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Automatic seizure detection based on imaged-EEG signals through fully convolutional networks
2020
Scientific Reports
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AbstractSeizure detection is a routine process in epilepsy units requiring manual intervention of well-trained specialists. This process could be extensive, inefficient and time-consuming, especially for long term recordings. We proposed an automatic method to detect epileptic seizures using an imaged-EEG representation of brain signals. To accomplish this, we analyzed EEG signals from two different datasets: the CHB-MIT Scalp EEG database and the EPILEPSIAE project that includes scalp and
doi:10.1038/s41598-020-78784-3
pmid:33311533
fatcat:tgigm3ldybfs7k4akigcow6zge
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... cranial recordings. We used fully convolutional neural networks to automatically detect seizures. For our best model, we reached average accuracy and specificity values of 99.3% and 99.6%, respectively, for the CHB-MIT dataset, and corresponding values of 98.0% and 98.3% for the EPILEPSIAE patients. For these patients, the inclusion of intracranial electrodes together with scalp ones increased the average accuracy and specificity values to 99.6% and 58.3%, respectively. Regarding the other metrics, our best model reached average precision of 62.7%, recall of 58.3%, F-measure of 59.0% and AP of 54.5% on the CHB-MIT recordings, and comparatively lowers performances for the EPILEPSIAE dataset. For both databases, the number of false alarms per hour reached values less than 0.5/h for 92% of the CHB-MIT patients and less than 1.0/h for 80% of the EPILEPSIAE patients. Compared to recent studies, our lightweight approach does not need any estimation of pre-selected features and demonstrates high performances with promising possibilities for the introduction of such automatic methods in the clinical practice.
Fundamental Dynamical Modes Underlying Human Brain Synchronization
2012
Computational and Mathematical Methods in Medicine
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Little is known about the long-term dynamics of widely interacting cortical and subcortical networks during the wake-sleep cycle. Using large-scale intracranial recordings of epileptic patients during seizure-free periods, we investigated local- and long-range synchronization between multiple brain regions over several days. For such high-dimensional data, summary information is required for understanding and modelling the underlying dynamics. Here, we suggest that a compact yet useful
doi:10.1155/2012/912729
pmid:22811753
pmcid:PMC3395243
fatcat:vpqsnnn3jbaqjiihnhiq4sk5oe
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... ation is given by a state space based on the first principal components. Using this representation, we report, with a remarkable similarity across the patients with different locations of electrode placement, that the seemingly complex patterns of brain synchrony during the wake-sleep cycle can be represented by a small number of characteristic dynamic modes. In this space, transitions between behavioral states occur through specific trajectories from one mode to another. These findings suggest that, at a coarse level of temporal resolution, the different brain states are correlated with several dominant synchrony patterns which are successively activated across wake-sleep states.
Pathologic electrographic changes after experimental traumatic brain injury
2016
Epilepsia
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Objective: To investigate possible electroencephalography (EEG) correlates of epileptogenesis after traumatic brain injury (TBI) using the fluid percussion model. Methods: Experiments were conducted on adult 2-to 4-month-old male Sprague-Dawley rats. Two groups of animals were studied: (1) the TBI group with depth and screw electrodes implanted immediately after the fluid percussion injury (FPI) procedure, and (2) a naive age-matched control group with the same electrode implantation montage.
