Ictal time-irreversible intracranial EEG signals as markers of the epileptogenic zone.

PubMed

Schindler, Kaspar; Rummel, Christian; Andrzejak, Ralph G; Goodfellow, Marc; Zubler, Frédéric; Abela, Eugenio; Wiest, Roland; Pollo, Claudio; Steimer, Andreas; Gast, Heidemarie

2016-09-01

To show that time-irreversible EEG signals recorded with intracranial electrodes during seizures can serve as markers of the epileptogenic zone. We use the recently developed method of mapping time series into directed horizontal graphs (dHVG). Each node of the dHVG represents a time point in the original intracranial EEG (iEEG) signal. Statistically significant differences between the distributions of the nodes' number of input and output connections are used to detect time-irreversible iEEG signals. In 31 of 32 seizure recordings we found time-irreversible iEEG signals. The maximally time-irreversible signals always occurred during seizures, with highest probability in the middle of the first seizure half. These signals spanned a large range of frequencies and amplitudes but were all characterized by saw-tooth like shaped components. Brain regions removed from patients who became post-surgically seizure-free generated significantly larger time-irreversibilities than regions removed from patients who still had seizures after surgery. Our results corroborate that ictal time-irreversible iEEG signals can indeed serve as markers of the epileptogenic zone and can be efficiently detected and quantified in a time-resolved manner by dHVG based methods. Ictal time-irreversible EEG signals can help to improve pre-surgical evaluation in patients suffering from pharmaco-resistant epilepsies. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

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.

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

Rhythmic ictal nonclonic hand (RINCH) motions in temporal lobe epilepsy: invasive EEG findings, incidence, and lateralizing value.

PubMed

Kuba, Robert; Musilová, Klára; Vojvodič, Nikola; Tyrlíková, Ivana; Rektor, Ivan; Brázdil, Milan

2013-10-01

The main purpose of this retrospective analysis was to evaluate the incidence and lateralization value of rhythmic ictal nonclonic hand (RINCH) motions in patients with temporal lobe epilepsy (TLE), who were classified as Engel I at least 2 years after epilepsy surgery. We analyzed the distribution of ictal activity at the time of RINCH appearance in patients in whom RINCH motions were present during invasive EEG monitoring. A group of 120 patients was included in this study. In total, we reviewed 491 seizures: 277 seizures in patients with temporal lobe epilepsy (TLE) associated with hippocampal sclerosis (TLE-HS group) and 214 in TLE caused by other lesions (TLE-OTH group). We analyzed 29 patients (79 of the seizures) during invasive EEG monitoring. Fisher's exact test and binomial test were used for the statistical analysis. RINCH motions were observed in 24 out of 120 patients (20%) and in 48 out of 491 seizures (9.8%). There was no significant difference between the occurrence of RINCH motions in patients with TLE-HS and in patients with TLE-OTH, or between gender, right/left-sided TLE, and language dominant/nondominant TLE. RINCH motions were contralateral to the seizure onset in 83.3% of patients and 91.7% of seizures (p=0.0015; p<0.001, respectively). There were no differences in the lateralizing value of RINCH motions in patients with TLE-HS or TLE-OTH. We analyzed RINCH motions in 5 patients/7 seizures during invasive EEG. In all 7 seizures with RINCH motions, we observed the widespread activation of the temporal lobe (mesial and lateral, opercular and polar regions) contralateral to the side of RINCH motions. In all 7 seizures, we observed that at the time of RINCH motion onset, at least 1 explored region of the frontal lobe was affected by the ictal activity. In 3 seizures, we observed time-locked epileptic activation associated with the appearance of RINCH motions, i.e., in the orbitofrontal cortex in 2 seizures and in both the orbitofrontal cortex and

[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).

Presurgical evaluation for partial epilepsy: Relative contributions of chronic depth-electrode recordings versus FDG-PET and scalp-sphenoidal ictal EEG

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

Engel, J. Jr.; Henry, T.R.; Risinger, M.W.

1990-11-01

One hundred fifty-three patients with medically refractory partial epilepsy underwent chronic stereotactic depth-electrode EEG (SEEG) evaluations after being studied by positron emission tomography (PET) with 18F-fluorodeoxyglucose (FDG) and scalp-sphenoidal EEG telemetry. We carried out retrospective standardized reviews of local cerebral metabolism and scalp-sphenoidal ictal onsets to determine when SEEG recordings revealed additional useful information. FDG-PET localization was misleading in only 3 patients with temporal lobe SEEG ictal onsets for whom extratemporal or contralateral hypometabolism could be attributed to obvious nonepileptic structural defects. Two patients with predominantly temporal hypometabolism may have had frontal epileptogenic regions, but ultimate localization remains uncertain. Scalp-sphenoidalmore » ictal onsets were misleading in 5 patients. For 37 patients with congruent focal scalp-sphenoidal ictal onsets and temporal hypometabolic zones, SEEG recordings never demonstrated extratemporal or contralateral epileptogenic regions; however, 3 of these patients had nondiagnostic SEEG evaluations. The results of subsequent subdural grid recordings indicated that at least 1 of these patients may have been denied beneficial surgery as a result of an equivocal SEEG evaluation. Weighing risks and benefits, it is concluded that anterior temporal lobectomy is justified without chronic intracranial recording when specific criteria for focal scalp-sphenoidal ictal EEG onsets are met, localized hypometabolism predominantly involves the same temporal lobe, and no other conflicting information has been obtained from additional tests of focal functional deficit, structural imaging, or seizure semiology.« less

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

Beyond Epilepsy: How Can Quantitative Electroencephalography Improve Conventional Electroencephalography Findings? A Systematic Review of Comparative EEG Studies.

PubMed

Martins, Cassio Henrique Taques; Assunção, Catarina De Marchi

2018-01-01

It is a fundamental element in both research and clinical applications of electroencephalography to know the frequency composition of brain electrical activity. The quantitative analysis of brain electrical activity uses computer resources to evaluate the electroencephalography and allows quantification of the data. The contribution of the quantitative perspective is unique, since conventional electroencephalography based on the visual examination of the tracing is not as objective. A systematic review was performed on the MEDLINE database in October 2017. The authors independently analyzed the studies, by title and abstract, and selected articles that met the inclusion criteria: comparative studies, not older than 30 years, that compared the use of conventional electroencephalogram (EEG) with the use of quantitative electroencephalogram (QEEG) in the English language. One hundred twelve articles were automatically selected by the MEDLINE search engine, but only six met the above criteria. The review found that given a 95% confidence interval, QEEG had no statistically higher sensitivity than EEG in four of the six studies reviewed. However, these results must be viewed with appropriate caution, particularly as groups in between studies were not matched on important variables such as gender, age, type of illness, recovery stage, and treatment. The authors' findings in this systematic review are suggestive of the importance of QEEG as an auxiliary tool to traditional EEG, and as such, justifying further refinement, standardization, and eventually the future execution of a head-to-head prospective study on comparing the two methods.

Electroencephalography in Mesial Temporal Lobe Epilepsy: A Review

PubMed Central

Javidan, Manouchehr

2012-01-01

Electroencephalography (EEG) has an important role in the diagnosis and classification of epilepsy. It can provide information for predicting the response to antiseizure drugs and to identify the surgically remediable epilepsies. In temporal lobe epilepsy (TLE) seizures could originate in the medial or lateral neocortical temporal region, and many of these patients are refractory to medical treatment. However, majority of patients have had excellent results after surgery and this often relies on the EEG and magnetic resonance imaging (MRI) data in presurgical evaluation. If the scalp EEG data is insufficient or discordant, invasive EEG recording with placement of intracranial electrodes could identify the seizure focus prior to surgery. This paper highlights the general information regarding the use of EEG in epilepsy, EEG patterns resembling epileptiform discharges, and the interictal, ictal and postictal findings in mesial temporal lobe epilepsy using scalp and intracranial recordings prior to surgery. The utility of the automated seizure detection and computerized mathematical models for increasing yield of non-invasive localization is discussed. This paper also describes the sensitivity, specificity, and predictive value of EEG for seizure recurrence after withdrawal of medications following seizure freedom with medical and surgical therapy. PMID:22957235

Diagnostic Utility of Wireless Video-Electroencephalography in Unsedated Dogs.

PubMed

James, F M K; Cortez, M A; Monteith, G; Jokinen, T S; Sanders, S; Wielaender, F; Fischer, A; Lohi, H

2017-09-01

Poor agreement between observers on whether an unusual event is a seizure drives the need for a specific diagnostic tool provided by video-electroencephalography (video-EEG) in human pediatric epileptology. That successful classification of events would be positively associated with increasing EEG recording length and higher event frequency reported before video-EEG evaluation; that a novel wireless video-EEG technique would clarify whether unusual behavioral events were seizures in unsedated dogs. Eighty-one client-owned dogs of various breeds undergoing investigation of unusual behavioral events at 4 institutions. Retrospective case series: evaluation of wireless video-EEG recordings in unsedated dogs performed at 4 institutions. Electroencephalography achieved/excluded diagnosis of epilepsy in 58 dogs (72%); 25 dogs confirmed with epileptic seizures based on ictal/interictal epileptiform discharges, and 33 dogs with no EEG abnormalities associated with their target events. As reported frequency of the target events decreased (annually, monthly, weekly, daily, hourly, minutes, seconds), EEG was less likely to achieve diagnosis (P < 0.001). Every increase in event frequency increased the odds of achieving diagnosis by 2.315 (95% confidence interval: 1.36-4.34). EEG recording length (mean = 3.69 hours, range: 0.17-22.5) was not associated (P = 0.2) with the likelihood of achieving a diagnosis. Wireless video-EEG in unsedated dogs had a high success for diagnosis of unusual behavioral events. This technique offered a reliable clinical tool to investigate the epileptic origin of behavioral events in dogs. Copyright © 2017 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.

Probing interval timing with scalp-recorded electroencephalography (EEG).

PubMed

Ng, Kwun Kei; Penney, Trevor B

2014-01-01

Humans, and other animals, are able to easily learn the durations of events and the temporal relationships among them in spite of the absence of a dedicated sensory organ for time. This chapter summarizes the investigation of timing and time perception using scalp-recorded electroencephalography (EEG), a non-invasive technique that measures brain electrical potentials on a millisecond time scale. Over the past several decades, much has been learned about interval timing through the examination of the characteristic features of averaged EEG signals (i.e., event-related potentials, ERPs) elicited in timing paradigms. For example, the mismatch negativity (MMN) and omission potential (OP) have been used to study implicit and explicit timing, respectively, the P300 has been used to investigate temporal memory updating, and the contingent negative variation (CNV) has been used as an index of temporal decision making. In sum, EEG measures provide biomarkers of temporal processing that allow researchers to probe the cognitive and neural substrates underlying time perception.

Is routine electroencephalography (EEG) a useful biomarker for pharmacoresistant epilepsy?

PubMed

Steinhoff, Bernhard J; Scholly, Julia; Dentel, Christel; Staack, Anke Maren

2013-05-01

People with seizure disorders who have been treated at the Kork Epilepsy Center over a prolonged time period and who thus provide data concerning the chronic course of epilepsy were investigated in order to address the potential role of electroencephalography (EEG) as a biomarker for pharmacoresistant epilepsy. Clinical course and the corresponding findings from their first recorded EEG, their first EEG following appropriate treatment, and their last EEG were compared. Furthermore, we investigated if interictal epileptiform discharges (IEDs) differ in amplitude and morphology if recorded in long-term seizure-free patients. The early cessation of IEDs was a relatively good marker for a good prognosis, especially in idiopathic generalized epilepsies. However, persistent IEDs had no major impact on the long-term prognosis. We found no differences between IEDs in seizure-free patients or patients with ongoing seizures. Therefore, in our hands, routine EEG was not an appropriate biomarker for the prediction of pharmacoresistant epilepsy. Additional factors such as etiology and pathophysiology also need to be considered. Wiley Periodicals, Inc. © 2013 International League Against Epilepsy.

Regional Reductions in Sleep Electroencephalography Power in Obstructive Sleep Apnea: A High-Density EEG Study

PubMed Central

Jones, Stephanie G.; Riedner, Brady A.; Smith, Richard F.; Ferrarelli, Fabio; Tononi, Giulio; Davidson, Richard J.; Benca, Ruth M.

2014-01-01

Study Objectives: Obstructive sleep apnea (OSA) is associated with significant alterations in neuronal integrity resulting from either hypoxemia and/or sleep loss. A large body of imaging research supports reductions in gray matter volume, alterations in white matter integrity and resting state activity, and functional abnormalities in response to cognitive challenge in various brain regions in patients with OSA. In this study, we used high-density electroencephalography (hdEEG), a functional imaging tool that could potentially be used during routine clinical care, to examine the regional distribution of neural activity in a non-clinical sample of untreated men and women with moderate/severe OSA. Design: Sleep was recorded with 256-channel EEG in relatively healthy subjects with apnea-hypopnea index (AHI) > 10, as well as age-, sex-, and body mass index-matched controls selected from a research population initially recruited for a study on sleep and meditation. Setting: Sleep laboratory. Patients or Participants: Nine subjects with AHI > 10 and nine matched controls. Interventions: N/A. Measurements and Results: Topographic analysis of hdEEG data revealed a broadband reduction in EEG power in a circumscribed region overlying the parietal cortex in OSA subjects. This parietal reduction in neural activity was present, to some extent, across all frequency bands in all stages and episodes of nonrapid eye movement sleep. Conclusion: This investigation suggests that regional deficits in electroencephalography (EEG) power generation may be a useful clinical marker for neural disruption in obstructive sleep apnea, and that high-density EEG may have the sensitivity to detect pathological cortical changes early in the disease process. Citation: Jones SG; Riedner BA; Smith RF; Ferrarelli F; Tononi G; Davidson RJ; Benca RM. Regional reductions in sleep electroencephalography power in obstructive sleep apnea: a high-density EEG study. SLEEP 2014;37(2):399-407. PMID:24497668

Ictal EEG fractal dimension in ECT predicts outcome at 2 weeks in schizophrenia.

PubMed

Abhishekh, Hulegar A; Thirthalli, Jagadisha; Manjegowda, Anusha; Phutane, Vivek H; Muralidharan, Kesavan; Gangadhar, Bangalore N

2013-09-30

Studies of electroconvulsive therapy (ECT) have found an association between ictal electroencephalographic (EEG) measures and clinical outcome in depression. Such studies are lacking in schizophrenia. Consenting schizophrenia patients receiving ECT were assessed using the Brief Psychiatric Rating Scale (BPRS) before and 2 weeks after the start of ECT. The patients' seizure was monitored using EEG. In 26 patients, completely artifact-free EEG derived from the left frontal-pole (FP1) channel and electrocardiography (ECG) were available. The fractal dimension (FD) was computed to assess 4-s EEG epochs, and the maximal value from the earliest ECT session (2nd, 3rd or 4th) was used for analysis. There was a significant inverse correlation between the maximum FD and the total score following 6th ECT. An inverse Inverse correlation was also observed between the maximum FD and the total number of ECTs administered as well as the maximum heart rate (HR) and BPRS scores following 6th ECT. In patients with schizophrenia greater intensity of seizures (higher FD) during initial sessions of ECT is associated with better response at the end of 2 weeks. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Electroencephalography(EEG)-based instinctive brain-control of a quadruped locomotion robot.

PubMed

Jia, Wenchuan; Huang, Dandan; Luo, Xin; Pu, Huayan; Chen, Xuedong; Bai, Ou

2012-01-01

Artificial intelligence and bionic control have been applied in electroencephalography (EEG)-based robot system, to execute complex brain-control task. Nevertheless, due to technical limitations of the EEG decoding, the brain-computer interface (BCI) protocol is often complex, and the mapping between the EEG signal and the practical instructions lack of logic associated, which restrict the user's actual use. This paper presents a strategy that can be used to control a quadruped locomotion robot by user's instinctive action, based on five kinds of movement related neurophysiological signal. In actual use, the user drives or imagines the limbs/wrists action to generate EEG signal to adjust the real movement of the robot according to his/her own motor reflex of the robot locomotion. This method is easy for real use, as the user generates the brain-control signal through the instinctive reaction. By adopting the behavioral control of learning and evolution based on the proposed strategy, complex movement task may be realized by instinctive brain-control.

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 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.

Five pediatric cases of ictal fear with variable outcomes.

PubMed

Akiyama, Mari; Kobayashi, Katsuhiro; Inoue, Takushi; Akiyama, Tomoyuki; Yoshinaga, Harumi

2014-10-01

Ictal fear is an uncommon condition in which fear manifests as the main feature of epileptic seizures. The literature has suggested that ictal fear is generally associated with poor seizure outcomes. We wanted to clarify the variability in seizure outcome of children with ictal fear. We identified five pediatric patients with ictal fear who were followed up on at Okayama University Hospital between January 2003 and December 2012. We retrospectively reviewed their clinical records and EEG findings. The onset age of epilepsy ranged from 8 months to 9 years and 10 months. The common ictal symptoms were sudden fright, clinging to someone nearby, and subsequent impairment of consciousness, which were often accompanied by complex visual hallucinations and psychosis-like complaints. Ictal fear, in four patients, was perceived as a nonepileptic disorder by their parents. Ictal electroencephalograms (EEG) of ictal fear were obtained in all patients. Three showed frontal onset, while the other two showed centrotemporal or occipital onsets. Two patients were seizure free at last follow-up, while seizures persisted in the other three. A patient with seizure onset during infancy had a favorable outcome, which was considered to be compatible with benign partial epilepsy with affective symptoms. Ictal fear is not always associated with a symptomatic cause or a poor seizure outcome. It is quite important to make a correct diagnosis of ictal fear as early as possible to optimize treatment. Copyright © 2014 The Japanese Society of Child Neurology. Published by Elsevier B.V. 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.

Regional reductions in sleep electroencephalography power in obstructive sleep apnea: a high-density EEG study.

PubMed

Jones, Stephanie G; Riedner, Brady A; Smith, Richard F; Ferrarelli, Fabio; Tononi, Giulio; Davidson, Richard J; Benca, Ruth M

2014-02-01

Obstructive sleep apnea (OSA) is associated with significant alterations in neuronal integrity resulting from either hypoxemia and/or sleep loss. A large body of imaging research supports reductions in gray matter volume, alterations in white matter integrity and resting state activity, and functional abnormalities in response to cognitive challenge in various brain regions in patients with OSA. In this study, we used high-density electroencephalography (hdEEG), a functional imaging tool that could potentially be used during routine clinical care, to examine the regional distribution of neural activity in a non-clinical sample of untreated men and women with moderate/severe OSA. Sleep was recorded with 256-channel EEG in relatively healthy subjects with apnea-hypopnea index (AHI) > 10, as well as age-, sex-, and body mass index-matched controls selected from a research population initially recruited for a study on sleep and meditation. Sleep laboratory. Nine subjects with AHI > 10 and nine matched controls. N/A. Topographic analysis of hdEEG data revealed a broadband reduction in EEG power in a circumscribed region overlying the parietal cortex in OSA subjects. This parietal reduction in neural activity was present, to some extent, across all frequency bands in all stages and episodes of nonrapid eye movement sleep. This investigation suggests that regional deficits in electroencephalography (EEG) power generation may be a useful clinical marker for neural disruption in obstructive sleep apnea, and that high-density EEG may have the sensitivity to detect pathological cortical changes early in the disease process.

Electroencephalography (EEG) for neurological prognostication after cardiac arrest and targeted temperature management; rationale and study design.

PubMed

Westhall, Erik; Rosén, Ingmar; Rossetti, Andrea O; van Rootselaar, Anne-Fleur; Kjaer, Troels Wesenberg; Horn, Janneke; Ullén, Susann; Friberg, Hans; Nielsen, Niklas; Cronberg, Tobias

2014-08-16

Electroencephalography (EEG) is widely used to assess neurological prognosis in patients who are comatose after cardiac arrest, but its value is limited by varying definitions of pathological patterns and by inter-rater variability. The American Clinical Neurophysiology Society (ACNS) has recently proposed a standardized EEG-terminology for critical care to address these limitations. In the TTM-trial, 399 post cardiac arrest patients who remained comatose after rewarming underwent a routine EEG. The presence of clinical seizures, use of sedatives and antiepileptic drugs during the EEG-registration were prospectively documented. A well-defined terminology for interpreting post cardiac arrest EEGs is critical for the use of EEG as a prognostic tool. The TTM-trial is registered at ClinicalTrials.gov (NCT01020916).

Prolonged ictal aphasia: a diagnosis to consider.

PubMed

Herskovitz, Moshe; Schiller, Yitzhak

2012-11-01

Aphasia is a common symptom encountered by clinical neurologists. It is usually caused by strokes or lesions involving language regions of the brain, yet prolonged aphasia is rarely the sole manifestation of a simple partial status epilepticus. We report six patients, who suffered from prolonged ictal aphasia. All but one patient had a structural lesion in the left hemisphere, only three suffered from clinical seizures during or shortly prior to the aphasic episode. All patients had ictal patterns on the electroencephalogram (EEG), four of whom had periodic lateralized epileptiform discharges, and five showed frequent recurrent electrographic seizures during the aphasic state. The aphasia lasted several days in all patients, and it resolved after administration of antiepileptic drug treatment. In conclusion, prolonged ictal aphasia is a rare but important treatable cause of aphasia. Surface EEG recordings should be obtained in all patients with unexplained prolonged aphasia to diagnose this rare but treatable entity. Crown Copyright © 2012. Published by Elsevier Ltd. 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.

Amplitude Integrated Electroencephalography Compared With Conventional Video EEG for Neonatal Seizure Detection: A Diagnostic Accuracy Study.

PubMed

Rakshasbhuvankar, Abhijeet; Rao, Shripada; Palumbo, Linda; Ghosh, Soumya; Nagarajan, Lakshmi

2017-08-01

This diagnostic accuracy study compared the accuracy of seizure detection by amplitude-integrated electroencephalography with the criterion standard conventional video EEG in term and near-term infants at risk of seizures. Simultaneous recording of amplitude-integrated EEG (2-channel amplitude-integrated EEG with raw trace) and video EEG was done for 24 hours for each infant. Amplitude-integrated EEG was interpreted by a neonatologist; video EEG was interpreted by a neurologist independently. Thirty-five infants were included in the analysis. In the 7 infants with seizures on video EEG, there were 169 seizure episodes on video EEG, of which only 57 were identified by amplitude-integrated EEG. Amplitude-integrated EEG had a sensitivity of 33.7% for individual seizure detection. Amplitude-integrated EEG had an 86% sensitivity for detection of babies with seizures; however, it was nonspecific, in that 50% of infants with seizures detected by amplitude-integrated EEG did not have true seizures by video EEG. In conclusion, our study suggests that amplitude-integrated EEG is a poor screening tool for neonatal seizures.

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.

Transcranial magnetic stimulation (TMS) coupled with electroencephalography (EEG): Biomarker of the future.

PubMed

Kimiskidis, V K

2016-02-01

In recent years, a number of novel brain-stimulation techniques have been developed (such as TMS-EEG, TMS-fMRI and TMS-NIRS), yet they remain underutilized in the field of epilepsy. Accumulating evidence suggests that transcranial magnetic stimulation (TMS) combined with electroencephalography (TMS-EEG) is a highly relevant technique for exploration of the pathophysiology of human epilepsies as well as a promising biomarker with diagnostic and prognostic potential. In genetic generalized epilepsies, TMS-EEG has provided pathophysiological insight by revealing quasi-stable, covert states of excitability, a subclass of which is associated with the generation of TMS-induced epileptiform discharges (EDs). In focal epilepsy, TMS-induced EDs were successfully employed to identify the epileptogenic zone. In addition, TMS trains applied during focal EDs can terminate them, and appear to restore the effective connectivity of the brain network significantly altered by EDs. This abortive effect of TMS on EDs may possibly serve as a biomarker of response to invasive neuromodulatory techniques. TMS-EEG-based stimulation paradigms can provide insight into the mechanisms underlying human epilepsies and, thus, warrant further study as diagnostic and prognostic biomarkers. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

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.

Association of Electroencephalography (EEG) Power Spectra with Corneal Nerve Fiber Injury in Retinoblastoma Patients.

PubMed

Liu, Jianliang; Sun, Juanjuan; Diao, Yumei; Deng, Aijun

2016-09-04

BACKGROUND In our clinical experience we discovered that EEG band power may be correlated with corneal nerve injury in retinoblastoma patients. This study aimed to investigate biomarkers obtained from electroencephalography (EEG) recordings to reflect corneal nerve injury in retinoblastoma patients. MATERIAL AND METHODS Our study included 20 retinoblastoma patients treated at the Department of Ophthalmology, Affiliated Hospital of Weifang Medical University between 2010 and 2014. Twenty normal individuals were included in the control group. EEG activity was recorded continuously with 32 electrodes using standard EEG electrode placement for detecting EEG power. A cornea confocal microscope was used to examine corneal nerve injury in retinoblastoma patients and normal individuals. Spearman rank correlation analysis was used to analyze the correlation between corneal nerve injury and EEG power changes. The sensitivity and specificity of changed EEG power in diagnosis of corneal nerve injury were also analyzed. RESULTS The predominantly slow EEG oscillations changed gradually into faster waves in retinoblastoma patients. The EEG pattern in retinoblastoma patients was characterized by a distinct increase of delta (P<0.01) and significant decrease of theta power P<0.05). Corneal nerves were damaged in corneas of retinoblastoma patients. Corneal nerve injury was positively correlated with delta EEG spectra power and negatively correlated with theta EEG spectra power. The diagnostic sensitivity and specificity by compounding in the series were 60% and 67%, respectively. CONCLUSIONS Changes in delta and theta of EEG appear to be associated with occurrence of corneal nerve injury. Useful information can be provided for evaluating corneal nerve damage in retinoblastoma patients through analyzing EEG power bands.

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.

Measuring the Differences between Traditional Learning and Game-Based Learning Using Electroencephalography (EEG) Physiologically Based Methodology

ERIC Educational Resources Information Center

Chen, Ching-Huei

2017-01-01

Students' cognitive states can reflect a learning experience that results in engagement in an activity. In this study, we used electroencephalography (EEG) physiologically based methodology to evaluate students' levels of attention and relaxation, as well as their learning performance within a traditional and game-based learning context. While no…

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.

Statistical methods to estimate treatment effects from multichannel electroencephalography (EEG) data in clinical trials.

PubMed

Ma, Junshui; Wang, Shubing; Raubertas, Richard; Svetnik, Vladimir

2010-07-15

With the increasing popularity of using electroencephalography (EEG) to reveal the treatment effect in drug development clinical trials, the vast volume and complex nature of EEG data compose an intriguing, but challenging, topic. In this paper the statistical analysis methods recommended by the EEG community, along with methods frequently used in the published literature, are first reviewed. A straightforward adjustment of the existing methods to handle multichannel EEG data is then introduced. In addition, based on the spatial smoothness property of EEG data, a new category of statistical methods is proposed. The new methods use a linear combination of low-degree spherical harmonic (SPHARM) basis functions to represent a spatially smoothed version of the EEG data on the scalp, which is close to a sphere in shape. In total, seven statistical methods, including both the existing and the newly proposed methods, are applied to two clinical datasets to compare their power to detect a drug effect. Contrary to the EEG community's recommendation, our results suggest that (1) the nonparametric method does not outperform its parametric counterpart; and (2) including baseline data in the analysis does not always improve the statistical power. In addition, our results recommend that (3) simple paired statistical tests should be avoided due to their poor power; and (4) the proposed spatially smoothed methods perform better than their unsmoothed versions. Copyright 2010 Elsevier B.V. All rights reserved.

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.

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

Long-Term Clinical and Electroencephalography (EEG) Consequences of Idiopathic Partial Epilepsies.

PubMed

Dörtcan, Nimet; Tekin Guveli, Betul; Dervent, Aysin

2016-05-03

BACKGROUND Idiopathic partial epilepsies of childhood (IPE) affect a considerable proportion of children. Three main electroclinical syndromes of IPE are the Benign Childhood Epilepsy with Centro-temporal Spikes (BECTS), Panayiotopoulos Syndrome (PS), and Childhood Epilepsy with Occipital Paroxysms (CEOP). In this study we investigated the long-term prognosis of patients with IPE and discussed the semiological and electroencephalography (EEG) data in terms of syndromic characteristics. MATERIAL AND METHODS This study included a group of consecutive patients with IPE who had been followed since 1990. Demographic and clinical variables were investigated. Patients were divided into 3 groups - A: Cases suitable for a single IPE (BECTS, PS and CEOP); B: cases with intermediate characteristics within IPEs; and C: cases with both IPE and IGE characteristics. Long-term data regarding the individual seizure types and EEG findings were re-evaluated. RESULTS A total of 61 patients were included in the study. Mean follow-up duration was 7.8 ± 4.50 years. The mean age at onset of seizures was 7.7 years. There were 40 patients in group A 40, 14 in group B, and 7 in group C. Seizure and EEG characteristics were also explored independently from the syndromic approach. Incidence of autonomic seizures is considerably high at 2-5 years and incidence of oromotor seizures is high at age 9-11 years. The EEG is most abnormal at 6-8 years. The vast majority (86%) of epileptic activity (EA) with parietooccipital is present at 2-5 years, whereas EA with fronto-temporal or multiple sites become more abundant between ages 6 and 11. CONCLUSIONS Results of the present study provide support for the age-related characteristics of the seizures and EEGs in IPE syndromes. Acknowledgement of those phenomena may improve the management of IPEs and give a better estimate of the future consequences.

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

Electroencephalography and analgesics.

PubMed

Malver, Lasse Paludan; Brokjaer, Anne; Staahl, Camilla; Graversen, Carina; Andresen, Trine; Drewes, Asbjørn Mohr

2014-01-01

To assess centrally mediated analgesic mechanisms in clinical trials with pain patients, objective standardized methods such as electroencephalography (EEG) has many advantages. The aim of this review is to provide the reader with an overview of present findings in analgesics assessed with spontaneous EEG and evoked brain potentials (EPs) in humans. Furthermore, EEG methodologies will be discussed with respect to translation from animals to humans and future perspectives in predicting analgesic efficacy. We searched PubMed with MeSH terms 'analgesics', 'electroencephalography' and 'evoked potentials' for relevant articles. Combined with a search in their reference lists 15 articles on spontaneous EEG and 55 papers on EPs were identified. Overall, opioids produced increased activity in the delta band in the spontaneous EEG, but increases in higher frequency bands were also seen. The EP amplitudes decreased in the majority of studies. Anticonvulsants used as analgesics showed inconsistent results. The N-methyl-D-aspartate receptor antagonist ketamine showed an increase in the theta band in spontaneous EEG and decreases in EP amplitudes. Tricyclic antidepressants increased the activity in the delta, theta and beta bands in the spontaneous EEG while EPs were inconsistently affected. Weak analgesics were mainly investigated with EPs and a decrease in amplitudes was generally observed. This review reveals that both spontaneous EEG and EPs are widely used as biomarkers for analgesic drug effects. Methodological differences are common and a more uniform approach will further enhance the value of such biomarkers for drug development and prediction of treatment response in individual patients. © 2013 The British Pharmacological Society.

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

Electroencephalography and quantitative electroencephalography in mild traumatic brain injury.

PubMed

Haneef, Zulfi; Levin, Harvey S; Frost, James D; Mizrahi, Eli M

2013-04-15

Mild traumatic brain injury (mTBI) causes brain injury resulting in electrophysiologic abnormalities visible in electroencephalography (EEG) recordings. Quantitative EEG (qEEG) makes use of quantitative techniques to analyze EEG characteristics such as frequency, amplitude, coherence, power, phase, and symmetry over time independently or in combination. QEEG has been evaluated for its use in making a diagnosis of mTBI and assessing prognosis, including the likelihood of progressing to the postconcussive syndrome (PCS) phase. We review the EEG and qEEG changes of mTBI described in the literature. An attempt is made to separate the findings seen during the acute, subacute, and chronic phases after mTBI. Brief mention is also made of the neurobiological correlates of qEEG using neuroimaging techniques or in histopathology. Although the literature indicates the promise of qEEG in making a diagnosis and indicating prognosis of mTBI, further study is needed to corroborate and refine these methods.

Electroencephalography and Quantitative Electroencephalography in Mild Traumatic Brain Injury

PubMed Central

Levin, Harvey S.; Frost, James D.; Mizrahi, Eli M.

2013-01-01

Abstract Mild traumatic brain injury (mTBI) causes brain injury resulting in electrophysiologic abnormalities visible in electroencephalography (EEG) recordings. Quantitative EEG (qEEG) makes use of quantitative techniques to analyze EEG characteristics such as frequency, amplitude, coherence, power, phase, and symmetry over time independently or in combination. QEEG has been evaluated for its use in making a diagnosis of mTBI and assessing prognosis, including the likelihood of progressing to the postconcussive syndrome (PCS) phase. We review the EEG and qEEG changes of mTBI described in the literature. An attempt is made to separate the findings seen during the acute, subacute, and chronic phases after mTBI. Brief mention is also made of the neurobiological correlates of qEEG using neuroimaging techniques or in histopathology. Although the literature indicates the promise of qEEG in making a diagnosis and indicating prognosis of mTBI, further study is needed to corroborate and refine these methods. PMID:23249295

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.

Time is of the Essence: A Review of Electroencephalography (EEG) and Event-Related Brain Potentials (ERPs) in Language Research.

PubMed

Beres, Anna M

2017-12-01

The discovery of electroencephalography (EEG) over a century ago has changed the way we understand brain structure and function, in terms of both clinical and research applications. This paper starts with a short description of EEG and then focuses on the event-related brain potentials (ERPs), and their use in experimental settings. It describes the typical set-up of an ERP experiment. A description of a number of ERP components typically involved in language research is presented. Finally, the advantages and disadvantages of using ERPs in language research are discussed. EEG has an extensive use in today's world, including medical, psychology, or linguistic research. The excellent temporal resolution of EEG information allows one to track a brain response in milliseconds and therefore makes it uniquely suited to research concerning language processing.

Electroencephalography (EEG) in the Study of Equivalence Class Formation. An Explorative Study.

PubMed

Arntzen, Erik; Steingrimsdottir, Hanna S

2017-01-01

Teaching arbitrary conditional discriminations and testing for derived relations may be essential for understanding changes in cognitive skills. Such conditional discrimination procedures are often used within stimulus equivalence research. For example, the participant is taught AB and BC relations and tested if emergent relations as BA, CB, AC and CA occur. The purpose of the current explorative experiment was to study stimulus equivalence class formation in older adults with electroencephalography (EEG) recordings as an additional measure. The EEG was used to learn about whether there was an indication of cognitive changes such as those observed in neurocognitive disorders (NCD). The present study included four participants who did conditional discrimination training and testing. The experimental design employed pre-class formation sorting and post-class formation sorting of the stimuli used in the experiment. EEG recordings were conducted before training, after training and after testing. The results showed that two participants formed equivalence classes, one participant failed in one of the three test relations, and one participant failed in two of the three test relations. This fourth participant also failed to sort the stimuli in accordance with the experimenter-defined stimulus equivalence classes during post-class formation sorting. The EEG indicated no cognitive decline in the first three participants but possible mild cognitive impairment (MCI) in the fourth participant. The results suggest that equivalence class formation may provide information about cognitive impairments such as those that are likely to occur in the early stages of NCD. The study recommends replications with broader samples.

Electroencephalography (EEG) in the Study of Equivalence Class Formation. An Explorative Study

PubMed Central

Arntzen, Erik; Steingrimsdottir, Hanna S.

2017-01-01

Teaching arbitrary conditional discriminations and testing for derived relations may be essential for understanding changes in cognitive skills. Such conditional discrimination procedures are often used within stimulus equivalence research. For example, the participant is taught AB and BC relations and tested if emergent relations as BA, CB, AC and CA occur. The purpose of the current explorative experiment was to study stimulus equivalence class formation in older adults with electroencephalography (EEG) recordings as an additional measure. The EEG was used to learn about whether there was an indication of cognitive changes such as those observed in neurocognitive disorders (NCD). The present study included four participants who did conditional discrimination training and testing. The experimental design employed pre-class formation sorting and post-class formation sorting of the stimuli used in the experiment. EEG recordings were conducted before training, after training and after testing. The results showed that two participants formed equivalence classes, one participant failed in one of the three test relations, and one participant failed in two of the three test relations. This fourth participant also failed to sort the stimuli in accordance with the experimenter-defined stimulus equivalence classes during post-class formation sorting. The EEG indicated no cognitive decline in the first three participants but possible mild cognitive impairment (MCI) in the fourth participant. The results suggest that equivalence class formation may provide information about cognitive impairments such as those that are likely to occur in the early stages of NCD. The study recommends replications with broader samples. PMID:28377704

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.

Using Electroencephalography to Measure Cognitive Load

ERIC Educational Resources Information Center

Antonenko, Pavlo; Paas, Fred; Grabner, Roland; van Gog, Tamara

2010-01-01

Application of physiological methods, in particular electroencephalography (EEG), offers new and promising approaches to educational psychology research. EEG is identified as a physiological index that can serve as an online, continuous measure of cognitive load detecting subtle fluctuations in instantaneous load, which can help explain effects of…

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

Assessment of the QT interval in the electroencephalography (EEG) of children with syncope, epilepsy, and attention-deficit hyperactivity disorder (ADHD).

PubMed

Jha, Om P; Khurana, Divya S; Carvalho, Karen S; Melvin, Joseph J; Legido, Agustin; O'Riordan, Anna C; Valencia, Ignacio

2010-03-01

The interpretation of QT interval is often neglected during electroencephalography (EEG) reading. We compared the incidence of prolonged QT interval, as seen in the electrocardiography (ECG) recording lead of the EEG, in children presenting with seizure, syncope, or attention-deficit hyperactivity disorder (ADHD). Abnormal QT was defined as >460 ms. The incidence of prolonged QT in the seizure, syncope, and ADHD groups was 1/50 (2%), 7/50 (14%), and 2/50 (4%), respectively (P = .036, chi-square). The mean +/- SD of QT were 405 +/- 34, 424 +/- 39, and 414 +/- 36, respectively (P = .035, analysis of variance [ANOVA], syncope group, compared with seizure group). The incidence of prolonged QT as measured in the EEG was unexpectedly high in children presenting with seizure, syncope, or ADHD. These data support the concept that QT evaluation should be emphasized during routine EEG reading, as it may aid in identifying cases of undiagnosed cardiac conduction abnormalities. Prospective studies comparing EEG-ECG tracings with 12-lead ECG are warranted.

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.

"The wondrous eyes of a new technology"-a history of the early electroencephalography (EEG) of psychopathy, delinquency, and immorality.

PubMed

Schirmann, Felix

2014-01-01

This article presents a history of the early electroencephalography (EEG) of psychopathy, delinquency, and immorality in Great Britain and the United States in the 1940s and 1950s. Then, EEG was a novel research tool that promised ground-breaking insights in psychiatry and criminology. Experts explored its potential regarding the diagnosis, classification, etiology, and treatment of unethical and unlawful persons. This line of research yielded tentative and inconsistent findings, which the experts attributed to methodological and theoretical shortcomings. Accordingly, the scientific community discussed the reliability, validity, and utility of EEG, and launched initiatives to calibrate and standardize the novel tool. The analysis shows that knowledge production, gauging of the research tool, and attempts to establish credibility for EEG in the study of immoral persons occurred simultaneously. The paper concludes with a reflection on the similarities between EEG and neuroimaging-the prime research tool in the current neuroscience of morality-and calls for a critical assessment of their potentials and limitations in the study of immorality and crime.

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).

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.

Discovering the Neural Nature of Moral Cognition? Empirical, Theoretical, and Practical Challenges in Bioethical Research with Electroencephalography (EEG).

PubMed

Wagner, Nils-Frederic; Chaves, Pedro; Wolff, Annemarie

2017-06-01

In this article we critically review the neural mechanisms of moral cognition that have recently been studied via electroencephalography (EEG). Such studies promise to shed new light on traditional moral questions by helping us to understand how effective moral cognition is embodied in the brain. It has been argued that conflicting normative ethical theories require different cognitive features and can, accordingly, in a broadly conceived naturalistic attempt, be associated with different brain processes that are rooted in different brain networks and regions. This potentially morally relevant brain activity has been empirically investigated through EEG-based studies on moral cognition. From neuroscientific evidence gathered in these studies, a variety of normative conclusions have been drawn and bioethical applications have been suggested. We discuss methodological and theoretical merits and demerits of the attempt to use EEG techniques in a morally significant way, point to legal challenges and policy implications, indicate the potential to reveal biomarkers of psychopathological conditions, and consider issues that might inform future bioethical work.

Significant improvement in one-dimensional cursor control using Laplacian electroencephalography over electroencephalography

NASA Astrophysics Data System (ADS)

Boudria, Yacine; Feltane, Amal; Besio, Walter

2014-06-01

Objective. Brain-computer interfaces (BCIs) based on electroencephalography (EEG) have been shown to accurately detect mental activities, but the acquisition of high levels of control require extensive user training. Furthermore, EEG has low signal-to-noise ratio and low spatial resolution. The objective of the present study was to compare the accuracy between two types of BCIs during the first recording session. EEG and tripolar concentric ring electrode (TCRE) EEG (tEEG) brain signals were recorded and used to control one-dimensional cursor movements. Approach. Eight human subjects were asked to imagine either ‘left’ or ‘right’ hand movement during one recording session to control the computer cursor using TCRE and disc electrodes. Main results. The obtained results show a significant improvement in accuracies using TCREs (44%-100%) compared to disc electrodes (30%-86%). Significance. This study developed the first tEEG-based BCI system for real-time one-dimensional cursor movements and showed high accuracies with little training.

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.

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.

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.

Investigating social cognition in infants and adults using dense array electroencephalography ((d)EEG).

