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.

Automated electroencephalography system and electroencephalographic correlates of space motion sickness, part 4

NASA Technical Reports Server (NTRS)

Frost, J. D., Jr.

1977-01-01

Comparative data for further assessments of the EEG alterations seen during Skylab are elaborated. The variability of alpha, beta, theta, and delta EEG characteristics was analyzed with quantitative computer techniques in a group of six normal individuals over a period of two months, and the EEG effects of a prolonged period of bed rest were evaluated in two subjects. The results confirm that the inflight EEG changes seen during Skylab are statistically significant, but the absolute values obtained for the various parameters do not exceed the maximal range expected in a normal population. Further, the EEG manifestations of extended bed rest do not appear similar to those of space flight.

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.

Drug Treated Schizophrenia, Schizoaffective and Bipolar Disorder Patients Evaluated by qEEG Absolute Spectral Power and Mean Frequency Analysis.

PubMed

Wix-Ramos, Richard; Moreno, Xiomara; Capote, Eduardo; González, Gilbert; Uribe, Ezequiel; Eblen-Zajjur, Antonio

2014-04-01

Research of electroencephalograph (EEG) power spectrum and mean frequency has shown inconsistent results in patients with schizophrenic, schizoaffective and bipolar disorders during medication when compared to normal subjects thus; the characterization of these parameters is an important task. We applied quantitative EEG (qEEG) to investigate 38 control, 15 schizophrenic, 7 schizoaffective and 11 bipolar disorder subjects which remaine under the administration of psychotropic drugs (except control group). Absolute spectral power (ASP), mean frequency and hemispheric electrical asymmetry were measured by 19 derivation qEEG. Group mean values were compared with non parametrical Mann-Whitney test and spectral EEG maps with z-score method at p < 0.05. Most frequent drug treatments for schizophrenic patients were neuroleptic+antiepileptic (40% of cases) or 2 neuroleptics (33.3%). Schizoaffective patients received neuroleptic+benzodiazepine (71.4%) and for bipolar disorder patients neuroleptic+antiepileptic (81.8%). Schizophrenic (at all derivations except for Fp1, Fp2, F8 and T6) and schizoaffective (only at C3) show higher values of ASP (+57.7% and +86.1% respectively) compared to control group. ASP of bipolar disorder patients did not show differences against control group. The mean frequency was higher at Fp1 (+14.2%) and Fp2 (+17.4%) in bipolar disorder patients than control group, but no differences were found in frequencies between schizophrenic or schizoaffective patients against the control group. Majority of spectral differences were found at the left hemisphere in schizophrenic and schizoaffective but not in bipolar disorder subjects. The present report contributes to characterize quantitatively the qEEG in drug treated schizophrenic, schizoaffective or bipolar disorder patients.

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 outcome six months after discharge was significantly worse in patients with early epileptiform discharges (p=0.01). Epileptiform discharges within the first 30 min of EEG recording are predictive for the occurrence of ictal EEG patterns and for RPPIIU on subsequent cEEG, for acute convulsive seizures during the ICU stay, and for a worse functional outcome after 6 months of follow-up. This article is part of a Special Issue entitled Status Epilepticus. Copyright © 2015 Elsevier Inc. All rights reserved.

EEG-fMRI in the presurgical evaluation of temporal lobe epilepsy.

PubMed

Coan, Ana C; Chaudhary, Umair J; Frédéric Grouiller; Campos, Brunno M; Perani, Suejen; De Ciantis, Alessio; Vulliemoz, Serge; Diehl, Beate; Beltramini, Guilherme C; Carmichael, David W; Thornton, Rachel C; Covolan, Roberto J; Cendes, Fernando; Lemieux, Louis

2016-06-01

Drug-resistant temporal lobe epilepsy (TLE) often requires thorough investigation to define the epileptogenic zone for surgical treatment. We used simultaneous interictal scalp EEG-fMRI to evaluate its value for predicting long-term postsurgical outcome. 30 patients undergoing presurgical evaluation and proceeding to temporal lobe (TL) resection were studied. Interictal epileptiform discharges (IEDs) were identified on intra-MRI EEG and used to build a model of haemodynamic changes. In addition, topographic electroencephalographic correlation maps were calculated between the average IED during video-EEG and intra-MRI EEG, and used as a condition. This allowed the analysis of all data irrespective of the presence of IED on intra-MRI EEG. Mean follow-up after surgery was 46 months. International League Against Epilepsy (ILAE) outcomes 1 and 2 were considered good, and 3-6 poor, surgical outcome. Haemodynamic maps were classified according to the presence (Concordant) or absence (Discordant) of Blood Oxygen Level-Dependent (BOLD) change in the TL overlapping with the surgical resection. The proportion of patients with good surgical outcome was significantly higher (13/16; 81%) in the Concordant than in the Discordant group (3/14; 21%) (χ(2) test, Yates correction, p=0.003) and multivariate analysis showed that Concordant BOLD maps were independently related to good surgical outcome (p=0.007). Sensitivity and specificity of EEG-fMRI results to identify patients with good surgical outcome were 81% and 79%, respectively, and positive and negative predictive values were 81% and 79%, respectively. The presence of significant BOLD changes in the area of resection on interictal EEG-fMRI in patients with TLE retrospectively confirmed the epileptogenic zone. Surgical resection including regions of haemodynamic changes in the TL may lead to better postoperative outcome. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

A new method for quantifying the performance of EEG blind source separation algorithms by referencing a simultaneously recorded ECoG signal.

PubMed

Oosugi, Naoya; Kitajo, Keiichi; Hasegawa, Naomi; Nagasaka, Yasuo; Okanoya, Kazuo; Fujii, Naotaka

2017-09-01

Blind source separation (BSS) algorithms extract neural signals from electroencephalography (EEG) data. However, it is difficult to quantify source separation performance because there is no criterion to dissociate neural signals and noise in EEG signals. This study develops a method for evaluating BSS performance. The idea is neural signals in EEG can be estimated by comparison with simultaneously measured electrocorticography (ECoG). Because the ECoG electrodes cover the majority of the lateral cortical surface and should capture most of the original neural sources in the EEG signals. We measured real EEG and ECoG data and developed an algorithm for evaluating BSS performance. First, EEG signals are separated into EEG components using the BSS algorithm. Second, the EEG components are ranked using the correlation coefficients of the ECoG regression and the components are grouped into subsets based on their ranks. Third, canonical correlation analysis estimates how much information is shared between the subsets of the EEG components and the ECoG signals. We used our algorithm to compare the performance of BSS algorithms (PCA, AMUSE, SOBI, JADE, fastICA) via the EEG and ECoG data of anesthetized nonhuman primates. The results (Best case >JADE = fastICA >AMUSE = SOBI ≥ PCA >random separation) were common to the two subjects. To encourage the further development of better BSS algorithms, our EEG and ECoG data are available on our Web site (http://neurotycho.org/) as a common testing platform. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. 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 (57.9%) vs. 11/36 (30.6%) patients, respectively, p = 0.049]. Hospital LOS, in-hospital mortality and frequency of unfavorable outcomes did not differ between Ictal patients treated exclusively with AEDs or IVADs. Conclusion In patients with acute altered consciousness and abnormal routine EEG, antiepileptic treatment did not improve outcomes regardless of the presence of periodic, rhythmic or ictal EEG patterns. PMID:28886073

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, respectively, p = 0.049]. Hospital LOS, in-hospital mortality and frequency of unfavorable outcomes did not differ between Ictal patients treated exclusively with AEDs or IVADs. In patients with acute altered consciousness and abnormal routine EEG, antiepileptic treatment did not improve outcomes regardless of the presence of periodic, rhythmic or ictal EEG patterns.

Consensus-based guidelines for Video EEG monitoring in the pre-surgical evaluation of children with epilepsy in the UK.

PubMed

Pressler, Ronit M; Seri, Stefano; Kane, Nick; Martland, Tim; Goyal, Sushma; Iyer, Anand; Warren, Elliott; Notghi, Lesley; Bill, Peter; Thornton, Rachel; Appleton, Richard; Doyle, Sarah; Rushton, Sarah; Worley, Alan; Boyd, Stewart G

2017-08-01

Paediatric Epilepsy surgery in the UK has recently been centralised in order to improve expertise and quality of service available to children. Video EEG monitoring or telemetry is a highly specialised and a crucial component of the pre-surgical evaluation. Although many Epilepsy Monitoring Units work to certain standards, there is no national or international guideline for paediatric video telemetry. Due to lack of evidence we used a modified Delphi process utilizing the clinical and academic expertise of the clinical neurophysiology sub-specialty group of Children's Epilepsy Surgical Service (CESS) centres in England and Wales. This process consisted of the following stages I: Identification of the consensus working group, II: Identification of key areas for guidelines, III: Consensus practice points and IV: Final review. Statements that gained consensus (median score of either 4 or 5 using a five-point Likerttype scale) were included in the guideline. Two rounds of feedback and amendments were undertaken. The consensus guidelines includes the following topics: referral pathways, neurophysiological equipment standards, standards of recording techniques, with specific emphasis on safety of video EEG monitoring both with and without drug withdrawal, a protocol for testing patient's behaviours, data storage and guidelines for writing factual reports and conclusions. All statements developed received a median score of 5 and were adopted by the group. Using a modified Delphi process we were able to develop universally-accepted video EEG guidelines for the UK CESS. Although these recommendations have been specifically developed for the pre-surgical evaluation of children with epilepsy, it is assumed that most components are transferable to any paediatric video EEG monitoring setting. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Scalp EEG does not predict hemispherectomy outcome

PubMed Central

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

2012-01-01

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

Magnetic resonance imaging of the brain in epileptic adult patients: experience in Ramathibodi Hospital.

PubMed

Solosrungruang, Anusorn; Laothamatas, Jiraporn; Chinwarun, Yotin

2007-04-01

The purpose of the present study was to classify the imaging structural abnormalities of epileptic adult patients referred for magnetic resonance imaging (MR imaging) of the brain at Ramathibodi Hospital and to correlate with the clinical data and EEG. MR imaging of 91 adult epileptic patients (age ranging from 15-85 years old with an average of 36.90 years old) were retrospectively reviewed and classified into eight groups according to etiologies. Then clinical data and EEG correlations were analyzed using the Kappa analysis. All of the MR imaging of the brain were performed at Ramathibodi Hospital from January 2001 to December 2002. Secondary generalized tonic clonic seizure was the most common clinical presenting seizure type. Extra temporal lobe epilepsy was the most common clinical diagnosis. Of the thirty-three patients who underwent EEG before performing MR imaging, 17 had normal EEG From MR imaging, temporal lobe lesion was the main affected location and mesial temporal sclerosis (MTS) was the most common cause of the epilepsy in patients. For age group classification, young adult (15-34 years old) and adult (35-64 years old) age groups, MTS was the most common etiology of epilepsy with cortical dysplasia being the second most common cause for the first group and vascular disease for the latter group. For the older age group (> 64 years old), vascular disease and idiopathic cause were equally common etiologies. MRI, EEG findings, and clinical data were all concordant with statistical significance. MRI is the non-invasive modality of choice for evaluation of the epileptic patients. The result is concordant with the clinical and EEG findings. It can detect and localize the structural abnormality accurately and is useful in the treatment planning.

Comparison of EEG propagation speeds under emotional stimuli on smartphone between the different anxiety states

PubMed Central

Asakawa, Tetsuya; Muramatsu, Ayumi; Hayashi, Takuto; Urata, Tatsuya; Taya, Masato; Mizuno-Matsumoto, Yuko

2014-01-01

The current study evaluated the effect of different anxiety states on information processing as measured by an electroencephalography (EEG) using emotional stimuli on a smartphone. Twenty-three healthy subjects were assessed for their anxiety states using The State Trait Anxiety Inventory (STAI) and divided into two groups: low anxiety (I, II) or high anxiety (III and IV, V). An EEG was performed while the participant was presented with emotionally laden audiovisual stimuli (resting, pleasant, and unpleasant sessions) and emotionally laden sentence stimuli (pleasant sentence, unpleasant sentence sessions) and EEG data was analyzed using propagation speed analysis. The propagation speed of the low anxiety group at the medial coronal for resting stimuli for all time segments was higher than those of high anxiety group. The low anxiety group propagation speeds at the medial sagittal for unpleasant stimuli in the 0–30 and 60–150 s time frames were higher than those of high anxiety group. The propagation speeds at 150 s for all stimuli in the low anxiety group were significantly higher than the correspondent propagation speeds of the high anxiety group. These events suggest that neural information processes concerning emotional stimuli differ based on current anxiety state. PMID:25540618

Correlation between amygdala BOLD activity and frontal EEG asymmetry during real-time fMRI neurofeedback training in patients with depression

PubMed Central

Zotev, Vadim; Yuan, Han; Misaki, Masaya; Phillips, Raquel; Young, Kymberly D.; Feldner, Matthew T.; Bodurka, Jerzy

2016-01-01

Real-time fMRI neurofeedback (rtfMRI-nf) is an emerging approach for studies and novel treatments of major depressive disorder (MDD). EEG performed simultaneously with an rtfMRI-nf procedure allows an independent evaluation of rtfMRI-nf brain modulation effects. Frontal EEG asymmetry in the alpha band is a widely used measure of emotion and motivation that shows profound changes in depression. However, it has never been directly related to simultaneously acquired fMRI data. We report the first study investigating electrophysiological correlates of the rtfMRI-nf procedure, by combining the rtfMRI-nf with simultaneous and passive EEG recordings. In this pilot study, MDD patients in the experimental group (n = 13) learned to upregulate BOLD activity of the left amygdala using an rtfMRI-nf during a happy emotion induction task. MDD patients in the control group (n = 11) were provided with a sham rtfMRI-nf. Correlations between frontal EEG asymmetry in the upper alpha band and BOLD activity across the brain were examined. Average individual changes in frontal EEG asymmetry during the rtfMRI-nf task for the experimental group showed a significant positive correlation with the MDD patients' depression severity ratings, consistent with an inverse correlation between the depression severity and frontal EEG asymmetry at rest. The average asymmetry changes also significantly correlated with the amygdala BOLD laterality. Temporal correlations between frontal EEG asymmetry and BOLD activity were significantly enhanced, during the rtfMRI-nf task, for the amygdala and many regions associated with emotion regulation. Our findings demonstrate an important link between amygdala BOLD activity and frontal EEG asymmetry during emotion regulation. Our EEG asymmetry results indicate that the rtfMRI-nf training targeting the amygdala is beneficial to MDD patients. They further suggest that EEG-nf based on frontal EEG asymmetry in the alpha band would be compatible with the amygdala-based rtfMRI-nf. Combination of the two could enhance emotion regulation training and benefit MDD patients. PMID:26958462

Seven-star needle stimulation improves language and social interaction of children with autistic spectrum disorders.

PubMed

Chan, Agnes S; Cheung, Mei-Chun; Sze, Sophia L; Leung, Winnie W

2009-01-01

This is a randomized controlled trial that aimed to evaluate the effect of the Seven-star Needle Stimulation treatment on children with Autistic Spectrum Disorders (ASD). Thirty-two children with ASD were assigned randomly into the treatment and control groups. Children in the treatment group underwent 30 sessions of stimulation over 6 weeks, while children in the control group were on a waiting list and did not receive treatment during this period of time. Intervention consisted of a treatment regime comprising of 30 sessions of Seven-star Needle Stimulation, delivered over 6 weeks. Each session lasted 5 to 10 min, children in the treatment group were stimulated at the front and back sides of their body and the head by using Seven-star Needles. The change in the children's behavior was evaluated using parents' report and neurophysiological changes were measured by quantitative EEG (qEEG). Results showed that the treatment group demonstrated significant improvement in language and social interaction, but not in stereotyped behavior or motor function, compared to the control group. qEEG spectral amplitudes in the treatment, but not in the control group, were also reduced significantly. The results suggested that Seven-star Needle Stimulation might be an effective intervention to improve language and social functioning of children with ASD.

Nonlinear aspects of the EEG during sleep in children

NASA Astrophysics Data System (ADS)

Berryman, Matthew J.; Coussens, Scott W.; Pamula, Yvonne; Kennedy, Declan; Lushington, Kurt; Shalizi, Cosma; Allison, Andrew; Martin, A. James; Saint, David; Abbott, Derek

2005-05-01

Electroencephalograph (EEG) analysis enables the dynamic behavior of the brain to be examined. If the behavior is nonlinear then nonlinear tools can be used to glean information on brain behavior, and aid in the diagnosis of sleep abnormalities such as obstructive sleep apnea syndrome (OSAS). In this paper the sleep EEGs of a set of normal children and children with mild OSAS are evaluated for nonlinear brain behaviour. We found that there were differences in the nonlinearity of the brain behaviour between different sleep stages, and between the two groups of children.

Two Different Populations within the Healthy Elderly: Lack of Conflict Detection in Those at Risk of Cognitive Decline

PubMed Central

Sánchez-Moguel, Sergio M.; Alatorre-Cruz, Graciela C.; Silva-Pereyra, Juan; González-Salinas, Sofía; Sanchez-Lopez, Javier; Otero-Ojeda, Gloria A.; Fernández, Thalía

2018-01-01

During healthy aging, inhibitory processing is affected at the sensorial, perceptual, and cognitive levels. The assessment of event-related potentials (ERPs) during the Stroop task has been used to study age-related decline in the efficiency of inhibitory processes. Studies using ERPs have found that the P300 amplitude increases and the N500 amplitude is attenuated in healthy elderly adults compared to those in young adults. On the other hand, it has been reported that theta excess in resting EEG with eyes closed is a good predictor of cognitive decline during aging 7 years later, while a normal EEG increases the probability of not developing cognitive decline. The behavioral and ERP responses during a Counting-Stroop task were compared between 22 healthy elderly subjects with normal EEG (Normal-EEG group) and 22 healthy elderly subjects with an excess of EEG theta activity (Theta-EEG group). Behaviorally, the Normal-EEG group showed a higher behavioral interference effect than the Theta-EEG group. ERP patterns were different between the groups, and two facts are highlighted: (a) the P300 amplitude was higher in the Theta-EEG group, with both groups showing a P300 effect in almost all electrodes, and (b) the Theta-EEG group did not show an N500 effect. These results suggest that the diminishment in inhibitory control observed in the Theta-EEG group may be compensated by different processes in earlier stages, which would allow them to perform the task with similar efficiency to that of participants with a normal EEG. This study is the first to show that healthy elderly subjects with an excess of theta EEG activity not only are at risk of developing cognitive decline but already have a cognitive impairment. PMID:29375352

Two Different Populations within the Healthy Elderly: Lack of Conflict Detection in Those at Risk of Cognitive Decline.

PubMed

Sánchez-Moguel, Sergio M; Alatorre-Cruz, Graciela C; Silva-Pereyra, Juan; González-Salinas, Sofía; Sanchez-Lopez, Javier; Otero-Ojeda, Gloria A; Fernández, Thalía

2017-01-01

During healthy aging, inhibitory processing is affected at the sensorial, perceptual, and cognitive levels. The assessment of event-related potentials (ERPs) during the Stroop task has been used to study age-related decline in the efficiency of inhibitory processes. Studies using ERPs have found that the P300 amplitude increases and the N500 amplitude is attenuated in healthy elderly adults compared to those in young adults. On the other hand, it has been reported that theta excess in resting EEG with eyes closed is a good predictor of cognitive decline during aging 7 years later, while a normal EEG increases the probability of not developing cognitive decline. The behavioral and ERP responses during a Counting-Stroop task were compared between 22 healthy elderly subjects with normal EEG (Normal-EEG group) and 22 healthy elderly subjects with an excess of EEG theta activity (Theta-EEG group). Behaviorally, the Normal-EEG group showed a higher behavioral interference effect than the Theta-EEG group. ERP patterns were different between the groups, and two facts are highlighted: (a) the P300 amplitude was higher in the Theta-EEG group, with both groups showing a P300 effect in almost all electrodes, and (b) the Theta-EEG group did not show an N500 effect. These results suggest that the diminishment in inhibitory control observed in the Theta-EEG group may be compensated by different processes in earlier stages, which would allow them to perform the task with similar efficiency to that of participants with a normal EEG. This study is the first to show that healthy elderly subjects with an excess of theta EEG activity not only are at risk of developing cognitive decline but already have a cognitive impairment.

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

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).

A Cross-Correlational Analysis between Electroencephalographic and End-Tidal Carbon Dioxide Signals: Methodological Issues in the Presence of Missing Data and Real Data Results

PubMed Central

Morelli, Maria Sole; Giannoni, Alberto; Passino, Claudio; Landini, Luigi; Emdin, Michele; Vanello, Nicola

2016-01-01

Electroencephalographic (EEG) irreducible artifacts are common and the removal of corrupted segments from the analysis may be required. The present study aims at exploring the effects of different EEG Missing Data Segment (MDS) distributions on cross-correlation analysis, involving EEG and physiological signals. The reliability of cross-correlation analysis both at single subject and at group level as a function of missing data statistics was evaluated using dedicated simulations. Moreover, a Bayesian-based approach for combining the single subject results at group level by considering each subject’s reliability was introduced. Starting from the above considerations, the cross-correlation function between EEG Global Field Power (GFP) in delta band and end-tidal CO2 (PETCO2) during rest and voluntary breath-hold was evaluated in six healthy subjects. The analysis of simulated data results at single subject level revealed a worsening of precision and accuracy in the cross-correlation analysis in the presence of MDS. At the group level, a large improvement in the results’ reliability with respect to single subject analysis was observed. The proposed Bayesian approach showed a slight improvement with respect to simple average results. Real data results were discussed in light of the simulated data tests and of the current physiological findings. PMID:27809243

The effect of methylphenidate on very low frequency electroencephalography oscillations in adult ADHD.

PubMed

Cooper, Ruth E; Skirrow, Caroline; Tye, Charlotte; McLoughlin, Grainne; Rijsdijk, Fruhling; Banaschweski, Tobias; Brandeis, Daniel; Kuntsi, Jonna; Asherson, Philip

2014-04-01

Altered very low-frequency electroencephalographic (VLF-EEG) activity is an endophenotype of ADHD in children and adolescents. We investigated VLF-EEG case-control differences in adult samples and the effects of methylphenidate (MPH). A longitudinal case-control study was conducted examining the effects of MPH on VLF-EEG (.02-0.2Hz) during a cued continuous performance task. 41 untreated adults with ADHD and 47 controls were assessed, and 21 cases followed up after MPH treatment, with a similar follow-up for 38 controls (mean follow-up=9.4months). Cases had enhanced frontal and parietal VLF-EEG and increased omission errors. In the whole sample, increased parietal VLF-EEG correlated with increased omission errors. After controlling for subthreshold comorbid symptoms, VLF-EEG case-control differences and treatment effects remained. Post-treatment, a time by group interaction emerged; VLF-EEG and omission errors reduced to the same level as controls, with decreased inattentive symptoms in cases. Reduced VLF-EEG following MPH treatment provides preliminary evidence that changes in VLF-EEG may relate to MPH treatment effects on ADHD symptoms; and that VLF-EEG may be an intermediate phenotype of ADHD. Further studies of the treatment effect of MPH in larger controlled studies are required to formally evaluate any causal link between MPH, VLF-EEG and ADHD symptoms. Copyright © 2014 Elsevier Inc. All rights reserved.

Knowing when not to swing: EEG evidence that enhanced perception-action coupling underlies baseball batter expertise.

PubMed

Muraskin, Jordan; Sherwin, Jason; Sajda, Paul

2015-12-01

Given a decision that requires less than half a second for evaluating the characteristics of the incoming pitch and generating a motor response, hitting a baseball potentially requires unique perception-action coupling to achieve high performance. We designed a rapid perceptual decision-making experiment modeled as a Go/No-Go task yet tailored to reflect a real scenario confronted by a baseball hitter. For groups of experts (Division I baseball players) and novices (non-players), we recorded electroencephalography (EEG) while they performed the task. We analyzed evoked EEG single-trial variability, contingent negative variation (CNV), and pre-stimulus alpha power with respect to the expert vs. novice groups. We found strong evidence for differences in inhibitory processes between the two groups, specifically differential activity in supplementary motor areas (SMA), indicative of enhanced inhibitory control in the expert (baseball player) group. We also found selective activity in the fusiform gyrus (FG) and orbital gyrus in the expert group, suggesting an enhanced perception-action coupling in baseball players that differentiates them from matched controls. In sum, our results show that EEG correlates of decision formation can be used to identify neural markers of high-performance athletes. Copyright © 2015 Elsevier Inc. All rights reserved.

Changes in Resting EEG in Colombian Ex-combatants ith Antisocial Personality Disorder.

PubMed

Ramos, Claudia; Duque-Grajales, Jon; Rendón, Jorge; Montoya-Betancur, Alejandro; Baena, Ana; Pineda, David; Tobón, Carlos

Although the social and economic consequences of Colombian internal conflicts mainly affected the civilian population, they also had other implications. The ex-combatants, the other side of the conflict, have been the subject of many studies that question their personality structures and antisocial features. Results suggest that ex-combatants usually have characteristics of an antisocial personality disorder (ASPD) that is related with their behaviour. Quantitative EEG (qEEG) was used to evaluate differences in cortical activity patterns between an ex-combatants group and a control group. The Psychopathy Checklist-Revised (PCL-R) was used to assess the presence of ASPD in the ex-combatants group, as well as the Diagnostic Interview for Genetic Studies (DIGS) for other mental disorders classified in the DCI-10. There are significant differences in psychopathy levels between groups, as well as in alpha-2 and beta waves, especially in left temporal and frontal areas for alpha-2 waves and left temporal-central regions for beta waves. qEEG measurements allow spectral resting potential to be differentiated between groups that are related with features typically involved in antisocial personality disorder, and to correlate them with patterns in the questionnaires and clinical interview. Copyright © 2017 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Prognostic value of EEG in different etiological types of coma.

PubMed

Khaburzania, M; Beridze, M

2013-06-01

Study aimed at evaluation of prognostic value of standard EEG in different etiology of coma and the influence of etiological factor on the EEG patterns and coma outcome. Totally 175 coma patients were investigated. Patients were evaluated by Glasgow Coma Scale (GCS), clinically and by 16 channel electroencephalography. Auditory evoked potentials studied by EEG -regime for evoked potentials in patients with vegetative state (VS). Patients divided in 8 groups according to coma etiology. All patients were studied for photoreaction, brainstem reflexes, localization of sound and pain, length of coma state and outcome. Brain injury visualized by conventional CT. Outcome defined as death, VS, recovery with disability and without disability. Disability was rated by Disability Rating Scale (DRS). Recovered patients assessed by Mini Mental State Examination (MMSE) scale. Statistics performed by SPSS-11.0. From 175 coma patients 55 patients died, 23 patients found in VS, 97 patients recovered with and without disability. In all etiological groups of coma the background EEG patterns were established. Correspondence analysis of all investigated factors revealed that sound localization had the significant association with EEG delta and theta rhythms and with recovery from coma state (Chi-sqr. =31.10493; p= 0.000001). Among 23 VS patients 9 patients had the signs of MCS and showed the long latency waves (p300) after binaural stimulation. The high amplitude theta frequencies in frontal and temporal lobes significantly correlated with prolongation of latency of cognitive evoked potentials (r=+0.47; p<0.01). Etiological factor had the significant effect on EEG patterns' association with coma outcome only in hemorrhagic and traumatic coma (chi-sqr.=12.95; p<0.005; chi-sqr.=7.92; p<0.03 respectively). Significant correlations established between the delta and theta EEG patterns and coma outcome. Low amplitude decreased power delta and theta frequencies correlated with SND in survived coma patients (r=+0.21; p<0.001; r=+0.27; p<0.001 respectively). Standard EEG is the useful tool for elucidation of coma patients with a high probability to recover as well as those patients, who are at high risk of SND in case of recovery from coma state.

Short and long-term effects of sham-controlled prefrontal EEG-neurofeedback training in healthy subjects.

PubMed

Engelbregt, H J; Keeser, D; van Eijk, L; Suiker, E M; Eichhorn, D; Karch, S; Deijen, J B; Pogarell, O

2016-04-01

In this study we evaluated long-term effects of frontal beta EEG-neurofeedback training (E-NFT) on healthy subjects. We hypothesized that E-NFT can change frontal beta activity in the long-term and that changes in frontal beta EEG activity are accompanied by altered cognitive performance. 25 healthy subjects were included and randomly assigned to active or sham E-NFT. On average the subjects underwent 15 E-NFT training sessions with a training duration of 45 min. Resting-state EEG was recorded prior to E-NFT training (t1) and in a 3-year follow-up (t3). Compared to sham E-NFT, which was used for the control group, real E-NFT increased beta activity in a predictable way. This increase was maintained over a period of three years post training. However, E-NFT did not result in significantly improved cognitive performance. Based on our results, we conclude that EEG-NFT can selectively modify EEG beta activity both in short and long-term. This is a sham controlled EEG neurofeedback study demonstrating long-term effects in resting state EEG. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

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.

High-Frequency EEG Variations in Children with Autism Spectrum Disorder during Human Faces Visualization

PubMed Central

Reategui, Camille; Costa, Bruna Karen de Sousa; da Fonseca, Caio Queiroz; da Silva, Luana; Morya, Edgard

2017-01-01

Autism spectrum disorder (ASD) is a neuropsychiatric disorder characterized by the impairment in the social reciprocity, interaction/language, and behavior, with stereotypes and signs of sensory function deficits. Electroencephalography (EEG) is a well-established and noninvasive tool for neurophysiological characterization and monitoring of the brain electrical activity, able to identify abnormalities related to frequency range, connectivity, and lateralization of brain functions. This research aims to evidence quantitative differences in the frequency spectrum pattern between EEG signals of children with and without ASD during visualization of human faces in three different expressions: neutral, happy, and angry. Quantitative clinical evaluations, neuropsychological evaluation, and EEG of children with and without ASD were analyzed paired by age and gender. The results showed stronger activation in higher frequencies (above 30 Hz) in frontal, central, parietal, and occipital regions in the ASD group. This pattern of activation may correlate with developmental characteristics in the children with ASD. PMID:29018811

Impact of age on both BIS values and EEG bispectrum during anaesthesia with sevoflurane in children.

PubMed

Wodey, E; Tirel, O; Bansard, J Y; Terrier, A; Chanavaz, C; Harris, R; Ecoffey, C; Senhadji, L

2005-06-01

The aim of this study was to evaluate the potential relationship between age, BIS (Aspect), and the EEG bispectrum during anaesthesia with sevoflurane. BIS and raw EEG were recorded at a steady state of 1 MAC in 100 children, and during a decrease from 2 to 0.5 MAC in a sub-group of 29 children. The bispectrum of the EEG was estimated using MATLAB software. For analysis, the bispectrum was divided into 36 frequencies of coupling (P(i))--the MatBis. A multiple correspondence analysis (MCA) was used to establish an underlying structure of the pattern of each individual's MatBis at 1 MAC. Clustering of children into homogeneous groups was conducted by a hierarchical ascending classification (HAC). The level of statistical significance was set at 0.05. At 1 MAC, the BIS values for all children ranged from 20 to 74 (median 40). Projection of both age and BIS value recorded at 1 MAC onto the structured model of the MCA showed them to be distributed along the same axis, demonstrating that the different values of BIS obtained in younger or older children are mainly dependent on their MatBis. At 1 MAC, six homogeneous groups of children were obtained through the HAC. Groups 5 (30 months; range 23-49) and 6 (18 months; range 6-180) were the younger children and Group 1 (97 months; range 46-162) the older. Groups 5 and 6 had the highest median values of BIS (54; range 50-59) (55; range 26-74) and Group 1 the lowest values (29; range 22-37). The EEG bispectrum, as well as the BIS appeared to be strongly related to the age of children at 1 MAC sevoflurane.

Neural network detects the effects of p-CPA pre-treatment on brain electrophysiology in a rat model of focal brain injury.

PubMed

Sinha, Rakesh Kumar; Aggarwal, Yogender

2009-04-01

To examine the performance of Artificial Neural Network (ANN) in evaluation of the effects of pretreatment of para-Chlorophenylalanine (p-CPA), a serotonin blocker, in experimental brain injury. Continuous 4 h digital electroencephalogram (EEG) recordings from male Charles Foster rats and its power spectrum analysis by using fast Fourier transform (FFT) were performed in two experimental (i) drug untreated injury group; (ii) p-CPA pretreated injury group as well as a control group. The EEG power spectrum data were tested by ANN containing 60 nodes in input layer, weighted from the digital values of power spectrum from 0 to 30 Hz, 18 nodes in hidden layer and an output node. The effects of injury and of the drug pretreatment were confirmed with the help of calculation of edematous swelling in the brain. The changes in EEG spectral patterns were compared with the ANN and the accuracy was determined in terms of percent (%). Overall performance of the network was found the best in control group (97.9%) in comparison to p-CPA untreated injury group (96.3%) and p-CPA pretreated injury group (71.9%). The decrease in accuracy in p-CPA pretreated injury group of subjects have occurred due to increase in misclassified patterns due to faster recovery in brain cortical potentials. EEG spectrum analysis with ANN was found successful in identifying the changes due to brain swelling as well as the effect of pretreatment of p-CPA in focal brain injury condition. Thus, the training and testing of ANN with EEG power spectra can be used as an effective diagnostic tool for early prediction and monitoring of brain injury as well as the effects of drugs in this condition.

Abnormal cortical sources of resting state electroencephalographic rhythms in single treatment-naïve HIV individuals: A statistical z-score index.

PubMed

Babiloni, Claudio; Pennica, Alfredo; Del Percio, Claudio; Noce, Giuseppe; Cordone, Susanna; Muratori, Chiara; Ferracuti, Stefano; Donato, Nicole; Di Campli, Francesco; Gianserra, Laura; Teti, Elisabetta; Aceti, Antonio; Soricelli, Andrea; Viscione, Magdalena; Limatola, Cristina; Andreoni, Massimo; Onorati, Paolo

2016-03-01

This study tested a simple statistical procedure to recognize single treatment-naïve HIV individuals having abnormal cortical sources of resting state delta (<4 Hz) and alpha (8-13 Hz) electroencephalographic (EEG) rhythms with reference to a control group of sex-, age-, and education-matched healthy individuals. Compared to the HIV individuals with a statistically normal EEG marker, those with abnormal values were expected to show worse cognitive status. Resting state eyes-closed EEG data were recorded in 82 treatment-naïve HIV (39.8 ys.±1.2 standard error mean, SE) and 59 age-matched cognitively healthy subjects (39 ys.±2.2 SE). Low-resolution brain electromagnetic tomography (LORETA) estimated delta and alpha sources in frontal, central, temporal, parietal, and occipital cortical regions. Ratio of the activity of parietal delta and high-frequency alpha sources (EEG marker) showed the maximum difference between the healthy and the treatment-naïve HIV group. Z-score of the EEG marker was statistically abnormal in 47.6% of treatment-naïve HIV individuals with reference to the healthy group (p<0.05). Compared to the HIV individuals with a statistically normal EEG marker, those with abnormal values exhibited lower mini mental state evaluation (MMSE) score, higher CD4 count, and lower viral load (p<0.05). This statistical procedure permitted for the first time to identify single treatment-naïve HIV individuals having abnormal EEG activity. This procedure might enrich the detection and monitoring of effects of HIV on brain function in single treatment-naïve HIV individuals. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

EEG indices correlate with sustained attention performance in patients affected by diffuse axonal injury.

