 virtual electrodes using a scalar beamformer and marked ripples (80-250 Hz) co-occurring with spikes in physical and virtual electrodes. Ripple numbers in physical and virtual electrodes were compared, and sensitivity and specificity of ripples for the region of interest (ROI; based on clinical information) were determined. Five patients had ripples in the physical electrodes and eight in the virtual electrodes, with more ripples in virtual than in physical electrodes (101 vs. 57, p = .007). Ripples in virtual electrodes predicted the ROI better than physical electrodes (AUC 0.65 vs. 0.56, p = .03). Beamforming increased ripple visibility in surface EEG. Virtual ripples predicted the ROI better than physical ripples, although sensitivity was still poor. Beamforming can facilitate ripple identification in EEG. Ripple localization needs to be improved to enable its use for presurgical evaluation in people with epilepsy. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Modification of EEG functional connectivity and EEG power spectra in overweight and obese patients with food addiction: An eLORETA study.

PubMed

Imperatori, Claudio; Fabbricatore, Mariantonietta; Innamorati, Marco; Farina, Benedetto; Quintiliani, Maria Isabella; Lamis, Dorian A; Mazzucchi, Edoardo; Contardi, Anna; Vollono, Catello; Della Marca, Giacomo

2015-12-01

We evaluated the modifications of electroencephalographic (EEG) power spectra and EEG connectivity in overweight and obese patients with elevated food addiction (FA) symptoms. Fourteen overweight and obese patients (3 men and 11 women) with three or more FA symptoms and fourteen overweight and obese patients (3 men and 11 women) with two or less FA symptoms were included in the study. EEG was recorded during three different conditions: 1) five minutes resting state (RS), 2) five minutes resting state after a single taste of a chocolate milkshake (ML-RS), and 3) five minutes resting state after a single taste of control neutral solution (N-RS). EEG analyses were conducted by means of the exact Low Resolution Electric Tomography software (eLORETA). Significant modification was observed only in the ML-RS condition. Compared to controls, patients with three or more FA symptoms showed an increase of delta power in the right middle frontal gyrus (Brodmann Area [BA] 8) and in the right precentral gyrus (BA 9), and theta power in the right insula (BA 13) and in the right inferior frontal gyrus (BA 47). Furthermore, compared to controls, patients with three or more FA symptoms showed an increase of functional connectivity in fronto-parietal areas in both the theta and alpha band. The increase of functional connectivity was also positively associated with the number of FA symptoms. Taken together, our results show that FA has similar neurophysiological correlates of other forms of substance-related and addictive disorders suggesting similar psychopathological mechanisms.

Discriminative Ocular Artifact Correction for Feature Learning in EEG Analysis.

PubMed

Xinyang Li; Cuntai Guan; Haihong Zhang; Kai Keng Ang

2017-08-01

Electrooculogram (EOG) artifact contamination is a common critical issue in general electroencephalogram (EEG) studies as well as in brain-computer interface (BCI) research. It is especially challenging when dedicated EOG channels are unavailable or when there are very few EEG channels available for independent component analysis based ocular artifact removal. It is even more challenging to avoid loss of the signal of interest during the artifact correction process, where the signal of interest can be multiple magnitudes weaker than the artifact. To address these issues, we propose a novel discriminative ocular artifact correction approach for feature learning in EEG analysis. Without extra ocular movement measurements, the artifact is extracted from raw EEG data, which is totally automatic and requires no visual inspection of artifacts. Then, artifact correction is optimized jointly with feature extraction by maximizing oscillatory correlations between trials from the same class and minimizing them between trials from different classes. We evaluate this approach on a real-world EEG dataset comprising 68 subjects performing cognitive tasks. The results showed that the approach is capable of not only suppressing the artifact components but also improving the discriminative power of a classifier with statistical significance. We also demonstrate that the proposed method addresses the confounding issues induced by ocular movements in cognitive EEG study.

Is EEG-biofeedback an effective treatment in autism spectrum disorders? A randomized controlled trial.

PubMed

Kouijzer, Mirjam E J; van Schie, Hein T; Gerrits, Berrie J L; Buitelaar, Jan K; de Moor, Jan M H

2013-03-01

EEG-biofeedback has been reported to reduce symptoms of autism spectrum disorders (ASD) in several studies. However, these studies did not control for nonspecific effects of EEG-biofeedback and did not distinguish between participants who succeeded in influencing their own EEG activity and participants who did not. To overcome these methodological shortcomings, this study evaluated the effects of EEG-biofeedback in ASD in a randomized pretest-posttest control group design with blinded active comparator and six months follow-up. Thirty-eight participants were randomly allocated to the EEG-biofeedback, skin conductance (SC)-biofeedback or waiting list group. EEG- and SC-biofeedback sessions were similar and participants were blinded to the type of feedback they received. Assessments pre-treatment, post-treatment, and after 6 months included parent ratings of symptoms of ASD, executive function tasks, and 19-channel EEG recordings. Fifty-four percent of the participants significantly reduced delta and/or theta power during EEG-biofeedback sessions and were identified as EEG-regulators. In these EEG-regulators, no statistically significant reductions of symptoms of ASD were observed, but they showed significant improvement in cognitive flexibility as compared to participants who managed to regulate SC. EEG-biofeedback seems to be an applicable tool to regulate EEG activity and has specific effects on cognitive flexibility, but it did not result in significant reductions in symptoms of ASD. An important finding was that no nonspecific effects of EEG-biofeedback were demonstrated.

MRI with and without a high-density EEG cap--what makes the difference?

PubMed

Klein, Carina; Hänggi, Jürgen; Luechinger, Roger; Jäncke, Lutz

2015-02-01

Besides the benefit of combining electroencephalography (EEG) and magnetic resonance imaging (MRI), much effort has been spent to develop algorithms aimed at successfully cleaning the EEG data from MRI-related gradient and ballistocardiological artifacts. However, there are also studies showing a negative influence of the EEG on MRI data quality. Therefore, in the present study, we focused for the first time on the influence of the EEG on morphometric measurements of T1-weighted MRI data (voxel- and surfaced-based morphometry). Here, we demonstrate a strong influence of the EEG on cortical thickness, surface area, and volume as well as subcortical volumes due to local EEG-related inhomogeneities of the static magnetic (B0) and the gradient field (B1). In a second step, we analyzed the signal-to-noise ratios for both the anatomical and the functional data when recorded simultaneously with EEG and MRI and compared them to the ratios of the MRI data without simultaneous EEG measurements. These analyses revealed consistently lower signal-to-noise ratios for anatomical as well as functional MRI data during simultaneous EEG registration. In contrast, further analyses of T2*-weighted images provided reliable results independent of whether including the individuals' T1-weighted image with or without the EEG cap in the fMRI preprocessing stream. Based on our findings, we strongly recommend against using the structural images obtained during simultaneous EEG-MRI recordings for further anatomical data analysis. Copyright © 2014 Elsevier Inc. All rights reserved.

The Default Mode Network and EEG Regional Spectral Power: A Simultaneous fMRI-EEG Study

PubMed Central

Werner, Cornelius J.; Hitz, Konrad; Boers, Frank; Kawohl, Wolfram; Shah, N. Jon

2014-01-01

Electroencephalography (EEG) frequencies have been linked to specific functions as an “electrophysiological signature” of a function. A combination of oscillatory rhythms has also been described for specific functions, with or without predominance of one specific frequency-band. In a simultaneous fMRI-EEG study at 3 T we studied the relationship between the default mode network (DMN) and the power of EEG frequency bands. As a methodological approach, we applied Multivariate Exploratory Linear Optimized Decomposition into Independent Components (MELODIC) and dual regression analysis for fMRI resting state data. EEG power for the alpha, beta, delta and theta-bands were extracted from the structures forming the DMN in a region-of-interest approach by applying Low Resolution Electromagnetic Tomography (LORETA). A strong link between the spontaneous BOLD response of the left parahippocampal gyrus and the delta-band extracted from the anterior cingulate cortex was found. A positive correlation between the beta-1 frequency power extracted from the posterior cingulate cortex (PCC) and the spontaneous BOLD response of the right supplementary motor cortex was also established. The beta-2 frequency power extracted from the PCC and the precuneus showed a positive correlation with the BOLD response of the right frontal cortex. Our results support the notion of beta-band activity governing the “status quo” in cognitive and motor setup. The highly significant correlation found between the delta power within the DMN and the parahippocampal gyrus is in line with the association of delta frequencies with memory processes. We assumed “ongoing activity” during “resting state” in bringing events from the past to the mind, in which the parahippocampal gyrus is a relevant structure. Our data demonstrate that spontaneous BOLD fluctuations within the DMN are associated with different EEG-bands and strengthen the conclusion that this network is characterized by a specific

EEG correlates of social interaction at distance

PubMed Central

Giroldini, William; Pederzoli, Luciano; Bilucaglia, Marco; Caini, Patrizio; Ferrini, Alessandro; Melloni, Simone; Prati, Elena; Tressoldi, Patrizio

2016-01-01

This study investigated EEG correlates of social interaction at distance between twenty-five pairs of participants who were not connected by any traditional channels of communication. Each session involved the application of 128 stimulations separated by intervals of random duration ranging from 4 to 6 seconds. One of the pair received a one-second stimulation from a light signal produced by an arrangement of red LEDs, and a simultaneous 500 Hz sinusoidal audio signal of the same length. The other member of the pair sat in an isolated sound-proof room, such that any sensory interaction between the pair was impossible. An analysis of the Event-Related Potentials associated with sensory stimulation using traditional averaging methods showed a distinct peak at approximately 300 ms, but only in the EEG activity of subjects who were directly stimulated. However, when a new algorithm was applied to the EEG activity based on the correlation between signals from all active electrodes, a weak but robust response was also detected in the EEG activity of the passive member of the pair, particularly within 9 – 10 Hz in the Alpha range. Using the Bootstrap method and the Monte Carlo emulation, this signal was found to be statistically significant. PMID:26966513

Automatic removal of eye-movement and blink artifacts from EEG signals.