PubMed

Akano, Adekemi J; Haley, David W; Dudek, Joanna

2011-06-27

Dense array electroencephalography ((d)EEG), which provides a non-invasive window for measuring brain activity and a temporal resolution unsurpassed by any other current brain imaging technology¹, ² is being used increasingly in the study of social cognitive functioning in infants and adults. While (d)EEG is enabling researchers to examine brain activity patterns with unprecedented levels of sensitivity, conventional EEG recording systems continue to face certain limitations, including 1) poor spatial resolution and source localization³,⁴2) the physical discomfort for test subjects of enduring the individual application of numerous electrodes to the surface of the scalp, and 3) the complexity for researchers of learning to use multiple software packages to collect and process data. Here we present an overview of an established methodology that represents a significant improvement on conventional methodologies for studying EEG in infants and adults. Although several analytical software techniques can be used to establish indirect indices of source localization to improve the spatial resolution of (d)EEG, the HydroCel Geodesic Sensor Net (HCGSN) by Electrical Geodesics, Inc. (EGI), a dense sensory array that maintains equal distances among adjacent recording electrodes on all surfaces of the scalp, further enhances spatial resolution⁴,⁵(,)⁶ compared to standard (d)EEG systems. The sponge-based HCGSN can be applied rapidly and without scalp abrasion, making it ideal for use with adults⁷,⁸ children⁹,¹⁰, ¹¹,¹² and infants¹², in both research and clinical ⁴,⁵,⁶,¹³,¹⁴,¹⁵settings. This feature allows for considerable cost and time savings by decreasing the average net application time compared to other (d)EEG systems. Moreover, the HCGSN includes unified, seamless software applications for all phases of data, greatly simplifying the collection, processing, and analysis of (d)EEG data. The HCGSN features a low-profile electrode

“The wondrous eyes of a new technology”—a history of the early electroencephalography (EEG) of psychopathy, delinquency, and immorality

PubMed Central

Schirmann, Felix

2014-01-01

This article presents a history of the early electroencephalography (EEG) of psychopathy, delinquency, and immorality in Great Britain and the United States in the 1940s and 1950s. Then, EEG was a novel research tool that promised ground-breaking insights in psychiatry and criminology. Experts explored its potential regarding the diagnosis, classification, etiology, and treatment of unethical and unlawful persons. This line of research yielded tentative and inconsistent findings, which the experts attributed to methodological and theoretical shortcomings. Accordingly, the scientific community discussed the reliability, validity, and utility of EEG, and launched initiatives to calibrate and standardize the novel tool. The analysis shows that knowledge production, gauging of the research tool, and attempts to establish credibility for EEG in the study of immoral persons occurred simultaneously. The paper concludes with a reflection on the similarities between EEG and neuroimaging—the prime research tool in the current neuroscience of morality—and calls for a critical assessment of their potentials and limitations in the study of immorality and crime. PMID:24860464

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.

Open Ephys electroencephalography (Open Ephys  +  EEG): a modular, low-cost, open-source solution to human neural recording

NASA Astrophysics Data System (ADS)

Black, Christopher; Voigts, Jakob; Agrawal, Uday; Ladow, Max; Santoyo, Juan; Moore, Christopher; Jones, Stephanie

2017-06-01

Objective. Electroencephalography (EEG) offers a unique opportunity to study human neural activity non-invasively with millisecond resolution using minimal equipment in or outside of a lab setting. EEG can be combined with a number of techniques for closed-loop experiments, where external devices are driven by specific neural signals. However, reliable, commercially available EEG systems are expensive, often making them impractical for individual use and research development. Moreover, by design, a majority of these systems cannot be easily altered to the specification needed by the end user. We focused on mitigating these issues by implementing open-source tools to develop a new EEG platform to drive down research costs and promote collaboration and innovation. Approach. Here, we present methods to expand the open-source electrophysiology system, Open Ephys (www.openephys.org), to include human EEG recordings. We describe the equipment and protocol necessary to interface various EEG caps with the Open Ephys acquisition board, and detail methods for processing data. We present applications of Open Ephys  +  EEG as a research tool and discuss how this innovative EEG technology lays a framework for improved closed-loop paradigms and novel brain-computer interface experiments. Main results. The Open Ephys  +  EEG system can record reliable human EEG data, as well as human EMG data. A side-by-side comparison of eyes closed 8-14 Hz activity between the Open Ephys  +  EEG system and the Brainvision ActiCHamp EEG system showed similar average power and signal to noise. Significance. Open Ephys  +  EEG enables users to acquire high-quality human EEG data comparable to that of commercially available systems, while maintaining the price point and extensibility inherent to open-source systems.

Open Ephys electroencephalography (Open Ephys  +  EEG): a modular, low-cost, open-source solution to human neural recording.

PubMed

Black, Christopher; Voigts, Jakob; Agrawal, Uday; Ladow, Max; Santoyo, Juan; Moore, Christopher; Jones, Stephanie

2017-06-01

Electroencephalography (EEG) offers a unique opportunity to study human neural activity non-invasively with millisecond resolution using minimal equipment in or outside of a lab setting. EEG can be combined with a number of techniques for closed-loop experiments, where external devices are driven by specific neural signals. However, reliable, commercially available EEG systems are expensive, often making them impractical for individual use and research development. Moreover, by design, a majority of these systems cannot be easily altered to the specification needed by the end user. We focused on mitigating these issues by implementing open-source tools to develop a new EEG platform to drive down research costs and promote collaboration and innovation. Here, we present methods to expand the open-source electrophysiology system, Open Ephys (www.openephys.org), to include human EEG recordings. We describe the equipment and protocol necessary to interface various EEG caps with the Open Ephys acquisition board, and detail methods for processing data. We present applications of Open Ephys  +  EEG as a research tool and discuss how this innovative EEG technology lays a framework for improved closed-loop paradigms and novel brain-computer interface experiments. The Open Ephys  +  EEG system can record reliable human EEG data, as well as human EMG data. A side-by-side comparison of eyes closed 8-14 Hz activity between the Open Ephys  +  EEG system and the Brainvision ActiCHamp EEG system showed similar average power and signal to noise. Open Ephys  +  EEG enables users to acquire high-quality human EEG data comparable to that of commercially available systems, while maintaining the price point and extensibility inherent to open-source systems.

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

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.

Interictal Electroencephalography (EEG) Findings in Children with Epilepsy and Bilateral Brain Lesions on Magnetic Resonance Imaging (MRI).

PubMed

Zubcevic, Smail; Milos, Maja; Catibusic, Feriha; Uzicanin, Sajra; Krdzalic, Belma

2015-12-01

Neuroimaging procedures and electroencephalography (EEG) are basic parts of investigation of patients with epilepsies. The aim is to try to assess relationship between bilaterally localized brain lesions found in routine management of children with newly diagnosed epilepsy and their interictal EEG findings. Total amount of 68 patients filled criteria for inclusion in the study that was performed at Neuropediatrics Department, Pediatric Hospital, University Clinical Center Sarajevo, or its outpatient clinic. There were 33 girls (48,5%) and 35 boys (51,5%). Average age at diagnosis of epilepsy was 3,5 years. Both neurological and neuropsychological examination in the moment of making diagnosis of epilepsy was normal in 27 (39,7%) patients, and showed some kind of delay or other neurological finding in 41 (60,3%). Brain MRI showed lesions that can be related to antenatal or perinatal events in most of the patients (ventricular dilation in 30,9%, delayed myelination and post-hypoxic changes in 27,9%). More than half of patients (55,9%) showed bilateral interictal epileptiform discharges on their EEGs, and further 14,7% had other kinds of bilateral abnormalities. Frequency of bilateral epileptic discharges showed statistically significant predominance on level of p<0,05. Cross tabulation between specific types of bilateral brain MRI lesions and EEG finding did not reveal significant type of EEG for assessed brain lesions. We conclude that there exists relationship between bilaterally localized brain MRI lesions and interictal bilateral epileptiform or nonspecific EEG findings in children with newly diagnosed epilepsies. These data are suggesting that in cases when they do not correlate there is a need for further investigation of seizure etiology.

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.

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.

The inverse electroencephalography pipeline

NASA Astrophysics Data System (ADS)

Weinstein, David Michael

The inverse electroencephalography (EEG) problem is defined as determining which regions of the brain are active based on remote measurements recorded with scalp EEG electrodes. An accurate solution to this problem would benefit both fundamental neuroscience research and clinical neuroscience applications. However, constructing accurate patient-specific inverse EEG solutions requires complex modeling, simulation, and visualization algorithms, and to date only a few systems have been developed that provide such capabilities. In this dissertation, a computational system for generating and investigating patient-specific inverse EEG solutions is introduced, and the requirements for each stage of this Inverse EEG Pipeline are defined and discussed. While the requirements of many of the stages are satisfied with existing algorithms, others have motivated research into novel modeling and simulation methods. The principal technical results of this work include novel surface-based volume modeling techniques, an efficient construction for the EEG lead field, and the Open Source release of the Inverse EEG Pipeline software for use by the bioelectric field research community. In this work, the Inverse EEG Pipeline is applied to three research problems in neurology: comparing focal and distributed source imaging algorithms; separating measurements into independent activation components for multifocal epilepsy; and localizing the cortical activity that produces the P300 effect in schizophrenia.

Topographic mapping of electroencephalography coherence in hypnagogic state.

PubMed

Tanaka, H; Hayashi, M; Hori, T

1998-04-01

The present study examined the topographic characteristics of hypnagogic electroencephalography (EEG), using topographic mapping of EEG power and coherence corresponding to nine EEG stages (Hori's hypnagogic EEG stages). EEG stages 1 and 2, the EEG stages 3-8, and the EEG stage 9 each correspond with standard sleep stage W, 1 and 2, respectively. The dominant topographic components of delta and theta activities increased clearly from the vertex sharp-wave stage (the EEG stages 6 and 7) in the anterior-central areas. The dominant topographic component of alpha 3 activities increased clearly from the EEG stage 9 in the anterior-central areas. The dominant topographic component of sigma activities increased clearly from the EEG stage 8 in the central-parietal area. These results suggested basic sleep process might start before the onset of sleep stage 2 or of the manually scored spindles.

Selective mutism and abnormal electroencephalography (EEG) tracings.

PubMed

Politi, Keren; Kivity, Sara; Goldberg-Stern, Hadassa; Halevi, Ayelet; Shuper, Avinoam

2011-11-01

Epileptic discharges are not considered a part of the clinical picture of selective mutism, and electroencephalography is generally not recommended in its work-up. This report describes 6 children with selective mutism who were found to have a history of epilepsy and abnormal interictal or subclinical electroencephalography recordings. Two of them had benign epilepsy of childhood with centro-temporal spikes. The mutism was not related in time to the presence of active seizures. While seizures could be controlled in all children by medications, the mutism resolved only in 1. Although the discharges could be coincidental, they might represent a co-morbidity of selective mutism or even play a role in its pathogenesis. Selective mutism should be listed among the psychiatric disorders that may be associated with electroencephalographic abnormalities. It can probably be regarded as a symptom of a more complicated organic brain disorder.

Electroencephalography after a single unprovoked seizure.

PubMed

Debicki, Derek B

2017-07-01

Electroencephalography (EEG) is an essential diagnostic tool in the evaluation of seizure disorders. In particular, EEG is used as an additional investigation for a single unprovoked seizure. Epileptiform abnormalities are related to seizure disorders and have been shown to predict recurrent unprovoked seizures (i.e., a clinical definition of epilepsy). Thus, the identification of epileptiform abnormalities after a single unprovoked seizure can inform treatment options. The current review addresses the relationship between EEG abnormalities and seizure recurrence. This review also addresses factors that are found to improve the yield of recording epileptiform abnormalities including timing of EEG relative to the new-onset seizure, use of repeat studies, use of sleep deprivation and prolonged recordings. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

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

[EEG technician-nurse collaboration during stereo-electroencephalography].

PubMed

Jomard, Caroline; Benghezal, Mouna; Cheramy, Isabelle; De Beaumont, Ségolène

2017-01-01

Drug-resistant epilepsy has significant repercussions on the daily life of children. Surgery may represent a hope. The nurse and the electroencephalogram technician carry out important teamwork during pre-surgical assessment tests and notably the stereo-electroencephalography. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Electroencephalography and analgesics

PubMed Central

Malver, Lasse Paludan; Brokjær, Anne; Staahl, Camilla; Graversen, Carina; Andresen, Trine; Drewes, Asbjørn Mohr

2014-01-01

To assess centrally mediated analgesic mechanisms in clinical trials with pain patients, objective standardized methods such as electroencephalography (EEG) has many advantages. The aim of this review is to provide the reader with an overview of present findings in analgesics assessed with spontaneous EEG and evoked brain potentials (EPs) in humans. Furthermore, EEG methodologies will be discussed with respect to translation from animals to humans and future perspectives in predicting analgesic efficacy. We searched PubMed with MeSH terms ‘analgesics’, ‘electroencephalography’ and ‘evoked potentials’ for relevant articles. Combined with a search in their reference lists 15 articles on spontaneous EEG and 55 papers on EPs were identified. Overall, opioids produced increased activity in the delta band in the spontaneous EEG, but increases in higher frequency bands were also seen. The EP amplitudes decreased in the majority of studies. Anticonvulsants used as analgesics showed inconsistent results. The N-methyl-D-aspartate receptor antagonist ketamine showed an increase in the theta band in spontaneous EEG and decreases in EP amplitudes. Tricyclic antidepressants increased the activity in the delta, theta and beta bands in the spontaneous EEG while EPs were inconsistently affected. Weak analgesics were mainly investigated with EPs and a decrease in amplitudes was generally observed. This review reveals that both spontaneous EEG and EPs are widely used as biomarkers for analgesic drug effects. Methodological differences are common and a more uniform approach will further enhance the value of such biomarkers for drug development and prediction of treatment response in individual patients. PMID:23593934

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.

Nitrous oxide as a humane method for piglet euthanasia: Behavior and electroencephalography (EEG).

PubMed

Rault, Jean-Loup; Kells, Nikki; Johnson, Craig; Dennis, Rachel; Sutherland, Mhairi; Lay, Donald C

2015-11-01

The search for humane methods to euthanize piglets is critical to address public concern that current methods are not optimal. Blunt force trauma is considered humane but esthetically objectionable. Carbon dioxide (CO2) is used but criticized as aversive. This research sought to: 1) evaluate the aversiveness of inhaling nitrous oxide (N2O; 'laughing gas') using an approach-avoidance test relying on the piglet's perspective, and 2) validate its humaneness to induce loss of consciousness by electroencephalography (EEG). The gas mixtures tested were N2O and air (90%:10%; '90 N'); N2O, oxygen and air (60%:30%:10%; '60 N'); and CO2 and air (90%:10%; '90 C'). Experiment 1 allowed piglets to walk freely between one chamber filled with air and another prefilled with 60 N or 90 N. All piglets exposed to 60 N lasted for the 10 min test duration whereas all piglets exposed to 90 N had to be removed within 5 min because they fell recumbent and unresponsive and then started to flail. Experiment 2 performed the same test except the gas chamber held N2O prefilled at 25%, 50%, or 75% or CO2 prefilled at 7%, 14%, or 21%. The test was terminated more quickly at higher concentrations due to the piglets' responses. Time spent ataxic was greater in the middle concentration gradients. Flailing behavior tended to correlate with increasing concentrations of CO2 but not N2O. Experiment 3, using the minimal anesthesia model, showed that both 90 N and 90 C induced isoelectric EEG, in 71 and 59 s respectively, but not 60 N within 15 min. The EEG results together with the observed behavioral changes reflect differences in the animal's perceptive experience. The implications for animal welfare are that N2O is much less aversive than CO2, and 90% N2O can euthanize piglets. Copyright © 2015 Elsevier Inc. All rights reserved.

An Intracranial Electroencephalography (iEEG) Brain Function Mapping Tool with an Application to Epilepsy Surgery Evaluation.

PubMed

Wang, Yinghua; Yan, Jiaqing; Wen, Jianbin; Yu, Tao; Li, Xiaoli

2016-01-01

Before epilepsy surgeries, intracranial electroencephalography (iEEG) is often employed in function mapping and epileptogenic foci localization. Although the implanted electrodes provide crucial information for epileptogenic zone resection, a convenient clinical tool for electrode position registration and Brain Function Mapping (BFM) visualization is still lacking. In this study, we developed a BFM Tool, which facilitates electrode position registration and BFM visualization, with an application to epilepsy surgeries. The BFM Tool mainly utilizes electrode location registration and function mapping based on pre-defined brain models from other software. In addition, the electrode node and mapping properties, such as the node size/color, edge color/thickness, mapping method, can be adjusted easily using the setting panel. Moreover, users may manually import/export location and connectivity data to generate figures for further application. The role of this software is demonstrated by a clinical study of language area localization. The BFM Tool helps clinical doctors and researchers visualize implanted electrodes and brain functions in an easy, quick and flexible manner. Our tool provides convenient electrode registration, easy brain function visualization, and has good performance. It is clinical-oriented and is easy to deploy and use. The BFM tool is suitable for epilepsy and other clinical iEEG applications.

An Intracranial Electroencephalography (iEEG) Brain Function Mapping Tool with an Application to Epilepsy Surgery Evaluation

PubMed Central

Wang, Yinghua; Yan, Jiaqing; Wen, Jianbin; Yu, Tao; Li, Xiaoli

2016-01-01

Objects: Before epilepsy surgeries, intracranial electroencephalography (iEEG) is often employed in function mapping and epileptogenic foci localization. Although the implanted electrodes provide crucial information for epileptogenic zone resection, a convenient clinical tool for electrode position registration and Brain Function Mapping (BFM) visualization is still lacking. In this study, we developed a BFM Tool, which facilitates electrode position registration and BFM visualization, with an application to epilepsy surgeries. Methods: The BFM Tool mainly utilizes electrode location registration and function mapping based on pre-defined brain models from other software. In addition, the electrode node and mapping properties, such as the node size/color, edge color/thickness, mapping method, can be adjusted easily using the setting panel. Moreover, users may manually import/export location and connectivity data to generate figures for further application. The role of this software is demonstrated by a clinical study of language area localization. Results: The BFM Tool helps clinical doctors and researchers visualize implanted electrodes and brain functions in an easy, quick and flexible manner. Conclusions: Our tool provides convenient electrode registration, easy brain function visualization, and has good performance. It is clinical-oriented and is easy to deploy and use. The BFM tool is suitable for epilepsy and other clinical iEEG applications. PMID:27199729

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.

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

Prognostic value of electroencephalography (EEG) after out-of-hospital cardiac arrest in successfully resuscitated patients used in daily clinical practice.

PubMed

Søholm, Helle; Kjær, Troels Wesenberg; Kjaergaard, Jesper; Cronberg, Tobias; Bro-Jeppesen, John; Lippert, Freddy K; Køber, Lars; Wanscher, Michael; Hassager, Christian

2014-11-01

Out-of-hospital cardiac arrest (OHCA) is associated with a poor prognosis and predicting outcome is complex with neurophysiological testing and repeated clinical neurological examinations as key components of the assessment. In this study we examine the association between different electroencephalography (EEG) patterns and mortality in a clinical cohort of OHCA-patients. From 2002 to 2011 consecutive patients were admitted to an intensive-care-unit after resuscitation from OHCA. Utstein-criteria for pre-hospital data and review of individual patients' charts for post-resuscitation care were used. EEG reports were analysed according to the 2012 American Clinical Neurophysiology Society's guidelines. A total of 1076 patients were included, and EEG was performed in 20% (n=219) with a median of 3(IQR 2-4) days after OHCA. Rhythmic Delta Activity (RDA) was found in 71 patients (36%) and Periodic Discharges (PD) in 100 patients (45%). Background EEG frequency of Alpha+ or Theta was noted in 107 patients (49%), and change in cerebral EEG activity to stimulation (reactivity) was found in 38 patients (17%). Suppression (all activity <10 μV) was found in 26 (12%) and burst-suppression in 17 (8%) patients. A favourable EEG pattern (reactivity, favourable background frequency and RDA) was independently associated with reduced mortality with hazard ratio (HR) 0.43 (95%CI: 0.24-0.76), p=0.004 (false positive rate: 31%) and a non-favourable EEG pattern (no reactivity, unfavourable background frequency, and PD, suppressed voltage or burst-suppression) was associated with higher mortality (HR=1.62(1.09-2.41), p=0.02) after adjustment for known prognostic factors (false positive rate: 9%). EEG may be useful in work-up in prognostication of patients with OHCA. Findings such as Rhythmic Delta Activity (RDA) seem to be associated with a better prognosis, whereas suppressed voltage and burst-suppression patterns were associated with poor prognosis. Copyright © 2014 Elsevier Ireland

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.

A Fast, Efficient Domain Adaptation Technique for Cross-Domain Electroencephalography(EEG)-Based Emotion Recognition.

PubMed

Chai, Xin; Wang, Qisong; Zhao, Yongping; Li, Yongqiang; Liu, Dan; Liu, Xin; Bai, Ou

2017-05-03

Electroencephalography (EEG)-based emotion recognition is an important element in psychiatric health diagnosis for patients. However, the underlying EEG sensor signals are always non-stationary if they are sampled from different experimental sessions or subjects. This results in the deterioration of the classification performance. Domain adaptation methods offer an effective way to reduce the discrepancy of marginal distribution. However, for EEG sensor signals, both marginal and conditional distributions may be mismatched. In addition, the existing domain adaptation strategies always require a high level of additional computation. To address this problem, a novel strategy named adaptive subspace feature matching (ASFM) is proposed in this paper in order to integrate both the marginal and conditional distributions within a unified framework (without any labeled samples from target subjects). Specifically, we develop a linear transformation function which matches the marginal distributions of the source and target subspaces without a regularization term. This significantly decreases the time complexity of our domain adaptation procedure. As a result, both marginal and conditional distribution discrepancies between the source domain and unlabeled target domain can be reduced, and logistic regression (LR) can be applied to the new source domain in order to train a classifier for use in the target domain, since the aligned source domain follows a distribution which is similar to that of the target domain. We compare our ASFM method with six typical approaches using a public EEG dataset with three affective states: positive, neutral, and negative. Both offline and online evaluations were performed. The subject-to-subject offline experimental results demonstrate that our component achieves a mean accuracy and standard deviation of 80.46% and 6.84%, respectively, as compared with a state-of-the-art method, the subspace alignment auto-encoder (SAAE), which achieves values

A computer-based information system for epilepsy and electroencephalography.

PubMed

Finnerup, N B; Fuglsang-Frederiksen, A; Røssel, P; Jennum, P

1999-08-01

This paper describes a standardised computer-based information system for electroencephalography (EEG) focusing on epilepsy. The system was developed using a prototyping approach. It is based on international recommendations for EEG examination, interpretation and terminology, international guidelines for epidemiological studies on epilepsy and classification of epileptic seizures and syndromes and international classification of diseases. It is divided into: (1) clinical information and epilepsy relevant data; and (2) EEG data, which is hierarchically structured including description and interpretation of EEG. Data is coded but is supplemented with unrestricted text. The resulting patient database can be integrated with other clinical databases and with the patient record system and may facilitate clinical and epidemiological research and development of standards and guidelines for EEG description and interpretation. The system is currently used for teleconsultation between Gentofte and Lisbon.

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.

Electroencephalography and Brain MRI Patterns in Encephalopathy.

PubMed

Wabulya, Angela; Lesser, Ronald P; Llinas, Rafael; Kaplan, Peter W

2016-04-01

Using electroencephalography (EEG) and histology in patients with diffuse encephalopathy, Gloor et al reported that paroxysmal synchronous discharges (PSDs) on EEG required combined cortical gray (CG) and "subcortical" gray (SCG) matter pathology, while polymorphic delta activity (PDA) occurred in patients with white matter pathology. In patients with encephalopathy, we compared EEG findings and magnetic resonance imaging (MRI) to determine if MRI reflected similar pathological EEG correlations. Retrospective case control study of 52 cases with EEG evidence of encephalopathy and 50 controls without evidence of encephalopathy. Review of clinical, EEG and MRI data acquired within 4 days of each other. The most common EEG finding in encephalopathy was background slowing, in 96.1%. We found PSDs in 0% of cases with the combination of CG and SCG abnormalities. Although 13.5% (n=7) had PSDs on EEG; 3 of these had CG and 4 had SCG abnormalities. A total of 73.1% (38/52) had white matter abnormalities-of these 28.9% (11/38) had PDA. PSDs were found with either CG or "SCG" MRI abnormalities and did not require a combination of the two. In agreement with Gloor et al, PDA occurred with white matter MRI abnormalities in the absence of gray matter abnormalities. © EEG and Clinical Neuroscience Society (ECNS) 2015.

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

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.

The impact of hyperoxia on brain activity: A resting-state and task-evoked electroencephalography (EEG) study.

PubMed

Sheng, Min; Liu, Peiying; Mao, Deng; Ge, Yulin; Lu, Hanzhang

2017-01-01

A better understanding of the effect of oxygen on brain electrophysiological activity may provide a more mechanistic insight into clinical studies that use oxygen treatment in pathological conditions, as well as in studies that use oxygen to calibrate functional magnetic resonance imaging (fMRI) signals. This study applied electroencephalography (EEG) in healthy subjects and investigated how high a concentration of oxygen in inhaled air (i.e., normobaric hyperoxia) alters brain activity under resting-state and task-evoked conditions. Study 1 investigated its impact on resting EEG and revealed that hyperoxia suppressed α (8-13Hz) and β (14-35Hz) band power (by 15.6±2.3% and 14.1±3.1%, respectively), but did not change the δ (1-3Hz), θ (4-7Hz), and γ (36-75Hz) bands. Sham control experiments did not result in such changes. Study 2 reproduced these findings, and, furthermore, examined the effect of hyperoxia on visual stimulation event-related potentials (ERP). It was found that the main peaks of visual ERP, specifically N1 and P2, were both delayed during hyperoxia compared to normoxia (P = 0.04 and 0.02, respectively). In contrast, the amplitude of the peaks did not show a change. Our results suggest that hyperoxia has a pronounced effect on brain neural activity, for both resting-state and task-evoked potentials.

The impact of hyperoxia on brain activity: A resting-state and task-evoked electroencephalography (EEG) study

PubMed Central

Sheng, Min; Liu, Peiying; Mao, Deng; Ge, Yulin

2017-01-01

A better understanding of the effect of oxygen on brain electrophysiological activity may provide a more mechanistic insight into clinical studies that use oxygen treatment in pathological conditions, as well as in studies that use oxygen to calibrate functional magnetic resonance imaging (fMRI) signals. This study applied electroencephalography (EEG) in healthy subjects and investigated how high a concentration of oxygen in inhaled air (i.e., normobaric hyperoxia) alters brain activity under resting-state and task-evoked conditions. Study 1 investigated its impact on resting EEG and revealed that hyperoxia suppressed α (8-13Hz) and β (14-35Hz) band power (by 15.6±2.3% and 14.1±3.1%, respectively), but did not change the δ (1-3Hz), θ (4-7Hz), and γ (36-75Hz) bands. Sham control experiments did not result in such changes. Study 2 reproduced these findings, and, furthermore, examined the effect of hyperoxia on visual stimulation event-related potentials (ERP). It was found that the main peaks of visual ERP, specifically N1 and P2, were both delayed during hyperoxia compared to normoxia (P = 0.04 and 0.02, respectively). In contrast, the amplitude of the peaks did not show a change. Our results suggest that hyperoxia has a pronounced effect on brain neural activity, for both resting-state and task-evoked potentials. PMID:28464001

Active Deep Learning-Based Annotation of Electroencephalography Reports for Cohort Identification

PubMed Central

Maldonado, Ramon; Goodwin, Travis R; Harabagiu, Sanda M

2017-01-01

The annotation of a large corpus of Electroencephalography (EEG) reports is a crucial step in the development of an EEG-specific patient cohort retrieval system. The annotation of multiple types of EEG-specific medical concepts, along with their polarity and modality, is challenging, especially when automatically performed on Big Data. To address this challenge, we present a novel framework which combines the advantages of active and deep learning while producing annotations that capture a variety of attributes of medical concepts. Results obtained through our novel framework show great promise. PMID:28815135

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

Outcome of no resection after long-term subdural electroencephalography evaluation in children with epilepsy.

PubMed

Pestana Knight, Elia M; Loddenkemper, Tobias; Lachhwani, Deepak; Kotagal, Prakash; Wyllie, Elaine; Bingaman, William; Gupta, Ajay

2011-09-01

The aim of this study was to identify the reasons for and predictors of no resection of the epileptogenic zone in children with epilepsy who had undergone long-term invasive subdural grid electroencephalography (SDG-EEG) evaluation. The authors retrospectively reviewed the consecutive medical records of children (< 19 years of age) who had undergone SDG-EEG evaluation over a 7-year period (1997-2004). To determine the predictors of no resection, the authors obtained the clinical characteristics and imaging and EEG findings of children who had no resection after long-term invasive SDG-EEG evaluation and compared these data with those in a group of children who did undergo resection. They describe the indications for SDG-EEG evaluation and the reasons for no resection in these patients. Of 66 children who underwent SDG-EEG evaluation, 9 (13.6%) did not undergo subsequent resection (no-resection group; 6 males). Of these 9 patients, 6 (66.7%) had normal neurological examinations and 5 (55.6%) had normal findings on brain MR imaging. Scalp video EEG localized epilepsy to the left hemisphere in 6 of the 9 patients and to the right hemisphere in 2; it was nonlocalizable in 1 of the 9 patients. Indications for SDG-EEG in the no-resection group were ictal onset zone (IOZ) localization (9 of 9 patients), motor cortex localization (5 of 9 patients), and language area localization (4 of 9 patients). Reasons for no resection after SDG-EEG evaluation were the lack of a well-defined IOZ in 5 of 9 patients (4 multifocal IOZs and 1 nonlocalizable IOZ) and anticipated new permanent postoperative neurological deficits in 7 of 9 patients (3 motor, 2 language, and 2 motor and language deficits). Comparison with the resection group (57 patients) demonstrated that postictal Todd paralysis in the dominant hand was the only variable seen more commonly (χ(2) = 4.781, p = 0.029) in the no-resection group (2 [22.2%] of 9 vs 2 [3.5%] of 57 patients). The no-resection group had a larger

A Fast, Efficient Domain Adaptation Technique for Cross-Domain Electroencephalography(EEG)-Based Emotion Recognition

PubMed Central

Chai, Xin; Wang, Qisong; Zhao, Yongping; Li, Yongqiang; Liu, Dan; Liu, Xin; Bai, Ou

2017-01-01

Electroencephalography (EEG)-based emotion recognition is an important element in psychiatric health diagnosis for patients. However, the underlying EEG sensor signals are always non-stationary if they are sampled from different experimental sessions or subjects. This results in the deterioration of the classification performance. Domain adaptation methods offer an effective way to reduce the discrepancy of marginal distribution. However, for EEG sensor signals, both marginal and conditional distributions may be mismatched. In addition, the existing domain adaptation strategies always require a high level of additional computation. To address this problem, a novel strategy named adaptive subspace feature matching (ASFM) is proposed in this paper in order to integrate both the marginal and conditional distributions within a unified framework (without any labeled samples from target subjects). Specifically, we develop a linear transformation function which matches the marginal distributions of the source and target subspaces without a regularization term. This significantly decreases the time complexity of our domain adaptation procedure. As a result, both marginal and conditional distribution discrepancies between the source domain and unlabeled target domain can be reduced, and logistic regression (LR) can be applied to the new source domain in order to train a classifier for use in the target domain, since the aligned source domain follows a distribution which is similar to that of the target domain. We compare our ASFM method with six typical approaches using a public EEG dataset with three affective states: positive, neutral, and negative. Both offline and online evaluations were performed. The subject-to-subject offline experimental results demonstrate that our component achieves a mean accuracy and standard deviation of 80.46% and 6.84%, respectively, as compared with a state-of-the-art method, the subspace alignment auto-encoder (SAAE), which achieves values

Using Electroencephalography for Treatment Guidance in Major Depressive Disorder.

PubMed

Wade, Elizabeth C; Iosifescu, Dan V

2016-09-01

Given the high prevalence of treatment-resistant depression and the long delays in finding effective treatments via trial and error, valid biomarkers of treatment outcome with the ability to guide treatment selection represent one of the most important unmet needs in mood disorders. A large body of research has investigated, for this purpose, biomarkers derived from electroencephalography (EEG), using resting state EEG or evoked potentials. Most studies have focused on specific EEG features (or combinations thereof), whereas more recently machine-learning approaches have been used to define the EEG features with the best predictive abilities without a priori hypotheses. While reviewing these different approaches, we have focused on the predictor characteristics and the quality of the supporting evidence. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

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

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

Evidence of a Faster Posterior Dominant EEG Rhythm in Children with Autism

ERIC Educational Resources Information Center

Gregory, Michael D.; Mandelbaum, David E.

2012-01-01

Multiple electroencephalography (EEG) abnormalities have been associated with autism. In the course of clinical work, we have observed a posterior dominant EEG rhythm at higher frequency in children with autism. To test this observation, 56 EEG tracings of children with autism were compared to the EEGs of age-matched controls. Children with autism…

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.

[Digital electroencephalography in brain death diagnostics : Technical requirements and results of a survey on the compatibility with medical guidelines of digital EEG systems from providers in Germany].

PubMed

Walter, U; Noachtar, S; Hinrichs, H

2018-02-01

The guidelines of the German Medical Association and the German Society for Clinical Neurophysiology and Functional Imaging (DGKN) require a high procedural and technical standard for electroencephalography (EEG) as an ancillary method for diagnosing the irreversible cessation of brain function (brain death). Nowadays, digital EEG systems are increasingly being applied in hospitals. So far it is unclear to what extent the digital EEG systems currently marketed in Germany meet the guidelines for diagnosing brain death. In the present article, the technical und safety-related requirements for digital EEG systems and the EEG documentation for diagnosing brain death are described in detail. On behalf of the DGKN, the authors sent out a questionnaire to all identified distributors of digital EEG systems in Germany with respect to the following technical demands: repeated recording of the calibration signals during an ongoing EEG recording, repeated recording of all electrode impedances during an ongoing EEG recording, assessability of intrasystem noise and galvanic isolation of measurement earthing from earthing conductor (floating input). For 15 of the identified 20 different digital EEG systems the specifications were provided by the distributors (among them all distributors based in Germany). All of these EEG systems are provided with a galvanic isolation (floating input). The internal noise can be tested with all systems; however, some systems do not allow repeated recording of the calibration signals and/or the electrode impedances during an ongoing EEG recording. The majority but not all of the currently available digital EEG systems offered for clinical use are eligible for use in brain death diagnostics as per German guidelines.

Automated electroencephalography system and electroencephalographic coordinates of space motion sickness, part 1

NASA Technical Reports Server (NTRS)

Frost, J. D., Jr.

1976-01-01

A self-contained and portable device which permits clinical electroencephalography (EEG) to be conducted in remote locations by minimally trained, nontechnical personnel was developed and tested. The unit accomplishes semiautomatic acquisition of EEG data from the patient, simultaneous transmission of eight data channels to a central hospital facility over conventional telephone equipment, and automatic printing (at the remote site) of the EEG report generated at the central location. Consequently, this system enables the delivery of high-quality EEG diagnostic services in a geographically remote site with the accuracy and speed formerly possible only in certain large medical centers. Beside obvious potential clinical applications, this system serves as an initial prototype of a unit which could provide inflight EEG during future space missions.

The evolution of endovascular electroencephalography: historical perspective and future applications.

PubMed

Sefcik, Roberta K; Opie, Nicholas L; John, Sam E; Kellner, Christopher P; Mocco, J; Oxley, Thomas J

2016-05-01

Current standard practice requires an invasive approach to the recording of electroencephalography (EEG) for epilepsy surgery, deep brain stimulation (DBS), and brain-machine interfaces (BMIs). The development of endovascular techniques offers a minimally invasive route to recording EEG from deep brain structures. This historical perspective aims to describe the technical progress in endovascular EEG by reviewing the first endovascular recordings made using a wire electrode, which was followed by the development of nanowire and catheter recordings and, finally, the most recent progress in stent-electrode recordings. The technical progress in device technology over time and the development of the ability to record chronic intravenous EEG from electrode arrays is described. Future applications for the use of endovascular EEG in the preoperative and operative management of epilepsy surgery are then discussed, followed by the possibility of the technique's future application in minimally invasive operative approaches to DBS and BMI.

Simultaneous electroencephalography-functional MRI at 3 T: an analysis of safety risks imposed by performing anatomical reference scans with the EEG equipment in place.

PubMed

Nöth, Ulrike; Laufs, Helmut; Stoermer, Robert; Deichmann, Ralf

2012-03-01

To describe heating effects to be expected in simultaneous electroencephalography (EEG) and magnetic resonance imaging (MRI) when deviating from the EEG manufacturer's instructions; to test which anatomical MRI sequences have a sufficiently low specific absorption rate (SAR) to be performed with the EEG equipment in place; and to suggest precautions to reduce the risk of heating. Heating was determined in vivo below eight EEG electrodes, using both head and body coil transmission and sequences covering the whole range of SAR values. Head transmit coil: temperature increases were below 2.2°C for low SAR sequences, but reached 4.6°C (one subject, clavicle) for high SAR sequences; the equilibrium temperature T(eq) remained below 39°C. Body transmit coil: temperature increases were higher and more frequent over subjects and electrodes, with values below 2.6°C for low SAR sequences, reaching 6.9°C for high SAR sequences (T8 electrode) with T(eq) exceeding a critical level of 40°C. Anatomical imaging should be based on T1-weighted sequences (FLASH, MPRAGE, MDEFT) with an SAR below values for functional MRI sequences based on gradient echo planar imaging. Anatomical sequences with a high SAR can pose a significant risk, which is reduced by using head coil transmission. Copyright © 2011 Wiley-Liss, Inc.

Clonidine Sedation Effects in Children During Electroencephalography.

PubMed

Barzegar, Mohammad; Piri, Reza; Naghavi-Behzad, Mohammad; Ghasempour, Masoumeh

2017-09-01

It is very important to have proper management in children with Seizure. Electroencephalography (EEG) as a diagnostic instrument has a key role in determining the management method of seizure in children. Because of poor cooperation of some children (especially children with attention deficit hyperactivity disorders and developmental disorders) in performing EEG, it is the best choice to sedate children before EEG. The aim of present study is to evaluate the sedation efficacy of clonidine in children before EEG. In a randomized clinical trial, 45 children age 2 to 12 with seizure, who referred to Children Hospital of Tabriz University of Medical Sciences and candidate for EEG, were studied. Sedation before EEG induced by 0.5 to 2.0 mg clonidine orally. Sedation score (0 to 5) measured by using eyes condition, response to voice, and response to touch. Successful sedation, EEG performing, and hemodynamic stability were evaluated during sedation. Of all patients, 40 patients (88.88%) were sedated successfully, and EEG was performed for all of the children. Mean onset time of clonidine effect was 35.47±13.56 minutes and mean time of that the patients' level of consciousness back to the level before administrating of clonidine was 77.55±26.87 minutes. Hemodynamic states of all patients were stable during the study, and there were no significant changes in vital sign of patients. In conclusion, clonidine can be considered as a safe alternative medication for sedation for EEG, which is fortunately associated with no significant change in vital signs, which may complicate overall status of patients.

Characterizing and Modulating Brain Circuitry through Transcranial Magnetic Stimulation Combined with Electroencephalography.

PubMed

Farzan, Faranak; Vernet, Marine; Shafi, Mouhsin M D; Rotenberg, Alexander; Daskalakis, Zafiris J; Pascual-Leone, Alvaro

2016-01-01

The concurrent combination of transcranial magnetic stimulation (TMS) with electroencephalography (TMS-EEG) is a powerful technology for characterizing and modulating brain networks across developmental, behavioral, and disease states. Given the global initiatives in mapping the human brain, recognition of the utility of this technique is growing across neuroscience disciplines. Importantly, TMS-EEG offers translational biomarkers that can be applied in health and disease, across the lifespan, and in humans and animals, bridging the gap between animal models and human studies. However, to utilize the full potential of TMS-EEG methodology, standardization of TMS-EEG study protocols is needed. In this article, we review the principles of TMS-EEG methodology, factors impacting TMS-EEG outcome measures, and the techniques for preventing and correcting artifacts in TMS-EEG data. To promote the standardization of this technique, we provide comprehensive guides for designing TMS-EEG studies and conducting TMS-EEG experiments. We conclude by reviewing the application of TMS-EEG in basic, cognitive and clinical neurosciences, and evaluate the potential of this emerging technology in brain research.

Characterizing and Modulating Brain Circuitry through Transcranial Magnetic Stimulation Combined with Electroencephalography

PubMed Central

Farzan, Faranak; Vernet, Marine; Shafi, Mouhsin M. D.; Rotenberg, Alexander; Daskalakis, Zafiris J.; Pascual-Leone, Alvaro

2016-01-01

The concurrent combination of transcranial magnetic stimulation (TMS) with electroencephalography (TMS-EEG) is a powerful technology for characterizing and modulating brain networks across developmental, behavioral, and disease states. Given the global initiatives in mapping the human brain, recognition of the utility of this technique is growing across neuroscience disciplines. Importantly, TMS-EEG offers translational biomarkers that can be applied in health and disease, across the lifespan, and in humans and animals, bridging the gap between animal models and human studies. However, to utilize the full potential of TMS-EEG methodology, standardization of TMS-EEG study protocols is needed. In this article, we review the principles of TMS-EEG methodology, factors impacting TMS-EEG outcome measures, and the techniques for preventing and correcting artifacts in TMS-EEG data. To promote the standardization of this technique, we provide comprehensive guides for designing TMS-EEG studies and conducting TMS-EEG experiments. We conclude by reviewing the application of TMS-EEG in basic, cognitive and clinical neurosciences, and evaluate the potential of this emerging technology in brain research. PMID:27713691

Quantitative electroencephalography in a swine model of blast-induced brain injury.

PubMed

Chen, Chaoyang; Zhou, Chengpeng; Cavanaugh, John M; Kallakuri, Srinivasu; Desai, Alok; Zhang, Liying; King, Albert I

2017-01-01

Electroencephalography (EEG) was used to examine brain activity abnormalities earlier after blast exposure using a swine model to develop a qEEG data analysis protocol. Anaesthetized swine were exposed to 420-450 Kpa blast overpressure and survived for 3 days after blast. EEG recordings were performed at 15 minutes before the blast and 15 minutes, 30 minutes, 2 hours and 1, 2 and 3 days post-blast using surface recording electrodes and a Biopac 4-channel data acquisition system. Off-line quantitative EEG (qEEG) data analysis was performed to determine qEEG changes. Blast induced qEEG changes earlier after blast exposure, including a decrease of mean amplitude (MAMP), an increase of delta band power, a decrease of alpha band root mean square (RMS) and a decrease of 90% spectral edge frequency (SEF90). This study demonstrated that qEEG is sensitive for cerebral injury. The changes of qEEG earlier after the blast indicate the potential of utilization of multiple parameters of qEEG for diagnosis of blast-induced brain injury. Early detection of blast induced brain injury will allow early screening and assessment of brain abnormalities in soldiers to enable timely therapeutic intervention.