doi:10.1111/epi.13359
pmid:27012461
pmcid:PMC5081251
fatcat:3brbsbgzpngmlnauapu3jo7bmy
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... irs of tungsten microelectrodes (50 lm outer diameter) and screw electrodes were implanted in neocortex inside the TBI core, areas adjacent to TBI, and remote areas. EEG activity, recorded on the day of FPI, and continuously for 2 weeks, was analyzed for possible electrographic biomarkers of epileptogenesis. Video-EEG monitoring was also performed continuously in the TBI group to capture electrographic and behavioral seizures until the caps came off (28-189 days), and for 1 week, at 2, 3, and 6 months of age, in the control group. Results: Pathologic high-frequency oscillations (pHFOs) with a central frequency between 100 and 600 Hz, were recorded from microelectrodes, beginning during the first two post-FPI weeks, in 7 of 12 animals in the TBI group (58%) and never in the controls. pHFOs only occurred in cortical areas within or adjacent to the TBI core. These were associated with synchronous multiunit discharges and popSpikes, duration 15-40 msec. Repetitive pHFOs and EEG spikes (rHFOSs) formed paroxysmal activity, with a unique arcuate pattern, in the frequency band 10-16 Hz in the same areas as isolated pHFOs, and these events were also recorded by screw electrodes. Although loss of caps prevented long-term recordings from all rats, pHFOs and rHFOSs occurred during the first 2 weeks in all four animals that later developed seizures, and none of the rats without these events developed late seizures. Significance: pHFOs, similar to those associated with epileptogenesis in the status rat model of epilepsy, may also reflect epileptogenesis after FPI. rHFOSs could be noninvasive biomarkers of epileptogenesis.
Assist-As-Needed Exoskeleton for Hand Joint Rehabilitation Based on Muscle Effort Detection
2021
Sensors
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Robotic-assisted systems have gained significant traction in post-stroke therapies to support rehabilitation, since these systems can provide high-intensity and high-frequency treatment while allowing accurate motion-control over the patient's progress. In this paper, we tackle how to provide active support through a robotic-assisted exoskeleton by developing a novel closed-loop architecture that continually measures electromyographic signals (EMG), in order to adjust the assistance given by
doi:10.3390/s21134372
pmid:34206714
fatcat:oeyec32sarcvnjsrfdcbw4ilku
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... exoskeleton. We used EMG signals acquired from four patients with post-stroke hand impairments for training machine learning models used to characterize muscle effort by classifying three muscular condition levels based on contraction strength, co-activation, and muscular activation measurements. The proposed closed-loop system takes into account the EMG muscle effort to modulate the exoskeleton velocity during the rehabilitation therapy. Experimental results indicate the maximum variation on velocity was 0.7 mm/s, while the proposed control system effectively modulated the movements of the exoskeleton based on the EMG readings, keeping a reference tracking error <5%.
Human Gamma Oscillations during Slow Wave Sleep
2012
PLoS ONE
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Neocortical local field potentials have shown that gamma oscillations occur spontaneously during slow-wave sleep (SWS). At the macroscopic EEG level in the human brain, no evidences were reported so far. In this study, by using simultaneous scalp and intracranial EEG recordings in 20 epileptic subjects, we examined gamma oscillations in cerebral cortex during SWS. We report that gamma oscillations in low (30-50 Hz) and high (60-120 Hz) frequency bands recurrently emerged in all investigated
doi:10.1371/journal.pone.0033477
pmid:22496749
pmcid:PMC3319559
fatcat:2slmpafor5dszh475fdl6tepiy
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... ons and their amplitudes coincided with specific phases of the cortical slow wave. In most of the cases, multiple oscillatory bursts in different frequency bands from 30 to 120 Hz were correlated with positive peaks of scalp slow waves ("IN-phase" pattern), confirming previous animal findings. In addition, we report another gamma pattern that appears preferentially during the negative phase of the slow wave ("ANTI-phase" pattern). This new pattern presented dominant peaks in the high gamma range and was preferentially expressed in the temporal cortex. Finally, we found that the spatial coherence between cortical sites exhibiting gamma activities was local and fell off quickly when computed between distant sites. Overall, these results provide the first human evidences that gamma oscillations can be observed in macroscopic EEG recordings during sleep. They support the concept that these high-frequency activities might be associated with phasic increases of neural activity during slow oscillations. Such patterned activity in the sleeping brain could play a role in off-line processing of cortical networks.
Lista actualizada y nuevos registros de las algas rojas (Rhodophyta) del litoral de Michoacán, México
2020
Revista Mexicana de Biodiversidad
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of red algae (Rhodophyta) from the coast of Michoacán, Mexico Resumen Se hizo una investigación bibliográfica de algas rojas registradas para la costa de Michoacán, México. ...
Revista Mexicana de Biodiversidad 91 (2020): e913353 Taxonomía y sistemática Lista actualizada y nuevos registros de las algas rojas (Rhodophyta) del litoral de Michoacán, México Updated list and new records ...