PubMed

Coelli, Stefania; Barbieri, Riccardo; Reni, Gianluigi; Zucca, Claudio; Bianchi, Anna Maria

2018-06-01

The aim of this study is to assess the ability of EEG-based indices in providing relevant information about cognitive engagement level during the execution of a clinical sustained attention (SA) test in healthy volunteers and DAI (diffused axonal injury)-affected patients. We computed three continuous power-based engagement indices (P β /P α , 1/P α , and P β / (P α + P θ )) from EEG recordings in a control group (n = 7) and seven DAI-affected patients executing a 10-min Conners' "not-X" continuous performance test (CPT). A correlation analysis was performed in order to investigate the existence of relations between the EEG metrics and behavioral parameters in both the populations. P β /P α and 1/P α indices were found to be correlated with reaction times in both groups while P β / (P α + P θ ) and P β /P α also correlated with the errors rate for DAI patients. In line with previous studies, time course fluctuations revealed a first strong decrease of attention after 2 min from the beginning of the test and a final fading at the end. Our results provide evidence that EEG-derived indices extraction and evaluation during SA tasks are helpful in the assessment of attention level in healthy subjects and DAI patients, offering motivations for including EEG monitoring in cognitive rehabilitation practice. Graphical abstract Three EEG-derived indices were computed from four electrodes montages in a population of seven healthy volunteers and a group of seven DAI-affected patients. Results show a significant correlation between the time course of the indices and behavioral parameters, thus demonstrating their usefulness in monitoring mental engagement level during a sustained attention task.

An Investigation of Stimulant Effects on the EEG of Children With Attention-Deficit/Hyperactivity Disorder.

PubMed

Clarke, Adam R; Barry, Robert J; Baker, Iris E; McCarthy, Rory; Selikowitz, Mark

2017-07-01

Stimulant medications are the most commonly prescribed treatment for Attention-Deficit/Hyperactivity Disorder (AD/HD). These medications result in a normalization of the EEG. However, past research has found that complete normalization of the EEG is not always achieved. One reason for this may be that studies have used different medications interchangeably, or groups of subjects on different stimulants. This study investigated whether methylphenidate and dexamphetamine produce different levels of normalization of the EEG in children with AD/HD. Three groups of 20 boys participated in this study. There were 2 groups with a diagnosis of AD/HD; one group, good responders to methylphenidate, and the second, good responders to dexamphetamine. The third group was a normal control group. Baseline EEGs were recorded using an eyes-closed resting condition, and analyzed for total power and relative delta, theta, alpha, and beta. Subjects were placed on a 6-month trial of methylphenidate or dexamphetamine, after which a second EEG was recorded. At baseline, the children with AD/HD had elevated relative theta, less relative alpha and beta compared with controls. Baseline differences were found between the two medication groups, with the dexamphetamine group having greater EEG abnormalities than the methylphenidate group. The results indicate that good responders to methylphenidate and dexamphetamine have different EEG profiles when assessed before medication, and these differences may represent different underlying central nervous system deficits. The 2 medications were found to result in substantial normalization of the EEG, with no significant differences in EEG changes occurring between the 2 medications. This indicates that the degree of pretreatment EEG abnormality was the major factor contributing to the degree of normalization of the EEG. As good responders to the 2 medications appear to have different central nervous system abnormalities, it is recommended that stimulant medications be treated independently and not used interchangeably in research and treatment of AD/HD.

Neurofeedback Against Binge Eating: A Randomized Controlled Trial in a Female Subclinical Threshold Sample.

PubMed

Schmidt, Jennifer; Martin, Alexandra

2016-09-01

Brain-directed treatment techniques, such as neurofeedback, have recently been proposed as adjuncts in the treatment of eating disorders to improve therapeutic outcomes. In line with this recommendation, a cue exposure EEG-neurofeedback protocol was developed. The present study aimed at the evaluation of the specific efficacy of neurofeedback to reduce subjective binge eating in a female subthreshold sample. A total of 75 subjects were randomized to EEG-neurofeedback, mental imagery with a comparable treatment set-up or a waitlist group. At post-treatment, only EEG-neurofeedback led to a reduced frequency of binge eating (p = .015, g = 0.65). The effects remained stable to a 3-month follow-up. EEG-neurofeedback further showed particular beneficial effects on perceived stress and dietary self-efficacy. Differences in outcomes did not arise from divergent treatment expectations. Because EEG-neurofeedback showed a specific efficacy, it may be a promising brain-directed approach that should be tested as a treatment adjunct in clinical groups with binge eating. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association.

Combining early post-resuscitation EEG and HRV features improves the prognostic performance in cardiac arrest model of rats.

PubMed

Dai, Chenxi; Wang, Zhi; Wei, Liang; Chen, Gang; Chen, Bihua; Zuo, Feng; Li, Yongqin

2018-04-09

Early and reliable prediction of neurological outcome remains a challenge for comatose survivors of cardiac arrest (CA). The purpose of this study was to evaluate the predictive ability of EEG, heart rate variability (HRV) features and the combination of them for outcome prognostication in CA model of rats. Forty-eight male Sprague-Dawley rats were randomized into 6 groups (n=8 each) with different cause and duration of untreated arrest. Cardiopulmonary resuscitation was initiated after 5, 6 and 7min of ventricular fibrillation or 4, 6 and 8min of asphyxia. EEG and ECG were continuously recorded for 4h under normothermia after resuscitation. The relationships between features of early post-resuscitation EEG, HRV and 96-hour outcome were investigated. Prognostic performances were evaluated using the area under receiver operating characteristic curve (AUC). All of the animals were successfully resuscitated and 27 of them survived to 96h. Weighted-permutation entropy (WPE) and normalized high frequency (nHF) outperformed other EEG and HRV features for the prediction of survival. The AUC of WPE was markedly higher than that of nHF (0.892 vs. 0.759, p<0.001). The AUC was 0.954 when WPE and nHF were combined using a logistic regression model, which was significantly higher than the individual EEG (p=0.018) and HRV (p<0.001) features. Earlier post-resuscitation HRV provided prognostic information complementary to quantitative EEG in the CA model of rats. The combination of EEG and HRV features leads to improving performance of outcome prognostication compared to either EEG or HRV based features alone. Copyright © 2018. Published by Elsevier Inc.

EEG in children with spelling disabilities.

PubMed

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

1991-10-01

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

Early evaluation of the therapeutic effectiveness in children with epilepsy by quantitative EEG: a model of Mozart K.448 listening--a preliminary study.

PubMed

Lin, Lung-Chang; Ouyang, Chen-Sen; Chiang, Ching-Tai; Wu, Hui-Chuan; Yang, Rei-Cheng

2014-10-01

There are many treatments being developed for patients with epilepsy, including anti-epileptic drugs, ketogenic diet and vagus nerve stimulation. To date, there is a lack of valid methods to predict at an early stage the therapeutic effects on patients with epilepsy who receive one of these treatments. Our previous studies revealed that epileptiform discharges which were observed in patients with epilepsy were significantly decreased while listening to Mozart K.448. In this study, we attempted to develop a useful marker by utilizing a quantitative electroencephalogram (qEEG) method in analyzing the features of EEG to early evaluate the effect of the music on children with epilepsy, even without epileptiform discharges. EEG segments from 19 Taiwanese children who were selected from a large screen study of music effect (eight boys and 11 girls) diagnosed with epilepsy were analyzed. EEG examinations were performed in two parallel periods in each patient; before, and while listening to Mozart K.448's first movement (8 min 22s) and EEG data were compared by qEEG. EEG segments were classified into music effective/ineffective group. The term "effective" was defined as patient exposure to music resulting in over a 25% reduction in epileptiform discharges. On the contrary, the term "ineffective" was defined as patient exposure to music resulting in less than a 5% reduction in epileptiform discharges. There were four global feature descriptors selected for the music effective/ineffective classification. Two descriptors, DecorrTime_avg_AVG and DecorrTime_std_AVG, were related to the EEG feature "decorrelation" whereas the other two descriptors, RelPowGamma_avg_SNR and RelPowGamma_std_SNR, were related to "relative power of gamma." There were significantly higher RelPowGamma_std_SNR (0.190±0.133 vs. -0.026±0.119, p=0.0029), DecorrTime_std_AVG (0.005±0.004 vs. 0.0003±0.0016, p=0.0055), DecorrTime_avg_AVG (0.005±0.005 vs. -0.002±0.008, p=0.0179), and RelPowGamma_avg_SNR (0.176±0.219 vs. -0.078±0.244, p=0.0222) in the effective group than in the ineffective group. The precision rate of classification was 0.953. Using qEEG, we have developed a useful model for predicting therapeutic effectiveness of music in patients with epilepsy. Among the limited number of patients, the tool is of potential to predict the effectiveness in patients even without epileptiform discharges. It is worthwhile in the application of other therapeutic model. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

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.

Evaluation of the WIPP Project`s compliance with the EPA radiation protection standards for disposal of transuranic waste

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

Neill, R.H.; Chaturvedi, L.; Rucker, D.F.

The US Environmental Protection Agency`s (EPA) proposed rule to certify that the Waste Isolation Pilot Plant (WIPP) meets compliance with the long-term radiation protection standards for geologic repositories (40CFR191 Subparts B and C), is one of the most significant milestones to date for the WIPP project in particular, and for the nuclear waste issue in general. The Environmental Evaluation Group (EEG) has provided an independent technical oversight for the WIPP project since 1978, and is responsible for many improvements in the location, design, and testing of various aspects of the project, including participation in the development of the EPA standardsmore » since the early 1980s. The EEG reviewed the development of documentation for assessing the WIPP`s compliance by the Sandia National Laboratories following the 1985 promulgation by EPA, and provided many written and verbal comments on various aspects of this effort, culminating in the overall review of the 1992 performance assessment. For the US Department of Energy`s (DOE) compliance certification application (CCA), the EEG provided detailed comments on the draft CCA in March, 1996, and additional comments through unpublished letters in 1997 (included as Appendices 8.1 and 8.2 in this report). Since the October 30, 1997, publication of the EPA`s proposed rule to certify WIPP, the EEG gave presentations on important issues to the EPA on December 10, 1997, and sent a December 31, 1997 letter with attachments to clarify those issues (Appendix 8.3). The EEG has raised a number of questions that may have an impact on compliance. In spite of the best efforts by the EEG, the EPA reaction to reviews and suggestions has been slow and apparently driven by legal considerations. This report discusses in detail the questions that have been raised about containment requirements. Also discussed are assurance requirements, groundwater protection, individual protection, and an evaluation of EPA`s responses to EEG`s comments.« less

Electrophysiological correlates of aesthetic processing of webpages: a comparison of experts and laypersons

PubMed Central

Hösker, Thomas M.; Hirschfeld, Gerrit; Thielsch, Meinald T.

2017-01-01

We investigated whether design experts or laypersons evaluate webpages differently. Twenty participants, 10 experts and 10 laypersons, judged the aesthetic value of a webpage in an EEG-experiment. Screenshots of 150 webpages, judged as aesthetic or as unaesthetic by another 136 participants, served as stimulus material. Behaviorally, experts and laypersons evaluated unaesthetic webpages similarly, but they differed in their evaluation of aesthetic ones: experts evaluated aesthetic webpages as unaesthetic more often than laypersons did. The ERP-data show main effects of level of expertise and of aesthetic value only. There was no interaction of expertise and aesthetics. In a time-window of 110–130 ms after stimulus onset, aesthetic webpages elicited a more negative EEG-amplitude than unaesthetic webpages. In the same time window, experts had more negative EEG-amplitudes than laypersons. This patterning of results continued until a time window of 600–800 ms in which group and aesthetic differences diminished. An interaction of perceiver characteristics and object properties that several interactionist theories postulate was absent in the EEG-data. Experts seem to process the stimuli in a more thorough manner than laypersons. The early activation differences between aesthetic and unaesthetic webpages is in contrast with some theories of aesthetic processing and has not been reported before. PMID:28603676

Electrophysiological correlates of aesthetic processing of webpages: a comparison of experts and laypersons.

PubMed

Bölte, Jens; Hösker, Thomas M; Hirschfeld, Gerrit; Thielsch, Meinald T

2017-01-01

We investigated whether design experts or laypersons evaluate webpages differently. Twenty participants, 10 experts and 10 laypersons, judged the aesthetic value of a webpage in an EEG-experiment. Screenshots of 150 webpages, judged as aesthetic or as unaesthetic by another 136 participants, served as stimulus material. Behaviorally, experts and laypersons evaluated unaesthetic webpages similarly, but they differed in their evaluation of aesthetic ones: experts evaluated aesthetic webpages as unaesthetic more often than laypersons did. The ERP-data show main effects of level of expertise and of aesthetic value only. There was no interaction of expertise and aesthetics. In a time-window of 110-130 ms after stimulus onset, aesthetic webpages elicited a more negative EEG-amplitude than unaesthetic webpages. In the same time window, experts had more negative EEG-amplitudes than laypersons. This patterning of results continued until a time window of 600-800 ms in which group and aesthetic differences diminished. An interaction of perceiver characteristics and object properties that several interactionist theories postulate was absent in the EEG-data. Experts seem to process the stimuli in a more thorough manner than laypersons. The early activation differences between aesthetic and unaesthetic webpages is in contrast with some theories of aesthetic processing and has not been reported before.

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.

k-Nearest neighbour local linear prediction of scalp EEG activity during intermittent photic stimulation.

PubMed

Erla, Silvia; Faes, Luca; Tranquillini, Enzo; Orrico, Daniele; Nollo, Giandomenico

2011-05-01

The characterization of the EEG response to photic stimulation (PS) is an important issue with significant clinical relevance. This study aims to quantify and map the complexity of the EEG during PS, where complexity is measured as the degree of unpredictability resulting from local linear prediction. EEG activity was recorded with eyes closed (EC) and eyes open (EO) during resting and PS at 5, 10, and 15 Hz in a group of 30 healthy subjects and in a case-report of a patient suffering from cerebral ischemia. The mean squared prediction error (MSPE) resulting from k-nearest neighbour local linear prediction was calculated in each condition as an index of EEG unpredictability. The linear or nonlinear nature of the system underlying EEG activity was evaluated quantifying MSPE as a function of the neighbourhood size during local linear prediction, and by surrogate data analysis as well. Unpredictability maps were obtained for each subject interpolating MSPE values over a schematic head representation. Results on healthy subjects evidenced: (i) the prevalence of linear mechanisms in the generation of EEG dynamics, (ii) the lower predictability of EO EEG, (iii) the desynchronization of oscillatory mechanisms during PS leading to increased EEG complexity, (iv) the entrainment of alpha rhythm during EC obtained by 10 Hz PS, and (v) differences of EEG predictability among different scalp regions. Ischemic patient showed different MSPE values in healthy and damaged regions. The EEG predictability decreased moving from the early acute stage to a stage of partial recovery. These results suggest that nonlinear prediction can be a useful tool to characterize EEG dynamics during PS protocols, and may consequently constitute a complement of quantitative EEG analysis in clinical applications. Copyright © 2010 IPEM. Published by Elsevier Ltd. All rights reserved.

Melatonin use for neuroprotection in perinatal asphyxia: a randomized controlled pilot study.

PubMed

Aly, H; Elmahdy, H; El-Dib, M; Rowisha, M; Awny, M; El-Gohary, T; Elbatch, M; Hamisa, M; El-Mashad, A-R

2015-03-01

Melatonin has been shown to be neuroprotective in animal models. The objective of this study is to examine the effect of melatonin on clinical, biochemical, neurophysiological and radiological outcomes of neonates with hypoxic-ischemic encephalopathy (HIE). We conducted a prospective trial on 45 newborns, 30 with HIE and 15 healthy controls. HIE infants were randomized into: hypothermia group (N=15; received 72-h whole-body cooling) and melatonin/hypothermia group (N=15; received hypothermia and five daily enteral doses of melatonin 10 mg kg(-1)). Serum melatonin, plasma superoxide dismutase (SOD) and serum nitric oxide (NO) were measured at enrollment for all infants (N=45) and at 5 days for the HIE groups (N=30). In addition to electroencephalography (EEG) at enrollment, all surviving HIE infants were studied with brain magnetic resonance imaging (MRI) and repeated EEG at 2 weeks of life. Neurologic evaluations and Denver Developmental Screening Test II were performed at 6 months. Compared with healthy neonates, the two HIE groups had increased melatonin, SOD and NO. At enrollment, the two HIE groups did not differ in clinical, laboratory or EEG findings. At 5 days, the melatonin/hypothermia group had greater increase in melatonin (P<0.001) and decline in NO (P<0.001), but less decline in SOD (P=0.004). The melatonin/hypothermia group had fewer seizures on follow-up EEG and less white matter abnormalities on MRI. At 6 months, the melatonin/hypothermia group had improved survival without neurological or developmental abnormalities (P<0.001). Early administration of melatonin to asphyxiated term neonates is feasible and may ameliorate brain injury.

Evaluation of TV commercials using neurophysiological responses.

PubMed

Yang, Taeyang; Lee, Do-Young; Kwak, Youngshin; Choi, Jinsook; Kim, Chajoong; Kim, Sung-Phil

2015-04-24

In recent years, neuroscientific knowledge has been applied to marketing as a novel and efficient means to comprehend the cognitive and behavioral aspects of consumers. A number of studies have attempted to evaluate media contents, especially TV commercials using various neuroimaging techniques such as electroencephalography (EEG). Yet neurophysiological examination of detailed cognitive and affective responses in viewers is still required to provide practical information to marketers. Here, this study develops a method to analyze temporal patterns of EEG data and extract affective and cognitive indices such as happiness, surprise, and attention for TV commercial evaluation. Twenty participants participated in the study. We developed the neurophysiological indices for TV commercial evaluation using classification model. Specifically, these model-based indices were customized using individual EEG features. We used a video game for developing the index of attention and four video clips for developing indices of happiness and surprise. Statistical processes including one-way analyses of variance (ANOVA) and the cross validation scheme were used to select EEG features for each index. The EEG features were composed of the combinations of spectral power at selected channels from the cross validation for each individual. The Fisher's linear discriminant classifier (FLDA) was used to estimate each neurophysiological index during viewing four different TV commercials. Post hoc behavioral responses of preference, short-term memory, and recall were measured. Behavioral results showed significant differences for all preference, short-term memory rates, and recall rates between commercials, leading to a 'high-ranked' commercial group and a 'low-ranked' group (P < 0.05). Neural estimation of happiness results revealed a significant difference between the high-ranked and the low-ranked commercials in happiness index (P < 0.01). The order of rankings based on happiness and attention matched well with the order of behavioral response rankings. In the elapsed-time analysis of the highest-ranked commercial, we could point to visual and auditory semantic structures of the commercial that induced increases in the happiness index. Our results demonstrated that the neurophysiological indices developed in this study may provide a useful tool for evaluating TV commercials.

Oxytocin reduces amygdala activity, increases social interactions and reduces anxiety-like behavior irrespective of NMDAR antagonism

PubMed Central

Sobota, Rosanna; Mihara, Takuma; Forrest, Alexandra; Featherstone, Robert E.; Siegel, Steven J.

2015-01-01

Standard dopamine therapies for schizophrenia are not efficacious for negative symptoms of the disease, including asociality. This reduced social behavior may be due to glutamatergic dysfunction within the amygdala leading to increased fear and social anxiety. Several studies have demonstrated the pro-social effects of oxytocin in schizophrenia patients. Therefore, this study evaluates the effect of sub-chronic oxytocin on electroencephalographic (EEG) activity in amygdala of mice during performance of the three chamber social choice and open field tests following acute ketamine as a model of glutamatergic dysfunction. Oxytocin did not restore social deficits introduced by ketamine, but did significantly increase sociality in comparison to the control group. Ketamine had no effect on time spent in the center during the open field trials, while oxytocin increased overall center time across all groups, suggesting a reduction in anxiety. Amygdala activity was consistent across all drug groups during social and nonsocial behavioral trials. However, oxytocin reduced overall amygdala EEG power during the two behavioral tasks. Alternatively, ketamine did not significantly affect EEG power throughout the tasks. Decreased EEG power in the amygdala, as caused by oxytocin, may be related to both reduced anxiety and increased social behaviors. Data suggest that separate pro-social and social anxiety pathways may mediate social preference. PMID:26214213

Electroencephalographic and electromyographic changes during the use of detomidine and detomidine-butorphanol combination in standing horses.

PubMed

Kruluc, P; Nemec, Alenka

2006-03-01

Clinically, the use of detomidine and butorphanol is suitable for sedation and deepening of analgosedation. The aim of our study was to establish the influence of detomidine used alone and a butorphanol-detomidine combination on brain activity and to evaluate and compare brain responses (using electroencephalography, EEG) by recording SEF90 (spectral edge frequency 90%), individual brain wave fractions (beta, alpha, theta and delta) and electromyographic (EMG) changes in the left temporal muscle in standing horses. Ten clinically healthy cold-blooded horses were divided into two groups of five animals each. Group I received detomidine and Group II received detomidine followed by butorphanol 10 min later. SEF90, individual brain wave fractions and EMG were recorded with a pEEG (processed EEG) monitor using computerised processed electroencephalography and electromyography. The present study found that detomidine alone and the detomidine-butorphanol combination significantly reduced SEF90 and EMG, and they caused changes in individual brain wave fractions during sedation and particularly during analgosedation. The EMG results showed that the detomidine-butorphanol combination provided greater and longer muscle relaxation. Our EEG and EMG results confirmed that the detomidine-butorphanol combination is safer and more appropriate for painless and non-painless procedures on standing horses compared to detomidine alone.

Identification of scalp EEG circadian variation using a novel correlation sum measure

NASA Astrophysics Data System (ADS)

Shahidi Zandi, Ali; Boudreau, Philippe; Boivin, Diane B.; Dumont, Guy A.

2015-10-01

Objective. In this paper, we propose a novel method to determine the circadian variation of scalp electroencephalogram (EEG) in both individual and group levels using a correlation sum measure, quantifying self-similarity of the EEG relative energy across waking epochs. Approach. We analysed EEG recordings from central-parietal and occipito-parietal montages in nine healthy subjects undergoing a 72 h ultradian sleep-wake cycle protocol. Each waking epoch (˜1 s) of every nap opportunity was decomposed using the wavelet packet transform, and the relative energy for that epoch was calculated in the desired frequency band using the corresponding wavelet coefficients. Then, the resulting set of energy values was resampled randomly to generate different subsets with equal number of elements. The correlation sum of each subset was then calculated over a range of distance thresholds, and the average over all subsets was computed. This average value was finally scaled for each nap opportunity and considered as a new circadian measure. Main results. According to the evaluation results, a clear circadian rhythm was identified in some EEG frequency ranges, particularly in 4-8 Hz and 10-12 Hz. The correlation sum measure not only was able to disclose the circadian rhythm on the group data but also revealed significant circadian variations in most individual cases, as opposed to previous studies only reporting the circadian rhythms on a population of subjects. Compared to a naive measure based on the EEG absolute energy in the frequency band of interest, the proposed measure showed a clear superiority using both individual and group data. Results also suggested that the acrophase (i.e., the peak) of the circadian rhythm in 10-12 Hz occurs close to the core body temperature minimum. Significance. These results confirm the potential usefulness of the proposed EEG-based measure as a non-invasive circadian marker.

EEG power during waking and NREM sleep in primary insomnia.

PubMed

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

2013-10-15

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

Quantitative EEG in Children and Adults With Attention Deficit Hyperactivity Disorder: Comparison of Absolute and Relative Power Spectra and Theta/Beta Ratio.

PubMed

Markovska-Simoska, Silvana; Pop-Jordanova, Nada

2017-01-01

In recent decades, resting state electroencephalographic (EEG) measures have been widely used to document underlying neurophysiological dysfunction in attention deficit hyperactivity disorder (ADHD). Although most EEG studies focus on children, there is a growing interest in adults with ADHD too. The aim of this study was to objectively assess and compare the absolute and relative EEG power as well as the theta/beta ratio in children and adults with ADHD. The evaluated sample comprised 30 male children and 30 male adults with ADHD diagnosed according to DSM-IV criteria. They were compared with 30 boys and 30 male adults matched by age. The mean age (±SD) of the children's group was 9 (±2.44) years and the adult group 35.8 (±8.65) years. EEG was recorded during an eyes-open condition. Spectral analysis of absolute (μV 2 ) and relative power (%) was carried out for 4 frequency bands: delta (2-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), and beta (13-21 Hz). The findings obtained for ADHD children are increased absolute power of slow waves (theta and delta), whereas adults exhibited no differences compared with normal subjects. For the relative power spectra there were no differences between the ADHD and control groups. Across groups, the children showed greater relative power than the adults in the delta and theta bands, but for the higher frequency bands (alpha and beta) the adults showed more relative power than children. Only ADHD children showed greater theta/beta ratio compared to the normal group. Classification analysis showed that ADHD children could be differentiated from the control group by the absolute theta values and theta/beta ratio at Cz, but this was not the case with ADHD adults. The question that should be further explored is if these differences are mainly due to maturation processes or if there is a core difference in cortical arousal between ADHD children and adults. © EEG and Clinical Neuroscience Society (ECNS) 2016.

The SafeBoosC II randomized trial: treatment guided by near-infrared spectroscopy reduces cerebral hypoxia without changing early biomarkers of brain injury

PubMed Central

Plomgaard, Anne M.; van Oeveren, Wim; Petersen, Tue H.; Alderliesten, Thomas; Austin, Topun; van Bel, Frank; Benders, Manon; Claris, Olivier; Dempsey, Eugene; Franz, Axel; Fumagalli, Monica; Gluud, Christian; Hagmann, Cornelia; Hyttel-Sorensen, Simon; Lemmers, Petra; Pellicer, Adelina; Pichler, Gerhard; Winkel, Per; Greisen, Gorm

2016-01-01

Background: The SafeBoosC phase II multicentre randomized clinical trial investigated the benefits and harms of monitoring cerebral oxygenation by near-infrared spectroscopy (NIRS) combined with an evidence-based treatment guideline vs. no NIRS data and treatment as usual in the control group during the first 72 h of life. The trial demonstrated a significant reduction in the burden of cerebral hypoxia in the experimental group. We now report the blindly assessed and analyzed treatment effects on electroencephalographic (EEG) outcomes (burst rate and spectral edge frequency 95% (SEF95)) and blood biomarkers of brain injury (S100β, brain fatty acid-binding protein, and neuroketal). Methods: One hundred and sixty-six extremely preterm infants were randomized to either experimental or control group. EEG was recorded at 64 h of age and blood samples were collected at 6 and 64 h of age. Results: One hundred and thirty-three EEGs were evaluated. The two groups did not differ regarding burst rates (experimental 7.2 vs. control 7.7 burst/min) or SEF95 (experimental 18.1 vs. control 18.0 Hz). The two groups did not differ regarding blood S100β, brain fatty acid-binding protein, and neuroketal concentrations at 6 and 64 h (n = 123 participants). Conclusion: Treatment guided by NIRS reduced the cerebral burden of hypoxia without affecting EEG or the selected blood biomarkers. PMID:26679155

Phenobarbitone, neonatal seizures, and video-EEG

PubMed Central

Boylan, G; Rennie, J; Pressler, R; Wilson, G; Morton, M; Binnie, C

2002-01-01

Aims: To evaluate the effectiveness of phenobarbitone as an anticonvulsant in neonates. Methods: An observational study using video-EEG telemetry. Video-EEG was obtained before treatment was started, for an hour after treatment was given, two hours after treatment was given, and again between 12 and 24 hours after treatment was given. Patients were recruited from all babies who required phenobarbitone (20–40 mg/kg intravenously over 20 minutes) for suspected clinical seizures and had EEG monitoring one hour before and up to 24 hours after the initial dose. An EEG seizure discharge was defined as a sudden repetitive stereotyped discharge lasting for at least 10 seconds. Neonatal status epilepticus was defined as continuous seizure activity for at least 30 minutes. Seizures were categorised as EEG seizure discharges only (electrographic), or as EEG seizure discharges with accompanying clinical manifestations (electroclinical). Surviving babies were assessed at one year using the Griffiths neurodevelopmental score. Results: Fourteen babies were studied. Four responded to phenobarbitone; these had normal or moderately abnormal EEG background abnormalities and outcome was good. In the other 10 babies electrographic seizures increased after treatment, whereas electroclinical seizures reduced. Three babies were treated with second line anticonvulsants, of whom two responded. One of these had a normal neurodevelopmental score at one year, but the outcome for the remainder of the whole group was poor. Conclusion: Phenobarbitone is often ineffective as a first line anticonvulsant in neonates with seizures in whom the background EEG is significantly abnormal. PMID:11978746

A Novel EEG Based Spectral Analysis of Persistent Brain Function Alteration in Athletes with Concussion History.

PubMed

Munia, Tamanna T K; Haider, Ali; Schneider, Charles; Romanick, Mark; Fazel-Rezai, Reza

2017-12-08

The neurocognitive sequelae of a sport-related concussion and its management are poorly defined. Detecting deficits are vital in making a decision about the treatment plan as it can persist one year or more following a brain injury. The reliability of traditional cognitive assessment tools is debatable, and thus attention has turned to assessments based on electroencephalogram (EEG) to evaluate subtle post-concussive alterations. In this study, we calculated neurocognitive deficits combining EEG analysis with three standard post-concussive assessment tools. Data were collected for all testing modalities from 21 adolescent athletes (seven concussive and fourteen healthy) in three different trials. For EEG assessment, along with linear frequency-based features, we introduced a set of time-frequency (Hjorth Parameters) and nonlinear features (approximate entropy and Hurst exponent) for the first time to explore post-concussive deficits. Besides traditional frequency-band analysis, we also presented a new individual frequency-based approach for EEG assessment. While EEG analysis exhibited significant discrepancies between the groups, none of the cognitive assessment resulted in significant deficits. Therefore, the evidence from the study highlights that our proposed EEG analysis and markers are more efficient at deciphering post-concussion residual neurocognitive deficits and thus has a potential clinical utility of proper concussion assessment and management.

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

PubMed

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

2008-12-01

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

How Long Should Routine EEG Be Recorded to Get Relevant Information?

PubMed

Doudoux, Hannah; Skaare, Kristina; Geay, Thomas; Kahane, Philippe; Bosson, Jean L; Sabourdy, Cécile; Vercueil, Laurent

2017-03-01

The optimal duration of routine EEG (rEEG) has not been determined on a clinical basis. This study aims to determine the time required to obtain relevant information during rEEG with respect to the clinical request. All rEEGs performed over 3 months in unselected patients older than 14 years in an academic hospital were analyzed retrospectively. The latency required to obtain relevant information was determined for each rEEG by 2 independent readers blinded to the clinical data. EEG final diagnoses and latencies were analyzed with respect to the main clinical requests: subacute cognitive impairment, spells, transient focal neurologic manifestation or patients referred by epileptologists. From 430 rEEGs performed in the targeted period, 364 were analyzed: 92% of the pathological rEEGs were provided within the first 10 minutes of recording. Slowing background activity was diagnosed from the beginning, whereas interictal epileptiform discharges were recorded over time. Moreover, the time elapsed to demonstrate a pattern differed significantly in the clinical groups: in patients with subacute cognitive impairment, EEG abnormalities appeared within the first 10 minutes, whereas in the other groups, data could be provided over time. Patients with subacute cognitive impairment differed from those in the other groups significantly in the elapsed time required to obtain relevant information during rEEG, suggesting that 10-minute EEG recordings could be sufficient, arguing in favor of individualized rEEG. However, this conclusion does not apply to intensive care unit patients.

Clozapine-induced EEG abnormalities and clinical response to clozapine.

PubMed

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

1995-01-01

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

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.

Underlying neurological dysfunction in children with language, speech or learning difficulties and a verbal IQ--performance IQ discrepancy.

PubMed

Meulemans, J; Goeleven, A; Zink, I; Loyez, L; Lagae, L; Debruyne, F

2012-01-01

We investigated the relationship between possible underlying neurological dysfunction and a significant discrepancy between verbal IQ/performance IQ (VIQ-PIQ) in children with language, speech or learning difficulties. In a retrospective study, we analysed data obtained from intelligence testing and neurological evaluation in 49 children with a significant VIQ-PIQ discrepancy (> or = 25 points) who were referred because of language, speech or learning difficulties to the Multidisciplinary University Centre for Logopedics and Audiology (MUCLA) of the University Hospitals of Leuven, Belgium. The group of children broke down into a group of 35 children with PIQ > VIQ and a group of 14 children with VIQ > PIQ. In the first group, neurological data were present for 24 children. The neurological history and clinical neurological examination were normal in all cases. Brain MRI was performed in 15 cases and proved to be normal in all children. Brain activity was assessed with long-term video EEG monitoring in ten children. In two children, the EEG results were abnormal: there was an epileptic focus in one child and a manifest alteration in the EEG typical of Landau-Kleffner syndrome in the other. In the second group of 14 children whose VIQ was higher than the PIQ, neurological data were available for ten children. Neurological history and clinical neurological examination were normal in all cases. Brain MRI was performed in five cases and was normal in all children. EEG monitoring was performed in one child. This revealed benign childhood epilepsy with centrotemporal spikes. In a small number of children (9%) with speech, language and learning difficulties and a discrepancy between VIQ and PIQ, an underlying neurological abnormality is present. We recommend referring children with a significant VIQ-PIQ mismatch to a paediatric neurologist. As an epileptic disorder seems to be the most common underlying neurological pathology in this specific group of children, EEG monitoring should be recommended in these children. Neuro-imaging should only be used in selected patients.

Pilot study of EEG in neonates born to mothers with gestational diabetes mellitus.

PubMed

Léveillé-, Pauline; Hamel, Mathieu; Ardilouze, Jean-Luc; Pasquier, Jean-Charles; Deacon, Charles; Whittingstall, Kevin; Plourde, Mélanie

2018-05-01

The goal was to evaluate whether there was neurodevelopmental deficits in newborns born to mothers with gestational diabetes mellitus (GDM) compared to control newborns born to healthy mothers. Forty-six pregnant women (21 controls and 25 GDM) were recruited. Electroencephalogram (EEG) was recorded in the newborns within 48 h after birth. The EEG signal was quantitatively analyzed using power spectral density (PSD); coherence between hemispheres was calculated in paired channels of frontal, temporal, central and occipital regions. The left centro-occipital PSD in control newborns was 12% higher than in GDM newborns (p = 0.036) but was not significant after adjustment for gestational age. While coherence was higher in the frontal regions compared to the occipital regions (p < 0.001), there was no difference between the groups for the fronto-temporal, frontal-central, centro-occipital and tempo-occipital regions. Our results support that EEG differences between groups were mainly modified by gestational age and less by GDM status of the mothers. However, there is a need to confirm this result with a higher number of mother-newborns. Quantitative EEG in GDM newborns within 48 h after birth is feasible. This study emphasizes the importance of controlling blood glucose during GDM to protect infant brain development. Copyright © 2018 ISDN. Published by Elsevier Ltd. All rights reserved.

Evaluation of artifact-corrected electroencephalographic (EEG) training: a pilot study.

PubMed

La Marca, Jeffry P; Cruz, Daniel; Fandino, Jennifer; Cacciaguerra, Fabiana R; Fresco, Joseph J; Guerra, Austin T

2018-07-01

This double-blind study examined the effect of electromyographical (EMG) artifacts, which contaminate electroencephalographical (EEG) signals, by comparing artifact-corrected (AC) and non-artifact-corrected (NAC) neurofeedback (NF) training procedures. 14 unmedicated college students were randomly assigned to two groups: AC (n = 7) or NAC (n = 7). Both groups received 12 sessions of NF and were trained using identical NF treatment protocols to reduce their theta/beta power ratios (TBPR). Outcomes on a continuous performance test revealed that the AC group had statistically significant increases across measures of auditory and visual attention. The NAC group showed smaller gains that only reached statistical significance on measures of visual attention. Only the AC group reduced their TBPR, the NAC group did not. AC NF appears to play an important role during training that leads to improvements in both auditory and visual attention. Additional research is required to confirm the results of this study.