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

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

Negligible Motion Artifacts in Scalp Electroencephalography (EEG) During Treadmill Walking.

PubMed

Nathan, Kevin; Contreras-Vidal, Jose L

2015-01-01

Recent mobile brain/body imaging (MoBI) techniques based on active electrode scalp electroencephalogram (EEG) allow the acquisition and real-time analysis of brain dynamics during active unrestrained motor behavior involving whole body movements such as treadmill walking, over-ground walking and other locomotive and non-locomotive tasks. Unfortunately, MoBI protocols are prone to physiological and non-physiological artifacts, including motion artifacts that may contaminate the EEG recordings. A few attempts have been made to quantify these artifacts during locomotion tasks but with inconclusive results due in part to methodological pitfalls. In this paper, we investigate the potential contributions of motion artifacts in scalp EEG during treadmill walking at three different speeds (1.5, 3.0, and 4.5 km/h) using a wireless 64 channel active EEG system and a wireless inertial sensor attached to the subject's head. The experimental setup was designed according to good measurement practices using state-of-the-art commercially available instruments, and the measurements were analyzed using Fourier analysis and wavelet coherence approaches. Contrary to prior claims, the subjects' motion did not significantly affect their EEG during treadmill walking although precaution should be taken when gait speeds approach 4.5 km/h. Overall, these findings suggest how MoBI methods may be safely deployed in neural, cognitive, and rehabilitation engineering applications.

Electroencephalography in Normotensive and Hypertensive Pregnancies and Subsequent Quality of Life.

PubMed

Brussé, Ingrid A; Duvekot, Johannes J; Meester, Ivette; Jansen, Gerard; Rizopoulos, Dimitris; Steegers, Eric A P; Visser, Gerhard H

2016-01-01

To compare electroencephalography (EEG) findings during pregnancy and postpartum in women with normotensive pregnancies and pregnancies complicated by hypertensive disorders. Also the health related quality of life postpartum was related to these EEG findings. An observational case-control study in a university hospital in the Netherlands. Twenty-nine normotensive and 58 hypertensive pregnant women were included. EEG's were recorded on several occasions during pregnancy and 6-8 weeks postpartum. Postpartum, the women filled out health related quality of life questionnaires. Main outcome measures were qualitative and quantitative assessments on EEG, multidimensional fatigue inventory, Short Form (36) Health Survey and EuroQoL visual analogue scale. In women with severe preeclampsia significantly lower alpha peak frequency, more delta and theta activity bilaterally and a higher EEG Sum Score were seen. Postpartum, these women showed impaired mental health, mental fatigue and social functioning, which could not be related to the EEG findings. Severe preeclamptic patients show more EEG abnormalities and have impaired mental wellbeing postpartum, but these findings are not correlated.

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

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

Measuring Cognitive Load with Electroencephalography and Self-Report: Focus on the Effect of English-Medium Learning for Korean Students

ERIC Educational Resources Information Center

Lee, Hyunjeong

2014-01-01

This study investigated a reliable and valid method for measuring cognitive load during learning through comparing various types of cognitive load measurements: electroencephalography (EEG), self-reporting, and learning outcome. A total of 43 college-level students underwent watching a documentary delivered in English or in Korean. EEG was…

Electroencephalography for diagnosis and prognosis of acute encephalitis.

PubMed

Sutter, Raoul; Kaplan, Peter W; Cervenka, Mackenzie C; Thakur, Kiran T; Asemota, Anthony O; Venkatesan, Arun; Geocadin, Romergryko G

2015-08-01

To confirm the previously identified EEG characteristics for HSV encephalitis and to determine the diagnostic and predictive value of electroencephalography (EEG) features for etiology and outcome of acute encephalitis in adults. In addition, we sought to investigate their independence from possible clinical confounders. This study was performed in the Intensive Care Units of two academic tertiary care centers. From 1997 to 2011, all consecutive patients with acute encephalitis who received one or more EEGs were included. Examination of the diagnostic and predictive value of EEG patterns regarding etiology, clinical conditions, and survival was performed. The main outcome measure was in-hospital death. Of 103 patients with encephalitis, EEGs were performed in 76 within a median of 1 day (inter quartile range 0.5-3) after admission. Mortality was 19.7%. Higher proportions of periodic discharges (PDs) (p=0.029) and focal slowing (p=0.017) were detected in Herpes Simplex virus (HSV) encephalitis as compared to non-HSV encephalitis, while clinical characteristics did not differ. Normal EEG remained the strongest association with a low relative risk for death in multivariable analyses (RR<0.001, p<0.001) adjusting for confounders as coma, global cerebral edema and mechanical ventilation. None of the patients with a normal EEG had a GCS of 15. Normal EEG predicted survival independently from possible confounders, highlighting the prognostic value of EEG in evaluating patients with encephalitis. EEG revealed higher proportions of PDs along with focal slowing in HSV encephalitis as compared to other etiologies. EEG significantly adds to clinical, diagnostic and prognostic information in patients with acute encephalitis. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

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.

Combined process automation for large-scale EEG analysis.

PubMed

Sfondouris, John L; Quebedeaux, Tabitha M; Holdgraf, Chris; Musto, Alberto E

2012-01-01

Epileptogenesis is a dynamic process producing increased seizure susceptibility. Electroencephalography (EEG) data provides information critical in understanding the evolution of epileptiform changes throughout epileptic foci. We designed an algorithm to facilitate efficient large-scale EEG analysis via linked automation of multiple data processing steps. Using EEG recordings obtained from electrical stimulation studies, the following steps of EEG analysis were automated: (1) alignment and isolation of pre- and post-stimulation intervals, (2) generation of user-defined band frequency waveforms, (3) spike-sorting, (4) quantification of spike and burst data and (5) power spectral density analysis. This algorithm allows for quicker, more efficient EEG analysis. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

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.

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.

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.

A quantitative evaluation of dry-sensor electroencephalography

NASA Astrophysics Data System (ADS)

Uy, E. Timothy

Neurologists, neuroscientists, and experimental psychologists study electrical activity within the brain by recording voltage fluctuations at the scalp. This is electroencephalography (EEG). In conventional or "wet" EEG, scalp abrasion and use of electrolytic paste are required to insure good electrical connection between sensor and skin. Repeated abrasion quickly becomes irritating to subjects, severely limiting the number and frequency of sessions. Several groups have produced "dry" EEG sensors that do not require abrasion or conductive paste. These, in addition to sidestepping the issue of abrasion, promise to reduce setup time from about 30 minutes with a technician to less than 30 seconds without one. The availability of such an instrument would (1) reduce the cost of brain-related medical care, (2) lower the barrier of entry on brain experimentation, and (3) allow individual subjects to contribute substantially more data without fear of abrasion or fatigue. Accuracy of the EEG is paramount in the medical diagnosis of epilepsy, in experimental psychology and in the burgeoning field of brain-computer interface. Without a sufficiently accurate measurement, the advantages of dry sensors remain a moot point. However, even after nearly a decade, demonstrations of dry EEG accuracy with respect to wet have been limited to visual comparison of short snippets of spontaneous EEG, averaged event-related potentials or plots of power spectrum. In this dissertation, I propose a detailed methodology based on single-trial EEG classification for comparing dry EEG sensors to their wet counterparts. Applied to a set of commercially fabricated dry sensors, this work reveals that dry sensors can perform as well their wet counterparts with careful screening and attention to the bandwidth of interest.

Correlating magnetoencephalography to stereo-electroencephalography in patients undergoing epilepsy surgery

PubMed Central

Murakami, Hiroatsu; Wang, Zhong I.; Marashly, Ahmad; Krishnan, Balu; Prayson, Richard A.; Kakisaka, Yosuke; Mosher, John C.; Bulacio, Juan; Gonzalez-Martinez, Jorge A.; Bingaman, William E.; Najm, Imad M.; Burgess, Richard C.; Alexopoulos, Andreas V.

2016-01-01

See Bear and Kirsch (doi:10.1093/aww248) for a scientific commentary on this article. Magnetoencephalography and stereo-electroencephalography are often necessary in the course of the non-invasive and invasive presurgical evaluation of challenging patients with medically intractable focal epilepsies. In this study, we aim to examine the significance of magnetoencephalography dipole clusters and their relationship to stereo-electroencephalography findings, area of surgical resection, and seizure outcome. We also aim to define the positive and negative predictors based on magnetoencephalography dipole cluster characteristics pertaining to seizure-freedom. Included in this retrospective study were a consecutive series of 50 patients who underwent magnetoencephalography and stereo-electroencephalography at the Cleveland Clinic Epilepsy Center. Interictal magnetoencephalography localization was performed using a single equivalent current dipole model. Magnetoencephalography dipole clusters were classified based on tightness and orientation criteria. Magnetoencephalography dipole clusters, stereo-electroencephalography findings and area of resection were reconstructed and examined in the same space using the patient’s own magnetic resonance imaging scan. Seizure outcomes at 1 year postoperative were dichotomized into seizure-free or not seizure-free. We found that patients in whom the magnetoencephalography clusters were completely resected had a much higher chance of seizure-freedom compared to the partial and no resection groups (P = 0.007). Furthermore, patients had a significantly higher chance of being seizure-free when stereo-electroencephalography completely sampled the area identified by magnetoencephalography as compared to those with incomplete or no sampling of magnetoencephalography results (P = 0.012). Partial concordance between magnetoencephalography and interictal or ictal stereo-electroencephalography was associated with a much lower chance of seizure

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

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.

Midazolam or diazepam administration during electroencephalography helps to diagnose subacute sclerosing panencephalitis (SSPE).

PubMed

Yilmaz, Kutluhan; Sahin, Derya Aydin

2010-08-01

Although diagnostic contribution of intravenous diazepam administration during electroencephalography (EEG) recording in subacute sclerosing panencephalitis has been known, no another drug with less potential side effects has been studied in this procedure. In this study, diazepam is compared with midazolam in 25 subacute sclerosing panencephalitis-diagnosed children and 10 children with subacute sclerosing panencephalitis-suggesting symptoms, normal EEG findings and no certain diagnosis. Neither midazolam nor diazepam affected typical periodic slow-wave complexes. However, in the patients with atypical EEG abnormalities, midazolam, like diazepam, attenuated sharp or sharp-and-slow waves, and therefore made the identification of periodic slow-wave paroxysms easier. In the patients with normal EEGs, both midazolam and diazepam revealed typical periodic complexes on EEG recording in the same 3 patients. Cerebrospinal fluid examination verified the diagnosis of subacute sclerosing panencephalitis. The findings suggest that midazolam or diazepam administration increases the contribution of EEG recording in atypical cases with subacute sclerosing panencephalitis.

Hemispheric asymmetry of electroencephalography-based functional brain networks.

PubMed

Jalili, Mahdi

2014-11-12

Electroencephalography (EEG)-based functional brain networks have been investigated frequently in health and disease. It has been shown that a number of graph theory metrics are disrupted in brain disorders. EEG-based brain networks are often studied in the whole-brain framework, where all the nodes are grouped into a single network. In this study, we studied the brain networks in two hemispheres and assessed whether there are any hemispheric-specific patterns in the properties of the networks. To this end, resting state closed-eyes EEGs from 44 healthy individuals were processed and the network structures were extracted separately for each hemisphere. We examined neurophysiologically meaningful graph theory metrics: global and local efficiency measures. The global efficiency did not show any hemispheric asymmetry, whereas the local connectivity showed rightward asymmetry for a range of intermediate density values for the constructed networks. Furthermore, the age of the participants showed significant direct correlations with the global efficiency of the left hemisphere, but only in the right hemisphere, with local connectivity. These results suggest that only local connectivity of EEG-based functional networks is associated with brain hemispheres.

Older People's Experiences of Mobility and Mood in an Urban Environment: A Mixed Methods Approach Using Electroencephalography (EEG) and Interviews.

PubMed

Tilley, Sara; Neale, Chris; Patuano, Agnès; Cinderby, Steve

2017-02-04

There are concerns about mental wellbeing in later life in older people as the global population becomes older and more urbanised. Mobility in the built environment has a role to play in improving quality of life and wellbeing, as it facilitates independence and social interaction. Recent studies using neuroimaging methods in environmental psychology research have shown that different types of urban environments may be associated with distinctive patterns of brain activity, suggesting that we interact differently with varying environments. This paper reports on research that explores older people's responses to urban places and their mobility in and around the built environment. The project aim was to understand how older people experience different urban environments using a mixed methods approach including electroencephalography (EEG), self-reported measures, and interview results. We found that older participants experience changing levels of "excitement", "engagement" and "frustration" (as interpreted by proprietary EEG software) whilst walking between a busy built urban environment and an urban green space environment. These changes were further reflected in the qualitative themes that emerged from transcribed interviews undertaken one week post-walk. There has been no research to date that has directly assessed neural responses to an urban environment combined with qualitative interview analysis. A synergy of methods offers a deeper understanding of the changing moods of older people across time whilst walking in city settings.

Seizures and electroencephalography findings in 61 patients with fetal alcohol spectrum disorders.

PubMed

Boronat, S; Vicente, M; Lainez, E; Sánchez-Montañez, A; Vázquez, E; Mangado, L; Martínez-Ribot, L; Del Campo, M

2017-01-01

Fetal alcohol spectrum disorders (FASD) cause neurodevelopmental abnormalities. However, publications about epilepsy and electroencephalographic features are scarce. In this study, we prospectively performed electroencephalography (EEG) and brain magnetic resonance (MR) imaging in 61 patients with diagnosis of FASD. One patient had multiple febrile seizures with normal EEGs. Fourteen children showed EEG anomalies, including slow background activity and interictal epileptiform discharges, focal and/or generalized, and 3 of them had epilepsy. In one patient, seizures were first detected during the EEG recording and one case had an encephalopathy with electrical status epilepticus during slow sleep (ESES). Focal interictal discharges in our patients did not imply the presence of underlying visible focal brain lesions in the neuroimaging studies, such as cortical dysplasia or polymicrogyria. However, they had nonspecific brain MR abnormalities, including corpus callosum hypoplasia, vermis hypoplasia or cavum septum pellucidum. The latter was significantly more frequent in the group with EEG abnormal findings (p < 0.01). Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Continuous Monitoring via Tethered Electroencephalography of Spontaneous Recurrent Seizures in Mice

PubMed Central

Bin, Na-Ryum; Song, Hongmei; Wu, Chiping; Lau, Marcus; Sugita, Shuzo; Eubanks, James H.; Zhang, Liang

2017-01-01

We describe here a simple, cost-effective apparatus for continuous tethered electroencephalographic (EEG) monitoring of spontaneous recurrent seizures in mice. We used a small, low torque slip ring as an EEG commutator, mounted the slip ring onto a standard mouse cage and connected rotary wires of the slip ring directly to animal's implanted headset. Modifications were made in the cage to allow for a convenient installation of the slip ring and accommodation of animal ambient activity. We tested the apparatus for hippocampal EEG recordings in adult C57 black mice. Spontaneous recurrent seizures were induced using extended hippocampal kindling (≥95 daily stimulation). Control animals underwent similar hippocampal electrode implantations but no stimulations were given. Combined EEG and webcam monitoring were performed for 24 h daily for 5–9 consecutive days. During the monitoring periods, the animals moved and accessed water and food freely and showed no apparent restriction in ambient cage activities. Ictal-like hippocampal EEG discharges and concurrent convulsive behaviors that are characteristics of spontaneous recurrent seizures were reliably recorded in a majority of the monitoring experiments in extendedly kindled but not in control animals. However, 1–2 rotary wires were disconnected from the implanted headset in some animals after continuous recordings for ≥5 days. The key features and main limitations of our recording apparatus are discussed. PMID:28959196

Decoding human swallowing via electroencephalography: a state-of-the-art review

PubMed Central

Jestrović, Iva; Coyle, James L.

2015-01-01

Swallowing and swallowing disorders have garnered continuing interest over the past several decades. Electroencephalography (EEG) is an inexpensive and non-invasive procedure with very high temporal resolution which enables analysis of short and fast swallowing events, as well as an analysis of the organizational and behavioral aspects of cortical motor preparation, swallowing execution and swallowing regulation. EEG is a powerful technique which can be used alone or in combination with other techniques for monitoring swallowing, detection of swallowing motor imagery for diagnostic or biofeedback purposes, or to modulate and measure the effects of swallowing rehabilitation. This paper provides a review of the existing literature which has deployed EEG in the investigation of oropharyngeal swallowing, smell, taste and texture related to swallowing, cortical pre-motor activation in swallowing, and swallowing motor imagery detection. Furthermore, this paper provides a brief review of the different modalities of brain imaging techniques used to study swallowing brain activities, as well as the EEG components of interest for studies on swallowing and on swallowing motor imagery. Lastly, this paper provides directions for future swallowing investigations using EEG. PMID:26372528

Electroencephalography in premature and full-term infants. Developmental features and glossary.

PubMed

André, M; Lamblin, M-D; d'Allest, A M; Curzi-Dascalova, L; Moussalli-Salefranque, F; S Nguyen The, Tich; Vecchierini-Blineau, M-F; Wallois, F; Walls-Esquivel, E; Plouin, P

2010-05-01

Following the pioneering work of C. Dreyfus-Brisac and N. Monod, research into neonatal electroencephalography (EEG) has developed tremendously in France. French neurophysiologists who had been trained in Paris (France) collaborated on a joint project on the introduction, development, and currently available neonatal EEG recording techniques. They assessed the analytical criteria for the different maturational stages and standardized neonatal EEG terminology on the basis of the large amount of data available in the French and the English literature. The results of their work were presented in 1999. Since the first edition, technology has moved towards the widespread use of digitized recordings. Although the data obtained with analog recordings can be applied to digitized EEG tracings, the present edition, including new published data, is illustrated with digitized recordings. Herein, the reader can find a comprehensive description of EEG features and neonatal behavioural states at different gestational ages, and also a definition of the main aspects and patterns of both pathological and normal EEGs, presented in glossary form. In both sections, numerous illustrations have been provided. This precise neonatal EEG terminology should improve homogeneity in the analysis of neonatal EEG recordings, and facilitate the setting up of multicentric studies on certain aspects of normal EEG recordings and various pathological patterns. Copyright 2010 Elsevier Masson SAS. All rights reserved.

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.

The standardization debate: A conflation trap in critical care electroencephalography

PubMed Central

Ng, Marcus C.; Gaspard, Nicolas; Cole, Andrew J.; Hoch, Daniel B.; Cash, Sydney S.; Bianchi, Matt; O’Rourke, Deirdre A.; Rosenthal, Eric S.; Chu, Catherine J.; Westover, M. Brandon

2015-01-01

Purpose Persistent uncertainty over the clinical significance of various pathological continuous electroencephalography (cEEG) findings in the intensive care unit (ICU) has prompted efforts to standardize ICU cEEG terminology and an ensuing debate. We set out to understand the reasons for, and a satisfactory resolution to, this debate. Method We review the positions for and against standardization, and examine their deeper philosophical basis. Results We find that the positions for and against standardization are not fundamentally irreconcilable. Rather, both positions stem from conflating the three cardinal steps in the classic approach to EEG, which we term “description”, “interpretation”, and “prescription”. Using real-world examples we show how this conflation yields muddled clinical reasoning and unproductive debate among electroencephalographers that is translated into confusion among treating clinicians. We propose a middle way that judiciously uses both standardized terminology and clinical reasoning to disentangle these critical steps and apply them in proper sequence. Conclusion The systematic approach to ICU cEEG findings presented herein not only resolves the standardization debate but also clarifies clinical reasoning by helping electroencephalographers assign appropriate weights to cEEG findings in the face of uncertainty. PMID:25457454

The standardization debate: A conflation trap in critical care electroencephalography.

PubMed

Ng, Marcus C; Gaspard, Nicolas; Cole, Andrew J; Hoch, Daniel B; Cash, Sydney S; Bianchi, Matt; O'Rourke, Deirdre A; Rosenthal, Eric S; Chu, Catherine J; Westover, M Brandon

2015-01-01

Persistent uncertainty over the clinical significance of various pathological continuous electroencephalography (cEEG) findings in the intensive care unit (ICU) has prompted efforts to standardize ICU cEEG terminology and an ensuing debate. We set out to understand the reasons for, and a satisfactory resolution to, this debate. We review the positions for and against standardization, and examine their deeper philosophical basis. We find that the positions for and against standardization are not fundamentally irreconcilable. Rather, both positions stem from conflating the three cardinal steps in the classic approach to EEG, which we term "description", "interpretation", and "prescription". Using real-world examples we show how this conflation yields muddled clinical reasoning and unproductive debate among electroencephalographers that is translated into confusion among treating clinicians. We propose a middle way that judiciously uses both standardized terminology and clinical reasoning to disentangle these critical steps and apply them in proper sequence. The systematic approach to ICU cEEG findings presented herein not only resolves the standardization debate but also clarifies clinical reasoning by helping electroencephalographers assign appropriate weights to cEEG findings in the face of uncertainty. Copyright © 2014 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Novel bifunctional cap for simultaneous electroencephalography and transcranial electrical stimulation.

PubMed

Wunder, Sophia; Hunold, Alexander; Fiedler, Patrique; Schlegelmilch, Falk; Schellhorn, Klaus; Haueisen, Jens

2018-05-08

Neuromodulation induced by transcranial electric stimulation (TES) exhibited promising potential for clinical practice. However, the underlying mechanisms remain subject of research. The combination of TES and electroencephalography (EEG) offers great potential for investigating these mechanisms and brain function in general, especially when performed simultaneously. In conventional applications, the combination of EEG and TES suffers from limitations on the electrode level (gel for electrode-skin interface) and the usability level (preparation time, reproducibility of positioning). To overcome these limitations, we designed a bifunctional cap for simultaneous TES-EEG applications. We used novel electrode materials, namely textile stimulation electrodes and dry EEG electrodes integrated in a flexible textile cap. We verified the functionality of this cap by analysing the effect of TES on visual evoked potentials (VEPs). In accordance with previous reports using standard TES, the amplitude of the N75 component was significantly decreased post-stimulation, indicating the feasibility of using this novel flexible cap for simultaneous TES and EEG. Further, we found a significant reduction of the P100 component only during TES, indicating a different brain modulation effect during and after TES. In conclusion, the novel bifunctional cap offers a novel tool for simultaneous TES-EEG applications in clinical research, therapy monitoring and closed-loop stimulation.

Protocol Based Real-Time Continuous Electroencephalography for Detecting Vasospasm in Subarachnoid Hemorrhage.

PubMed

Hong, Jeong-Ho; Bang, Jae Seung; Chung, Jin-Heon; Han, Moon-Ku

2016-03-01

A continuous electroencephalography (cEEG) can be helpful in detecting vasospasm and delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage (SAH). We describe a patient with an aneurysmal SAH whose symptomatic vasospasm was detected promptly by using a real-time cEEG. Patient was immediately treated by intraarterial vasodilator therapy. A 50-year-old woman without any significant medical history presented with a severe bifrontal headache due to acute SAH with a ruptured aneurysm on the anterior communicating artery (Fisher grade 3). On bleed day 6, she developed a sudden onset of global aphasia and left hemiparesis preceded by cEEG changes consistent with vasospasm. A stat chemical dilator therapy was performed and she recovered without significant neurological deficits. A real-time and protocol-based cEEG can be utilized in order to avoid any delay in detection of vasospasm in aneurysmal SAH and thereby improve clinical outcomes.

Cot-side electroencephalography monitoring is not clinically useful in the detection of mild neonatal hypoglycemia.

PubMed

Harris, Deborah L; Weston, Philip J; Williams, Christopher E; Pleasants, Anthony B; Battin, Malcolm R; Spooner, Claire G; Harding, Jane E

2011-11-01

To determine whether there is a relationship between electroencephalography patterns and hypoglycemia, by using simultaneous cot-side amplitude integrated electroencephalography (aEEG) and continuous interstitial glucose monitoring, and whether non-glucose cerebral fuels modified these patterns. Eligible babies were ≥ 32 weeks gestation, at risk for hypoglycemia, and admitted to the neonatal intensive care unit. Electrodes were placed in C3-P3, C4-P4 O1-O2 montages. A continuous interstitial glucose sensor was placed subcutaneously, and blood glucose was measured by using the glucose oxidase method. Non-glucose cerebral fuels were measured at study entry, exit, and during recognized hypoglycemia. A total of 101 babies were enrolled, with a median weight of 2179 g and gestation of 35 weeks. Twenty-four of the babies had aEEG recordings, and glucose concentrations were low (< 2.6 mM). There were 103 episodes of low glucose concentrations lasting 5 to 475 minutes, but no observable changes in aEEG variables. Plasma concentrations of lactate, beta-hydroxybutyrate, and glycerol were low and did not alter during hypoglycemia. Cot-side aEEG was not useful for the detection of neurological changes during mild hypoglycemia. Plasma concentrations of non-glucose cerebral fuels were low and unlikely to provide substantial neuroprotection. Copyright © 2011 Mosby, Inc. All rights reserved.

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.

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.

EEG Estimates of Cognitive Workload and Engagement Predict Math Problem Solving Outcomes

ERIC Educational Resources Information Center

Beal, Carole R.; Galan, Federico Cirett

2012-01-01

In the present study, the authors focused on the use of electroencephalography (EEG) data about cognitive workload and sustained attention to predict math problem solving outcomes. EEG data were recorded as students solved a series of easy and difficult math problems. Sequences of attention and cognitive workload estimates derived from the EEG…

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.

Older People’s Experiences of Mobility and Mood in an Urban Environment: A Mixed Methods Approach Using Electroencephalography (EEG) and Interviews

PubMed Central

Tilley, Sara; Neale, Chris; Patuano, Agnès; Cinderby, Steve

2017-01-01

There are concerns about mental wellbeing in later life in older people as the global population becomes older and more urbanised. Mobility in the built environment has a role to play in improving quality of life and wellbeing, as it facilitates independence and social interaction. Recent studies using neuroimaging methods in environmental psychology research have shown that different types of urban environments may be associated with distinctive patterns of brain activity, suggesting that we interact differently with varying environments. This paper reports on research that explores older people’s responses to urban places and their mobility in and around the built environment. The project aim was to understand how older people experience different urban environments using a mixed methods approach including electroencephalography (EEG), self-reported measures, and interview results. We found that older participants experience changing levels of “excitement”, “engagement” and “frustration” (as interpreted by proprietary EEG software) whilst walking between a busy built urban environment and an urban green space environment. These changes were further reflected in the qualitative themes that emerged from transcribed interviews undertaken one week post-walk. There has been no research to date that has directly assessed neural responses to an urban environment combined with qualitative interview analysis. A synergy of methods offers a deeper understanding of the changing moods of older people across time whilst walking in city settings. PMID:28165409

Electroencephalography signatures of attention-deficit/hyperactivity disorder: clinical utility.

PubMed

Alba, Guzmán; Pereda, Ernesto; Mañas, Soledad; Méndez, Leopoldo D; González, Almudena; González, Julián J

2015-01-01

The techniques and the most important results on the use of electroencephalography (EEG) to extract different measures are reviewed in this work, which can be clinically useful to study subjects with attention-deficit/hyperactivity disorder (ADHD). First, we discuss briefly and in simple terms the EEG analysis and processing techniques most used in the context of ADHD. We review techniques that both analyze individual EEG channels (univariate measures) and study the statistical interdependence between different EEG channels (multivariate measures), the so-called functional brain connectivity. Among the former ones, we review the classical indices of absolute and relative spectral power and estimations of the complexity of the channels, such as the approximate entropy and the Lempel-Ziv complexity. Among the latter ones, we focus on the magnitude square coherence and on different measures based on the concept of generalized synchronization and its estimation in the state space. Second, from a historical point of view, we present the most important results achieved with these techniques and their clinical utility (sensitivity, specificity, and accuracy) to diagnose ADHD. Finally, we propose future research lines based on these results.

Brainstorm: A User-Friendly Application for MEG/EEG Analysis

PubMed Central

Tadel, François; Baillet, Sylvain; Mosher, John C.; Pantazis, Dimitrios; Leahy, Richard M.

2011-01-01

Brainstorm is a collaborative open-source application dedicated to magnetoencephalography (MEG) and electroencephalography (EEG) data visualization and processing, with an emphasis on cortical source estimation techniques and their integration with anatomical magnetic resonance imaging (MRI) data. The primary objective of the software is to connect MEG/EEG neuroscience investigators with both the best-established and cutting-edge methods through a simple and intuitive graphical user interface (GUI). PMID:21584256

Electroencephalography (EEG) Based Control in Assistive Mobile Robots: A Review

NASA Astrophysics Data System (ADS)

Krishnan, N. Murali; Mariappan, Muralindran; Muthukaruppan, Karthigayan; Hijazi, Mohd Hanafi Ahmad; Kitt, Wong Wei

2016-03-01

Recently, EEG based control in assistive robot usage has been gradually increasing in the area of biomedical field for giving quality and stress free life for disabled and elderly people. This study reviews the deployment of EGG based control in assistive robots, especially for those who in need and neurologically disabled. The main objective of this paper is to describe the methods used for (i) EEG data acquisition and signal preprocessing, (ii) feature extraction and (iii) signal classification methods. Besides that, this study presents the specific research challenges in the designing of these control systems and future research directions.

Decoding of intentional actions from scalp electroencephalography (EEG) in freely-behaving infants.

PubMed

Hernandez, Zachery R; Cruz-Garza, Jesus; Tse, Teresa; Contreras-Vidal, Jose L

2014-01-01

The mirror neuron system (MNS) in humans is thought to enable an individual's understanding of the meaning of actions performed by others and the potential imitation and learning of those actions. In humans, electroencephalographic (EEG) changes in sensorimotor a-band at central electrodes, which desynchronizes both during execution and observation of goal-directed actions (i.e., μ suppression), have been considered an analog to MNS function. However, methodological and developmental issues, as well as the nature of generalized μ suppression to imagined, observed, and performed actions, have yet to provide a mechanistic relationship between EEG μ-rhythm and MNS function, and the extent to which EEG can be used to infer intent during MNS tasks remains unknown. In this study we present a novel methodology using active EEG and inertial sensors to record brain activity and behavioral actions from freely-behaving infants during exploration, imitation, attentive rest, pointing, reaching and grasping, and interaction with an actor. We used 5-band (1-4Hz) EEG as input to a dimensionality reduction algorithm (locality-preserving Fisher's discriminant analysis, LFDA) followed by a neural classifier (Gaussian mixture models, GMMs) to decode the each MNS task performed by freely-behaving 6-24 month old infants during interaction with an adult actor. Here, we present results from a 20-month male infant to illustrate our approach and show the feasibility of EEG-based classification of freely occurring MNS behaviors displayed by an infant. These results, which provide an alternative to the μ-rhythm theory of MNS function, indicate the informative nature of EEG in relation to intentionality (goal) for MNS tasks which may support action-understanding and thus bear implications for advancing the understanding of MNS function.

Fuzzy topological digital space and their properties of flat electroencephalography in epilepsy disease

NASA Astrophysics Data System (ADS)

Muzafar Shah, Mazlina; Fatah Wahab, Abdul

2017-09-01

There are an abnormal electric activities or irregular interference in brain of epilepsy patient. Then a sensor will be put in patient’s scalp to measure and records all electric activities in brain. The result of the records known as Electroencephalography (EEG). The EEG has been transfer to flat EEG because it’s easier to analyze. In this study, the uncertainty in flat EEG data will be considered as fuzzy digital space. The purpose of this research is to show that the flat EEG is fuzzy topological digital space. Therefore, the main focus for this research is to introduce fuzzy topological digital space concepts with their properties such as neighbourhood, interior and closure by using fuzzy set digital concept and Chang’s fuzzy topology approach. The product fuzzy topology digital also will be shown. By introduce this concept, the data in flat EEG can considering having fuzzy topology digital properties and can identify the area in fuzzy digital space that has been affected by epilepsy seizure in epileptic patient’s brain.

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.

[Electroencephalography (EEG) recording techniques and artifact detection in early premature babies].

PubMed

Wallois, F; Vecchierini, M-F; Héberlé, C; Walls-Esquivel, E

2007-01-01

EEG recording techniques in early premature babies are not very different from those used for full-term neonates. Here, we emphasise the most important points: asepsis precautions, full knowledge of the clinical data and drug therapies, the fundamental role of a well-trained technician in supervising the EEG recording and monitoring the baby. The best electrode positions, the most informative montages and their standardisation between neurophysiological laboratories, are suggested. Artifact detection constitutes an important aspect of EEG signal analysis in preterm babies of less than 30 weeks. It is obviously necessary to discriminate between meaningful information and artefacts. The complexity of the signal in neonates makes artifact detection difficult. We present some characteristic features and describe some methods for eliminating them. We underline the positive aspect of some artifacts and their clinical use. We emphasise the crucial role of the technicians.

Inter-hemispheric electroencephalography coherence analysis: assessing brain activity during monotonous driving.

PubMed

Jap, Budi Thomas; Lal, Sara; Fischer, Peter

2010-06-01

The current study investigated the effect of monotonous driving on inter-hemispheric electroencephalography (EEG) coherence. Twenty-four non-professional drivers were recruited to perform a fatigue instigating monotonous driving task while 30 channels of EEG were simultaneously recorded. The EEG recordings were then divided into 5 equal sections over the entire driving period for analysis. Inter-hemispheric coherence was computed from 5 homologous EEG electrode pairs (FP1-FP2, C3-C4, T7-T8, P7-P8, and O1-O2) for delta, theta, alpha and beta frequency bands. Results showed that frontal and occipital inter-hemispheric coherence values were significantly higher than central, parietal, and temporal sites for all four frequency bands (p<0.0001). In the alpha frequency band, significant difference was found between earlier and later driving sections (p=0.02). The coherence values in all EEG frequency bands were slightly increased at the end of the driving session, except for FP1-FP2 electrode pair, which showed no significant change in coherence in the beta frequency band at the end of the driving session. Copyright 2010 Elsevier B.V. All rights reserved.

Human electroencephalography and the tobacco industry: a review of internal documents.

PubMed

Panzano, Vincent C; Wayne, Geoffrey Ferris; Pickworth, Wallace B; Connolly, Gregory N

2010-04-01

To determine the extent and implications of internal human electroencephalography (EEG) research conducted by the tobacco industry. This study analysed internal documents that describe the results of human EEG studies conducted by tobacco manufacturers. Emphasis was placed on documents that pertain to the application of EEG to product evaluation efforts. Internal EEG research was used to determine dose-response relations and effective threshold levels for nicotine, emphasising the importance of form and mechanism of nicotine delivery for initiating robust central nervous system (CNS) effects. Internal studies also highlight the importance of human behaviour during naturalistic smoking, revealing neurophysiological markers of compensation during smoking of reduced nicotine cigarettes. Finally, internal research demonstrates the effectiveness of EEG for the evaluation of non-nicotine phenomena including smoke-component discrimination by smokers, classification of sensory characteristics and measurement of hedonics and other subjective effects. Tobacco manufacturers successfully developed objective, EEG-based techniques to evaluate the influence of product characteristics on acceptance and use. Internal results suggest that complex interactions between pharmacological, sensory and behavioural factors mediate the brain changes that occur with smoking. These findings have implications for current proposals regarding the regulation of tobacco products and argue for the incorporation of objective measures of product effects when evaluating the health risks of new and existing tobacco products.

An adaptive singular spectrum analysis method for extracting brain rhythms of electroencephalography

PubMed Central

Hu, Hai; Guo, Shengxin; Liu, Ran

2017-01-01

Artifacts removal and rhythms extraction from electroencephalography (EEG) signals are important for portable and wearable EEG recording devices. Incorporating a novel grouping rule, we proposed an adaptive singular spectrum analysis (SSA) method for artifacts removal and rhythms extraction. Based on the EEG signal amplitude, the grouping rule determines adaptively the first one or two SSA reconstructed components as artifacts and removes them. The remaining reconstructed components are then grouped based on their peak frequencies in the Fourier transform to extract the desired rhythms. The grouping rule thus enables SSA to be adaptive to EEG signals containing different levels of artifacts and rhythms. The simulated EEG data based on the Markov Process Amplitude (MPA) EEG model and the experimental EEG data in the eyes-open and eyes-closed states were used to verify the adaptive SSA method. Results showed a better performance in artifacts removal and rhythms extraction, compared with the wavelet decomposition (WDec) and another two recently reported SSA methods. Features of the extracted alpha rhythms using adaptive SSA were calculated to distinguish between the eyes-open and eyes-closed states. Results showed a higher accuracy (95.8%) than those of the WDec method (79.2%) and the infinite impulse response (IIR) filtering method (83.3%). PMID:28674650

Characterization of electroencephalography signals for estimating saliency features in videos.

PubMed

Liang, Zhen; Hamada, Yasuyuki; Oba, Shigeyuki; Ishii, Shin

2018-05-12

Understanding the functions of the visual system has been one of the major targets in neuroscience formany years. However, the relation between spontaneous brain activities and visual saliency in natural stimuli has yet to be elucidated. In this study, we developed an optimized machine learning-based decoding model to explore the possible relationships between the electroencephalography (EEG) characteristics and visual saliency. The optimal features were extracted from the EEG signals and saliency map which was computed according to an unsupervised saliency model ( Tavakoli and Laaksonen, 2017). Subsequently, various unsupervised feature selection/extraction techniques were examined using different supervised regression models. The robustness of the presented model was fully verified by means of ten-fold or nested cross validation procedure, and promising results were achieved in the reconstruction of saliency features based on the selected EEG characteristics. Through the successful demonstration of using EEG characteristics to predict the real-time saliency distribution in natural videos, we suggest the feasibility of quantifying visual content through measuring brain activities (EEG signals) in real environments, which would facilitate the understanding of cortical involvement in the processing of natural visual stimuli and application developments motivated by human visual processing. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

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.

Brain Monitoring with Electroencephalography and the Electroencephalogram-Derived Bispectral Index During Cardiac Surgery

PubMed Central

Kertai, Miklos D.; Whitlock, Elizabeth L.; Avidan, Michael S.

2011-01-01

Cardiac surgery presents particular challenges for the anesthesiologist. In addition to standard and advanced monitors typically used during cardiac surgery, anesthesiologists may consider monitoring the brain with raw or processed electroencephalography (EEG). There is strong evidence that a protocol incorporating the processed EEG Bispectral Index (BIS) decreases the incidence intraoperative awareness compared with standard practice. However there is conflicting evidence that incorporating the BIS into cardiac anesthesia practice improves “fast-tracking,” decreases anesthetic drug use, or detects cerebral ischemia. Recent research, including many cardiac surgical patients, shows that a protocol based on BIS monitoring is not superior to a protocol based on end tidal anesthetic concentration monitoring in preventing awareness. There has been a resurgence of interest in the anesthesia literature in limited montage EEG monitoring, including nonproprietary processed indices. This has been accompanied by research showing that with structured training, anesthesiologists can glean useful information from the raw EEG trace. In this review, we discuss both the hypothesized benefits and limitations of BIS and frontal channel EEG monitoring in the cardiac surgical population. PMID:22253267

Neural signatures of economic parameters during decision-making: a functional MRI (FMRI), electroencephalography (EEG) and autonomic monitoring study.

PubMed

Minati, Ludovico; Grisoli, Marina; Franceschetti, Silvana; Epifani, Francesca; Granvillano, Alice; Medford, Nick; Harrison, Neil A; Piacentini, Sylvie; Critchley, Hugo D

2012-01-01

Adaptive behaviour requires an ability to obtain rewards by choosing between different risky options. Financial gambles can be used to study effective decision-making experimentally, and to distinguish processes involved in choice option evaluation from outcome feedback and other contextual factors. Here, we used a paradigm where participants evaluated 'mixed' gambles, each presenting a potential gain and a potential loss and an associated variable outcome probability. We recorded neural responses using autonomic monitoring, electroencephalography (EEG) and functional neuroimaging (fMRI), and used a univariate, parametric design to test for correlations with the eleven economic parameters that varied across gambles, including expected value (EV) and amount magnitude. Consistent with behavioural economic theory, participants were risk-averse. Gamble evaluation generated detectable autonomic responses, but only weak correlations with outcome uncertainty were found, suggesting that peripheral autonomic feedback does not play a major role in this task. Long-latency stimulus-evoked EEG potentials were sensitive to expected gain and expected value, while alpha-band power reflected expected loss and amount magnitude, suggesting parallel representations of distinct economic qualities in cortical activation and central arousal. Neural correlates of expected value representation were localized using fMRI to ventromedial prefrontal cortex, while the processing of other economic parameters was associated with distinct patterns across lateral prefrontal, cingulate, insula and occipital cortices including default-mode network and early visual areas. These multimodal data provide complementary evidence for distributed substrates of choice evaluation across multiple, predominantly cortical, brain systems wherein distinct regions are preferentially attuned to specific economic features. Our findings extend biologically-plausible models of risky decision-making while providing

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.

Memory-Augmented Active Deep Learning for Identifying Relations Between Distant Medical Concepts in Electroencephalography Reports.

PubMed

Maldonado, Ramon; Goodwin, Travis R; Harabagiu, Sanda M

2018-01-01

The automatic identification of relations between medical concepts in a large corpus of Electroencephalography (EEG) reports is an important step in the development of an EEG-specific patient cohort retrieval system as well as in the acquisition of EEG-specific knowledge from this corpus. EEG-specific relations involve medical concepts that are not typically mentioned in the same sentence or even the same section of a report, thus requiring extraction techniques that can handle such long-distance dependencies. To address this challenge, we present a novel frame work which combines the advantages of a deep learning framework employing Dynamic Relational Memory (DRM) with active learning. While DRM enables the prediction of long-distance relations, active learning provides a mechanism for accurately identifying relations with minimal training data, obtaining an 5-fold cross validationF1 score of 0.7475 on a set of 140 EEG reports selected with active learning. The results obtained with our novel framework show great promise.

Prognostic value of continuous electroencephalography monitoring in children with severe brain damage.

