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Intracranial EEG

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https://www.readbyqxmd.com/read/28337411/physiological-and-pathological-high-frequency-oscillations-have-distinct-sleep-homeostatic-properties
#1
Nicolás von Ellenrieder, François Dubeau, Jean Gotman, Birgit Frauscher
OBJECTIVE: The stage of sleep is a known modulator of high-frequency oscillations (HFOs). For instance, high amplitude slow waves during NREM sleep and the subtypes of REM sleep were shown to contribute to a better separation between physiological and pathological HFOs. This study investigated rates and spatial spread of the different HFO types (physiological and pathological ripples in the 80-250 Hz frequency band, and fast ripples above 250 Hz) depending on time spent in sleep across the different sleep cycles...
2017: NeuroImage: Clinical
https://www.readbyqxmd.com/read/28328980/early-biomarkers-of-brain-injury-and-cerebral-hypo-and-hyperoxia-in-the-safeboosc-ii-trial
#2
Anne M Plomgaard, Thomas Alderliesten, Topun Austin, Frank van Bel, Manon Benders, Olivier Claris, Eugene Dempsey, Monica Fumagalli, Christian Gluud, Cornelia Hagmann, Simon Hyttel-Sorensen, Petra Lemmers, Wim van Oeveren, Adelina Pellicer, Tue H Petersen, Gerhard Pichler, Per Winkel, Gorm Greisen
BACKGROUND: The randomized clinical trial, SafeBoosC II, examined the effect of monitoring of cerebral oxygenation by near-infrared spectroscopy combined with a guideline on treatment when cerebral oxygenation was out of the target range. Data on cerebral oxygenation was collected in both the intervention and the control group. The primary outcome was the reduction in the burden of cerebral hypo- and hyperoxia between the two groups. In this study we describe the associations between the burden of cerebral hypo- and hyperoxia, regardless of allocation to intervention or control group, and the biomarkers of brain injury from birth till term equivalent age that was collected as secondary and explorative outcomes in the SafeBoosC II trial...
2017: PloS One
https://www.readbyqxmd.com/read/28327467/automated-detection-of-epileptic-ripples-in-meg-using-beamformer-based-virtual-sensors
#3
Carolina Migliorelli, Joan Alonso, Sergio Romero, Rafal Nowak, Antonio Russi, Miguel Mananas
OBJECTIVE: In epilepsy, high-frequency oscillations (HFOs) are considered events highly linked to the seizure onset zone (SOZ). The detection of HFOs in noninvasive signals such as scalp EEG and MEG is still a challenging task. The aim of this study was to automatize the detection of ripples in MEG signals reducing the high-frequency noise using beamformer-based virtual sensors (VS) and applying an automatic procedure exploring the time-frequency content of the detected events. APPROACH: 200 seconds of MEG signals and simultaneous iEEG were selected in nine patients with refractory epilepsy...
March 22, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28324954/hardware-friendly-seizure-detection-with-a-boosted-ensemble-of-shallow-decision-trees
#4
Mahsa Shoaran, Masoud Farivar, Azita Emami
Efficient on-chip learning is becoming an essential element of implantable biomedical devices. Despite a substantial literature on automated seizure detection algorithms, hardware-friendly implementation of such techniques is not sufficiently addressed. In this paper, we propose to employ a gradientboosted ensemble of decision trees to achieve a reasonable trade-off between detection accuracy and implementation cost. Combined with the proposed feature extraction model, we show that these classifiers quickly become competitive with more complex learning models previously proposed for hardware implementation, with only a small number of low-depth (d <; 4) "shallow" trees...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28324680/somatic-complications-of-epilepsy-surgery-over-25-years-at-a-single-center
#5
Inuka K Gooneratne, Shahidul Mannan, Jane de Tisi, Juan C Gonzalez, Andrew W McEvoy, Anna Miserocchi, Beate Diehl, Tim Wehner, Gail S Bell, Josemir W Sander, John S Duncan
INTRODUCTION: Epilepsy surgery is an effective treatment for refractory focal epilepsy. Risks of surgery need to be considered when advising individuals of treatment options. We describe the frequency and nature of physical adverse events associated with epilepsy surgery in a single center. MATERIAL AND METHODS: We reviewed the prospectively maintained records of adults who underwent epilepsy surgery at our center between 1990 and 2014 to identify peri/postsurgical adverse events...