PubMed

Gao, Jun Feng; Yang, Yong; Lin, Pan; Wang, Pei; Zheng, Chong Xun

2010-03-01

Frequent occurrence of electrooculography (EOG) artifacts leads to serious problems in interpreting and analyzing the electroencephalogram (EEG). In this paper, a robust method is presented to automatically eliminate eye-movement and eye-blink artifacts from EEG signals. Independent Component Analysis (ICA) is used to decompose EEG signals into independent components. Moreover, the features of topographies and power spectral densities of those components are extracted to identify eye-movement artifact components, and a support vector machine (SVM) classifier is adopted because it has higher performance than several other classifiers. The classification results show that feature-extraction methods are unsuitable for identifying eye-blink artifact components, and then a novel peak detection algorithm of independent component (PDAIC) is proposed to identify eye-blink artifact components. Finally, the artifact removal method proposed here is evaluated by the comparisons of EEG data before and after artifact removal. The results indicate that the method proposed could remove EOG artifacts effectively from EEG signals with little distortion of the underlying brain signals.

Deep learning for EEG-Based preference classification

NASA Astrophysics Data System (ADS)

Teo, Jason; Hou, Chew Lin; Mountstephens, James

2017-10-01

Electroencephalogram (EEG)-based emotion classification is rapidly becoming one of the most intensely studied areas of brain-computer interfacing (BCI). The ability to passively identify yet accurately correlate brainwaves with our immediate emotions opens up truly meaningful and previously unattainable human-computer interactions such as in forensic neuroscience, rehabilitative medicine, affective entertainment and neuro-marketing. One particularly useful yet rarely explored areas of EEG-based emotion classification is preference recognition [1], which is simply the detection of like versus dislike. Within the limited investigations into preference classification, all reported studies were based on musically-induced stimuli except for a single study which used 2D images. The main objective of this study is to apply deep learning, which has been shown to produce state-of-the-art results in diverse hard problems such as in computer vision, natural language processing and audio recognition, to 3D object preference classification over a larger group of test subjects. A cohort of 16 users was shown 60 bracelet-like objects as rotating visual stimuli on a computer display while their preferences and EEGs were recorded. After training a variety of machine learning approaches which included deep neural networks, we then attempted to classify the users' preferences for the 3D visual stimuli based on their EEGs. Here, we show that that deep learning outperforms a variety of other machine learning classifiers for this EEG-based preference classification task particularly in a highly challenging dataset with large inter- and intra-subject variability.

EEG phase reset due to auditory attention: an inverse time-scale approach.

PubMed

Low, Yin Fen; Strauss, Daniel J

2009-08-01

We propose a novel tool to evaluate the electroencephalograph (EEG) phase reset due to auditory attention by utilizing an inverse analysis of the instantaneous phase for the first time. EEGs were acquired through auditory attention experiments with a maximum entropy stimulation paradigm. We examined single sweeps of auditory late response (ALR) with the complex continuous wavelet transform. The phase in the frequency band that is associated with auditory attention (6-10 Hz, termed as theta-alpha border) was reset to the mean phase of the averaged EEGs. The inverse transform was applied to reconstruct the phase-modified signal. We found significant enhancement of the N100 wave in the reconstructed signal. Analysis of the phase noise shows the effects of phase jittering on the generation of the N100 wave implying that a preferred phase is necessary to generate the event-related potential (ERP). Power spectrum analysis shows a remarkable increase of evoked power but little change of total power after stabilizing the phase of EEGs. Furthermore, by resetting the phase only at the theta border of no attention data to the mean phase of attention data yields a result that resembles attention data. These results show strong connections between EEGs and ERP, in particular, we suggest that the presentation of an auditory stimulus triggers the phase reset process at the theta-alpha border which leads to the emergence of the N100 wave. It is concluded that our study reinforces other studies on the importance of the EEG in ERP genesis.

EEG

MedlinePlus

... injuries Infections Tumors EEG is also used to: Evaluate problems with sleep ( sleep disorders ) Monitor the brain ... Tissue death due to a blockage in blood flow (cerebral infarction) Drug or alcohol abuse Head injury ...

Alpha-theta border EEG abnormalities in preclinical Huntington's disease.

PubMed

Ponomareva, Natalya; Klyushnikov, Sergey; Abramycheva, Natalya; Malina, Daria; Scheglova, Nadejda; Fokin, Vitaly; Ivanova-Smolenskaia, Irina; Illarioshkin, Sergey

2014-09-15

Brain dysfunction precedes clinical manifestation of Huntington's disease (HD) by decades. This study was aimed to determine whether resting EEG is altered in preclinical HD mutations carriers (pre-HD). We examined relative power of broad traditional EEG bands as well as 1-Hz sub-bands of theta and alpha from the resting-state EEG of 29 pre-HD individuals and of 29 age-matched normal controls. The relative power of the narrow sub-band in the border of theta-alpha (7-8 Hz) was significantly reduced in pre-HD subjects as compared to normal controls, while the alterations in relative power of the broad frequency bands were not significant. In pre-HD subjects, the number of CAG repeats in the huntingtin (HTT) gene as well as the disease burden score (DBS) showed a positive correlation with relative power of the delta and theta frequency bands and their sub-bands and a negative correlation with alpha band relative power and the differences of relative power of the 7-8 Hz and 4-5 Hz frequency sub-bands. The obtained results suggest that EEG alterations in pre-HD individuals may be related to the course of the pathological process and to HD endophenotype. Analysis of the narrow EEG bands was found to be more useful for assessing EEG alterations in pre-HD individuals than a more traditional approach using broad bandwidths. Copyright © 2014 Elsevier B.V. All rights reserved.

A continuous mapping of sleep states through association of EEG with a mesoscale cortical model.

PubMed

Lopour, Beth A; Tasoglu, Savas; Kirsch, Heidi E; Sleigh, James W; Szeri, Andrew J

2011-04-01

Here we show that a mathematical model of the human sleep cycle can be used to obtain a detailed description of electroencephalogram (EEG) sleep stages, and we discuss how this analysis may aid in the prediction and prevention of seizures during sleep. The association between EEG data and the cortical model is found via locally linear embedding (LLE), a method of dimensionality reduction. We first show that LLE can distinguish between traditional sleep stages when applied to EEG data. It reliably separates REM and non-REM sleep and maps the EEG data to a low-dimensional output space where the sleep state changes smoothly over time. We also incorporate the concept of strongly connected components and use this as a method of automatic outlier rejection for EEG data. Then, by using LLE on a hybrid data set containing both sleep EEG and signals generated from the mesoscale cortical model, we quantify the relationship between the data and the mathematical model. This enables us to take any sample of sleep EEG data and associate it with a position among the continuous range of sleep states provided by the model; we can thus infer a trajectory of states as the subject sleeps. Lastly, we show that this method gives consistent results for various subjects over a full night of sleep and can be done in real time.

Reproducibility of EEG-fMRI results in a patient with fixation-off sensitivity.

PubMed

Formaggio, Emanuela; Storti, Silvia Francesca; Galazzo, Ilaria Boscolo; Bongiovanni, Luigi Giuseppe; Cerini, Roberto; Fiaschi, Antonio; Manganotti, Paolo

2014-07-01

Blood oxygenation level-dependent (BOLD) activation associated with interictal epileptiform discharges in a patient with fixation-off sensitivity (FOS) was studied using a combined electroencephalography-functional magnetic resonance imaging (EEG-fMRI) technique. An automatic approach for combined EEG-fMRI analysis and a subject-specific hemodynamic response function was used to improve general linear model analysis of the fMRI data. The EEG showed the typical features of FOS, with continuous epileptiform discharges during elimination of central vision by eye opening and closing and fixation; modification of this pattern was clearly visible and recognizable. During all 3 recording sessions EEG-fMRI activations indicated a BOLD signal decrease related to epileptiform activity in the parietal areas. This study can further our understanding of this EEG phenomenon and can provide some insight into the reliability of the EEG-fMRI technique in localizing the irritative zone.

Epilepsy with myoclonic-atonic seizures (Doose syndrome): When video-EEG polygraphy holds the key to syndrome diagnosis.

PubMed

Dragoumi, Pinelopi; Chivers, Fiona; Brady, Megan; Craft, Sheila; Mushati, David; Venkatachalam, Gopalakrishnan; Cross, Judith Helen; Das, Krishna B

2016-01-01

An electroclinical epilepsy syndrome diagnosis enables physicians to predict outcomes as well as select appropriate treatment options. We report a child who presented with reflex myoclonus at the age of 9 months and was initially diagnosed with myoclonic epilepsy in infancy. After 9 years of medically resistant myoclonic seizures, extensive investigations, and emerging learning difficulties, she was referred for video-telemetry to characterize her seizures in an attempt to make a syndromic diagnosis. A three-day video-telemetry assessment was performed to document seizures. Neck and deltoid EMG channels were applied from the onset of the recording. Frequent generalized bursts of 3- to 5-Hz spike/polyspike and slow wave discharges, associated with clinical manifestations, mostly myoclonic seizures, were noted. In addition, definite atonic components were noted on the neck EMG as well as the deltoids associated with the slow component of the ictal discharges. The EEG and polygraphy findings are suggestive of a generalized epilepsy characterized by predominantly myoclonic seizures with atonic components. This raises the possibility whether a variant of epilepsy with myoclonic-atonic seizures (Doose syndrome) may be the underlying diagnosis for this girl. A trial of the ketogenic diet would therefore be considered as an option in her future management in view of its beneficial effect in this condition.

Phenobarbitone, neonatal seizures, and video-EEG

PubMed Central

Boylan, G; Rennie, J; Pressler, R; Wilson, G; Morton, M; Binnie, C

2002-01-01

Aims: To evaluate the effectiveness of phenobarbitone as an anticonvulsant in neonates. Methods: An observational study using video-EEG telemetry. Video-EEG was obtained before treatment was started, for an hour after treatment was given, two hours after treatment was given, and again between 12 and 24 hours after treatment was given. Patients were recruited from all babies who required phenobarbitone (20–40 mg/kg intravenously over 20 minutes) for suspected clinical seizures and had EEG monitoring one hour before and up to 24 hours after the initial dose. An EEG seizure discharge was defined as a sudden repetitive stereotyped discharge lasting for at least 10 seconds. Neonatal status epilepticus was defined as continuous seizure activity for at least 30 minutes. Seizures were categorised as EEG seizure discharges only (electrographic), or as EEG seizure discharges with accompanying clinical manifestations (electroclinical). Surviving babies were assessed at one year using the Griffiths neurodevelopmental score. Results: Fourteen babies were studied. Four responded to phenobarbitone; these had normal or moderately abnormal EEG background abnormalities and outcome was good. In the other 10 babies electrographic seizures increased after treatment, whereas electroclinical seizures reduced. Three babies were treated with second line anticonvulsants, of whom two responded. One of these had a normal neurodevelopmental score at one year, but the outcome for the remainder of the whole group was poor. Conclusion: Phenobarbitone is often ineffective as a first line anticonvulsant in neonates with seizures in whom the background EEG is significantly abnormal. PMID:11978746

Source-Modeling Auditory Processes of EEG Data Using EEGLAB and Brainstorm.