PubMed

Lan, Yan-huai; Zhu, Xiao-mei; Zhou, Yuan-feng; Qiu, Peng-ling; Lu, Guo-ping; Sun, Dao-kai; Wang, Yi

2015-06-01

The purpose of this study is to determine whether there is a relationship between continuous electroencephalography (EEG) monitoring patterns and prognosis for children with severe brain damage. Patients and The different patterns of EEG were analyzed for 103 children (Glasgow Coma Scale [GCS] score < 8) who were monitored with continuous video-EEG (CVEEG) within 72 hours after the onset of coma. The clinical outcomes were scored and evaluated at hospital discharge by the modified Pediatric Cerebral and Overall Performance Category Scale (PCOPCS). EEG parameters of the different prognosis groups were compared and risk factors for prognosis were identified. Of the 103 children, 36 were in the good prognosis group (PCOPCS scores 1 and 2) and 67 were in the poor prognosis group (PCOPCS scores 3-6). The poor prognosis group had the lower proportion of events in reactive EEG patterns and sleep architecture, and a higher proportion of low-voltage events. Multivariate analyses showed that the lower GCS score and no sleep architecture were significantly associated with poor prognosis. Comatose children with higher GCS score and sleep architecture have better clinical outcomes in terms of morbidity and mortality. Georg Thieme Verlag KG Stuttgart · New York.

Childhood temporal lobe epilepsy: correlation between electroencephalography and magnetic resonance spectroscopy: a case-control study.

PubMed

Azab, Seham Fa; Sherief, Laila M; Saleh, Safaa H; Elshafeiy, Mona M; Siam, Ahmed G; Elsaeed, Wafaa F; Arafa, Mohamed A; Bendary, Eman A; Sherbiny, Hanan S; Elbehedy, Rabab M; Aziz, Khalid A

2015-04-18

The diagnosis of epilepsy should be made as early as possible to give a child the best chance for treatment success and also to decrease complications such as learning difficulties and social and behavioral problems. In this study, we aimed to assess the ability of magnetic resonance spectroscopy (MRS) in detecting the lateralization side in patients with Temporal lobe epilepsy (TLE) in correlation with EEG and MRI findings. This was a case-control study including 40 patients diagnosed (clinically and by EEG) as having temporal lobe epilepsy aged 8 to 14 years (mean, 10.4 years) and 20 healthy children with comparable age and gender as the control group. All patients were subjected to clinical examination, interictal electroencephalography and magnetic resonance imaging (MRI). Proton magnetic resonance spectroscopic examination (MRS) was performed to the patients and the controls. According to the findings of electroencephalography, our patients were classified to three groups: Group 1 included 20 patients with unitemporal (lateralized) epileptic focus, group 2 included 12 patients with bitemporal (non-lateralized) epileptic focus and group 3 included 8 patients with normal electroencephalography. Magnetic resonance spectroscopy could lateralize the epileptic focus in 19 patients in group 1, nine patients in group2 and five patients in group 3 with overall lateralization of (82.5%), while electroencephalography was able to lateralize the focus in (50%) of patients and magnetic resonance imaging detected lateralization of mesial temporal sclerosis in (57.5%) of patients. Magnetic resonance spectroscopy is a promising tool in evaluating patients with epilepsy and offers increased sensitivity to detect temporal pathology that is not obvious on structural MRI imaging.

High-throughput ocular artifact reduction in multichannel electroencephalography (EEG) using component subspace projection.

PubMed

Ma, Junshui; Bayram, Sevinç; Tao, Peining; Svetnik, Vladimir

2011-03-15

After a review of the ocular artifact reduction literature, a high-throughput method designed to reduce the ocular artifacts in multichannel continuous EEG recordings acquired at clinical EEG laboratories worldwide is proposed. The proposed method belongs to the category of component-based methods, and does not rely on any electrooculography (EOG) signals. Based on a concept that all ocular artifact components exist in a signal component subspace, the method can uniformly handle all types of ocular artifacts, including eye-blinks, saccades, and other eye movements, by automatically identifying ocular components from decomposed signal components. This study also proposes an improved strategy to objectively and quantitatively evaluate artifact reduction methods. The evaluation strategy uses real EEG signals to synthesize realistic simulated datasets with different amounts of ocular artifacts. The simulated datasets enable us to objectively demonstrate that the proposed method outperforms some existing methods when no high-quality EOG signals are available. Moreover, the results of the simulated datasets improve our understanding of the involved signal decomposition algorithms, and provide us with insights into the inconsistency regarding the performance of different methods in the literature. The proposed method was also applied to two independent clinical EEG datasets involving 28 volunteers and over 1000 EEG recordings. This effort further confirms that the proposed method can effectively reduce ocular artifacts in large clinical EEG datasets in a high-throughput fashion. Copyright © 2011 Elsevier B.V. All rights reserved.

Effects of Cable Sway, Electrode Surface Area, and Electrode Mass on Electroencephalography Signal Quality during Motion.

PubMed

Symeonidou, Evangelia-Regkina; Nordin, Andrew D; Hairston, W David; Ferris, Daniel P

2018-04-03

More neuroscience researchers are using scalp electroencephalography (EEG) to measure electrocortical dynamics during human locomotion and other types of movement. Motion artifacts corrupt the EEG and mask underlying neural signals of interest. The cause of motion artifacts in EEG is often attributed to electrode motion relative to the skin, but few studies have examined EEG signals under head motion. In the current study, we tested how motion artifacts are affected by the overall mass and surface area of commercially available electrodes, as well as how cable sway contributes to motion artifacts. To provide a ground-truth signal, we used a gelatin head phantom with embedded antennas broadcasting electrical signals, and recorded EEG with a commercially available electrode system. A robotic platform moved the phantom head through sinusoidal displacements at different frequencies (0-2 Hz). Results showed that a larger electrode surface area can have a small but significant effect on improving EEG signal quality during motion and that cable sway is a major contributor to motion artifacts. These results have implications in the development of future hardware for mobile brain imaging with EEG.

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

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.

Clinical review: Continuous and simplified electroencephalography to monitor brain recovery after cardiac arrest

PubMed Central

2013-01-01

There has been a dramatic change in hospital care of cardiac arrest survivors in recent years, including the use of target temperature management (hypothermia). Clinical signs of recovery or deterioration, which previously could be observed, are now concealed by sedation, analgesia, and muscle paralysis. Seizures are common after cardiac arrest, but few centers can offer high-quality electroencephalography (EEG) monitoring around the clock. This is due primarily to its complexity and lack of resources but also to uncertainty regarding the clinical value of monitoring EEG and of treating post-ischemic electrographic seizures. Thanks to technical advances in recent years, EEG monitoring has become more available. Large amounts of EEG data can be linked within a hospital or between neighboring hospitals for expert opinion. Continuous EEG (cEEG) monitoring provides dynamic information and can be used to assess the evolution of EEG patterns and to detect seizures. cEEG can be made more simple by reducing the number of electrodes and by adding trend analysis to the original EEG curves. In our version of simplified cEEG, we combine a reduced montage, displaying two channels of the original EEG, with amplitude-integrated EEG trend curves (aEEG). This is a convenient method to monitor cerebral function in comatose patients after cardiac arrest but has yet to be validated against the gold standard, a multichannel cEEG. We recently proposed a simplified system for interpreting EEG rhythms after cardiac arrest, defining four major EEG patterns. In this topical review, we will discuss cEEG to monitor brain function after cardiac arrest in general and how a simplified cEEG, with a reduced number of electrodes and trend analysis, may facilitate and improve care. PMID:23876221

Use Case Analysis: The Ambulatory EEG in Navy Medicine for Traumatic Brain Injuries

DTIC Science & Technology

2016-12-01

best uses of the device for naval medicine. 14. SUBJECT TERMS traumatic brain injuries, electroencephalography, EEG, use case study 15. NUMBER OF...Traumatic Brain Injury NCS Non-Convulsive Seizures PD Parkinson’s Disease QEEG Quantitative EEG SPECT Single-Photon Emission Computerized Tomography...INTENTIONALLY LEFT BLANK 1 I. INTRODUCTION This study examines the diagnosis of traumatic brain injuries (TBI). Early detection and diagnosis is

TMS-EEG: From basic research to clinical applications

NASA Astrophysics Data System (ADS)

Hernandez-Pavon, Julio C.; Sarvas, Jukka; Ilmoniemi, Risto J.

2014-11-01

Transcranial magnetic stimulation (TMS) combined with electroencephalography (EEG) is a powerful technique for non-invasively studying cortical excitability and connectivity. The combination of TMS and EEG has widely been used to perform basic research and recently has gained importance in different clinical applications. In this paper, we will describe the physical and biological principles of TMS-EEG and different applications in basic research and clinical applications. We will present methods based on independent component analysis (ICA) for studying the TMS-evoked EEG responses. These methods have the capability to remove and suppress large artifacts, making it feasible, for instance, to study language areas with TMS-EEG. We will discuss the different applications and limitations of TMS and TMS-EEG in clinical applications. Potential applications of TMS are presented, for instance in neurosurgical planning, depression and other neurological disorders. Advantages and disadvantages of TMS-EEG and its variants such as repetitive TMS (rTMS) are discussed in comparison to other brain stimulation and neuroimaging techniques. Finally, challenges that researchers face when using this technique will be summarized.

Identification of the epileptogenic zone of temporal lobe epilepsy from stereo-electroencephalography signals: A phase transfer entropy and graph theory approach.

PubMed

Wang, Meng-Yang; Wang, Jing; Zhou, Jian; Guan, Yu-Guang; Zhai, Feng; Liu, Chang-Qing; Xu, Fei-Fei; Han, Yi-Xian; Yan, Zhao-Fen; Luan, Guo-Ming

2017-01-01

The aim of this research is to apply an approach based on phase transfer entropy (PTE) and graph theory to study the interactions between the stereo-electroencephalography (SEEG) activities recorded in multilobar origin, in order to evaluate their ability to detect the epileptogenic zone (EZ) of temporal lobe epilepsies (TLE). Forty-three patients were included in this retrospective study. Five to sixteen (median = 12) multilead electrodes were implanted per patient, and, for each patient, a sub-set of between 10 and 32 (median = 22) bipolar derivations was selected for analysis. The leads were classified into the onset leads (OLs), the early propagation leads (EPLs), and the rest of the leads (RLs). The results showed that a significantly different dynamic trend of the out/in ratio (more obvious in the gamma band) distinguishes the OLs from RLs in the 23 patients who were seizure-free not only during the ictal event (significant elevation), but also during the inter-,pre-, late-ictal periods, and especially in the post-ictal (sharp decline) state. However, in the 20 patients who were not-seizure-free, the differences between the OLs and RLs during the post-ictal period were not found in any frequency band. The dynamic trend was used to predict surgical outcome, and the results showed that the sensitivity was 91% and the specificity was 70%. In brief, this study indicates that our approach may add new and valuable information, providing efficient quantitative measures useful for localizing the EZ.

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.

Validation of a low-cost EEG device for mood induction studies.

PubMed

Rodríguez, Alejandro; Rey, Beatriz; Alcañiz, Mariano

2013-01-01

New electroencephalography (EEG) devices, more portable and cheaper, are appearing on the market. Studying the reliability of these EEG devices for emotional studies would be interesting, as these devices could be more economical and compatible with Virtual Reality (VR) settings. Therefore, the aim in this work was to validate a low-cost EEG device (Emotiv Epoc) to monitor brain activity during a positive emotional induction procedure. Emotional pictures (IAPS) were used to induce a positive mood in sixteen participants. Changes in the brain activity of subjects were compared between positive induction and neutral conditions. Obtained results were in accordance with previous scientific literature regarding frontal EEG asymmetry, which supports the possibility of using this low-cost EEG device in future mood induction studies combined with VR.

Emotion Regulation Training for Treating Warfighters with Combat-Related PTSD Using Real-Time fMRI and EEG-Assisted Neurofeedback

DTIC Science & Technology

2014-10-01

Real-Time fMRI and EEG -Assisted Neurofeedback . PRINCIPAL INVESTIGATOR: Jerzy Bodurka RECIPIENT: Laureate Institute for Brain Research REPORT...imaging neurofeedback (rtfMRI-nf) training with concurrent electroencephalography ( EEG ) recordings to directly target and modulate the emotion...the project and are actively enrolling veterans to complete rtfMRI-nf neurofeedback training with simultaneous EEG recordings, and a pre-, post

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.

Automated Detection of Electroencephalography Artifacts in Human, Rodent and Canine Subjects using Machine Learning.

PubMed

Levitt, Joshua; Nitenson, Adam; Koyama, Suguru; Heijmans, Lonne; Curry, James; Ross, Jason T; Kamerling, Steven; Saab, Carl Y

2018-06-23

Electroencephalography (EEG) invariably contains extra-cranial artifacts that are commonly dealt with based on qualitative and subjective criteria. Failure to account for EEG artifacts compromises data interpretation. We have developed a quantitative and automated support vector machine (SVM)-based algorithm to accurately classify artifactual EEG epochs in awake rodent, canine and humans subjects. An embodiment of this method also enables the determination of 'eyes open/closed' states in human subjects. The levels of SVM accuracy for artifact classification in humans, Sprague Dawley rats and beagle dogs were 94.17%, 83.68%, and 85.37%, respectively, whereas 'eyes open/closed' states in humans were labeled with 88.60% accuracy. Each of these results was significantly higher than chance. Comparison with Existing Methods: Other existing methods, like those dependent on Independent Component Analysis, have not been tested in non-human subjects, and require full EEG montages, instead of only single channels, as this method does. We conclude that our EEG artifact detection algorithm provides a valid and practical solution to a common problem in the quantitative analysis and assessment of EEG in pre-clinical research settings across evolutionary spectra. Copyright © 2018. Published by Elsevier B.V.

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.

Design, Fabrication, and Experimental Validation of Novel Flexible Silicon-Based Dry Sensors for Electroencephalography Signal Measurements.

PubMed

Yu, Yi-Hsin; Lu, Shao-Wei; Liao, Lun-De; Lin, Chin-Teng

2014-01-01

Many commercially available electroencephalography (EEG) sensors, including conventional wet and dry sensors, can cause skin irritation and user discomfort owing to the foreign material. The EEG products, especially sensors, highly prioritize the comfort level during devices wear. To overcome these drawbacks for EEG sensors, this paper designs Societe Generale de Surveillance S [Formula: see text] A [Formula: see text] (SGS)-certified, silicon-based dry-contact EEG sensors (SBDSs) for EEG signal measurements. According to the SGS testing report, SBDSs extract does not irritate skin or induce noncytotoxic effects on L929 cells according to ISO10993-5. The SBDS is also lightweight, flexible, and nonirritating to the skin, as well as capable of easily fitting to scalps without any skin preparation or use of a conductive gel. For forehead and hairy sites, EEG signals can be measured reliably with the designed SBDSs. In particular, for EEG signal measurements at hairy sites, the acicular and flexible design of SBDS can push the hair aside to achieve satisfactory scalp contact, as well as maintain low skin-electrode interface impedance. Results of this paper demonstrate that the proposed sensors perform well in the EEG measurements and are feasible for practical applications.

Augmented reality-based electrode guidance system for reliable electroencephalography.

PubMed

Song, Chanho; Jeon, Sangseo; Lee, Seongpung; Ha, Ho-Gun; Kim, Jonghyun; Hong, Jaesung

2018-05-24

In longitudinal electroencephalography (EEG) studies, repeatable electrode positioning is essential for reliable EEG assessment. Conventional methods use anatomical landmarks as fiducial locations for the electrode placement. Since the landmarks are manually identified, the EEG assessment is inevitably unreliable because of individual variations among the subjects and the examiners. To overcome this unreliability, an augmented reality (AR) visualization-based electrode guidance system was proposed. The proposed electrode guidance system is based on AR visualization to replace the manual electrode positioning. After scanning and registration of the facial surface of a subject by an RGB-D camera, the AR of the initial electrode positions as reference positions is overlapped with the current electrode positions in real time. Thus, it can guide the position of the subsequently placed electrodes with high repeatability. The experimental results with the phantom show that the repeatability of the electrode positioning was improved compared to that of the conventional 10-20 positioning system. The proposed AR guidance system improves the electrode positioning performance with a cost-effective system, which uses only RGB-D camera. This system can be used as an alternative to the international 10-20 system.

Syndrome of transient headache and neurological deficits with cerebrospinal fluid lymphocytosis (HaNDL): A case report with serial electroencephalography (EEG) recordings.. Is there an association with human herpes virus type 7 (HHV-7) infection?

PubMed

Stelten, Bianca Ml; Venhovens, Jeroen; van der Velden, Lieven Bj; Meulstee, Jan; Verhagen, Wim Im

2016-11-01

Introduction The syndrome of transient headache and neurological deficits with cerebrospinal fluid lymphocytosis (HaNDL) is a diagnosis made by exclusion. In the literature, different etiological explanations are proposed for HaNDL, including an immune-mediated reaction after a viral infection. Case description We present a case of a 23-year-old woman with several episodes of transient headache, neurological deficits and cerebrospinal fluid lymphocytosis. All diagnostic criteria for the HaNDL syndrome were fulfilled; however, additional cerebrospinal fluid analysis showed a positive polymerase chain reaction (PCR) for human herpes virus type 7 (HHV-7). Discussion The possible role of a (prodromal) viral infection in the etiology of HaNDL is discussed. Also the role of electroencephalography (EEG) recordings is discussed. Serial EEG recordings showed generalized slowing, frontal intermittent rhythmic delta activity (FIRDA) and symmetric triphasic frontal waves with a dilation lag.

EEG - A Valuable Biomarker of Brain Injury in Preterm Infants.

PubMed

Pavlidis, Elena; Lloyd, Rhodri O; Boylan, Geraldine B

2017-01-01

This review focuses on the role of electroencephalography (EEG) in monitoring abnormalities of preterm brain function. EEG features of the most common developmental brain injuries in preterm infants, including intraventricular haemorrhage, periventricular leukomalacia, and perinatal asphyxia, are described. We outline the most common EEG biomarkers associated with these injuries, namely seizures, positive rolandic sharp waves, EEG suppression/increased interburst intervals, mechanical delta brush activity, and other deformed EEG waveforms, asymmetries, and asynchronies. The increasing survival rate of preterm infants, in particular those that are very and extremely preterm, has led to a growing demand for a specific and shared characterization of the patterns related to adverse outcome in this unique population. This review includes abundant high-quality images of the EEG patterns seen in premature infants and will provide a valuable resource for everyone working in developmental neuroscience. © 2017 S. Karger AG, Basel.

Pharmaco-EEG: A Study of Individualized Medicine in Clinical Practice.

PubMed

Swatzyna, Ronald J; Kozlowski, Gerald P; Tarnow, Jay D

2015-07-01

Pharmaco-electroencephalography (Pharmaco-EEG) studies using clinical EEG and quantitative EEG (qEEG) technologies have existed for more than 4 decades. This is a promising area that could improve psychotropic intervention using neurological data. One of the objectives in our clinical practice has been to collect EEG and quantitative EEG (qEEG) data. In the past 5 years, we have identified a subset of refractory cases (n = 386) found to contain commonalities of a small number of electrophysiological features in the following diagnostic categories: mood, anxiety, autistic spectrum, and attention deficit disorders, Four abnormalities were noted in the majority of medication failure cases and these abnormalities did not appear to significantly align with their diagnoses. Those were the following: encephalopathy, focal slowing, beta spindles, and transient discharges. To analyze the relationship noted, they were tested for association with the assigned diagnoses. Fisher's exact test and binary logistics regression found very little (6%) association between particular EEG/qEEG abnormalities and diagnoses. Findings from studies of this type suggest that EEG/qEEG provides individualized understanding of pharmacotherapy failures and has the potential to improve medication selection. © EEG and Clinical Neuroscience Society (ECNS) 2014.

Correspondence of electroencephalography and near-infrared spectroscopy sensitivities to the cerebral cortex using a high-density layout

PubMed Central

Giacometti, Paolo; Diamond, Solomon G.

2014-01-01

Abstract. This study investigates the correspondence of the cortical sensitivity of electroencephalography (EEG) and near-infrared spectroscopy (NIRS). EEG forward model sensitivity to the cerebral cortex was calculated for 329 EEG electrodes following the 10-5 EEG positioning system using a segmented structural magnetic resonance imaging scan of a human subject. NIRS forward model sensitivity was calculated for the same subject using 156 NIRS source-detector pairs selected from 32 source and 32 detector optodes positioned on the scalp using a subset of the 10-5 EEG positioning system. Sensitivity correlations between colocalized NIRS source-detector pair groups and EEG channels yielded R=0.46±0.08. Groups of NIRS source-detector pairs with maximum correlations to EEG electrode sensitivities are tabulated. The mean correlation between the point spread functions for EEG and NIRS regions of interest (ROI) was R=0.43±0.07. Spherical ROIs with radii of 26 mm yielded the maximum correlation between EEG and NIRS averaged across all cortical mesh nodes. These sensitivity correlations between EEG and NIRS should be taken into account when designing multimodal studies of neurovascular coupling and when using NIRS as a statistical prior for EEG source localization. PMID:25558462

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

Multiscale entropy analysis of electroencephalography during sleep in patients with Parkinson disease.

PubMed

Chung, Chen-Chih; Kang, Jiunn-Horng; Yuan, Rey-Yue; Wu, Dean; Chen, Chih-Chung; Chi, Nai-Fang; Chen, Po-Chih; Hu, Chaur-Jong

2013-07-01

Sleep disorders are frequently seen in patients with Parkinson disease (PD), including rapid eye movement (REM) behavior disorder and periodic limb movement disorder. However, knowledge about changes in non-REM sleep in patients with PD is limited. This study explored the characteristics of electroencephalography (EEG) during sleep in patients with PD and non-PD controls. We further conducted multiscale entropy (MSE) analysis to evaluate and compare the complexity of sleep EEG for the 2 groups. There were 9 patients with PD (Hoehn-Yahr stage 1 or 2) and 11 non-PD controls. All participants underwent standard whole-night polysomnography (PSG), which included 23 channels, 6 of which were for EEG. The raw data of the EEG were extracted and subjected to MSE analysis. Patients with PD had a longer sleep onset time and a higher spontaneous EEG arousal index. Sleep stage-specific increased MSE was observed in patients with PD during non-REM sleep. The difference was more marked and significant at higher time scale factors (TSFs). In conclusion, increased biosignal complexity, as revealed by MSE analysis, was found in patients with PD during non-REM sleep at high TSFs. This finding might reflect a compensatory mechanism for early defects in neuronal network control machinery in PD.

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.

Effects of Cable Sway, Electrode Surface Area, and Electrode Mass on Electroencephalography Signal Quality during Motion

PubMed Central

Symeonidou, Evangelia-Regkina; Nordin, Andrew D.; Hairston, W. David

2018-01-01

More neuroscience researchers are using scalp electroencephalography (EEG) to measure electrocortical dynamics during human locomotion and other types of movement. Motion artifacts corrupt the EEG and mask underlying neural signals of interest. The cause of motion artifacts in EEG is often attributed to electrode motion relative to the skin, but few studies have examined EEG signals under head motion. In the current study, we tested how motion artifacts are affected by the overall mass and surface area of commercially available electrodes, as well as how cable sway contributes to motion artifacts. To provide a ground-truth signal, we used a gelatin head phantom with embedded antennas broadcasting electrical signals, and recorded EEG with a commercially available electrode system. A robotic platform moved the phantom head through sinusoidal displacements at different frequencies (0–2 Hz). Results showed that a larger electrode surface area can have a small but significant effect on improving EEG signal quality during motion and that cable sway is a major contributor to motion artifacts. These results have implications in the development of future hardware for mobile brain imaging with EEG. PMID:29614020

Outcome of intracranial electroencephalography monitoring and surgery in magnetic resonance imaging-negative temporal lobe epilepsy.

PubMed

Lee, Ricky W; Hoogs, Marietta M; Burkholder, David B; Trenerry, Max R; Drazkowski, Joseph F; Shih, Jerry J; Doll, Karey E; Tatum, William O; Cascino, Gregory D; Marsh, W Richard; Wirrell, Elaine C; Worrell, Gregory A; So, Elson L

2014-07-01

We evaluated the outcomes of intracranial electroencephalography (iEEG) recording and subsequent resective surgery in patients with magnetic resonance imaging (MRI)-negative temporal lobe epilepsy (TLE). Thirty-two patients were identified from the Mayo Clinic Epilepsy Surgery Database (Arizona, Florida, and Minnesota). Eight (25.0%) had chronic iEEG monitoring that recorded neocortical temporal seizure onsets; 12 (37.5%) had mesial temporal seizure onsets; 5 (15.6%) had independent neocortical and mesial temporal seizure onsets; and 7 (21.9%) had simultaneous neocortical and mesial seizure onsets. Neocortical temporal lobe seizure semiology was the only factor significantly associated with neocortical temporal seizure onsets on iEEG. Only 33.3% of patients who underwent lateral temporal neocorticectomy had an Engel class 1 outcome, whereas 76.5% of patients with iEEG-guided anterior temporal lobectomy that included the amygdala and the hippocampus had an Engel class 1 outcome. Limitations in cohort size precluded statistical analysis of neuropsychological test data. Copyright © 2014 Elsevier B.V. All rights reserved.

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%.

An EEG (electroencephalogram) recording system with carbon wire electrodes for simultaneous EEG-fMRI (functional magnetic resonance imaging) recording

PubMed Central

Negishi, Michiro; Abildgaard, Mark; Laufer, Ilan; Nixon, Terry; Constable, Robert Todd

2008-01-01

Simultaneous EEG-fMRI (Electroencephalography-functional Magnetic Resonance Imaging) recording provides a means for acquiring high temporal resolution electrophysiological data and high spatial resolution metabolic data of the brain in the same experimental runs. Carbon wire electrodes (not metallic EEG electrodes with carbon wire leads) are suitable for simultaneous EEG-fMRI recording, because they cause less RF (radio-frequency) heating and susceptibility artifacts than metallic electrodes. These characteristics are especially desirable for recording the EEG in high field MRI scanners. Carbon wire electrodes are also comfortable to wear during long recording sessions. However, carbon electrodes have high electrode-electrolyte potentials compared to widely used Ag/AgCl (silver/silver-chloride) electrodes, which may cause slow voltage drifts. This paper introduces a prototype EEG recording system with carbon wire electrodes and a circuit that suppresses the slow voltage drift. The system was tested for the voltage drift, RF heating, susceptibility artifact, and impedance, and was also evaluated in a simultaneous ERP (event-related potential)-fMRI experiment. PMID:18588913

Comparison of corrected QT interval as measured on electroencephalography versus 12-lead electrocardiography in children with a history of syncope.

PubMed

Massey, Shavonne L; Wise, Marshall S; Madan, Nandini; Carvalho, Karen; Khurana, Divya; Legido, Agustin; Valencia, Ignacio

2011-11-01

Long QT syndrome can present with neurological manifestations, including syncope and seizure-like activity. These patients often receive an initial neurologic evaluation, including electroencephalography (EEG). Our previous retrospective study suggested an increased prevalence of prolonged corrected QT interval (QTc) measured during the EEG of patients with syncope. The aim of the current study is to assess the accuracy of the EEG QTc reading compared with the nonsimultaneous 12-lead electrocardiography (ECG) in children with syncope. Abnormal QTc was defined as ≥450 ms in boys, ≥460 ms in girls. Forty-two children were included. There was no significant correlation between QTc readings in the EEG and ECG. EEG failed to identify 2 children with prolonged QTc in the ECG and overestimated the QTc in 3 children with normal QTc in the ECG. This study suggests that interpretation of the QTc segment during an EEG is limited. Further studies with simultaneous EEG and 12-lead ECG are warranted.

Prediction of Human Performance Using Electroencephalography under Different Indoor Room Temperatures

PubMed Central

Zhang, Tinghe; Mao, Zijing; Xu, Xiaojing; Zhang, Lin; Pack, Daniel J.; Dong, Bing; Huang, Yufei

2018-01-01

Varying indoor environmental conditions is known to affect office worker’s performance; wherein past research studies have reported the effects of unfavorable indoor temperature and air quality causing sick building syndrome (SBS) among office workers. Thus, investigating factors that can predict performance in changing indoor environments have become a highly important research topic bearing significant impact in our society. While past research studies have attempted to determine predictors for performance, they do not provide satisfactory prediction ability. Therefore, in this preliminary study, we attempt to predict performance during office-work tasks triggered by different indoor room temperatures (22.2 °C and 30 °C) from human brain signals recorded using electroencephalography (EEG). Seven participants were recruited, from whom EEG, skin temperature, heart rate and thermal survey questionnaires were collected. Regression analyses were carried out to investigate the effectiveness of using EEG power spectral densities (PSD) as predictors of performance. Our results indicate EEG PSDs as predictors provide the highest R2 (> 0.70), that is 17 times higher than using other physiological signals as predictors and is more robust. Finally, the paper provides insight on the selected predictors based on brain activity patterns for low- and high-performance levels under different indoor-temperatures. PMID:29690601

Prediction of Human Performance Using Electroencephalography under Different Indoor Room Temperatures.

PubMed

Nayak, Tapsya; Zhang, Tinghe; Mao, Zijing; Xu, Xiaojing; Zhang, Lin; Pack, Daniel J; Dong, Bing; Huang, Yufei

2018-04-23

Varying indoor environmental conditions is known to affect office worker’s performance; wherein past research studies have reported the effects of unfavorable indoor temperature and air quality causing sick building syndrome (SBS) among office workers. Thus, investigating factors that can predict performance in changing indoor environments have become a highly important research topic bearing significant impact in our society. While past research studies have attempted to determine predictors for performance, they do not provide satisfactory prediction ability. Therefore, in this preliminary study, we attempt to predict performance during office-work tasks triggered by different indoor room temperatures (22.2 °C and 30 °C) from human brain signals recorded using electroencephalography (EEG). Seven participants were recruited, from whom EEG, skin temperature, heart rate and thermal survey questionnaires were collected. Regression analyses were carried out to investigate the effectiveness of using EEG power spectral densities (PSD) as predictors of performance. Our results indicate EEG PSDs as predictors provide the highest R ² (> 0.70), that is 17 times higher than using other physiological signals as predictors and is more robust. Finally, the paper provides insight on the selected predictors based on brain activity patterns for low- and high-performance levels under different indoor-temperatures.

Fuzzy topological digital space and digital fuzzy spline of electroencephalography during epileptic seizures

NASA Astrophysics Data System (ADS)

Shah, Mazlina Muzafar; Wahab, Abdul Fatah

2017-08-01

Epilepsy disease occurs because of there is a temporary electrical disturbance in a group of brain cells (nurons). The recording of electrical signals come from the human brain which can be collected from the scalp of the head is called Electroencephalography (EEG). EEG then considered in digital format and in fuzzy form makes it a fuzzy digital space data form. The purpose of research is to identify the area (curve and surface) in fuzzy digital space affected by inside epilepsy seizure in epileptic patient's brain. The main focus for this research is to generalize fuzzy topological digital space, definition and basic operation also the properties by using digital fuzzy set and the operations. By using fuzzy digital space, the theory of digital fuzzy spline can be introduced to replace grid data that has been use previously to get better result. As a result, the flat of EEG can be fuzzy topological digital space and this type of data can be use to interpolate the digital fuzzy spline.

Two volume integral equations for the inhomogeneous and anisotropic forward problem in electroencephalography

NASA Astrophysics Data System (ADS)

Rahmouni, Lyes; Mitharwal, Rajendra; Andriulli, Francesco P.

2017-11-01

This work presents two new volume integral equations for the Electroencephalography (EEG) forward problem which, differently from the standard integral approaches in the domain, can handle heterogeneities and anisotropies of the head/brain conductivity profiles. The new formulations translate to the quasi-static regime some volume integral equation strategies that have been successfully applied to high frequency electromagnetic scattering problems. This has been obtained by extending, to the volume case, the two classical surface integral formulations used in EEG imaging and by introducing an extra surface equation, in addition to the volume ones, to properly handle boundary conditions. Numerical results corroborate theoretical treatments, showing the competitiveness of our new schemes over existing techniques and qualifying them as a valid alternative to differential equation based methods.

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.

Electroencephalography Amplitude Modulation Analysis for Automated Affective Tagging of Music Video Clips

PubMed Central

Clerico, Andrea; Tiwari, Abhishek; Gupta, Rishabh; Jayaraman, Srinivasan; Falk, Tiago H.

2018-01-01

The quantity of music content is rapidly increasing and automated affective tagging of music video clips can enable the development of intelligent retrieval, music recommendation, automatic playlist generators, and music browsing interfaces tuned to the users' current desires, preferences, or affective states. To achieve this goal, the field of affective computing has emerged, in particular the development of so-called affective brain-computer interfaces, which measure the user's affective state directly from measured brain waves using non-invasive tools, such as electroencephalography (EEG). Typically, conventional features extracted from the EEG signal have been used, such as frequency subband powers and/or inter-hemispheric power asymmetry indices. More recently, the coupling between EEG and peripheral physiological signals, such as the galvanic skin response (GSR), have also been proposed. Here, we show the importance of EEG amplitude modulations and propose several new features that measure the amplitude-amplitude cross-frequency coupling per EEG electrode, as well as linear and non-linear connections between multiple electrode pairs. When tested on a publicly available dataset of music video clips tagged with subjective affective ratings, support vector classifiers trained on the proposed features were shown to outperform those trained on conventional benchmark EEG features by as much as 6, 20, 8, and 7% for arousal, valence, dominance and liking, respectively. Moreover, fusion of the proposed features with EEG-GSR coupling features showed to be particularly useful for arousal (feature-level fusion) and liking (decision-level fusion) prediction. Together, these findings show the importance of the proposed features to characterize human affective states during music clip watching. PMID:29367844

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.

Recovering TMS-evoked EEG responses masked by muscle artifacts.

PubMed

Mutanen, Tuomas P; Kukkonen, Matleena; Nieminen, Jaakko O; Stenroos, Matti; Sarvas, Jukka; Ilmoniemi, Risto J

2016-10-01

Combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) often suffers from large muscle artifacts. Muscle artifacts can be removed using signal-space projection (SSP), but this can make the visual interpretation of the remaining EEG data difficult. We suggest to use an additional step after SSP that we call source-informed reconstruction (SIR). SSP-SIR improves substantially the signal quality of artifactual TMS-EEG data, causing minimal distortion in the neuronal signal components. In the SSP-SIR approach, we first project out the muscle artifact using SSP. Utilizing an anatomical model and the remaining signal, we estimate an equivalent source distribution in the brain. Finally, we map the obtained source estimate onto the original signal space, again using anatomical information. This approach restores the neuronal signals in the sensor space and interpolates EEG traces onto the completely rejected channels. The introduced algorithm efficiently suppresses TMS-related muscle artifacts in EEG while retaining well the neuronal EEG topographies and signals. With the presented method, we can remove muscle artifacts from TMS-EEG data and recover the underlying brain responses without compromising the readability of the signals of interest. Copyright © 2016 Elsevier Inc. All rights reserved.

Association between waking electroencephalography and cognitive event-related potentials in patients with obstructive sleep apnea.

PubMed

Baril, Andrée-Ann; Gagnon, Katia; Gagnon, Jean-François; Montplaisir, Jacques; Gosselin, Nadia

2013-07-01

Sleepiness, cognitive deficits, abnormal event-related potentials (ERP), and slowing of the waking electroencephalography (EEG) activity have been reported in patients with obstructive sleep apnea (OSA). Our study aimed at evaluating if an association exists between the severity of ERP abnormalities and EEG slowing to better understand cerebral dysfunctions in OSA. Twelve OSA patients and 12 age-matched controls underwent an overnight polysomnographic recording, an EEG recording of 10 min of wakefulness, and an auditory ERP protocol known to specifically recruit attention. P300 and P3a ERP components were measured as well as the spectral power in each frequency band of the waking EEG. Pearson product moment correlations were used to measure associations between ERP characteristics and EEG spectral power in OSA patients and control subjects. A positive correlation between the late P300 amplitude and θ power in the occipital region was observed in OSA subjects (P<.01). A positive correlation was also found between P3a amplitude and β1 power in central region in OSA subjects (P<.01). No correlation was observed for control subjects. ERP abnormalities observed in an attention task are associated with a slowing of the waking EEG recorded at rest in OSA. Copyright © 2013 Elsevier B.V. All rights reserved.

The Accuracy, Night-to-Night Variability, and Stability of Frontopolar Sleep Electroencephalography Biomarkers

PubMed Central

Levendowski, Daniel J.; Ferini-Strambi, Luigi; Gamaldo, Charlene; Cetel, Mindy; Rosenberg, Robert; Westbrook, Philip R.

2017-01-01

Study Objectives: To assess the validity of sleep architecture and sleep continuity biomarkers obtained from a portable, multichannel forehead electroencephalography (EEG) recorder. Methods: Forty-seven subjects simultaneously underwent polysomnography (PSG) while wearing a multichannel frontopolar EEG recording device (Sleep Profiler). The PSG recordings independently staged by 5 registered polysomnographic technologists were compared for agreement with the autoscored sleep EEG before and after expert review. To assess the night-to-night variability and first night bias, 2 nights of self-applied, in-home EEG recordings obtained from a clinical cohort of 63 patients were used (41% with a diagnosis of insomnia/depression, 35% with insomnia/obstructive sleep apnea, and 17.5% with all three). The between-night stability of abnormal sleep biomarkers was determined by comparing each night's data to normative reference values. Results: The mean overall interscorer agreements between the 5 technologists were 75.9%, and the mean kappa score was 0.70. After visual review, the mean kappa score between the autostaging and five raters was 0.67, and staging agreed with a majority of scorers in at least 80% of the epochs for all stages except stage N1. Sleep spindles, autonomic activation, and stage N3 exhibited the least between-night variability (P < .0001) and strongest between-night stability. Antihypertensive medications were found to have a significant effect on sleep quality biomarkers (P < .02). Conclusions: A strong agreement was observed between the automated sleep staging and human-scored PSG. One night's recording appeared sufficient to characterize abnormal slow wave sleep, sleep spindle activity, and heart rate variability in patients, but a 2-night average improved the assessment of all other sleep biomarkers. Commentary: Two commentaries on this article appear in this issue on pages 771 and 773. Citation: Levendowski DJ, Ferini-Strambi L, Gamaldo C, Cetel M

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.

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.

Comparison of Electroencephalography (EEG) Coherence between Major Depressive Disorder (MDD) without Comorbidity and MDD Comorbid with Internet Gaming Disorder.

PubMed

Youh, Joohyung; Hong, Ji Sun; Han, Doug Hyun; Chung, Un Sun; Min, Kyoung Joon; Lee, Young Sik; Kim, Sun Mi

2017-07-01

Internet gaming disorder (IGD) has many comorbid psychiatric problems including major depressive disorder (MDD). In the present study, we compared the neurobiological differences between MDD without comorbidity (MDD-only) and MDD comorbid with IGD (MDD+IGD) by analyzing the quantitative electroencephalogram (QEEG) findings. We recruited 14 male MDD+IGD (mean age, 20.0 ± 5.9 years) and 15 male MDD-only (mean age, 20.3 ± 5.5 years) patients. The electroencephalography (EEG) coherences were measured using a 21-channel digital EEG system and computed to assess synchrony in the frequency ranges of alpha (7.5-12.5 Hz) and beta (12.5-35.0 Hz) between the following 12 electrode site pairs: inter-hemispheric (Fp1-Fp2, F7-F8, T3-T4, and P3-P4) and intra-hemispheric (F7-T3, F8-T4, C3-P3, C4-P4, T5-O1, T6-O2, P3-O1, and P4-O2) pairs. Differences in inter- and intra-hemispheric coherence values for the frequency bands between groups were analyzed using the independent t-test. Inter-hemispheric coherence value for the alpha band between Fp1-Fp2 electrodes was significantly lower in MDD+IGD than MDD-only patients. Intra-hemispheric coherence value for the alpha band between P3-O1 electrodes was higher in MDD+IGD than MDD-only patients. Intra-hemispheric coherence values for the beta band between F8-T4, T6-O2, and P4-O2 electrodes were higher in MDD+IGD than MDD-only patients. There appears to be an association between decreased inter-hemispheric connectivity in the frontal region and vulnerability to attention problems in the MDD+IGD group. Increased intra-hemisphere connectivity in the fronto-temporo-parieto-occipital areas may result from excessive online gaming. © 2017 The Korean Academy of Medical Sciences.

An accuracy aware low power wireless EEG unit with information content based adaptive data compression.

PubMed

Tolbert, Jeremy R; Kabali, Pratik; Brar, Simeranjit; Mukhopadhyay, Saibal

2009-01-01

We present a digital system for adaptive data compression for low power wireless transmission of Electroencephalography (EEG) data. The proposed system acts as a base-band processor between the EEG analog-to-digital front-end and RF transceiver. It performs a real-time accuracy energy trade-off for multi-channel EEG signal transmission by controlling the volume of transmitted data. We propose a multi-core digital signal processor for on-chip processing of EEG signals, to detect signal information of each channel and perform real-time adaptive compression. Our analysis shows that the proposed approach can provide significant savings in transmitter power with minimal impact on the overall signal accuracy.

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.

Novel wireless electroencephalography system with a minimal preparation time for use in emergencies and prehospital care

PubMed Central

2014-01-01

Background Although clinical applications such as emergency medicine and prehospital care could benefit from a fast-mounting electroencephalography (EEG) recording system, the lack of specifically designed equipment restricts the use of EEG in these environments. Methods This paper describes the design and testing of a six-channel emergency EEG (emEEG) system with a rapid preparation time intended for use in emergency medicine and prehospital care. The novel system comprises a quick-application cap, a device for recording and transmitting the EEG wirelessly to a computer, and custom software for displaying and streaming the data in real-time to a hospital. Bench testing was conducted, as well as healthy volunteer and patient measurements in three different environments: a hospital EEG laboratory, an intensive care unit, and an ambulance. The EEG data was evaluated by two experienced clinical neurophysiologists and compared with recordings from a commercial system. Results The bench tests demonstrated that the emEEG system's performance is comparable to that of a commercial system while the healthy volunteer and patient measurements confirmed that the system can be applied quickly and that it records quality EEG data in a variety of environments. Furthermore, the recorded data was judged to be of diagnostic quality by two experienced clinical neurophysiologists. Conclusions In the future, the emEEG system may be used to record high-quality EEG data in emergency medicine and during ambulance transportation. Its use could lead to a faster diagnostic, a more accurate treatment, and a shorter recovery time for patients with neurological brain disorders. PMID:24886096

Multi-modal Patient Cohort Identification from EEG Report and Signal Data

PubMed Central

Goodwin, Travis R.; Harabagiu, Sanda M.