Putative EEG measures of social anxiety: Comparing frontal alpha asymmetry and delta-beta cross-frequency correlation.

PubMed

Harrewijn, A; Van der Molen, M J W; Westenberg, P M

2016-12-01

The goal of the present study was to examine whether frontal alpha asymmetry and delta-beta cross-frequency correlation during resting state, anticipation, and recovery are electroencephalographic (EEG) measures of social anxiety. For the first time, we jointly examined frontal alpha asymmetry and delta-beta correlation during resting state and during a social performance task in high (HSA) versus low (LSA) socially anxious females. Participants performed a social performance task in which they first watched and evaluated a video of a peer, and then prepared their own speech. They believed that their speech would be videotaped and evaluated by a peer. We found that HSA participants showed significant negative delta-beta correlation as compared to LSA participants during both anticipation of and recovery from the stressful social situation. This negative delta-beta correlation might reflect increased activity in subcortical brain regions and decreased activity in cortical brain regions. As we hypothesized, no group differences in delta-beta correlation were found during the resting state. This could indicate that a certain level of stress is needed to find EEG measures of social anxiety. As for frontal alpha asymmetry, we did not find any group differences. The present frontal alpha asymmetry results are discussed in relation to the evident inconsistencies in the frontal alpha asymmetry literature. Together, our results suggest that delta-beta correlation is a putative EEG measure of social anxiety.

Education research: evaluating the use of podcasting for residents during EEG instruction: a pilot study.

PubMed

Bensalem-Owen, Meriem; Chau, Destiny F; Sardam, Sean C; Fahy, Brenda G

2011-08-23

Educational methods for residents are shifting toward greater learner independence aided by technological advances. A Web-based program using a podcast was created for resident EEG instruction, replacing conventional didactics. The EEG curriculum also consisted of EEG interpretations under the tutelage of a neurophysiologist. This pilot study aimed to objectively evaluate the effectiveness of the podcast as a new teaching tool. A podcast for resident EEG instruction was implemented on the Web, replacing the traditional lecture. After Institutional Review Board approval, consent was obtained from the participating residents. Using 25-question evaluation tools, participants were assessed at baseline before any EEG instruction, and reassessed after podcasting and after 10 clinical EEG exposures. Each 25-item evaluation tool contained tracings used for clinical EEG interpretations. Scores after podcast training were also compared to scores after traditional didactic training from a previous study among anesthesiology trainees. Ten anesthesiology residents completed the study. The mean scores with standard deviations are 9.50 ± 2.92 at baseline, 13.40 ± 3.31 (p = 0.034) after the podcast, and 16.20 ± 1.87 (p = 0.019) after interpreting 10 EEGs. No differences were noted between the mean educational tool scores for those who underwent podcasting training compared to those who had undergone traditional didactic training. In this pilot study, podcast training was as effective as the prior conventional lecture in meeting the curricular goals of increasing EEG knowledge after 10 EEG interpretations as measured by assessment tools.

[Wavelet packet extraction and entropy analysis of telemetry EEG from the prelimbic cortex of medial prefrontal cortex in morphine-induced CPP rats].

PubMed

Bai, Yu; Bai, Jia-Ming; Li, Jing; Li, Min; Yu, Ran; Pan, Qun-Wan

2014-12-25

The purpose of the present study is to analyze the relationship between the telemetry electroencephalogram (EEG) changes of the prelimbic (PL) cortex and the drug-seeking behavior of morphine-induced conditioned place preference (CPP) rats by using the wavelet packet extraction and entropy measurement. The recording electrode was stereotactically implanted into the PL cortex of rats. The animals were then divided randomly into operation-only control and morphine-induced CPP groups, respectively. A CPP video system in combination with an EEG wireless telemetry device was used for recording EEG of PL cortex when the rats shuttled between black-white or white-black chambers. The telemetry recorded EEGs were analyzed by wavelet packet extraction, Welch power spectrum estimate, normalized amplitude and Shannon entropy algorithm. The results showed that, compared with operation-only control group, the left PL cortex's EEG of morphine-induced CPP group during black-white chamber shuttling exhibited the following changes: (1) the amplitude of average EEG for each frequency bands extracted by wavelet packet was reduced; (2) the Welch power intensity was increased significantly in 10-50 Hz EEG band (P < 0.01 or P < 0.05); (3) Shannon entropy was increased in β, γ₁, and γ₂waves of the EEG (P < 0.01 or P < 0.05); and (4) the average information entropy was reduced (P < 0.01). The results suggest that above mentioned EEG changes in morphine-induced CPP group rat may be related to animals' drug-seeking motivation and behavior launching.

Cerebrospinal Fluid Levels of Monoamine Metabolites in the Epileptic Baboon

PubMed Central

Szabó, C. Ákos; Patel, Mayuri; Uteshev, Victor V.

2016-01-01

The baboon represents a natural model for genetic generalized epilepsy and sudden unexpected death in epilepsy (SUDEP). In this retrospective study, cerebrospinal fluid (CSF) monoamine metabolites and scalp electroencephalography (EEG) were evaluated in 263 baboons of a pedigreed colony. CSF monoamine abnormalities have been linked to reduced seizure thresholds, behavioral abnormalities and SUDEP in various animal models of epilepsy. The levels of 3-hydroxy-4-methoxyphenylglycol, 5-hydroxyindolacetic acid and homovanillic acid in CSF samples drawn from the cisterna magna were analyzed using high-performance liquid chromatography. These levels were compared between baboons with seizures (SZ), craniofacial trauma (CFT) and asymptomatic, control (CTL) baboons, between baboons with abnormal and normal EEG studies. We hypothesized that the CSF levels of major monoaminergic metabolites (i.e., dopamine, serotonin and norepinephrine) associate with the baboons’ electroclinical status and thus can be used as clinical biomarkers applicable to seizures/epilepsy. However, despite apparent differences in metabolite levels between the groups, usually lower in SZ and CFT baboons and in baboons with abnormal EEG studies, we did not find any statistically significant differences using a logistic regression analysis. Significant correlations between the metabolite levels, especially between 5-HIAA and HVA, were preserved in all electroclinical groups. While we were not able to demonstrate significant differences in monoamine metabolites in relation to seizures or EEG markers of epilepsy, we cannot exclude the monoaminergic system as a potential source of pathogenesis in epilepsy and SUDEP. A prospective study evaluating serial CSF monoamine levels in baboons with recently witnessed seizures, and evaluation of abnormal expression and function of monoaminergic receptors and transporters within epilepsy-related brain regions, may impact the electroclinical status. PMID:26924854

Intelligence and EEG current density using low-resolution electromagnetic tomography (LORETA).

PubMed

Thatcher, R W; North, D; Biver, C

2007-02-01

The purpose of this study was to compare EEG current source densities in high IQ subjects vs. low IQ subjects. Resting eyes closed EEG was recorded from 19 scalp locations with a linked ears reference from 442 subjects ages 5 to 52 years. The Wechsler Intelligence Test was administered and subjects were divided into low IQ (< or =90), middle IQ (>90 to <120) and high IQ (> or =120) groups. Low-resolution electromagnetic tomographic current densities (LORETA) from 2,394 cortical gray matter voxels were computed from 1-30 Hz based on each subject's EEG. Differences in current densities using t tests, multivariate analyses of covariance, and regression analyses were used to evaluate the relationships between IQ and current density in Brodmann area groupings of cortical gray matter voxels. Frontal, temporal, parietal, and occipital regions of interest (ROIs) consistently exhibited a direct relationship between LORETA current density and IQ. Maximal t test differences were present at 4 Hz, 9 Hz, 13 Hz, 18 Hz, and 30 Hz with different anatomical regions showing different maxima. Linear regression fits from low to high IQ groups were statistically significant (P < 0.0001). Intelligence is directly related to a general level of arousal and to the synchrony of neural populations driven by thalamo-cortical resonances. A traveling frame model of sequential microstates is hypothesized to explain the results.

EEG entropy measures indicate decrease of cortical information processing in Disorders of Consciousness.

PubMed

Thul, Alexander; Lechinger, Julia; Donis, Johann; Michitsch, Gabriele; Pichler, Gerald; Kochs, Eberhard F; Jordan, Denis; Ilg, Rüdiger; Schabus, Manuel

2016-02-01

Clinical assessments that rely on behavioral responses to differentiate Disorders of Consciousness are at times inapt because of some patients' motor disabilities. To objectify patients' conditions of reduced consciousness the present study evaluated the use of electroencephalography to measure residual brain activity. We analyzed entropy values of 18 scalp EEG channels of 15 severely brain-damaged patients with clinically diagnosed Minimally-Conscious-State (MCS) or Unresponsive-Wakefulness-Syndrome (UWS) and compared the results to a sample of 24 control subjects. Permutation entropy (PeEn) and symbolic transfer entropy (STEn), reflecting information processes in the EEG, were calculated for all subjects. Participants were tested on a modified active own-name paradigm to identify correlates of active instruction following. PeEn showed reduced local information content in the EEG in patients, that was most pronounced in UWS. STEn analysis revealed altered directed information flow in the EEG of patients, indicating impaired feed-backward connectivity. Responses to auditory stimulation yielded differences in entropy measures, indicating reduced information processing in MCS and UWS. Local EEG information content and information flow are affected in Disorders of Consciousness. This suggests local cortical information capacity and feedback information transfer as neural correlates of consciousness. The utilized EEG entropy analyses were able to relate to patient groups with different Disorders of Consciousness. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

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

PubMed

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

2016-05-01

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

Incorporating an ERP Project into Undergraduate Instruction

PubMed Central

Nyhus, Erika; Curtis, Nancy

2016-01-01

Electroencephalogram (EEG) is a relatively non-invasive, simple technique, and recent advances in open source analysis tools make it feasible to implement EEG as a component in undergraduate neuroscience curriculum. We have successfully led students to design novel experiments, record EEG data, and analyze event-related potentials (ERPs) during a one-semester laboratory course for undergraduates in cognitive neuroscience. First, students learned how to set up an EEG recording and completed an analysis tutorial. Students then learned how to set up a novel EEG experiment; briefly, they formed groups of four and designed an EEG experiment on a topic of their choice. Over the course of two weeks students collected behavioral and EEG data. Each group then analyzed their behavioral and ERP data and presented their results both as a presentation and as a final paper. Upon completion of the group project students reported a deeper understanding of cognitive neuroscience methods and a greater appreciation for the strengths and weaknesses of the EEG technique. Although recent advances in open source software made this project possible, it also required access to EEG recording equipment and proprietary software. Future efforts should be directed at making publicly available datasets to learn ERP analysis techniques and making publicly available EEG recording and analysis software to increase the accessibility of hands-on research experience in undergraduate cognitive neuroscience laboratory courses. PMID:27385925

EEG study of the mirror neuron system in children with high functioning autism.

PubMed

Raymaekers, Ruth; Wiersema, Jan Roelf; Roeyers, Herbert

2009-12-22

Individuals with Autism Spectrum Disorder (ASD) are characterised by an impaired imitation, thought to be critical for early affective, social and communicative development. One neurological system proposed to underlie this function is the mirror neuron system (MNS) and previous research has suggested a dysfunctional MNS in ASD. The EEG mu frequency, more precisely the reduction of the mu power, is considered to be an index for mirror neuron functioning. In this work, EEG registrations are used to evaluate the mirror neuron functioning of twenty children with high functioning autism (HFA) between 8 and 13 years. Their mu suppression to self-executed and observed movement is compared to typically developing peers and related to age, intelligence and symptom severity. Both groups show significant mu suppression to both self and observed hand movements. No group differences are found in either condition. These results do not support the hypothesis that HFA is associated with a dysfunctional MNS. The discrepancy with previous research is discussed in light of the heterogeneity of the ASD population.

Repeated transcranial direct current stimulation in prolonged disorders of consciousness: A double-blind cross-over study.

PubMed

Estraneo, Anna; Pascarella, Angelo; Moretta, Pasquale; Masotta, Orsola; Fiorenza, Salvatore; Chirico, Grazia; Crispino, Emanuela; Loreto, Vincenzo; Trojano, Luigi

2017-04-15

To evaluate effects of 5 sessions of transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex in patients with prolonged disorders of consciousness (DOC). Seven patients in vegetative state (VS) and 6 in minimally conscious state (MCS), at ≥3months after brain injury, were randomized into two groups: group 1 received one week of active tDCS and 1week of sham stimulation, separated by 1 resting week; group 2 received active and sham stimulation in reverse order. We performed clinical and EEG evaluations before and after the first stimulation session, two hours after the last weekly stimulation, twice during the resting week, and during a 3-month follow-up. We observed small changes of patients' conditions after the first tDCS session and immediately after the 5 active stimulations. Substantial clinical and EEG changes were observed in 5/13 patients (3 in MCS and 2 in VS) starting after entire (active and sham) stimulation protocol and further progressing during the next months. No baseline features distinguished patients who improved from patients who did not improve. Repeated tDCS did not exert remarkable short-term clinical and EEG effects in patients with prolonged DOC. Further studies should ascertain whether tDCS might promote clinical recovery in the long-term period. Copyright © 2017 Elsevier B.V. All rights reserved.

Traumatic Brain Injury Detection Using Electrophysiological Methods

PubMed Central

Rapp, Paul E.; Keyser, David O.; Albano, Alfonso; Hernandez, Rene; Gibson, Douglas B.; Zambon, Robert A.; Hairston, W. David; Hughes, John D.; Krystal, Andrew; Nichols, Andrew S.

2015-01-01

Measuring neuronal activity with electrophysiological methods may be useful in detecting neurological dysfunctions, such as mild traumatic brain injury (mTBI). This approach may be particularly valuable for rapid detection in at-risk populations including military service members and athletes. Electrophysiological methods, such as quantitative electroencephalography (qEEG) and recording event-related potentials (ERPs) may be promising; however, the field is nascent and significant controversy exists on the efficacy and accuracy of the approaches as diagnostic tools. For example, the specific measures derived from an electroencephalogram (EEG) that are most suitable as markers of dysfunction have not been clearly established. A study was conducted to summarize and evaluate the statistical rigor of evidence on the overall utility of qEEG as an mTBI detection tool. The analysis evaluated qEEG measures/parameters that may be most suitable as fieldable diagnostic tools, identified other types of EEG measures and analysis methods of promise, recommended specific measures and analysis methods for further development as mTBI detection tools, identified research gaps in the field, and recommended future research and development thrust areas. The qEEG study group formed the following conclusions: (1) Individual qEEG measures provide limited diagnostic utility for mTBI. However, many measures can be important features of qEEG discriminant functions, which do show significant promise as mTBI detection tools. (2) ERPs offer utility in mTBI detection. In fact, evidence indicates that ERPs can identify abnormalities in cases where EEGs alone are non-disclosing. (3) The standard mathematical procedures used in the characterization of mTBI EEGs should be expanded to incorporate newer methods of analysis including non-linear dynamical analysis, complexity measures, analysis of causal interactions, graph theory, and information dynamics. (4) Reports of high specificity in qEEG evaluations of TBI must be interpreted with care. High specificities have been reported in carefully constructed clinical studies in which healthy controls were compared against a carefully selected TBI population. The published literature indicates, however, that similar abnormalities in qEEG measures are observed in other neuropsychiatric disorders. While it may be possible to distinguish a clinical patient from a healthy control participant with this technology, these measures are unlikely to discriminate between, for example, major depressive disorder, bipolar disorder, or TBI. The specificities observed in these clinical studies may well be lost in real world clinical practice. (5) The absence of specificity does not preclude clinical utility. The possibility of use as a longitudinal measure of treatment response remains. However, efficacy as a longitudinal clinical measure does require acceptable test–retest reliability. To date, very few test–retest reliability studies have been published with qEEG data obtained from TBI patients or from healthy controls. This is a particular concern because high variability is a known characteristic of the injured central nervous system. PMID:25698950

Traumatic brain injury detection using electrophysiological methods.

PubMed

Rapp, Paul E; Keyser, David O; Albano, Alfonso; Hernandez, Rene; Gibson, Douglas B; Zambon, Robert A; Hairston, W David; Hughes, John D; Krystal, Andrew; Nichols, Andrew S

2015-01-01

Measuring neuronal activity with electrophysiological methods may be useful in detecting neurological dysfunctions, such as mild traumatic brain injury (mTBI). This approach may be particularly valuable for rapid detection in at-risk populations including military service members and athletes. Electrophysiological methods, such as quantitative electroencephalography (qEEG) and recording event-related potentials (ERPs) may be promising; however, the field is nascent and significant controversy exists on the efficacy and accuracy of the approaches as diagnostic tools. For example, the specific measures derived from an electroencephalogram (EEG) that are most suitable as markers of dysfunction have not been clearly established. A study was conducted to summarize and evaluate the statistical rigor of evidence on the overall utility of qEEG as an mTBI detection tool. The analysis evaluated qEEG measures/parameters that may be most suitable as fieldable diagnostic tools, identified other types of EEG measures and analysis methods of promise, recommended specific measures and analysis methods for further development as mTBI detection tools, identified research gaps in the field, and recommended future research and development thrust areas. The qEEG study group formed the following conclusions: (1) Individual qEEG measures provide limited diagnostic utility for mTBI. However, many measures can be important features of qEEG discriminant functions, which do show significant promise as mTBI detection tools. (2) ERPs offer utility in mTBI detection. In fact, evidence indicates that ERPs can identify abnormalities in cases where EEGs alone are non-disclosing. (3) The standard mathematical procedures used in the characterization of mTBI EEGs should be expanded to incorporate newer methods of analysis including non-linear dynamical analysis, complexity measures, analysis of causal interactions, graph theory, and information dynamics. (4) Reports of high specificity in qEEG evaluations of TBI must be interpreted with care. High specificities have been reported in carefully constructed clinical studies in which healthy controls were compared against a carefully selected TBI population. The published literature indicates, however, that similar abnormalities in qEEG measures are observed in other neuropsychiatric disorders. While it may be possible to distinguish a clinical patient from a healthy control participant with this technology, these measures are unlikely to discriminate between, for example, major depressive disorder, bipolar disorder, or TBI. The specificities observed in these clinical studies may well be lost in real world clinical practice. (5) The absence of specificity does not preclude clinical utility. The possibility of use as a longitudinal measure of treatment response remains. However, efficacy as a longitudinal clinical measure does require acceptable test-retest reliability. To date, very few test-retest reliability studies have been published with qEEG data obtained from TBI patients or from healthy controls. This is a particular concern because high variability is a known characteristic of the injured central nervous system.

Evaluation of driver fatigue on two channels of EEG data.

PubMed

Li, Wei; He, Qi-chang; Fan, Xiu-min; Fei, Zhi-min

2012-01-11

Electroencephalogram (EEG) data is an effective indicator to evaluate driver fatigue. The 16 channels of EEG data are collected and transformed into three bands (θ, α, and β) in the current paper. First, 12 types of energy parameters are computed based on the EEG data. Then, Grey Relational Analysis (GRA) is introduced to identify the optimal indicator of driver fatigue, after which, the number of significant electrodes is reduced using Kernel Principle Component Analysis (KPCA). Finally, the evaluation model for driver fatigue is established with the regression equation based on the EEG data from two significant electrodes (Fp1 and O1). The experimental results verify that the model is effective in evaluating driver fatigue. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Time course of EEG slow-wave activity in pre-school children with sleep disordered breathing: a possible mechanism for daytime deficits?

PubMed

Biggs, Sarah N; Walter, Lisa M; Nisbet, Lauren C; Jackman, Angela R; Anderson, Vicki; Nixon, Gillian M; Davey, Margot J; Trinder, John; Hoffmann, Robert; Armitage, Roseanne; Horne, Rosemary S C

2012-09-01

Daytime deficits in children with sleep disordered breathing (SDB) are theorized to result from hypoxic insult to the developing brain or fragmented sleep. Yet, these do not explain why deficits occur in primary snorers (PS). The time course of slow wave EEG activity (SWA), a proxy of homeostatic regulation and cortical maturation, may provide insight. Clinical and control subjects (N=175: mean age 4.3±0.9 y: 61% male) participated in overnight polysomnography (PSG). Standard sleep scoring and power spectral analyses were conducted on EEG (C4/A1; 0.5-<3.9Hz). Univariate ANOVA's evaluated group differences in sleep stages and respiratory parameters. Repeated-measures ANCOVA evaluated group differences in the time course of SWA. Four groups were classified: controls (OAHI ≤ 1 event/h; no clinical history); PS (OAHI ≤ 1 event/h; clinical history); mild OSA (OAHI=1-5 events/h); and moderate to severe OSA (MS OSA: OAHI>5 events/h). Group differences were found in the percentage of time spent in NREM Stages 1 and 4 (p<0.001) and in the time course of SWA. PS and Mild OSA children had higher SWA in the first NREM period than controls (p<0.05). All SDB groups had higher SWA in the fourth NREM period (p<0.01). These results suggest enhanced sleep pressure but impaired restorative sleep function in pre-school children with SDB, providing new insights into the possible mechanism for daytime deficits observed in all severities of SDB. Copyright © 2012 Elsevier B.V. All rights reserved.

[Procedural learning and anxiolytic effects: electroencephalographic, motor and attentional measures].

PubMed

Portella, Claudio Elidio; Silva, Julio Guilherme; Bastos, Victor Hugo; Machado, Dionis; Cunha, Marlo; Cagy, Maurício; Basile, Luis; Piedade, Roberto; Ribeiro, Pedro

2006-06-01

The objective of the present study was to evaluate attentional, motor and electroencephalographic (EEG) parameters during a procedural task when subjects have ingested 6 mg of bromazepam. The sample consisted of 26 healthy subjects, male or female, between 19 and 36 years of age. The control (placebo) and experimental (bromazepam 6 mg) groups were submitted to a typewriting task in a randomized, double-blind design. The findings did not show significant differences in attentional and motor measures between groups. Coherence measures (qEEG) were evaluated between scalp regions, in theta, alpha and beta bands. A first analysis revealed a main effect for condition (Anova 2-way--condition versus blocks). A second Anova 2-way (condition versus scalp regions) showed a main effect for both factors. The coherence measure was not a sensitive tool at demonstrating differences between cortical areas as a function of procedural learning.

Peripheral Inflammatory Markers Contributing to Comorbidities in Autism

PubMed Central

Inga Jácome, Martha Cecilia; Morales Chacòn, Lilia Maria; Vera Cuesta, Hector; Maragoto Rizo, Carlos; Whilby Santiesteban, Mabel; Ramos Hernandez, Lesyanis; Noris García, Elena; González Fraguela, Maria Elena; Fernandez Verdecia, Caridad Ivette; Vegas Hurtado, Yamilé; Siniscalco, Dario; Gonçalves, Carlos Alberto; Robinson-Agramonte, Maria de los Angeles

2016-01-01

This study evaluates the contribution of peripheral biomarkers to comorbidities and clinical findings in autism. Seventeen autistic children and age-matched typically developing (AMTD), between three to nine years old were evaluated. The diagnostic followed the Diagnostic and Statistical Manual of Mental Disorders 4th Edition (DMS-IV) and the Childhood Autism Rating Scale (CARS) was applied to classify the severity. Cytokine profile was evaluated in plasma using a sandwich type ELISA. Paraclinical events included electroencephalography (EEG) record. Statistical analysis was done to explore significant differences in cytokine profile between autism and AMTD groups and respect clinical and paraclinical parameters. Significant differences were found to IL-1β, IL-6, IL-17, IL-12p40, and IL-12p70 cytokines in individuals with autism compared with AMTD (p < 0.05). All autistic patients showed interictalepileptiform activity at EEG, however, only 37.5% suffered epilepsy. There was not a regional focalization of the abnormalities that were detectable with EEG in autistic patients with history of epilepsy. A higher IL-6 level was observed in patients without history of epilepsy with interictalepileptiform activity in the frontal brain region, p < 0.05. In conclusion, peripheral inflammatory markers might be useful as potential biomarkers to predict comorbidities in autism as well as reinforce and aid informed decision-making related to EEG findings in children with Autism spectrum disorders (ASD). PMID:27983615

Impact of age on both BIS values and EEG bispectrum during anaesthesia with sevoflurane in children

PubMed Central

Wodey, Eric; Tirel, Olivier; Bansard, Jean-Yves; Terrier, Anne; Chanavaz, Charles; Harris, Rupert; Ecoffey, Claude; Senhadji, Lotfi

2005-01-01

The aim of this study was to evaluate the potential relationship between age, BIS (Aspect™) and the EEG bispectrum during anesthesia with sevoflurane. BIS and raw EEG sampled at 400 Hz were recorded at a steady state of 1 MAC sevoflurane in 100 children, and during a decrease from 2 MAC to 0.5 MAC in a sub-group of 29 children. The bispectrum of the EEG was estimated on successive epochs of 20 seconds using MATLAB© software, independently of the Aspect™ device. For analysis, the bispectrum was divided into 36 frequencies of coupling (Pi) - the MatBis. A multiple correspondence analysis (MCA) was used to establish an underlying structure of the pattern of each individual’s MatBis at the steady state of 1 MAC. Clustering of children into homogeneous groups was conducted by a hierarchical ascending classification (HAC). The level of statistical significance was set at 0.05. At the steady state of 1 MAC sevoflurane, the BIS values for all 100 children ranged from 20 to 74 (median 40). Projection of both age and BIS value recorded at 1 MAC (T10) onto the structured model of the MCA showed them to be distributed along axis F1 of this model. In contrast, projection of children’s position during the decrease in sevoflurane concentration was linked to axis F2. At 1 MAC sevoflurane, six homogeneous groups of children were obtained through the HAC. Groups 5 (30 months; range 23–49) and 6 (18 months; range 6–180) were the younger children and group 1 (97 months; range 46–162) the older. Groups 5 and 6 had the highest median values of BIS (54; range 50–59)(55; range 26–74) and the group 1 the lowest values (29; range 22–37). The EEG bispectrum, as well as the BIS (Aspect XP™) measured at 1 MAC sevoflurane appeared to be strongly related to the age of children. PMID:15833781

Effects of Neurofeekback Training on EEG, Continuous Performance Task (CPT), and ADHD Symptoms in ADHD-prone College Students.

PubMed

Ryoo, Manhee; Son, Chongnak

2015-12-01

This study explored the effects of neurofeedback training on Electroencephalogram (EEG), Continuous Performance Task (CPT) and ADHD symptoms in ADHD prone college students. Two hundred forty seven college students completed Korean Version of Conners' Adult ADHD Rating Scales (CAARS-K) and Korean Version of Beck Depression Inventory (K-BDI). The 16 participants who ranked in the top 25% of CAARS-K score and had 16 less of K-BDI score participated in this study. Among them, 8 participants who are fit for the research schedule were assigned to neurofeedback training group and 8 not fit for the research schedule to the control group. All participants completed Adult Attention Deficiency Questionnaire, CPT and EEG measurement at pretest. The neurofeedback group received 15 neurofeedback training sessions (5 weeks, 3 sessions per week). The control group did not receive any treatment. Four weeks after completion of the program, all participants completed CAARS-K, Adult Attention Deficiency Questionnaire, CPT and EEG measurement for post-test. The neurofeedback group showed more significant improvement in EEG, CPT performance and ADHD symptoms than the control group. The improvements were maintained at follow up. Neurofeedback training adjusted abnormal EEG and was effective in improving objective and subjective ADHD symptoms in ADHD prone college students.

Changes of EEG Spectra and Functional Connectivity during an Object-Location Memory Task in Alzheimer's Disease.

PubMed

Han, Yuliang; Wang, Kai; Jia, Jianjun; Wu, Weiping

2017-01-01

Object-location memory is particularly fragile and specifically impaired in Alzheimer's disease (AD) patients. Electroencephalogram (EEG) was utilized to objectively measure memory impairment for memory formation correlates of EEG oscillatory activities. We aimed to construct an object-location memory paradigm and explore EEG signs of it. Two groups of 20 probable mild AD patients and 19 healthy older adults were included in a cross-sectional analysis. All subjects took an object-location memory task. EEG recordings performed during object-location memory tasks were compared between the two groups in the two EEG parameters (spectral parameters and phase synchronization). The memory performance of AD patients was worse than that of healthy elderly adults The power of object-location memory of the AD group was significantly higher than the NC group (healthy elderly adults) in the alpha band in the encoding session, and alpha and theta bands in the retrieval session. The channels-pairs the phase lag index value of object-location memory in the AD group was clearly higher than the NC group in the delta, theta, and alpha bands in encoding sessions and delta and theta bands in retrieval sessions. The results provide support for the hypothesis that the AD patients may use compensation mechanisms to remember the items and episode.

Impact of brain injury on functional measures of amplitude-integrated EEG at term equivalent age in premature infants.

PubMed

El Ters, N M; Vesoulis, Z A; Liao, S M; Smyser, C D; Mathur, A M

2017-08-01

To evaluate the association between qualitative and quantitative amplitude-integrated EEG (aEEG) measures at term equivalent age (TEA) and brain injury on magnetic resonance imaging (MRI) in preterm infants. A cohort of premature infants born at <30 weeks of gestation and with moderate-to-severe MRI injury on a TEA MRI scan was identified. A contemporaneous group of gestational age-matched control infants also born at <30 weeks of gestation with none/mild injury on MRI was also recruited. Quantitative aEEG measures, including maximum and minimum amplitudes, bandwidth span and spectral edge frequency (SEF 90 ), were calculated using an offline software package. The aEEG recordings were qualitatively scored using the Burdjalov system. MRI scans, performed on the same day as aEEG, occurred at a mean postmenstrual age of 38.0 (range 37 to 42) weeks and were scored for abnormality in a blinded manner using an established MRI scoring system. Twenty-eight (46.7%) infants had a normal MRI or mild brain abnormality, while 32 (53.3%) infants had moderate-to-severe brain abnormality. Univariate regression analysis demonstrated an association between severity of brain abnormality and quantitative measures of left and right SEF 90 and bandwidth span (β=-0.38, -0.40 and 0.30, respectively) and qualitative measures of cyclicity, continuity and total Burdjalov score (β=-0.10, -0.14 and -0.12, respectively). After correcting for confounding variables, the relationship between MRI abnormality score and aEEG measures of SEF 90 , bandwidth span and Burdjalov score remained significant. Brain abnormalities on MRI at TEA in premature infants are associated with abnormalities on term aEEG measures, suggesting that anatomical brain injury may contribute to delay in functional brain maturation as assessed using aEEG.

Robust Multimodal Cognitive Load Measurement

DTIC Science & Technology

2014-03-26

dimension, Hurst exponent ) of electroencephalogram (EEG) signals to evaluate changes in working memory load during the performance of a cognitive task...dimension, Hurst exponent ) of electroencephalogram (EEG) signals to evaluate changes in working memory load during the performance of a cognitive task with...approximate entropies, wavelet-based complexity measures, correlation dimension, Hurst exponent ) of electroencephalogram (EEG) signals to evaluate changes

Correlation of Visuospatial Ability and EEG Slowing in Patients with Parkinson's Disease

PubMed Central

Meyer, Antonia; Chaturvedi, Menorca; Hatz, Florian; Gschwandtner, Ute

2017-01-01

Background. Visuospatial dysfunction is among the first cognitive symptoms in Parkinson's disease (PD) and is often predictive for PD-dementia. Furthermore, cognitive status in PD-patients correlates with quantitative EEG. This cross-sectional study aimed to investigate the correlation between EEG slowing and visuospatial ability in nondemented PD-patients. Methods. Fifty-seven nondemented PD-patients (17 females/40 males) were evaluated with a comprehensive neuropsychological test battery and a high-resolution 256-channel EEG was recorded. A median split was performed for each cognitive test dividing the patients sample into either a normal or lower performance group. The electrodes were split into five areas: frontal, central, temporal, parietal, and occipital. A linear mixed effects model (LME) was used for correlational analyses and to control for confounding factors. Results. Subsequently, for the lower performance, LME analysis showed a significant positive correlation between ROCF score and parietal alpha/theta ratio (b = .59, p = .012) and occipital alpha/theta ratio (b = 0.50, p = .030). No correlations were found in the group of patients with normal visuospatial abilities. Conclusion. We conclude that a reduction of the parietal alpha/theta ratio is related to visuospatial impairments in PD-patients. These findings indicate that visuospatial impairment in PD-patients could be influenced by parietal dysfunction. PMID:28348918

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

OCCIPITAL SOURCES OF RESTING STATE ALPHA RHYTHMS ARE RELATED TO LOCAL GRAY MATTER DENSITY IN SUBJECTS WITH AMNESIC MILD COGNITIVE IMPAIRMENT AND ALZHEIMER’S DISEASE

PubMed Central

Claudio, Babiloni; Claudio, Del Percio; Marina, Boccardi; Roberta, Lizio; Susanna, Lopez; Filippo, Carducci; Nicola, Marzano; Andrea, Soricelli; Raffaele, Ferri; Ivano, Triggiani Antonio; Annapaola, Prestia; Serenella, Salinari; Rasser Paul, E; Erol, Basar; Francesco, Famà; Flavio, Nobili; Görsev, Yener; Durusu, Emek-Savaş Derya; Gesualdo, Loreto; Ciro, Mundi; Thompson Paul, M; Rossini Paolo, M.; Frisoni Giovanni, B

2014-01-01

Occipital sources of resting state electroencephalographic (EEG) alpha rhythms are abnormal, at the group level, in patients with amnesic mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Here we evaluated the hypothesis that amplitude of these occipital sources is related to neurodegeneration in occipital lobe as measured by magnetic resonance imaging (MRI). Resting-state eyes-closed EEG rhythms were recorded in 45 healthy elderly (Nold), 100 MCI, and 90 AD subjects. Neurodegeneration of occipital lobe was indexed by weighted averages of gray matter density (GMD), estimated from structural MRIs. EEG rhythms of interest were alpha 1 (8–10.5 Hz) and alpha 2 (10.5–13 Hz). EEG cortical sources were estimated by low resolution brain electromagnetic tomography (LORETA). Results showed a positive correlation between occipital GMD and amplitude of occipital alpha 1 sources in Nold, MCI and AD subjects as a whole group (r=0.3, p=0.000004, N=235). Furthermore, there was a positive correlation between amplitude of occipital alpha 1 sources and cognitive status as revealed by Mini Mental State Evaluation (MMSE) score across all subjects (r=0.38, p=0.000001, N=235). Finally, amplitude of occipital alpha 1 sources allowed a moderate classification of individual Nold and AD subjects (sensitivity: 87.8%; specificity: 66.7%; area under the Receiver Operating Characteristic (ROC) curve: 0.81). These results suggest that the amplitude of occipital sources of resting state alpha rhythms is related to AD neurodegeneration in occipital lobe along pathological aging. PMID:25442118

Cross-conditional entropy and coherence analysis of pharmaco-EEG changes induced by alprazolam.