March 1, 2017: Epilepsy Research
https://www.readbyqxmd.com/read/28322026/objective-3d-surface-evaluation-of-intracranial-electrophysiologic-correlates-of-cerebral-glucose-metabolic-abnormalities-in-children-with-focal-epilepsy
#6
Jeong-Won Jeong, Eishi Asano, Vinod Kumar Pilli, Yasuo Nakai, Harry T Chugani, Csaba Juhász
To determine the spatial relationship between 2-deoxy-2[(18) F]fluoro-D-glucose (FDG) metabolic and intracranial electrophysiological abnormalities in children undergoing two-stage epilepsy surgery, statistical parametric mapping (SPM) was used to correlate hypo- and hypermetabolic cortical regions with ictal and interictal electrocorticography (ECoG) changes mapped onto the brain surface. Preoperative FDG-PET scans of 37 children with intractable epilepsy (31 with non-localizing MRI) were compared with age-matched pseudo-normal pediatric control PET data...
March 21, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28318128/proton-mr-spectroscopy-in-patients-with-nonlesional-insular-cortex-epilepsy-confirmed-by-invasive-eeg-recordings
#7
Yasmine Aitouche, Steve A Gibbs, Guillaume Gilbert, Olivier Boucher, Alain Bouthillier, Dang Khoa Nguyen
BACKGROUND AND PURPOSE: Recent studies suggest that a nonnegligible proportion of drug-resistant epilepsy surgery candidates have an epileptogenic zone that involves the insula. We aimed to examine the value of proton magnetic resonance spectroscopy ((1) H-MRS) in identifying patients with insular cortex epilepsy. METHODS: Patients with possible nonlesional drug-refractory insular epilepsy underwent a voxel-based (1) H-MRS study prior to an intracranial electroencephalographic (EEG) study...
March 20, 2017: Journal of Neuroimaging: Official Journal of the American Society of Neuroimaging
https://www.readbyqxmd.com/read/28303098/ielectrodes-a-comprehensive-open-source-toolbox-for-depth-and-subdural-grid-electrode-localization
#8
Alejandro O Blenkmann, Holly N Phillips, Juan P Princich, James B Rowe, Tristan A Bekinschtein, Carlos H Muravchik, Silvia Kochen
The localization of intracranial electrodes is a fundamental step in the analysis of invasive electroencephalography (EEG) recordings in research and clinical practice. The conclusions reached from the analysis of these recordings rely on the accuracy of electrode localization in relationship to brain anatomy. However, currently available techniques for localizing electrodes from magnetic resonance (MR) and/or computerized tomography (CT) images are time consuming and/or limited to particular electrode types or shapes...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28294306/the-hemodynamic-response-to-interictal-epileptic-discharges-localizes-the-seizure-onset-zone
#9
Hui Ming Khoo, Yongfu Hao, Nicolás von Ellenrieder, Natalja Zazubovits, Jeffery Hall, André Olivier, François Dubeau, Jean Gotman
OBJECTIVE: Intracranial electroencephalography (EEG), performed presurgically in patients with drug-resistant and difficult-to-localize focal epilepsy, samples only a small fraction of brain tissue and thus requires strong hypotheses regarding the possible localization of the epileptogenic zone. EEG/fMRI (functional magnetic resonance imaging), a noninvasive tool resulting in hemodynamic responses, could contribute to the generation of these hypotheses. This study assessed how these responses, despite their interictal origin, predict the seizure-onset zone (SOZ)...