2016-01-01

Clinical electroencephalography (EEG) is the most important investigation in the diagnosis and management of epilepsies. An EEG records the electrical activity along the scalp and measures spontaneous electrical activity of the brain. Because the EEG signal is complex, its interpretation is known to produce moderate inter-observer agreement among neurologists. This problem can be addressed by providing clinical experts with the ability to automatically retrieve similar EEG signals and EEG reports through a patient cohort retrieval system operating on a vast archive of EEG data. In this paper, we present a multi-modal EEG patient cohort retrieval system called MERCuRY which leverages the heterogeneous nature of EEG data by processing both the clinical narratives from EEG reports as well as the raw electrode potentials derived from the recorded EEG signal data. At the core of MERCuRY is a novel multimodal clinical indexing scheme which relies on EEG data representations obtained through deep learning. The index is used by two clinical relevance models that we have generated for identifying patient cohorts satisfying the inclusion and exclusion criteria expressed in natural language queries. Evaluations of the MERCuRY system measured the relevance of the patient cohorts, obtaining MAP scores of 69.87% and a NDCG of 83.21%. PMID:28269938

Using a Wireless Electroencephalography Device to Evaluate E-Health and E-Learning Interventions.

PubMed

Mailhot, Tanya; Lavoie, Patrick; Maheu-Cadotte, Marc-André; Fontaine, Guillaume; Cournoyer, Alexis; Côté, José; Dupuis, France; Karsenti, Thierry; Cossette, Sylvie

Measuring engagement and other reactions of patients and health professionals to e-health and e-learning interventions remains a challenge for researchers. The aim of this pilot study was to assess the feasibility and acceptability of using a wireless electroencephalography (EEG) device to measure affective (anxiety, enjoyment, relaxation) and cognitive (attention, engagement, interest) reactions of patients and healthcare professionals during e-health or e-learning interventions. Using a wireless EEG device, we measured patient (n = 6) and health professional (n = 7) reactions during a 10-minute session of an e-health or e-learning intervention. The following feasibility and acceptability indicators were assessed and compared for patients and healthcare professionals: number of eligible participants who consented to participate, reasons for refusal, time to install and calibrate the wireless EEG device, number of participants who completed the full 10-minute sessions, participant comfort when wearing the device, signal quality, and number of observations obtained for each reaction. The wireless EEG readings were compared to participant self-rating of their reactions. We obtained at least 75% of possible observations for attention, engagement, enjoyment, and interest. EEG scores were similar to self-reported scores, but they varied throughout the sessions, which gave information on participants' real-time reactions to the e-health/e-learning interventions. Results on the other indicators support the feasibility and acceptability of the wireless EEG device for both patients and professionals. Using the wireless EEG device was feasible and acceptable. Future studies must examine its use in other contexts of care and explore which components of the interventions affected participant reactions by combining wireless EEG and eye tracking.

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.

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.

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.

Chloral hydrate, chloral hydrate--promethazine and chloral hydrate -hydroxyzine efficacy in electroencephalography sedation.

PubMed

Fallah, Razieh; Alaei, Ali; Akhavan Karbasi, Sedighah; Shajari, Ahmad

2014-06-01

To compare efficacy and safety of chloral hydrate (CH), chloral hydrate and promethazine (CH + P) and chloral hydrate and hydroxyzine (CH + H) in electroencephalography (EEG) sedation. In a parallel single-blinded randomized clinical trial, ninety 1-7 y-old uncooperative kids who were referred to Pediatric Neurology Clinic of Shahid Sadoughi University, Yazd, Iran from April through August 2012, were randomly assigned to receive 40 mg/kg of chloral hydrate or 40 mg/kg of chloral hydrate and 1 mg/kg of promethazine or 40 mg/kg of chloral hydrate and 2 mg/kg of hydroxyzine. The primary endpoint was efficacy in sufficient sedation (obtaining four Ramsay sedation score) and successful completion of EEG. Secondary endpoint was clinical adverse events. Thirty nine girls (43.3 %) and 51 boys (56.7 %) with mean age of 3.34 ± 1.47 y were assessed. Sufficient sedation and completion of EEG were achieved in 70 % (N = 21) of chloral hydrate group, in 83.3 % (N = 25) of CH + H group and in 96.7 % (N = 29) of CH + P group (p = 0.02). Mild clinical adverse events including vomiting [16.7 % (N = 5) in CH, 6.7 % (N = 2) in CH + P, 6.7 % (N = 2) in CH + H], agitation in 3.3 % of CH + P (N = 1) group and mild transient hypotension in 3.3 % of CH + H (N = 1) group occurred. Safety of these three sedation regimens was not statistically significant different (p = 0.14). Combination of chloral hydrate-antihistamines can be used as the most effective and safe sedation regimen in drug induced sleep electroencephalography of kids.

Diagnostic yield of five minutes compared to three minutes hyperventilation during electroencephalography.

PubMed

Craciun, Laura; Varga, Edina Timea; Mindruta, Ioana; Meritam, Pirgit; Horváth, Zoltán; Terney, Daniella; Gardella, Elena; Alving, Jørgen; Vécsei, László; Beniczky, Sándor

2015-08-01

To investigate whether hyperventilation (HV) for 5min increases the diagnostic yield of electroencephalography (EEG) compared to 3min HV. data were evaluated from 1084 consecutive patients, from three European centres, referred to EEG on suspicion of epilepsy. Seizures and interictal EEG abnormalities precipitated during the first 3min and during the last 2min of the HV period (totally 5min) were determined. Eight hundred seventy-seven patients (81%) completed 5min HV. Seizures were precipitated during the first 3min of HV in 21 patients, and during the last 2min in four more patients. Interictal EEG abnormalities were precipitated in the first 3min of HV in 16 patients, and during the last 2min in 7 more patients. Psychogenic nonepileptic seizures occurred in eight patients during the first 3min of HV and in two more patients during the last 2min. No adverse events occurred during the last 2min of HV, but eight patients (1%) stopped HV during the last 2min because they were not able to hyperventilate further. 16% of seizures and 30% of interictal EEG abnormalities triggered by HV occurred during the last 2min of HV, suggesting the clinical usefulness of prolonged hyperventilation for 5min. The vast majority of patients (99%) who are able to hyperventilate for 3min can complete 5min HV, without additional adverse events. Copyright © 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

The inverse problem in electroencephalography using the bidomain model of electrical activity.

PubMed

Lopez Rincon, Alejandro; Shimoda, Shingo

2016-12-01

Acquiring information about the distribution of electrical sources in the brain from electroencephalography (EEG) data remains a significant challenge. An accurate solution would provide an understanding of the inner mechanisms of the electrical activity in the brain and information about damaged tissue. In this paper, we present a methodology for reconstructing brain electrical activity from EEG data by using the bidomain formulation. The bidomain model considers continuous active neural tissue coupled with a nonlinear cell model. Using this technique, we aim to find the brain sources that give rise to the scalp potential recorded by EEG measurements taking into account a non-static reconstruction. We simulate electrical sources in the brain volume and compare the reconstruction to the minimum norm estimates (MNEs) and low resolution electrical tomography (LORETA) results. Then, with the EEG dataset from the EEG Motor Movement/Imagery Database of the Physiobank, we identify the reaction to visual stimuli by calculating the time between stimulus presentation and the spike in electrical activity. Finally, we compare the activation in the brain with the registered activation using the LinkRbrain platform. Our methodology shows an improved reconstruction of the electrical activity and source localization in comparison with MNE and LORETA. For the Motor Movement/Imagery Database, the reconstruction is consistent with the expected position and time delay generated by the stimuli. Thus, this methodology is a suitable option for continuously reconstructing brain potentials. Copyright © 2016 The Author(s). Published by Elsevier B.V. All rights reserved.

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 �

Usefulness of electroencephalography for the management of epilepsy in emergency departments.

PubMed

Viloria Alebesque, A; López Bravo, A; Bellosta Diago, E; Santos Lasaosa, S; Mauri Llerda, J A

2017-11-03

Electroencephalography (EEG) is an essential diagnostic tool in epilepsy. Its use in emergency departments (ED) is usually restricted to the diagnosis and management of non-convulsive status epilepticus (NCSE). However, EDs may also benefit from EEG in the context of other situations in epilepsy. We conducted a retrospective observational study using the clinical histories of patients treated at our hospital's ED for epileptic seizures and suspicion of NCSE and undergoing EEG studies in 2015 and 2016. We collected a series of demographic and clinical variables. Our sample included 87 patients (mean age of 44 years). Epileptic seizures constituted the most common reason for consultation: 59.8% due to the first episode of epileptic seizures (FES), 27.6% due to recurrence, and 12.6% due to suspected NCSE. Interictal epileptiform discharges (IED) were observed in 38.4% of patients reporting FES and in 33.3% of those with a known diagnosis of epilepsy. NCSE was confirmed by EEG in 36.4% of all cases of suspected NCSE. Presence of IED led to administration of or changes in long-term treatment in 59.8% of the patients. EEG is a useful tool for seizure management in EDs, not only for severe, sudden-onset clinical situations such as NCSE but also for diagnosis in cases of non-affiliated epilepsy and in patients experiencing the first episode of epilepsy. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

The use of routine EEG in acute ischemic stroke patients without seizures: generalized but not focal EEG pathology is associated with clinical deterioration.

PubMed

Wolf, Marc E; Ebert, Anne D; Chatzikonstantinou, Anastasios

2017-05-01

Specialized electroencephalography (EEG) methods have been used to provide clues about stroke features and prognosis. However, the value of routine EEG in stroke patients without (suspected) seizures has been somewhat neglected. We aimed to assess this in a group of acute ischemic stroke patients in regard to short-term prognosis and basic stroke features. We assessed routine (10-20) EEG findings in 69 consecutive acute ischemic stroke patients without seizures. Associations between EEG abnormalities and NIHSS scores, clinical improvement or deterioration as well as MRI stroke characteristics were evaluated. Mean age was 69 ± 18 years, 43 of the patients (62.3%) were men. Abnormal EEG was found in 40 patients (58%) and was associated with higher age (p = 0.021). The most common EEG pathology was focal slowing (30; 43.5%). No epileptiform potentials were found. Abnormal EEG in general and generalized or focal slowing in particular was significantly associated with higher NIHSS score on admission and discharge as well as with hemorrhagic transformation of the ischemic lesion. Abnormal EEG and generalized (but not focal) slowing were associated with clinical deterioration ( p = 0.036, p = 0.003). Patients with lacunar strokes had no EEG abnormalities. Abnormal EEG in general and generalized slowing in particular are associated with clinical deterioration after acute ischemic stroke. The study demonstrates the value of routine EEG as a simple diagnostic tool in the evaluation of stroke patients especially with regard to short-term prognosis.

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

Effect of intravenous sodium salicylate administration prior to castration on plasma cortisol and electroencephalography parameters in calves.

PubMed

Bergamasco, L; Coetzee, J F; Gehring, R; Murray, L; Song, T; Mosher, R A

2011-12-01

Nociception is an unavoidable consequence of many routine management procedures such as castration in cattle. This study investigated electroencephalography (EEG) parameters and cortisol levels in calves receiving intravenous sodium salicylate in response to a castration model. Twelve Holstein calves were randomly assigned to the following groups: (i) castrated, untreated controls, (ii) 50 mg/kg sodium salicylate IV precastration, were blood sampled at 0, 5, 10, 20, 30, 45, 60, 90, 120, 150, 180, 240, 360, and 480 min postcastration. The EEG recording included baseline, castration, immediate recovery (0-5 min after castration), middle recovery (5-10 min after castration), and late recovery (10-20 min after castration). Samples were analyzed by competitive chemiluminescent immunoassay and fluorescence polarization immunoassay for cortisol and salicylate, respectively. EEG visual inspection and spectral analysis were performed. Statistical analyses included anova repeated measures and correlations between response variable. No treatment effect was noted between the two groups for cortisol and EEG measurements, namely an attenuation of acute cortisol response and EEG desynchronization in sodium salicylate group. Time effects were noted for EEG measurements, cortisol and salicylates levels. Significant correlations between cortisol and EEG parameters were noted. These findings have implications for designing effective analgesic regimens, and they suggest that EEG can be useful to monitor pain attributable to castration. © 2011 Blackwell Publishing Ltd.

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.

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.

EEG-Informed fMRI: A Review of Data Analysis Methods

PubMed Central

Abreu, Rodolfo; Leal, Alberto; Figueiredo, Patrícia

2018-01-01

The simultaneous acquisition of electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) is a very promising non-invasive technique for the study of human brain function. Despite continuous improvements, it remains a challenging technique, and a standard methodology for data analysis is yet to be established. Here we review the methodologies that are currently available to address the challenges at each step of the data analysis pipeline. We start by surveying methods for pre-processing both EEG and fMRI data. On the EEG side, we focus on the correction for several MR-induced artifacts, particularly the gradient and pulse artifacts, as well as other sources of EEG artifacts. On the fMRI side, we consider image artifacts induced by the presence of EEG hardware inside the MR scanner, and the contamination of the fMRI signal by physiological noise of non-neuronal origin, including a review of several approaches to model and remove it. We then provide an overview of the approaches specifically employed for the integration of EEG and fMRI when using EEG to predict the blood oxygenation level dependent (BOLD) fMRI signal, the so-called EEG-informed fMRI integration strategy, the most commonly used strategy in EEG-fMRI research. Finally, we systematically review methods used for the extraction of EEG features reflecting neuronal phenomena of interest. PMID:29467634

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

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.

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

Hemimegalencephaly: Clinical, EEG, neuroimaging, and IMP-SPECT correlation

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

Konkol, R.J.; Maister, B.H.; Wells, R.G.

1990-11-01

Iofetamine-single photon emission computed tomography (IMP-SPECT) was performed on 2 girls (5 1/2 and 6 years of age) with histories of intractable seizures, developmental delay, and unilateral hemiparesis secondary to hemimegalencephaly. Electroencephalography (EEG) revealed frequent focal discharges in 1 patient, while a nearly continuous burst suppression pattern over the malformed hemisphere was recorded in the other. IMP-SPECT demonstrated a good correlation with neuroimaging studies. In spite of the different EEG patterns, which had been proposed to predict contrasting clinical outcomes, both IMP-SPECT scans disclosed a similar decrease in tracer uptake in the malformed hemisphere. These results are consistent with themore » pattern of decreased tracer uptake found in other interictal studies of focal seizures without cerebral malformations. In view of recent recommendations for hemispherectomy in these patients, we suggest that the IMP-SPECT scan be used to compliment EEG as a method to define the extent of abnormality which may be more relevant to long-term prognosis than EEG alone.« less

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

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

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

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

Dry EEG Electrodes

PubMed Central

Lopez-Gordo, M. A.; Sanchez-Morillo, D.; Valle, F. Pelayo

2014-01-01

Electroencephalography (EEG) emerged in the second decade of the 20th century as a technique for recording the neurophysiological response. Since then, there has been little variation in the physical principles that sustain the signal acquisition probes, otherwise called electrodes. Currently, new advances in technology have brought new unexpected fields of applications apart from the clinical, for which new aspects such as usability and gel-free operation are first order priorities. Thanks to new advances in materials and integrated electronic systems technologies, a new generation of dry electrodes has been developed to fulfill the need. In this manuscript, we review current approaches to develop dry EEG electrodes for clinical and other applications, including information about measurement methods and evaluation reports. We conclude that, although a broad and non-homogeneous diversity of approaches has been evaluated without a consensus in procedures and methodology, their performances are not far from those obtained with wet electrodes, which are considered the gold standard, thus enabling the former to be a useful tool in a variety of novel applications. PMID:25046013

Automatic Seizure Detection in Rats Using Laplacian EEG and Verification with Human Seizure Signals

PubMed Central

Feltane, Amal; Boudreaux-Bartels, G. Faye; Besio, Walter

2012-01-01

Automated detection of seizures is still a challenging problem. This study presents an approach to detect seizure segments in Laplacian electroencephalography (tEEG) recorded from rats using the tripolar concentric ring electrode (TCRE) configuration. Three features, namely, median absolute deviation, approximate entropy, and maximum singular value were calculated and used as inputs into two different classifiers: support vector machines and adaptive boosting. The relative performance of the extracted features on TCRE tEEG was examined. Results are obtained with an overall accuracy between 84.81 and 96.51%. In addition to using TCRE tEEG data, the seizure detection algorithm was also applied to the recorded EEG signals from Andrzejak et al. database to show the efficiency of the proposed method for seizure detection. PMID:23073989

Change in Mean Frequency of Resting-State Electroencephalography after Transcranial Direct Current Stimulation

PubMed Central

Boonstra, Tjeerd W.; Nikolin, Stevan; Meisener, Ann-Christin; Martin, Donel M.; Loo, Colleen K.

2016-01-01

Transcranial direct current stimulation (tDCS) is proposed as a tool to investigate cognitive functioning in healthy people and as a treatment for various neuropathological disorders. However, the underlying cortical mechanisms remain poorly understood. We aim to investigate whether resting-state electroencephalography (EEG) can be used to monitor the effects of tDCS on cortical activity. To this end we tested whether the spectral content of ongoing EEG activity is significantly different after a single session of active tDCS compared to sham stimulation. Twenty participants were tested in a sham-controlled, randomized, crossover design. Resting-state EEG was acquired before, during and after active tDCS to the left dorsolateral prefrontal cortex (15 min of 2 mA tDCS) and sham stimulation. Electrodes with a diameter of 3.14 cm2 were used for EEG and tDCS. Partial least squares (PLS) analysis was used to examine differences in power spectral density (PSD) and the EEG mean frequency to quantify the slowing of EEG activity after stimulation. PLS revealed a significant increase in spectral power at frequencies below 15 Hz and a decrease at frequencies above 15 Hz after active tDCS (P = 0.001). The EEG mean frequency was significantly reduced after both active tDCS (P < 0.0005) and sham tDCS (P = 0.001), though the decrease in mean frequency was smaller after sham tDCS than after active tDCS (P = 0.073). Anodal tDCS of the left DLPFC using a high current density bi-frontal electrode montage resulted in general slowing of resting-state EEG. The similar findings observed following sham stimulation question whether the standard sham protocol is an appropriate control condition for tDCS. PMID:27375462

On the identification of sleep stages in mouse electroencephalography time-series.

PubMed

Lampert, Thomas; Plano, Andrea; Austin, Jim; Platt, Bettina

2015-05-15

The automatic identification of sleep stages in electroencephalography (EEG) time-series is a long desired goal for researchers concerned with the study of sleep disorders. This paper presents advances towards achieving this goal, with particular application to EEG time-series recorded from mice. Approaches in the literature apply supervised learning classifiers, however, these do not reach the performance levels required for use within a laboratory. In this paper, detection reliability is increased, most notably in the case of REM stage identification, by naturally decomposing the problem and applying a support vector machine (SVM) based classifier to each of the EEG channels. Their outputs are integrated within a multiple classifier system. Furthermore, there exists no general consensus on the ideal choice of parameter values in such systems. Therefore, an investigation into the effects upon the classification performance is presented by varying parameters such as the epoch length; features size; number of training samples; and the method for calculating the power spectral density estimate. Finally, the results of these investigations are brought together to demonstrate the performance of the proposed classification algorithm in two cases: intra-animal classification and inter-animal classification. It is shown that, within a dataset of 10 EEG recordings, and using less than 1% of an EEG as training data, a mean classification errors of Awake 6.45%, NREM 5.82%, and REM 6.65% (with standard deviations less than 0.6%) are achieved in intra-animal analysis and, when using the equivalent of 7% of one EEG as training data, Awake 10.19%, NREM 7.75%, and REM 17.43% are achieved in inter-animal analysis (with mean standard deviations of 6.42%, 2.89%, and 9.69% respectively). A software package implementing the proposed approach will be made available through Cybula Ltd. Copyright © 2015 Elsevier B.V. All rights reserved.

Non-invasive, home-based electroencephalography hypoglycaemia warning system for personal monitoring using skin surface electrodes: a single-case feasibility study.

PubMed

Clewett, Christopher J; Langley, Phillip; Bateson, Anthony D; Asghar, Aziz; Wilkinson, Antony J

2016-03-01

Hypoglycaemia unawareness is a common condition associated with increased risk of severe hypoglycaemia. The purpose of the authors' study was to develop a simple to use, home-based and non-invasive hypoglycaemia warning system based on electroencephalography (EEG), and to demonstrate its use in a single-case feasibility study. A participant with type 1 diabetes forms a single-person case study where blood sugar levels and EEG were recorded. EEG was recorded using skin surface electrodes placed behind the ear located within the T3 region by the participant in the home. EEG was analysed retrospectively to develop an algorithm which would trigger a warning if EEG changes associated with hypoglycaemia onset were detected. All hypoglycaemia events were detected by the EEG hypoglycaemia warning algorithm. Warnings were triggered with blood glucose concentration levels at or below 4.2 mmol/l in this participant and no warnings were issued when in euglycaemia. The feasibility of a non-invasive EEG-based hypoglycaemia warning system for personal monitoring in the home has been demonstrated in a single case study. The results suggest that further studies are warranted to evaluate the system prospectively in a larger group of participants.

Patient prognosis based on feature extraction, selection and classification of EEG periodic activity.

PubMed

Sánchez-González, Alain; García-Zapirain, Begoña; Maestro Saiz, Iratxe; Yurrebaso Santamaría, Izaskun

2015-01-01

Periodic activity in electroencephalography (PA-EEG) is shown as comprising a series of repetitive wave patterns that may appear in different cerebral regions and are due to many different pathologies. The diagnosis based on PA-EEG is an arduous task for experts in Clinical Neurophysiology, being mainly based on other clinical features of patients. Considering this difficulty in the diagnosis it is also very complicated to establish the prognosis of patients who present PA-EEG. The goal of this paper is to propose a method capable of determining patient prognosis based on characteristics of the PA-EEG activity. The approach, based on a parallel classification architecture and a majority vote system has proven successful by obtaining a success rate of 81.94% in the classification of patient prognosis of our database.

A review of classification algorithms for EEG-based brain-computer interfaces.

PubMed

Lotte, F; Congedo, M; Lécuyer, A; Lamarche, F; Arnaldi, B

2007-06-01

In this paper we review classification algorithms used to design brain-computer interface (BCI) systems based on electroencephalography (EEG). We briefly present the commonly employed algorithms and describe their critical properties. Based on the literature, we compare them in terms of performance and provide guidelines to choose the suitable classification algorithm(s) for a specific BCI.

Cerebrospinal Fluid Biomarkers of Alzheimer's Disease Correlate With Electroencephalography Parameters Assessed by Exact Low-Resolution Electromagnetic Tomography (eLORETA).

PubMed

Hata, Masahiro; Tanaka, Toshihisa; Kazui, Hiroaki; Ishii, Ryouhei; Canuet, Leonides; Pascual-Marqui, Roberto D; Aoki, Yasunori; Ikeda, Shunichiro; Sato, Shunsuke; Suzuki, Yukiko; Kanemoto, Hideki; Yoshiyama, Kenji; Iwase, Masao

2017-09-01

Recently, cerebrospinal fluid (CSF) biomarkers related to Alzheimer's disease (AD) have garnered a lot of clinical attention. To explore neurophysiological traits of AD and parameters for its clinical diagnosis, we examined the association between CSF biomarkers and electroencephalography (EEG) parameters in 14 probable AD patients. Using exact low-resolution electromagnetic tomography (eLORETA), artifact-free 40-sesond EEG data were estimated with current source density (CSD) and lagged phase synchronization (LPS) as the EEG parameters. Correlations between CSF biomarkers and the EEG parameters were assessed. Patients with AD showed significant negative correlation between CSF beta-amyloid (Aβ)-42 concentration and the logarithms of CSD over the right temporal area in the theta band. Total tau concentration was negatively correlated with the LPS between the left frontal eye field and the right auditory area in the alpha-2 band in patients with AD. Our study results suggest that AD biomarkers, in particular CSF Aβ42 and total tau concentrations are associated with the EEG parameters CSD and LPS, respectively. Our results could yield more insights into the complicated pathology of AD.

Long-lasting repetitive transcranial magnetic stimulation modulates electroencephalography oscillation in patients with disorders of consciousness.

PubMed

Xia, Xiaoyu; Liu, Yang; Bai, Yang; Liu, Ziyuan; Yang, Yi; Guo, Yongkun; Xu, Ruxiang; Gao, Xiaorong; Li, Xiaoli; He, Jianghong

2017-10-18

Repetitive transcranial magnetic stimulation (rTMS) has been applied for the treatment of patients with disorders of consciousness (DOC). Timely and accurate assessments of its modulation effects are very useful. This study evaluated rTMS modulation effects on electroencephalography (EEG) oscillation in patients with chronic DOC. Eighteen patients with a diagnosis of DOC lasting more than 3 months were recruited. All patients received one session of 10-Hz rTMS at the left dorsolateral prefrontal cortex and then 12 of them received consecutive rTMS treatment everyday for 20 consecutive days. Resting-state EEGs were recorded before the experiment (T0) after one session of rTMS (T1) and after the entire treatment (T2). The JFK Coma Recovery Scale-Revised scale scores were also recorded at the time points. Our data showed that application of 10-Hz rTMS to the left dorsolateral prefrontal cortex decreased low-frequency band power and increased high-frequency band power in DOC patients, especially in minimal conscious state patients. Considering the correlation of the EEG spectrum with the consciousness level of patients with DOC, quantitative EEG might be useful for assessment of the effect of rTMS in DOC patients.

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.

Resting-state qEEG predicts rate of second language learning in adults.

PubMed

Prat, Chantel S; Yamasaki, Brianna L; Kluender, Reina A; Stocco, Andrea

2016-01-01

Understanding the neurobiological basis of individual differences in second language acquisition (SLA) is important for research on bilingualism, learning, and neural plasticity. The current study used quantitative electroencephalography (qEEG) to predict SLA in college-aged individuals. Baseline, eyes-closed resting-state qEEG was used to predict language learning rate during eight weeks of French exposure using an immersive, virtual scenario software. Individual qEEG indices predicted up to 60% of the variability in SLA, whereas behavioral indices of fluid intelligence, executive functioning, and working-memory capacity were not correlated with learning rate. Specifically, power in beta and low-gamma frequency ranges over right temporoparietal regions were strongly positively correlated with SLA. These results highlight the utility of resting-state EEG for studying the neurobiological basis of SLA in a relatively construct-free, paradigm-independent manner. Published by Elsevier Inc.

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.

Synchronizing MIDI and wireless EEG measurements during natural piano performance.

PubMed

Zamm, Anna; Palmer, Caroline; Bauer, Anna-Katharina R; Bleichner, Martin G; Demos, Alexander P; Debener, Stefan

2017-07-08

Although music performance has been widely studied in the behavioural sciences, less work has addressed the underlying neural mechanisms, perhaps due to technical difficulties in acquiring high-quality neural data during tasks requiring natural motion. The advent of wireless electroencephalography (EEG) presents a solution to this problem by allowing for neural measurement with minimal motion artefacts. In the current study, we provide the first validation of a mobile wireless EEG system for capturing the neural dynamics associated with piano performance. First, we propose a novel method for synchronously recording music performance and wireless mobile EEG. Second, we provide results of several timing tests that characterize the timing accuracy of our system. Finally, we report EEG time domain and frequency domain results from N=40 pianists demonstrating that wireless EEG data capture the unique temporal signatures of musicians' performances with fine-grained precision and accuracy. Taken together, we demonstrate that mobile wireless EEG can be used to measure the neural dynamics of piano performance with minimal motion constraints. This opens many new possibilities for investigating the brain mechanisms underlying music performance. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluation of Electroencephalography Source Localization Algorithms with Multiple Cortical Sources.

PubMed

Bradley, Allison; Yao, Jun; Dewald, Jules; Richter, Claus-Peter

2016-01-01

Source localization algorithms often show multiple active cortical areas as the source of electroencephalography (EEG). Yet, there is little data quantifying the accuracy of these results. In this paper, the performance of current source density source localization algorithms for the detection of multiple cortical sources of EEG data has been characterized. EEG data were generated by simulating multiple cortical sources (2-4) with the same strength or two sources with relative strength ratios of 1:1 to 4:1, and adding noise. These data were used to reconstruct the cortical sources using current source density (CSD) algorithms: sLORETA, MNLS, and LORETA using a p-norm with p equal to 1, 1.5 and 2. Precision (percentage of the reconstructed activity corresponding to simulated activity) and Recall (percentage of the simulated sources reconstructed) of each of the CSD algorithms were calculated. While sLORETA has the best performance when only one source is present, when two or more sources are present LORETA with p equal to 1.5 performs better. When the relative strength of one of the sources is decreased, all algorithms have more difficulty reconstructing that source. However, LORETA 1.5 continues to outperform other algorithms. If only the strongest source is of interest sLORETA is recommended, while LORETA with p equal to 1.5 is recommended if two or more of the cortical sources are of interest. These results provide guidance for choosing a CSD algorithm to locate multiple cortical sources of EEG and for interpreting the results of these algorithms.

Evaluation of Electroencephalography Source Localization Algorithms with Multiple Cortical Sources

PubMed Central

Bradley, Allison; Yao, Jun; Dewald, Jules; Richter, Claus-Peter

2016-01-01

Background Source localization algorithms often show multiple active cortical areas as the source of electroencephalography (EEG). Yet, there is little data quantifying the accuracy of these results. In this paper, the performance of current source density source localization algorithms for the detection of multiple cortical sources of EEG data has been characterized. Methods EEG data were generated by simulating multiple cortical sources (2–4) with the same strength or two sources with relative strength ratios of 1:1 to 4:1, and adding noise. These data were used to reconstruct the cortical sources using current source density (CSD) algorithms: sLORETA, MNLS, and LORETA using a p-norm with p equal to 1, 1.5 and 2. Precision (percentage of the reconstructed activity corresponding to simulated activity) and Recall (percentage of the simulated sources reconstructed) of each of the CSD algorithms were calculated. Results While sLORETA has the best performance when only one source is present, when two or more sources are present LORETA with p equal to 1.5 performs better. When the relative strength of one of the sources is decreased, all algorithms have more difficulty reconstructing that source. However, LORETA 1.5 continues to outperform other algorithms. If only the strongest source is of interest sLORETA is recommended, while LORETA with p equal to 1.5 is recommended if two or more of the cortical sources are of interest. These results provide guidance for choosing a CSD algorithm to locate multiple cortical sources of EEG and for interpreting the results of these algorithms. PMID:26809000

Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy

PubMed Central

Papadelis, Christos; Tamilia, Eleonora; Stufflebeam, Steven; Grant, Patricia E.; Madsen, Joseph R.; Pearl, Phillip L.; Tanaka, Naoaki

2016-01-01

Crucial to the success of epilepsy surgery is the availability of a robust biomarker that identifies the Epileptogenic Zone (EZ). High Frequency Oscillations (HFOs) have emerged as potential presurgical biomarkers for the identification of the EZ in addition to Interictal Epileptiform Discharges (IEDs) and ictal activity. Although they are promising to localize the EZ, they are not yet suited for the diagnosis or monitoring of epilepsy in clinical practice. Primary barriers remain: the lack of a formal and global definition for HFOs; the consequent heterogeneity of methodological approaches used for their study; and the practical difficulties to detect and localize them noninvasively from scalp recordings. Here, we present a methodology for the recording, detection, and localization of interictal HFOs from pediatric patients with refractory epilepsy. We report representative data of HFOs detected noninvasively from interictal scalp EEG and MEG from two children undergoing surgery. The underlying generators of HFOs were localized by solving the inverse problem and their localization was compared to the Seizure Onset Zone (SOZ) as this was defined by the epileptologists. For both patients, Interictal Epileptogenic Discharges (IEDs) and HFOs were localized with source imaging at concordant locations. For one patient, intracranial EEG (iEEG) data were also available. For this patient, we found that the HFOs localization was concordant between noninvasive and invasive methods. The comparison of iEEG with the results from scalp recordings served to validate these findings. To our best knowledge, this is the first study that presents the source localization of scalp HFOs from simultaneous EEG and MEG recordings comparing the results with invasive recordings. These findings suggest that HFOs can be reliably detected and localized noninvasively with scalp EEG and MEG. We conclude that the noninvasive localization of interictal HFOs could significantly improve the

Combined electroencephalography-functional magnetic resonance imaging and electrical source imaging improves localization of pediatric focal epilepsy.

PubMed

Centeno, Maria; Tierney, Tim M; Perani, Suejen; Shamshiri, Elhum A; St Pier, Kelly; Wilkinson, Charlotte; Konn, Daniel; Vulliemoz, Serge; Grouiller, Frédéric; Lemieux, Louis; Pressler, Ronit M; Clark, Christopher A; Cross, J Helen; Carmichael, David W

2017-08-01

Surgical treatment in epilepsy is effective if the epileptogenic zone (EZ) can be correctly localized and characterized. Here we use simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) data to derive EEG-fMRI and electrical source imaging (ESI) maps. Their yield and their individual and combined ability to (1) localize the EZ and (2) predict seizure outcome were then evaluated. Fifty-three children with drug-resistant epilepsy underwent EEG-fMRI. Interictal discharges were mapped using both EEG-fMRI hemodynamic responses and ESI. A single localization was derived from each individual test (EEG-fMRI global maxima [GM]/ESI maximum) and from the combination of both maps (EEG-fMRI/ESI spatial intersection). To determine the localization accuracy and its predictive performance, the individual and combined test localizations were compared to the presumed EZ and to the postsurgical outcome. Fifty-two of 53 patients had significant maps: 47 of 53 for EEG-fMRI, 44 of 53 for ESI, and 34 of 53 for both. The EZ was well characterized in 29 patients; 26 had an EEG-fMRI GM localization that was correct in 11, 22 patients had ESI localization that was correct in 17, and 12 patients had combined EEG-fMRI and ESI that was correct in 11. Seizure outcome following resection was correctly predicted by EEG-fMRI GM in 8 of 20 patients, and by the ESI maximum in 13 of 16. The combined EEG-fMRI/ESI region entirely predicted outcome in 9 of 9 patients, including 3 with no lesion visible on MRI. EEG-fMRI combined with ESI provides a simple unbiased localization that may predict surgery better than each individual test, including in MRI-negative patients. Ann Neurol 2017;82:278-287. © 2017 American Neurological Association.

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.

Graph theory network function in Parkinson's disease assessed with electroencephalography.

PubMed

Utianski, Rene L; Caviness, John N; van Straaten, Elisabeth C W; Beach, Thomas G; Dugger, Brittany N; Shill, Holly A; Driver-Dunckley, Erika D; Sabbagh, Marwan N; Mehta, Shyamal; Adler, Charles H; Hentz, Joseph G

2016-05-01

To determine what differences exist in graph theory network measures derived from electroencephalography (EEG), between Parkinson's disease (PD) patients who are cognitively normal (PD-CN) and matched healthy controls; and between PD-CN and PD dementia (PD-D). EEG recordings were analyzed via graph theory network analysis to quantify changes in global efficiency and local integration. This included minimal spanning tree analysis. T-tests and correlations were used to assess differences between groups and assess the relationship with cognitive performance. Network measures showed increased local integration across all frequency bands between control and PD-CN; in contrast, decreased local integration occurred in PD-D when compared to PD-CN in the alpha1 frequency band. Differences found in PD-MCI mirrored PD-D. Correlations were found between network measures and assessments of global cognitive performance in PD. Our results reveal distinct patterns of band and network measure type alteration and breakdown for PD, as well as with cognitive decline in PD. These patterns suggest specific ways that interaction between cortical areas becomes abnormal and contributes to PD symptoms at various stages. Graph theory analysis by EEG suggests that network alteration and breakdown are robust attributes of PD cortical dysfunction pathophysiology. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Remembered or Forgotten?—An EEG-Based Computational Prediction Approach

PubMed Central

Sun, Xuyun; Qian, Cunle; Chen, Zhongqin; Wu, Zhaohui; Luo, Benyan; Pan, Gang

2016-01-01

Prediction of memory performance (remembered or forgotten) has various potential applications not only for knowledge learning but also for disease diagnosis. Recently, subsequent memory effects (SMEs)—the statistical differences in electroencephalography (EEG) signals before or during learning between subsequently remembered and forgotten events—have been found. This finding indicates that EEG signals convey the information relevant to memory performance. In this paper, based on SMEs we propose a computational approach to predict memory performance of an event from EEG signals. We devise a convolutional neural network for EEG, called ConvEEGNN, to predict subsequently remembered and forgotten events from EEG recorded during memory process. With the ConvEEGNN, prediction of memory performance can be achieved by integrating two main stages: feature extraction and classification. To verify the proposed approach, we employ an auditory memory task to collect EEG signals from scalp electrodes. For ConvEEGNN, the average prediction accuracy was 72.07% by using EEG data from pre-stimulus and during-stimulus periods, outperforming other approaches. It was observed that signals from pre-stimulus period and those from during-stimulus period had comparable contributions to memory performance. Furthermore, the connection weights of ConvEEGNN network can reveal prominent channels, which are consistent with the distribution of SME studied previously. PMID:27973531

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

Localizing seizure-onset zones in presurgical evaluation of drug-resistant epilepsy by electroencephalography/fMRI: effectiveness of alternative thresholding strategies.

PubMed

Hauf, M; Jann, K; Schindler, K; Scheidegger, O; Meyer, K; Rummel, C; Mariani, L; Koenig, T; Wiest, R

2012-10-01

Simultaneous EEG/fMRI is an effective noninvasive tool for identifying and localizing the SOZ in patients with focal epilepsy. In this study, we evaluated different thresholding strategies in EEG/fMRI for the assessment of hemodynamic responses to IEDs in the SOZ of drug-resistant epilepsy. Sixteen patients with focal epilepsy were examined by using simultaneous 92-channel EEG and BOLD fMRI. The temporal fluctuation of epileptiform signals on the EEG was extracted by independent component analysis to predict the hemodynamic responses to the IEDs. We applied 3 different threshold criteria to detect hemodynamic responses within the SOZ: 1) PA, 2) a fixed threshold at P < .05 corrected for multiple comparison (FWE), and 3) FAV (4000 ± 200 activated voxels within the brain). PA identified the SOZ in 9 of 16 patients; FWE resulted in concordant BOLD signal correlates in 11 of 16, and FAV in 13 of 16 patients. Hemodynamic responses were detected within the resected areas in 5 (PA), 6 (FWE), and 8 (FAV) of 10 patients who remained seizure-free after surgery. EEG/fMRI is a noninvasive tool for the presurgical work-up of patients with epilepsy, which can be performed during seizure-free periods and is complementary to the ictal electroclinical assessment. Our findings suggest that the effectiveness of EEG/fMRI in delineating the SOZ may be further improved by the additional use of alternative analysis strategies such as FAV.

Decoding human mental states by whole-head EEG+fNIRS during category fluency task performance

NASA Astrophysics Data System (ADS)

Omurtag, Ahmet; Aghajani, Haleh; Onur Keles, Hasan

2017-12-01

Objective. Concurrent scalp electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), which we refer to as EEG+fNIRS, promises greater accuracy than the individual modalities while remaining nearly as convenient as EEG. We sought to quantify the hybrid system’s ability to decode mental states and compare it with its unimodal components. Approach. We recorded from healthy volunteers taking the category fluency test and applied machine learning techniques to the data. Main results. EEG+fNIRS’s decoding accuracy was greater than that of its subsystems, partly due to the new type of neurovascular features made available by hybrid data. Significance. Availability of an accurate and practical decoding method has potential implications for medical diagnosis, brain-computer interface design, and neuroergonomics.

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.

Design, Fabrication, and Experimental Validation of Novel Flexible Silicon-Based Dry Sensors for Electroencephalography Signal Measurements

PubMed Central

Yu, Yi-Hsin; Lu, Shao-Wei; Liao, Lun-De; Lin, Chin-Teng

2014-01-01

Many commercially available electroencephalography (EEG) sensors, including conventional wet and dry sensors, can cause skin irritation and user discomfort owing to the foreign material. The EEG products, especially sensors, highly prioritize the comfort level during devices wear. To overcome these drawbacks for EEG sensors, this paper designs Societe Generale de Surveillance S \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$\\cdot $ \\end{document} A \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$\\cdot $ \\end{document} (SGS)-certified, silicon-based dry-contact EEG sensors (SBDSs) for EEG signal measurements. According to the SGS testing report, SBDSs extract does not irritate skin or induce noncytotoxic effects on L929 cells according to ISO10993-5. The SBDS is also lightweight, flexible, and nonirritating to the skin, as well as capable of easily fitting to scalps without any skin preparation or use of a conductive gel. For forehead and hairy sites, EEG signals can be measured reliably with the designed SBDSs. In particular, for EEG signal measurements at hairy sites, the acicular and flexible design of SBDS can push the hair aside to achieve satisfactory scalp contact, as well as maintain low skin-electrode interface impedance. Results of this paper demonstrate that the proposed sensors perform well in the EEG measurements and are feasible for practical applications. PMID:27170884

Interrater agreement in the interpretation of neonatal electroencephalography in hypoxic-ischemic encephalopathy.

PubMed

Wusthoff, Courtney J; Sullivan, Joseph; Glass, Hannah C; Shellhaas, Renée A; Abend, Nicholas S; Chang, Taeun; Tsuchida, Tammy N

2017-03-01

Research using neonatal electroencephalography (EEG) has been limited by a lack of a standardized classification system and interpretation terminology. In 2013, the American Clinical Neurophysiology Society (ACNS) published a guideline for standardized terminology and categorization in the description of continuous EEG in neonates. We sought to assess interrater agreement for this neonatal EEG categorization system as applied by a group of pediatric neurophysiologists. A total of 60 neonatal EEG studies were collected from three institutions. All EEG segments were from term neonates with hypoxic-ischemic encephalopathy. Three pediatric neurophysiologists independently reviewed each record using the ACNS standardized scoring system. Unweighted kappa values were calculated for interrater agreement of categorical data across multiple observers. Interrater agreement was very good for identification of seizures (κ = 0.93, p < 0.001), with perfect agreement in 95% of records (57 of 60). Interrater agreement was moderate for classifying records as normal or having any abnormality (κ = 0.49, p < 0.001), with perfect agreement in 78% of records (47 of 60). Interrater agreement was good in classifying EEG backgrounds on a 5-category scale (normal, excessively discontinuous, burst suppression, status epilepticus, or electrocerebral inactivity) (κ = 0.70, p < 0.001), with perfect agreement in 72% of records (43 of 60). Other specific background features had lower agreement, including voltage (κ = 0.41, p < 0.001), variability (κ = 0.35, p < 0.001), symmetry (κ = 0.18, p = 0.01), presence of abnormal sharp waves (κ < 0.20, p < 0.05), and presence of brief rhythmic discharges (κ < 0.20, p < 0.05). We found good or very good interrater agreement applying the ACNS system for identification of seizures and classification of EEG background. Other specific EEG features showed limited interrater agreement. Of importance to both clinicians and

Stimulus-dependent spiking relationships with the EEG

PubMed Central

Snyder, Adam C.