PubMed

Alonso, J F; Mañanas, M A; Romero, S; Rojas-Martínez, M; Riba, J

2012-06-01

Quantitative analysis of electroencephalographic signals (EEG) and their interpretation constitute a helpful tool in the assessment of the bioavailability of psychoactive drugs in the brain. Furthermore, psychotropic drug groups have typical signatures which relate biochemical mechanisms with specific EEG changes. To analyze the pharmacological effect of a dose of alprazolam on the connectivity of the brain during wakefulness by means of linear and nonlinear approaches. EEG signals were recorded after alprazolam administration in a placebo-controlled crossover clinical trial. Nonlinear couplings assessed by means of corrected cross-conditional entropy were compared to linear couplings measured with the classical magnitude squared coherence. Linear variables evidenced a statistically significant drug-induced decrease, whereas nonlinear variables showed significant increases. All changes were highly correlated to drug plasma concentrations. The spatial distribution of the observed connectivity changes clearly differed from a previous study: changes before and after the maximum drug effect were mainly observed over the anterior half of the scalp. Additionally, a new variable with very low computational cost was defined to evaluate nonlinear coupling. This is particularly interesting when all pairs of EEG channels are assessed as in this study. Results showed that alprazolam induced changes in terms of uncoupling between regions of the scalp, with opposite trends depending on the variables: decrease in linear ones and increase in nonlinear features. Maps provided consistent information about the way brain changed in terms of connectivity being definitely necessary to evaluate separately linear and nonlinear interactions.

Zolpidem arousing effect in persistent vegetative state patients: autonomic, EEG and behavioral assessment.

PubMed

Machado, Calixto; Estévez, Mario; Rodríguez, Rafael; Pérez-Nellar, Jesús; Chinchilla, Mauricio; DeFina, Philip; Leisman, Gerry; Carrick, Frederick R; Melillo, Robert; Schiavi, Adam; Gutiérrez, Joel; Carballo, Maylén; Machado, Andrés; Olivares, Ana; Pérez-Cruz, Nuvia

2014-01-01

To study the Zolpidem arousing effect in persistent vegetative state (PVS) patients combining clinical evaluation, autonomic assessment by heart rate variability (HRV), and EEG records. We studied a group of 8 PVS patients and other 8 healthy control subjects, matched by age and gender. The patients and controls received drug or placebo in two experimental sessions, separated by 10-14 days. The first 30 minutes of the session were considered the basal record, and then Zolpidem was administered. All participants were evaluated clinically, by EEG, and by HRV during the basal record, and for 90 minutes after drug intake. We found in all patients, time-related arousing signs after Zolpidem intake: behavioral (yawns and hiccups), activation of EEG cortical activity, and a vagolytic chronotropic effect without a significant increment of the vasomotor sympathetic tone. We demonstrated time-related arousing signs after Zolpidem intake. We discussed possible mechanisms to explain these patho-physiological findings regarding EEG cortical activation and an autonomic vagolytic drug effect. As this autonomic imbalance might induce cardiocirculatory complications, which we didn't find in any of our patients, we suggest developing future trials under control of physiological indices by bedside monitoring. However, considering that this arousing Zolpidem effect might be certainly related to brain function improvement, it should be particularly considered for the development of new neuro-rehabilitation programs in PVS cases. According to the literature review, we claim that this is the first report about the vagolitic effect of Zolpidem in PVS cases.

On-going electroencephalographic rhythms related to cortical arousal in wild-type mice: the effect of aging.

PubMed

Del Percio, Claudio; Drinkenburg, Wilhelmus; Lopez, Susanna; Infarinato, Francesco; Bastlund, Jesper Frank; Laursen, Bettina; Pedersen, Jan T; Christensen, Ditte Zerlang; Forloni, Gianluigi; Frasca, Angelisa; Noè, Francesco M; Bentivoglio, Marina; Fabene, Paolo Francesco; Bertini, Giuseppe; Colavito, Valeria; Kelley, Jonathan; Dix, Sophie; Richardson, Jill C; Babiloni, Claudio

2017-01-01

Resting state electroencephalographic (EEG) rhythms reflect the fluctuation of cortical arousal and vigilance in a typical clinical setting, namely the EEG recording for few minutes with eyes closed (i.e., passive condition) and eyes open (i.e., active condition). Can this procedure be back-translated to C57 (wild type) mice for aging studies? On-going EEG rhythms were recorded from a frontoparietal bipolar channel in 85 (19 females) C57 mice. Male mice were subdivided into 3 groups: 25 young (4.5-6 months), 18 middle-aged (12-15 months), and 23 old (20-24 months) mice to test the effect of aging. EEG power density was compared between short periods (about 5 minutes) of awake quiet behavior (passive) and dynamic exploration of the cage (active). Compared with the passive condition, the active condition induced decreased EEG power at 1-2 Hz and increased EEG power at 6-10 Hz in the group of 85 mice. Concerning the aging effects, the passive condition showed higher EEG power at 1-2 Hz in the old group than that in the others. Furthermore, the active condition exhibited a maximum EEG power at 6-8 Hz in the former group and 8-10 Hz in the latter. In the present conditions, delta and theta EEG rhythms reflected changes in cortical arousal and vigilance in freely behaving C57 mice across aging. These changes resemble the so-called slowing of resting state EEG rhythms observed in humans across physiological and pathological aging. The present EEG procedures may be used to enhance preclinical phases of drug discovery in mice for understanding the neurophysiological effects of new compounds against brain aging. Copyright © 2016 Elsevier Inc. All rights reserved.

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

[Mexidol in treatment of children with generalized epilepsy and febrile seizures].

PubMed

Natriashvili, G; Natriashvili, S; Kapanadze, N

2005-05-01

The aim of our study was to estimate the role of Mexidol in ceasing of epileptic fits and improving electroencephalographic (EEG) pathological patterns in children. 120 patients with generalized epilepsy (from 4 to 16 years old) were investigated. All patients were treated by Depakin chrono 30 mg/kg. Children were divided into 2 groups: 1st--study group consisted of 60 children with combined treatment with Depakin and Mexidol (5 mg/kg). In the control group (60 children) treatment was performed only by Depakin. 100 children with the first episode of febrile seizures (from 6 months to 4 years old) were investigated. 50 children composed the study group with monotheraphy by Mexidol and 50 patients--the control group, without any treatment. The EEG examination was done by computer EEG Topography "Brain Surveyor Saico". Using Depakin in combination with Mexidol in the study group of patients with generalized epilepsy, improvement of clinical picture of disease and normalization of EEG patterns in 93% of cases has been observed. In the study group of patients with febrile seizures, normalization of EEG pathological patterns was observed in 82% cases and in 18% its improvement was seen. The relapse of seizures at high temperature was observed in 3 patients. In control group EEG patterns were improved only in 20%, in 48% no positive effect was observed and in 41% the worsening of EEG findings was seen. The relapse of febrile seizures was observed in 26 cases. Mexidol titrated to the target doze of 5mg/kg may be effective in combination with Depakin for treatment of patients with generalized epilepsy and as monotherapy in patients with first episode of febrile seizures.

A realistic multimodal modeling approach for the evaluation of distributed source analysis: application to sLORETA.

PubMed

Cosandier-Rimélé, D; Ramantani, G; Zentner, J; Schulze-Bonhage, A; Dümpelmann, M

2017-10-01

Electrical source localization (ESL) deriving from scalp EEG and, in recent years, from intracranial EEG (iEEG), is an established method in epilepsy surgery workup. We aimed to validate the distributed ESL derived from scalp EEG and iEEG, particularly regarding the spatial extent of the source, using a realistic epileptic spike activity simulator. ESL was applied to the averaged scalp EEG and iEEG spikes of two patients with drug-resistant structural epilepsy. The ESL results for both patients were used to outline the location and extent of epileptic cortical patches, which served as the basis for designing a spatiotemporal source model. EEG signals for both modalities were then generated for different anatomic locations and spatial extents. ESL was subsequently performed on simulated signals with sLORETA, a commonly used distributed algorithm. ESL accuracy was quantitatively assessed for iEEG and scalp EEG. The source volume was overestimated by sLORETA at both EEG scales, with the error increasing with source size, particularly for iEEG. For larger sources, ESL accuracy drastically decreased, and reconstruction volumes shifted to the center of the head for iEEG, while remaining stable for scalp EEG. Overall, the mislocalization of the reconstructed source was more pronounced for iEEG. We present a novel multiscale framework for the evaluation of distributed ESL, based on realistic multiscale EEG simulations. Our findings support that reconstruction results for scalp EEG are often more accurate than for iEEG, owing to the superior 3D coverage of the head. Particularly the iEEG-derived reconstruction results for larger, widespread generators should be treated with caution.

A realistic multimodal modeling approach for the evaluation of distributed source analysis: application to sLORETA

NASA Astrophysics Data System (ADS)

Cosandier-Rimélé, D.; Ramantani, G.; Zentner, J.; Schulze-Bonhage, A.; Dümpelmann, M.

2017-10-01

Objective. Electrical source localization (ESL) deriving from scalp EEG and, in recent years, from intracranial EEG (iEEG), is an established method in epilepsy surgery workup. We aimed to validate the distributed ESL derived from scalp EEG and iEEG, particularly regarding the spatial extent of the source, using a realistic epileptic spike activity simulator. Approach. ESL was applied to the averaged scalp EEG and iEEG spikes of two patients with drug-resistant structural epilepsy. The ESL results for both patients were used to outline the location and extent of epileptic cortical patches, which served as the basis for designing a spatiotemporal source model. EEG signals for both modalities were then generated for different anatomic locations and spatial extents. ESL was subsequently performed on simulated signals with sLORETA, a commonly used distributed algorithm. ESL accuracy was quantitatively assessed for iEEG and scalp EEG. Main results. The source volume was overestimated by sLORETA at both EEG scales, with the error increasing with source size, particularly for iEEG. For larger sources, ESL accuracy drastically decreased, and reconstruction volumes shifted to the center of the head for iEEG, while remaining stable for scalp EEG. Overall, the mislocalization of the reconstructed source was more pronounced for iEEG. Significance. We present a novel multiscale framework for the evaluation of distributed ESL, based on realistic multiscale EEG simulations. Our findings support that reconstruction results for scalp EEG are often more accurate than for iEEG, owing to the superior 3D coverage of the head. Particularly the iEEG-derived reconstruction results for larger, widespread generators should be treated with caution.

Human brain networks in physiological aging: a graph theoretical analysis of cortical connectivity from EEG data.

PubMed

Vecchio, Fabrizio; Miraglia, Francesca; Bramanti, Placido; Rossini, Paolo Maria

2014-01-01

Modern analysis of electroencephalographic (EEG) rhythms provides information on dynamic brain connectivity. To test the hypothesis that aging processes modulate the brain connectivity network, EEG recording was conducted on 113 healthy volunteers. They were divided into three groups in accordance with their ages: 36 Young (15-45 years), 46 Adult (50-70 years), and 31 Elderly (>70 years). To evaluate the stability of the investigated parameters, a subgroup of 10 subjects underwent a second EEG recording two weeks later. Graph theory functions were applied to the undirected and weighted networks obtained by the lagged linear coherence evaluated by eLORETA on cortical sources. EEG frequency bands of interest were: delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), beta2 (20-30 Hz), and gamma (30-40 Hz). The spectral connectivity analysis of cortical sources showed that the normalized Characteristic Path Length (λ) presented the pattern Young > Adult>Elderly in the higher alpha band. Elderly also showed a greater increase in delta and theta bands than Young. The correlation between age and λ showed that higher ages corresponded to higher λ in delta and theta and lower in the alpha2 band; this pattern reflects the age-related modulation of higher (alpha) and decreased (delta) connectivity. The Normalized Clustering coefficient (γ) and small-world network modeling (σ) showed non-significant age-modulation. Evidence from the present study suggests that graph theory can aid in the analysis of connectivity patterns estimated from EEG and can facilitate the study of the physiological and pathological brain aging features of functional connectivity networks.

Malformations of cortical development and epilepsy: evaluation of 101 cases (part II).

PubMed

Güngör, Serdal; Yalnizoğlu, Dilek; Turanli, Güzide; Saatçi, Işil; Erdoğan-Bakar, Emel; Topçu, Meral

2007-01-01

Malformations of cortical development (MCD) form a spectrum of lesions produced by insult to the developing neocortex. Clinical presentation and electrophysiologic findings of MCD are variable and depend on the affected cortical area. We evaluated epilepsy, EEG, and response to antiepileptic treatment in patients with MCD with respect to the neuroimaging findings. We studied 101 patients, ranging between 1 month and 19 years of age. Fifty-four patients were diagnosed with polymicrogyria (PMG), 23 patients with lissencephaly, 12 patients with schizencephaly, and 12 patients with heterotopia. With regards to epilepsy and seizure type, 72/101 (71.3%) patients had epilepsy, and 62/101 (61.4%) patients presented with seizures. Overall, 32.7% of patients had generalized seizures, and 25.7% had complex partial seizures. Mean age at the onset of seizures was 2.7 +/- 3.4 years. The onset of epilepsy tended to be younger in patients with lissencephaly and older in patients with heterotopias. Of the cases, 79.2% had abnormal EEG (56.3% with epileptiform abnormality, 22.9% with non-epileptiform abnormality). EEG was abnormal in 44.9% (13/29) of the cases without epilepsy. EEG showed bilateral synchronous and diffuse epileptiform discharges in 90% of patients with lissencephaly. Patients with schizencephaly had mostly focal epileptiform discharges. Heterotopia cases had a high rate of EEG abnormalities (72.7%). Patients with PMG had epileptiform abnormality in 59.5% of the cases. Patients with heterotopias and PMG achieved better seizure control in comparison with the other groups. In conclusion, epilepsy is the most common problem in MCD. Epilepsy and EEG findings of patients with MCD are variable and seem to be correlated with the extent of cortical involvement.

Prediction of subjective ratings of emotional pictures by EEG features

NASA Astrophysics Data System (ADS)

McFarland, Dennis J.; Parvaz, Muhammad A.; Sarnacki, William A.; Goldstein, Rita Z.; Wolpaw, Jonathan R.

2017-02-01

Objective. Emotion dysregulation is an important aspect of many psychiatric disorders. Brain-computer interface (BCI) technology could be a powerful new approach to facilitating therapeutic self-regulation of emotions. One possible BCI method would be to provide stimulus-specific feedback based on subject-specific electroencephalographic (EEG) responses to emotion-eliciting stimuli. Approach. To assess the feasibility of this approach, we studied the relationships between emotional valence/arousal and three EEG features: amplitude of alpha activity over frontal cortex; amplitude of theta activity over frontal midline cortex; and the late positive potential over central and posterior mid-line areas. For each feature, we evaluated its ability to predict emotional valence/arousal on both an individual and a group basis. Twenty healthy participants (9 men, 11 women; ages 22-68) rated each of 192 pictures from the IAPS collection in terms of valence and arousal twice (96 pictures on each of 4 d over 2 weeks). EEG was collected simultaneously and used to develop models based on canonical correlation to predict subject-specific single-trial ratings. Separate models were evaluated for the three EEG features: frontal alpha activity; frontal midline theta; and the late positive potential. In each case, these features were used to simultaneously predict both the normed ratings and the subject-specific ratings. Main results. Models using each of the three EEG features with data from individual subjects were generally successful at predicting subjective ratings on training data, but generalization to test data was less successful. Sparse models performed better than models without regularization. Significance. The results suggest that the frontal midline theta is a better candidate than frontal alpha activity or the late positive potential for use in a BCI-based paradigm designed to modify emotional reactions.

EEG abnormalities and two year outcome in first episode psychosis.

PubMed

Manchanda, R; Norman, R; Malla, A; Harricharan, R; Takhar, J; Northcott, S

2005-03-01

This study examines the relationship of EEG to 2 year symptomatic outcome, duration of illness and untreated psychosis and gender. A total of 122 patients presenting for treatment of first episode psychosis had their baseline EEG classified by modified Mayo Clinic system criteria as normal, essentially normal or dysrhythmia. Positive and negative symptoms of psychoses were rated on entry and after 2 years of treatment. The socio-demographic variables and duration of illness and of untreated psychosis were also recorded. Patients with a normal EEG showed significantly more reduction in both positive and negative symptoms of psychoses over 2 years and were more likely to be in 'remission' as compared with the essentially normal or dysrhythmia group. The dysrhythmic group had significantly higher duration of illness than either the normal or essentially normal groups. There were no gender differences in the distribution of EEGs. An abnormal EEG in patients with first episode psychosis is associated with a poorer prognosis and a longer duration of untreated illness. Copyright (c) Blackwell Munksgaard 2005

Effects of action observation therapy on hand dexterity and EEG-based cortical activation patterns in patients with post-stroke hemiparesis.

PubMed

Kuk, Eun-Ju; Kim, Jong-Man; Oh, Duck-Won; Hwang, Han-Jeong

2016-10-01

Previous reports have suggested that action observation training (AOT) is beneficial in enhancing the early learning of new motor tasks; however, EEG-based investigation has received little attention for AOT. The purpose of this study was to illustrate the effects of AOT on hand dexterity and cortical activation in patients with post-stroke hemiparesis. Twenty patients with post-stroke hemiparesis were randomly divided into either the experimental group (EG) or control group (CG), with 10 patients in each group. Prior to the execution of motor tasks (carrying wooden blocks from one box to another), subjects in the EG and CG observed a video clip displaying the execution of the same motor task and pictures showing landscapes, respectively. Outcome measures included the box and block test (BBT) to evaluate hand dexterity and EEG-based brain mapping to detect changes in cortical activation. The BBT scores (EG: 20.50 ± 6.62 at pre-test and 24.40 ± 5.42 at post-test; CG: 20.20 ± 6.12 at pre-test and 20.60 ± 7.17 at post-test) revealed significant main effects for the time and group and significant time-by-group interactions (p < 0.05). For the subjects in the EG, topographical representations obtained with the EEG-based brain mapping system were different in each session of the AOT and remarkable changes occurred from the 2nd session of AOT. Furthermore, the middle frontal gyrus was less active at post-test than at pre-test. These findings support that AOT may be beneficial in altering cortical activation patterns and hand dexterity.

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.

Etiological associations and outcome predictors of acute electroencephalography in childhood encephalitis.

PubMed

Mohammad, Shekeeb S; Soe, Samantha M; Pillai, Sekhar C; Nosadini, Margherita; Barnes, Elizabeth H; Gill, Deepak; Dale, Russell C

2016-10-01

To examine EEG features in a retrospective 13-year cohort of children with encephalitis. 354 EEGs from 119 patients during their admission were rated blind using a proforma with demonstrated inter-rater reliability (mean k=0.78). Patients belonged to 12 etiological groups that could be grouped into infectious and infection-associated (n=47), immune-mediated (n=36) and unknown (n=33). EEG features were analyzed between groups and for risk of abnormal Liverpool Outcome Score and drug resistant epilepsy (DRE) at last follow up. 86% children had an abnormal first EEG and 89% had at least one abnormal EEG. 55% had an abnormal outcome, and 13% had DRE after median follow-up of 7.3years (2.0-15.8years). Reactive background on first EEGs (9/11, p=0.04) and extreme spindles (4/11, p<0.001) distinguished patients with anti-N-Methyl-d-Aspartate Receptor encephalitis. Non-reactive EEG background (48% first EEGs) predicted abnormal outcome (OR 3.8, p<0.001). A shifting focal seizure pattern, seen in FIRES (4/5), anti-voltage gated potassium channel (2/3), Mycoplasma (1/10), other viral (1/10) and other unknown (1/28) encephalitis, was most predictive of DRE after multivariable analysis (OR 11.9, p<0.001). Non-reactive EEG background and the presence of shifting focal seizures resembling migrating partial seizures of infancy are predictors of abnormal outcome and DRE respectively in childhood encephalitis. EEG is a sensitive but non-discriminatory marker of childhood encephalitis. We highlight the EEG features that predict abnormal outcome and DRE. Copyright © 2016 International Federation of Clinical Neurophysiology. All rights reserved.

Effects of Aerobic Exercise on Anxiety Symptoms and Cortical Activity in Patients with Panic Disorder: A Pilot Study.

PubMed

Lattari, Eduardo; Budde, Henning; Paes, Flávia; Neto, Geraldo Albuquerque Maranhão; Appolinario, José Carlos; Nardi, Antônio Egídio; Murillo-Rodriguez, Eric; Machado, Sérgio

2018-01-01

The effects of the aerobic exercise on anxiety symptoms in patients with Panic Disorder (PD) remain unclear. Thus, the investigation of possible changes in EEG frontal asymmetry could contribute to understand the relationship among exercise, brain and anxiety. To investigate the acute effects of aerobic exercise on the symptoms of anxiety and the chronic effects of aerobic exercise on severity and symptoms related to PD, besides the changes in EEG frontal asymmetry. Ten PD patients were divided into two groups, Exercise Group (EG; n=5) and Control Group (CG; n=5), in a randomized allocation. At baseline and post-intervention, they submitted the psychological evaluation through Panic Disorder Severity Scale (PDSS), Beck Anxiety Inventory (BAI), Beck Depression Inventory-II (BDI-II), EEG frontal asymmetry, and maximal oxygen consumption (VO 2 max). On the second visit, the patients of EG being submitted to the aerobic exercise (treadmill, 25 minutes, and 50-55% of heart rate reserve) and the CG remained seated for the same period of time. Both groups submitted a psychological evaluation with Subjective Units of Distress Scale (SUDS) at baseline, immediately after (Post-0), and after 10 minutes of the rest pause (Post-10). The patients performed 12 sessions of aerobic exercise with 48-72 hours of interval between sessions. In EG, SUDS increased immediately after exercise practice and showed chronic decrease in BAI and BDI-II as well as increased in VO 2 max (Post-intervention). Aerobic exercise can promote increase in anxiety acutely and regular aerobic exercise promotes reduction in anxiety levels.

Evaluating the effectiveness of using electroencephalogram power indices to measure visual fatigue.

PubMed

Hsu, Bin-Wei; Wang, Mao-Jiun J

2013-02-01

Electroencephalography (EEG) is widely used in cognitive and behavioral research. This study evaluates the effectiveness of using the EEG power index to measure visual fatigue. Three common visual fatigue measures, critical-flicker fusion (CFF), near-point accommodation (NPA), and subjective eye-fatigue rating, were used for comparison. The study participants were 20 men with a mean age of 20.4 yr. (SD = 1.5). The experimental task was a car-racing video game. Results indicated that the EEG power indices were valid as a visual fatigue measure and the sensitivity of the objective measures (CFF and EEG power index) was higher than the subjective measure. The EEG beta and EEG alpha were effective for measuring visual fatigue in short- and long-duration tasks, respectively. EEG beta/alpha were the most effective power indexes for the visual fatigue measure.

A feature-based approach to combine functional MRI, structural MRI and EEG brain imaging data.

PubMed

Calhoun, V; Adali, T; Liu, J

2006-01-01

The acquisition of multiple brain imaging types for a given study is a very common practice. However these data are typically examined in separate analyses, rather than in a combined model. We propose a novel methodology to perform joint independent component analysis across image modalities, including structural MRI data, functional MRI activation data and EEG data, and to visualize the results via a joint histogram visualization technique. Evaluation of which combination of fused data is most useful is determined by using the Kullback-Leibler divergence. We demonstrate our method on a data set composed of functional MRI data from two tasks, structural MRI data, and EEG data collected on patients with schizophrenia and healthy controls. We show that combining data types can improve our ability to distinguish differences between groups.

Combined EEG-fNIRS decoding of motor attempt and imagery for brain switch control: an offline study in patients with tetraplegia.

PubMed

Blokland, Yvonne; Spyrou, Loukianos; Thijssen, Dick; Eijsvogels, Thijs; Colier, Willy; Floor-Westerdijk, Marianne; Vlek, Rutger; Bruhn, Jorgen; Farquhar, Jason

2014-03-01

Combining electrophysiological and hemodynamic features is a novel approach for improving current performance of brain switches based on sensorimotor rhythms (SMR). This study was conducted with a dual purpose: to test the feasibility of using a combined electroencephalogram/functional near-infrared spectroscopy (EEG-fNIRS) SMR-based brain switch in patients with tetraplegia, and to examine the performance difference between motor imagery and motor attempt for this user group. A general improvement was found when using both EEG and fNIRS features for classification as compared to using the single-modality EEG classifier, with average classification rates of 79% for attempted movement and 70% for imagined movement. For the control group, rates of 87% and 79% were obtained, respectively, where the "attempted movement" condition was replaced with "actual movement." A combined EEG-fNIRS system might be especially beneficial for users who lack sufficient control of current EEG-based brain switches. The average classification performance in the patient group for attempted movement was significantly higher than for imagined movement using the EEG-only as well as the combined classifier, arguing for the case of a paradigm shift in current brain switch research.

Support vector machine and fuzzy C-mean clustering-based comparative evaluation of changes in motor cortex electroencephalogram under chronic alcoholism.

PubMed

Kumar, Surendra; Ghosh, Subhojit; Tetarway, Suhash; Sinha, Rakesh Kumar

2015-07-01

In this study, the magnitude and spatial distribution of frequency spectrum in the resting electroencephalogram (EEG) were examined to address the problem of detecting alcoholism in the cerebral motor cortex. The EEG signals were recorded from chronic alcoholic conditions (n = 20) and the control group (n = 20). Data were taken from motor cortex region and divided into five sub-bands (delta, theta, alpha, beta-1 and beta-2). Three methodologies were adopted for feature extraction: (1) absolute power, (2) relative power and (3) peak power frequency. The dimension of the extracted features is reduced by linear discrimination analysis and classified by support vector machine (SVM) and fuzzy C-mean clustering. The maximum classification accuracy (88 %) with SVM clustering was achieved with the EEG spectral features with absolute power frequency on F4 channel. Among the bands, relatively higher classification accuracy was found over theta band and beta-2 band in most of the channels when computed with the EEG features of relative power. Electrodes wise CZ, C3 and P4 were having more alteration. Considering the good classification accuracy obtained by SVM with relative band power features in most of the EEG channels of motor cortex, it can be suggested that the noninvasive automated online diagnostic system for the chronic alcoholic condition can be developed with the help of EEG signals.

Comparison of Quantitative Characteristics of Early Post-resuscitation EEG Between Asphyxial and Ventricular Fibrillation Cardiac Arrest in Rats.

PubMed

Chen, Bihua; Chen, Gang; Dai, Chenxi; Wang, Pei; Zhang, Lei; Huang, Yuanyuan; Li, Yongqin

2018-04-01

Quantitative electroencephalogram (EEG) analysis has shown promising results in studying brain injury and functional recovery after cardiac arrest (CA). However, whether the quantitative characteristics of EEG, as potential indicators of neurological prognosis, are influenced by CA causes is unknown. The purpose of this study was designed to compare the quantitative characteristics of early post-resuscitation EEG between asphyxial CA (ACA) and ventricular fibrillation CA (VFCA) in rats. Thirty-two Sprague-Dawley rats of both sexes were randomized into either ACA or VFCA group. Cardiopulmonary resuscitation was initiated after 5-min untreated CA. Characteristics of early post-resuscitation EEG were compared, and the relationships between quantitative EEG features and neurological outcomes were investigated. Compared with VFCA, serum level of S100B, neurological deficit score and brain histopathologic damage score were dramatically higher in the ACA group. Quantitative measures of EEG, including onset time of EEG burst, time to normal trace, burst suppression ratio, and information quantity, were significantly lower for CA caused by asphyxia and correlated with the 96-h neurological outcome and survival. Characteristics of earlier post-resuscitation EEG differed between cardiac and respiratory causes. Quantitative measures of EEG not only predicted neurological outcome and survival, but also have the potential to stratify CA with different causes.

The impact of cognitive load on reward evaluation.

PubMed

Krigolson, Olave E; Hassall, Cameron D; Satel, Jason; Klein, Raymond M

2015-11-19

The neural systems that afford our ability to evaluate rewards and punishments are impacted by a variety of external factors. Here, we demonstrate that increased cognitive load reduces the functional efficacy of a reward processing system within the human medial-frontal cortex. In our paradigm, two groups of participants used performance feedback to estimate the exact duration of one second while electroencephalographic (EEG) data was recorded. Prior to performing the time estimation task, both groups were instructed to keep their eyes still and avoid blinking in line with well established EEG protocol. However, during performance of the time-estimation task, one of the two groups was provided with trial-to-trial-feedback about their performance on the time-estimation task and their eye movements to induce a higher level of cognitive load relative to participants in the other group who were solely provided with feedback about the accuracy of their temporal estimates. In line with previous work, we found that the higher level of cognitive load reduced the amplitude of the feedback-related negativity, a component of the human event-related brain potential associated with reward evaluation within the medial-frontal cortex. Importantly, our results provide further support that increased cognitive load reduces the functional efficacy of a neural system associated with reward processing. Copyright © 2015 Elsevier B.V. All rights reserved.

Massage therapy of moderate and light pressure and vibrator effects on EEG and heart rate.

PubMed

Diego, Miguel A; Field, Tiffany; Sanders, Chris; Hernandez-Reif, Maria

2004-01-01

Three types of commonly used massage therapy techniques were assessed in a sample of 36 healthy adults, randomly assigned to: (1) moderate massage, (2) light massage, or (3) vibratory stimulation group (n = 12 per group). Changes in anxiety and stress were assessed, and EEG and EKG were recorded. Anxiety scores decreased for all groups, but the moderate pressure massage group reported the greatest decrease in stress. The moderate massage group also experienced a decrease in heart rate and EEG changes including an increase in delta and a decrease in alpha and beta activity, suggesting a relaxation response. Finally, this group showed increased positive affect, as indicated by a shift toward left frontal EEG activation. The light massage group showed increased arousal, as indicated by decreased delta and increased deta activity and increased heart rate. The vibratory stimulation group also showed increased arousal, as indicated by increased heart rate and increased theta, alpha, and beta activity.

Methodological standards and interpretation of video-electroencephalography in adult control rodents. A TASK1-WG1 report of the AES/ILAE Translational Task Force of the ILAE.

PubMed

Kadam, Shilpa D; D'Ambrosio, Raimondo; Duveau, Venceslas; Roucard, Corinne; Garcia-Cairasco, Norberto; Ikeda, Akio; de Curtis, Marco; Galanopoulou, Aristea S; Kelly, Kevin M

2017-11-01

In vivo electrophysiological recordings are widely used in neuroscience research, and video-electroencephalography (vEEG) has become a mainstay of preclinical neuroscience research, including studies of epilepsy and cognition. Studies utilizing vEEG typically involve comparison of measurements obtained from different experimental groups, or from the same experimental group at different times, in which one set of measurements serves as "control" and the others as "test" of the variables of interest. Thus, controls provide mainly a reference measurement for the experimental test. Control rodents represent an undiagnosed population, and cannot be assumed to be "normal" in the sense of being "healthy." Certain physiological EEG patterns seen in humans are also seen in control rodents. However, interpretation of rodent vEEG studies relies on documented differences in frequency, morphology, type, location, behavioral state dependence, reactivity, and functional or structural correlates of specific EEG patterns and features between control and test groups. This paper will focus on the vEEG of standard laboratory rodent strains with the aim of developing a small set of practical guidelines that can assist researchers in the design, reporting, and interpretation of future vEEG studies. To this end, we will: (1) discuss advantages and pitfalls of common vEEG techniques in rodents and propose a set of recommended practices and (2) present EEG patterns and associated behaviors recorded from adult rats of a variety of strains. We will describe the defining features of selected vEEG patterns (brain-generated or artifactual) and note similarities to vEEG patterns seen in adult humans. We will note similarities to normal variants or pathological human EEG patterns and defer their interpretation to a future report focusing on rodent seizure patterns. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Quantitative EEG of Rapid-Eye-Movement Sleep: A Marker of Amnestic Mild Cognitive Impairment.

PubMed

Brayet, Pauline; Petit, Dominique; Frauscher, Birgit; Gagnon, Jean-François; Gosselin, Nadia; Gagnon, Katia; Rouleau, Isabelle; Montplaisir, Jacques

2016-04-01

The basal forebrain cholinergic system, which is impaired in early Alzheimer's disease, is more crucial for the activation of rapid-eye-movement (REM) sleep electroencephalogram (EEG) than it is for wakefulness. Quantitative EEG from REM sleep might thus provide an earlier and more accurate marker of the development of Alzheimer's disease in subjects with mild cognitive impairment (MCI) subjects than that from wakefulness. To assess the superiority of the REM sleep EEG as a screening tool for preclinical Alzheimer's disease, 22 subjects with amnestic MCI (a-MCI; 63.9±7.7 years), 10 subjects with nonamnestic MCI (na-MCI; 64.1±4.5 years) and 32 controls (63.7±6.6 years) participated in the study. Spectral analyses of the waking EEG and REM sleep EEG were performed and the [(delta+theta)/(alpha+beta)] ratio was used to assess between-group differences in EEG slowing. The a-MCI subgroup showed EEG slowing in frontal lateral regions compared to both na-MCI and control groups. This EEG slowing was present in wakefulness (compared to controls) but was much more prominent in REM sleep. Moreover, the comparison between amnestic and nonamnestic subjects was found significant only for the REM sleep EEG. There was no difference in EEG power ratio between na-MCI and controls for any of the 7 cortical regions studied. These findings demonstrate the superiority of the REM sleep EEG in the discrimination between a-MCI and both na-MCI and control subjects. © EEG and Clinical Neuroscience Society (ECNS) 2015.

QEEG and LORETA in Teenagers With Conduct Disorder and Psychopathic Traits.

PubMed

Calzada-Reyes, Ana; Alvarez-Amador, Alfredo; Galán-García, Lídice; Valdés-Sosa, Mitchell

2017-05-01

Few studies have investigated the impact of the psychopathic traits on the EEG of teenagers with conduct disorder (CD). To date, there is no other research studying low-resolution brain electromagnetic tomography (LORETA) technique using quantitative EEG (QEEG) analysis in adolescents with CD and psychopathic traits. To find electrophysiological differences specifically related to the psychopathic traits. The current investigation compares the QEEG and the current source density measures between adolescents with CD and psychopathic traits and adolescents with CD without psychopathic traits. The resting EEG activity and LORETA for the EEG fast spectral bands were evaluated in 42 teenagers with CD, 25 with and 17 without psychopathic traits according to the Antisocial Process Screening Device. All adolescents were assessed using the DSM-IV-TR criteria. The EEG visual inspection characteristics and the use of frequency domain quantitative analysis techniques (narrow band spectral parameters) are described. QEEG analysis showed a pattern of beta activity excess on the bilateral frontal-temporal regions and decreases of alpha band power on the left central-temporal and right frontal-central-temporal regions in the psychopathic traits group. Current source density calculated at 17.18 Hz showed an increase within fronto-temporo-striatal regions in the psychopathic relative to the nonpsychopathic traits group. These findings indicate that QEEG analysis and techniques of source localization may reveal differences in brain electrical activity among teenagers with CD and psychopathic traits, which was not obvious to visual inspection. Taken together, these results suggest that abnormalities in a fronto-temporo-striatal network play a relevant role in the neurobiological basis of psychopathic behavior.

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.

Test-retest reliability of a single-channel, wireless EEG system.