March 15, 2017: Epilepsia
https://www.readbyqxmd.com/read/28279512/intracranial-video-eeg-monitoring-in-presurgical-evaluation-of-patients-with-refractory-epilepsy
#10
Marlena Hupalo, Rafal Wojcik, Dariusz J Jaskolski
OBJECTIVE: Reviewing our experience in intracranial video-EEG monitoring in the presurgical evaluation of patients with refractory epilepsy. METHODS: We report on 62 out of 202 (31%) patients with refractory epilepsy, who underwent a long term video-EEG monitoring (LTM). The epileptogenic zone (EZ) was localised either based on the results of LTM or after intracranial EEG recordings from depth, subdural or foramen ovale electrodes. The decision on the location of the electrodes was based upon semiology of the seizures, EEG findings and the lesions visualised in MRI brain scan...
March 2, 2017: Neurologia i Neurochirurgia Polska
https://www.readbyqxmd.com/read/28269702/predicting-seizures-from-local-field-potentials-recorded-via-intracortical-microelectrode-arrays
#11
Mehdi Aghagolzadeh, Leigh R Hochberg, Sydney S Cash, Wilson Truccolo
The need for new therapeutic interventions to treat pharmacologically resistant focal epileptic seizures has led recently to the development of closed-loop systems for seizure control. Once a seizure is predicted/detected by the system, electrical stimulation is delivered to prevent seizure initiation or spread. So far, seizure prediction/detection has been limited to tracking non-invasive electroencephalogram (EEG) or intracranial EEG (iEEG) signals. Here, we examine seizure prediction based on local field potentials (LFPs) from a small neocortical patch recorded via a 10×10 microelectrode array implanted in a patient with focal seizures...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268493/automatic-seizure-detection-using-correlation-integral-with-nonlinear-adaptive-denoising-and-kalman-filter
#12
Hongda Wang, Chiu-Sing Choy
The ability of correlation integral for automatic seizure detection using scalp EEG data has been re-examined in this paper. To facilitate the detection performance and overcome the shortcoming of correlation integral, nonlinear adaptive denoising and Kalman filter have been adopted for pre-processing and post-processing. The three-stage algorithm has achieved 84.6% sensitivity and 0.087/h false detection rate, which are comparable to many machine learning based methods, but at much lower computational cost...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28261083/automatic-and-precise-localization-and-cortical-labeling-of-subdural-and-depth-intracranial-electrodes
#13
Chaoyi Qin, Zheng Tan, Yali Pan, Yanyan Li, Lin Wang, Liankun Ren, Wenjing Zhou, Liang Wang
Object: Subdural or deep intracerebral electrodes are essential in order to precisely localize epileptic zone in patients with medically intractable epilepsy. Precise localization of the implanted electrodes is critical to clinical diagnosing and treatment as well as for scientific studies. In this study, we sought to automatically and precisely extract intracranial electrodes using pre-operative MRI and post-operative CT images. Method: The subdural and depth intracranial electrodes were readily detected using clustering-based segmentation...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28258840/increased-prognostic-accuracy-of-tbi-when-a-brain-electrical-activity-biomarker-is-added-to-loss-of-consciousness-loc
#14
Dallas Hack, J Stephen Huff, Kenneth Curley, Roseanne Naunheim, Samanwoy Ghosh Dastidar, Leslie S Prichep
BACKGROUND: Extremely high accuracy for predicting CT+ traumatic brain injury (TBI) using a quantitative EEG (QEEG) based multivariate classification algorithm was demonstrated in an independent validation trial, in Emergency Department (ED) patients, using an easy to use handheld device. This study compares the predictive power using that algorithm (which includes LOC and amnesia), to the predictive power of LOC alone or LOC plus traumatic amnesia. PARTICIPANTS: ED patients 18-85years presenting within 72h of closed head injury, with GSC 12-15, were study candidates...
February 20, 2017: American Journal of Emergency Medicine
https://www.readbyqxmd.com/read/28238858/automatic-detection-of-periods-of-slow-wave-sleep-based-on-intracranial-depth-electrode-recordings
#15
Chrystal M Reed, Kurtis G Birch, Jan Kamiński, Shannon Sullivan, Jeffrey M Chung, Adam N Mamelak, Ueli Rutishauser
BACKGROUND: An automated process for sleep staging based on intracranial EEG data alone is needed to facilitate research into the neural processes occurring during slow wave sleep (SWS). Current manual methods for sleep scoring require a full polysomnography (PSG) set-up, including electrooculography (EOG), electromyography (EMG), and scalp electroencephalography (EEG). This set-up can be technically difficult to place in the presence of intracranial EEG electrodes. There is thus a need for a method for sleep staging based on intracranial recordings alone...