2015-01-01

The development and refinement of noninvasive techniques for imaging neural activity is of paramount importance for human neuroscience. Currently, the most accessible and popular technique is electroencephalography (EEG). However, nearly all of what we know about the neural events that underlie EEG signals is based on inference, because of the dearth of studies that have simultaneously paired EEG recordings with direct recordings of single neurons. From the perspective of electrophysiologists there is growing interest in understanding how spiking activity coordinates with large-scale cortical networks. Evidence from recordings at both scales highlights that sensory neurons operate in very distinct states during spontaneous and visually evoked activity, which appear to form extremes in a continuum of coordination in neural networks. We hypothesized that individual neurons have idiosyncratic relationships to large-scale network activity indexed by EEG signals, owing to the neurons' distinct computational roles within the local circuitry. We tested this by recording neuronal populations in visual area V4 of rhesus macaques while we simultaneously recorded EEG. We found substantial heterogeneity in the timing and strength of spike-EEG relationships and that these relationships became more diverse during visual stimulation compared with the spontaneous state. The visual stimulus apparently shifts V4 neurons from a state in which they are relatively uniformly embedded in large-scale network activity to a state in which their distinct roles within the local population are more prominent, suggesting that the specific way in which individual neurons relate to EEG signals may hold clues regarding their computational roles. PMID:26108954

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

Portable Amplifier Design for a Novel EEG Monitor in Point-of-Care Applications.

PubMed

Luan, Bo; Sun, Mingui; Jia, Wenyan

2012-01-01

The Electroencephalography (EEG) is a common diagnostic tool for neurological diseases and dysfunctions, such as epilepsy and insomnia. However, the current EEG technology cannot be utilized quickly and conveniently at the point of care due to the complex skin preparation procedures required and the inconvenient EEG data acquisition systems. This work presents a portable amplifier design that integrates a set of skin screw electrodes and a wireless data link. The battery-operated amplifier contains an instrumentation amplifier, two noninverting amplifiers, two high-pass filters, and a low-pass filter. It is able to magnify the EEG signals over 10,000 times and has a high impedance, low noise, small size and low weight. Our electrode and amplifier are ideal for point-of-care applications, especially during transportation of patients suffering from traumatic brain injury or stroke.

Design, fabrication and experimental validation of a novel dry-contact sensor for measuring electroencephalography signals without skin preparation.

PubMed

Liao, Lun-De; Wang, I-Jan; Chen, Sheng-Fu; Chang, Jyh-Yeong; Lin, Chin-Teng

2011-01-01

In the present study, novel dry-contact sensors for measuring electro-encephalography (EEG) signals without any skin preparation are designed, fabricated by an injection molding manufacturing process and experimentally validated. Conventional wet electrodes are commonly used to measure EEG signals; they provide excellent EEG signals subject to proper skin preparation and conductive gel application. However, a series of skin preparation procedures for applying the wet electrodes is always required and usually creates trouble for users. To overcome these drawbacks, novel dry-contact EEG sensors were proposed for potential operation in the presence or absence of hair and without any skin preparation or conductive gel usage. The dry EEG sensors were designed to contact the scalp surface with 17 spring contact probes. Each probe was designed to include a probe head, plunger, spring, and barrel. The 17 probes were inserted into a flexible substrate using a one-time forming process via an established injection molding procedure. With these 17 spring contact probes, the flexible substrate allows for high geometric conformity between the sensor and the irregular scalp surface to maintain low skin-sensor interface impedance. Additionally, the flexible substrate also initiates a sensor buffer effect, eliminating pain when force is applied. The proposed dry EEG sensor was reliable in measuring EEG signals without any skin preparation or conductive gel usage, as compared with the conventional wet electrodes.

Design, Fabrication and Experimental Validation of a Novel Dry-Contact Sensor for Measuring Electroencephalography Signals without Skin Preparation

PubMed Central

Liao, Lun-De; Wang, I-Jan; Chen, Sheng-Fu; Chang, Jyh-Yeong; Lin, Chin-Teng

2011-01-01

In the present study, novel dry-contact sensors for measuring electro-encephalography (EEG) signals without any skin preparation are designed, fabricated by an injection molding manufacturing process and experimentally validated. Conventional wet electrodes are commonly used to measure EEG signals; they provide excellent EEG signals subject to proper skin preparation and conductive gel application. However, a series of skin preparation procedures for applying the wet electrodes is always required and usually creates trouble for users. To overcome these drawbacks, novel dry-contact EEG sensors were proposed for potential operation in the presence or absence of hair and without any skin preparation or conductive gel usage. The dry EEG sensors were designed to contact the scalp surface with 17 spring contact probes. Each probe was designed to include a probe head, plunger, spring, and barrel. The 17 probes were inserted into a flexible substrate using a one-time forming process via an established injection molding procedure. With these 17 spring contact probes, the flexible substrate allows for high geometric conformity between the sensor and the irregular scalp surface to maintain low skin-sensor interface impedance. Additionally, the flexible substrate also initiates a sensor buffer effect, eliminating pain when force is applied. The proposed dry EEG sensor was reliable in measuring EEG signals without any skin preparation or conductive gel usage, as compared with the conventional wet electrodes. PMID:22163929

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

Sedation for electroencephalography with dexmedetomidine or chloral hydrate: a comparative study on the qualitative and quantitative electroencephalogram pattern.

PubMed

Fernandes, Magda L; Oliveira, Welser Machado de; Santos, Maria do Carmo Vasconcellos; Gomez, Renato S

2015-01-01

Sedation for electroencephalography in uncooperative patients is a controversial issue because majority of sedatives, hypnotics, and general anesthetics interfere with the brain's electrical activity. Chloral hydrate (CH) is typically used for this sedation, and dexmedetomidine (DEX) was recently tested because preliminary data suggest that this drug does not affect the electroencephalogram (EEG). The aim of the present study was to compare the EEG pattern during DEX or CH sedation to test the hypothesis that both drugs exert similar effects on the EEG. A total of 17 patients underwent 2 EEGs on 2 separate occasions, one with DEX and the other with CH. The EEG qualitative variables included the phases of sleep and the background activity. The EEG quantitative analysis was performed during the first 2 minutes of the second stage of sleep. The EEG quantitative variables included density, duration, and amplitude of the sleep spindles and absolute spectral power. The results showed that the qualitative analysis, density, duration, and amplitude of sleep spindles did not differ between DEX and CH sedation. The power of the slow-frequency bands (δ and θ) was higher with DEX, but the power of the faster-frequency bands (α and β) was higher with CH. The total power was lower with DEX than with CH. The differences of DEX and CH in EEG power did not change the EEG qualitative interpretation, which was similar with the 2 drugs. Other studies comparing natural sleep and sleep induced by these drugs are needed to clarify the clinical relevance of the observed EEG quantitative differences.

A review on EEG-based methods for screening and diagnosing alcohol use disorder.

PubMed

Mumtaz, Wajid; Vuong, Pham Lam; Malik, Aamir Saeed; Rashid, Rusdi Bin Abd

2018-04-01

The screening test for alcohol use disorder (AUD) patients has been of subjective nature and could be misleading in particular cases such as a misreporting the actual quantity of alcohol intake. Although the neuroimaging modality such as electroencephalography (EEG) has shown promising research results in achieving objectivity during the screening and diagnosis of AUD patients. However, the translation of these findings for clinical applications has been largely understudied and hence less clear. This study advocates the use of EEG as a diagnostic and screening tool for AUD patients that may help the clinicians during clinical decision making. In this context, a comprehensive review on EEG-based methods is provided including related electrophysiological techniques reported in the literature. More specifically, the EEG abnormalities associated with the conditions of AUD patients are summarized. The aim is to explore the potentials of objective techniques involving quantities/features derived from resting EEG, event-related potentials or event-related oscillations data.

Evaluation of a Prototype Low-Cost, Modular, Wireless Electroencephalography (EEG) Headset Design for Widespread Application

DTIC Science & Technology

2016-06-01

therefore did not implement or test actual sensors or electronic components (analog-to-digital conversion, power , and the wireless transmission ...ARL-TR-7703 ● JUNE 2016 US Army Research Laboratory Evaluation of a Prototype Low-Cost, Modular, Wireless Electroencephalography...originator. ARL-TR-7703 ● JUNE 2016 US Army Research Laboratory Evaluation of a Prototype Low-Cost, Modular, Wireless

High-resolution imaging-guided electroencephalography source localization: temporal effect regularization incorporation in LORETA inverse solution

NASA Astrophysics Data System (ADS)

Boughariou, Jihene; Zouch, Wassim; Slima, Mohamed Ben; Kammoun, Ines; Hamida, Ahmed Ben

2015-11-01

Electroencephalography (EEG) and magnetic resonance imaging (MRI) are noninvasive neuroimaging modalities. They are widely used and could be complementary. The fusion of these modalities may enhance some emerging research fields targeting the exploration better brain activities. Such research attracted various scientific investigators especially to provide a convivial and helpful advanced clinical-aid tool enabling better neurological explorations. Our present research was, in fact, in the context of EEG inverse problem resolution and investigated an advanced estimation methodology for the localization of the cerebral activity. Our focus was, therefore, on the integration of temporal priors to low-resolution brain electromagnetic tomography (LORETA) formalism and to solve the inverse problem in the EEG. The main idea behind our proposed method was in the integration of a temporal projection matrix within the LORETA weighting matrix. A hyperparameter is the principal fact for such a temporal integration, and its importance would be obvious when obtaining a regularized smoothness solution. Our experimental results clearly confirmed the impact of such an optimization procedure adopted for the temporal regularization parameter comparatively to the LORETA method.

Nonconvulsive status epilepticus after cessation of convulsive status epilepticus in pediatric intensive care unit patients.

PubMed

Chen, Jin; Xie, Lingling; Hu, Yue; Lan, Xinghui; Jiang, Li

2018-05-01

Little is known about pediatric patients suffering from nonconvulsive status epilepticus (NCSE) after convulsive status epilepticus (CSE) cessation. The aim of this study was to identify in pediatric patients the clinical characteristics of NCSE after CSE cessation and the factors that contribute to patient outcomes. Data from clinical features, electroencephalography (EEG) characteristics, neuroimaging findings, treatments, and prognosis were systematically summarized, and the associations between clinical characteristics and prognosis were quantified. Thirty-eight children aged 51days-14years, 2months were identified in the Chongqing Medical University pediatric intensive care unit as having experienced NCSE after CSE cessation between October 1, 2014 and April 1, 2017. All patients were comatose, 15 of whom presented subtle motor signs. The most common underlying etiology was acute central nervous system (CNS) infection. Electroencephalography (EEG) data showed that, during the NCSE period, all patients had several discrete episodes (lasting from 30s to 6h long), and the most common duration was 1-5min. The ictal onset locations were classified as focal (16 patients, 42.1%), multiregional independent (10 patients, 26.3%), and generalized (12 patients, 31.6%). Wave morphologies varied during the ictal and interictal periods. Neuroimaging detected signal abnormalities in the cerebral cortex or subcortex of 33 patients with NCSE (87%), which were classified as either multifocal and consistent with extensive cortical edema (21 patients, 55.3%) or focal (12 patients, 31.6%). Twelve patients were on continuous intravenous phenobarbital, and 31 were on continuous infusion of either midazolam (27 patients) or propofol (4 patients). At least one other antiepileptic drug was prescribed for 32 patients. Three patients were on mild hypothermia therapy. The duration of NCSE lasted <24h for 20 patients and >24h for 18 patients. The mortality rate was 21.1%, and half of the

[Time-organization of EEG patterns' structure in anxiety and phobic disorders].

PubMed

Sviatogor, I A; Mokhovikova, I A

2005-01-01

Thirty-five patients, aged 19-48 years (mean age 38 years) with anxiety and phobic disorders were examined. According to ICD-10 criteria--social phobia (F40.1), panic disorder (F41.0), somatoform autonomic dysfunction (F45.3) were diagnosed. Using electroencephalography data, qualitative and quantitative characteristics of the time- and spatial-organization of brain EEG activity in anxiety and phobic disorders of different severity were established. It were determined 4 types of wave interactions between EEG components, which reflected a different extent of the regulatory mechanisms lesions: 2 structures with one core component (alpha or beta), a structure with two core components and a non-organized structure.

Brain-computer interface with language model-electroencephalography fusion for locked-in syndrome.

PubMed

Oken, Barry S; Orhan, Umut; Roark, Brian; Erdogmus, Deniz; Fowler, Andrew; Mooney, Aimee; Peters, Betts; Miller, Meghan; Fried-Oken, Melanie B

2014-05-01

Some noninvasive brain-computer interface (BCI) systems are currently available for locked-in syndrome (LIS) but none have incorporated a statistical language model during text generation. To begin to address the communication needs of individuals with LIS using a noninvasive BCI that involves rapid serial visual presentation (RSVP) of symbols and a unique classifier with electroencephalography (EEG) and language model fusion. The RSVP Keyboard was developed with several unique features. Individual letters are presented at 2.5 per second. Computer classification of letters as targets or nontargets based on EEG is performed using machine learning that incorporates a language model for letter prediction via Bayesian fusion enabling targets to be presented only 1 to 4 times. Nine participants with LIS and 9 healthy controls were enrolled. After screening, subjects first calibrated the system, and then completed a series of balanced word generation mastery tasks that were designed with 5 incremental levels of difficulty, which increased by selecting phrases for which the utility of the language model decreased naturally. Six participants with LIS and 9 controls completed the experiment. All LIS participants successfully mastered spelling at level 1 and one subject achieved level 5. Six of 9 control participants achieved level 5. Individuals who have incomplete LIS may benefit from an EEG-based BCI system, which relies on EEG classification and a statistical language model. Steps to further improve the system are discussed.

Compliant head probe for positioning electroencephalography electrodes and near-infrared spectroscopy optodes

NASA Astrophysics Data System (ADS)

Giacometti, Paolo; Diamond, Solomon G.

2013-02-01

A noninvasive head probe that combines near-infrared spectroscopy (NIRS) and electroencephalography (EEG) for simultaneous measurement of neural dynamics and hemodynamics in the brain is presented. It is composed of a compliant expandable mechanism that accommodates a wide range of head size variation and an elastomeric web that maintains uniform sensor contact pressure on the scalp as the mechanism expands and contracts. The design is intended to help maximize optical and electrical coupling and to maintain stability during head movement. Positioning electrodes at the inion, nasion, central, and preauricular fiducial locations mechanically shapes the probe to place 64 NIRS optodes and 65 EEG electrodes following the 10-5 scalp coordinates. The placement accuracy, precision, and scalp pressure uniformity of the sensors are evaluated. A root-mean-squared (RMS) positional precision of 0.89±0.23 mm, percent arc subdivision RMS accuracy of 0.19±0.15%, and mean normal force on the scalp of 2.28±0.88 N at 5 mm displacement were found. Geometric measurements indicate that the probe will accommodate the full range of adult head sizes. The placement accuracy, precision, and uniformity of sensor contact pressure of the proposed head probe are important determinants of data quality in noninvasive brain monitoring with simultaneous NIRS-EEG.

Relation of insulin resistance to neurocognitive function and electroencephalography in obese children.

PubMed

Akın, Onur; Eker, İbrahim; Arslan, Mutluay; Yavuz, Süleyman Tolga; Akman, Sevil; Taşçılar, Mehmet Emre; Ünay, Bülent

2017-10-26

Childhood obesity may lead to neuronal impairment in both the peripheral and the central nervous system. This study aimed to investigate the impact of obesity and insulin resistance (IR) on the central nervous system and neurocognitive functions in children. Seventy-three obese children (38 male and 35 female) and 42 healthy children (21 male and 21 female) were recruited. Standard biochemical indices and IR were evaluated. The Wechsler Intelligence Scale for Children-Revised (WISC-R) and electroencephalography (EEG) were administered to all participants. The obese participants were divided into two groups based on the presence or absence of IR, and the data were compared between the subgroups. Only verbal scores on the WISC-R in the IR+ group were significantly lower than those of the control and IR- groups. There were no differences between the groups with respect to other parameters of the WISC-R or the EEG. Verbal scores of the WISC-R were negatively correlated with obesity duration and homeostatic model assessment-insulin resistance (HOMA-IR) values. EEGs showed significantly more frequent 'slowing during hyperventilation' (SDHs) in obese children than non-obese children. Neurocognitive functions, particularly verbal abilities, were impaired in obese children with IR. An early examination of cognitive functions may help identify and correct such abnormalities in obese children.

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

Detecting large-scale networks in the human brain using high-density electroencephalography.

PubMed

Liu, Quanying; Farahibozorg, Seyedehrezvan; Porcaro, Camillo; Wenderoth, Nicole; Mantini, Dante

2017-09-01

High-density electroencephalography (hdEEG) is an emerging brain imaging technique that can be used to investigate fast dynamics of electrical activity in the healthy and the diseased human brain. Its applications are however currently limited by a number of methodological issues, among which the difficulty in obtaining accurate source localizations. In particular, these issues have so far prevented EEG studies from reporting brain networks similar to those previously detected by functional magnetic resonance imaging (fMRI). Here, we report for the first time a robust detection of brain networks from resting state (256-channel) hdEEG recordings. Specifically, we obtained 14 networks previously described in fMRI studies by means of realistic 12-layer head models and exact low-resolution brain electromagnetic tomography (eLORETA) source localization, together with independent component analysis (ICA) for functional connectivity analysis. Our analyses revealed three important methodological aspects. First, brain network reconstruction can be improved by performing source localization using the gray matter as source space, instead of the whole brain. Second, conducting EEG connectivity analyses in individual space rather than on concatenated datasets may be preferable, as it permits to incorporate realistic information on head modeling and electrode positioning. Third, the use of a wide frequency band leads to an unbiased and generally accurate reconstruction of several network maps, whereas filtering data in a narrow frequency band may enhance the detection of specific networks and penalize that of others. We hope that our methodological work will contribute to rise of hdEEG as a powerful tool for brain research. Hum Brain Mapp 38:4631-4643, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Resting state EEG abnormalities in autism spectrum disorders

PubMed Central

2013-01-01

Autism spectrum disorders (ASD) are a group of complex and heterogeneous developmental disorders involving multiple neural system dysfunctions. In an effort to understand neurophysiological substrates, identify etiopathophysiologically distinct subgroups of patients, and track outcomes of novel treatments with translational biomarkers, EEG (electroencephalography) studies offer a promising research strategy in ASD. Resting-state EEG studies of ASD suggest a U-shaped profile of electrophysiological power alterations, with excessive power in low-frequency and high-frequency bands, abnormal functional connectivity, and enhanced power in the left hemisphere of the brain. In this review, we provide a summary of recent findings, discuss limitations in available research that may contribute to inconsistencies in the literature, and offer suggestions for future research in this area for advancing the understanding of ASD. PMID:24040879

Combining near-infrared spectroscopy with electroencephalography and repetitive transcranial magnetic stimulation

NASA Astrophysics Data System (ADS)

Näsi, Tiina; Kotilahti, Kalle; Mäki, Hanna; Nissilä, Ilkka; Meriläinen, Pekka

2009-07-01

The objective of the study was to assess the usability of a near-infrared spectroscopy (NIRS) device in multimodal measurements. We combined NIRS with electroencephalography (EEG) to record hemodynamic responses and evoked potentials simultaneously, and with transcranial magnetic stimulation (TMS) to investigate hemodynamic responses to repetitive TMS (rTMS). Hemodynamic responses and visual evoked potentials (VEPs) to 3, 6, and 12 s stimuli consisting of pattern-reversing checkerboards were successfully recorded in the NIRS/EEG measurement, and ipsi- and contralateral hemodynamic responses to 0.5, 1, and 2 Hz rTMS in the NIRS/TMS measurement. In the NIRS/EEG measurements, the amplitudes of the hemodynamic responses increased from 3- to 6-s stimulus, but not from 6- to 12-s stimulus, and the VEPs showed peaks N75, P100, and N135. In the NIRS/TMS measurements, the 2-Hz stimulus produced the strongest hemodynamic responses compared to the 0.5- and 1-Hz stimuli. In two subjects oxyhemoglobin concentration decreased and in one increased as a consequence of the 2-Hz rTMS. To locate the origin of the measured NIRS responses, methods have to be developed to investigate TMS-induced scalp muscle contractions. In the future, multimodal measurements may prove useful in monitoring or treating diseases such as stroke or Alzheimer's disease.

Effects of signal artefacts on electroencephalography spectral power during sleep: quantifying the effectiveness of automated artefact-rejection algorithms.

PubMed

Liu, Jianbo; Ramakrishnan, Sridhar; Laxminarayan, Srinivas; Neal, Maxwell; Cashmere, David J; Germain, Anne; Reifman, Jaques

2018-02-01

Electroencephalography (EEG) recordings during sleep are often contaminated by muscle and ocular artefacts, which can affect the results of spectral power analyses significantly. However, the extent to which these artefacts affect EEG spectral power across different sleep states has not been quantified explicitly. Consequently, the effectiveness of automated artefact-rejection algorithms in minimizing these effects has not been characterized fully. To address these issues, we analysed standard 10-channel EEG recordings from 20 subjects during one night of sleep. We compared their spectral power when the recordings were contaminated by artefacts and after we removed them by visual inspection or by using automated artefact-rejection algorithms. During both rapid eye movement (REM) and non-REM (NREM) sleep, muscle artefacts contaminated no more than 5% of the EEG data across all channels. However, they corrupted delta, beta and gamma power levels substantially by up to 126, 171 and 938%, respectively, relative to the power level computed from artefact-free data. Although ocular artefacts were infrequent during NREM sleep, they affected up to 16% of the frontal and temporal EEG channels during REM sleep, primarily corrupting delta power by up to 33%. For both REM and NREM sleep, the automated artefact-rejection algorithms matched power levels to within ~10% of the artefact-free power level for each EEG channel and frequency band. In summary, although muscle and ocular artefacts affect only a small fraction of EEG data, they affect EEG spectral power significantly. This suggests the importance of using artefact-rejection algorithms before analysing EEG data. © 2017 European Sleep Research Society.

Information-Theoretical Analysis of EEG Microstate Sequences in Python.

PubMed

von Wegner, Frederic; Laufs, Helmut

2018-01-01

We present an open-source Python package to compute information-theoretical quantities for electroencephalographic data. Electroencephalography (EEG) measures the electrical potential generated by the cerebral cortex and the set of spatial patterns projected by the brain's electrical potential on the scalp surface can be clustered into a set of representative maps called EEG microstates. Microstate time series are obtained by competitively fitting the microstate maps back into the EEG data set, i.e., by substituting the EEG data at a given time with the label of the microstate that has the highest similarity with the actual EEG topography. As microstate sequences consist of non-metric random variables, e.g., the letters A-D, we recently introduced information-theoretical measures to quantify these time series. In wakeful resting state EEG recordings, we found new characteristics of microstate sequences such as periodicities related to EEG frequency bands. The algorithms used are here provided as an open-source package and their use is explained in a tutorial style. The package is self-contained and the programming style is procedural, focusing on code intelligibility and easy portability. Using a sample EEG file, we demonstrate how to perform EEG microstate segmentation using the modified K-means approach, and how to compute and visualize the recently introduced information-theoretical tests and quantities. The time-lagged mutual information function is derived as a discrete symbolic alternative to the autocorrelation function for metric time series and confidence intervals are computed from Markov chain surrogate data. The software package provides an open-source extension to the existing implementations of the microstate transform and is specifically designed to analyze resting state EEG recordings.

3D Printed Dry EEG Electrodes

PubMed Central

Krachunov, Sammy; Casson, Alexander J.

2016-01-01

Electroencephalography (EEG) is a procedure that records brain activity in a non-invasive manner. The cost and size of EEG devices has decreased in recent years, facilitating a growing interest in wearable EEG that can be used out-of-the-lab for a wide range of applications, from epilepsy diagnosis, to stroke rehabilitation, to Brain-Computer Interfaces (BCI). A major obstacle for these emerging applications is the wet electrodes, which are used as part of the EEG setup. These electrodes are attached to the human scalp using a conductive gel, which can be uncomfortable to the subject, causes skin irritation, and some gels have poor long-term stability. A solution to this problem is to use dry electrodes, which do not require conductive gel, but tend to have a higher noise floor. This paper presents a novel methodology for the design and manufacture of such dry electrodes. We manufacture the electrodes using low cost desktop 3D printers and off-the-shelf components for the first time. This allows quick and inexpensive electrode manufacturing and opens the possibility of creating electrodes that are customized for each individual user. Our 3D printed electrodes are compared against standard wet electrodes, and the performance of the proposed electrodes is suitable for BCI applications, despite the presence of additional noise. PMID:27706094

3D Printed Dry EEG Electrodes.

PubMed

Krachunov, Sammy; Casson, Alexander J

2016-10-02

Electroencephalography (EEG) is a procedure that records brain activity in a non-invasive manner. The cost and size of EEG devices has decreased in recent years, facilitating a growing interest in wearable EEG that can be used out-of-the-lab for a wide range of applications, from epilepsy diagnosis, to stroke rehabilitation, to Brain-Computer Interfaces (BCI). A major obstacle for these emerging applications is the wet electrodes, which are used as part of the EEG setup. These electrodes are attached to the human scalp using a conductive gel, which can be uncomfortable to the subject, causes skin irritation, and some gels have poor long-term stability. A solution to this problem is to use dry electrodes, which do not require conductive gel, but tend to have a higher noise floor. This paper presents a novel methodology for the design and manufacture of such dry electrodes. We manufacture the electrodes using low cost desktop 3D printers and off-the-shelf components for the first time. This allows quick and inexpensive electrode manufacturing and opens the possibility of creating electrodes that are customized for each individual user. Our 3D printed electrodes are compared against standard wet electrodes, and the performance of the proposed electrodes is suitable for BCI applications, despite the presence of additional noise.

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.

Does power mobility training impact a child's mastery motivation and spectrum of EEG activity? An exploratory project.

PubMed

Kenyon, Lisa K; Farris, John P; Aldrich, Naomi J; Rhodes, Samhita

2017-08-30

The purposes of this exploratory project were: (1) to evaluate the impact of power mobility training with a child who has multiple, severe impairments and (2) to determine if the child's spectrum of electroencephalography (EEG) activity changed during power mobility training. A single-subject A-B-A-B research design was conducted with a four-week duration for each phase. Two target behaviours were explored: (1) mastery motivation assessed via the dimensions of mastery questionnaire (DMQ) and (2) EEG data collected under various conditions. Power mobility skills were also assessed. The participant was a three-year, two-month-old girl with spastic quadriplegic cerebral palsy, gross motor function classification system level V. Each target behaviour was measured weekly. During intervention phases, power mobility training was provided. Improvements were noted in subscale scores of the DMQ. Short-term and long-term EEG changes were also noted. Improvements were noted in power mobility skills. The participant in this exploratory project demonstrated improvements in power mobility skill and function. EEG data collection procedures and variability in an individual's EEG activity make it difficult to determine if the participant's spectrum of EEG activity actually changed in response to power mobility training. Additional studies are needed to investigate the impact of power mobility training on the spectrum of EEG activity in children who have multiple, severe impairments. Implications for Rehabilitation Power mobility training appeared to be beneficial for a child with multiple, severe impairments though the child may never become an independent, community-based power wheelchair user. Electroencephalography may be a valuable addition to the study of power mobility use in children with multiple, severe impairments. Power mobility training appeared to impact mastery motivation (the internal drive to solve complex problems and master new skills) in a child who has multiple

A Review of Issues Related to Data Acquisition and Analysis in EEG/MEG Studies.

PubMed

Puce, Aina; Hämäläinen, Matti S

2017-05-31

Electroencephalography (EEG) and magnetoencephalography (MEG) are non-invasive electrophysiological methods, which record electric potentials and magnetic fields due to electric currents in synchronously-active neurons. With MEG being more sensitive to neural activity from tangential currents and EEG being able to detect both radial and tangential sources, the two methods are complementary. Over the years, neurophysiological studies have changed considerably: high-density recordings are becoming de rigueur; there is interest in both spontaneous and evoked activity; and sophisticated artifact detection and removal methods are available. Improved head models for source estimation have also increased the precision of the current estimates, particularly for EEG and combined EEG/MEG. Because of their complementarity, more investigators are beginning to perform simultaneous EEG/MEG studies to gain more complete information about neural activity. Given the increase in methodological complexity in EEG/MEG, it is important to gather data that are of high quality and that are as artifact free as possible. Here, we discuss some issues in data acquisition and analysis of EEG and MEG data. Practical considerations for different types of EEG and MEG studies are also discussed.

A Review of Issues Related to Data Acquisition and Analysis in EEG/MEG Studies

PubMed Central

Puce, Aina; Hämäläinen, Matti S.

2017-01-01

Electroencephalography (EEG) and magnetoencephalography (MEG) are non-invasive electrophysiological methods, which record electric potentials and magnetic fields due to electric currents in synchronously-active neurons. With MEG being more sensitive to neural activity from tangential currents and EEG being able to detect both radial and tangential sources, the two methods are complementary. Over the years, neurophysiological studies have changed considerably: high-density recordings are becoming de rigueur; there is interest in both spontaneous and evoked activity; and sophisticated artifact detection and removal methods are available. Improved head models for source estimation have also increased the precision of the current estimates, particularly for EEG and combined EEG/MEG. Because of their complementarity, more investigators are beginning to perform simultaneous EEG/MEG studies to gain more complete information about neural activity. Given the increase in methodological complexity in EEG/MEG, it is important to gather data that are of high quality and that are as artifact free as possible. Here, we discuss some issues in data acquisition and analysis of EEG and MEG data. Practical considerations for different types of EEG and MEG studies are also discussed. PMID:28561761

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.

EEG-Based Computer Aided Diagnosis of Autism Spectrum Disorder Using Wavelet, Entropy, and ANN

PubMed Central

AlSharabi, Khalil; Ibrahim, Sutrisno; Alsuwailem, Abdullah

2017-01-01

Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with core impairments in the social relationships, communication, imagination, or flexibility of thought and restricted repertoire of activity and interest. In this work, a new computer aided diagnosis (CAD) of autism ‎based on electroencephalography (EEG) signal analysis is investigated. The proposed method is based on discrete wavelet transform (DWT), entropy (En), and artificial neural network (ANN). DWT is used to decompose EEG signals into approximation and details coefficients to obtain EEG subbands. The feature vector is constructed by computing Shannon entropy values from each EEG subband. ANN classifies the corresponding EEG signal into normal or autistic based on the extracted features. The experimental results show the effectiveness of the proposed method for assisting autism diagnosis. A receiver operating characteristic (ROC) curve metric is used to quantify the performance of the proposed method. The proposed method obtained promising results tested using real dataset provided by King Abdulaziz Hospital, Jeddah, Saudi Arabia. PMID:28484720

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

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

High Resolution Topography of Age-Related Changes in Non-Rapid Eye Movement Sleep Electroencephalography

PubMed Central

Sprecher, Kate E.; Riedner, Brady A.; Smith, Richard F.; Tononi, Giulio; Davidson, Richard J.; Benca, Ruth M.

2016-01-01

Sleeping brain activity reflects brain anatomy and physiology. The aim of this study was to use high density (256 channel) electroencephalography (EEG) during sleep to characterize topographic changes in sleep EEG power across normal aging, with high spatial resolution. Sleep was evaluated in 92 healthy adults aged 18–65 years old using full polysomnography and high density EEG. After artifact removal, spectral power density was calculated for standard frequency bands for all channels, averaged across the NREM periods of the first 3 sleep cycles. To quantify topographic changes with age, maps were generated of the Pearson’s coefficient of the correlation between power and age at each electrode. Significant correlations were determined by statistical non-parametric mapping. Absolute slow wave power declined significantly with increasing age across the entire scalp, whereas declines in theta and sigma power were significant only in frontal regions. Power in fast spindle frequencies declined significantly with increasing age frontally, whereas absolute power of slow spindle frequencies showed no significant change with age. When EEG power was normalized across the scalp, a left centro-parietal region showed significantly less age-related decline in power than the rest of the scalp. This partial preservation was particularly significant in the slow wave and sigma bands. The effect of age on sleep EEG varies substantially by region and frequency band. This non-uniformity should inform the design of future investigations of aging and sleep. This study provides normative data on the effect of age on sleep EEG topography, and provides a basis from which to explore the mechanisms of normal aging as well as neurodegenerative disorders for which age is a risk factor. PMID:26901503

Can We Predict Functional Outcome in Neonates with Hypoxic Ischemic Encephalopathy by the Combination of Neuroimaging and Electroencephalography?

PubMed Central

Nanavati, Tania; Seemaladinne, Nirupama; Regier, Michael; Yossuck, Panitan; Pergami, Paola

2015-01-01

Background Neonatal hypoxic ischemic encephalopathy (HIE) is a major cause of mortality, morbidity, and long-term neurological deficits. Despite the availability of neuroimaging and neurophysiological testing, tools for accurate early diagnosis and prediction of developmental outcome are still lacking. The goal of this study was to determine if combined use of magnetic resonance imaging (MRI) and electroencephalography (EEG) findings could support outcome prediction. Methods We retrospectively reviewed records of 17 HIE neonates, classified brain MRI and EEG findings based on severity, and assessed clinical outcome up to 48 months. We determined the relation between MRI/EEG findings and clinical outcome. Results We demonstrated a significant relationship between MRI findings and clinical outcome (Fisher’s exact test, p = 0.017). EEG provided no additional information about the outcome beyond that contained in the MRI score. The statistical model for outcome prediction based on random forests suggested that EEG readings at 24 hours and 72 hours could be important variables for outcome prediction, but this needs to be investigated further. Conclusion Caution should be used when discussing prognosis for neonates with mild-to-moderate HIE based on early MR imaging and EEG findings. A robust, quantitative marker of HIE severity that allows for accurate prediction of long-term outcome, particularly for mild-to-moderate cases, is still needed. PMID:25862075

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 %.

The effects of automated artifact removal algorithms on electroencephalography-based Alzheimer's disease diagnosis

PubMed Central

Cassani, Raymundo; Falk, Tiago H.; Fraga, Francisco J.; Kanda, Paulo A. M.; Anghinah, Renato

2014-01-01

Over the last decade, electroencephalography (EEG) has emerged as a reliable tool for the diagnosis of cortical disorders such as Alzheimer's disease (AD). EEG signals, however, are susceptible to several artifacts, such as ocular, muscular, movement, and environmental. To overcome this limitation, existing diagnostic systems commonly depend on experienced clinicians to manually select artifact-free epochs from the collected multi-channel EEG data. Manual selection, however, is a tedious and time-consuming process, rendering the diagnostic system “semi-automated.” Notwithstanding, a number of EEG artifact removal algorithms have been proposed in the literature. The (dis)advantages of using such algorithms in automated AD diagnostic systems, however, have not been documented; this paper aims to fill this gap. Here, we investigate the effects of three state-of-the-art automated artifact removal (AAR) algorithms (both alone and in combination with each other) on AD diagnostic systems based on four different classes of EEG features, namely, spectral, amplitude modulation rate of change, coherence, and phase. The three AAR algorithms tested are statistical artifact rejection (SAR), blind source separation based on second order blind identification and canonical correlation analysis (BSS-SOBI-CCA), and wavelet enhanced independent component analysis (wICA). Experimental results based on 20-channel resting-awake EEG data collected from 59 participants (20 patients with mild AD, 15 with moderate-to-severe AD, and 24 age-matched healthy controls) showed the wICA algorithm alone outperforming other enhancement algorithm combinations across three tasks: diagnosis (control vs. mild vs. moderate), early detection (control vs. mild), and disease progression (mild vs. moderate), thus opening the doors for fully-automated systems that can assist clinicians with early detection of AD, as well as disease severity progression assessment. PMID:24723886

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

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.

Real-time mental arithmetic task recognition from EEG signals.

PubMed

Wang, Qiang; Sourina, Olga

2013-03-01

Electroencephalography (EEG)-based monitoring the state of the user's brain functioning and giving her/him the visual/audio/tactile feedback is called neurofeedback technique, and it could allow the user to train the corresponding brain functions. It could provide an alternative way of treatment for some psychological disorders such as attention deficit hyperactivity disorder (ADHD), where concentration function deficit exists, autism spectrum disorder (ASD), or dyscalculia where the difficulty in learning and comprehending the arithmetic exists. In this paper, a novel method for multifractal analysis of EEG signals named generalized Higuchi fractal dimension spectrum (GHFDS) was proposed and applied in mental arithmetic task recognition from EEG signals. Other features such as power spectrum density (PSD), autoregressive model (AR), and statistical features were analyzed as well. The usage of the proposed fractal dimension spectrum of EEG signal in combination with other features improved the mental arithmetic task recognition accuracy in both multi-channel and one-channel subject-dependent algorithms up to 97.87% and 84.15% correspondingly. Based on the channel ranking, four channels were chosen which gave the accuracy up to 97.11%. Reliable real-time neurofeedback system could be implemented based on the algorithms proposed in this paper.

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.

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.

The efficacy of routine hyperventilation for seizure activation during prolonged video-electroencephalography monitoring.

PubMed

Abubakr, Abuhuziefa; Ifeayni, Iwuchukwu; Wambacq, Ilse

2010-12-01

Hyperventilation (HV) is considered to be one of the activation procedures that provokes epileptic potentials and clinical seizures. However, the true clinical yield of HV is not well established. We retrospectively reviewed the records of all patients admitted to JFK Hospital, Edison, New Jersey, between October 2001 and December 2004 for long-term video-electroencephalography (EEG). A total of 475 patients (193 males; 282 females; age range 5-89 years) were included in the study. All patients underwent routine 3-minute HV as part of the evaluation of their clinical episodes. During the initial assessment, 165 patients did not experience a seizure event, 92 had non-epileptic events, 16 experienced psychogenic non-epileptic seizures (PNES) and six had a clinical event. During HV, of the 43 patients who had primary generalized epilepsy, nine had an abnormal EEG and two experienced seizures; however, out of the 159 patients who had partial seizures, only one patient demonstrated an abnormal EEG. Our study demonstrates that routine HV generally has a very low yield in our Epilepsy-Monitoring Unit. This finding also lends support to the idea that partial seizures are relatively resistant to HV activation. Copyright © 2010 Elsevier Ltd. All rights reserved.

Evaluation of cortical local field potential diffusion in stereotactic electro-encephalography recordings: A glimpse on white matter signal.

PubMed

Mercier, Manuel R; Bickel, Stephan; Megevand, Pierre; Groppe, David M; Schroeder, Charles E; Mehta, Ashesh D; Lado, Fred A

2017-02-15

While there is a strong interest in meso-scale field potential recording using intracranial electroencephalography with penetrating depth electrodes (i.e. stereotactic EEG or S-EEG) in humans, the signal recorded in the white matter remains ignored. White matter is generally considered electrically neutral and often included in the reference montage. Moreover, re-referencing electrophysiological data is a critical preprocessing choice that could drastically impact signal content and consequently the results of any given analysis. In the present stereotactic electroencephalography study, we first illustrate empirically the consequences of commonly used references (subdermal, white matter, global average, local montage) on inter-electrode signal correlation. Since most of these reference montages incorporate white matter signal, we next consider the difference between signals recorded in cortical gray matter and white matter. Our results reveal that electrode contacts located in the white matter record a mixture of activity, with part arising from the volume conduction (zero time delay) of activity from nearby gray matter. Furthermore, our analysis shows that white matter signal may be correlated with distant gray matter signal. While residual passive electrical spread from nearby matter may account for this relationship, our results suggest the possibility that this long distance correlation arises from the white matter fiber tracts themselves (i.e. activity from distant gray matter traveling along axonal fibers with time lag larger than zero); yet definitive conclusions about the origin of the white matter signal would require further experimental substantiation. By characterizing the properties of signals recorded in white matter and in gray matter, this study illustrates the importance of including anatomical prior knowledge when analyzing S-EEG data. Copyright © 2017 Elsevier Inc. All rights reserved.

Mental stress assessment using simultaneous measurement of EEG and fNIRS

PubMed Central

Al-Shargie, Fares; Kiguchi, Masashi; Badruddin, Nasreen; Dass, Sarat C.; Hani, Ahmad Fadzil Mohammad; Tang, Tong Boon

2016-01-01

Previous studies reported mental stress as one of the major contributing factors leading to various diseases such as heart attack, depression and stroke. An accurate stress assessment method may thus be of importance to clinical intervention and disease prevention. We propose a joint independent component analysis (jICA) based approach to fuse simultaneous measurement of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) on the prefrontal cortex (PFC) as a means of stress assessment. For the purpose of this study, stress was induced by using an established mental arithmetic task under time pressure with negative feedback. The induction of mental stress was confirmed by salivary alpha amylase test. Experiment results showed that the proposed fusion of EEG and fNIRS measurements improves the classification accuracy of mental stress by +3.4% compared to EEG alone and +11% compared to fNIRS alone. Similar improvements were also observed in sensitivity and specificity of proposed approach over unimodal EEG/fNIRS. Our study suggests that combination of EEG (frontal alpha rhythm) and fNIRS (concentration change of oxygenated hemoglobin) could be a potential means to assess mental stress objectively. PMID:27867700

Measurement of neurovascular coupling in human motor cortex using simultaneous transcranial doppler (TCD) and electroencephalography (EEG).