PubMed

Stropahl, Maren; Bauer, Anna-Katharina R; Debener, Stefan; Bleichner, Martin G

2018-01-01

Electroencephalography (EEG) source localization approaches are often used to disentangle the spatial patterns mixed up in scalp EEG recordings. However, approaches differ substantially between experiments, may be strongly parameter-dependent, and results are not necessarily meaningful. In this paper we provide a pipeline for EEG source estimation, from raw EEG data pre-processing using EEGLAB functions up to source-level analysis as implemented in Brainstorm. The pipeline is tested using a data set of 10 individuals performing an auditory attention task. The analysis approach estimates sources of 64-channel EEG data without the prerequisite of individual anatomies or individually digitized sensor positions. First, we show advanced EEG pre-processing using EEGLAB, which includes artifact attenuation using independent component analysis (ICA). ICA is a linear decomposition technique that aims to reveal the underlying statistical sources of mixed signals and is further a powerful tool to attenuate stereotypical artifacts (e.g., eye movements or heartbeat). Data submitted to ICA are pre-processed to facilitate good-quality decompositions. Aiming toward an objective approach on component identification, the semi-automatic CORRMAP algorithm is applied for the identification of components representing prominent and stereotypic artifacts. Second, we present a step-wise approach to estimate active sources of auditory cortex event-related processing, on a single subject level. The presented approach assumes that no individual anatomy is available and therefore the default anatomy ICBM152, as implemented in Brainstorm, is used for all individuals. Individual noise modeling in this dataset is based on the pre-stimulus baseline period. For EEG source modeling we use the OpenMEEG algorithm as the underlying forward model based on the symmetric Boundary Element Method (BEM). We then apply the method of dynamical statistical parametric mapping (dSPM) to obtain physiologically

Quantitative EEG analysis in minimally conscious state patients during postural changes.

PubMed

Greco, A; Carboncini, M C; Virgillito, A; Lanata, A; Valenza, G; Scilingo, E P

2013-01-01

Mobilization and postural changes of patients with cognitive impairment are standard clinical practices useful for both psychic and physical rehabilitation process. During this process, several physiological signals, such as Electroen-cephalogram (EEG), Electrocardiogram (ECG), Photopletysmography (PPG), Respiration activity (RESP), Electrodermal activity (EDA), are monitored and processed. In this paper we investigated how quantitative EEG (qEEG) changes with postural modifications in minimally conscious state patients. This study is quite novel and no similar experimental data can be found in the current literature, therefore, although results are very encouraging, a quantitative analysis of the cortical area activated in such postural changes still needs to be deeply investigated. More specifically, this paper shows EEG power spectra and brain symmetry index modifications during a verticalization procedure, from 0 to 60 degrees, of three patients in Minimally Consciousness State (MCS) with focused region of impairment. Experimental results show a significant increase of the power in β band (12 - 30 Hz), commonly associated to human alertness process, thus suggesting that mobilization and postural changes can have beneficial effects in MCS patients.

Long-Range Correlation in alpha-Wave Predominant EEG in Human

NASA Astrophysics Data System (ADS)

Sharif, Asif; Chyan Lin, Der; Kwan, Hon; Borette, D. S.

2004-03-01

The background noise in the alpha-predominant EEG taken from eyes-open and eyes-closed neurophysiological states is studied. Scale-free characteristic is found in both cases using the wavelet approach developed by Simonsen and Nes [1]. The numerical results further show the scaling exponent during eyes-closed is consistently lower than eyes-open. We conjecture the origin of this difference is related to the temporal reconfiguration of the neural network in the brain. To further investigate the scaling structure of the EEG background noise, we extended the second order statistics to higher order moments using the EEG increment process. We found that the background fluctuation in the alpha-predominant EEG is predominantly monofractal. Preliminary results are given to support this finding and its implication in brain functioning is discussed. [1] A.H. Simonsen and O.M. Nes, Physical Review E, 58, 2779¡V2748 (1998).

Nonlinear Recurrent Dynamics and Long-Term Nonstationarities in EEG Alpha Cortical Activity: Implications for Choosing Adequate Segment Length in Nonlinear EEG Analyses.

PubMed

Cerquera, Alexander; Vollebregt, Madelon A; Arns, Martijn

2018-03-01

Nonlinear analysis of EEG recordings allows detection of characteristics that would probably be neglected by linear methods. This study aimed to determine a suitable epoch length for nonlinear analysis of EEG data based on its recurrence rate in EEG alpha activity (electrodes Fz, Oz, and Pz) from 28 healthy and 64 major depressive disorder subjects. Two nonlinear metrics, Lempel-Ziv complexity and scaling index, were applied in sliding windows of 20 seconds shifted every 1 second and in nonoverlapping windows of 1 minute. In addition, linear spectral analysis was carried out for comparison with the nonlinear results. The analysis with sliding windows showed that the cortical dynamics underlying alpha activity had a recurrence period of around 40 seconds in both groups. In the analysis with nonoverlapping windows, long-term nonstationarities entailed changes over time in the nonlinear dynamics that became significantly different between epochs across time, which was not detected with the linear spectral analysis. Findings suggest that epoch lengths shorter than 40 seconds neglect information in EEG nonlinear studies. In turn, linear analysis did not detect characteristics from long-term nonstationarities in EEG alpha waves of control subjects and patients with major depressive disorder patients. We recommend that application of nonlinear metrics in EEG time series, particularly of alpha activity, should be carried out with epochs around 60 seconds. In addition, this study aimed to demonstrate that long-term nonlinearities are inherent to the cortical brain dynamics regardless of the presence or absence of a mental disorder.

Usefulness of a simple sleep-deprived EEG protocol for epilepsy diagnosis in de novo subjects.

PubMed

Giorgi, Filippo S; Perini, Daria; Maestri, Michelangelo; Guida, Melania; Pizzanelli, Chiara; Caserta, Anna; Iudice, Alfonso; Bonanni, Enrica

2013-11-01

In case series concerning the role of EEG after sleep deprivation (SD-EEG) in epilepsy, patients' features and protocols vary dramatically from one report to another. In this study, we assessed the usefulness of a simple SD-EEG method in well characterized patients. Among the 963 adult subjects submitted to SD-EEG at our Center, in the period 2003-2010, we retrospectively selected for analysis only those: (1) evaluated for suspected epileptic seizures; (2) with a normal/non-specific baseline EEG; (3) still drug-free at the time of SD-EEG; (4) with an MRI analysis; (5) with at least 1 year follow-up. SD-EEG consisted in SD from 2:00 AM and laboratory EEG from 8:00 AM to 10:30 AM. We analyzed epileptic interictal abnormalities (IIAs) and their correlations with patients' features. Epilepsy was confirmed in 131 patients. SD-EEG showed IIAs in 41.2% of all patients with epilepsy, and a 91.1% specificity for epilepsy diagnosis; IIAs types observed during SD-EEG are different in generalized versus focal epilepsies; for focal epilepsies, the IIAs yield in SD-EEG is higher than in second routine EEG. This simple SD-EEG protocol is very useful in de novo patients with suspected seizures. This study sheds new light on the role of SD-EEG in specific epilepsy populations. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

An EEG blind source separation algorithm based on a weak exclusion principle.

PubMed

Lan Ma; Blu, Thierry; Wang, William S-Y

2016-08-01

The question of how to separate individual brain and non-brain signals, mixed by volume conduction in electroencephalographic (EEG) and other electrophysiological recordings, is a significant problem in contemporary neuroscience. This study proposes and evaluates a novel EEG Blind Source Separation (BSS) algorithm based on a weak exclusion principle (WEP). The chief point in which it differs from most previous EEG BSS algorithms is that the proposed algorithm is not based upon the hypothesis that the sources are statistically independent. Our first step was to investigate algorithm performance on simulated signals which have ground truth. The purpose of this simulation is to illustrate the proposed algorithm's efficacy. The results show that the proposed algorithm has good separation performance. Then, we used the proposed algorithm to separate real EEG signals from a memory study using a revised version of Sternberg Task. The results show that the proposed algorithm can effectively separate the non-brain and brain sources.

Automated Classification and Removal of EEG Artifacts With SVM and Wavelet-ICA.

PubMed

Sai, Chong Yeh; Mokhtar, Norrima; Arof, Hamzah; Cumming, Paul; Iwahashi, Masahiro

2018-05-01

Brain electrical activity recordings by electroencephalography (EEG) are often contaminated with signal artifacts. Procedures for automated removal of EEG artifacts are frequently sought for clinical diagnostics and brain-computer interface applications. In recent years, a combination of independent component analysis (ICA) and discrete wavelet transform has been introduced as standard technique for EEG artifact removal. However, in performing the wavelet-ICA procedure, visual inspection or arbitrary thresholding may be required for identifying artifactual components in the EEG signal. We now propose a novel approach for identifying artifactual components separated by wavelet-ICA using a pretrained support vector machine (SVM). Our method presents a robust and extendable system that enables fully automated identification and removal of artifacts from EEG signals, without applying any arbitrary thresholding. Using test data contaminated by eye blink artifacts, we show that our method performed better in identifying artifactual components than did existing thresholding methods. Furthermore, wavelet-ICA in conjunction with SVM successfully removed target artifacts, while largely retaining the EEG source signals of interest. We propose a set of features including kurtosis, variance, Shannon's entropy, and range of amplitude as training and test data of SVM to identify eye blink artifacts in EEG signals. This combinatorial method is also extendable to accommodate multiple types of artifacts present in multichannel EEG. We envision future research to explore other descriptive features corresponding to other types of artifactual components.