En el caso del litoral de Oaxaca, Bastida-Zavala et al. (2013) registraron 149 especies de algas rojas para esa región. ...
doi:10.22201/ib.20078706e.2020.91.3353
fatcat:c3lsneisxfezrh3dgdvqu7iemy
Update on the mechanisms and roles of high-frequency oscillations in seizures and epileptic disorders
2017
Epilepsia
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Alvarado-Rojas et al. 92 demonstrated that different ripple types have a considerable overlap in spectral frequency despite distinct dynamic changes in inhibition and excitation during interictal and preictal ...
doi:10.1111/epi.13830
pmid:28681378
pmcid:PMC5554080
fatcat:g4yquoykwfe45j7kyrtd2dnmay
Single-unit activities during epileptic discharges in the human hippocampal formation
2013
Frontiers in Computational Neuroscience
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ACKNOWLEDGMENTS Catalina Alvarado-Rojas was supported by the Administrative Department for Science, Technology and Innovation (COLCIENCIAS), Colombia. ...
doi:10.3389/fncom.2013.00140
pmid:24151464
pmcid:PMC3799238
fatcat:pdln5sjepbdinkfns6rsdxvniy
Different mechanisms of ripple-like oscillations in the human epileptic subiculum
2014
Annals of Neurology
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Transient high-frequency oscillations (150-600 Hz) in local field potential generated by human hippocampal and parahippocampal areas have been related to both physiological and pathological processes. The cellular basis and effects of normal and abnormal forms of high-frequency oscillations (HFO) has been controversial. Here, we searched for HFOs in slices of the subiculum prepared from human hippocampal tissue resected for treatment of pharmacoresistant epilepsy. HFOs occurred spontaneously in
doi:10.1002/ana.24324
pmid:25448920
pmcid:PMC4409108
fatcat:weo76g4vnfdkhnuf5vewk6gp4e
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... extracellular field potentials during interictal discharges (IID) and also during pharmacologically induced preictal discharges (PID) preceding ictal-like events. While most of these events might be considered pathological since they invaded the fast ripple band (>250 Hz), others were spectrally similar to physiological ripples (150-250 Hz). Do similar cellular mechanisms underly IID-ripples and PID-ripples? Are ripple-like oscillations a valid proxy of epileptogenesis in human TLE? With combined intra-or juxta-cellular and extracellular recordings, we showed that, despite overlapping spectral components, ripple-like IID and PID oscillations were associated with different cellular and synaptic mechanisms. IID-ripples were associated with rhythmic GABAergic and glutamatergic synaptic potentials with moderate neuronal firing. In contrast, PID-ripples were associated with depolarizing synaptic inputs frequently reaching the threshold for bursting in most cells. Thus ripple-like oscillations (100-250 Hz) in the human epileptic hippocampus are associated with different mechanisms for synchrony reflecting distinct dynamic changes in inhibition and excitation during interictal and pre-ictal states. CA
RIPPLELAB: A Comprehensive Application for the Detection, Analysis and Classification of High Frequency Oscillations in Electroencephalographic Signals
2016
PLoS ONE
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High Frequency Oscillations (HFOs) in the brain have been associated with different physiological and pathological processes. In epilepsy, HFOs might reflect a mechanism of epileptic phenomena, serving as a biomarker of epileptogenesis and epileptogenicity. Despite the valuable information provided by HFOs, their correct identification is a challenging task. A comprehensive application, RIPPLELAB, was developed to facilitate the analysis of HFOs. RIPPLELAB provides a wide range of tools for
doi:10.1371/journal.pone.0158276
pmid:27341033
pmcid:PMC4920418
fatcat:hy7ron4wbzek7mbzeksa6aaip4
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... manual and automatic detection and visual validation; all of them are accessible from an intuitive graphical user interface. Four methods for automated detection-as well as several options for visualization and validation of detected events-were implemented and integrated in the application. Analysis of multiple files and channels is possible, and new options can be added by users. All features and capabilities implemented in RIPPLELAB for automatic detection were tested through the analysis of simulated signals and intracranial EEG recordings from epileptic patients (n = 16; 3,471 analyzed hours). Visual validation was also tested, and detected events were classified into different categories. Unlike other available software packages for EEG analysis, RIPPLELAB uniquely provides the appropriate graphical and algorithmic environment for HFOs detection (visual and automatic) and validation, in such a way that the power of elaborated detection methods are available to a wide range of users (experts and nonexperts) through the use of this application. We believe that this open-source tool will facilitate and promote the collaboration between clinical and research centers working on the HFOs field. The tool is available under public license and is accessible through a dedicated web site.