PubMed

Alam, Monzurul; Ahmed, Ghazanfar; Ling, Yan To; Zheng, Yong-Ping

2018-05-25

Event-related desynchronization (ERD) is a relative power decrease of electroencephalogram (EEG) signals in a specific frequency band during physical motor execution, while transcranial Doppler (TCD) measures cerebral blood flow velocity. The objective of this study was to investigate the neurovascular coupling in the motor cortex by using an integrated EEG and TCD system, and to find any difference in hemodynamic responses in healthy young male and female adults. Approach: 30 healthy volunteers, aged 20-30 years were recruited for this study. The subjects were asked to perform a motor task for the duration of a provided visual cue. Simultaneous EEG and TCD recording was carried out using a new integrated system to detect the ERD arising from the EEG signals, and to measure the mean blood flow velocity of the left and right middle cerebral arteries from bilateral TCD signals. Main Results: The results showed a significant decrease in EEG power in mu band (7.5-12.5 Hz) during the motor task compared to the resting phase. It showed significant increase in desynchronization on the contralateral side of the motor task compared to the ipsilateral side. Mean blood flow velocity during the task phase was significantly higher in comparison with the resting phase at the contralateral side. The results also showed a significantly higher increase in the percentage of mean blood flow velocity in the contralateral side of motor task compared to the ipsilateral side. However, no significant difference in desynchronization, or change of mean blood flow velocity was found between males and females. Significance: A combined TCD-EEG system successfully detects ERD and blood flow velocity in cerebral arteries, and can be used as a useful tool to study neurovascular coupling in the brain. There is no significant difference in the hemodynamic responses in healthy young males and females. © 2018 Institute of Physics and Engineering in Medicine.

Prevalence and etiology of false normal aEEG recordings in neonatal hypoxic-ischaemic encephalopathy

PubMed Central

2013-01-01

Background Amplitude-integrated electroencephalography (aEEG) is a useful tool to determine the severity of neonatal hypoxic-ischemic encephalopathy (HIE). Our aim was to assess the prevalence and study the origin of false normal aEEG recordings based on 85 aEEG recordings registered before six hours of age. Methods Raw EEG recordings were reevaluated retrospectively with Fourier analysis to identify and describe the frequency patterns of the raw EEG signal, in cases with inconsistent aEEG recordings and clinical symptoms. Power spectral density curves, power (P) and median frequency (MF) were determined using the raw EEG. In 7 patients non-depolarizing muscle relaxant (NDMR) exposure was found. The EEG sections were analyzed and compared before and after NDMR administration. Results The reevaluation found that the aEEG was truly normal in 4 neonates. In 3 neonates, high voltage electrocardiographic (ECG) artifacts were found with flat trace on raw EEG. High frequency component (HFC) was found as a cause of normal appearing aEEG in 10 neonates. HFC disappeared while P and MF decreased significantly upon NDMR administration in each observed case. Conclusion Occurrence of false normal aEEG background pattern is relatively high in neonates with HIE and hypothermia. High frequency EEG artifacts suggestive of shivering were found to be the most common cause of false normal aEEG in hypothermic neonates while high voltage ECG artifacts are less common. PMID:24268061

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.

Acquired auditory agnosia in childhood and normal sleep electroencephalography subsequently diagnosed as Landau-Kleffner syndrome: a report of three cases.

PubMed

van Bogaert, Patrick; King, Mary D; Paquier, Philippe; Wetzburger, Catherine; Labasse, Catherine; Dubru, Jean-Marie; Deonna, Thierry

2013-06-01

  We report three cases of Landau-Kleffner syndrome (LKS) in children (two females, one male) in whom diagnosis was delayed because the sleep electroencephalography (EEG) was initially normal.   Case histories including EEG, positron emission tomography findings, and long-term outcome were reviewed.   Auditory agnosia occurred between the age of 2 years and 3 years 6 months, after a period of normal language development. Initial awake and sleep EEG, recorded weeks to months after the onset of language regression, during a nap period in two cases and during a full night of sleep in the third case, was normal. Repeat EEG between 2 months and 2 years later showed epileptiform discharges during wakefulness and strongly activated by sleep, with a pattern of continuous spike-waves during slow-wave sleep in two patients. Patients were diagnosed with LKS and treated with various antiepileptic regimens, including corticosteroids. One patient in whom EEG became normal on hydrocortisone is making significant recovery. The other two patients did not exhibit a sustained response to treatment and remained severely impaired.   Sleep EEG may be normal in the early phase of acquired auditory agnosia. EEG should be repeated frequently in individuals in whom a firm clinical diagnosis is made to facilitate early treatment. © The Authors. Developmental Medicine & Child Neurology © 2012 Mac Keith Press.

A novel method for device-related electroencephalography artifact suppression to explore cochlear implant-related cortical changes in single-sided deafness.

PubMed

Kim, Kyungsoo; Punte, Andrea Kleine; Mertens, Griet; Van de Heyning, Paul; Park, Kyung-Joon; Choi, Hongsoo; Choi, Ji-Woong; Song, Jae-Jin

2015-11-30

Quantitative electroencephalography (qEEG) is effective when used to analyze ongoing cortical oscillations in cochlear implant (CI) users. However, localization of cortical activity in such users via qEEG is confounded by the presence of artifacts produced by the device itself. Typically, independent component analysis (ICA) is used to remove CI artifacts in auditory evoked EEG signals collected upon brief stimulation and it is effective for auditory evoked potentials (AEPs). However, AEPs do not reflect the daily environments of patients, and thus, continuous EEG data that are closer to such environments are desirable. In this case, device-related artifacts in EEG data are difficult to remove selectively via ICA due to over-completion of EEG data removal in the absence of preprocessing. EEGs were recorded for a long time under conditions of continuous auditory stimulation. To obviate the over-completion problem, we limited the frequency of CI artifacts to a significant characteristic peak and apply ICA artifact removal. Topographic brain mapping results analyzed via band-limited (BL)-ICA exhibited a better energy distribution, matched to the CI location, than data obtained using conventional ICA. Also, source localization data verified that BL-ICA effectively removed CI artifacts. The proposed method selectively removes CI artifacts from continuous EEG recordings, while ICA removal method shows residual peak and removes important brain activity signals. CI artifacts in EEG data obtained during continuous passive listening can be effectively removed with the aid of BL-ICA, opening up new EEG research possibilities in subjects with CIs. Copyright © 2015 Elsevier B.V. All rights reserved.

Classifying Drivers' Cognitive Load Using EEG Signals.

PubMed

Barua, Shaibal; Ahmed, Mobyen Uddin; Begum, Shahina

2017-01-01

A growing traffic safety issue is the effect of cognitive loading activities on traffic safety and driving performance. To monitor drivers' mental state, understanding cognitive load is important since while driving, performing cognitively loading secondary tasks, for example talking on the phone, can affect the performance in the primary task, i.e. driving. Electroencephalography (EEG) is one of the reliable measures of cognitive load that can detect the changes in instantaneous load and effect of cognitively loading secondary task. In this driving simulator study, 1-back task is carried out while the driver performs three different simulated driving scenarios. This paper presents an EEG based approach to classify a drivers' level of cognitive load using Case-Based Reasoning (CBR). The results show that for each individual scenario as well as using data combined from the different scenarios, CBR based system achieved approximately over 70% of classification accuracy.

Classification of driver fatigue in an electroencephalography-based countermeasure system with source separation module.

PubMed

Rifai Chai; Naik, Ganesh R; Tran, Yvonne; Sai Ho Ling; Craig, Ashley; Nguyen, Hung T

2015-08-01

An electroencephalography (EEG)-based counter measure device could be used for fatigue detection during driving. This paper explores the classification of fatigue and alert states using power spectral density (PSD) as a feature extractor and fuzzy swarm based-artificial neural network (ANN) as a classifier. An independent component analysis of entropy rate bound minimization (ICA-ERBM) is investigated as a novel source separation technique for fatigue classification using EEG analysis. A comparison of the classification accuracy of source separator versus no source separator is presented. Classification performance based on 43 participants without the inclusion of the source separator resulted in an overall sensitivity of 71.67%, a specificity of 75.63% and an accuracy of 73.65%. However, these results were improved after the inclusion of a source separator module, resulting in an overall sensitivity of 78.16%, a specificity of 79.60% and an accuracy of 78.88% (p <; 0.05).

EEG in the classroom: Synchronised neural recordings during video presentation

PubMed Central

Poulsen, Andreas Trier; Kamronn, Simon; Dmochowski, Jacek; Parra, Lucas C.; Hansen, Lars Kai

2017-01-01

We performed simultaneous recordings of electroencephalography (EEG) from multiple students in a classroom, and measured the inter-subject correlation (ISC) of activity evoked by a common video stimulus. The neural reliability, as quantified by ISC, has been linked to engagement and attentional modulation in earlier studies that used high-grade equipment in laboratory settings. Here we reproduce many of the results from these studies using portable low-cost equipment, focusing on the robustness of using ISC for subjects experiencing naturalistic stimuli. The present data shows that stimulus-evoked neural responses, known to be modulated by attention, can be tracked for groups of students with synchronized EEG acquisition. This is a step towards real-time inference of engagement in the classroom. PMID:28266588

EEG in the classroom: Synchronised neural recordings during video presentation

NASA Astrophysics Data System (ADS)

Poulsen, Andreas Trier; Kamronn, Simon; Dmochowski, Jacek; Parra, Lucas C.; Hansen, Lars Kai

2017-03-01

We performed simultaneous recordings of electroencephalography (EEG) from multiple students in a classroom, and measured the inter-subject correlation (ISC) of activity evoked by a common video stimulus. The neural reliability, as quantified by ISC, has been linked to engagement and attentional modulation in earlier studies that used high-grade equipment in laboratory settings. Here we reproduce many of the results from these studies using portable low-cost equipment, focusing on the robustness of using ISC for subjects experiencing naturalistic stimuli. The present data shows that stimulus-evoked neural responses, known to be modulated by attention, can be tracked for groups of students with synchronized EEG acquisition. This is a step towards real-time inference of engagement in the classroom.

Epileptic seizure classification of EEG time-series using rational discrete short-time fourier transform.

PubMed

Samiee, Kaveh; Kovács, Petér; Gabbouj, Moncef

2015-02-01

A system for epileptic seizure detection in electroencephalography (EEG) is described in this paper. One of the challenges is to distinguish rhythmic discharges from nonstationary patterns occurring during seizures. The proposed approach is based on an adaptive and localized time-frequency representation of EEG signals by means of rational functions. The corresponding rational discrete short-time Fourier transform (DSTFT) is a novel feature extraction technique for epileptic EEG data. A multilayer perceptron classifier is fed by the coefficients of the rational DSTFT in order to separate seizure epochs from seizure-free epochs. The effectiveness of the proposed method is compared with several state-of-art feature extraction algorithms used in offline epileptic seizure detection. The results of the comparative evaluations show that the proposed method outperforms competing techniques in terms of classification accuracy. In addition, it provides a compact representation of EEG time-series.

A Review of EEG-Based Brain-Computer Interfaces as Access Pathways for Individuals with Severe Disabilities

ERIC Educational Resources Information Center

Moghimi, Saba; Kushki, Azadeh; Guerguerian, Anne Marie; Chau, Tom

2013-01-01

Electroencephalography (EEG) is a non-invasive method for measuring brain activity and is a strong candidate for brain-computer interface (BCI) development. While BCIs can be used as a means of communication for individuals with severe disabilities, the majority of existing studies have reported BCI evaluations by able-bodied individuals.…

Intracranial electroencephalography power and phase synchronization changes during monaural and binaural beat stimulation.

PubMed

Becher, Ann-Katrin; Höhne, Marlene; Axmacher, Nikolai; Chaieb, Leila; Elger, Christian E; Fell, Juergen

2015-01-01

Auditory stimulation with monaural or binaural auditory beats (i.e. sine waves with nearby frequencies presented either to both ears or to each ear separately) represents a non-invasive approach to influence electrical brain activity. It is still unclear exactly which brain sites are affected by beat stimulation. In particular, an impact of beat stimulation on mediotemporal brain areas could possibly provide new options for memory enhancement or seizure control. Therefore, we examined how electroencephalography (EEG) power and phase synchronization are modulated by auditory stimulation with beat frequencies corresponding to dominant EEG rhythms based on intracranial recordings in presurgical epilepsy patients. Monaural and binaural beat stimuli with beat frequencies of 5, 10, 40 and 80 Hz and non-superposed control signals were administered with low amplitudes (60 dB SPL) and for short durations (5 s). EEG power was intracranially recorded from mediotemporal, temporo-basal and temporo-lateral and surface sites. Evoked and total EEG power and phase synchronization during beat vs. control stimulation were compared by the use of Bonferroni-corrected non-parametric label-permutation tests. We found that power and phase synchronization were significantly modulated by beat stimulation not only at temporo-basal, temporo-lateral and surface sites, but also at mediotemporal sites. Generally, more significant decreases than increases were observed. The most prominent power increases were seen after stimulation with monaural 40-Hz beats. The most pronounced power and synchronization decreases resulted from stimulation with monaural 5-Hz and binaural 80-Hz beats. Our results suggest that beat stimulation offers a non-invasive approach for the modulation of intracranial EEG characteristics. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Recent Advances in Resting-State Electroencephalography Biomarkers for Autism Spectrum Disorder-A Review of Methodological and Clinical Challenges.

PubMed

Heunis, Tosca-Marie; Aldrich, Chris; de Vries, Petrus J

2016-08-01

Electroencephalography (EEG) has been used for almost a century to identify seizure-related disorders in humans, typically through expert interpretation of multichannel recordings. Attempts have been made to quantify EEG through frequency analyses and graphic representations. These "traditional" quantitative EEG analysis methods were limited in their ability to analyze complex and multivariate data and have not been generally accepted in clinical settings. There has been growing interest in identification of novel EEG biomarkers to detect early risk of autism spectrum disorder, to identify clinically meaningful subgroups, and to monitor targeted intervention strategies. Most studies to date have, however, used quantitative EEG approaches, and little is known about the emerging multivariate analytical methods or the robustness of candidate biomarkers in the context of the variability of autism spectrum disorder. Here, we present a targeted review of methodological and clinical challenges in the search for novel resting-state EEG biomarkers for autism spectrum disorder. Three primary novel methodologies are discussed: (1) modified multiscale entropy, (2) coherence analysis, and (3) recurrence quantification analysis. Results suggest that these methods may be able to classify resting-state EEG as "autism spectrum disorder" or "typically developing", but many signal processing questions remain unanswered. We suggest that the move to novel EEG analysis methods is akin to the progress in neuroimaging from visual inspection, through region-of-interest analysis, to whole-brain computational analysis. Novel resting-state EEG biomarkers will have to evaluate a range of potential demographic, clinical, and technical confounders including age, gender, intellectual ability, comorbidity, and medication, before these approaches can be translated into the clinical setting. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

EEG potentials associated with artificial grammar learning in the primate brain.

PubMed

Attaheri, Adam; Kikuchi, Yukiko; Milne, Alice E; Wilson, Benjamin; Alter, Kai; Petkov, Christopher I

2015-09-01

Electroencephalography (EEG) has identified human brain potentials elicited by Artificial Grammar (AG) learning paradigms, which present participants with rule-based sequences of stimuli. Nonhuman animals are sensitive to certain AGs; therefore, evaluating which EEG Event Related Potentials (ERPs) are associated with AG learning in nonhuman animals could identify evolutionarily conserved processes. We recorded EEG potentials during an auditory AG learning experiment in two Rhesus macaques. The animals were first exposed to sequences of nonsense words generated by the AG. Then surface-based ERPs were recorded in response to sequences that were 'consistent' with the AG and 'violation' sequences containing illegal transitions. The AG violations strongly modulated an early component, potentially homologous to the Mismatch Negativity (mMMN), a P200 and a late frontal positivity (P500). The macaque P500 is similar in polarity and time of occurrence to a late EEG positivity reported in human AG learning studies but might differ in functional role. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Seizure semiology and electroencephalography in young children with lesional temporal lobe epilepsy.

PubMed

Lv, Rui-Juan; Sun, Zhen-Rong; Cui, Tao; Shao, Xiao-Qiu

2014-02-01

This study aimed to discuss the clinical features of seizure semiology and electroencephalography (EEG) in young children with lesional temporal lobe epilepsy (TLE). Children with lesional TLE received presurgical evaluation for intractable epilepsy. They were followed up for more than one year after temporal lobectomy. We reviewed the medical history and video-EEG monitoring of children with TLE to analyze the semiology of seizures and EEG findings and compared the semiology of seizures and EEG findings of childhood TLE and adult TLE. A total of 84 seizures were analyzed in 11 children (aged 23-108 months). The age of seizure onset was from 1 month to 26 months (a mean of 17.6 months). All of the patients exhibited prominent motor manifestations including epileptic spasm, tonic seizure, and unilateral clonic seizure. Seven children manifested behavioral arrest similar to an automotor seizure in adult TLE but with a shorter duration and higher frequency. The automatisms were typically orofacial, whereas manual automatisms were rarely observed. The EEG recordings revealed that diffuse discharge patterns were more common in younger children, whereas focal or unilateral patterns were more typical in older children. All of the patients were seizure-free after temporal lobectomy with more than one-year follow-up. All of the children had a mental development delay or regression; however, there was improvement after surgery, especially in those with surgery performed early. In contrast to TLE in adults, young children with lesional TLE probably represent a distinct nosological and probably less homogeneous syndrome. Although they had generalized clinical and electrographic features, resective epilepsy surgery should be considered as early as possible to obtain seizure control and improvement in mental development. Copyright © 2013 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

The Removal of EOG Artifacts From EEG Signals Using Independent Component Analysis and Multivariate Empirical Mode Decomposition.

PubMed

Wang, Gang; Teng, Chaolin; Li, Kuo; Zhang, Zhonglin; Yan, Xiangguo

2016-09-01

The recorded electroencephalography (EEG) signals are usually contaminated by electrooculography (EOG) artifacts. In this paper, by using independent component analysis (ICA) and multivariate empirical mode decomposition (MEMD), the ICA-based MEMD method was proposed to remove EOG artifacts (EOAs) from multichannel EEG signals. First, the EEG signals were decomposed by the MEMD into multiple multivariate intrinsic mode functions (MIMFs). The EOG-related components were then extracted by reconstructing the MIMFs corresponding to EOAs. After performing the ICA of EOG-related signals, the EOG-linked independent components were distinguished and rejected. Finally, the clean EEG signals were reconstructed by implementing the inverse transform of ICA and MEMD. The results of simulated and real data suggested that the proposed method could successfully eliminate EOAs from EEG signals and preserve useful EEG information with little loss. By comparing with other existing techniques, the proposed method achieved much improvement in terms of the increase of signal-to-noise and the decrease of mean square error after removing EOAs.

Effect of mental fatigue on the central nervous system: an electroencephalography study

PubMed Central

2012-01-01

Background Fatigue can be classified as mental and physical depending on its cause, and each type of fatigue has a multi-factorial nature. We examined the effect of mental fatigue on the central nervous system using electroencephalography (EEG) in eighteen healthy male volunteers. Methods After enrollment, subjects were randomly assigned to two groups in a single-blinded, crossover fashion to perform two types of mental fatigue-inducing experiments. Each experiment consisted of four 30-min fatigue-inducing 0- or 2-back test sessions and two evaluation sessions performed just before and after the fatigue-inducing sessions. During the evaluation session, the participants were assessed using EEG. Eleven electrodes were attached to the head skin, from positions F3, Fz, F4, C3, Cz, C4, P3, Pz, P4, O1, and O2. Results In the 2-back test, the beta power density on the Pz electrode and the alpha power densities on the P3 and O2 electrodes were decreased, and the theta power density on the Cz electrode was increased after the fatigue-inducing mental task sessions. In the 0-back test, no electrodes were altered after the fatigue-inducing sessions. Conclusions Different types of mental fatigue produced different kinds of alterations of the spontaneous EEG variables. Our findings provide new perspectives on the neural mechanisms underlying mental fatigue. PMID:22954020

Simultaneous ocular and muscle artifact removal from EEG data by exploiting diverse statistics.

PubMed

Chen, Xun; Liu, Aiping; Chen, Qiang; Liu, Yu; Zou, Liang; McKeown, Martin J

2017-09-01

Electroencephalography (EEG) recordings are frequently contaminated by both ocular and muscle artifacts. These are normally dealt with separately, by employing blind source separation (BSS) techniques relying on either second-order or higher-order statistics (SOS & HOS respectively). When HOS-based methods are used, it is usually in the setting of assuming artifacts are statistically independent to the EEG. When SOS-based methods are used, it is assumed that artifacts have autocorrelation characteristics distinct from the EEG. In reality, ocular and muscle artifacts do not completely follow the assumptions of strict temporal independence to the EEG nor completely unique autocorrelation characteristics, suggesting that exploiting HOS or SOS alone may be insufficient to remove these artifacts. Here we employ a novel BSS technique, independent vector analysis (IVA), to jointly employ HOS and SOS simultaneously to remove ocular and muscle artifacts. Numerical simulations and application to real EEG recordings were used to explore the utility of the IVA approach. IVA was superior in isolating both ocular and muscle artifacts, especially for raw EEG data with low signal-to-noise ratio, and also integrated usually separate SOS and HOS steps into a single unified step. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Fast, Open EEG Classification Framework Based on Feature Compression and Channel Ranking

PubMed Central

Han, Jiuqi; Zhao, Yuwei; Sun, Hongji; Chen, Jiayun; Ke, Ang; Xu, Gesen; Zhang, Hualiang; Zhou, Jin; Wang, Changyong

2018-01-01

Superior feature extraction, channel selection and classification methods are essential for designing electroencephalography (EEG) classification frameworks. However, the performance of most frameworks is limited by their improper channel selection methods and too specifical design, leading to high computational complexity, non-convergent procedure and narrow expansibility. In this paper, to remedy these drawbacks, we propose a fast, open EEG classification framework centralized by EEG feature compression, low-dimensional representation, and convergent iterative channel ranking. First, to reduce the complexity, we use data clustering to compress the EEG features channel-wise, packing the high-dimensional EEG signal, and endowing them with numerical signatures. Second, to provide easy access to alternative superior methods, we structurally represent each EEG trial in a feature vector with its corresponding numerical signature. Thus, the recorded signals of many trials shrink to a low-dimensional structural matrix compatible with most pattern recognition methods. Third, a series of effective iterative feature selection approaches with theoretical convergence is introduced to rank the EEG channels and remove redundant ones, further accelerating the EEG classification process and ensuring its stability. Finally, a classical linear discriminant analysis (LDA) model is employed to classify a single EEG trial with selected channels. Experimental results on two real world brain-computer interface (BCI) competition datasets demonstrate the promising performance of the proposed framework over state-of-the-art methods. PMID:29713262

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.

Simultaneous resting-state functional MRI and electroencephalography recordings of functional connectivity in patients with schizophrenia.

PubMed

Kirino, Eiji; Tanaka, Shoji; Fukuta, Mayuko; Inami, Rie; Arai, Heii; Inoue, Reiichi; Aoki, Shigeki

2017-04-01

It remains unclear how functional connectivity (FC) may be related to specific cognitive domains in neuropsychiatric disorders. Here we used simultaneous resting-state functional magnetic resonance imaging (rsfMRI) and electroencephalography (EEG) recording in patients with schizophrenia, to evaluate FC within and outside the default mode network (DMN). Our study population included 14 patients with schizophrenia and 15 healthy control participants. From all participants, we acquired rsfMRI data, and simultaneously recorded EEG data using an MR-compatible amplifier. We analyzed the rsfMRI-EEG data, and used the CONN toolbox to calculate the FC between regions of interest. We also performed between-group comparisons of standardized low-resolution electromagnetic tomography-based intracortical lagged coherence for each EEG frequency band. FC within the DMN, as measured by rsfMRI and EEG, did not significantly differ between groups. Analysis of rsfMRI data showed that FC between the right posterior inferior temporal gyrus and medial prefrontal cortex was stronger among patients with schizophrenia compared to control participants. Analysis of FC within the DMN using rsfMRI and EEG data revealed no significant differences between patients with schizophrenia and control participants. However, rsfMRI data revealed over-modulated FC between the medial prefrontal cortex and right posterior inferior temporal gyrus in patients with schizophrenia compared to control participants, suggesting that the patients had altered FC, with higher correlations across nodes within and outside of the DMN. Further studies using simultaneous rsfMRI and EEG are required to determine whether altered FC within the DMN is associated with schizophrenia. © 2016 The Authors. Psychiatry and Clinical Neurosciences published by John Wiley & Sons Australia, Ltd on behalf of Japanese Society of Psychiatry and Neurology.

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.

FFT transformed quantitative EEG analysis of short term memory load.

PubMed

Singh, Yogesh; Singh, Jayvardhan; Sharma, Ratna; Talwar, Anjana

2015-07-01

The EEG is considered as building block of functional signaling in the brain. The role of EEG oscillations in human information processing has been intensively investigated. To study the quantitative EEG correlates of short term memory load as assessed through Sternberg memory test. The study was conducted on 34 healthy male student volunteers. The intervention consisted of Sternberg memory test, which runs on a version of the Sternberg memory scanning paradigm software on a computer. Electroencephalography (EEG) was recorded from 19 scalp locations according to 10-20 international system of electrode placement. EEG signals were analyzed offline. To overcome the problems of fixed band system, individual alpha frequency (IAF) based frequency band selection method was adopted. The outcome measures were FFT transformed absolute powers in the six bands at 19 electrode positions. Sternberg memory test served as model of short term memory load. Correlation analysis of EEG during memory task was reflected as decreased absolute power in Upper alpha band in nearly all the electrode positions; increased power in Theta band at Fronto-Temporal region and Lower 1 alpha band at Fronto-Central region. Lower 2 alpha, Beta and Gamma band power remained unchanged. Short term memory load has distinct electroencephalographic correlates resembling the mentally stressed state. This is evident from decreased power in Upper alpha band (corresponding to Alpha band of traditional EEG system) which is representative band of relaxed mental state. Fronto-temporal Theta power changes may reflect the encoding and execution of memory task.

Dancing with a seizure, a case report.

PubMed

Kim, Keun Tae; Chu, Kon; Lee, Sang Kun

2017-01-25

Dancing is a very rare seizure semiology, and has only few case reports so far. Moreover, no case regarded as dancing with both description and video was presented. A 42-year-old woman with medical intractable epilepsy showed a typical semiology of right temporal lobe epilepsy: right hand automatism and ictal speech. The following semiology, appeared during ictal and post-ictal stage, was complex, rhythmical and sequential movement. It was enough to be called dancing. We hereby report the most plausible dancing in the ictal and post-ictal state, documented by simultaneous video and electroencephalography.

Spatio-temporal reconstruction of brain dynamics from EEG with a Markov prior.

PubMed

Hansen, Sofie Therese; Hansen, Lars Kai

2017-03-01

Electroencephalography (EEG) can capture brain dynamics in high temporal resolution. By projecting the scalp EEG signal back to its origin in the brain also high spatial resolution can be achieved. Source localized EEG therefore has potential to be a very powerful tool for understanding the functional dynamics of the brain. Solving the inverse problem of EEG is however highly ill-posed as there are many more potential locations of the EEG generators than EEG measurement points. Several well-known properties of brain dynamics can be exploited to alleviate this problem. More short ranging connections exist in the brain than long ranging, arguing for spatially focal sources. Additionally, recent work (Delorme et al., 2012) argues that EEG can be decomposed into components having sparse source distributions. On the temporal side both short and long term stationarity of brain activation are seen. We summarize these insights in an inverse solver, the so-called "Variational Garrote" (Kappen and Gómez, 2013). Using a Markov prior we can incorporate flexible degrees of temporal stationarity. Through spatial basis functions spatially smooth distributions are obtained. Sparsity of these are inherent to the Variational Garrote solver. We name our method the MarkoVG and demonstrate its ability to adapt to the temporal smoothness and spatial sparsity in simulated EEG data. Finally a benchmark EEG dataset is used to demonstrate MarkoVG's ability to recover non-stationary brain dynamics. Copyright © 2016 Elsevier Inc. All rights reserved.

Intra- and Interindividual Differences in Lateralized Cognitive Performance and Asymmetrical EEG Activity in the Frontal Cortex

ERIC Educational Resources Information Center

Papousek, Ilona; Murhammer, Daniela; Schulter, Gunter

2011-01-01

The study shows that changes in relative verbal vs. figural working memory and fluency performance from one session to a second session two to 3 weeks apart covary with spontaneously occurring changes of cortical asymmetry in the lateral frontal and central cortex, measured by electroencephalography (EEG) in resting conditions before the execution…

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-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.

Automated network analysis to measure brain effective connectivity estimated from EEG data of patients with alcoholism.

PubMed

Bae, Youngoh; Yoo, Byeong Wook; Lee, Jung Chan; Kim, Hee Chan

2017-05-01

Detection and diagnosis based on extracting features and classification using electroencephalography (EEG) signals are being studied vigorously. A network analysis of time series EEG signal data is one of many techniques that could help study brain functions. In this study, we analyze EEG to diagnose alcoholism. We propose a novel methodology to estimate the differences in the status of the brain based on EEG data of normal subjects and data from alcoholics by computing many parameters stemming from effective network using Granger causality. Among many parameters, only ten parameters were chosen as final candidates. By the combination of ten graph-based parameters, our results demonstrate predictable differences between alcoholics and normal subjects. A support vector machine classifier with best performance had 90% accuracy with sensitivity of 95.3%, and specificity of 82.4% for differentiating between the two groups.

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

PubMed Central

Bulea, Thomas C.; Kilicarslan, Atilla; Ozdemir, Recep; Paloski, William H.; Contreras-Vidal, Jose L.

2013-01-01

Recent studies support the involvement of supraspinal networks in control of bipedal human walking. Part of this evidence encompasses studies, including our previous work, demonstrating that gait kinematics and limb coordination during treadmill walking can be inferred from the scalp electroencephalogram (EEG) with reasonably high decoding accuracies. These results provide impetus for development of non-invasive brain-machine-interface (BMI) systems for use in restoration and/or augmentation of gait- a primary goal of rehabilitation research. To date, studies examining EEG decoding of activity during gait have been limited to treadmill walking in a controlled environment. However, to be practically viable a BMI system must be applicable for use in everyday locomotor tasks such as over ground walking and turning. Here, we present a novel protocol for non-invasive collection of brain activity (EEG), muscle activity (electromyography (EMG)), and whole-body kinematic data (head, torso, and limb trajectories) during both treadmill and over ground walking tasks. By collecting these data in the uncontrolled environment insight can be gained regarding the feasibility of decoding unconstrained gait and surface EMG from scalp EEG. PMID:23912203

Simultaneous scalp electroencephalography (EEG), electromyography (EMG), and whole-body segmental inertial recording for multi-modal neural decoding.

PubMed

Bulea, Thomas C; Kilicarslan, Atilla; Ozdemir, Recep; Paloski, William H; Contreras-Vidal, Jose L

2013-07-26

Recent studies support the involvement of supraspinal networks in control of bipedal human walking. Part of this evidence encompasses studies, including our previous work, demonstrating that gait kinematics and limb coordination during treadmill walking can be inferred from the scalp electroencephalogram (EEG) with reasonably high decoding accuracies. These results provide impetus for development of non-invasive brain-machine-interface (BMI) systems for use in restoration and/or augmentation of gait- a primary goal of rehabilitation research. To date, studies examining EEG decoding of activity during gait have been limited to treadmill walking in a controlled environment. However, to be practically viable a BMI system must be applicable for use in everyday locomotor tasks such as over ground walking and turning. Here, we present a novel protocol for non-invasive collection of brain activity (EEG), muscle activity (electromyography (EMG)), and whole-body kinematic data (head, torso, and limb trajectories) during both treadmill and over ground walking tasks. By collecting these data in the uncontrolled environment insight can be gained regarding the feasibility of decoding unconstrained gait and surface EMG from scalp EEG.

Brain Oscillations in Sport: Toward EEG Biomarkers of Performance.

PubMed

Cheron, Guy; Petit, Géraldine; Cheron, Julian; Leroy, Axelle; Cebolla, Anita; Cevallos, Carlos; Petieau, Mathieu; Hoellinger, Thomas; Zarka, David; Clarinval, Anne-Marie; Dan, Bernard

2016-01-01

Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The non-invasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP) in sport. In this context, the hypotheses of unified brain rhythms and continuity between wake and sleep states should provide a functional template for EEG biomarkers in sport. The oscillations in the thalamo-cortical and hippocampal circuitry including the physiology of the place cells and the grid cells provide a frame of reference for the analysis of delta, theta, beta, alpha (incl.mu), and gamma oscillations recorded in the space field of human performance. Based on recent neuronal models facilitating the distinction between the different dynamic regimes (selective gating and binding) in these different oscillations we suggest an integrated approach articulating together the classical biomechanical factors (3D movements and EMG) and the high-density EEG and ERP signals to allow finer mathematical analysis to optimize sport performance, such as microstates, coherency/directionality analysis and neural generators.

Brain Oscillations in Sport: Toward EEG Biomarkers of Performance

PubMed Central

Cheron, Guy; Petit, Géraldine; Cheron, Julian; Leroy, Axelle; Cebolla, Anita; Cevallos, Carlos; Petieau, Mathieu; Hoellinger, Thomas; Zarka, David; Clarinval, Anne-Marie; Dan, Bernard

2016-01-01

Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The non-invasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP) in sport. In this context, the hypotheses of unified brain rhythms and continuity between wake and sleep states should provide a functional template for EEG biomarkers in sport. The oscillations in the thalamo-cortical and hippocampal circuitry including the physiology of the place cells and the grid cells provide a frame of reference for the analysis of delta, theta, beta, alpha (incl.mu), and gamma oscillations recorded in the space field of human performance. Based on recent neuronal models facilitating the distinction between the different dynamic regimes (selective gating and binding) in these different oscillations we suggest an integrated approach articulating together the classical biomechanical factors (3D movements and EMG) and the high-density EEG and ERP signals to allow finer mathematical analysis to optimize sport performance, such as microstates, coherency/directionality analysis and neural generators. PMID:26955362

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

Application of polymer sensitive MRI sequence to localization of EEG electrodes.

PubMed

Butler, Russell; Gilbert, Guillaume; Descoteaux, Maxime; Bernier, Pierre-Michel; Whittingstall, Kevin

2017-02-15

The growing popularity of simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) opens up the possibility of imaging EEG electrodes while the subject is in the scanner. Such information could be useful for improving the fusion of EEG-fMRI datasets. Here, we report for the first time how an ultra-short echo time (UTE) MR sequence can image the materials of an MR-compatible EEG cap, finding that electrodes and some parts of the wiring are visible in a high resolution UTE. Using these images, we developed a segmentation procedure to obtain electrode coordinates based on voxel intensity from the raw UTE, using hand labeled coordinates as the starting point. We were able to visualize and segment 95% of EEG electrodes using a short (3.5min) UTE sequence. We provide scripts and template images so this approach can now be easily implemented to obtain precise, subject-specific EEG electrode positions while adding minimal acquisition time to the simultaneous EEG-fMRI protocol. T1 gel artifacts are not robust enough to localize all electrodes across subjects, the polymers composing Brainvision cap electrodes are not visible on a T1, and adding T1 visible materials to the EEG cap is not always possible. We therefore consider our method superior to existing methods for obtaining electrode positions in the scanner, as it is hardware free and should work on a wide range of materials (caps). EEG electrode positions are obtained with high precision and no additional hardware. Copyright © 2016 Elsevier B.V. All rights reserved.

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

Assessment of Cross-Chemical Predictibility for Changes in Serum Clinical Bioindicators and EEG Produced by Pesticides with Different Modes of Action

EPA Science Inventory

Electroencephalography (EEG) is often used as an apical measure of multiple types of central nervous system (CNS) changes, while biomarkers in blood may serve as predictors for adverse outcomes. Correlation between these two measures would suggest that certain changes in biomarke...

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.

Multichannel wearable system dedicated for simultaneous electroencephalography/near-infrared spectroscopy real-time data acquisitions

NASA Astrophysics Data System (ADS)

Lareau, Etienne; Lesage, Frederic; Pouliot, Philippe; Nguyen, Dang; Le Lan, Jerome; Sawan, Mohamad

2011-09-01

Functional neuroimaging is becoming a valuable tool in cognitive research and clinical applications. The clinical context brings specific constraints that include the requirement of a high channel count to cover the whole head, high sensitivity for single event detection, and portability for long-term bedside monitoring. For epilepsy and stroke monitoring, the combination of electroencephalography (EEG) and functional near-infrared spectroscopy (NIRS) is expected to provide useful clinical information, and efforts have been deployed to create prototypes able to simultaneously acquire both measurement modalities. However, to the best of our knowledge, existing systems lack portability, NIRS sensitivity, or have low channel count. We present a battery-powered, portable system with potentially up to 32 EEG channels, 32 NIRS light sources, and 32 detectors. Avalanche photodiodes allow for high NIRS sensitivity and the autonomy of the system is over 24 h. A reduced channel count prototype with 8 EEG channels, 8 sources, and 8 detectors was tested on phantoms. Further validation was done on five healthy adults using a visual stimulation protocol to detect local hemodynamic changes and visually evoked potentials. Results show good concordance with literature regarding functional activations and suggest sufficient performance for clinical use, provided some minor adjustments were made.

Modeling EEG Waveforms with Semi-Supervised Deep Belief Nets: Fast Classification and Anomaly Measurement

PubMed Central

Wulsin, D. F.; Gupta, J. R.; Mani, R.; Blanco, J. A.; Litt, B.

2011-01-01

Clinical electroencephalography (EEG) records vast amounts of human complex data yet is still reviewed primarily by human readers. Deep Belief Nets (DBNs) are a relatively new type of multi-layer neural network commonly tested on two-dimensional image data, but are rarely applied to times-series data such as EEG. We apply DBNs in a semi-supervised paradigm to model EEG waveforms for classification and anomaly detection. DBN performance was comparable to standard classifiers on our EEG dataset, and classification time was found to be 1.7 to 103.7 times faster than the other high-performing classifiers. We demonstrate how the unsupervised step of DBN learning produces an autoencoder that can naturally be used in anomaly measurement. We compare the use of raw, unprocessed data—a rarity in automated physiological waveform analysis—to hand-chosen features and find that raw data produces comparable classification and better anomaly measurement performance. These results indicate that DBNs and raw data inputs may be more effective for online automated EEG waveform recognition than other common techniques. PMID:21525569

The Use of Electroencephalography in Language Production Research: A Review

PubMed Central

Ganushchak, Lesya Y.; Christoffels, Ingrid K.; Schiller, Niels O.

2011-01-01

Speech production long avoided electrophysiological experiments due to the suspicion that potential artifacts caused by muscle activity of overt speech may lead to a bad signal-to-noise ratio in the measurements. Therefore, researchers have sought to assess speech production by using indirect speech production tasks, such as tacit or implicit naming, delayed naming, or meta-linguistic tasks, such as phoneme-monitoring. Covert speech may, however, involve different processes than overt speech production. Recently, overt speech has been investigated using electroencephalography (EEG). As the number of papers published is rising steadily, this clearly indicates the increasing interest and demand for overt speech research within the field of cognitive neuroscience of language. Our main goal here is to review all currently available results of overt speech production involving EEG measurements, such as picture naming, Stroop naming, and reading aloud. We conclude that overt speech production can be successfully studied using electrophysiological measures, for instance, event-related brain potentials (ERPs). We will discuss possible relevant components in the ERP waveform of speech production and aim to address the issue of how to interpret the results of ERP research using overt speech, and whether the ERP components in language production are comparable to results from other fields. PMID:21909333

Single-channel EEG-based mental fatigue detection based on deep belief network.

PubMed

Pinyi Li; Wenhui Jiang; Fei Su

2016-08-01

Mental fatigue has a pernicious influence on road and work place safety as well as a negative symptom of many acute and chronic illnesses, since the ability of concentrating, responding and judging quickly decreases during the fatigue or drowsiness stage. Electroencephalography (EEG) has been proven to be a robust physiological indicator of human cognitive state over the last few decades. But most existing EEG-based fatigue detection methods have poor performance in accuracy. This paper proposed a single-channel EEG-based mental fatigue detection method based on Deep Belief Network (DBN). The fused nonliear features from specified sub-bands and dynamic analysis, a total of 21 features are extracted as the input of the DBN to discriminate three classes of mental state including alert, slight fatigue and severe fatigue. Experimental results show the good performance of the proposed model comparing with those state-of-art methods.

Clinical utility of EEG in diagnosing and monitoring epilepsy in adults.

PubMed

Tatum, W O; Rubboli, G; Kaplan, P W; Mirsatari, S M; Radhakrishnan, K; Gloss, D; Caboclo, L O; Drislane, F W; Koutroumanidis, M; Schomer, D L; Kasteleijn-Nolst Trenite, D; Cook, Mark; Beniczky, S

2018-05-01

Electroencephalography (EEG) remains an essential diagnostic tool for people with epilepsy (PWE). The International Federation of Clinical Neurophysiology produces new guidelines as an educational service for clinicians to address gaps in knowledge in clinical neurophysiology. The current guideline was prepared in response to gaps present in epilepsy-related neurophysiological assessment and is not intended to replace sound clinical judgement in the care of PWE. Furthermore, addressing specific pathophysiological conditions of the brain that produce epilepsy is of primary importance though is beyond the scope of this guideline. Instead, our goal is to summarize the scientific evidence for the utility of EEG when diagnosing and monitoring PWE. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Combining Cryptography with EEG Biometrics

PubMed Central

Kazanavičius, Egidijus; Woźniak, Marcin

2018-01-01

Cryptographic frameworks depend on key sharing for ensuring security of data. While the keys in cryptographic frameworks must be correctly reproducible and not unequivocally connected to the identity of a user, in biometric frameworks this is different. Joining cryptography techniques with biometrics can solve these issues. We present a biometric authentication method based on the discrete logarithm problem and Bose-Chaudhuri-Hocquenghem (BCH) codes, perform its security analysis, and demonstrate its security characteristics. We evaluate a biometric cryptosystem using our own dataset of electroencephalography (EEG) data collected from 42 subjects. The experimental results show that the described biometric user authentication system is effective, achieving an Equal Error Rate (ERR) of 0.024.

Combining Cryptography with EEG Biometrics.