Analysis of EEG Related Saccadic Eye Movement

NASA Astrophysics Data System (ADS)

Funase, Arao; Kuno, Yoshiaki; Okuma, Shigeru; Yagi, Tohru

Our final goal is to establish the model for saccadic eye movement that connects the saccade and the electroencephalogram(EEG). As the first step toward this goal, we recorded and analyzed the saccade-related EEG. In the study recorded in this paper, we tried detecting a certain EEG that is peculiar to the eye movement. In these experiments, each subject was instructed to point their eyes toward visual targets (LEDs) or the direction of the sound sources (buzzers). In the control cases, the EEG was recorded in the case of no eye movemens. As results, in the visual experiments, we found that the potential of EEG changed sharply on the occipital lobe just before eye movement. Furthermore, in the case of the auditory experiments, similar results were observed. In the case of the visual experiments and auditory experiments without eye movement, we could not observed the EEG changed sharply. Moreover, when the subject moved his/her eyes toward a right-side target, a change in EEG potential was found on the right occipital lobe. On the contrary, when the subject moved his/her eyes toward a left-side target, a sharp change in EEG potential was found on the left occipital lobe.

Multifractal analysis of real and imaginary movements: EEG study

NASA Astrophysics Data System (ADS)

Pavlov, Alexey N.; Maksimenko, Vladimir A.; Runnova, Anastasiya E.; Khramova, Marina V.; Pisarchik, Alexander N.

2018-04-01

We study abilities of the wavelet-based multifractal analysis in recognition specific dynamics of electrical brain activity associated with real and imaginary movements. Based on the singularity spectra we analyze electroencephalograms (EEGs) acquired in untrained humans (operators) during imagination of hands movements, and show a possibility to distinguish between the related EEG patterns and the recordings performed during real movements or the background electrical brain activity. We discuss how such recognition depends on the selected brain region.

Auto-correlation in the motor/imaginary human EEG signals: A vision about the FDFA fluctuations.

PubMed

Zebende, Gilney Figueira; Oliveira Filho, Florêncio Mendes; Leyva Cruz, Juan Alberto

2017-01-01

In this paper we analyzed, by the FDFA root mean square fluctuation (rms) function, the motor/imaginary human activity produced by a 64-channel electroencephalography (EEG). We utilized the Physionet on-line databank, a publicly available database of human EEG signals, as a standardized reference database for this study. Herein, we report the use of detrended fluctuation analysis (DFA) method for EEG analysis. We show that the complex time series of the EEG exhibits characteristic fluctuations depending on the analyzed channel in the scalp-recorded EEG. In order to demonstrate the effectiveness of the proposed technique, we analyzed four distinct channels represented here by F332, F637 (frontal region of the head) and P349, P654 (parietal region of the head). We verified that the amplitude of the FDFA rms function is greater for the frontal channels than for the parietal. To tabulate this information in a better way, we define and calculate the difference between FDFA (in log scale) for the channels, thus defining a new path for analysis of EEG signals. Finally, related to the studied EEG signals, we obtain the auto-correlation exponent, αDFA by DFA method, that reveals self-affinity at specific time scale. Our results shows that this strategy can be applied to study the human brain activity in EEG processing.

EEG Sleep Stages Classification Based on Time Domain Features and Structural Graph Similarity.

PubMed

Diykh, Mohammed; Li, Yan; Wen, Peng

2016-11-01

The electroencephalogram (EEG) signals are commonly used in diagnosing and treating sleep disorders. Many existing methods for sleep stages classification mainly depend on the analysis of EEG signals in time or frequency domain to obtain a high classification accuracy. In this paper, the statistical features in time domain, the structural graph similarity and the K-means (SGSKM) are combined to identify six sleep stages using single channel EEG signals. Firstly, each EEG segment is partitioned into sub-segments. The size of a sub-segment is determined empirically. Secondly, statistical features are extracted, sorted into different sets of features and forwarded to the SGSKM to classify EEG sleep stages. We have also investigated the relationships between sleep stages and the time domain features of the EEG data used in this paper. The experimental results show that the proposed method yields better classification results than other four existing methods and the support vector machine (SVM) classifier. A 95.93% average classification accuracy is achieved by using the proposed method.

The FNS-based analyzing the EEG to diagnose the bipolar affective disorder

NASA Astrophysics Data System (ADS)

Panischev, Yu; Panischeva, S. N.; Demin, S. A.

2015-11-01

Here we demonstrate a capability of method based on the Flicker-Noise Spectroscopy (FNS) in analyzing the manifestation bipolar affective disorder (BAD) in EEG. Generally EEG from BAD patient does not show the visual differences from healthy EEG. Analyzing the behavior of FNS-parameters and the structure of 3D-cross correlators allows to discover the differential characteristics of BAD. The cerebral cortex electric activity of BAD patients have a specific collective dynamics and configuration of the FNS-characteristics in comparison with healthy subjects.

EEG source analysis of data from paralysed subjects

NASA Astrophysics Data System (ADS)

Carabali, Carmen A.; Willoughby, John O.; Fitzgibbon, Sean P.; Grummett, Tyler; Lewis, Trent; DeLosAngeles, Dylan; Pope, Kenneth J.

2015-12-01

One of the limitations of Encephalography (EEG) data is its quality, as it is usually contaminated with electric signal from muscle. This research intends to study results of two EEG source analysis methods applied to scalp recordings taken in paralysis and in normal conditions during the performance of a cognitive task. The aim is to determinate which types of analysis are appropriate for dealing with EEG data containing myogenic components. The data used are the scalp recordings of six subjects in normal conditions and during paralysis while performing different cognitive tasks including the oddball task which is the object of this research. The data were pre-processed by filtering it and correcting artefact, then, epochs of one second long for targets and distractors were extracted. Distributed source analysis was performed in BESA Research 6.0, using its results and information from the literature, 9 ideal locations for source dipoles were identified. The nine dipoles were used to perform discrete source analysis, fitting them to the averaged epochs for obtaining source waveforms. The results were statistically analysed comparing the outcomes before and after the subjects were paralysed. Finally, frequency analysis was performed for better explain the results. The findings were that distributed source analysis could produce confounded results for EEG contaminated with myogenic signals, conversely, statistical analysis of the results from discrete source analysis showed that this method could help for dealing with EEG data contaminated with muscle electrical signal.

Diagnosis of multiple sclerosis from EEG signals using nonlinear methods.

PubMed

Torabi, Ali; Daliri, Mohammad Reza; Sabzposhan, Seyyed Hojjat

2017-12-01

EEG signals have essential and important information about the brain and neural diseases. The main purpose of this study is classifying two groups of healthy volunteers and Multiple Sclerosis (MS) patients using nonlinear features of EEG signals while performing cognitive tasks. EEG signals were recorded when users were doing two different attentional tasks. One of the tasks was based on detecting a desired change in color luminance and the other task was based on detecting a desired change in direction of motion. EEG signals were analyzed in two ways: EEG signals analysis without rhythms decomposition and EEG sub-bands analysis. After recording and preprocessing, time delay embedding method was used for state space reconstruction; embedding parameters were determined for original signals and their sub-bands. Afterwards nonlinear methods were used in feature extraction phase. To reduce the feature dimension, scalar feature selections were done by using T-test and Bhattacharyya criteria. Then, the data were classified using linear support vector machines (SVM) and k-nearest neighbor (KNN) method. The best combination of the criteria and classifiers was determined for each task by comparing performances. For both tasks, the best results were achieved by using T-test criterion and SVM classifier. For the direction-based and the color-luminance-based tasks, maximum classification performances were 93.08 and 79.79% respectively which were reached by using optimal set of features. Our results show that the nonlinear dynamic features of EEG signals seem to be useful and effective in MS diseases diagnosis.

Analysis of tractable distortion metrics for EEG compression applications.

PubMed

Bazán-Prieto, Carlos; Blanco-Velasco, Manuel; Cárdenas-Barrera, Julián; Cruz-Roldán, Fernando

2012-07-01

Coding distortion in lossy electroencephalographic (EEG) signal compression methods is evaluated through tractable objective criteria. The percentage root-mean-square difference, which is a global and relative indicator of the quality held by reconstructed waveforms, is the most widely used criterion. However, this parameter does not ensure compliance with clinical standard guidelines that specify limits to allowable noise in EEG recordings. As a result, expert clinicians may have difficulties interpreting the resulting distortion of the EEG for a given value of this parameter. Conversely, the root-mean-square error is an alternative criterion that quantifies distortion in understandable units. In this paper, we demonstrate that the root-mean-square error is better suited to control and to assess the distortion introduced by compression methods. The experiments conducted in this paper show that the use of the root-mean-square error as target parameter in EEG compression allows both clinicians and scientists to infer whether coding error is clinically acceptable or not at no cost for the compression ratio.

Forecasting seizures in dogs with naturally occurring epilepsy.

PubMed

Howbert, J Jeffry; Patterson, Edward E; Stead, S Matt; Brinkmann, Ben; Vasoli, Vincent; Crepeau, Daniel; Vite, Charles H; Sturges, Beverly; Ruedebusch, Vanessa; Mavoori, Jaideep; Leyde, Kent; Sheffield, W Douglas; Litt, Brian; Worrell, Gregory A

2014-01-01

Seizure forecasting has the potential to create new therapeutic strategies for epilepsy, such as providing patient warnings and delivering preemptive therapy. Progress on seizure forecasting, however, has been hindered by lack of sufficient data to rigorously evaluate the hypothesis that seizures are preceded by physiological changes, and are not simply random events. We investigated seizure forecasting in three dogs with naturally occurring focal epilepsy implanted with a device recording continuous intracranial EEG (iEEG). The iEEG spectral power in six frequency bands: delta (0.1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), beta (12-30 Hz), low-gamma (30-70 Hz), and high-gamma (70-180 Hz), were used as features. Logistic regression classifiers were trained to discriminate labeled pre-ictal and inter-ictal data segments using combinations of the band spectral power features. Performance was assessed on separate test data sets via 10-fold cross-validation. A total of 125 spontaneous seizures were detected in continuous iEEG recordings spanning 6.5 to 15 months from 3 dogs. When considering all seizures, the seizure forecasting algorithm performed significantly better than a Poisson-model chance predictor constrained to have the same time in warning for all 3 dogs over a range of total warning times. Seizure clusters were observed in all 3 dogs, and when the effect of seizure clusters was decreased by considering the subset of seizures separated by at least 4 hours, the forecasting performance remained better than chance for a subset of algorithm parameters. These results demonstrate that seizures in canine epilepsy are not randomly occurring events, and highlight the feasibility of long-term seizure forecasting using iEEG monitoring.