Angiolipoleiomioma uterino: presentación de un caso y revisión de la literatura
2016
Revista Colombiana de Obstetricia y Ginecología
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Masa en la línea media anterior al útero, de contornos bien definidos, aspecto heterogéneo, con densidad de grasa en su interior (flecha roja) Posteriormente se realiza control a la paciente donde se evalúa ...
doi:10.18597/rcog.379
fatcat:3sjmx3vmabc2dpejlek2q4mefu
Teaching English Literature in Costa Rican Experimental Bilingual High Schools: EFL Teachers' Academic Training
2017
Revista Electrónica de Investigación Educativa
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Neurodevelopmental effects in children associated with exposure to organophosphate pesticides: A systematic review
2013
Neurotoxicology
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Individuals with wildtype PON1 (RR) have almost three times the PON activity as those with the Q/Q variant and about 1.5 times more activity than the R/Q variant (Rojas-García et al., 2005) . ...
doi:10.1016/j.neuro.2013.09.003
pmid:24121005
pmcid:PMC3899350
fatcat:d5wldumvszgevhtc2h5gypi3sa
The EPILEPSIAE database: An extensive electroencephalography database of epilepsy patients
2012
Epilepsia
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From the very beginning the seizure prediction community faced problems concerning evaluation, standardization, and reproducibility of its studies. One of the main reasons for these shortcomings was the lack of access to high-quality long-term electroencephalography (EEG) data. In this article we present the EPILEPSIAE database, which was made publicly available in 2012. We illustrate its content and scope. The EPILEPSIAE database provides long-term EEG recordings of 275 patients as well as
doi:10.1111/j.1528-1167.2012.03564.x
pmid:22738131
fatcat:e66xdkrywbhnldcyqd32oyosci
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... nsive metadata and standardized annotation of the data sets. It will adhere to the current standards in the field of prediction and facilitate reproducibility and comparison of those studies. Beyond seizure prediction, it may also be of considerable benefit for studies focusing on seizure detection, basic neurophysiology, and other fields.
Ictal onset patterns of local field potentials, high frequency oscillations, and unit activity in human mesial temporal lobe epilepsy
2015
Epilepsia
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Objective-To characterize local field potentials, high frequency oscillations, and single unit firing patterns in microelectrode recordings of human limbic onset seizures. Methods-Wide bandwidth local field potential recordings were acquired from microelectrodes implanted in mesial temporal structures during spontaneous seizures from six patients with mesial temporal lobe epilepsy. Results-In the seizure onset zone, distinct epileptiform discharges were evident in the local field potential
doi:10.1111/epi.13251
pmid:26611159
pmcid:PMC4862409
fatcat:pazhxwqnpjg6lnansjcsppd5ya
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... to the time of seizure onset in the intracranial EEG. In all three seizures with hypersynchronous (HYP) seizure onset, fast ripples with incrementally increasing power accompanied epileptiform discharges during the transition to the ictal state (p < 0.01). In a single low voltage fast (LVF) onset seizure a triad of evolving HYP LFP discharges, increased single unit activity, and fast ripples of incrementally increasing power were identified ~20 s prior to seizure onset (p < 0.01). In addition, incrementally increasing fast ripples occurred after seizure onset just prior to the transition to LVF activity (p < 0.01). HYP onset was associated with an increase in fast ripple and ripple rate (p < 0.05) and commonly each HYP discharge had a superimposed ripple followed by a fast ripple. Putative excitatory and inhibitory single units could be distinguished
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