February 24, 2017: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/28235654/is-burned-out-hippocampus-syndrome-a-distinct-electro-clinical-variant-of-mtle-hs-syndrome
#16
Pradeep P Nair, Ramshekhar N Menon, Ashalatha Radhakrishnan, Ajit Cherian, Mathew Abraham, George Vilanilam, C Kesavadas, Bejoy Thomas, Aley Alexander, Sanjeev V Thomas
AIM: 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). METHODS: 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...
February 21, 2017: Epilepsy & Behavior: E&B
https://www.readbyqxmd.com/read/28227963/predicting-seizures-from-local-field-potentials-recorded-via-intracortical-microelectrode-arrays
#17
Mehdi Aghagolzadeh, Leigh R Hochberg, Sydney S Cash, Wilson Truccolo, Mehdi Aghagolzadeh, Leigh R Hochberg, Sydney S Cash, Wilson Truccolo, Sydney S Cash, Wilson Truccolo, Mehdi Aghagolzadeh, Leigh R Hochberg
The need for new therapeutic interventions to treat pharmacologically resistant focal epileptic seizures has led recently to the development of closed-loop systems for seizure control. Once a seizure is predicted/detected by the system, electrical stimulation is delivered to prevent seizure initiation or spread. So far, seizure prediction/detection has been limited to tracking non-invasive electroencephalogram (EEG) or intracranial EEG (iEEG) signals. Here, we examine seizure prediction based on local field potentials (LFPs) from a small neocortical patch recorded via a 10×10 microelectrode array implanted in a patient with focal seizures...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226868/hardware-friendly-seizure-detection-with-a-boosted-ensemble-of-shallow-decision-trees
#18
Mahsa Shoaran, Masoud Farivar, Azita Emami, Mahsa Shoaran, Masoud Farivar, Azita Emami, Masoud Farivar, Azita Emami, Mahsa Shoaran
Efficient on-chip learning is becoming an essential element of implantable biomedical devices. Despite a substantial literature on automated seizure detection algorithms, hardware-friendly implementation of such techniques is not sufficiently addressed. In this paper, we propose to employ a gradientboosted ensemble of decision trees to achieve a reasonable trade-off between detection accuracy and implementation cost. Combined with the proposed feature extraction model, we show that these classifiers quickly become competitive with more complex learning models previously proposed for hardware implementation, with only a small number of low-depth (d <; 4) "shallow" trees...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226667/automatic-seizure-detection-using-correlation-integral-with-nonlinear-adaptive-denoising-and-kalman-filter
#19
Hongda Wang, Chiu-Sing Choy, Hongda Wang, Chiu-Sing Choy, Hongda Wang, Chiu-Sing Choy
The ability of correlation integral for automatic seizure detection using scalp EEG data has been re-examined in this paper. To facilitate the detection performance and overcome the shortcoming of correlation integral, nonlinear adaptive denoising and Kalman filter have been adopted for pre-processing and post-processing. The three-stage algorithm has achieved 84.6% sensitivity and 0.087/h false detection rate, which are comparable to many machine learning based methods, but at much lower computational cost...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28205340/predictive-modeling-of-eeg-time-series-for-evaluating-surgery-targets-in-epilepsy-patients
#20
Andreas Steimer, Michael Müller, Kaspar Schindler
During the last 20 years, predictive modeling in epilepsy research has largely been concerned with the prediction of seizure events, whereas the inference of effective brain targets for resective surgery has received surprisingly little attention. In this exploratory pilot study, we describe a distributional clustering framework for the modeling of multivariate time series and use it to predict the effects of brain surgery in epilepsy patients. By analyzing the intracranial EEG, we demonstrate how patients who became seizure free after surgery are clearly distinguished from those who did not...
February 16, 2017: Human Brain Mapping
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