Topographical characteristics and principal component structure of the hypnagogic EEG.

PubMed

Tanaka, H; Hayashi, M; Hori, T

1997-07-01

The purpose of the present study was to identify the dominant topographic components of electroencephalographs (EEG) and their behavior during the waking-sleeping transition period. Somnography of nocturnal sleep was recorded on 10 male subjects. Each recording, from "lights-off" to 5 minutes after the appearance of the first sleep spindle, was analyzed. The typical EEG patterns during hypnagogic period were classified into nine EEG stages. Topographic maps demonstrated that the dominant areas of alpha-band activity moved from the posterior areas to anterior areas along the midline of the scalp. In delta-, theta-, and sigma-band activities, the differences of EEG amplitude between the focus areas (the dominant areas) and the surrounding areas increased as a function of EEG stage. To identify the dominant topographic components, a principal component analysis was carried out on a 12-channel EEG data set for each of six frequency bands. The dominant areas of alpha 2- (9.6-11.4 Hz) and alpha 3- (11.6-13.4 Hz) band activities moved from the posterior to anterior areas, respectively. The distribution of alpha 2-band activity on the scalp clearly changed just after EEG stage 3 (alpha intermittent, < 50%). On the other hand, alpha 3-band activity became dominant in anterior areas after the appearance of vertex sharp-wave bursts (EEG stage 7). For the sigma band, the amplitude of extensive areas from the frontal pole to the parietal showed a rapid rise after the onset of stage 7 (the appearance of vertex sharp-wave bursts). Based on the results, sleep onset process probably started before the onset of sleep stage 1 in standard criteria. On the other hand, the basic sleep process may start before the onset of sleep stage 2 or the manually scored spindles.

Correlation of EEG with neuropsychological status in children with epilepsy.

PubMed

Hsu, David A; Rayer, Katherine; Jackson, Daren C; Stafstrom, Carl E; Hsu, Murielle; Ferrazzano, Peter A; Dabbs, Kevin; Worrell, Gregory A; Jones, Jana E; Hermann, Bruce P

2016-02-01

To determine correlations of the EEG frequency spectrum with neuropsychological status in children with idiopathic epilepsy. Forty-six children ages 8-18 years old with idiopathic epilepsy were retrospectively identified and analyzed for correlations between EEG spectra and neuropsychological status using multivariate linear regression. In addition, the theta/beta ratio, which has been suggested as a clinically useful EEG marker of attention-deficit hyperactivity disorder (ADHD), and an EEG spike count were calculated for each subject. Neuropsychological status was highly correlated with posterior alpha (8-15 Hz) EEG activity in a complex way, with both positive and negative correlations at lower and higher alpha frequency sub-bands for each cognitive task in a pattern that depends on the specific cognitive task. In addition, the theta/beta ratio was a specific but insensitive indicator of ADHD status in children with epilepsy; most children both with and without epilepsy have normal theta/beta ratios. The spike count showed no correlations with neuropsychological status. (1) The alpha rhythm may have at least two sub-bands which serve different purposes. (2) The theta/beta ratio is not a sensitive indicator of ADHD status in children with epilepsy. (3) The EEG frequency spectrum correlates more robustly with neuropsychological status than spike count analysis in children with idiopathic epilepsy. (1) The role of posterior alpha rhythms in cognition is complex and can be overlooked if EEG spectral resolution is too coarse or if neuropsychological status is assessed too narrowly. (2) ADHD in children with idiopathic epilepsy may involve different mechanisms from those in children without epilepsy. (3) Reliable correlations with neuropsychological status require longer EEG samples when using spike count analysis than when using frequency spectra. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights

Multi-Class Motor Imagery EEG Decoding for Brain-Computer Interfaces

PubMed Central

Wang, Deng; Miao, Duoqian; Blohm, Gunnar

2012-01-01

Recent studies show that scalp electroencephalography (EEG) as a non-invasive interface has great potential for brain-computer interfaces (BCIs). However, one factor that has limited practical applications for EEG-based BCI so far is the difficulty to decode brain signals in a reliable and efficient way. This paper proposes a new robust processing framework for decoding of multi-class motor imagery (MI) that is based on five main processing steps. (i) Raw EEG segmentation without the need of visual artifact inspection. (ii) Considering that EEG recordings are often contaminated not just by electrooculography (EOG) but also other types of artifacts, we propose to first implement an automatic artifact correction method that combines regression analysis with independent component analysis for recovering the original source signals. (iii) The significant difference between frequency components based on event-related (de-) synchronization and sample entropy is then used to find non-contiguous discriminating rhythms. After spectral filtering using the discriminating rhythms, a channel selection algorithm is used to select only relevant channels. (iv) Feature vectors are extracted based on the inter-class diversity and time-varying dynamic characteristics of the signals. (v) Finally, a support vector machine is employed for four-class classification. We tested our proposed algorithm on experimental data that was obtained from dataset 2a of BCI competition IV (2008). The overall four-class kappa values (between 0.41 and 0.80) were comparable to other models but without requiring any artifact-contaminated trial removal. The performance showed that multi-class MI tasks can be reliably discriminated using artifact-contaminated EEG recordings from a few channels. This may be a promising avenue for online robust EEG-based BCI applications. PMID:23087607

EEG analysis using wavelet-based information tools.

PubMed

Rosso, O A; Martin, M T; Figliola, A; Keller, K; Plastino, A

2006-06-15

Wavelet-based informational tools for quantitative electroencephalogram (EEG) record analysis are reviewed. Relative wavelet energies, wavelet entropies and wavelet statistical complexities are used in the characterization of scalp EEG records corresponding to secondary generalized tonic-clonic epileptic seizures. In particular, we show that the epileptic recruitment rhythm observed during seizure development is well described in terms of the relative wavelet energies. In addition, during the concomitant time-period the entropy diminishes while complexity grows. This is construed as evidence supporting the conjecture that an epileptic focus, for this kind of seizures, triggers a self-organized brain state characterized by both order and maximal complexity.

The quantitative measurement of consciousness during epileptic seizures.

PubMed

Nani, Andrea; Cavanna, Andrea E

2014-01-01

The assessment of consciousness is a fundamental element in the classification of epileptic seizures. It is, therefore, of great importance for clinical practice to develop instruments that enable an accurate and reliable measurement of the alteration of consciousness during seizures. Over the last few years, three psychometric scales have been specifically proposed to measure ictal consciousness: the Ictal Consciousness Inventory (ICI), the Consciousness Seizure Scale (CSS), and the Responsiveness in Epilepsy Scale--versions I and II (RES-I and RES-II). The ICI is a self-report psychometric instrument which retrospectively assesses ictal consciousness along the dimensions of the level/arousal and contents/awareness. The CSS has been used by clinicians to quantify the impairment of consciousness in order to establish correlations with the brain mechanisms underlying alterations of consciousness during temporal lobe seizures. The most recently developed observer-rated instrument is the RES-I, which has been used to assess responsiveness during epileptic seizures in patients undergoing video-EEG. The implementation of standardized psychometric tools for the assessment of ictal consciousness can complement clinical observations and contribute to improve accuracy in seizure classification. © 2013.

Quantitative EEG of Rapid-Eye-Movement Sleep: A Marker of Amnestic Mild Cognitive Impairment.

PubMed

Brayet, Pauline; Petit, Dominique; Frauscher, Birgit; Gagnon, Jean-François; Gosselin, Nadia; Gagnon, Katia; Rouleau, Isabelle; Montplaisir, Jacques

2016-04-01

The basal forebrain cholinergic system, which is impaired in early Alzheimer's disease, is more crucial for the activation of rapid-eye-movement (REM) sleep electroencephalogram (EEG) than it is for wakefulness. Quantitative EEG from REM sleep might thus provide an earlier and more accurate marker of the development of Alzheimer's disease in subjects with mild cognitive impairment (MCI) subjects than that from wakefulness. To assess the superiority of the REM sleep EEG as a screening tool for preclinical Alzheimer's disease, 22 subjects with amnestic MCI (a-MCI; 63.9±7.7 years), 10 subjects with nonamnestic MCI (na-MCI; 64.1±4.5 years) and 32 controls (63.7±6.6 years) participated in the study. Spectral analyses of the waking EEG and REM sleep EEG were performed and the [(delta+theta)/(alpha+beta)] ratio was used to assess between-group differences in EEG slowing. The a-MCI subgroup showed EEG slowing in frontal lateral regions compared to both na-MCI and control groups. This EEG slowing was present in wakefulness (compared to controls) but was much more prominent in REM sleep. Moreover, the comparison between amnestic and nonamnestic subjects was found significant only for the REM sleep EEG. There was no difference in EEG power ratio between na-MCI and controls for any of the 7 cortical regions studied. These findings demonstrate the superiority of the REM sleep EEG in the discrimination between a-MCI and both na-MCI and control subjects. © EEG and Clinical Neuroscience Society (ECNS) 2015.

Rapidly Learned Identification of Epileptic Seizures from Sonified EEG

PubMed Central

Loui, Psyche; Koplin-Green, Matan; Frick, Mark; Massone, Michael

2014-01-01

Sonification refers to a process by which data are converted into sound, providing an auditory alternative to visual display. Currently, the prevalent method for diagnosing seizures in epilepsy is by visually reading a patient’s electroencephalogram (EEG). However, sonification of the EEG data provides certain advantages due to the nature of human auditory perception. We hypothesized that human listeners will be able to identify seizures from EEGs using the auditory modality alone, and that accuracy of seizure identification will increase after a short training session. Here, we describe an algorithm that we have used to sonify EEGs of both seizure and non-seizure activity, followed by a training study in which subjects listened to short clips of sonified EEGs and determined whether each clip was of seizure or normal activity, both before and after a short training session. Results show that before training subjects performed at chance level in differentiating seizures from non-seizures, but there was a significant improvement of accuracy after the training session. After training, subjects successfully distinguished seizures from non-seizures using the auditory modality alone. Further analyses using signal detection theory demonstrated improvement in sensitivity and reduction in response bias as a result of training. This study demonstrates the potential of sonified EEGs to be used for the detection of seizures. Future studies will attempt to increase accuracy using novel training and sonification modifications, with the goals of managing, predicting, and ultimately controlling seizures using sonification as a possible biofeedback-based intervention for epilepsy. PMID:25352802

Correlation between perceived stigma and EEG paroxysmal abnormality in childhood epilepsy.