PubMed

Damaševičius, Robertas; Maskeliūnas, Rytis; Kazanavičius, Egidijus; Woźniak, Marcin

2018-01-01

Cryptographic frameworks depend on key sharing for ensuring security of data. While the keys in cryptographic frameworks must be correctly reproducible and not unequivocally connected to the identity of a user, in biometric frameworks this is different. Joining cryptography techniques with biometrics can solve these issues. We present a biometric authentication method based on the discrete logarithm problem and Bose-Chaudhuri-Hocquenghem (BCH) codes, perform its security analysis, and demonstrate its security characteristics. We evaluate a biometric cryptosystem using our own dataset of electroencephalography (EEG) data collected from 42 subjects. The experimental results show that the described biometric user authentication system is effective, achieving an Equal Error Rate (ERR) of 0.024.

Using robust principal component analysis to alleviate day-to-day variability in EEG based emotion classification.

PubMed

Ping-Keng Jao; Yuan-Pin Lin; Yi-Hsuan Yang; Tzyy-Ping Jung

2015-08-01

An emerging challenge for emotion classification using electroencephalography (EEG) is how to effectively alleviate day-to-day variability in raw data. This study employed the robust principal component analysis (RPCA) to address the problem with a posed hypothesis that background or emotion-irrelevant EEG perturbations lead to certain variability across days and somehow submerge emotion-related EEG dynamics. The empirical results of this study evidently validated our hypothesis and demonstrated the RPCA's feasibility through the analysis of a five-day dataset of 12 subjects. The RPCA allowed tackling the sparse emotion-relevant EEG dynamics from the accompanied background perturbations across days. Sequentially, leveraging the RPCA-purified EEG trials from more days appeared to improve the emotion-classification performance steadily, which was not found in the case using the raw EEG features. Therefore, incorporating the RPCA with existing emotion-aware machine-learning frameworks on a longitudinal dataset of each individual may shed light on the development of a robust affective brain-computer interface (ABCI) that can alleviate ecological inter-day variability.

Effect of Muslim prayer (Salat) on α electroencephalography and its relationship with autonomic nervous system activity.

PubMed

Doufesh, Hazem; Ibrahim, Fatimah; Ismail, Noor Azina; Wan Ahmad, Wan Azman

2014-07-01

This study investigated the effect of Muslim prayer (salat) on the α relative power (RPα) of electroencephalography (EEG) and autonomic nervous activity and the relationship between them by using spectral analysis of EEG and heart rate variability (HRV). Thirty healthy Muslim men participated in the study. Their electrocardiograms and EEGs were continuously recorded before, during, and after salat practice with a computer-based data acquisition system (MP150, BIOPAC Systems Inc., Camino Goleta, California). Power spectral analysis was conducted to extract the RPα and HRV components. During salat, a significant increase (p<.05) was observed in the mean RPα in the occipital and parietal regions and in the normalized unit of high-frequency (nuHF) power of HRV (as a parasympathetic index). Meanwhile, the normalized unit of low-frequency (nuLF) power and LF/HF of HRV (as sympathetic indices) decreased according to HRV analyses. RPα showed a significant positive correlation in the occipital and parietal electrodes with nuHF and significant negative correlations with nuLF and LF/HF. During salat, parasympathetic activity increased and sympathetic activity decreased. Therefore, regular salat practices may help promote relaxation, minimize anxiety, and reduce cardiovascular risk.

Revealing hidden states in visual working memory using electroencephalography

PubMed Central

Wolff, Michael J.; Ding, Jacqueline; Myers, Nicholas E.; Stokes, Mark G.

2015-01-01

It is often assumed that information in visual working memory (vWM) is maintained via persistent activity. However, recent evidence indicates that information in vWM could be maintained in an effectively “activity-silent” neural state. Silent vWM is consistent with recent cognitive and neural models, but poses an important experimental problem: how can we study these silent states using conventional measures of brain activity? We propose a novel approach that is analogous to echolocation: using a high-contrast visual stimulus, it may be possible to drive brain activity during vWM maintenance and measure the vWM-dependent impulse response. We recorded electroencephalography (EEG) while participants performed a vWM task in which a randomly oriented grating was remembered. Crucially, a high-contrast, task-irrelevant stimulus was shown in the maintenance period in half of the trials. The electrophysiological response from posterior channels was used to decode the orientations of the gratings. While orientations could be decoded during and shortly after stimulus presentation, decoding accuracy dropped back close to baseline in the delay. However, the visual evoked response from the task-irrelevant stimulus resulted in a clear re-emergence in decodability. This result provides important proof-of-concept for a promising and relatively simple approach to decode “activity-silent” vWM content using non-invasive EEG. PMID:26388748

MNE software for processing MEG and EEG data

PubMed Central

Gramfort, A.; Luessi, M.; Larson, E.; Engemann, D.; Strohmeier, D.; Brodbeck, C.; Parkkonen, L.; Hämäläinen, M.

2013-01-01

Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals originating from neural currents in the brain. Using these signals to characterize and locate brain activity is a challenging task, as evidenced by several decades of methodological contributions. MNE, whose name stems from its capability to compute cortically-constrained minimum-norm current estimates from M/EEG data, is a software package that provides comprehensive analysis tools and workflows including preprocessing, source estimation, time–frequency analysis, statistical analysis, and several methods to estimate functional connectivity between distributed brain regions. The present paper gives detailed information about the MNE package and describes typical use cases while also warning about potential caveats in analysis. The MNE package is a collaborative effort of multiple institutes striving to implement and share best methods and to facilitate distribution of analysis pipelines to advance reproducibility of research. Full documentation is available at http://martinos.org/mne. PMID:24161808

Evidence of emotion-antecedent appraisal checks in electroencephalography and facial electromyography

PubMed Central

Scherer, Klaus R.; Schuller, Björn W.

2018-01-01

In the present study, we applied Machine Learning (ML) methods to identify psychobiological markers of cognitive processes involved in the process of emotion elicitation as postulated by the Component Process Model (CPM). In particular, we focused on the automatic detection of five appraisal checks—novelty, intrinsic pleasantness, goal conduciveness, control, and power—in electroencephalography (EEG) and facial electromyography (EMG) signals. We also evaluated the effects on classification accuracy of averaging the raw physiological signals over different numbers of trials, and whether the use of minimal sets of EEG channels localized over specific scalp regions of interest are sufficient to discriminate between appraisal checks. We demonstrated the effectiveness of our approach on two data sets obtained from previous studies. Our results show that novelty and power appraisal checks can be consistently detected in EEG signals above chance level (binary tasks). For novelty, the best classification performance in terms of accuracy was achieved using features extracted from the whole scalp, and by averaging across 20 individual trials in the same experimental condition (UAR = 83.5 ± 4.2; N = 25). For power, the best performance was obtained by using the signals from four pre-selected EEG channels averaged across all trials available for each participant (UAR = 70.6 ± 5.3; N = 24). Together, our results indicate that accurate classification can be achieved with a relatively small number of trials and channels, but that averaging across a larger number of individual trials is beneficial for the classification for both appraisal checks. We were not able to detect any evidence of the appraisal checks under study in the EMG data. The proposed methodology is a promising tool for the study of the psychophysiological mechanisms underlying emotional episodes, and their application to the development of computerized tools (e.g., Brain-Computer Interface) for the study of

Evidence of emotion-antecedent appraisal checks in electroencephalography and facial electromyography.

PubMed

Coutinho, Eduardo; Gentsch, Kornelia; van Peer, Jacobien; Scherer, Klaus R; Schuller, Björn W

2018-01-01

In the present study, we applied Machine Learning (ML) methods to identify psychobiological markers of cognitive processes involved in the process of emotion elicitation as postulated by the Component Process Model (CPM). In particular, we focused on the automatic detection of five appraisal checks-novelty, intrinsic pleasantness, goal conduciveness, control, and power-in electroencephalography (EEG) and facial electromyography (EMG) signals. We also evaluated the effects on classification accuracy of averaging the raw physiological signals over different numbers of trials, and whether the use of minimal sets of EEG channels localized over specific scalp regions of interest are sufficient to discriminate between appraisal checks. We demonstrated the effectiveness of our approach on two data sets obtained from previous studies. Our results show that novelty and power appraisal checks can be consistently detected in EEG signals above chance level (binary tasks). For novelty, the best classification performance in terms of accuracy was achieved using features extracted from the whole scalp, and by averaging across 20 individual trials in the same experimental condition (UAR = 83.5 ± 4.2; N = 25). For power, the best performance was obtained by using the signals from four pre-selected EEG channels averaged across all trials available for each participant (UAR = 70.6 ± 5.3; N = 24). Together, our results indicate that accurate classification can be achieved with a relatively small number of trials and channels, but that averaging across a larger number of individual trials is beneficial for the classification for both appraisal checks. We were not able to detect any evidence of the appraisal checks under study in the EMG data. The proposed methodology is a promising tool for the study of the psychophysiological mechanisms underlying emotional episodes, and their application to the development of computerized tools (e.g., Brain-Computer Interface) for the study of

Neural Correlates of Phrase Rhythm: An EEG Study of Bipartite vs. Rondo Sonata Form.

PubMed

Martínez-Rodrigo, Arturo; Fernández-Sotos, Alicia; Latorre, José Miguel; Moncho-Bogani, José; Fernández-Caballero, Antonio

2017-01-01

This paper introduces the neural correlates of phrase rhythm. In short, phrase rhythm is the rhythmic aspect of phrase construction and the relationships between phrases. For the sake of establishing the neural correlates, a musical experiment has been designed to induce music-evoked stimuli related to phrase rhythm. Brain activity is monitored through electroencephalography (EEG) by using a brain-computer interface. The power spectral value of each EEG channel is estimated to obtain how power variance distributes as a function of frequency. Our experiment shows statistical differences in theta and alpha bands in the phrase rhythm variations of two classical sonatas, one in bipartite form and the other in rondo form.

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.

MATLAB Toolboxes for Reference Electrode Standardization Technique (REST) of Scalp EEG

PubMed Central

Dong, Li; Li, Fali; Liu, Qiang; Wen, Xin; Lai, Yongxiu; Xu, Peng; Yao, Dezhong

2017-01-01

Reference electrode standardization technique (REST) has been increasingly acknowledged and applied as a re-reference technique to transform an actual multi-channels recordings to approximately zero reference ones in electroencephalography/event-related potentials (EEG/ERPs) community around the world in recent years. However, a more easy-to-use toolbox for re-referencing scalp EEG data to zero reference is still lacking. Here, we have therefore developed two open-source MATLAB toolboxes for REST of scalp EEG. One version of REST is closely integrated into EEGLAB, which is a popular MATLAB toolbox for processing the EEG data; and another is a batch version to make it more convenient and efficient for experienced users. Both of them are designed to provide an easy-to-use for novice researchers and flexibility for experienced researchers. All versions of the REST toolboxes can be freely downloaded at http://www.neuro.uestc.edu.cn/rest/Down.html, and the detailed information including publications, comments and documents on REST can also be found from this website. An example of usage is given with comparative results of REST and average reference. We hope these user-friendly REST toolboxes could make the relatively novel technique of REST easier to study, especially for applications in various EEG studies. PMID:29163006

MATLAB Toolboxes for Reference Electrode Standardization Technique (REST) of Scalp EEG.

PubMed

Dong, Li; Li, Fali; Liu, Qiang; Wen, Xin; Lai, Yongxiu; Xu, Peng; Yao, Dezhong

2017-01-01

Reference electrode standardization technique (REST) has been increasingly acknowledged and applied as a re-reference technique to transform an actual multi-channels recordings to approximately zero reference ones in electroencephalography/event-related potentials (EEG/ERPs) community around the world in recent years. However, a more easy-to-use toolbox for re-referencing scalp EEG data to zero reference is still lacking. Here, we have therefore developed two open-source MATLAB toolboxes for REST of scalp EEG. One version of REST is closely integrated into EEGLAB, which is a popular MATLAB toolbox for processing the EEG data; and another is a batch version to make it more convenient and efficient for experienced users. Both of them are designed to provide an easy-to-use for novice researchers and flexibility for experienced researchers. All versions of the REST toolboxes can be freely downloaded at http://www.neuro.uestc.edu.cn/rest/Down.html, and the detailed information including publications, comments and documents on REST can also be found from this website. An example of usage is given with comparative results of REST and average reference. We hope these user-friendly REST toolboxes could make the relatively novel technique of REST easier to study, especially for applications in various EEG studies.

Multivariate pattern analysis of MEG and EEG: A comparison of representational structure in time and space.

PubMed

Cichy, Radoslaw Martin; Pantazis, Dimitrios

2017-09-01

Multivariate pattern analysis of magnetoencephalography (MEG) and electroencephalography (EEG) data can reveal the rapid neural dynamics underlying cognition. However, MEG and EEG have systematic differences in sampling neural activity. This poses the question to which degree such measurement differences consistently bias the results of multivariate analysis applied to MEG and EEG activation patterns. To investigate, we conducted a concurrent MEG/EEG study while participants viewed images of everyday objects. We applied multivariate classification analyses to MEG and EEG data, and compared the resulting time courses to each other, and to fMRI data for an independent evaluation in space. We found that both MEG and EEG revealed the millisecond spatio-temporal dynamics of visual processing with largely equivalent results. Beyond yielding convergent results, we found that MEG and EEG also captured partly unique aspects of visual representations. Those unique components emerged earlier in time for MEG than for EEG. Identifying the sources of those unique components with fMRI, we found the locus for both MEG and EEG in high-level visual cortex, and in addition for MEG in low-level visual cortex. Together, our results show that multivariate analyses of MEG and EEG data offer a convergent and complimentary view on neural processing, and motivate the wider adoption of these methods in both MEG and EEG research. Copyright © 2017 Elsevier Inc. All rights reserved.

Requests for electroencephalography in a district general hospital: retrospective and prospective audit

PubMed Central

Smith, D; Bartolo, R; Pickles, R M; Tedman, B M

2001-01-01

Objectives To determine the number of inappropriate requests for electroencephalography (EEG) and whether guidelines on use could reduce this number. Design Audit with retrospective and prospective components. Setting EEG department in district general hospital and centre for neurology and neurosurgery. Participants Retrospective: 368 at the general hospital and 143 patients at the neurology centre. Prospective: 241 patients undergoing EEG at the general hospital. Interventions Guidelines for EEG issued to users of service at the general hospital. Outcomes Retrospective: differences in requesting practice, result in different clinical scenarios, relative roles of procedure, clinical acumen in establishing diagnosis, usefulness of procedure. Prospective: change of requesting practice, impact on use. Results There were considerable differences in requesting practice. Non-specialists seem to use EEG as a diagnostic tool, especially in patients with “funny turns,” when it is much more likely to yield potentially misleading than clinically useful information. The overall proportion of procedures considered to influence management, to be justifiable, and to be inappropriate were 16% (59), 28.3% (104), and 55.7% (205), respectively. In the prospective study the total number of requests was significantly reduced (χ2=33.85, df=5, P<0.0001), mainly because of fewer requests in patients with non-specific “funny turns” (χ2=21.90, df=6, P=0.0013). There was a concomitant change in the usefulness of EEG (χ2 =26.99, df=2, P<0.0001). Conclusions This original audit informed clinical practice and had potential benefits for patients, clinicians, and provision of service. Systematic replication of this project, possibly on a regional basis, could result in financial savings, which would allow development of accessible local neurophysiology services. What is already known on this topicThere is unrestricted access to EEG in most district general hospitals throughout the

Prediction of fatigue-related driver performance from EEG data by deep Riemannian model.

PubMed

Hajinoroozi, Mehdi; Jianqiu Zhang; Yufei Huang

2017-07-01

Prediction of the drivers' drowsy and alert states is important for safety purposes. The prediction of drivers' drowsy and alert states from electroencephalography (EEG) using shallow and deep Riemannian methods is presented. For shallow Riemannian methods, the minimum distance to Riemannian mean (mdm) and Log-Euclidian metric are investigated, where it is shown that Log-Euclidian metric outperforms the mdm algorithm. In addition the SPDNet, a deep Riemannian model, that takes the EEG covariance matrix as the input is investigated. It is shown that SPDNet outperforms all tested shallow and deep classification methods. Performance of SPDNet is 6.02% and 2.86% higher than the best performance by the conventional Euclidian classifiers and shallow Riemannian models, respectively.

Microstates in Resting-State EEG: Current Status and Future Directions

PubMed Central

Khanna, Arjun; Pascual-Leone, Alvaro; Michel, Christoph M.; Farzan, Faranak

2015-01-01

Electroencephalography (EEG) is a powerful method of studying the electrophysiology of the brain with high temporal resolution. Several analytical approaches to extract information from the EEG signal have been proposed. One method, termed microstate analysis, considers the multichannel EEG recording as a series of quasi-stable “microstates” that are each characterized by a unique topography of electric potentials over the entire channel array. Because this technique simultaneously considers signals recorded from all areas of the cortex, it is capable of assessing the function of large-scale brain networks whose disruption is associated with several neuropsychiatric disorders. In this review, we first introduce the method of EEG microstate analysis. We then review studies that have discovered significant changes in the resting-state microstate series in a variety of neuropsychiatric disorders and behavioral states. We discuss the potential utility of this method in detecting neurophysiological impairments in disease and monitoring neurophysiological changes in response to an intervention. Finally, we discuss how the resting-state microstate series may reflect rapid switching among neural networks while the brain is at rest, which could represent activity of resting-state networks described by other neuroimaging modalities. We conclude by commenting on the current and future status of microstate analysis, and suggest that EEG microstates represent a promising neurophysiological tool for understanding and assessing brain network dynamics on a millisecond timescale in health and disease. PMID:25526823

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

Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

PubMed Central

Murta, Teresa; Leite, Marco; Carmichael, David W; Figueiredo, Patrícia; Lemieux, Louis

2015-01-01

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are important tools in cognitive and clinical neuroscience. Combined EEG–fMRI has been shown to help to characterise brain networks involved in epileptic activity, as well as in different sensory, motor and cognitive functions. A good understanding of the electrophysiological correlates of the blood oxygen level-dependent (BOLD) signal is necessary to interpret fMRI maps, particularly when obtained in combination with EEG. We review the current understanding of electrophysiological–haemodynamic correlates, during different types of brain activity. We start by describing the basic mechanisms underlying EEG and BOLD signals and proceed by reviewing EEG-informed fMRI studies using fMRI to map specific EEG phenomena over the entire brain (EEG–fMRI mapping), or exploring a range of EEG-derived quantities to determine which best explain colocalised BOLD fluctuations (local EEG–fMRI coupling). While reviewing studies of different forms of brain activity (epileptic and nonepileptic spontaneous activity; cognitive, sensory and motor functions), a significant attention is given to epilepsy because the investigation of its haemodynamic correlates is the most common application of EEG-informed fMRI. Our review is focused on EEG-informed fMRI, an asymmetric approach of data integration. We give special attention to the invasiveness of electrophysiological measurements and the simultaneity of multimodal acquisitions because these methodological aspects determine the nature of the conclusions that can be drawn from EEG-informed fMRI studies. We emphasise the advantages of, and need for, simultaneous intracranial EEG–fMRI studies in humans, which recently became available and hold great potential to improve our understanding of the electrophysiological correlates of BOLD fluctuations. PMID:25277370

How Useful Is Electroencephalography in the Diagnosis of Autism Spectrum Disorders and the Delineation of Subtypes: A Systematic Review

PubMed Central

Gurau, Oana; Bosl, William J.; Newton, Charles R.

2017-01-01

Autism spectrum disorders (ASD) are thought to be associated with abnormal neural connectivity. Presently, neural connectivity is a theoretical construct that cannot be easily measured. Research in network science and time series analysis suggests that neural network structure, a marker of neural activity, can be measured with electroencephalography (EEG). EEG can be quantified by different methods of analysis to potentially detect brain abnormalities. The aim of this review is to examine evidence for the utility of three methods of EEG signal analysis in the ASD diagnosis and subtype delineation. We conducted a review of literature in which 40 studies were identified and classified according to the principal method of EEG analysis in three categories: functional connectivity analysis, spectral power analysis, and information dynamics. All studies identified significant differences between ASD patients and non-ASD subjects. However, due to high heterogeneity in the results, generalizations could not be inferred and none of the methods alone are currently useful as a new diagnostic tool. The lack of studies prevented the analysis of these methods as tools for ASD subtypes delineation. These results confirm EEG abnormalities in ASD, but as yet not sufficient to help in the diagnosis. Future research with larger samples and more robust study designs could allow for higher sensitivity and consistency in characterizing ASD, paving the way for developing new means of diagnosis. PMID:28747892

Sparsity enables estimation of both subcortical and cortical activity from MEG and EEG

PubMed Central

Krishnaswamy, Pavitra; Obregon-Henao, Gabriel; Ahveninen, Jyrki; Khan, Sheraz; Iglesias, Juan Eugenio; Hämäläinen, Matti S.; Purdon, Patrick L.

2017-01-01

Subcortical structures play a critical role in brain function. However, options for assessing electrophysiological activity in these structures are limited. Electromagnetic fields generated by neuronal activity in subcortical structures can be recorded noninvasively, using magnetoencephalography (MEG) and electroencephalography (EEG). However, these subcortical signals are much weaker than those generated by cortical activity. In addition, we show here that it is difficult to resolve subcortical sources because distributed cortical activity can explain the MEG and EEG patterns generated by deep sources. We then demonstrate that if the cortical activity is spatially sparse, both cortical and subcortical sources can be resolved with M/EEG. Building on this insight, we develop a hierarchical sparse inverse solution for M/EEG. We assess the performance of this algorithm on realistic simulations and auditory evoked response data, and show that thalamic and brainstem sources can be correctly estimated in the presence of cortical activity. Our work provides alternative perspectives and tools for characterizing electrophysiological activity in subcortical structures in the human brain. PMID:29138310

Decoding of four movement directions using hybrid NIRS-EEG brain-computer interface

PubMed Central

Khan, M. Jawad; Hong, Melissa Jiyoun; Hong, Keum-Shik

2014-01-01

The hybrid brain-computer interface (BCI)'s multimodal technology enables precision brain-signal classification that can be used in the formulation of control commands. In the present study, an experimental hybrid near-infrared spectroscopy-electroencephalography (NIRS-EEG) technique was used to extract and decode four different types of brain signals. The NIRS setup was positioned over the prefrontal brain region, and the EEG over the left and right motor cortex regions. Twelve subjects participating in the experiment were shown four direction symbols, namely, “forward,” “backward,” “left,” and “right.” The control commands for forward and backward movement were estimated by performing arithmetic mental tasks related to oxy-hemoglobin (HbO) changes. The left and right directions commands were associated with right and left hand tapping, respectively. The high classification accuracies achieved showed that the four different control signals can be accurately estimated using the hybrid NIRS-EEG technology. PMID:24808844

Resting State EEG-based biometrics for individual identification using convolutional neural networks.

PubMed

Lan Ma; Minett, James W; Blu, Thierry; Wang, William S-Y

2015-08-01

Biometrics is a growing field, which permits identification of individuals by means of unique physical features. Electroencephalography (EEG)-based biometrics utilizes the small intra-personal differences and large inter-personal differences between individuals' brainwave patterns. In the past, such methods have used features derived from manually-designed procedures for this purpose. Another possibility is to use convolutional neural networks (CNN) to automatically extract an individual's best and most unique neural features and conduct classification, using EEG data derived from both Resting State with Open Eyes (REO) and Resting State with Closed Eyes (REC). Results indicate that this CNN-based joint-optimized EEG-based Biometric System yields a high degree of accuracy of identification (88%) for 10-class classification. Furthermore, rich inter-personal difference can be found using a very low frequency band (0-2Hz). Additionally, results suggest that the temporal portions over which subjects can be individualized is less than 200 ms.

Efficiency test of filtering methods for the removal of transcranial magnetic stimulation artifacts on human electroencephalography with artificially transcranial magnetic stimulation-corrupted signals

NASA Astrophysics Data System (ADS)

Zilber, Nicolas A.; Katayama, Yoshinori; Iramina, Keiji; Erich, Wintermantel

2010-05-01

A new approach is proposed to test the efficiency of methods, such as the Kalman filter and the independent component analysis (ICA), when applied to remove the artifacts induced by transcranial magnetic stimulation (TMS) from electroencephalography (EEG). By using EEG recordings corrupted by TMS induction, the shape of the artifacts is approximately described with a model based on an equivalent circuit simulation. These modeled artifacts are subsequently added to other EEG signals—this time not influenced by TMS. The resulting signals prove of interest since we also know their form without the pseudo-TMS artifacts. Therefore, they enable us to use a fit test to compare the signals we obtain after removing the artifacts with the original signals. This efficiency test turned out very useful in comparing the methods between them, as well as in determining the parameters of the filtering that give satisfactory results with the automatic ICA.

Single-channel in-ear-EEG detects the focus of auditory attention to concurrent tone streams and mixed speech.

PubMed

Fiedler, Lorenz; Wöstmann, Malte; Graversen, Carina; Brandmeyer, Alex; Lunner, Thomas; Obleser, Jonas

2017-06-01

Conventional, multi-channel scalp electroencephalography (EEG) allows the identification of the attended speaker in concurrent-listening ('cocktail party') scenarios. This implies that EEG might provide valuable information to complement hearing aids with some form of EEG and to install a level of neuro-feedback. To investigate whether a listener's attentional focus can be detected from single-channel hearing-aid-compatible EEG configurations, we recorded EEG from three electrodes inside the ear canal ('in-Ear-EEG') and additionally from 64 electrodes on the scalp. In two different, concurrent listening tasks, participants (n  =  7) were fitted with individualized in-Ear-EEG pieces and were either asked to attend to one of two dichotically-presented, concurrent tone streams or to one of two diotically-presented, concurrent audiobooks. A forward encoding model was trained to predict the EEG response at single EEG channels. Each individual participants' attentional focus could be detected from single-channel EEG response recorded from short-distance configurations consisting only of a single in-Ear-EEG electrode and an adjacent scalp-EEG electrode. The differences in neural responses to attended and ignored stimuli were consistent in morphology (i.e. polarity and latency of components) across subjects. In sum, our findings show that the EEG response from a single-channel, hearing-aid-compatible configuration provides valuable information to identify a listener's focus of attention.

Sustained Attention in Real Classroom Settings: An EEG Study.

PubMed

Ko, Li-Wei; Komarov, Oleksii; Hairston, W David; Jung, Tzyy-Ping; Lin, Chin-Teng

2017-01-01

Sustained attention is a process that enables the maintenance of response persistence and continuous effort over extended periods of time. Performing attention-related tasks in real life involves the need to ignore a variety of distractions and inhibit attention shifts to irrelevant activities. This study investigates electroencephalography (EEG) spectral changes during a sustained attention task within a real classroom environment. Eighteen healthy students were instructed to recognize as fast as possible special visual targets that were displayed during regular university lectures. Sorting their EEG spectra with respect to response times, which indicated the level of visual alertness to randomly introduced visual stimuli, revealed significant changes in the brain oscillation patterns. The results of power-frequency analysis demonstrated a relationship between variations in the EEG spectral dynamics and impaired performance in the sustained attention task. Across subjects and sessions, prolongation of the response time was preceded by an increase in the delta and theta EEG powers over the occipital region, and decrease in the beta power over the occipital and temporal regions. Meanwhile, implementation of the complex attention task paradigm into a real-world classroom setting makes it possible to investigate specific mutual links between brain activities and factors that cause impaired behavioral performance, such as development and manifestation of classroom mental fatigue. The findings of the study set a basis for developing a system capable of estimating the level of visual attention during real classroom activities by monitoring changes in the EEG spectra.

Sustained Attention in Real Classroom Settings: An EEG Study

PubMed Central

Ko, Li-Wei; Komarov, Oleksii; Hairston, W. David; Jung, Tzyy-Ping; Lin, Chin-Teng

2017-01-01

Sustained attention is a process that enables the maintenance of response persistence and continuous effort over extended periods of time. Performing attention-related tasks in real life involves the need to ignore a variety of distractions and inhibit attention shifts to irrelevant activities. This study investigates electroencephalography (EEG) spectral changes during a sustained attention task within a real classroom environment. Eighteen healthy students were instructed to recognize as fast as possible special visual targets that were displayed during regular university lectures. Sorting their EEG spectra with respect to response times, which indicated the level of visual alertness to randomly introduced visual stimuli, revealed significant changes in the brain oscillation patterns. The results of power-frequency analysis demonstrated a relationship between variations in the EEG spectral dynamics and impaired performance in the sustained attention task. Across subjects and sessions, prolongation of the response time was preceded by an increase in the delta and theta EEG powers over the occipital region, and decrease in the beta power over the occipital and temporal regions. Meanwhile, implementation of the complex attention task paradigm into a real-world classroom setting makes it possible to investigate specific mutual links between brain activities and factors that cause impaired behavioral performance, such as development and manifestation of classroom mental fatigue. The findings of the study set a basis for developing a system capable of estimating the level of visual attention during real classroom activities by monitoring changes in the EEG spectra. PMID:28824396

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.

Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals.

PubMed

Engemann, Denis A; Gramfort, Alexandre

2015-03-01

Magnetoencephalography and electroencephalography (M/EEG) measure non-invasively the weak electromagnetic fields induced by post-synaptic neural currents. The estimation of the spatial covariance of the signals recorded on M/EEG sensors is a building block of modern data analysis pipelines. Such covariance estimates are used in brain-computer interfaces (BCI) systems, in nearly all source localization methods for spatial whitening as well as for data covariance estimation in beamformers. The rationale for such models is that the signals can be modeled by a zero mean Gaussian distribution. While maximizing the Gaussian likelihood seems natural, it leads to a covariance estimate known as empirical covariance (EC). It turns out that the EC is a poor estimate of the true covariance when the number of samples is small. To address this issue the estimation needs to be regularized. The most common approach downweights off-diagonal coefficients, while more advanced regularization methods are based on shrinkage techniques or generative models with low rank assumptions: probabilistic PCA (PPCA) and factor analysis (FA). Using cross-validation all of these models can be tuned and compared based on Gaussian likelihood computed on unseen data. We investigated these models on simulations, one electroencephalography (EEG) dataset as well as magnetoencephalography (MEG) datasets from the most common MEG systems. First, our results demonstrate that different models can be the best, depending on the number of samples, heterogeneity of sensor types and noise properties. Second, we show that the models tuned by cross-validation are superior to models with hand-selected regularization. Hence, we propose an automated solution to the often overlooked problem of covariance estimation of M/EEG signals. The relevance of the procedure is demonstrated here for spatial whitening and source localization of MEG signals. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Spatial and temporal EEG dynamics of dual-task driving performance

PubMed Central

2011-01-01

Background Driver distraction is a significant cause of traffic accidents. The aim of this study is to investigate Electroencephalography (EEG) dynamics in relation to distraction during driving. To study human cognition under a specific driving task, simulated real driving using virtual reality (VR)-based simulation and designed dual-task events are built, which include unexpected car deviations and mathematics questions. Methods We designed five cases with different stimulus onset asynchrony (SOA) to investigate the distraction effects between the deviations and equations. The EEG channel signals are first converted into separated brain sources by independent component analysis (ICA). Then, event-related spectral perturbation (ERSP) changes of the EEG power spectrum are used to evaluate brain dynamics in time-frequency domains. Results Power increases in the theta and beta bands are observed in relation with distraction effects in the frontal cortex. In the motor area, alpha and beta power suppressions are also observed. All of the above results are consistently observed across 15 subjects. Additionally, further analysis demonstrates that response time and multiple cortical EEG power both changed significantly with different SOA. Conclusions This study suggests that theta power increases in the frontal area is related to driver distraction and represents the strength of distraction in real-life situations. PMID:21332977

Novel hydrogel-based preparation-free EEG electrode.

PubMed

Alba, Nicolas Alexander; Sclabassi, Robert J; Sun, Mingui; Cui, Xinyan Tracy

2010-08-01

The largest obstacles to signal transduction for electroencephalography (EEG) recording are the hair and the epidermal stratum corneum of the skin. In typical clinical situations, hair is parted or removed, and the stratum corneum is either abraded or punctured using invasive penetration devices. These steps increase preparation time, discomfort, and the risk of infection. Cross-linked sodium polyacrylate gel swelled with electrolyte was explored as a possible skin contact element for a prototype preparation-free EEG electrode. As a superabsorbent hydrogel, polyacrylate can swell with electrolyte solution to a degree far beyond typical contemporary electrode materials, delivering a strong hydrating effect to the skin surface. This hydrating power allows the material to increase the effective skin contact surface area through wetting, and noninvasively decrease or bypass the highly resistive barrier of the stratum corneum, allowing for reduced impedance and improved electrode performance. For the purposes of the tests performed in this study, the polyacrylate was prepared both as a solid elastic gel and as a flowable paste designed to penetrate dense scalp hair. The gel can hold 99.2% DI water or 91% electrolyte solution, and the water content remains high after 29 h of air exposure. The electrical impedance of the gel electrode on unprepared human forearm is significantly lower than a number of commercial ECG and EEG electrodes. This low impedance was maintained for at least 8 h (the longest time period measured). When a paste form of the electrode was applied directly onto scalp hair, the impedance was found to be lower than that measured with commercially available EEG paste applied in the same manner. Time-frequency transformation analysis of frontal lobe EEG recordings indicated comparable frequency response between the polyacrylate-based electrode on unprepared skin and the commercial EEG electrode on abraded skin. Evoked potential recordings demonstrated

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.

New Flexible Silicone-Based EEG Dry Sensor Material Compositions Exhibiting Improvements in Lifespan, Conductivity, and Reliability

PubMed Central

Yu, Yi-Hsin; Chen, Shih-Hsun; Chang, Che-Lun; Lin, Chin-Teng; Hairston, W. David; Mrozek, Randy A.

2016-01-01

This study investigates alternative material compositions for flexible silicone-based dry electroencephalography (EEG) electrodes to improve the performance lifespan while maintaining high-fidelity transmission of EEG signals. Electrode materials were fabricated with varying concentrations of silver-coated silica and silver flakes to evaluate their electrical, mechanical, and EEG transmission performance. Scanning electron microscope (SEM) analysis of the initial electrode development identified some weak points in the sensors’ construction, including particle pull-out and ablation of the silver coating on the silica filler. The newly-developed sensor materials achieved significant improvement in EEG measurements while maintaining the advantages of previous silicone-based electrodes, including flexibility and non-toxicity. The experimental results indicated that the proposed electrodes maintained suitable performance even after exposure to temperature fluctuations, 85% relative humidity, and enhanced corrosion conditions demonstrating improvements in the environmental stability. Fabricated flat (forehead) and acicular (hairy sites) electrodes composed of the optimum identified formulation exhibited low impedance and reliable EEG measurement; some initial human experiments demonstrate the feasibility of using these silicone-based electrodes for typical lab data collection applications. PMID:27809260

New Flexible Silicone-Based EEG Dry Sensor Material Compositions Exhibiting Improvements in Lifespan, Conductivity, and Reliability.

PubMed

Yu, Yi-Hsin; Chen, Shih-Hsun; Chang, Che-Lun; Lin, Chin-Teng; Hairston, W David; Mrozek, Randy A

2016-10-31

This study investigates alternative material compositions for flexible silicone-based dry electroencephalography (EEG) electrodes to improve the performance lifespan while maintaining high-fidelity transmission of EEG signals. Electrode materials were fabricated with varying concentrations of silver-coated silica and silver flakes to evaluate their electrical, mechanical, and EEG transmission performance. Scanning electron microscope (SEM) analysis of the initial electrode development identified some weak points in the sensors' construction, including particle pull-out and ablation of the silver coating on the silica filler. The newly-developed sensor materials achieved significant improvement in EEG measurements while maintaining the advantages of previous silicone-based electrodes, including flexibility and non-toxicity. The experimental results indicated that the proposed electrodes maintained suitable performance even after exposure to temperature fluctuations, 85% relative humidity, and enhanced corrosion conditions demonstrating improvements in the environmental stability. Fabricated flat (forehead) and acicular (hairy sites) electrodes composed of the optimum identified formulation exhibited low impedance and reliable EEG measurement; some initial human experiments demonstrate the feasibility of using these silicone-based electrodes for typical lab data collection applications.

Sex differences in a chronometric mental rotation test with cube figures: a behavioral, electroencephalography, and eye-tracking pilot study.

PubMed

Scheer, Clara; Mattioni Maturana, Felipe; Jansen, Petra

2018-05-07

In chronometric mental rotation tasks, sex differences are widely discussed. Most studies find men to be more skilled in mental rotation than women, which can be explained by the holistic strategy that they use to rotate stimuli. Women are believed to apply a piecemeal strategy. So far, there have been no studies investigating this phenomenon using eye-tacking methods in combination with electroencephalography (EEG) analysis: the present study compared behavioral responses, EEG activity, and eye movements of 15 men and 15 women while solving a three-dimensional chronometric mental rotation test. The behavioral analysis showed neither differences in reaction time nor in the accuracy rate between men and women. The EEG data showed a higher right activation on parietal electrodes for women and the eye-tracking results indicated a longer fixation in a higher number of areas of interest at 0° for women. Men and women are likely to possess different perceptual (visual search) and decision-making mechanisms, but similar mental rotation processes. Furthermore, men presented a longer visual search processing, characterized by the greater saccade latency of 0°-135°. Generally, this study could be considered a pilot study to investigate sex differences in mental rotation tasks while combining eye-tracking and EEG methods.

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.

Neural Correlates of Phrase Rhythm: An EEG Study of Bipartite vs. Rondo Sonata Form

PubMed Central

Martínez-Rodrigo, Arturo; Fernández-Sotos, Alicia; Latorre, José Miguel; Moncho-Bogani, José; Fernández-Caballero, Antonio

2017-01-01

This paper introduces the neural correlates of phrase rhythm. In short, phrase rhythm is the rhythmic aspect of phrase construction and the relationships between phrases. For the sake of establishing the neural correlates, a musical experiment has been designed to induce music-evoked stimuli related to phrase rhythm. Brain activity is monitored through electroencephalography (EEG) by using a brain–computer interface. The power spectral value of each EEG channel is estimated to obtain how power variance distributes as a function of frequency. Our experiment shows statistical differences in theta and alpha bands in the phrase rhythm variations of two classical sonatas, one in bipartite form and the other in rondo form. PMID:28496406

Non-convulsive seizures and electroencephalography findings as predictors of clinical outcomes at a tertiary intensive care unit in Saudi Arabia.

PubMed

Al-Said, Youssef A; Baeesa, Saleh S; Shivji, Zaitoon; Kayyali, Husam; Alqadi, Khalid; Kadi, Ghada; Cupler, Edward J; Abuzinadah, Ahmad R

2018-06-05

Electroencephalography (EEG) in the intensive care unit (ICU) is often done to detect non-convulsive seizures (NCS). The outcome of ICU patients with NCS strongly depends on the underlying etiology. The implication of NCS and other EEG findings on clinical outcome independent from their etiology is not well understood and our aim to investigate it. We retrospectively identified all adult patients in the ICU who underwent EEG monitoring between January 2008 and December 2011. The main goals were to define the rate of NCS or non-convulsive status epilepticus (NCSE) occurrence in our center among patients who underwent EEG monitoring and to examine if NCS/NCSE are associated with poor outcome [defined as death or dependence] with and without adjustment for underlying etiology. The rate of poor outcome among different EEG categories were also investigated. During the study period, 177 patients underwent EEG monitoring in our ICU. The overall outcome was poor in 62.7% of those undergoing EEG. The rate of occurrence of NCS/NCSE was 8.5% and was associated with poor outcome in 86.7% with an odds ratio (OR) of 5.1 (95% confidence interval [CI] 1.09-23.8). This association was maintained after adjusting for underlying etiologies with OR 5.6 (95% CI 1.05-29.6). The rate of poor outcome was high in the presence of periodic discharges and sharp and slow waves of 75% and 61.5%, respectively. Our cohort of ICU patients undergoing EEGs had a poor outcome. Those who developed NCS/NCSE experienced an even worse outcome regardless of the underlying etiology. Copyright © 2018 Elsevier B.V. All rights reserved.

Hybrid EEG-fNIRS-Based Eight-Command Decoding for BCI: Application to Quadcopter Control.

PubMed

Khan, Muhammad Jawad; Hong, Keum-Shik

2017-01-01

In this paper, a hybrid electroencephalography-functional near-infrared spectroscopy (EEG-fNIRS) scheme to decode eight active brain commands from the frontal brain region for brain-computer interface is presented. A total of eight commands are decoded by fNIRS, as positioned on the prefrontal cortex, and by EEG, around the frontal, parietal, and visual cortices. Mental arithmetic, mental counting, mental rotation, and word formation tasks are decoded with fNIRS, in which the selected features for classification and command generation are the peak, minimum, and mean ΔHbO values within a 2-s moving window. In the case of EEG, two eyeblinks, three eyeblinks, and eye movement in the up/down and left/right directions are used for four-command generation. The features in this case are the number of peaks and the mean of the EEG signal during 1 s window. We tested the generated commands on a quadcopter in an open space. An average accuracy of 75.6% was achieved with fNIRS for four-command decoding and 86% with EEG for another four-command decoding. The testing results show the possibility of controlling a quadcopter online and in real-time using eight commands from the prefrontal and frontal cortices via the proposed hybrid EEG-fNIRS interface.

Wavelet-Based Artifact Identification and Separation Technique for EEG Signals during Galvanic Vestibular Stimulation

PubMed Central

Adib, Mani; Cretu, Edmond

2013-01-01

We present a new method for removing artifacts in electroencephalography (EEG) records during Galvanic Vestibular Stimulation (GVS). The main challenge in exploiting GVS is to understand how the stimulus acts as an input to brain. We used EEG to monitor the brain and elicit the GVS reflexes. However, GVS current distribution throughout the scalp generates an artifact on EEG signals. We need to eliminate this artifact to be able to analyze the EEG signals during GVS. We propose a novel method to estimate the contribution of the GVS current in the EEG signals at each electrode by combining time-series regression methods with wavelet decomposition methods. We use wavelet transform to project the recorded EEG signal into various frequency bands and then estimate the GVS current distribution in each frequency band. The proposed method was optimized using simulated signals, and its performance was compared to well-accepted artifact removal methods such as ICA-based methods and adaptive filters. The results show that the proposed method has better performance in removing GVS artifacts, compared to the others. Using the proposed method, a higher signal to artifact ratio of −1.625 dB was achieved, which outperformed other methods such as ICA-based methods, regression methods, and adaptive filters. PMID:23956786