PubMed

Rogers, Jeffrey M; Johnstone, Stuart J; Aminov, Anna; Donnelly, James; Wilson, Peter H

2016-08-01

Recording systems to acquire electroencephalogram (EEG) data are traditionally lab-based. However, there are shortcomings to this method, and the ease of use and portability of emerging wireless EEG technologies offer a promising alternative. A previous validity study demonstrated data derived from a single-channel, wireless system (NeuroSky ThinkGear, San Jose, California) is comparable to EEG recorded from conventional lab-based equipment. The current study evaluated the reliability of this portable system using test-retest and reliable change analyses. Relative power (RP) of delta, theta, alpha, and beta frequency bands was derived from EEG data obtained from a single electrode over FP1 in 19 healthy youth (10-17years old), 21 healthy adults (18-28years old), and 19 healthy older adults (55-79years old), during eyes-open, eyes-closed, auditory oddball, and visual n-back conditions. Intra-class correlations (ICCs) and Coefficients of Repeatability (CRs) were calculated from RP data re-collected one-day, one-week, and one-month later. Participants' levels of mood and attention were consistent across sessions. Eyes-closed resting EEG measurements using the portable device were reproducible (ICCs 0.76-0.85) at short and longer retest intervals in all three participant age groups. While still of at least fair reliability (ICCs 0.57-0.85), EEG obtained during eyes-open paradigms was less stable, and any change observed over time during these testing conditions can be interpreted utilizing the CR values provided. Combined with existing validity data, these findings encourage application of the portable EEG system for the study of brain function. Copyright © 2016 Elsevier B.V. All rights reserved.

Quantitative EEG during REM and NREM sleep in combat-exposed veterans with and without Posttraumatic Stress Disorder

PubMed Central

Cohen, Daniel J.; Begley, Amy; Alman, Jennie J.; Cashmere, J. David; Pietrone, Regina N.; Seres, Robert J.; Germain, Anne

2012-01-01

Summary Sleep disturbances are a hallmark feature of posttraumatic stress disorder (PTSD), and associated with poor clinical outcomes. Few studies have examined sleep quantitative electroencephalography (qEEG), a technique able to detect subtle differences polysomnography does not capture. We hypothesized greater high-frequency qEEG would reflect “hyperarousal” in in combat veterans with PTSD (n=16) compared to veterans without PTSD (n=13). EEG power in traditional EEG frequency bands was computed for artifact-free sleep epochs across an entire night. Correlations were performed between qEEG and ratings of PTSD symptoms and combat exposure. The groups did not differ significantly in whole night qEEG measures for either REM or NREM. Non-significant medium effect sizes suggest less REM beta (opposite to our hypothesis), less REM and NREM sigma, and more NREM gamma in combat veterans with PTSD. Positive correlations were found between combat exposure and NREM beta (PTSD group only), and REM and NREM sigma (non-PTSD group only). Results did not support global hyperarousal in PTSD as indexed by increased beta qEEG activity. The correlation of sigma activity with combat exposure in those without PTSD, and the non-significant trend towards less sigma activity during both REM and NREM sleep in combat veterans with PTSD suggests that differential information processing during sleep may characterize combat-exposed military veterans with and without PTSD. PMID:22845675

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.

Practice advisory: The utility of EEG theta/beta power ratio in ADHD diagnosis

PubMed Central

Gloss, David; Varma, Jay K.; Pringsheim, Tamara; Nuwer, Marc R.

2016-01-01

Objective: To evaluate the evidence for EEG theta/beta power ratio for diagnosing, or helping to diagnose, attention-deficit/hyperactivity disorder (ADHD). Methods: We identified relevant studies and classified them using American Academy of Neurology criteria. Results: Two Class I studies assessing the ability of EEG theta/beta power ratio and EEG frontal beta power to identify patients with ADHD correctly identified 166 of 185 participants. Both studies evaluated theta/beta power ratio and frontal beta power in suspected ADHD or in syndromes typically included in an ADHD differential diagnosis. A bivariate model combining the diagnostic studies shows that the combination of EEG frontal beta power and theta/beta power ratio has relatively high sensitivity and specificity but is insufficiently accurate. Conclusions: It is unknown whether a combination of standard clinical examination and EEG theta/beta power ratio increases diagnostic certainty of ADHD compared with clinical examination alone. Recommendations: Level B: Clinicians should inform patients with suspected ADHD and their families that the combination of EEG theta/beta power ratio and frontal beta power should not replace a standard clinical evaluation. There is a risk for significant harm to patients from ADHD misdiagnosis because of the unacceptably high false-positive diagnostic rate of EEG theta/beta power ratio and frontal beta power. Level R: Clinicians should inform patients with suspected ADHD and their families that the EEG theta/beta power ratio should not be used to confirm an ADHD diagnosis or to support further testing after a clinical evaluation, unless such diagnostic assessments occur in a research setting. PMID:27760867

Magnetic Stimulation and Epilepsy

DTIC Science & Technology

2013-10-14

the seizure-induced groups exhibited varying degrees of EEG activity reduction. Figure 2. The effects of TMS on penicillin-induced seizures...the EEG recording including (a) baseline (pre-penicillin injection), (b) 30-min post-penicillin injection (30min-PI), (c) 10-min post- TMS stimulation...stable conditions 55% faster, and the 5 pps TMS -treated group 78% faster. Figure 3. Maximum frequency relationships in EEG activity among the

The EEG Split Alpha Peak: Phenomenological Origins and Methodological Aspects of Detection and Evaluation.

PubMed

Olejarczyk, Elzbieta; Bogucki, Piotr; Sobieszek, Aleksander

2017-01-01

Electroencephalographic (EEG) patterns were analyzed in a group of ambulatory patients who ranged in age and sex using spectral analysis as well as Directed Transfer Function, a method used to evaluate functional brain connectivity. We tested the impact of window size and choice of reference electrode on the identification of two or more peaks with close frequencies in the spectral power distribution, so called "split alpha." Together with the connectivity analysis, examination of spatiotemporal maps showing the distribution of amplitudes of EEG patterns allowed for better explanation of the mechanisms underlying the generation of split alpha peaks. It was demonstrated that the split alpha spectrum can be generated by two or more independent and interconnected alpha wave generators located in different regions of the cerebral cortex, but not necessarily in the occipital cortex. We also demonstrated the importance of appropriate reference electrode choice during signal recording. In addition, results obtained using the original data were compared with results obtained using re-referenced data, using average reference electrode and reference electrode standardization techniques.

Scale-specific effects: A report on multiscale analysis of acupunctured EEG in entropy and power

NASA Astrophysics Data System (ADS)

Song, Zhenxi; Deng, Bin; Wei, Xile; Cai, Lihui; Yu, Haitao; Wang, Jiang; Wang, Ruofan; Chen, Yingyuan

2018-02-01

Investigating acupuncture effects contributes to improving clinical application and understanding neuronal dynamics under external stimulation. In this report, we recorded electroencephalography (EEG) signals evoked by acupuncture at ST36 acupoint with three stimulus frequencies of 50, 100 and 200 times per minutes, and selected non-acupuncture EEGs as the control group. Multiscale analyses were introduced to investigate the possible acupuncture effects on complexity and power in multiscale level. Using multiscale weighted-permutation entropy, we found the significant effects on increased complexity degree in EEG signals induced by acupuncture. The comparison of three stimulation manipulations showed that 100 times/min generated most obvious effects, and affected most cortical regions. By estimating average power spectral density, we found decreased power induced by acupuncture. The joint distribution of entropy and power indicated an inverse correlation, and this relationship was weakened by acupuncture effects, especially under the manipulation of 100 times/min frequency. Above findings are more evident and stable in large scales than small scales, which suggests that multiscale analysis allows evaluating significant effects in specific scale and enables to probe the inherent characteristics underlying physiological signals.

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

PubMed

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

2003-01-01

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

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.

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 dose of 320mg/kg was considered to be the EEG no observed adverse effect level (NOAEL) in conscious freely moving cynomolgus monkeys. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Electroencephalography findings in patients presenting to the ED for evaluation of seizures.

PubMed

Kadambi, Pooja; Hart, Kimberly W; Adeoye, Opeolu M; Lindsell, Christopher J; Knight, William A

2015-01-01

Status epilepticus is a life-threatening, time-sensitive emergency. Acquiring an electroencephalogram (EEG) in the emergency department (ED) could impact therapeutic and disposition decisions for patients with suspected status epilepticus. The objective of this study is to estimate the proportion of EEGs diagnostic for seizures in patients presenting to an ED with a complaint of seizures. This retrospective chart review included adults presenting to the ED of an urban, academic, tertiary care hospital with suspected seizures or status epilepticus, who received an EEG within 24 hours of hospital admission. Data abstraction was performed by a single, trained, nonblinded abstractor. Seizures were defined as an epileptologist's diagnosis of either seizures or status epilepticus on EEG. The proportion of patients with seizures is given with confidence interval95 (CI95). Of 120 included patients, 67 (56%) had a history of epilepsy. Mean age was 52 years (SD, 16), 58% were White, and 61% were male. Within 24 hours, 3% had an EEG diagnostic for seizures. Electroencephalogram was obtained in the ED in 32 (27%) of 120 (CI95, 19%-35%), and 2 (6%) of 32 (CI95, 1%-19%) had seizures. Electroencephalogram was performed inpatient for 88 (73%) of 120 (CI95, 65%-81%), and 2 (2%) of 88 (CI95, 0.5%-7.1%) had seizures. Only 3% of ED patients with suspected seizures or status epilepticus had EEG confirmation of seizures within 24 hours. Early EEG acquisition in the ED may identify a group of patients amenable to ED observation and subsequent discharge from the hospital. Copyright © 2014 Elsevier Inc. All rights reserved.

Use of EEG in critically ill children and neonates in the United States of America.

PubMed

Gaínza-Lein, Marina; Sánchez Fernández, Iván; Loddenkemper, Tobias

2017-06-01

The objective of the study was to estimate the proportion of patients who receive an electroencephalogram (EEG) among five common indications for EEG monitoring in the intensive care unit: traumatic brain injury (TBI), extracorporeal membrane oxygenation (ECMO), cardiac arrest, cardiac surgery and hypoxic-ischemic encephalopathy (HIE). We performed a retrospective cross-sectional descriptive study utilizing the Kids' Inpatient Database (KID) for the years 2010-2012. The KID is the largest pediatric inpatient database in the USA and it is based on discharge reports created by hospitals for billing purposes. We evaluated the use of electroencephalogram (EEG) or video-electroencephalogram in critically ill children who were mechanically ventilated. The KID database had a population of approximately 6,000,000 pediatric admissions. Among 22,127 admissions of critically ill children who had mechanical ventilation, 1504 (6.8%) admissions had ECMO, 9201 (41.6%) TBI, 4068 (18.4%) HIE, 2774 (12.5%) cardiac arrest, and 4580 (20.7%) cardiac surgery. All five conditions had a higher proportion of males, with the highest (69.8%) in the TBI group. The mortality rates ranged from 7.02 to 39.9% (lowest in cardiac surgery and highest in ECMO). The estimated use of EEG was 1.6% in cardiac surgery, 4.1% in TBI, 7.2% in ECMO, 8.2% in cardiac arrest, and 12.1% in HIE, with an overall use of 5.8%. Among common indications for EEG monitoring in critically ill children and neonates, the estimated proportion of patients actually having an EEG is low.

Evaluation of central nervous system in patients with glycogen storage disease type 1a.

PubMed

Aydemir, Yusuf; Gürakan, Figen; Saltık Temizel, İnci Nur; Demir, Hülya; Oğuz, Kader Karlı; Yalnızoğlu, Dilek; Topçu, Meral; Özen, Hasan; Yüce, Aysel

2016-01-01

We aimed to evaluate structure and functions of central nervous system (CNS) in children with glycogen storage disease (GSD) type 1a. Neurological examination, psychometric tests, electroencephalography (EEG), magnetic resonance imaging (MRI), visual evoked potentials (VEP) and brainstem auditory evoked potentials (BAEP) were performed. The results were compared between patients with good and poor metabolic control and healthy children. Twenty-three patients with GSD type 1a were studied. Twelve patients were in poor metabolic control group and 11 patients in good metabolic control group. Five patients had intellectual disability, 10 had EEG abnormalities, seven had abnormal VEP and two had abnormal BAEP results. MRI was abnormal in five patients. There was significant correlation between the number of hypoglycemic attacks and MRI abnormalities. Central nervous system may be affected in GSD type 1a even in patients with normal neurologic examination. Accumulation of abnormal results in patients with poor metabolic control supports the importance of metabolic control in GSD type 1a.

Resting-state EEG power and coherence vary between migraine phases.

PubMed

Cao, Zehong; Lin, Chin-Teng; Chuang, Chun-Hsiang; Lai, Kuan-Lin; Yang, Albert C; Fuh, Jong-Ling; Wang, Shuu-Jiun

2016-12-01

Migraine is characterized by a series of phases (inter-ictal, pre-ictal, ictal, and post-ictal). It is of great interest whether resting-state electroencephalography (EEG) is differentiable between these phases. We compared resting-state EEG energy intensity and effective connectivity in different migraine phases using EEG power and coherence analyses in patients with migraine without aura as compared with healthy controls (HCs). EEG power and isolated effective coherence of delta (1-3.5 Hz), theta (4-7.5 Hz), alpha (8-12.5 Hz), and beta (13-30 Hz) bands were calculated in the frontal, central, temporal, parietal, and occipital regions. Fifty patients with episodic migraine (1-5 headache days/month) and 20 HCs completed the study. Patients were classified into inter-ictal, pre-ictal, ictal, and post-ictal phases (n = 22, 12, 8, 8, respectively), using 36-h criteria. Compared to HCs, inter-ictal and ictal patients, but not pre- or post-ictal patients, had lower EEG power and coherence, except for a higher effective connectivity in fronto-occipital network in inter-ictal patients (p < .05). Compared to data obtained from the inter-ictal group, EEG power and coherence were increased in the pre-ictal group, with the exception of a lower effective connectivity in fronto-occipital network (p < .05). Inter-ictal and ictal patients had decreased EEG power and coherence relative to HCs, which were "normalized" in the pre-ictal or post-ictal groups. Resting-state EEG power density and effective connectivity differ between migraine phases and provide an insight into the complex neurophysiology of migraine.

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.

Cross-Participant EEG-Based Assessment of Cognitive Workload Using Multi-Path Convolutional Recurrent Neural Networks.

PubMed

Hefron, Ryan; Borghetti, Brett; Schubert Kabban, Christine; Christensen, James; Estepp, Justin

2018-04-26

Applying deep learning methods to electroencephalograph (EEG) data for cognitive state assessment has yielded improvements over previous modeling methods. However, research focused on cross-participant cognitive workload modeling using these techniques is underrepresented. We study the problem of cross-participant state estimation in a non-stimulus-locked task environment, where a trained model is used to make workload estimates on a new participant who is not represented in the training set. Using experimental data from the Multi-Attribute Task Battery (MATB) environment, a variety of deep neural network models are evaluated in the trade-space of computational efficiency, model accuracy, variance and temporal specificity yielding three important contributions: (1) The performance of ensembles of individually-trained models is statistically indistinguishable from group-trained methods at most sequence lengths. These ensembles can be trained for a fraction of the computational cost compared to group-trained methods and enable simpler model updates. (2) While increasing temporal sequence length improves mean accuracy, it is not sufficient to overcome distributional dissimilarities between individuals’ EEG data, as it results in statistically significant increases in cross-participant variance. (3) Compared to all other networks evaluated, a novel convolutional-recurrent model using multi-path subnetworks and bi-directional, residual recurrent layers resulted in statistically significant increases in predictive accuracy and decreases in cross-participant variance.

Olfactory Hallucinations without Clinical Motor Activity: A Comparison of Unirhinal with Birhinal Phantosmia

PubMed Central

Henkin, Robert I.; Potolicchio, Samuel J.; Levy, Lucien M.

2013-01-01

Olfactory hallucinations without subsequent myoclonic activity have not been well characterized or understood. Herein we describe, in a retrospective study, two major forms of olfactory hallucinations labeled phantosmias: one, unirhinal, the other, birhinal. To describe these disorders we performed several procedures to elucidate similarities and differences between these processes. From 1272, patients evaluated for taste and smell dysfunction at The Taste and Smell Clinic, Washington, DC with clinical history, neurological and otolaryngological examinations, evaluations of taste and smell function, EEG and neuroradiological studies 40 exhibited cyclic unirhinal phantosmia (CUP) usually without hyposmia whereas 88 exhibited non-cyclic birhinal phantosmia with associated symptomology (BPAS) with hyposmia. Patients with CUP developed phantosmia spontaneously or after laughing, coughing or shouting initially with spontaneous inhibition and subsequently with Valsalva maneuvers, sleep or nasal water inhalation; they had frequent EEG changes usually ipsilateral sharp waves. Patients with BPAS developed phantosmia secondary to several clinical events usually after hyposmia onset with few EEG changes; their phantosmia could not be initiated or inhibited by any physiological maneuver. CUP is uncommonly encountered and represents a newly defined clinical syndrome. BPAS is commonly encountered, has been observed previously but has not been clearly defined. Mechanisms responsible for phantosmia in each group were related to decreased gamma-aminobutyric acid (GABA) activity in specific brain regions. Treatment which activated brain GABA inhibited phantosmia in both groups. PMID:24961619

Cross-Participant EEG-Based Assessment of Cognitive Workload Using Multi-Path Convolutional Recurrent Neural Networks

PubMed Central

Hefron, Ryan; Borghetti, Brett; Schubert Kabban, Christine; Christensen, James; Estepp, Justin

2018-01-01

Applying deep learning methods to electroencephalograph (EEG) data for cognitive state assessment has yielded improvements over previous modeling methods. However, research focused on cross-participant cognitive workload modeling using these techniques is underrepresented. We study the problem of cross-participant state estimation in a non-stimulus-locked task environment, where a trained model is used to make workload estimates on a new participant who is not represented in the training set. Using experimental data from the Multi-Attribute Task Battery (MATB) environment, a variety of deep neural network models are evaluated in the trade-space of computational efficiency, model accuracy, variance and temporal specificity yielding three important contributions: (1) The performance of ensembles of individually-trained models is statistically indistinguishable from group-trained methods at most sequence lengths. These ensembles can be trained for a fraction of the computational cost compared to group-trained methods and enable simpler model updates. (2) While increasing temporal sequence length improves mean accuracy, it is not sufficient to overcome distributional dissimilarities between individuals’ EEG data, as it results in statistically significant increases in cross-participant variance. (3) Compared to all other networks evaluated, a novel convolutional-recurrent model using multi-path subnetworks and bi-directional, residual recurrent layers resulted in statistically significant increases in predictive accuracy and decreases in cross-participant variance. PMID:29701668

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

PubMed

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

2017-03-01

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

Specificity of spontaneous EEG associated with different levels of cognitive and communicative dysfunctions in children.

PubMed

Kozhushko, Nadezhda Ju; Nagornova, Zhanna V; Evdokimov, Sergey A; Shemyakina, Natalia V; Ponomarev, Valery A; Tereshchenko, Ekaterina P; Kropotov, Jury D

2018-06-01

This study aimed to reveal electrophysiological markers of communicative and cognitive dysfunctions of different severity in children with autism spectrum disorder (ASD). Eyes-opened electroencephalograms (EEGs) of 42 children with ASD, divided into two groups according to the severity of their communicative and cognitive dysfunctions (24 with severe and 18 children with less severe ASD), and 70 age-matched controls aged 4-9 years were examined by means of spectral and group independent component (gIC) analyses. A predominance of theta and beta EEG activity in both groups of children with ASD compared to the activity in the control group was found in the global gIC together with a predominance of beta EEG activity in the right occipital region. The quantity of local gICs with enhanced slow and high-frequency EEG activity (within the frontal, temporal, and parietal cortex areas) in children 4-9 years of age might be considered a marker of cognitive and communicative dysfunction severity. Copyright © 2018 Elsevier B.V. All rights reserved.

The effect of alpha rhythm sleep on EEG activity and individuals' attention.

PubMed

Kim, Seon Chill; Lee, Myoung Hee; Jang, Chel; Kwon, Jung Won; Park, Joo Wan

2013-12-01

[Purpose] This study examined whether the alpha rhythm sleep alters the EEG activity and response time in the attention and concentration tasks. [Subjects and Methods] The participants were 30 healthy university students, who were randomly and equally divided into two groups, the experimental and control groups. They were treated using the Happy-sleep device or a sham device, respectively. All participants had a one-week training period. Before and after training sessions, a behavioral task test was performed and EEG alpha waves were measured to confirm the effectiveness of training on cognitive function. [Results] In terms of the behavioral task test, reaction time (RT) variations in the experimental group were significantly larger than in the control group for the attention item. Changes in the EEG alpha power in the experimental group were also significantly larger than those of the control group. [Conclusions] These findings suggest that sleep induced using the Happy-sleep device modestly enhances the ability to pay attention and focus during academic learning.

[INDIVIDUAL EVALUATION OF LORETA ABNORMALITIES IN IDIOPATHIC GENERALIZED EPILEPSY].

PubMed

Clemens, Béla; Puskás, Szilvia; Besenyei, Mónika; Kondákor, István; Hollódy, Katalin; Fogarasi, Andrós; Bense, Katalin; Emri, Miklós; Opposits Gábor; Kovács, Noémi Zsuzsanna; Fekete, István

2016-03-30

Contemporary neuroimaging methods disclosed structural and functional cerebral abnormalities in idiopathic generalized epilepsies (IGEs). However, individual electrical (EEG) abnormalities have not been evaluated yet in IGE patients. IGE patients were investigated in the drug-free condition and after 3-6 month of antiepileptic treatment. To estimate the reproducibility of qEEG variables a retrospective recruited cohort of IGE patients was investigated. 19-channel resting state EEG activity was recorded. For each patient a total of 2 minutes EEG activity was analyzed by LORETA (Low Resolution Electromagnetic Tomography). Raw LORETA values were Z-transformed and projected to a MRI template. Z-values outside within the [+3Z] to [-3Z] range were labelled as statistically abnormal. 1. In drug-free condition, 41-50% of IGE patients showed abnormal LORETA values. 2. Abnormal LORETA findings showed great inter-individual variability. 3. Most abnormal LORETA-findings were symmetrical. 4. Most maximum Z-values were localized to frontal or temporal cortex. 5. Succesfull treatment was mostly coupled with disappearence of LORETA-abnormality, persistent seizures were accompanied by persistent LORETA abnormality. 1. LORETA abnormalities detected in the untreated condition reflect seizure-generating property of the cortex in IGE patients. 2. Maximum LORETA-Z abnormalities were topographically congruent with structural abnormalities reported by other research groups. 3. LORETA might help to investigate drug effects at the whole-brain level.

Automatic detection of rhythmic and periodic patterns in critical care EEG based on American Clinical Neurophysiology Society (ACNS) standardized terminology.

PubMed

Fürbass, F; Hartmann, M M; Halford, J J; Koren, J; Herta, J; Gruber, A; Baumgartner, C; Kluge, T

2015-09-01

Continuous EEG from critical care patients needs to be evaluated time efficiently to maximize the treatment effect. A computational method will be presented that detects rhythmic and periodic patterns according to the critical care EEG terminology (CCET) of the American Clinical Neurophysiology Society (ACNS). The aim is to show that these detected patterns support EEG experts in writing neurophysiological reports. First of all, three case reports exemplify the evaluation procedure using graphically presented detections. Second, 187 hours of EEG from 10 critical care patients were used in a comparative trial study. For each patient the result of a review session using the EEG and the visualized pattern detections was compared to the original neurophysiology report. In three out of five patients with reported seizures, all seizures were reported correctly. In two patients, several subtle clinical seizures with unclear EEG correlation were missed. Lateralized periodic patterns (LPD) were correctly found in 2/2 patients and EEG slowing was correctly found in 7/9 patients. In 8/10 patients, additional EEG features were found including LPDs, EEG slowing, and seizures. The use of automatic pattern detection will assist in review of EEG and increase efficiency. The implementation of bedside surveillance devices using our detection algorithm appears to be feasible and remains to be confirmed in further multicenter studies. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Exploration of Lower Frequency EEG Dynamics and Cortical Alpha Asymmetry in Long-term Rajyoga Meditators

PubMed Central

Sharma, Kanishka; Chandra, Sushil; Dubey, Ashok Kumar

2018-01-01

Background: Rajyoga meditation is taught by Prajapita Brahmakumaris World Spiritual University (Brahmakumaris) and has been followed by more than one million followers across the globe. However, rare studies were conducted on physiological aspects of rajyoga meditation using electroencephalography (EEG). Band power and cortical asymmetry were not studied with Rajyoga meditators. Aims: This study aims to investigate the effect of regular meditation practice on EEG brain dynamics in low-frequency bands of long-term Rajyoga meditators. Settings and Design: Subjects were matched for age in both groups. Lower frequency EEG bands were analyzed in resting and during meditation. Materials and Methods: Twenty-one male long-term meditators (LTMs) and same number of controls were selected to participate in study as par inclusion criteria. Semi high-density EEG was recorded before and during meditation in LTM group and resting in control group. The main outcome of the study was spectral power of alpha and theta bands and cortical (hemispherical) asymmetry calculated using band power. Statistical Analysis: One-way ANOVA was performed to find the significant difference between EEG spectral properties of groups. Pearson's Chi-square test was used to find difference among demographics data. Results: Results reveal high-band power in alpha and theta spectra in meditators. Cortical asymmetry calculated through EEG power was also found to be high in frontal as well as parietal channels. However, no correlation was seen between the experience of meditation (years, hours) practice and EEG indices. Conclusion: Overall findings indicate contribution of smaller frequencies (alpha and theta) while maintaining meditative experience. This suggests a positive impact of meditation on frontal and parietal areas of brain, involved in the processes of regulation of selective and sustained attention as well as provide evidence about their involvement in emotion and cognitive processing. PMID:29343928

A random forest model based classification scheme for neonatal amplitude-integrated EEG.

PubMed

Chen, Weiting; Wang, Yu; Cao, Guitao; Chen, Guoqiang; Gu, Qiufang

2014-01-01

Modern medical advances have greatly increased the survival rate of infants, while they remain in the higher risk group for neurological problems later in life. For the infants with encephalopathy or seizures, identification of the extent of brain injury is clinically challenging. Continuous amplitude-integrated electroencephalography (aEEG) monitoring offers a possibility to directly monitor the brain functional state of the newborns over hours, and has seen an increasing application in neonatal intensive care units (NICUs). This paper presents a novel combined feature set of aEEG and applies random forest (RF) method to classify aEEG tracings. To that end, a series of experiments were conducted on 282 aEEG tracing cases (209 normal and 73 abnormal ones). Basic features, statistic features and segmentation features were extracted from both the tracing as a whole and the segmented recordings, and then form a combined feature set. All the features were sent to a classifier afterwards. The significance of feature, the data segmentation, the optimization of RF parameters, and the problem of imbalanced datasets were examined through experiments. Experiments were also done to evaluate the performance of RF on aEEG signal classifying, compared with several other widely used classifiers including SVM-Linear, SVM-RBF, ANN, Decision Tree (DT), Logistic Regression(LR), ML, and LDA. The combined feature set can better characterize aEEG signals, compared with basic features, statistic features and segmentation features respectively. With the combined feature set, the proposed RF-based aEEG classification system achieved a correct rate of 92.52% and a high F1-score of 95.26%. Among all of the seven classifiers examined in our work, the RF method got the highest correct rate, sensitivity, specificity, and F1-score, which means that RF outperforms all of the other classifiers considered here. The results show that the proposed RF-based aEEG classification system with the combined feature set is efficient and helpful to better detect the brain disorders in newborns.

Effects of Aerobic Exercise on Anxiety Symptoms and Cortical Activity in Patients with Panic Disorder: A Pilot Study

PubMed Central

Lattari, Eduardo; Budde, Henning; Paes, Flávia; Neto, Geraldo Albuquerque Maranhão; Appolinario, José Carlos; Nardi, Antônio Egídio; Murillo-Rodriguez, Eric; Machado, Sérgio

2018-01-01

Background: The effects of the aerobic exercise on anxiety symptoms in patients with Panic Disorder (PD) remain unclear. Thus, the investigation of possible changes in EEG frontal asymmetry could contribute to understand the relationship among exercise, brain and anxiety. Objective: To investigate the acute effects of aerobic exercise on the symptoms of anxiety and the chronic effects of aerobic exercise on severity and symptoms related to PD, besides the changes in EEG frontal asymmetry. Methods: Ten PD patients were divided into two groups, Exercise Group (EG; n=5) and Control Group (CG; n=5), in a randomized allocation. At baseline and post-intervention, they submitted the psychological evaluation through Panic Disorder Severity Scale (PDSS), Beck Anxiety Inventory (BAI), Beck Depression Inventory-II (BDI-II), EEG frontal asymmetry, and maximal oxygen consumption (VO2max). On the second visit, the patients of EG being submitted to the aerobic exercise (treadmill, 25 minutes, and 50-55% of heart rate reserve) and the CG remained seated for the same period of time. Both groups submitted a psychological evaluation with Subjective Units of Distress Scale (SUDS) at baseline, immediately after (Post-0), and after 10 minutes of the rest pause (Post-10). The patients performed 12 sessions of aerobic exercise with 48-72 hours of interval between sessions. Results: In EG, SUDS increased immediately after exercise practice and showed chronic decrease in BAI and BDI-II as well as increased in VO2max (Post-intervention). Conclusion: Aerobic exercise can promote increase in anxiety acutely and regular aerobic exercise promotes reduction in anxiety levels. PMID:29515644

[EEG-correlates of pilots' functional condition in simulated flight dynamics].

PubMed

Kiroy, V N; Aslanyan, E V; Bakhtin, O M; Minyaeva, N R; Lazurenko, D M

2015-01-01

The spectral characteristics of the EEG recorded on two professional pilots in the simulator TU-154 aircraft in flight dynamics, including takeoff, landing and horizontal flight (in particular during difficult conditions) were analyzed. EEG recording was made with frequency band 0.1-70 Hz continuously from 15 electrodes. The EEG recordings were evaluated using analysis of variance and discriminant analysis. Statistical significant of the identified differences and the influence of the main factors and their interactions were evaluated using Greenhouse - Gaiser corrections. It was shown that the spectral characteristics of the EEG are highly informative features of the state of the pilots, reflecting the different flight phases. High validity ofthe differences including individual characteristic, indicates their non-random nature and the possibility of constructing a system of pilots' state control during all phases of flight, based on EEG features.

Stable Sparse Classifiers Identify qEEG Signatures that Predict Learning Disabilities (NOS) Severity

PubMed Central

Bosch-Bayard, Jorge; Galán-García, Lídice; Fernandez, Thalia; Lirio, Rolando B.; Bringas-Vega, Maria L.; Roca-Stappung, Milene; Ricardo-Garcell, Josefina; Harmony, Thalía; Valdes-Sosa, Pedro A.

2018-01-01

In this paper, we present a novel methodology to solve the classification problem, based on sparse (data-driven) regressions, combined with techniques for ensuring stability, especially useful for high-dimensional datasets and small samples number. The sensitivity and specificity of the classifiers are assessed by a stable ROC procedure, which uses a non-parametric algorithm for estimating the area under the ROC curve. This method allows assessing the performance of the classification by the ROC technique, when more than two groups are involved in the classification problem, i.e., when the gold standard is not binary. We apply this methodology to the EEG spectral signatures to find biomarkers that allow discriminating between (and predicting pertinence to) different subgroups of children diagnosed as Not Otherwise Specified Learning Disabilities (LD-NOS) disorder. Children with LD-NOS have notable learning difficulties, which affect education but are not able to be put into some specific category as reading (Dyslexia), Mathematics (Dyscalculia), or Writing (Dysgraphia). By using the EEG spectra, we aim to identify EEG patterns that may be related to specific learning disabilities in an individual case. This could be useful to develop subject-based methods of therapy, based on information provided by the EEG. Here we study 85 LD-NOS children, divided in three subgroups previously selected by a clustering technique over the scores of cognitive tests. The classification equation produced stable marginal areas under the ROC of 0.71 for discrimination between Group 1 vs. Group 2; 0.91 for Group 1 vs. Group 3; and 0.75 for Group 2 vs. Group1. A discussion of the EEG characteristics of each group related to the cognitive scores is also presented. PMID:29379411

Stable Sparse Classifiers Identify qEEG Signatures that Predict Learning Disabilities (NOS) Severity.

PubMed

Bosch-Bayard, Jorge; Galán-García, Lídice; Fernandez, Thalia; Lirio, Rolando B; Bringas-Vega, Maria L; Roca-Stappung, Milene; Ricardo-Garcell, Josefina; Harmony, Thalía; Valdes-Sosa, Pedro A

2017-01-01

In this paper, we present a novel methodology to solve the classification problem, based on sparse (data-driven) regressions, combined with techniques for ensuring stability, especially useful for high-dimensional datasets and small samples number. The sensitivity and specificity of the classifiers are assessed by a stable ROC procedure, which uses a non-parametric algorithm for estimating the area under the ROC curve. This method allows assessing the performance of the classification by the ROC technique, when more than two groups are involved in the classification problem, i.e., when the gold standard is not binary. We apply this methodology to the EEG spectral signatures to find biomarkers that allow discriminating between (and predicting pertinence to) different subgroups of children diagnosed as Not Otherwise Specified Learning Disabilities (LD-NOS) disorder. Children with LD-NOS have notable learning difficulties, which affect education but are not able to be put into some specific category as reading (Dyslexia), Mathematics (Dyscalculia), or Writing (Dysgraphia). By using the EEG spectra, we aim to identify EEG patterns that may be related to specific learning disabilities in an individual case. This could be useful to develop subject-based methods of therapy, based on information provided by the EEG. Here we study 85 LD-NOS children, divided in three subgroups previously selected by a clustering technique over the scores of cognitive tests. The classification equation produced stable marginal areas under the ROC of 0.71 for discrimination between Group 1 vs. Group 2; 0.91 for Group 1 vs. Group 3; and 0.75 for Group 2 vs. Group1. A discussion of the EEG characteristics of each group related to the cognitive scores is also presented.

Iron Deficiency (ID) at Both Birth and 9 Months Predicts Right Frontal EEG Asymmetry in Infancy

PubMed Central

Armony-Sivan, Rinat; Zhu, Bingquan; Clark, Katy M.; Richards, Blair; Ji, Chai; Kaciroti, Niko; Shao, Jie

2016-01-01

This study considered effects of timing and duration of iron deficiency (ID) on frontal EEG asymmetry in infancy. In healthy term Chinese infants, EEG was recorded at 9 months in three experimental conditions: baseline, peek-a-boo, and stranger approach. Eighty infants provided data for all conditions. Prenatal ID was defined as low cord ferritin or high ZPP/H. Postnatal ID was defined as ≥ two abnormal iron measures at 9 months. Study groups were pre- and postnatal ID, prenatal ID only, postnatal ID only, and not ID. GLM repeated measure analysis showed a main effect for iron group. The pre- and postnatal ID group had negative asymmetry scores, reflecting right frontal EEG asymmetry (mean ±SE: −.18 ±.07) versus prenatal ID only (.00 ±.04), postnatal ID only (.03 ±.04), and not ID (.02 ±.04). Thus, ID at both birth and 9 months was associated with right frontal EEG asymmetry, a neural correlate of behavioral withdrawal and negative emotions. PMID:26668100

Modulation of EEG Theta Band Signal Complexity by Music Therapy

NASA Astrophysics Data System (ADS)

Bhattacharya, Joydeep; Lee, Eun-Jeong

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

Recurrence quantification analysis of electroencephalograph signals during standard tasks of Waterloo-Stanford group scale of hypnotic susceptibility.

PubMed

Yargholi, Elahe'; Nasrabadi, Ali Motie

2015-01-01

The purpose of this study was to apply RQA (recurrence quantification analysis) on hypnotic electroencephalograph (EEG) signals recorded after hypnotic induction while subjects were doing standard tasks of the Waterloo-Stanford Group Scale (WSGS) of hypnotic susceptibility. Then recurrence quantifiers were used to analyse the influence of hypnotic depth on EEGs. By the application of this method, the capability of tasks to distinguish subjects of different hypnotizability levels was determined. Besides, medium hypnotizable subjects showed the highest disposition to be inducted by hypnotizer. Similarities between brain governing dynamics during tasks of the same type were also observed. The present study demonstrated two remarkable innovations; investigating the EEGs of the hypnotized as doing mental tasks of Waterloo-Stanford Group Scale (WSGS) and applying RQA on hypnotic EEGs.