PubMed

Kanemura, Hideaki; Sano, Fumikazu; Ohyama, Tetsuo; Sugita, Kanji; Aihara, Masao

2015-11-01

We investigated the relationship between abnormal electroencephalogram (EEG) findings such as localized EEG paroxysmal abnormality (PA) and the perception of stigma to determine EEG factors associated with perceived stigma in childhood epilepsy. Participants comprised 40 patients (21 boys, 19 girls; mean age, 14.6 years) with epilepsy at enrollment. The criteria for inclusion were as follows: 1) age of 12-18 years, inclusive; 2) ≥6 months after epilepsy onset; 3) the ability to read and speak Japanese; and 4) the presence of EEG PA. Fifteen healthy seizure-free children were included as a control group. Participants were asked to rate how often they felt or acted in the ways described in the items of the Child Stigma Scale using a 5-point scale. Electroencephalogram paroxysms were classified based on the presence of spikes, sharp waves, or spike-wave complexes, whether focal or generalized. Participants showed significantly higher stigma scores than healthy subjects (p<0.01). A higher score reflects a greater perception of stigma. The average total scores of patients presenting with EEG PA at generalized, frontal, RD, midtemporal, and occipital regions were 2.3, 4.0, 2.4, 3.2, and 2.2, respectively. The scores of all questions were higher in the frontal group than those in other regions (p<0.01). Children presenting with frontal EEG PA perceived a greater stigma than children presenting with nonfrontal EEG PA (p<0.01). A relationship was identified between frontal EEG PA and a greater perception of stigma. Further studies are needed to confirm whether frontal EEG PA may function as a mediator of emotional responses such as perceived stigma in childhood epilepsy. Copyright © 2015 Elsevier Inc. All rights reserved.

Contribution of EEG in transient neurological deficits.

PubMed

Lozeron, Pierre; Tcheumeni, Nadine Carole; Turki, Sahar; Amiel, Hélène; Meppiel, Elodie; Masmoudi, Sana; Roos, Caroline; Crassard, Isabelle; Plaisance, Patrick; Benbetka, Houria; Guichard, Jean-Pierre; Houdart, Emmanuel; Baudoin, Hélène; Kubis, Nathalie

2018-01-01

Identification of stroke mimics and 'chameleons' among transient neurological deficits (TND) is critical. Diagnostic workup consists of a brain imaging study, for a vascular disease or a brain tumour and EEG, for epileptiform discharges. The precise role of EEG in this diagnostic workup has, however, never been clearly delineated. However, this could be crucial in cases of atypical or incomplete presentation with consequences on disease management and treatment. We analysed the EEG patterns on 95 consecutive patients referred for an EEG within 7 days of a TND with diagnostic uncertainty. Patients were classified at the discharge or the 3-month follow-up visit as: 'ischemic origin', 'migraine aura', 'focal seizure', and 'other'. All patients had a brain imaging study. EEG characteristics were correlated to the TND symptoms, imaging study, and final diagnosis. Sixty four (67%) were of acute onset. Median symptom duration was 45 min. Thirty two % were 'ischemic', 14% 'migraine aura', 19% 'focal seizure', and 36% 'other' cause. EEGs were recorded with a median delay of 1.6 day after symptoms onset. Forty EEGs (42%) were abnormal. Focal slow waves were the most common finding (43%), also in the ischemic group (43%), whether patients had a typical presentation or not. Epileptiform discharges were found in three patients, one with focal seizure and two with migraine aura. Non-specific EEG focal slowing is commonly found in TND, and may last several days. We found no difference in EEG presentation between stroke mimics and stroke chameleons, and between other diagnoses.

Long-term monitoring of cardiorespiratory patterns in drug-resistant epilepsy.

PubMed

Goldenholz, Daniel M; Kuhn, Amanda; Austermuehle, Alison; Bachler, Martin; Mayer, Christopher; Wassertheurer, Siegfried; Inati, Sara K; Theodore, William H

2017-01-01

Sudden unexplained death in epilepsy (SUDEP) during inpatient electroencephalography (EEG) monitoring has been a rare but potentially preventable event, with associated cardiopulmonary markers. To date, no systematic evaluation of alarm settings for a continuous pulse oximeter (SpO 2 ) has been performed. In addition, evaluation of the interrelationship between the ictal and interictal states for cardiopulmonary measures has not been reported. Patients with epilepsy were monitored using video-EEG, SpO 2 , and electrocardiography (ECG). Alarm thresholds were tested systematically, balancing the number of false alarms with true seizure detections. Additional cardiopulmonary patterns were explored using automated ECG analysis software. One hundred ninety-three seizures (32 generalized) were evaluated from 45 patients (7,104 h recorded). Alarm thresholds of 80-86% SpO 2 detected 63-73% of all generalized convulsions and 20-28% of all focal seizures (81-94% of generalized and 25-36% of focal seizures when considering only evaluable data). These same thresholds resulted in 25-146 min between false alarms. The sequential probability of ictal SpO 2 revealed a potential common seizure termination pathway of desaturation. A statistical model of corrected QT intervals (QTc), heart rate (HR), and SpO 2 revealed close cardiopulmonary coupling ictally. Joint probability maps of QTc and SpO 2 demonstrated that many patients had baseline dysfunction in either cardiac, pulmonary, or both domains, and that ictally there was dissociation-some patients exhibited further dysfunction in one or both domains. Optimal selection of continuous pulse oximetry thresholds involves a tradeoff between seizure detection accuracy and false alarm frequency. Alarming at 86% for patients that tend to have fewer false alarms and at 80% for those who have more, would likely result in a reasonable tradeoff. The cardiopulmonary findings may lead to SUDEP biomarkers and early seizure termination therapies

EEG and MEG: sensitivity to epileptic spike activity as function of source orientation and depth.

PubMed

Hunold, A; Funke, M E; Eichardt, R; Stenroos, M; Haueisen, J

2016-07-01

Simultaneous electroencephalography (EEG) and magnetoencephalography (MEG) recordings of neuronal activity from epileptic patients reveal situations in which either EEG or MEG or both modalities show visible interictal spikes. While different signal-to-noise ratios (SNRs) of the spikes in EEG and MEG have been reported, a quantitative relation of spike source orientation and depth as well as the background brain activity to the SNR has not been established. We investigated this quantitative relationship for both dipole and patch sources in an anatomically realistic cortex model. Altogether, 5600 dipole and 3300 patch sources were distributed on the segmented cortical surfaces of two volunteers. The sources were classified according to their quantified depths and orientations, ranging from 20 mm to 60 mm below the skin surface and radial and tangential, respectively. The source time-courses mimicked an interictal spike, and the simulated background activity emulated resting activity. Simulations were conducted with individual three-compartment boundary element models. The SNR was evaluated for 128 EEG, 102 MEG magnetometer, and 204 MEG gradiometer channels. For superficial dipole and superficial patch sources, EEG showed higher SNRs for dominantly radial orientations, and MEG showed higher values for dominantly tangential orientations. Gradiometers provided higher SNR than magnetometers for superficial sources, particularly for those with dominantly tangential orientations. The orientation dependent difference in SNR in EEG and MEG gradually changed as the sources were located deeper, where the interictal spikes generated higher SNRs in EEG compared to those in MEG for all source orientations. With deep sources, the SNRs in gradiometers and magnetometers were of the same order. To better detect spikes, both EEG and MEG should be used.

Detecting determinism with improved sensitivity in time series: rank-based nonlinear predictability score.

PubMed

Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G

2014-09-01

The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

Detecting determinism with improved sensitivity in time series: Rank-based nonlinear predictability score

NASA Astrophysics Data System (ADS)

Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G.

2014-09-01

The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

Amplitude-integrated EEG colored according to spectral edge frequency.

PubMed

Kobayashi, Katsuhiro; Mimaki, Nobuyoshi; Endoh, Fumika; Inoue, Takushi; Yoshinaga, Harumi; Ohtsuka, Yoko

2011-10-01

To improve the interpretability of figures containing an amplitude-integrated electroencephalogram (aEEG), we devised a color scale that allows us to incorporate spectral edge frequency (SEF) information into aEEG figures. Preliminary clinical assessment of this novel technique, which we call aEEG/SEF, was performed using neonatal and early infantile seizure data. We created aEEG, color density spectral array (DSA), and aEEG/SEF figures for focal seizures recorded in seven infants. Each seizure was paired with an interictal period from the same patient. After receiving instructions on how to interpret the figures, eight test reviewers examined each of the 72 figures displaying compressed data in aEEG, DSA, or aEEG/SEF form (12 seizures and 12 corresponding interictal periods) and attempted to identify each as a seizure or otherwise. They were not provided with any information regarding the original record. The median number of correctly identified seizures, out of a total of 12, was 7 (58.3%) for aEEG figures, 8 (66.7%) for DSA figures and 10 (83.3%) for aEEG/SEF figures; the differences among these are statistically significant (p=0.011). All reviewers concluded that aEEG/SEF figures were the easiest to interpret. The aEEG/SEF data presentation technique is a valid option in aEEG recordings of seizures. Copyright © 2011 Elsevier B.V. All rights reserved.

Cognitive workload modulation through degraded visual stimuli: a single-trial EEG study

NASA Astrophysics Data System (ADS)

Yu, K.; Prasad, I.; Mir, H.; Thakor, N.; Al-Nashash, H.