Time-linked concurrence of sleep bruxism, periodic limb movements, and EEG arousals in sleep bruxers and healthy controls.

PubMed

van der Zaag, Jacques; Naeije, Machiel; Wicks, Darrel J; Hamburger, Hans L; Lobbezoo, Frank

2014-01-01

Sleep bruxism (SB) and periodic limb movements during sleep (PLMS) may have a common underlying neurophysiologic mechanism, especially in relation to the occurrence of sleep-related electroencephalographic (EEG) arousals. To test this hypothesis, three research questions were assessed. First, it was assessed whether PLMS events occur more frequently in SB patients than in individuals without SB. Second, the question was put forward whether the combined presence of SB and PLMS events is more common than that of isolated SB or PLMS events in a group of SB patients. Third, as to further unravel the possible role of EEG arousals in the underlying neurophysiologic mechanism of SB and PLMS, it was assessed in a group of SB patients whether combined SB/PLMS events with associated EEG arousals are more common than those without associated EEG arousals. Positive answers to these questions could suggest a common neurophysiological basis for both movement disorders. Seventeen SB patients and 11 healthy controls were polysomnographically studied. SB, PLMS, and EEG arousals were scored. An association was noted when the occurrence was within a 3-s association zone. The PLMS index was higher in SB patients than in healthy controls (P < 0.001). Within the group of SB patients, the combined SB/PLMS index was higher than the isolated SB index (P < 0.001) and the isolated PLMS index (P = 0.018). Similarly, the combined SB/PLMS index with EEG arousal was higher than the combined SB/PLMS index without EEG arousal in SB patients (P < 0.001). The results of this study indicate that SB, PLMS, and EEG arousals commonly concur during sleep in a time-linked manner. SB and PLMS probably have a common underlying neurophysiological mechanism.

Human interaction with robotic systems: performance and workload evaluations.

PubMed

Reinerman-Jones, L; Barber, D J; Szalma, J L; Hancock, P A

2017-10-01

We first tested the effect of differing tactile informational forms (i.e. directional cues vs. static cues vs. dynamic cues) on objective performance and perceived workload in a collaborative human-robot task. A second experiment evaluated the influence of task load and informational message type (i.e. single words vs. grouped phrases) on that same collaborative task. In both experiments, the relationship of personal characteristics (attentional control and spatial ability) to performance and workload was also measured. In addition to objective performance and self-report of cognitive load, we evaluated different physiological responses in each experiment. Results showed a performance-workload association for directional cues, message type and task load. EEG measures however, proved generally insensitive to such task load manipulations. Where significant EEG effects were observed, right hemisphere amplitude differences predominated, although unexpectedly these latter relationships were negative. Although EEG measures were partially associated with performance, they appear to possess limited utility as measures of workload in association with tactile displays. Practitioner Summary: As practitioners look to take advantage of innovative tactile displays in complex operational realms like human-robotic interaction, associated performance effects are mediated by cognitive workload. Despite some patterns of association, reliable reflections of operator state can be difficult to discern and employ as the number, complexity and sophistication of these respective measures themselves increase.

Moderate unconjugated hyperbilirubinemia causes a transient but delayed suppression of amplitude-integrated electroencephalographic activity in preterm infants.

PubMed

Ter Horst, Hendrik J; Bos, Arend F; Duijvendijk, Jildou; Hulzebos, Christian V

2012-01-01

Unconjugated hyperbilirubinemia occurs frequently in preterm infants and may result in bilirubin encephalopathy. Amplitude-integrated electroencephalography (aEEG) is used to evaluate brain function in newborns. To investigate the influence of total serum bilirubin (TSB) on the aEEG amplitude of preterm infants and to evaluate aEEG as a noninvasive method to identify acute bilirubin encephalopathy. We performed a prospective observational study of 34 infants with a gestational age (GA) of 26-31 6/7 weeks. Infants had aEEG recordings on the 1st-5th, 8th and 15th day after birth. Infants with asphyxia, intraventricular hemorrhage >grade I or circulatory insufficiency were excluded. aEEG was evaluated by calculating the mean 5th, 50th and 95th centiles of the aEEG amplitudes. TSB peaked on the 4th day after birth. There was no synchronous relationship between TSB and aEEG amplitudes. The 5th, 50th, and 95th aEEG amplitude centiles on the 8th day correlated negatively with the TSB peak value (r = -0.37, p = 0.048; r = -0.60, p = 0.001; r = -0.44, p = 0.017, respectively), irrespective of GA. The 5th and 50th aEEG amplitude centiles increased with increasing GA (r = 0.45, p < 0.001, and r = 0.26, p < 0.001, respectively) and postnatal age (r = 0.25, p < 0.001, and r = 0.16, p = 0.023, respectively). TSB had no direct effect on aEEG amplitudes in preterm infants. There is, however, a delayed effect on electrocerebral activity in the 2nd week after birth. Copyright © 2012 S. Karger AG, Basel.

Reappraisal of abnormal EEG findings in children with ADHD: on the relationship between ADHD and epileptiform discharges.

PubMed

Kanazawa, Osamu

2014-12-01

Attention-deficit hyperactivity disorder is suggested to be closely related to epilepsy. A recent large-scale study revealed that ADHD in children is often accompanied by epilepsy. In Japan, methylphenidate (MPH) as a sustained-action tablet and atomoxetine (ATX) became commercially available as medications for children recently. Since then, the number of prescriptions of both medicines has increased rapidly. Methylphenidate, as a psychostimulant, has been a source of concern because of the perceived lowered threshold for convulsions in children. Based on this background, reappraisal of EEG findings in children with ADHD is important in order to detect indications of potential comorbid epilepsy and to investigate the developmental mechanisms of the neurophysiological manifestations in patients with ADHD. EEG findings in children newly diagnosed with ADHD and their relationship with clinical findings were investigated. The author evaluated 208 patients with ADHD newly diagnosed between 2008 and 2013. Of these, there were 145 patients for whom EEG findings were obtained along with a clinical follow-up for at least three months. Patients with IQ<70 were excluded in order to obtain a homogenous group of patients with ADHD. The male-to-female ratio was 130:15, and the age range was between 5 years, 9 months and 19 years, 9 months, with mean age of 11 years, 4 months. The results revealed that about half (48.3%) of the children with ADHD had abnormal EEG findings and that 22.1% of them had epileptiform discharges. Patients without comorbidity of autism spectrum disorder (ore homogenous group with ADHD) were especially likely to show abnormal EEG findings (51.0%) including epileptiform discharges (24.5%). Afebrile seizures, that is, epileptic seizures, occurred in a boy three days after commencement of administration with MPH as a sustained-action tablet. In four patients with a past history of epilepsy, neither relapse of EEG abnormality nor epileptic seizures were observed during the follow-up period. There was to be a significantly close relationship between ADHD and epileptiform discharges. Therefore, in patients with ADHD, it is important to obtain more precise information about seizures and presence of epilepsy from the personal and family histories, as well as to undertake a thorough EEG examination. Copyright © 2014 Elsevier Inc. All rights reserved.

Different quantitative EEG alterations induced by TBI among patients with different APOE genotypes.

PubMed

Jiang, Li; Yin, Xiaohong; Yin, Cheng; Zhou, Shuai; Dan, Wei; Sun, Xiaochuan

2011-11-14

Although several studies have revealed the EEG alterations in AD and TBI patients, the influence of APOE (apolipoprotein E) genotype in EEG at the early stage of TBI has not been reported yet. We have previously studied EEG alterations caused by TBI among different APOE genotype carriers. In this study, we firstly investigated the relationship between APOE polymorphisms and quantitative EEG (QEEG) changes after TBI. A total of 118 consecutive TBI patients with a Glasgow Coma Scale (GCS) of 9 or higher were recruited, and 40 normal adults were also included as a control group. APOE genotype was determined by PCR-RFLP for each subject, and QEEG recordings were performed in rest, relaxed, awake and with eyes closed in normal subjects and TBI patients during 1-3 days after TBI. In the normal control group, both APOEɛ4 carriers and non-carriers had normal EEG, and no significant difference of QEEG data was found between APOEɛ4 carriers and non-carriers. But in the TBI group, APOEɛ4 carriers had more focal or global irregular slow wave activities than APOEɛ4 non-carriers. APOE gene did not influence brain electrical activity under normal conditions, but TBI can induce different alterations among different APOE gene carriers, and APOEɛ4 allele enhances the EEG abnormalities at the early stage of TBI. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Neurophysiological Pharmacodynamic Measures of Groups and Individuals Extended from Simple Cognitive Tasks to More “Lifelike” Activities

PubMed Central

Gevins, Alan; Chan, Cynthia S.; Jiang, An; Sam-Vargas, Lita

2012-01-01

Objective Extend a method to track neurophysiological pharmacodynamics during repetitive cognitive testing to a more complex “lifelike” task. Methods Alcohol was used as an exemplar psychoactive substance. An equation, derived in an exploratory analysis to detect alcohol’s EEGs effects during repetitive cognitive testing, was validated in a confirmatory study on a new group whose EEGs after alcohol and placebo were recorded during working memory testing and while operating an automobile driving simulator. Results The equation recognized alcohol by combining five times beta plus theta power. It worked well (p<.0001) when applied to both tasks in the confirmatory group. The maximum EEG effect occurred 2–2.5 hours after drinking (>1hr after peak BAC) and remained at 90% at 3.5–4 hours (BAC <50% of peak). Individuals varied in the magnitude and timing of the EEG effect. Conclusion The equation tracked the EEG response to alcohol in the confirmatory study during both repetitive cognitive testing and a more complex “lifelike” task. The EEG metric was more sensitive to alcohol than several autonomic physiological measures, task performance measures or self-reports. Significance Using EEG as a biomarker to track neurophysiological pharmacodynamics during complex “lifelike” activities may prove useful for assessing how drugs affect integrated brain functioning. PMID:23194853

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

PubMed Central

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

1995-01-01

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

EMG parameters and EEG α Index change at fatigue period during different types of muscle contraction

NASA Astrophysics Data System (ADS)

Zhang, Li; Zhou, Bin; Song, Gaoqing

2010-10-01

The purpose of this study is to measure and analyze the characteristics in change of EMG and EEG parameters at muscle fatigue period in participants with different exercise capacity. Twenty participants took part in the tests. They were divided into two groups, Group A (constant exerciser) and Group B (seldom-exerciser). MVC dynamic and 1/3 isometric exercises were performed; EMG and EEG signals were recorded synchronously during different type of muscle contraction. Results indicated that values of MVC, RMS and IEMG in Group A were greater than Group B, but isometric exercise time was shorter than the time of dynamic exercise although its intensity was light. Turning point of IEMG and α Index occurred synchronously during constant muscle contraction of isometric or dynamic exercise. It is concluded that IEMG turning point may be an indication to justify muscle fatigue. Synchronization of EEG and EMG reflects its common characteristics on its bio-electric change.

EMG parameters and EEG α Index change at fatigue period during different types of muscle contraction

NASA Astrophysics Data System (ADS)

Zhang, Li; Zhou, Bin; Song, Gaoqing

2011-03-01

The purpose of this study is to measure and analyze the characteristics in change of EMG and EEG parameters at muscle fatigue period in participants with different exercise capacity. Twenty participants took part in the tests. They were divided into two groups, Group A (constant exerciser) and Group B (seldom-exerciser). MVC dynamic and 1/3 isometric exercises were performed; EMG and EEG signals were recorded synchronously during different type of muscle contraction. Results indicated that values of MVC, RMS and IEMG in Group A were greater than Group B, but isometric exercise time was shorter than the time of dynamic exercise although its intensity was light. Turning point of IEMG and α Index occurred synchronously during constant muscle contraction of isometric or dynamic exercise. It is concluded that IEMG turning point may be an indication to justify muscle fatigue. Synchronization of EEG and EMG reflects its common characteristics on its bio-electric change.

EEG neurofeedback effects in the treatment of adolescent anorexia nervosa.

PubMed

Lackner, Nina; Unterrainer, Human-Friedrich; Skliris, Dimitris; Shaheen, Sandra; Dunitz-Scheer, Marguerite; Wood, Guilherme; Scheer, Peter Jaron Zwi; Wallner-Liebmann, Sandra Johanna; Neuper, Christa

2016-01-01

A pre-post design including 22 females was used to evaluate the effectiveness of neurofeedback in the treatment of adolescent anorexia nervosa. Resting EEG measures and a psychological test-battery assessing eating behavior traits, clinical symptoms, emotionality, and mood were obtained. While both the experimental (n = 10) and control group (n = 12) received their usual maintenance treatment, the experimental group received 10 sessions of individual alpha frequency training over a period of 5 weeks as additional treatment. Significant training effects were shown in eating behavior traits, emotion regulation, and in relative theta power in the eyes closed condition. Although the results are limited due to the small sample size, these are the first empirical data demonstrating the benefits of neurofeedback as a treatment adjunct in individuals with anorexia nervosa.

Early and Later Life Stress Alter Brain Activity and Sleep in Rats

PubMed Central

Mrdalj, Jelena; Pallesen, Ståle; Milde, Anne Marita; Jellestad, Finn Konow; Murison, Robert; Ursin, Reidun; Bjorvatn, Bjørn; Grønli, Janne

2013-01-01

Exposure to early life stress may profoundly influence the developing brain in lasting ways. Neuropsychiatric disorders associated with early life adversity may involve neural changes reflected in EEG power as a measure of brain activity and disturbed sleep. The main aim of the present study was for the first time to characterize possible changes in adult EEG power after postnatal maternal separation in rats. Furthermore, in the same animals, we investigated how EEG power and sleep architecture were affected after exposure to a chronic mild stress protocol. During postnatal day 2–14 male rats were exposed to either long maternal separation (180 min) or brief maternal separation (10 min). Long maternally separated offspring showed a sleep-wake nonspecific reduction in adult EEG power at the frontal EEG derivation compared to the brief maternally separated group. The quality of slow wave sleep differed as the long maternally separated group showed lower delta power in the frontal-frontal EEG and a slower reduction of the sleep pressure. Exposure to chronic mild stress led to a lower EEG power in both groups. Chronic exposure to mild stressors affected sleep differently in the two groups of maternal separation. Long maternally separated offspring showed more total sleep time, more episodes of rapid eye movement sleep and higher percentage of non-rapid eye movement episodes ending in rapid eye movement sleep compared to brief maternal separation. Chronic stress affected similarly other sleep parameters and flattened the sleep homeostasis curves in all offspring. The results confirm that early environmental conditions modulate the brain functioning in a long-lasting way. PMID:23922857

Feasibility of imaging epileptic seizure onset with EIT and depth electrodes.

PubMed

Witkowska-Wrobel, Anna; Aristovich, Kirill; Faulkner, Mayo; Avery, James; Holder, David

2018-06-01

Imaging ictal and interictal activity with Electrical Impedance Tomography (EIT) using intracranial electrode mats has been demonstrated in animal models of epilepsy. In human epilepsy subjects undergoing presurgical evaluation, depth electrodes are often preferred. The purpose of this work was to evaluate the feasibility of using EIT to localise epileptogenic areas with intracranial electrodes in humans. The accuracy of localisation of the ictal onset zone was evaluated in computer simulations using 9M element FEM models derived from three subjects. 5 mm radius perturbations imitating a single seizure onset event were placed in several locations forming two groups: under depth electrode coverage and in the contralateral hemisphere. Simulations were made for impedance changes of 1% expected for neuronal depolarisation over milliseconds and 10% for cell swelling over seconds. Reconstructions were compared with EEG source modelling for a radially orientated dipole with respect to the closest EEG recording contact. The best accuracy of EIT was obtained using all depth and 32 scalp electrodes, greater than the equivalent accuracy with EEG inverse source modelling. The localisation error was 5.2 ± 1.8, 4.3 ± 0 and 46.2 ± 25.8 mm for perturbations within the volume enclosed by depth electrodes and 29.6 ± 38.7, 26.1 ± 36.2, 54.0 ± 26.2 mm for those without (EIT 1%, 10% change, EEG source modelling, n = 15 in 3 subjects, p < 0.01). As EIT was insensitive to source dipole orientation, all 15 perturbations within the volume enclosed by depth electrodes were localised, whereas the standard clinical method of visual inspection of EEG voltages, only localised 8 out of 15 cases. This suggests that adding EIT to SEEG measurements could be beneficial in localising the onset of seizures. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Analysis of absence seizure generation using EEG spatial-temporal regularity measures.

PubMed

Mammone, Nadia; Labate, Domenico; Lay-Ekuakille, Aime; Morabito, Francesco C

2012-12-01

Epileptic seizures are thought to be generated and to evolve through an underlying anomaly of synchronization in the activity of groups of neuronal populations. The related dynamic scenario of state transitions is revealed by detecting changes in the dynamical properties of Electroencephalography (EEG) signals. The recruitment procedure ending with the crisis can be explored through a spatial-temporal plot from which to extract suitable descriptors that are able to monitor and quantify the evolving synchronization level from the EEG tracings. In this paper, a spatial-temporal analysis of EEG recordings based on the concept of permutation entropy (PE) is proposed. The performance of PE are tested on a database of 24 patients affected by absence (generalized) seizures. The results achieved are compared to the dynamical behavior of the EEG of 40 healthy subjects. Being PE a feature which is dependent on two parameters, an extensive study of the sensitivity of the performance of PE with respect to the parameters' setting was carried out on scalp EEG. Once the optimal PE configuration was determined, its ability to detect the different brain states was evaluated. According to the results here presented, it seems that the widely accepted model of "jump" transition to absence seizure should be in some cases coupled (or substituted) by a gradual transition model characteristic of self-organizing networks. Indeed, it appears that the transition to the epileptic status is heralded before the preictal state, ever since the interictal stages. As a matter of fact, within the limits of the analyzed database, the frontal-temporal scalp areas appear constantly associated to PE levels higher compared to the remaining electrodes, whereas the parieto-occipital areas appear associated to lower PE values. The EEG of healthy subjects neither shows any similar dynamic behavior nor exhibits any recurrent portrait in PE topography.

The effectiveness of a staff education program on the use of continuous EEG with patients in neuroscience intensive care units.

PubMed

Seiler, Lisa; Fields, Jennifer; Peach, Elizabeth; Zwerin, Suzanne; Savage, Christine

2012-04-01

Approximately a third of patients in neuroscience intensive care units (ICUs) experience subclinical seizures and, as a result, are at higher risk for poor outcomes. The use of continuous electroencephalography (cEEG) monitoring can help nurses detect seizure activity and initiate early prevention. Nurse competency in the use of cEEG is important to facilitate effective bedside monitoring. The objective of this study was to evaluate the effectiveness of a staff educational program aimed at improving the knowledge of nurses in the use of cEEG monitoring in adults. A quasi-experimental pretest/posttest 1-group design was utilized. Neuroscience ICU registered nurses, whose experience ranged from 2 months to 24 years, participated in the study. Participants completed a pretest on seizure knowledge and the use of cEEG monitoring. Participants received a 4-hour educational session on the use of cEEG monitoring. Immediately after the program and again 1 month later, they completed a posttest. Test scores improved significantly from pretest to the first posttest (t = -15.093, p < .001). Although there was a slight decline in the mean score from the posttest to the 1-month follow-up, posttest scores were significantly better than the pretest score (t = -12.42, df = 44, p < .001). Whereas years of experience correlated positively to the pretest score, after the intervention, no such correlation was evident. The results demonstrated that an educational program improved the competency of nurses in the use of cEEG with adult patients in a neuroscience ICU and that this knowledge was sustained over time. Further research is needed to demonstrate the effectiveness of this intervention in other settings.

Detection of Intracranial Signatures of Interictal Epileptiform Discharges from Concurrent Scalp EEG.

PubMed

Spyrou, Loukianos; Martín-Lopez, David; Valentín, Antonio; Alarcón, Gonzalo; Sanei, Saeid

2016-06-01

Interictal epileptiform discharges (IEDs) are transient neural electrical activities that occur in the brain of patients with epilepsy. A problem with the inspection of IEDs from the scalp electroencephalogram (sEEG) is that for a subset of epileptic patients, there are no visually discernible IEDs on the scalp, rendering the above procedures ineffective, both for detection purposes and algorithm evaluation. On the other hand, intracranially placed electrodes yield a much higher incidence of visible IEDs as compared to concurrent scalp electrodes. In this work, we utilize concurrent scalp and intracranial EEG (iEEG) from a group of temporal lobe epilepsy (TLE) patients with low number of scalp-visible IEDs. The aim is to determine whether by considering the timing information of the IEDs from iEEG, the resulting concurrent sEEG contains enough information for the IEDs to be reliably distinguished from non-IED segments. We develop an automatic detection algorithm which is tested in a leave-subject-out fashion, where each test subject's detection algorithm is based on the other patients' data. The algorithm obtained a [Formula: see text] accuracy in recognizing scalp IED from non-IED segments with [Formula: see text] accuracy when trained and tested on the same subject. Also, it was able to identify nonscalp-visible IED events for most patients with a low number of false positive detections. Our results represent a proof of concept that IED information for TLE patients is contained in scalp EEG even if they are not visually identifiable and also that between subject differences in the IED topology and shape are small enough such that a generic algorithm can be used.

Neurophysiological correlates of depressive symptoms in young adults: A quantitative EEG study.

PubMed

Lee, Poh Foong; Kan, Donica Pei Xin; Croarkin, Paul; Phang, Cheng Kar; Doruk, Deniz

2018-01-01

There is an unmet need for practical and reliable biomarkers for mood disorders in young adults. Identifying the brain activity associated with the early signs of depressive disorders could have important diagnostic and therapeutic implications. In this study we sought to investigate the EEG characteristics in young adults with newly identified depressive symptoms. Based on the initial screening, a total of 100 participants (n = 50 euthymic, n = 50 depressive) underwent 32-channel EEG acquisition. Simple logistic regression and C-statistic were used to explore if EEG power could be used to discriminate between the groups. The strongest EEG predictors of mood using multivariate logistic regression models. Simple logistic regression analysis with subsequent C-statistics revealed that only high-alpha and beta power originating from the left central cortex (C3) have a reliable discriminative value (ROC curve >0.7 (70%)) for differentiating the depressive group from the euthymic group. Multivariate regression analysis showed that the single most significant predictor of group (depressive vs. euthymic) is the high-alpha power over C3 (p = 0.03). The present findings suggest that EEG is a useful tool in the identification of neurophysiological correlates of depressive symptoms in young adults with no previous psychiatric history. Our results could guide future studies investigating the early neurophysiological changes and surrogate outcomes in depression. Copyright © 2017 Elsevier Ltd. All rights reserved.

Group Independent Component Analysis (gICA) and Current Source Density (CSD) in the study of EEG in ADHD adults.

PubMed

Ponomarev, Valery A; Mueller, Andreas; Candrian, Gian; Grin-Yatsenko, Vera A; Kropotov, Juri D

2014-01-01

To investigate the performance of the spectral analysis of resting EEG, Current Source Density (CSD) and group independent components (gIC) in diagnosing ADHD adults. Power spectra of resting EEG, CSD and gIC (19 channels, linked ears reference, eyes open/closed) from 96 ADHD and 376 healthy adults were compared between eyes open and eyes closed conditions, and between groups of subjects. Pattern of differences in gIC and CSD spectral power between conditions was approximately similar, whereas it was more widely spatially distributed for EEG. Size effect (Cohen's d) of differences in gIC and CSD spectral power between groups of subjects was considerably greater than in the case of EEG. Significant reduction of gIC and CSD spectral power depending on conditions was found in ADHD patients. Reducing power in a wide frequency range in the fronto-central areas is a common phenomenon regardless of whether the eyes were open or closed. Spectral power of local EEG activity isolated by gICA or CSD in the fronto-central areas may be a suitable marker for discrimination of ADHD and healthy adults. Spectral analysis of gIC and CSD provides better sensitivity to discriminate ADHD and healthy adults. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

[The changes of EEG correlation synchrony at depressive disorder of psychogenic type].

PubMed

Kulaichev, A P; Iznak, A F; Iznak, E V; Kornilov, V V; Sorokin, S A

2014-01-01

In this work we use the alternative method of assessing the EEG-synchrony which previously has proved its high sensitivity to the differentiation of psychopathological and functional states. The original recording of EEG had been performed in the state of quiet wakefulness with eyes closed for two groups of examinees/patients at the age of 49-82 years: a group of normal subjects (n = 29) and the group of subjects with depressive deviations of F43.21 category according to ICD-10 (n = 51). As a result of research it is received the comprehensive picture of significant topographical, interhemispheric and regional differences between groups of norm and depression. One of basic features of the obtained integrated picture is existence at a depression of the extended zones of reduced EEG-synchrony covering the entire premedial region in the frontal-occiptal direction, including intrahemispheric connections as well as lateral frontal-temporal connections in both hemispheres. It testifies to the deep deprivation with depression frontal-occipital and interhemispheric interaction. As a compensatory reaction during depression the increase of synchrony in axial aimed intrahemispheric pairs of derivations. It is noted the similarity of changes in EEG-synchrony topography of depression to those observed in schizophrenia. The used method has provided close to 100% reliability of the classification of the EEG norms and depressive deviations, which makes possible and promising its use as an auxiliary quantitative differential indicator.

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 © 2015 Elsevier Inc. All rights reserved.

FACET - a "Flexible Artifact Correction and Evaluation Toolbox" for concurrently recorded EEG/fMRI data.

PubMed

Glaser, Johann; Beisteiner, Roland; Bauer, Herbert; Fischmeister, Florian Ph S

2013-11-09

In concurrent EEG/fMRI recordings, EEG data are impaired by the fMRI gradient artifacts which exceed the EEG signal by several orders of magnitude. While several algorithms exist to correct the EEG data, these algorithms lack the flexibility to either leave out or add new steps. The here presented open-source MATLAB toolbox FACET is a modular toolbox for the fast and flexible correction and evaluation of imaging artifacts from concurrently recorded EEG datasets. It consists of an Analysis, a Correction and an Evaluation framework allowing the user to choose from different artifact correction methods with various pre- and post-processing steps to form flexible combinations. The quality of the chosen correction approach can then be evaluated and compared to different settings. FACET was evaluated on a dataset provided with the FMRIB plugin for EEGLAB using two different correction approaches: Averaged Artifact Subtraction (AAS, Allen et al., NeuroImage 12(2):230-239, 2000) and the FMRI Artifact Slice Template Removal (FASTR, Niazy et al., NeuroImage 28(3):720-737, 2005). Evaluation of the obtained results were compared to the FASTR algorithm implemented in the EEGLAB plugin FMRIB. No differences were found between the FACET implementation of FASTR and the original algorithm across all gradient artifact relevant performance indices. The FACET toolbox not only provides facilities for all three modalities: data analysis, artifact correction as well as evaluation and documentation of the results but it also offers an easily extendable framework for development and evaluation of new approaches.

FACET – a “Flexible Artifact Correction and Evaluation Toolbox” for concurrently recorded EEG/fMRI data

PubMed Central

2013-01-01

Background In concurrent EEG/fMRI recordings, EEG data are impaired by the fMRI gradient artifacts which exceed the EEG signal by several orders of magnitude. While several algorithms exist to correct the EEG data, these algorithms lack the flexibility to either leave out or add new steps. The here presented open-source MATLAB toolbox FACET is a modular toolbox for the fast and flexible correction and evaluation of imaging artifacts from concurrently recorded EEG datasets. It consists of an Analysis, a Correction and an Evaluation framework allowing the user to choose from different artifact correction methods with various pre- and post-processing steps to form flexible combinations. The quality of the chosen correction approach can then be evaluated and compared to different settings. Results FACET was evaluated on a dataset provided with the FMRIB plugin for EEGLAB using two different correction approaches: Averaged Artifact Subtraction (AAS, Allen et al., NeuroImage 12(2):230–239, 2000) and the FMRI Artifact Slice Template Removal (FASTR, Niazy et al., NeuroImage 28(3):720–737, 2005). Evaluation of the obtained results were compared to the FASTR algorithm implemented in the EEGLAB plugin FMRIB. No differences were found between the FACET implementation of FASTR and the original algorithm across all gradient artifact relevant performance indices. Conclusion The FACET toolbox not only provides facilities for all three modalities: data analysis, artifact correction as well as evaluation and documentation of the results but it also offers an easily extendable framework for development and evaluation of new approaches. PMID:24206927

Attention-Induced Deactivations in Very Low Frequency EEG Oscillations: Differential Localisation According to ADHD Symptom Status

PubMed Central

Broyd, Samantha J.; Helps, Suzannah K.; Sonuga-Barke, Edmund J. S.

2011-01-01

Background The default-mode network (DMN) is characterised by coherent very low frequency (VLF) brain oscillations. The cognitive significance of this VLF profile remains unclear, partly because of the temporally constrained nature of the blood oxygen-level dependent (BOLD) signal. Previously we have identified a VLF EEG network of scalp locations that shares many features of the DMN. Here we explore the intracranial sources of VLF EEG and examine their overlap with the DMN in adults with high and low ADHD ratings. Methodology/Principal Findings DC-EEG was recorded using an equidistant 66 channel electrode montage in 25 adult participants with high- and 25 participants with low-ratings of ADHD symptoms during a rest condition and an attention demanding Eriksen task. VLF EEG power was calculated in the VLF band (0.02 to 0.2 Hz) for the rest and task condition and compared for high and low ADHD participants. sLORETA was used to identify brain sources associated with the attention-induced deactivation of VLF EEG power, and to examine these sources in relation to ADHD symptoms. There was significant deactivation of VLF EEG power between the rest and task condition for the whole sample. Using s-LORETA the sources of this deactivation were localised to medial prefrontal regions, posterior cingulate cortex/precuneus and temporal regions. However, deactivation sources were different for high and low ADHD groups: In the low ADHD group attention-induced VLF EEG deactivation was most significant in medial prefrontal regions while for the high ADHD group this deactivation was predominantly localised to the temporal lobes. Conclusions/Significance Attention-induced VLF EEG deactivations have intracranial sources that appear to overlap with those of the DMN. Furthermore, these seem to be related to ADHD symptom status, with high ADHD adults failing to significantly deactivate medial prefrontal regions while at the same time showing significant attenuation of VLF EEG power in temporal lobes. PMID:21408092

Discovering EEG resting state alterations of semantic dementia.

PubMed

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

2016-05-01

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

Levetiracetam versus phenytoin for seizure prophylaxis in severe traumatic brain injury

PubMed Central

Jones, Kristen E.; Puccio, Ava M.; Harshman, Kathy J.; Falcione, Bonnie; Benedict, Neal; Jankowitz, Brian T.; Stippler, Martina; Fischer, Michael; Sauber-Schatz, Erin K.; Fabio, Anthony; Darby, Joseph M.; Okonkwo, David O.

2013-01-01

Object Current standard of care for patients with severe traumatic brain injury (TBI) is prophylactic treatment with phenytoin for 7 days to decrease the risk of early posttraumatic seizures. Phenytoin alters drug metabolism, induces fever, and requires therapeutic-level monitoring. Alternatively, levetiracetam (Keppra) does not require serum monitoring or have significant pharmacokinetic interactions. In the current study, the authors compare the EEG findings in patients receiving phenytoin with those receiving levetiracetam monotherapy for seizure prophylaxis following severe TBI. Methods Data were prospectively collected in 32 cases in which patients received levetiracetam for the first 7 days after severe TBI and compared with data from a historical cohort of 41 cases in which patients received phenytoin monotherapy. Patients underwent 1-hour electroencephalographic (EEG) monitoring if they displayed persistent coma, decreased mental status, or clinical signs of seizures. The EEG results were grouped into normal and abnormal findings, with abnormal EEG findings further categorized as seizure activity or seizure tendency. Results Fifteen of 32 patients in the levetiracetam group warranted EEG monitoring. In 7 of these 15 cases the results were normal and in 8 abnormal; 1 patient had seizure activity, whereas 7 had seizure tendency. Twelve of 41 patients in the phenytoin group received EEG monitoring, with all results being normal. Patients treated with levetiracetam and phenytoin had equivalent incidence of seizure activity (p = 0.556). Patients receiving levetiracetam had a higher incidence of abnormal EEG findings (p = 0.003). Conclusions Levetiracetam is as effective as phenytoin in preventing early posttraumatic seizures but is associated with an increased seizure tendency on EEG analysis. PMID:18828701

Childhood Trauma Associated with Enhanced High Frequency Band Powers and Induced Subjective Inattention of Adults

PubMed Central

Lee, Seung-Hwan; Park, Yeonsoo; Jin, Min Jin; Lee, Yeon Jeong; Hahn, Sang Woo

2017-01-01

Childhood trauma can lead to various psychological and cognitive symptoms. It has been demonstrated that high frequency electroencephalogram (EEG) powers could be closely correlated with inattention. In this study, we explored the relationship between high frequency EEG powers, inattention, symptoms of adult attention deficit hyperactivity disorder (ADHD), and childhood traumatic experiences. A total of 157 healthy Korean adult volunteers were included and divided into two groups using the Childhood Trauma Questionnaire (CTQ) score. The subjective inattention scores, ADHD scale, and anxiety and depression symptom were evaluated. EEG was recorded and quantitative band powers were analyzed. The results were as follows: (1) the high CTQ group showed significantly increased delta, beta1, beta2, beta3 and gamma, and significantly decreased low alpha power compared to the low CTQ group; (2) the high CTQ group had higher inattention score compared to the low CTQ group; (3) the high CTQ group had higher adult ADHD scores; (4) CTQ scores showed significant positive correlations with inattention scores, and adult ADHD scores; (5) unexpectedly, the inattention scores showed significant positive correlations with beta powers and a negative correlation with low alpha power; and (6) the moderated mediation model was confirmed: the depression fully mediated the path from state anxiety to inattention, and the CTQ significantly moderated the pathway between anxiety and depression. Our results show the possibility that childhood adversity may cause subjective inattention and adult ADHD symptoms. Depressive symptoms fully mediated the path from anxiety to inattention, especially in those who report severe childhood traumatic experiences. PMID:28860979

[Attention deficit hyperactivity disorder treated with scalp acupuncture and EEG biofeedback therapy in children: a randomized controlled trial].

PubMed

He, Cai-Di; Lang, Bo-Xu; Jin, Ling-Qing; Li, Bing

2014-12-01

To compare the difference in clinical efficacy on children attention deficit hyperactivity disorder (ADHD) between the combined therapy of scalp acupuncture and EGG biofeedback and the simple EEG biofeedback therapy so as to search the better therapeutic method for ADHD. One hundred patients were randomized into an observation group and a control group, 50 cases in each one. In the control group, the simple EEG biofeedback therapy was adopted. In the observation group, on the basis of biofeedback therapy, scalp acupuncture was added and applied to Dingzhongxian (MS 5), Dingpangyixian (MS 8), Baihui (GV 20), Sishencong (EX-HN 1), etc. The ten treatments made one session. After four sessions of treatment, FIQ value in Wechsler intelligence scale, CIH score in Conners children behavior questionnaire, the ratio of 0 wave and p wave in EEG, FRCQ and FAQ in the integrated visual and auditory continuous performance test (IVA-CPT) and clinical comprehensive efficacy were observed before and after treatment in the two groups separately. Three cases were dropped out in the observation group and 2 cases were out in the control group. In the two groups, FIQ, FRCQ and FAQ were all increased after treatment (P < 0.01, P < 0.05); the increases in the observation group were much more significant than those in the control group after treatment (all P < 0.05). In the two groups, CIH score and the ratio of 0 wave and p wave were all reduced after treatment (P < 0.01, P < 0.05); the reduction in the observation group were much more apparent as compared with those in the control group (both P< 0.05). The total effective rate was 91.5% (43/47) in the observation group and better than 83. 3% (40/48, P < 0.01) in the control group. The combined therapy of scalp acupuncture and EEG biofeedback achieves the superior efficacy on children ADHD as compared with the simple biofeedback therapy. This combined therapy rapidly relieves the essential symptoms of ADHD and improves EEG waveform in children patients. Importantly, this therapy obtains and consolidates the significant efficacy.

Chaos-chaos transition of left hemisphere EEGs during standard tasks of Waterloo-Stanford Group Scale of hypnotic susceptibility.

PubMed

Yargholi, Elahe'; Nasrabadi, Ali Motie

2015-01-01

A recent study, recurrence quantification analysis of EEG signals during standard tasks of Waterloo-Stanford Group Scale of hypnotic susceptibility investigated recurrence quantifiers (RQs) of hypnotic electroencephalograph (EEG) signals recorded after hypnotic induction while subjects were doing standard tasks of Waterloo-Stanford Group Scale (WSGS) of hypnotic susceptibility to distinguish subjects of different hypnotizability levels. Following the same analysis, the current study determines the capability of different RQs to distinguish subjects of low, medium and high hypnotizability level and studies the influence of hypnotizability level on underlying dynamic of tasks. Besides, EEG channels were sorted according to the number of their RQs, which differed significantly among subjects of different hypnotizability levels. Another valuable result was determination of major brain regions in observing significant differences in various task types (ideomotors, hallucination, challenge and memory).

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.

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.

Detection of Interictal Discharges With Convolutional Neural Networks Using Discrete Ordered Multichannel Intracranial EEG.

PubMed

Antoniades, Andreas; Spyrou, Loukianos; Martin-Lopez, David; Valentin, Antonio; Alarcon, Gonzalo; Sanei, Saeid; Cheong Took, Clive

2017-12-01

Detection algorithms for electroencephalography (EEG) data, especially in the field of interictal epileptiform discharge (IED) detection, have traditionally employed handcrafted features, which utilized specific characteristics of neural responses. Although these algorithms achieve high accuracy, mere detection of an IED holds little clinical significance. In this paper, we consider deep learning for epileptic subjects to accommodate automatic feature generation from intracranial EEG data, while also providing clinical insight. Convolutional neural networks are trained in a subject independent fashion to demonstrate how meaningful features are automatically learned in a hierarchical process. We illustrate how the convolved filters in the deepest layers provide insight toward the different types of IEDs within the group, as confirmed by our expert clinicians. The morphology of the IEDs found in filters can help evaluate the treatment of a patient. To improve the learning of the deep model, moderately different score classes are utilized as opposed to binary IED and non-IED labels. The resulting model achieves state-of-the-art classification performance and is also invariant to time differences between the IEDs. This paper suggests that deep learning is suitable for automatic feature generation from intracranial EEG data, while also providing insight into the data.

Cortex-based inter-subject analysis of iEEG and fMRI data sets: application to sustained task-related BOLD and gamma responses.

PubMed

Esposito, Fabrizio; Singer, Neomi; Podlipsky, Ilana; Fried, Itzhak; Hendler, Talma; Goebel, Rainer

2013-02-01

Linking regional metabolic changes with fluctuations in the local electromagnetic fields directly on the surface of the human cerebral cortex is of tremendous importance for a better understanding of detailed brain processes. Functional magnetic resonance imaging (fMRI) and intra-cranial electro-encephalography (iEEG) measure two technically unrelated but spatially and temporally complementary sets of functional descriptions of human brain activity. In order to allow fine-grained spatio-temporal human brain mapping at the population-level, an effective comparative framework for the cortex-based inter-subject analysis of iEEG and fMRI data sets is needed. We combined fMRI and iEEG recordings of the same patients with epilepsy during alternated intervals of passive movie viewing and music listening to explore the degree of local spatial correspondence and temporal coupling between blood oxygen level dependent (BOLD) fMRI changes and iEEG spectral power modulations across the cortical surface after cortex-based inter-subject alignment. To this purpose, we applied a simple model of the iEEG activity spread around each electrode location and the cortex-based inter-subject alignment procedure to transform discrete iEEG measurements into cortically distributed group patterns by establishing a fine anatomic correspondence of many iEEG cortical sites across multiple subjects. Our results demonstrate the feasibility of a multi-modal inter-subject cortex-based distributed analysis for combining iEEG and fMRI data sets acquired from multiple subjects with the same experimental paradigm but with different iEEG electrode coverage. The proposed iEEG-fMRI framework allows for improved group statistics in a common anatomical space and preserves the dynamic link between the temporal features of the two modalities. Copyright © 2012 Elsevier Inc. All rights reserved.

Joint time-frequency analysis of EEG signals based on a phase-space interpretation of the recording process

NASA Astrophysics Data System (ADS)

Testorf, M. E.; Jobst, B. C.; Kleen, J. K.; Titiz, A.; Guillory, S.; Scott, R.; Bujarski, K. A.; Roberts, D. W.; Holmes, G. L.; Lenck-Santini, P.-P.

2012-10-01

Time-frequency transforms are used to identify events in clinical EEG data. Data are recorded as part of a study for correlating the performance of human subjects during a memory task with pathological events in the EEG, called spikes. The spectrogram and the scalogram are reviewed as tools for evaluating spike activity. A statistical evaluation of the continuous wavelet transform across trials is used to quantify phase-locking events. For simultaneously improving the time and frequency resolution, and for representing the EEG of several channels or trials in a single time-frequency plane, a multichannel matching pursuit algorithm is used. Fundamental properties of the algorithm are discussed as well as preliminary results, which were obtained with clinical EEG data.

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.

Hypoglycemia-Associated EEG Changes Following Antecedent Hypoglycemia in Type 1 Diabetes Mellitus.

PubMed

Sejling, Anne-Sophie; Kjaer, Troels W; Pedersen-Bjergaard, Ulrik; Remvig, Line S; Frandsen, Christian S; Hilsted, Linda; Faber, Jens; Holst, Jens Juul; Tarnow, Lise; Møller, Jakob Skadkær; Nielsen, Martin N; Thorsteinsson, Birger; Juhl, Claus B

2017-02-01

Recurrent hypoglycemia has been shown to blunt hypoglycemia symptom scores and counterregulatory hormonal responses during subsequent hypoglycemia. We therefore studied whether hypoglycemia-associated electroencephalogram (EEG) changes are affected by an antecedent episode of hypoglycemia. Twenty-four patients with type 1 diabetes mellitus (10 with normal hypoglycemia awareness, 14 with hypoglycemia unawareness) were studied on 2 consecutive days by hyperinsulinemic glucose clamp at hypoglycemia (2.0-2.5 mmol/L) during a 1-h period. EEG was recorded, cognitive function assessed, and hypoglycemia symptom scores and counterregulatory hormonal responses were obtained. Twenty-one patients completed the study. Hypoglycemia-associated EEG changes were identified on both days with no differences in power or frequency distribution in the theta, alpha, or the combined theta-alpha band during hypoglycemia on the 2 days. Similar degree of cognitive dysfunction was also present during hypoglycemia on both days. When comparing the aware and unaware group, there were no differences in the hypoglycemia-associated EEG changes. There were very subtle differences in cognitive function between the two groups on day 2. The symptom response was higher in the aware group on both days, while only subtle differences were seen in the counterregulatory hormonal response. Antecedent hypoglycemia does not affect hypoglycemia-associated EEG changes in patients with type 1 diabetes mellitus.

EEG amplitude modulation analysis for semi-automated diagnosis of Alzheimer's disease

NASA Astrophysics Data System (ADS)

Falk, Tiago H.; Fraga, Francisco J.; Trambaiolli, Lucas; Anghinah, Renato

2012-12-01

Recent experimental evidence has suggested a neuromodulatory deficit in Alzheimer's disease (AD). In this paper, we present a new electroencephalogram (EEG) based metric to quantitatively characterize neuromodulatory activity. More specifically, the short-term EEG amplitude modulation rate-of-change (i.e., modulation frequency) is computed for five EEG subband signals. To test the performance of the proposed metric, a classification task was performed on a database of 32 participants partitioned into three groups of approximately equal size: healthy controls, patients diagnosed with mild AD, and those with moderate-to-severe AD. To gauge the benefits of the proposed metric, performance results were compared with those obtained using EEG spectral peak parameters which were recently shown to outperform other conventional EEG measures. Using a simple feature selection algorithm based on area-under-the-curve maximization and a support vector machine classifier, the proposed parameters resulted in accuracy gains, relative to spectral peak parameters, of 21.3% when discriminating between the three groups and by 50% when mild and moderate-to-severe groups were merged into one. The preliminary findings reported herein provide promising insights that automated tools may be developed to assist physicians in very early diagnosis of AD as well as provide researchers with a tool to automatically characterize cross-frequency interactions and their changes with disease.

Differences in the perceived music pleasantness between monolateral cochlear implanted and normal hearing children assessed by EEG.

PubMed

Vecchiato, G; Maglione, A G; Scorpecci, A; Malerba, P; Graziani, I; Cherubino, P; Astolfi, L; Marsella, P; Colosimo, A; Babiloni, Fabio

2013-01-01

The perception of the music in cochlear implanted (CI) patients is an important aspect of their quality of life. In fact, the pleasantness of the music perception by such CI patients can be analyzed through a particular analysis of EEG rhythms. Studies on healthy subjects show that exists a particular frontal asymmetry of the EEG alpha rhythm which can be correlated with pleasantness of the perceived stimuli (approach-withdrawal theory). In particular, here we describe differences between EEG activities estimated in the alpha frequency band for a monolateral CI group of children and a normal hearing one during the fruition of a musical cartoon. The results of the present analysis showed that the alpha EEG asymmetry patterns related to the normal hearing group refers to a higher pleasantness perception when compared to the cerebral activity of the monolateral CI patients. In fact, the present results support the statement that a monolateral CI group could perceive the music in a less pleasant way when compared to normal hearing children.

Ethanolic Extract of Traditional Chinese Medicine (TCM) Gamboge Inhibits Colon Cancer via the Wnt/Beta-Catenin Signaling Pathway in an Orthotopic Mouse Model.

PubMed

Wang, Wei; Li, Youran; Chen, Yiqi; Chen, Hongjin; Zhu, Ping; Xu, Minmin; Wang, Hao; Wu, Minna; Yang, Zhijian; Hoffman, Robert M; Gu, Yunfei

2018-04-01

The aim of the present study was to investigate the efficacy of an ethanolic extract of gamboge (EEG), a traditional Chinese medicine (TCM), both in vitro on colon cancer cells and in vivo in an orthotopic mouse model of human colon cancer. The in vitro cytotoxicity of EEG on colon cancer cells was determined with the CCK8 proliferation assay and the Annexin V-PE/7-AAD apoptosis assay. Efficacy of EEG in vivo was evaluated in an orthotopic mouse model of human colon cancer implated with the green fluorescent protein-expressing human colon cancer cell line SW480-GFP. The tumor-bearing mice were treated with vehicle (0.2 ml/dose normal saline, po, daily), irinotecan (50 mg/kg/dose, ip, twice a week), 5-FU (15 mg/kg/dose, ip, every other day) as positive controls or EEG at doses of 12.5, 25 and 50 mg/kg/dose, po, daily. Real-time fluorescence imaging was performed to determine tumor inhibition in each treated group compared to the untreated controls. The protein expression of β-catenin, MMP-7, cyclin D1 and E-cadherin in the tumors was analyzed by immunohistochemistry. EEG significantly induced proliferation inhibition and apoptosis of SW480 colon cancer cells in vitro in a dose-dependent manner. Tumor growth in the colon-cancer orthotopic model was significantly inhibited by irinotecan, 5-FU and all three doses of EEG. The efficacy of EEG was comparable to irinotecan and 5-FU. Irinotecan, 5-FU and 50 mg/kg EEG significantly decreased the protein expression of β-catenin and MMP-7. Cyclin D1 expression was decreased and E-cadherin expression was increased by irinotecan, 5-FU and all three doses of EEG. The present study demonstrates anti-tumor efficacy of EEG on colon cancer both in vitro and in vivo through inducing proliferation inhibition and apoptosis of SW480 colon cancer cells and inhibiting tumor growth, respectively. EEG exerts anti-tumor activity at least partly via down-regulation of the Wnt/β-catenin signaling pathway. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

EEG activity during estral cycle in the rat.

PubMed

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

1992-10-01

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

Quantitative electroencephalography during rapid eye movement (REM) and non-REM sleep in combat-exposed veterans with and without post-traumatic stress disorder.

PubMed

Cohen, Daniel J; Begley, Amy; Alman, Jennie J; Cashmere, David J; Pietrone, Regina N; Seres, Robert J; Germain, Anne

2013-02-01

Sleep disturbances are a hallmark feature of post-traumatic stress disorder (PTSD), and associated with poor clinical outcomes. Few studies have examined sleep quantitative electroencephalography (qEEG), a technique able to detect subtle differences that polysomnography does not capture. We hypothesized that greater high-frequency qEEG would reflect 'hyperarousal' in combat veterans with PTSD (n = 16) compared to veterans without PTSD (n = 13). EEG power in traditional EEG frequency bands was computed for artifact-free sleep epochs across an entire night. Correlations were performed between qEEG and ratings of PTSD symptoms and combat exposure. The groups did not differ significantly in whole-night qEEG measures for either rapid eye movement (REM) or non-REM (NREM) sleep. Non-significant medium effect sizes suggest less REM beta (opposite to our hypothesis), less REM and NREM sigma and more NREM gamma in combat veterans with PTSD. Positive correlations were found between combat exposure and NREM beta (PTSD group only), and REM and NREM sigma (non-PTSD group only). Results did not support global hyperarousal in PTSD as indexed by increased beta qEEG activity. The correlation of sigma activity with combat exposure in those without PTSD and the non-significant trend towards less sigma activity during both REM and NREM sleep in combat veterans with PTSD suggests that differential information processing during sleep may characterize combat-exposed military veterans with and without PTSD. © 2012 European Sleep Research Society.

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

PubMed Central

2012-01-01

Background We describe and characterize the performance of microEEG compared to that of a commercially available and widely used clinical EEG machine. microEEG is a portable, battery-operated, wireless EEG device, developed by Bio-Signal Group to overcome the obstacles to routine use of EEG in emergency departments (EDs). Methods The microEEG was used to obtain EEGs from healthy volunteers in the EEG laboratory and ED. The standard system was used to obtain EEGs from healthy volunteers in the EEG laboratory, and studies recorded from patients in the ED or ICU were also used for comparison. In one experiment, a signal splitter was used to record simultaneous microEEG and standard EEG from the same electrodes. Results EEG signal analysis techniques indicated good agreement between microEEG and the standard system in 66 EEGs recorded in the EEG laboratory and the ED. In the simultaneous recording the microEEG and standard system signals differed only in a smaller amount of 60 Hz noise in the microEEG signal. In a blinded review by a board-certified clinical neurophysiologist, differences in technical quality or interpretability were insignificant between standard recordings in the EEG laboratory and microEEG recordings from standard or electrode cap electrodes in the ED or EEG laboratory. The microEEG data recording characteristics such as analog-to-digital conversion resolution (16 bits), input impedance (>100MΩ), and common-mode rejection ratio (85 dB) are similar to those of commercially available systems, although the microEEG is many times smaller (88 g and 9.4 × 4.4 × 3.8 cm). Conclusions Our results suggest that the technical qualities of microEEG are non-inferior to a standard commercially available EEG recording device. EEG in the ED is an unmet medical need due to space and time constraints, high levels of ambient electrical noise, and the cost of 24/7 EEG technologist availability. This study suggests that using microEEG with an electrode cap that can be applied easily and quickly can surmount these obstacles without compromising technical quality. PMID:23006616

Multimodal neuroimaging in presurgical evaluation of drug-resistant epilepsy☆

PubMed Central

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

2013-01-01

Intracranial EEG (icEEG) monitoring is critical in epilepsy surgical planning, but it has limitations. The advances of neuroimaging have made it possible to reveal epileptic abnormalities that could not be identified previously and improve the localization of the seizure focus and the vital cortex. A frequently asked question in the field is whether non-invasive neuroimaging could replace invasive icEEG or reduce the need for icEEG in presurgical evaluation. This review considers promising neuroimaging techniques in epilepsy presurgical assessment in order to address this question. In addition, due to large variations in the accuracies of neuroimaging across epilepsy centers, multicenter neuroimaging studies are reviewed, and there is much need for randomized controlled trials (RCTs) to better reveal the utility of presurgical neuroimaging. The results of multiple studies indicate that non-invasive neuroimaging could not replace invasive icEEG in surgical planning especially in non-lesional or extratemporal lobe epilepsies, but it could reduce the need for icEEG in certain cases. With technical advances, multimodal neuroimaging may play a greater role in presurgical evaluation to reduce the costs and risks of epilepsy surgery, and provide surgical options for more patients with drug-resistant epilepsy. PMID:24282678

Mutual information measures applied to EEG signals for sleepiness characterization.

PubMed

Melia, Umberto; Guaita, Marc; Vallverdú, Montserrat; Embid, Cristina; Vilaseca, Isabel; Salamero, Manel; Santamaria, Joan

2015-03-01

Excessive daytime sleepiness (EDS) is one of the main symptoms of several sleep related disorders with a great impact on the patient lives. While many studies have been carried out in order to assess daytime sleepiness, the automatic EDS detection still remains an open problem. In this work, a novel approach to this issue based on non-linear dynamical analysis of EEG signal was proposed. Multichannel EEG signals were recorded during five maintenance of wakefulness (MWT) and multiple sleep latency (MSLT) tests alternated throughout the day from patients suffering from sleep disordered breathing. A group of 20 patients with excessive daytime sleepiness (EDS) was compared with a group of 20 patients without daytime sleepiness (WDS), by analyzing 60-s EEG windows in waking state. Measures obtained from cross-mutual information function (CMIF) and auto-mutual-information function (AMIF) were calculated in the EEG. These functions permitted a quantification of the complexity properties of the EEG signal and the non-linear couplings between different zones of the scalp. Statistical differences between EDS and WDS groups were found in β band during MSLT events (p-value < 0.0001). WDS group presented more complexity than EDS in the occipital zone, while a stronger nonlinear coupling between occipital and frontal zones was detected in EDS patients than in WDS. The AMIF and CMIF measures yielded sensitivity and specificity above 80% and AUC of ROC above 0.85 in classifying EDS and WDS patients. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

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.

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

ERIC Educational Resources Information Center

Nidich, Sanford I.; And Others

1983-01-01

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

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 possible the build-up of a multinational database, and it will help in training young neurophysiologists. PMID:23506075

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

PubMed

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

2014-02-01

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

EEG-fMRI Evaluation of Patients with Mesial Temporal Lobe Sclerosis

PubMed Central

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

2014-01-01

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

Issues in establishing an aerosol radiological baseline for the waste isolation pilot plant near Carlsbad, New Mexico.

PubMed

Rodgers, J C; Kenney, J W

1997-02-01

The Department of Energy has constructed a deep geologic repository for defense transuranic waste disposal. The Waste Isolation Pilot Plant, located in Southeastern New Mexico, is slated to receive transuranic waste by truck delivery beginning in 1998. The Environmental Evaluation Group (EEG) provides an independent evaluation of the impact on the health and environment in New Mexico of the WIPP project. Since 1985, the EEG has operated a network of air monitoring sites around WIPP and in nearby communities. The radionuclide concentration data from these air samples have been assembled into a useful baseline data base after resolution of a number of methodological and quality assurance issues. Investigation thresholds for the principal radionuclides have been calculated from combined data collected from several sites. These action levels will provide a critical quantitative basis for decisions of whether future airborne radionuclide measurements are attributable to accidental releases.

Correlation between perceived stigma and EEG paroxysmal abnormality in childhood epilepsy.

PubMed

Kanemura, Hideaki; Sano, Fumikazu; Ohyama, Tetsuo; Sugita, Kanji; Aihara, Masao

2015-11-01

We investigated the relationship between abnormal electroencephalogram (EEG) findings such as localized EEG paroxysmal abnormality (PA) and the perception of stigma to determine EEG factors associated with perceived stigma in childhood epilepsy. Participants comprised 40 patients (21 boys, 19 girls; mean age, 14.6 years) with epilepsy at enrollment. The criteria for inclusion were as follows: 1) age of 12-18 years, inclusive; 2) ≥6 months after epilepsy onset; 3) the ability to read and speak Japanese; and 4) the presence of EEG PA. Fifteen healthy seizure-free children were included as a control group. Participants were asked to rate how often they felt or acted in the ways described in the items of the Child Stigma Scale using a 5-point scale. Electroencephalogram paroxysms were classified based on the presence of spikes, sharp waves, or spike-wave complexes, whether focal or generalized. Participants showed significantly higher stigma scores than healthy subjects (p<0.01). A higher score reflects a greater perception of stigma. The average total scores of patients presenting with EEG PA at generalized, frontal, RD, midtemporal, and occipital regions were 2.3, 4.0, 2.4, 3.2, and 2.2, respectively. The scores of all questions were higher in the frontal group than those in other regions (p<0.01). Children presenting with frontal EEG PA perceived a greater stigma than children presenting with nonfrontal EEG PA (p<0.01). A relationship was identified between frontal EEG PA and a greater perception of stigma. Further studies are needed to confirm whether frontal EEG PA may function as a mediator of emotional responses such as perceived stigma in childhood epilepsy. Copyright © 2015 Elsevier Inc. All rights reserved.

Electroencephalographic coherences discriminate between children with different pedagogical evaluation.

PubMed

Marosi, E; Harmony, T; Becker, J; Reyes, A; Bernal, J; Fernández, T; Rodríguez, M; Silva, J; Guerrero, V

1995-02-01

The relationship of reading-writing ability and EEG coherences was studied in 84 subjects from two age groups 7.0-8.9 and 9-11.2 years old. All children were divided into three groups according to their performance on a pedagogical test: ped1, normal children; ped2, children with mild problems; ped3, children with reading-writing disability. The following results were obtained: in general, children showed higher coherences in groups with poor performance in the delta, theta and beta bands. In the alpha band, higher coherence values were related to better performance. The exceptions to this general pattern were rare. Group ped2 had higher coherences in delta, theta and alpha bands than ped1 and ped3, in left temporal leads. In older children the same tendency was observed, but group differences in the theta, alpha and beta bands were few. In this age range, the significant group differences were almost all interhemispheric coherences. The discriminant analysis that classified subjects by their coherence values gave very good results, fact that demonstrates, that EEG coherence is a highly sensitive measurement indicating not only the existence of a reading-writing problem, but also the degree of its severity.

Children's Electrophysiological Responses to Music.

ERIC Educational Resources Information Center

Flohr, John W.; And Others

This study examined the electrophysiological differences between baseline EEG frequencies and EEG frequencies obtained while listening to music stimuli. The experimental group comprised 22 children, ages 4 to 6 years old, who received special music instruction twice a week for 25 minutes for 7 weeks. The control group received no music…

Neural correlates of brain state in chronic ischemia and stroke: combined resting state electroencephalogram and transcranial Doppler ultrasonographic study.

PubMed

Martynova, Olga V; Portnova, Galina V; Gladun, Ksenya V

2017-02-08

Clinical neurology is constantly searching for reliable indices of ischemic brain damage to prevent a possible development of stroke. We suggest that resting state electroencephalogram (rsEEG) with respect to other clinical data may provide important information about the severity of ischemia. We carried out correlation analysis of rsEEG, data of transcranial Doppler ultrasonography of head vessels, and clinical assessment scores collected from healthy volunteers and four groups of patients with mild chronic microvascular ischemia (CMI-1), moderate CMI (CMI-2), severe atrophy of the cerebral hemisphere, ischemic stroke in the left middle cerebral artery stroke, and ischemic stroke in the right middle cerebral artery stroke. Using independent component analysis and k-mean clustering of EEG data, we observed prominent changes in rsEEG reflected in specific distributions of spectral peaks in all groups of patients. We found a significant correlation of EEG spectral distribution and the blood flow velocity in coronal arteries, which was also affected by the severity of ischemia and the localization of stroke. Moreover, EEG spectral distribution was more indicative of early stages of ischemia than the blood flow velocity. Our data support the hypothesis that rsEEG may reflect altered neural activity caused by ischemic brain damage.

Quantification of EEG reactivity in comatose patients

PubMed Central

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

2016-01-01

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

Brain Functional Connectivity in MS: An EEG-NIRS Study

DTIC Science & Technology

2015-10-01

electrical (EEG) and blood volume and blood oxygen-based (NIRS and fMRI ) signals, and to use the results to help optimize blood oxygen level...dependent (BOLD) fMRI analyses of brain activity. Participants will be patients with MS (n=25) and healthy demographically matched controls (n=25) who will...undergo standardized evaluations and imaging using combined EEG-NIRS- fMRI . EEG-NIRS data will be used to construct maps of neurovascular coupling

An analysis of the kangaroo care intervention using neonatal EEG complexity: a preliminary study.

PubMed

Kaffashi, F; Scher, M S; Ludington-Hoe, S M; Loparo, K A

2013-02-01

Skin-to-skin contact (SSC) promotes physiological stability and interaction between parents and infants. Temporal analyses of predictability in EEG-sleep time series can elucidate functional brain maturation between SSC and non-SSC cohorts at similar post-menstrual ages (PMAs). Sixteen EEG-sleep studies were performed on eight preterm infants who received 8 weeks of SSC, and compared with two non-SSC cohorts at term (N=126) that include a preterm group corrected to term age and a full term group. Two time series measures of predictability were used for comparisons. The SSC premature neonate group had increased complexity when compared to the non-SSC premature neonate group at the same PMA. Discriminant analysis shows that SSC neonates at 40 weeks PMA are closer to the full term neonate non-SSC group than to the premature non-SSC group at the same PMA; suggesting that the KC intervention accelerates neurophysiological maturation of premature neonates. Based on the hypothesis that EEG-derived complexity increases with neurophysiological maturation as supported by previously published research, SSC accelerates brain maturation in healthy preterm infants as quantified by time series measures of predictability when compared to a similar non-SSC group. Times series methods that quantify predictability of EEG sleep in neonates can provide useful information about altered neural development after developmental care interventions such as SSC. Analyses of this type may be helpful in assessing other neuroprotection strategies. Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data From Healthy Versus Addiction Treated Versus Addiction Not Treated Subjects.

PubMed

Doborjeh, Maryam Gholami; Wang, Grace Y; Kasabov, Nikola K; Kydd, Robert; Russell, Bruce

2016-09-01

This paper introduces a method utilizing spiking neural networks (SNN) for learning, classification, and comparative analysis of brain data. As a case study, the method was applied to electroencephalography (EEG) data collected during a GO/NOGO cognitive task performed by untreated opiate addicts, those undergoing methadone maintenance treatment (MMT) for opiate dependence and a healthy control group. the method is based on an SNN architecture called NeuCube, trained on spatiotemporal EEG data. NeuCube was used to classify EEG data across subject groups and across GO versus NOGO trials, but also facilitated a deeper comparative analysis of the dynamic brain processes. This analysis results in a better understanding of human brain functioning across subject groups when performing a cognitive task. In terms of the EEG data classification, a NeuCube model obtained better results (the maximum obtained accuracy: 90.91%) when compared with traditional statistical and artificial intelligence methods (the maximum obtained accuracy: 50.55%). more importantly, new information about the effects of MMT on cognitive brain functions is revealed through the analysis of the SNN model connectivity and its dynamics. this paper presented a new method for EEG data modeling and revealed new knowledge on brain functions associated with mental activity which is different from the brain activity observed in a resting state of the same subjects.

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

Improved epileptic seizure detection combining dynamic feature normalization with EEG novelty detection.

PubMed

Bogaarts, J G; Hilkman, D M W; Gommer, E D; van Kranen-Mastenbroek, V H J M; Reulen, J P H

2016-12-01

Continuous electroencephalographic monitoring of critically ill patients is an established procedure in intensive care units. Seizure detection algorithms, such as support vector machines (SVM), play a prominent role in this procedure. To correct for inter-human differences in EEG characteristics, as well as for intra-human EEG variability over time, dynamic EEG feature normalization is essential. Recently, the median decaying memory (MDM) approach was determined to be the best method of normalization. MDM uses a sliding baseline buffer of EEG epochs to calculate feature normalization constants. However, while this method does include non-seizure EEG epochs, it also includes EEG activity that can have a detrimental effect on the normalization and subsequent seizure detection performance. In this study, EEG data that is to be incorporated into the baseline buffer are automatically selected based on a novelty detection algorithm (Novelty-MDM). Performance of an SVM-based seizure detection framework is evaluated in 17 long-term ICU registrations using the area under the sensitivity-specificity ROC curve. This evaluation compares three different EEG normalization methods, namely a fixed baseline buffer (FB), the median decaying memory (MDM) approach, and our novelty median decaying memory (Novelty-MDM) method. It is demonstrated that MDM did not improve overall performance compared to FB (p < 0.27), partly because seizure like episodes were included in the baseline. More importantly, Novelty-MDM significantly outperforms both FB (p = 0.015) and MDM (p = 0.0065).

Evaluation of an automated spike-and-wave complex detection algorithm in the EEG from a rat model of absence epilepsy.

PubMed

Bauquier, Sebastien H; Lai, Alan; Jiang, Jonathan L; Sui, Yi; Cook, Mark J

2015-10-01

The aim of this prospective blinded study was to evaluate an automated algorithm for spike-and-wave discharge (SWD) detection applied to EEGs from genetic absence epilepsy rats from Strasbourg (GAERS). Five GAERS underwent four sessions of 20-min EEG recording. Each EEG was manually analyzed for SWDs longer than one second by two investigators and automatically using an algorithm developed in MATLAB®. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for the manual (reference) versus the automatic (test) methods. The results showed that the algorithm had specificity, sensitivity, PPV and NPV >94%, comparable to published methods that are based on analyzing EEG changes in the frequency domain. This provides a good alternative as a method designed to mimic human manual marking in the time domain.

Automatic burst detection for the EEG of the preterm infant.

PubMed

Jennekens, Ward; Ruijs, Loes S; Lommen, Charlotte M L; Niemarkt, Hendrik J; Pasman, Jaco W; van Kranen-Mastenbroek, Vivianne H J M; Wijn, Pieter F F; van Pul, Carola; Andriessen, Peter

2011-10-01

To aid with prognosis and stratification of clinical treatment for preterm infants, a method for automated detection of bursts, interburst-intervals (IBIs) and continuous patterns in the electroencephalogram (EEG) is developed. Results are evaluated for preterm infants with normal neurological follow-up at 2 years. The detection algorithm (MATLAB®) for burst, IBI and continuous pattern is based on selection by amplitude, time span, number of channels and numbers of active electrodes. Annotations of two neurophysiologists were used to determine threshold values. The training set consisted of EEG recordings of four preterm infants with postmenstrual age (PMA, gestational age + postnatal age) of 29-34 weeks. Optimal threshold values were based on overall highest sensitivity. For evaluation, both observers verified detections in an independent dataset of four EEG recordings with comparable PMA. Algorithm performance was assessed by calculation of sensitivity and positive predictive value. The results of algorithm evaluation are as follows: sensitivity values of 90% ± 6%, 80% ± 9% and 97% ± 5% for burst, IBI and continuous patterns, respectively. Corresponding positive predictive values were 88% ± 8%, 96% ± 3% and 85% ± 15%, respectively. In conclusion, the algorithm showed high sensitivity and positive predictive values for bursts, IBIs and continuous patterns in preterm EEG. Computer-assisted analysis of EEG may allow objective and reproducible analysis for clinical treatment.

Analysis of spontaneous EEG activity in Alzheimer's disease using cross-sample entropy and graph theory.

PubMed

Gomez, Carlos; Poza, Jesus; Gomez-Pilar, Javier; Bachiller, Alejandro; Juan-Cruz, Celia; Tola-Arribas, Miguel A; Carreres, Alicia; Cano, Monica; Hornero, Roberto

2016-08-01

The aim of this pilot study was to analyze spontaneous electroencephalography (EEG) activity in Alzheimer's disease (AD) by means of Cross-Sample Entropy (Cross-SampEn) and two local measures derived from graph theory: clustering coefficient (CC) and characteristic path length (PL). Five minutes of EEG activity were recorded from 37 patients with dementia due to AD and 29 elderly controls. Our results showed that Cross-SampEn values were lower in the AD group than in the control one for all the interactions among EEG channels. This finding indicates that EEG activity in AD is characterized by a lower statistical dissimilarity among channels. Significant differences were found mainly for fronto-central interactions (p <; 0.01, permutation test). Additionally, the application of graph theory measures revealed diverse neural network changes, i.e. lower CC and higher PL values in AD group, leading to a less efficient brain organization. This study suggests the usefulness of our approach to provide further insights into the underlying brain dynamics associated with AD.

Non-parametric early seizure detection in an animal model of temporal lobe epilepsy

NASA Astrophysics Data System (ADS)

Talathi, Sachin S.; Hwang, Dong-Uk; Spano, Mark L.; Simonotto, Jennifer; Furman, Michael D.; Myers, Stephen M.; Winters, Jason T.; Ditto, William L.; Carney, Paul R.

2008-03-01

The performance of five non-parametric, univariate seizure detection schemes (embedding delay, Hurst scale, wavelet scale, nonlinear autocorrelation and variance energy) were evaluated as a function of the sampling rate of EEG recordings, the electrode types used for EEG acquisition, and the spatial location of the EEG electrodes in order to determine the applicability of the measures in real-time closed-loop seizure intervention. The criteria chosen for evaluating the performance were high statistical robustness (as determined through the sensitivity and the specificity of a given measure in detecting a seizure) and the lag in seizure detection with respect to the seizure onset time (as determined by visual inspection of the EEG signal by a trained epileptologist). An optimality index was designed to evaluate the overall performance of each measure. For the EEG data recorded with microwire electrode array at a sampling rate of 12 kHz, the wavelet scale measure exhibited better overall performance in terms of its ability to detect a seizure with high optimality index value and high statistics in terms of sensitivity and specificity.

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

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

PubMed

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

1998-06-01

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

Circulating progenitor cells during exercise, muscle electro-stimulation and intermittent hypobaric hypoxia in patients with traumatic brain injury: a pilot study.

PubMed

Corral, Luisa; Conde, Laura; Guillamó, Elisabet; Blasi, Juan; Juncadella, Montserrat; Javierre, Casimiro; Viscor, Ginés; Ventura, Josep L

2014-01-01

Circulating progenitor cells (CPC) treatments may have great potential for the recovery of neurons and brain function. To increase and maintain CPC with a program of exercise, muscle electro-stimulation (ME) and/or intermittent-hypobaric-hypoxia (IHH), and also to study the possible improvement in physical or psychological functioning of participants with Traumatic Brain Injury (TBI). Twenty-one participants. Four groups: exercise and ME group (EEG), cycling group (CyG), IHH and ME group (HEG) and control group (CG). Psychological and physical stress tests were carried out. CPC were measured in blood several times during the protocol. Psychological tests did not change. In the physical stress tests the VO2 uptake increased in the EEG and the CyG, and the maximal tolerated workload increased in the HEG. CPC levels increased in the last three weeks in EEG, but not in CyG, CG and HEG. CPC levels increased in the last three weeks of the EEG program, but not in the other groups and we did not detect performed psychological test changes in any group. The detected aerobic capacity or workload improvement must be beneficial for the patients who have suffered TBI, but exercise type and the mechanisms involved are not clear.