2015-08-01

Objective. Our experiments explored the effect of visual stimuli degradation on cognitive workload. Approach. We investigated the subjective assessment, event-related potentials (ERPs) as well as electroencephalogram (EEG) as measures of cognitive workload. Main results. These experiments confirm that degradation of visual stimuli increases cognitive workload as assessed by subjective NASA task load index and confirmed by the observed P300 amplitude attenuation. Furthermore, the single-trial multi-level classification using features extracted from ERPs and EEG is found to be promising. Specifically, the adopted single-trial oscillatory EEG/ERP detection method achieved an average accuracy of 85% for discriminating 4 workload levels. Additionally, we found from the spatial patterns obtained from EEG signals that the frontal parts carry information that can be used for differentiating workload levels. Significance. Our results show that visual stimuli can modulate cognitive workload, and the modulation can be measured by the single trial EEG/ERP detection method.

Automatic Identification of Artifact-Related Independent Components for Artifact Removal in EEG Recordings.

PubMed

Zou, Yuan; Nathan, Viswam; Jafari, Roozbeh

2016-01-01

Electroencephalography (EEG) is the recording of electrical activity produced by the firing of neurons within the brain. These activities can be decoded by signal processing techniques. However, EEG recordings are always contaminated with artifacts which hinder the decoding process. Therefore, identifying and removing artifacts is an important step. Researchers often clean EEG recordings with assistance from independent component analysis (ICA), since it can decompose EEG recordings into a number of artifact-related and event-related potential (ERP)-related independent components. However, existing ICA-based artifact identification strategies mostly restrict themselves to a subset of artifacts, e.g., identifying eye movement artifacts only, and have not been shown to reliably identify artifacts caused by nonbiological origins like high-impedance electrodes. In this paper, we propose an automatic algorithm for the identification of general artifacts. The proposed algorithm consists of two parts: 1) an event-related feature-based clustering algorithm used to identify artifacts which have physiological origins; and 2) the electrode-scalp impedance information employed for identifying nonbiological artifacts. The results on EEG data collected from ten subjects show that our algorithm can effectively detect, separate, and remove both physiological and nonbiological artifacts. Qualitative evaluation of the reconstructed EEG signals demonstrates that our proposed method can effectively enhance the signal quality, especially the quality of ERPs, even for those that barely display ERPs in the raw EEG. The performance results also show that our proposed method can effectively identify artifacts and subsequently enhance the classification accuracies compared to four commonly used automatic artifact removal methods.

Automatic Identification of Artifact-related Independent Components for Artifact Removal in EEG Recordings

PubMed Central

Zou, Yuan; Nathan, Viswam; Jafari, Roozbeh

2017-01-01

Electroencephalography (EEG) is the recording of electrical activity produced by the firing of neurons within the brain. These activities can be decoded by signal processing techniques. However, EEG recordings are always contaminated with artifacts which hinder the decoding process. Therefore, identifying and removing artifacts is an important step. Researchers often clean EEG recordings with assistance from Independent Component Analysis (ICA), since it can decompose EEG recordings into a number of artifact-related and event related potential (ERP)-related independent components (ICs). However, existing ICA-based artifact identification strategies mostly restrict themselves to a subset of artifacts, e.g. identifying eye movement artifacts only, and have not been shown to reliably identify artifacts caused by non-biological origins like high-impedance electrodes. In this paper, we propose an automatic algorithm for the identification of general artifacts. The proposed algorithm consists of two parts: 1) an event-related feature based clustering algorithm used to identify artifacts which have physiological origins and 2) the electrode-scalp impedance information employed for identifying non-biological artifacts. The results on EEG data collected from 10 subjects show that our algorithm can effectively detect, separate, and remove both physiological and non-biological artifacts. Qualitative evaluation of the reconstructed EEG signals demonstrates that our proposed method can effectively enhance the signal quality, especially the quality of ERPs, even for those that barely display ERPs in the raw EEG. The performance results also show that our proposed method can effectively identify artifacts and subsequently enhance the classification accuracies compared to four commonly used automatic artifact removal methods. PMID:25415992

A novel hydrogel electrolyte extender for rapid application of EEG sensors and extended recordings.

PubMed

Kleffner-Canucci, Killian; Luu, Phan; Naleway, John; Tucker, Don M

2012-04-30

Dense-array EEG recordings are now commonplace in research and gaining acceptance in clinical settings. Application of many sensors with traditional electrolytes is time consuming. Saline electrolytes can be used to minimize application time but recording duration is limited due to evaporation. In the present study, we evaluate a NIPAm (N-isopropyl acrylamide:acrylic acid) base electrolyte extender for use with saline electrolytes. Sensor-scalp impedances and EEG data quality acquired with the electrolyte extender are compared with those obtained for saline and an EEG electrolyte commonly used in clinical exams (Elefix). The results show that when used in conjunction with saline, electrode-scalp impedances and data across the EEG spectrum are comparable with those obtained using Elefix EEG paste. When used in conjunction with saline, the electrolyte extender permits rapid application of dense-sensor arrays and stable, high-quality EEG data to be obtained for at least 4.5 h. This is an enabling technology that will make benefits of dense-array EEG recordings practical for clinical applications. Copyright © 2011 Elsevier B.V. All rights reserved.

Automated Identification of Abnormal Adult EEGs

PubMed Central

López, S.; Suarez, G.; Jungreis, D.; Obeid, I.; Picone, J.

2016-01-01

The interpretation of electroencephalograms (EEGs) is a process that is still dependent on the subjective analysis of the examiners. Though interrater agreement on critical events such as seizures is high, it is much lower on subtler events (e.g., when there are benign variants). The process used by an expert to interpret an EEG is quite subjective and hard to replicate by machine. The performance of machine learning technology is far from human performance. We have been developing an interpretation system, AutoEEG, with a goal of exceeding human performance on this task. In this work, we are focusing on one of the early decisions made in this process – whether an EEG is normal or abnormal. We explore two baseline classification algorithms: k-Nearest Neighbor (kNN) and Random Forest Ensemble Learning (RF). A subset of the TUH EEG Corpus was used to evaluate performance. Principal Components Analysis (PCA) was used to reduce the dimensionality of the data. kNN achieved a 41.8% detection error rate while RF achieved an error rate of 31.7%. These error rates are significantly lower than those obtained by random guessing based on priors (49.5%). The majority of the errors were related to misclassification of normal EEGs. PMID:27195311

An EEG Finger-Print of fMRI deep regional activation.

PubMed

Meir-Hasson, Yehudit; Kinreich, Sivan; Podlipsky, Ilana; Hendler, Talma; Intrator, Nathan

2014-11-15

This work introduces a general framework for producing an EEG Finger-Print (EFP) which can be used to predict specific brain activity as measured by fMRI at a given deep region. This new approach allows for improved EEG spatial resolution based on simultaneous fMRI activity measurements. Advanced signal processing and machine learning methods were applied on EEG data acquired simultaneously with fMRI during relaxation training guided by on-line continuous feedback on changing alpha/theta EEG measure. We focused on demonstrating improved EEG prediction of activation in sub-cortical regions such as the amygdala. Our analysis shows that a ridge regression model that is based on time/frequency representation of EEG data from a single electrode, can predict the amygdala related activity significantly better than a traditional theta/alpha activity sampled from the best electrode and about 1/3 of the times, significantly better than a linear combination of frequencies with a pre-defined delay. The far-reaching goal of our approach is to be able to reduce the need for fMRI scanning for probing specific sub-cortical regions such as the amygdala as the basis for brain-training procedures. On the other hand, activity in those regions can be characterized with higher temporal resolution than is obtained by fMRI alone thus revealing additional information about their processing mode. Copyright © 2013 Elsevier Inc. All rights reserved.

Efficacy and safety of a video-EEG protocol for genetic generalized epilepsies.

PubMed

De Marchi, Luciana Rodrigues; Corso, Jeana Torres; Zetehaku, Ana Carolina; Uchida, Carina Gonçalves Pedroso; Guaranha, Mirian Salvadori Bittar; Yacubian, Elza Márcia Targas

2017-05-01

Video-EEG has been used to characterize genetic generalized epilepsies (GGE). For best performance, sleep recording, photic stimulation, hyperventilation, and neuropsychological protocols are added to the monitoring. However, risks and benefits of these video-EEG protocols are not well established. The aim of this study was to analyze the efficacy and safety of a video-EEG neuropsychological protocol (VNPP) tailored for GGE and compare its value with that of routine EEG (R-EEG). We reviewed the VNPP and R-EEG of patients with GGE. We considered confirmation of the clinical suspicion of a GGE syndrome and characterization of reflex traits as benefits; and falls, injuries, psychiatric and behavioral changes, generalized tonic-clonic (GTC) seizures, and status epilepticus (SE) as the main risks of the VNPP. The VNPPs of 113 patients were analyzed. The most common epileptic syndrome was juvenile myoclonic epilepsy (85.8%). The protocol confirmed a GGE syndrome in 97 patients and 62 had seizures. Sleep recording had a provocative effect in 51.2% of patients. The second task that showed highest efficacy was praxis (39.3%) followed by hyperventilation (31.3%). Among the risks, 1.8% had GTC seizures and another 1.8%, SE. Eighteen percent of patients had persistently normal R-EEG, 72.2% of them had discharges during VNPP. Generalized tonic-clonic seizures, myoclonic status epilepticus, and repeated seizures were the main risks of VNPP present in 6 (5.31%) patients while there were no complications during R-EEG. The VNPP in GGE is a useful tool in diagnosis and characterization of reflex traits, and is a safe procedure. Its use might preclude multiple R-EEG exams. Copyright © 2017 Elsevier Inc. All rights reserved.

An Automatic Prediction of Epileptic Seizures Using Cloud Computing and Wireless Sensor Networks.

PubMed

Sareen, Sanjay; Sood, Sandeep K; Gupta, Sunil Kumar

2016-11-01

Epilepsy is one of the most common neurological disorders which is characterized by the spontaneous and unforeseeable occurrence of seizures. An automatic prediction of seizure can protect the patients from accidents and save their life. In this article, we proposed a mobile-based framework that automatically predict seizures using the information contained in electroencephalography (EEG) signals. The wireless sensor technology is used to capture the EEG signals of patients. The cloud-based services are used to collect and analyze the EEG data from the patient's mobile phone. The features from the EEG signal are extracted using the fast Walsh-Hadamard transform (FWHT). The Higher Order Spectral Analysis (HOSA) is applied to FWHT coefficients in order to select the features set relevant to normal, preictal and ictal states of seizure. We subsequently exploit the selected features as input to a k-means classifier to detect epileptic seizure states in a reasonable time. The performance of the proposed model is tested on Amazon EC2 cloud and compared in terms of execution time and accuracy. The findings show that with selected HOS based features, we were able to achieve a classification accuracy of 94.6 %.

Novel artefact removal algorithms for co-registered EEG/fMRI based on selective averaging and subtraction.

PubMed

de Munck, Jan C; van Houdt, Petra J; Gonçalves, Sónia I; van Wegen, Erwin; Ossenblok, Pauly P W

2013-01-01

a least squares procedure. The relevance of this approach is illustrated by determining the BCG artefacts in a data set consisting of 29 healthy subjects recorded in a 1.5 T scanner and 15 patients with epilepsy recorded in a 3 T scanner. Analysis of the relationship between artefact amplitude, duration and heartbeat interval shows that in 22% (1.5T data) to 30% (3T data) of the cases BCG artefacts show an overlap. The BCG artefacts of the EEG/fMRI data recorded on the 1.5T scanner show a small negative correlation between HBI and BCG amplitude. In conclusion, the proposed methodology provides a substantial improvement of the quality of the EEG signal without excessive computer power or additional hardware than standard EEG-compatible equipment. Copyright © 2012 Elsevier Inc. All rights reserved.

Wireless system for long-term EEG monitoring of absence epilepsy

NASA Astrophysics Data System (ADS)

Whitchurch, Ashwin K.; Ashok, B. H.; Kumaar, R. V.; Saurkesi, K.; Varadan, Vijay K.

2002-11-01

Absence epilepsy is a form of epilepsy common mostly in children. The most common manifestations of Absence epilepsy are staring and transient loss of responsiveness. Also, subtle motor activities may occur. Due to the subtle nature of these symptoms, episodes of absence epilepsy may often go unrecognized for long periods of time or be mistakenly attributed to attention deficit disorder or daydreaming. Spells of absence epilepsy may last about 10 seconds and occur hundreds of times each day. Patients have no recollections of the events that occurred during those seizures and will resume normal activity without any postictal symptoms. The EEG during such episodes of Absence epilepsy shows intermittent activity of 3 Hz generalized spike and wave complexes. As EEG is the only way of detecting such symptoms, it is required to monitor the EEG of the patient for a long time and thus remain only in bed. So, effectively the EEG is being monitored only when the patient is stationary. The wireless monitoring sys tem described in this paper aims at eliminating this constraint and enables the physicial to monitor the EEG when the patient resumes his normal activities. This approach could even help the doctor identify possible triggers of absence epilepsy.

Single-trial EEG RSVP classification using convolutional neural networks

NASA Astrophysics Data System (ADS)

Shamwell, Jared; Lee, Hyungtae; Kwon, Heesung; Marathe, Amar R.; Lawhern, Vernon; Nothwang, William

2016-05-01

Traditionally, Brain-Computer Interfaces (BCI) have been explored as a means to return function to paralyzed or otherwise debilitated individuals. An emerging use for BCIs is in human-autonomy sensor fusion where physiological data from healthy subjects is combined with machine-generated information to enhance the capabilities of artificial systems. While human-autonomy fusion of physiological data and computer vision have been shown to improve classification during visual search tasks, to date these approaches have relied on separately trained classification models for each modality. We aim to improve human-autonomy classification performance by developing a single framework that builds codependent models of human electroencephalograph (EEG) and image data to generate fused target estimates. As a first step, we developed a novel convolutional neural network (CNN) architecture and applied it to EEG recordings of subjects classifying target and non-target image presentations during a rapid serial visual presentation (RSVP) image triage task. The low signal-to-noise ratio (SNR) of EEG inherently limits the accuracy of single-trial classification and when combined with the high dimensionality of EEG recordings, extremely large training sets are needed to prevent overfitting and achieve accurate classification from raw EEG data. This paper explores a new deep CNN architecture for generalized multi-class, single-trial EEG classification across subjects. We compare classification performance from the generalized CNN architecture trained across all subjects to the individualized XDAWN, HDCA, and CSP neural classifiers which are trained and tested on single subjects. Preliminary results show that our CNN meets and slightly exceeds the performance of the other classifiers despite being trained across subjects.

A close look at EEG in subacute sclerosing panencephalitis.

PubMed

Demir, Nurhak; Cokar, Ozlem; Bolukbasi, Feray; Demirbilek, Veysi; Yapici, Zuhal; Yalcinkaya, Cengiz; Direskeneli, Guher Saruhan; Yentur, Sibel; Onal, Emel; Yilmaz, Gulden; Dervent, Aysin

2013-08-01

To define atypical clinical and EEG features of patients with subacute sclerosing panencephalitis that may require an overview of differential diagnosis. A total of 66 EEGs belonging to 53 (17 females and 36 males) consecutive patients with serologically confirmed subacute sclerosing panencephalitis were included in this study. Patient files and EEG data were evaluated retrospectively. EEGs included in the study were sleep-waking EEGs and/or sleep-waking video-EEG records with at least 2 hours duration. Cranial MRIs of the patients taken 2 months before or after the EEG records were included. Age range at the onset of the disease was 15 to 192 months (mean age: 80.02 months). Epilepsy was diagnosed in 21 (43%) patients. Among epileptic seizures excluding myoclonic jerks, generalized tonic-clonic type constituted the majority (58%). Tonic seizures were documented during the video-EEG recordings in four patients. Epileptogenic activities were found in 56 (83%) EEG recordings. They were localized mainly in frontal (58%), posterior temporal, parietal, occipital (26%), and centrotemporal (8%) regions. Multiple foci were detected in 26 recordings (39%). Epileptiform activities in the 39 (59%) EEGs appeared as unilateral or bilateral diffuse paroxysmal discharges. Recognition of uncommon clinical and EEG findings of subacute sclerosing panencephalitis, especially in countries where subacute sclerosing panencephalitis has not been eliminated yet, could be helpful in prevention of misdiagnosis and delay in the management of improvable conditions.

Integrating EEG and fMRI in epilepsy.

PubMed

Formaggio, Emanuela; Storti, Silvia Francesca; Bertoldo, Alessandra; Manganotti, Paolo; Fiaschi, Antonio; Toffolo, Gianna Maria

2011-02-14

Integrating electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) studies enables to non-invasively investigate human brain function and to find the direct correlation of these two important measures of brain activity. Presurgical evaluation of patients with epilepsy is one of the areas where EEG and fMRI integration has considerable clinical relevance for localizing the brain regions generating interictal epileptiform activity. The conventional analysis of EEG-fMRI data is based on the visual identification of the interictal epileptiform discharges (IEDs) on scalp EEG. The convolution of these EEG events, represented as stick functions, with a model of the fMRI response, i.e. the hemodynamic response function, provides the regressor for general linear model (GLM) analysis of fMRI data. However, the conventional analysis is not automatic and suffers of some subjectivity in IEDs classification. Here, we present an easy-to-use and automatic approach for combined EEG-fMRI analysis able to improve IEDs identification based on Independent Component Analysis and wavelet analysis. EEG signal due to IED is reconstructed and its wavelet power is used as a regressor in GLM. The method was validated on simulated data and then applied on real data set consisting of 2 normal subjects and 5 patients with partial epilepsy. In all continuous EEG-fMRI recording sessions a good quality EEG was obtained allowing the detection of spontaneous IEDs and the analysis of the related BOLD activation. The main clinical finding in EEG-fMRI studies of patients with partial epilepsy is that focal interictal slow-wave activity was invariably associated with increased focal BOLD responses in a spatially related brain area. Our study extends current knowledge on epileptic foci localization and confirms previous reports suggesting that BOLD activation associated with slow activity might have a role in localizing the epileptogenic region even in the absence of clear

Standardized Computer-based Organized Reporting of EEG: SCORE

PubMed Central

Beniczky, Sándor; Aurlien, Harald; Brøgger, Jan C; Fuglsang-Frederiksen, Anders; Martins-da-Silva, António; Trinka, Eugen; Visser, Gerhard; Rubboli, Guido; Hjalgrim, Helle; Stefan, Hermann; Rosén, Ingmar; Zarubova, Jana; Dobesberger, Judith; Alving, Jørgen; Andersen, Kjeld V; Fabricius, Martin; Atkins, Mary D; Neufeld, Miri; Plouin, Perrine; Marusic, Petr; Pressler, Ronit; Mameniskiene, Ruta; Hopfengärtner, Rüdiger; Emde Boas, Walter; Wolf, Peter

2013-01-01

The electroencephalography (EEG) signal has a high complexity, and the process of extracting clinically relevant features is achieved by visual analysis of the recordings. The interobserver agreement in EEG interpretation is only moderate. This is partly due to the method of reporting the findings in free-text format. The purpose of our endeavor was to create a computer-based system for EEG assessment and reporting, where the physicians would construct the reports by choosing from predefined elements for each relevant EEG feature, as well as the clinical phenomena (for video-EEG recordings). A working group of EEG experts took part in consensus workshops in Dianalund, Denmark, in 2010 and 2011. The faculty was approved by the Commission on European Affairs of the International League Against Epilepsy (ILAE). The working group produced a consensus proposal that went through a pan-European review process, organized by the European Chapter of the International Federation of Clinical Neurophysiology. The Standardised Computer-based Organised Reporting of EEG (SCORE) software was constructed based on the terms and features of the consensus statement and it was tested in the clinical practice. The main elements of SCORE are the following: personal data of the patient, referral data, recording conditions, modulators, background activity, drowsiness and sleep, interictal findings, “episodes” (clinical or subclinical events), physiologic patterns, patterns of uncertain significance, artifacts, polygraphic channels, and diagnostic significance. The following specific aspects of the neonatal EEGs are scored: alertness, temporal organization, and spatial organization. For each EEG finding, relevant features are scored using predefined terms. Definitions are provided for all EEG terms and features. SCORE can potentially improve the quality of EEG assessment and reporting; it will help incorporate the results of computer-assisted analysis into the report, it will make

Electrical source localization by LORETA in patients with epilepsy: Confirmation by postoperative MRI.

PubMed