Empirical Analysis of EEG and ERPs for Psychophysiological Adaptive Task Allocation

NASA Technical Reports Server (NTRS)

Prinzel, Lawrence J., III; Pope, Alan T.; Freeman, Frederick G.; Scerbo, Mark W.; Mikulka, Peter J.

2001-01-01

The present study was designed to test the efficacy of using Electroencephalogram (EEG) and Event-Related Potentials (ERPs) for making task allocation decisions. Thirty-six participants were randomly assigned to an experimental, yoked, or control group condition. Under the experimental condition, a tracking task was switched between task modes based upon the participant's EEG. The results showed that the use of adaptive aiding improved performance and lowered subjective workload under negative feedback as predicted. Additionally, participants in the adaptive group had significantly lower RMSE and NASA-TLX ratings than participants in either the yoked or control group conditions. Furthermore, the amplitudes of the N1 and P3 ERP components were significantly larger under the experimental group condition than under either the yoked or control group conditions. These results are discussed in terms of the implications for adaptive automation design.

Cortical light scattering during interictal epileptic spikes in frontal lobe epilepsy in children: A fast optical signal and electroencephalographic study.

PubMed

Manoochehri, Mana; Mahmoudzadeh, Mahdi; Bourel-Ponchel, Emilie; Wallois, Fabrice

2017-12-01

Interictal epileptic spikes (IES) represent a signature of the transient synchronous and excessive discharge of a large ensemble of cortical heterogeneous neurons. Epilepsy cannot be reduced to a hypersynchronous activation of neurons whose functioning is impaired, resulting on electroencephalogram (EEG) in epileptic seizures or IES. The complex pathophysiological mechanisms require a global approach to the interactions between neural synaptic and nonsynaptic, vascular, and metabolic systems. In the present study, we focused on the interaction between synaptic and nonsynaptic mechanisms through the simultaneous noninvasive multimodal multiscale recording of high-density EEG (HD-EEG; synaptic) and fast optical signal (FOS; nonsynaptic), which evaluate rapid changes in light scattering related to changes in membrane configuration occurring during neuronal activation of IES. To evaluate changes in light scattering occurring around IES, three children with frontal IES were simultaneously recorded with HD-EEG and FOS. To evaluate change in synchronization, time-frequency representation analysis of the HD-EEG was performed simultaneously around the IES. To independently evaluate our multimodal method, a control experiment with somatosensory stimuli was designed and applied to five healthy volunteers. Alternating increase-decrease-increase in optical signals occurred 200 ms before to 180 ms after the IES peak. These changes started before any changes in EEG signal. In addition, time-frequency domain EEG analysis revealed alternating decrease-increase-decrease in the EEG spectral power concomitantly with changes in the optical signal during IES. These results suggest a relationship between (de)synchronization and neuronal volume changes in frontal lobe epilepsy during IES. These changes in the neuronal environment around IES in frontal lobe epilepsy observed in children, as they have been in rats, raise new questions about the synaptic/nonsynaptic mechanisms that propel the neurons to hypersynchronization, as occurs during IES. We further demonstrate that this noninvasive multiscale multimodal approach is suitable for studying the pathophysiology of the IES in patients. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

EEG Oscillatory States: Universality, Uniqueness and Specificity across Healthy-Normal, Altered and Pathological Brain Conditions

PubMed Central

Fingelkurts, Alexander A.; Fingelkurts, Andrew A.

2014-01-01

For the first time the dynamic repertoires and oscillatory types of local EEG states in 13 diverse conditions (examined over 9 studies) that covered healthy-normal, altered and pathological brain states were quantified within the same methodological and conceptual framework. EEG oscillatory states were assessed by the probability-classification analysis of short-term EEG spectral patterns. The results demonstrated that brain activity consists of a limited repertoire of local EEG states in any of the examined conditions. The size of the state repertoires was associated with changes in cognition and vigilance or neuropsychopathologic conditions. Additionally universal, optional and unique EEG states across 13 diverse conditions were observed. It was demonstrated also that EEG oscillations which constituted EEG states were characteristic for different groups of conditions in accordance to oscillations’ functional significance. The results suggested that (a) there is a limit in the number of local states available to the cortex and many ways in which these local states can rearrange themselves and still produce the same global state and (b) EEG individuality is determined by varying proportions of universal, optional and unique oscillatory states. The results enriched our understanding about dynamic microstructure of EEG-signal. PMID:24505292

Design of a Wireless EEG System for Point-of-Care Applications.

PubMed

Jia, Wenyan; Bai, Yicheng; Sun, Mingui; Sclabassi, Robert J

2013-04-01

This study aims to develop a wireless EEG system to provide critical point-of-care information about brain electrical activity. A novel dry electrode, which can be installed rapidly, is used to acquire EEG from the scalp. A wireless data link between the electrode and a data port (i.e., a smartphone) is established based on the Bluetooth technology. A prototype of this system has been implemented and its performance in acquiring EEG has been evaluated.

Frequency domain beamforming of magnetoencephalographic beta band activity in epilepsy patients with focal cortical dysplasia.

PubMed

Heers, Marcel; Hirschmann, Jan; Jacobs, Julia; Dümpelmann, Matthias; Butz, Markus; von Lehe, Marec; Elger, Christian E; Schnitzler, Alfons; Wellmer, Jörg

2014-09-01

Spike-based magnetoencephalography (MEG) source localization is an established method in the presurgical evaluation of epilepsy patients. Focal cortical dysplasias (FCDs) are associated with focal epileptic discharges of variable morphologies in the beta frequency band in addition to single epileptic spikes. Therefore, we investigated the potential diagnostic value of MEG-based localization of spike-independent beta band (12-30Hz) activity generated by epileptogenic lesions. Five patients with FCD IIB underwent MEG. In one patient, invasive EEG (iEEG) was recorded simultaneously with MEG. In two patients, iEEG succeeded MEG, and two patients had MEG only. MEG and iEEG were evaluated for epileptic spikes. Two minutes of iEEG data and MEG epochs with no spikes as well as MEG epochs with epileptic spikes were analyzed in the frequency domain. MEG oscillatory beta band activity was localized using Dynamic Imaging of Coherent Sources. Intralesional beta band activity was coherent between simultaneous MEG and iEEG recordings. Continuous 14Hz beta band power correlated with the rate of interictal epileptic discharges detected in iEEG. In cases where visual MEG evaluation revealed epileptic spikes, the sources of beta band activity localized within <2cm of the epileptogenic lesion as shown on magnetic resonance imaging. This result held even when visually marked epileptic spikes were deselected. When epileptic spikes were detectable in iEEG but not MEG, MEG beta band activity source localization failed. Source localization of beta band activity has the potential to contribute to the identification of epileptic foci in addition to source localization of visually marked epileptic spikes. Thus, this technique may assist in the localization of epileptic foci in patients with suspected FCD. Copyright © 2014 Elsevier B.V. All rights reserved.

Effects of Drawing on Alpha Activity: A Quantitative EEG Study with Implications for Art Therapy

ERIC Educational Resources Information Center

Belkofer, Christopher M.; Van Hecke, Amy Vaughan; Konopka, Lukasz M.

2014-01-01

Little empirical evidence exists as to how materials used in art therapy affect the brain and its neurobiological functioning. This pre/post within-groups study utilized the quantitative electroencephalogram (qEEG) to measure residual effects in the brain after 20 minutes of drawing. EEG recordings were conducted before and after participants (N =…

Maturation of EEG Power Spectra in Early Adolescence: A Longitudinal Study

ERIC Educational Resources Information Center

Cragg, Lucy; Kovacevic, Natasa; McIntosh, Anthony Randal; Poulsen, Catherine; Martinu, Kristina; Leonard, Gabriel; Paus, Tomas

2011-01-01

This study investigated the fine-grained development of the EEG power spectra in early adolescence, and the extent to which it is reflected in changes in peak frequency. It also sought to determine whether sex differences in the EEG power spectra reflect differential patterns of maturation. A group of 56 adolescents were tested at age 10 years and…

Guidelines and best practices for electrophysiological data collection, analysis and reporting in autism

PubMed Central

Webb, S. J.; Bernier, R.; Henderson, H. A.; Johnson, M. H.; Jones, E. J. H.; Lerner, M. D.; McPartland, J. C.; Nelson, C. A.; Rojas, D. C.; Townsend, J.; Westerfield, M.

2014-01-01

The EEG reflects the activation of large populations of neurons that act in synchrony and propagate to the scalp surface. This activity reflects both the brain’s background electrical activity and when the brain is being challenged by a task. Despite strong theoretical and methodological arguments for the use of EEG in understanding the neural correlates of autism, the practice of collecting, processing and evaluating EEG data is complex. Scientists should take into consideration both the nature of development in autism given the life-long, pervasive course of the disorder and the disability of altered or atypical social, communicative, and motor behaviors, all of which require accommodations to traditional EEG environments and paradigms. This paper presents guidelines for the recording, analyzing, and interpreting of EEG data with participants with autism. The goal is to articulate a set of scientific standards as well as methodological considerations that will increase the general field’s understanding of EEG methods, provide support for collaborative projects, and contribute to the evaluation of results and conclusions. PMID:23975145

Correlation between disease severity and brain electric LORETA tomography in Alzheimer's disease.

PubMed

Gianotti, Lorena R R; Künig, Gabriella; Lehmann, Dietrich; Faber, Pascal L; Pascual-Marqui, Roberto D; Kochi, Kieko; Schreiter-Gasser, Ursula

2007-01-01

To compare EEG power spectra and LORETA-computed intracortical activity between Alzheimer's disease (AD) patients and healthy controls, and to correlate the results with cognitive performance in the AD group. Nineteen channel resting EEG was recorded in 21 mild to moderate AD patients and in 23 controls. Power spectra and intracortical LORETA tomography were computed in seven frequency bands and compared between groups. In the AD patients, the EEG results were correlated with cognitive performance (Mini Mental State Examination, MMSE). AD patients showed increased power in EEG delta and theta frequency bands, and decreased power in alpha2, beta1, beta2 and beta3. LORETA specified that increases and decreases of power affected different cortical areas while largely sparing prefrontal cortex. Delta power correlated negatively and alpha1 power positively with the AD patients' MMSE scores; LORETA tomography localized these correlations in left temporo-parietal cortex. The non-invasive EEG method of LORETA localized pathological cortical activity in our mild to moderate AD patients in agreement with the literature, and yielded striking correlations between EEG delta and alpha1 activity and MMSE scores in left temporo-parietal cortex. The present data support the hypothesis of an asymmetrical progression of the Alzheimer's disease.

Usefulness of a simple sleep-deprived EEG protocol for epilepsy diagnosis in de novo subjects.

PubMed

Giorgi, Filippo S; Perini, Daria; Maestri, Michelangelo; Guida, Melania; Pizzanelli, Chiara; Caserta, Anna; Iudice, Alfonso; Bonanni, Enrica

2013-11-01

In case series concerning the role of EEG after sleep deprivation (SD-EEG) in epilepsy, patients' features and protocols vary dramatically from one report to another. In this study, we assessed the usefulness of a simple SD-EEG method in well characterized patients. Among the 963 adult subjects submitted to SD-EEG at our Center, in the period 2003-2010, we retrospectively selected for analysis only those: (1) evaluated for suspected epileptic seizures; (2) with a normal/non-specific baseline EEG; (3) still drug-free at the time of SD-EEG; (4) with an MRI analysis; (5) with at least 1 year follow-up. SD-EEG consisted in SD from 2:00 AM and laboratory EEG from 8:00 AM to 10:30 AM. We analyzed epileptic interictal abnormalities (IIAs) and their correlations with patients' features. Epilepsy was confirmed in 131 patients. SD-EEG showed IIAs in 41.2% of all patients with epilepsy, and a 91.1% specificity for epilepsy diagnosis; IIAs types observed during SD-EEG are different in generalized versus focal epilepsies; for focal epilepsies, the IIAs yield in SD-EEG is higher than in second routine EEG. This simple SD-EEG protocol is very useful in de novo patients with suspected seizures. This study sheds new light on the role of SD-EEG in specific epilepsy populations. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Surgical outcome of MRI-negative refractory extratemporal lobe epilepsy.

PubMed

Shi, Jianguo; Lacuey, Nuria; Lhatoo, Samden

2017-07-01

The aim of this study is to determine outcome of resective epilepsy surgery in MRI-negative extratemporal lobe epilepsy (MNETLE) patients who underwent invasive evaluations and to determine factors governing outcome. We studied 28 patients who underwent resective epilepsy surgery for MNETLE from August 2006 to November 2015, in whom complete follow-up information was available. Electro-clinical, pathological and surgical data were evaluated. 24 patients (82.8%) were explored with intracranial EEG (9 stereoelectroencephalography (SEEG), 7 subdural grids and 8 both). All patients were followed for at least 6 months. During a mean follow up period of 32 [6-113] months, 13 (46.4%) patients became seizure-free (ILAE 1) and 18 (64.3%) had a good (ILAE 1, 2, 3) outcome. 21 (75.0%) patients had focal cortical dysplasia (FCD). Univariate analysis showed that more restricted (regional) interictal and ictal epileptiform discharges in surface EEG were significantly associated with seizure freedom (P=0.016 and P=0.024). Multivariate analysis confirmed that having ≥120 electrode contacts in the evaluation is an independent variable predicting seizure freedom (HR=4.283, 95% CI=1.342-13.676, P=0.014). Invasive EEG is a powerful tool in the pre-surgical evaluation of patients with MNETLE. Invasive EEG implantation that include the irritative zone and EEG onset zone as indicated by surface EEG, as well as wider brain coverage predict seizure freedom, contingent upon a sound anatomo-electro-clinical hypothesis for implantation. Copyright © 2017 Elsevier B.V. All rights reserved.

Cordance derived from REM sleep EEG as a biomarker for treatment response in depression--a naturalistic study after antidepressant medication.

PubMed

Adamczyk, Marek; Gazea, Mary; Wollweber, Bastian; Holsboer, Florian; Dresler, Martin; Steiger, Axel; Pawlowski, Marcel

2015-04-01

To evaluate whether prefrontal cordance in theta frequency band derived from REM sleep EEG after the first week of antidepressant medication could characterize the treatment response after 4 weeks of therapy in depressed patients. 20 in-patients (15 females, 5 males) with a depressive episode and 20 healthy matched controls were recruited into 4-week, open label, case-control study. Patients were treated with various antidepressants. No significant differences in age (responders (mean ± SD): 45 ± 22) years; non-responders: 49 ± 12 years), medication or Hamilton Depression Rating Scale (HAM-D) score (responders: 23.8 ± 4.5; non-responders 24.5 ± 7.6) at inclusion into the study were found between responders and non-responders. Response to treatment was defined as a ≥50% reduction of HAM-D score at the end of four weeks of active medication. Sleep EEG of patients was recorded after the first and the fourth week of medication. Cordance was computed for prefrontal EEG channels in theta frequency band during tonic REM sleep. The group of 8 responders had significantly higher prefrontal theta cordance in relation to the group of 12 non-responders after the first week of antidepressant medication. This finding was significant also when controlling for age, gender and number of previous depressive episodes (F1,15 = 6.025, P = .027). Furthermore, prefrontal cordance of all patients showed significant positive correlation (r = 0.52; P = .019) with the improvement of HAM-D score between the inclusion week and fourth week of medication. The results suggest that prefrontal cordance derived from REM sleep EEG could provide a biomarker for the response to antidepressant treatment in depressed patients. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

Unified Bayesian Estimator of EEG Reference at Infinity: rREST (Regularized Reference Electrode Standardization Technique).

PubMed

Hu, Shiang; Yao, Dezhong; Valdes-Sosa, Pedro A

2018-01-01

The choice of reference for the electroencephalogram (EEG) is a long-lasting unsolved issue resulting in inconsistent usages and endless debates. Currently, both the average reference (AR) and the reference electrode standardization technique (REST) are two primary, apparently irreconcilable contenders. We propose a theoretical framework to resolve this reference issue by formulating both (a) estimation of potentials at infinity, and (b) determination of the reference, as a unified Bayesian linear inverse problem, which can be solved by maximum a posterior estimation. We find that AR and REST are very particular cases of this unified framework: AR results from biophysically non-informative prior; while REST utilizes the prior based on the EEG generative model. To allow for simultaneous denoising and reference estimation, we develop the regularized versions of AR and REST, named rAR and rREST, respectively. Both depend on a regularization parameter that is the noise to signal variance ratio. Traditional and new estimators are evaluated with this framework, by both simulations and analysis of real resting EEGs. Toward this end, we leverage the MRI and EEG data from 89 subjects which participated in the Cuban Human Brain Mapping Project. Generated artificial EEGs-with a known ground truth, show that relative error in estimating the EEG potentials at infinity is lowest for rREST. It also reveals that realistic volume conductor models improve the performances of REST and rREST. Importantly, for practical applications, it is shown that an average lead field gives the results comparable to the individual lead field. Finally, it is shown that the selection of the regularization parameter with Generalized Cross-Validation (GCV) is close to the "oracle" choice based on the ground truth. When evaluated with the real 89 resting state EEGs, rREST consistently yields the lowest GCV. This study provides a novel perspective to the EEG reference problem by means of a unified inverse solution framework. It may allow additional principled theoretical formulations and numerical evaluation of performance.

The Natural History of Epilepsy in 163 Untreated Patients: Looking for “Oligoepilepsy”

PubMed Central

Gasparini, Sara; Ferlazzo, Edoardo; Leonardi, Cinzia Grazia; Cianci, Vittoria; Mumoli, Laura; Sueri, Chiara; Labate, Angelo; Gambardella, Antonio; Aguglia, Umberto

2016-01-01

The clinical evolution of untreated epilepsy has been rarely studied in developed countries, and the existence of a distinct syndrome characterized by rarely repeated seizures (oligoepilepsy) is debated. The aim of this study is to assess the natural history of 163 untreated patients with epilepsy in order to evaluate whether oligoepilepsy retains specific features. We retrospectively evaluated 7344 patients with ≥2 unprovoked seizures. Inclusion criteria: sufficient anamnestic/EEG data, disease duration ≥10 years, follow-up ≥3 years. Exclusion criteria: psychogenic seizures, natural history of disease <5 years. The 163 included subjects were divided into 2 groups according to seizure frequency: oligoepilepsy (≤1/year; 47 subjects) and controls (>1/year; 116 subjects). We also evaluated seizure frequency during the natural history. There were no differences between groups regarding duration of natural history, family history of epilepsy/febrile seizures, interictal EEG. Subjects with oligoepilepsy differed from controls in terms of sex (females 38% vs. 58%, p = 0.03) and drug resistance (6% vs 28%; p = 0.003). Juvenile myoclonic epilepsy was more frequent in controls (9.5% vs 0%, p = 0.04). Patients with oligoepilepsy, differently from controls, had stable seizure frequency. Oligoepilepsy represents a favourable evolution of different epileptic syndromes and keeps a stable seizure frequency over time. PMID:27657542

Early prediction of medication refractoriness in children with idiopathic epilepsy based on scalp EEG analysis.

PubMed

Lin, Lung-Chang; Ouyang, Chen-Sen; Chiang, Ching-Tai; Yang, Rei-Cheng; Wu, Rong-Ching; Wu, Hui-Chuan

2014-11-01

Refractory epilepsy often has deleterious effects on an individual's health and quality of life. Early identification of patients whose seizures are refractory to antiepileptic drugs is important in considering the use of alternative treatments. Although idiopathic epilepsy is regarded as having a significantly lower risk factor of developing refractory epilepsy, still a subset of patients with idiopathic epilepsy might be refractory to medical treatment. In this study, we developed an effective method to predict the refractoriness of idiopathic epilepsy. Sixteen EEG segments from 12 well-controlled patients and 14 EEG segments from 11 refractory patients were analyzed at the time of first EEG recordings before antiepileptic drug treatment. Ten crucial EEG feature descriptors were selected for classification. Three of 10 were related to decorrelation time, and four of 10 were related to relative power of delta/gamma. There were significantly higher values in these seven feature descriptors in the well-controlled group as compared to the refractory group. On the contrary, the remaining three feature descriptors related to spectral edge frequency, kurtosis, and energy of wavelet coefficients demonstrated significantly lower values in the well-controlled group as compared to the refractory group. The analyses yielded a weighted precision rate of 94.2%, and a 93.3% recall rate. Therefore, the developed method is a useful tool in identifying the possibility of developing refractory epilepsy in patients with idiopathic epilepsy.

A neural network method for detection of obstructive sleep apnea and narcolepsy based on pupil size and EEG.

PubMed

Liu, D; Pang, Z; Lloyd, S R

2008-02-01

Electroencephalogram (EEG) is able to indicate states of mental activity ranging from concentrated cognitive efforts to sleepiness. Such mental activity can be reflected by EEG energy. In particular, intrusion of EEG theta wave activity into the beta activity of active wakefulness has been interpreted as ensuing sleepiness. Pupil behavior can also provide information regarding alertness. This paper develops an innovative signal classification method that is capable of differentiating subjects with sleep disorders which cause excessive daytime sleepiness (EDS) from normal control subjects who do not have a sleep disorder based on EEG and pupil size. Subjects with sleep disorders include persons with untreated obstructive sleep apnea (OSA) and narcolepsy. The Yoss pupil staging rule is used to scale levels of wakefulness and at the same time theta energy ratios are calculated from the same 2-s sliding windows by Fourier or wavelet transforms. Then, an artificial neural network (NN) of modified adaptive resonance theory (ART2) is utilized to identify the two groups within a combined group of subjects including those with OSA and healthy controls. This grouping from the NN is then compared with the actual diagnostic classification of subjects as OSA or controls and is found to be 91% accurate in differentiating between the two groups. The same algorithm results in 90% correct differentiation between narcoleptic and control subjects.

Long-term outcome characteristics in mesial temporal lobe epilepsy with and without associated cortical dysplasia.

PubMed

Schmeiser, B; Hammen, T; Steinhoff, B J; Zentner, J; Schulze-Bonhage, A

2016-10-01

The intention of our study was to identify predictive characteristics for long-term seizure control and running down phenomenon after surgical treatment of pharmacoresistant mesiotemporal lobe epilepsy (mTLE) with and without associated cortical dysplasia. Our study comprises a consecutive series of 458 patients who underwent surgical treatment for intractable mTLE at the Epilepsy Center Freiburg. Data evaluated included semiology, duration and frequency of seizures, results of presurgical diagnostics including video-EEG monitoring, MRI, PET and SPECT as well as postoperative seizure outcome. Results were evaluated forming two groups: Group A consisted of isolated mesiotemporal lesions. Group B comprised patients with mTLE and additional focal cortical dysplasia (FCD). Statistical evaluation was based on the Kaplan Meier survival analysis, using log-rank-tests and a multivariate regression model. Postoperative running down phenomenon was defined as seizure freedom after a period of gradual reduction of postoperative seizure frequency. This was compared to patients with ongoing epilepsy. Complete seizure freedom was achieved in 65.0% of investigated patients at 1year and in 56.5% at long-term follow-up of ≥5 years after surgery. Corresponding results were 64.2% and 56.8% at 1 and ≥5 years, respectively in group A and 66.4% and 56.0%, respectively in group B. Predictive for favorable postoperative outcome in the total group were younger age at surgery, shorter duration of epilepsy, absence of secondarily generalized tonic-clonic seizures (SGTCS), presence of strictly ipsilateral temporal interictal epileptiform discharges (IEDs), complete resection of the lesion as well as absence of postoperative epileptiform activity and of early postoperative seizures. In subgroup analyses, patients of group A demonstrated longer postoperative seizure-free intervals with adolescent age at surgery, short duration of epilepsy before surgery and absence of SGTCS, whereas in patients of group B ipsilateral temporal seizure onset and strictly unilateral IEDs in EEG as well as complete resection were predictors for favorable seizure outcome. Furthermore, absence of early postoperative seizures and of spikes in EEG were predictive factors for long-term seizure-freedom in both subgroups. The running down phenomenon was found in 33 (7.2%) patients. None of the parameters evaluated demonstrated significant predictive power. Only late seizure onset and neoplastic lesions showed a trend for postoperative gradual seizure reduction in multivariate analyses. Depending on the presence or absence of focal cortical dysplasia in addition to mesiotemporal structural alterations, predictors of long-term seizure control differed regarding the relevant clinical and electrophysiological features. This is important for specific patient counseling in respective groups. Copyright © 2016 Elsevier B.V. All rights reserved.

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

DTIC Science & Technology

2013-09-01

for Treating Warfighters with Combat-Related PTSD Using Real-Time fMRI and EEG -Assisted Neurofeedback . PRINCIPAL INVESTIGATOR: Jerzy Bodurka...Treating Warfighters with Combat-Related PTSD Using Real-Time fMRI and EEG -Assisted Neurofeedback . 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-12-1...rtfMRI-nf neurofeedback training with simultaneous EEG recordings, and a pre-, post-training clinical assessment battery to evaluate improvement on the

Quantification of EEG reactivity in comatose patients.

PubMed

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

2016-01-01

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

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.

Classification of epileptiform and wicket spike of EEG pattern using backpropagation neural network

NASA Astrophysics Data System (ADS)

Puspita, Juni Wijayanti; Jaya, Agus Indra; Gunadharma, Suryani

2017-03-01

Epilepsy is characterized by recurrent seizures that is resulted by permanent brain abnormalities. One of tools to support the diagnosis of epilepsy is Electroencephalograph (EEG), which describes the recording of brain electrical activity. Abnormal EEG patterns in epilepsy patients consist of Spike and Sharp waves. While both waves, there is a normal pattern that sometimes misinterpreted as epileptiform by electroenchepalographer (EEGer), namely Wicket Spike. The main difference of the three waves are on the time duration that related to the frequency. In this study, we proposed a method to classify a EEG wave into Sharp wave, Spike wave or Wicket spike group using Backpropagation Neural Network based on the frequency and amplitude of each wave. The results show that the proposed method can classifies the three group of waves with good accuracy.

Sparse EEG/MEG source estimation via a group lasso

PubMed Central

Lim, Michael; Ales, Justin M.; Cottereau, Benoit R.; Hastie, Trevor

2017-01-01

Non-invasive recordings of human brain activity through electroencephalography (EEG) or magnetoencelphalography (MEG) are of value for both basic science and clinical applications in sensory, cognitive, and affective neuroscience. Here we introduce a new approach to estimating the intra-cranial sources of EEG/MEG activity measured from extra-cranial sensors. The approach is based on the group lasso, a sparse-prior inverse that has been adapted to take advantage of functionally-defined regions of interest for the definition of physiologically meaningful groups within a functionally-based common space. Detailed simulations using realistic source-geometries and data from a human Visual Evoked Potential experiment demonstrate that the group-lasso method has improved performance over traditional ℓ2 minimum-norm methods. In addition, we show that pooling source estimates across subjects over functionally defined regions of interest results in improvements in the accuracy of source estimates for both the group-lasso and minimum-norm approaches. PMID:28604790

Stable Scalp EEG Spatiospectral Patterns Across Paradigms Estimated by Group ICA.

PubMed

Labounek, René; Bridwell, David A; Mareček, Radek; Lamoš, Martin; Mikl, Michal; Slavíček, Tomáš; Bednařík, Petr; Baštinec, Jaromír; Hluštík, Petr; Brázdil, Milan; Jan, Jiří

2018-01-01

Electroencephalography (EEG) oscillations reflect the superposition of different cortical sources with potentially different frequencies. Various blind source separation (BSS) approaches have been developed and implemented in order to decompose these oscillations, and a subset of approaches have been developed for decomposition of multi-subject data. Group independent component analysis (Group ICA) is one such approach, revealing spatiospectral maps at the group level with distinct frequency and spatial characteristics. The reproducibility of these distinct maps across subjects and paradigms is relatively unexplored domain, and the topic of the present study. To address this, we conducted separate group ICA decompositions of EEG spatiospectral patterns on data collected during three different paradigms or tasks (resting-state, semantic decision task and visual oddball task). K-means clustering analysis of back-reconstructed individual subject maps demonstrates that fourteen different independent spatiospectral maps are present across the different paradigms/tasks, i.e. they are generally stable.

Developing an Adaptability Training Strategy and Policy for the DoD

DTIC Science & Technology

2008-10-01

might include monitoring of trainees using electroencephalogram ( EEG ) technology to gain neurofeedback during scenario performance. In order to...group & adequate sample; pre and post iii. Possibly including EEG monitoring (and even neurofeedback ) 4. Should seek to determine general...Dr. John Cowan has developed a system called the Peak Achievement Trainer (PAT) EEG , which traces electrical activity in the brain and provides

A capacitive, biocompatible and adhesive electrode for long-term and cap-free monitoring of EEG signals.

PubMed

Lee, Seung Min; Kim, Jeong Hun; Byeon, Hang Jin; Choi, Yoon Young; Park, Kwang Suk; Lee, Sang-Hoon

2013-06-01

Long-term electroencephalogram (EEG) monitoring broadens EEG applications to various areas, but it requires cap-free recording of EEG signals. Our objective here is to develop a capacitive, small-sized, adhesive and biocompatible electrode for the cap-free and long-term EEG monitoring. We have developed an electrode made of polydimethylsiloxane (PDMS) and adhesive PDMS for EEG monitoring. This electrode can be attached to a hairy scalp and be completely hidden by the hair. We tested its electrical and mechanical (adhesive) properties by measuring voltage gain to frequency and adhesive force using 30 repeat cycles of the attachment and detachment test. Electrode performance on EEG was evaluated by alpha rhythm detection and measuring steady state visually evoked potential and N100 auditory evoked potential. We observed the successful recording of alpha rhythm and evoked signals to diverse stimuli with high signal quality. The biocompatibility of the electrode was verified and a survey found that the electrode was comfortable and convenient to wear. These results indicate that the proposed EEG electrode is suitable and convenient for long term EEG monitoring.

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.

Evaluation of Dry Sensors for Neonatal EEG recordings

PubMed Central

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

2015-01-01

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

Using a virtual training program to train community neurologist on EEG reading skills.

PubMed

Ochoa, Juan; Naritoku, Dean K

2012-01-01

EEG training requires iterative exposure of different patterns with continuous feedback from the instructor. This training is traditionally acquired through a traditional fellowship program, but only 28% of neurologists in training plan to do a fellowship in EEG. The purpose of this study was to determine the value of online EEG training to improve EEG knowledge among general neurologists. The participants were general neurologists invited through bulk e-mail and paid a fee to enroll in the virtual EEG program. A 40-question pretest exam was performed before training. The training included 4 online learning units about basic EEG principles and 40 online clinical EEG tutorials. In addition there were weekly live teleconferences for Q&A sessions. At the end of the program, the participants were asked to complete a posttest exam. Fifteen of 20 participants successfully completed the program and took both the pre- and posttest exams. All the subjects scored significantly higher in the posttest compared to their baseline score. The average score in the pretest evaluation was 61.7% and the posttest average was 87.8% (p = .0002, two-tailed). Virtual EEG training can improve EEG knowledge among community neurologists.

Driving behavior recognition using EEG data from a simulated car-following experiment.

PubMed

Yang, Liu; Ma, Rui; Zhang, H Michael; Guan, Wei; Jiang, Shixiong

2018-07-01

Driving behavior recognition is the foundation of driver assistance systems, with potential applications in automated driving systems. Most prevailing studies have used subjective questionnaire data and objective driving data to classify driving behaviors, while few studies have used physiological signals such as electroencephalography (EEG) to gather data. To bridge this gap, this paper proposes a two-layer learning method for driving behavior recognition using EEG data. A simulated car-following driving experiment was designed and conducted to simultaneously collect data on the driving behaviors and EEG data of drivers. The proposed learning method consists of two layers. In Layer I, two-dimensional driving behavior features representing driving style and stability were selected and extracted from raw driving behavior data using K-means and support vector machine recursive feature elimination. Five groups of driving behaviors were classified based on these two-dimensional driving behavior features. In Layer II, the classification results from Layer I were utilized as inputs to generate a k-Nearest-Neighbor classifier identifying driving behavior groups using EEG data. Using independent component analysis, a fast Fourier transformation, and linear discriminant analysis sequentially, the raw EEG signals were processed to extract two core EEG features. Classifier performance was enhanced using the adaptive synthetic sampling approach. A leave-one-subject-out cross validation was conducted. The results showed that the average classification accuracy for all tested traffic states was 69.5% and the highest accuracy reached 83.5%, suggesting a significant correlation between EEG patterns and car-following behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

Interhemispheric EEG differences in olfactory bulbectomized rats with different cognitive abilities and brain beta-amyloid levels.

PubMed

Bobkova, Natalia; Vorobyov, Vasily; Medvinskaya, Natalia; Aleksandrova, Irina; Nesterova, Inna

2008-09-26

Alterations in electroencephalogram (EEG) asymmetry and deficits in interhemispheric integration of information have been shown in patients with Alzheimer's disease (AD). However, no direct evidence of an association between EEG asymmetry, morphological markers in the brain, and cognition was found either in AD patients or in AD models. In this study we used rats with bilateral olfactory bulbectomy (OBX) as one of the AD models and measured their learning/memory abilities, brain beta-amyloid levels and EEG spectra in symmetrical frontal and occipital cortices. One year after OBX or sham-surgery, the rats were tested with the Morris water paradigm and assigned to three groups: sham-operated rats, SO, and OBX rats with virtually normal, OBX(+), or abnormal, OBX(-), learning (memory) abilities. In OBX vs. SO, the theta EEG activity was enhanced to a higher extent in the right frontal cortex and in the left occipital cortex. This produced significant interhemispheric differences in the frontal cortex of the OBX(-) rats and in the occipital cortex of both OBX groups. The beta1 EEG asymmetry in SO was attenuated in OBX(+) and completely eliminated in OBX(-). OBX produced highly significant beta2 EEG decline in the right frontal cortex, with OBX(-)>OBX(+) rank order of strength. The beta-amyloid level, examined by post-mortem immunological DOT-analysis in the cortex-hippocampus samples, was about six-fold higher in OBX(-) than in SO, but significantly less (enhanced by 82% vs. SO) in OBX(+) than in OBX(-). The involvement of the brain mediatory systems in the observed EEG asymmetry differences is discussed.

EEG

MedlinePlus

... injuries Infections Tumors EEG is also used to: Evaluate problems with sleep ( sleep disorders ) Monitor the brain ... Tissue death due to a blockage in blood flow (cerebral infarction) Drug or alcohol abuse Head injury ...

Electroencephalogram complexity analysis in children with attention-deficit/hyperactivity disorder during a visual cognitive task.

PubMed

Zarafshan, Hadi; Khaleghi, Ali; Mohammadi, Mohammad Reza; Moeini, Mahdi; Malmir, Nastaran

2016-01-01

The aim of this study was to investigate electroencephalogram (EEG) dynamics using complexity analysis in children with attention-deficit/hyperactivity disorder (ADHD) compared with healthy control children when performing a cognitive task. Thirty 7-12-year-old children meeting Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-5) criteria for ADHD and 30 healthy control children underwent an EEG evaluation during a cognitive task, and Lempel-Ziv complexity (LZC) values were computed. There were no significant differences between ADHD and control groups on age and gender. The mean LZC of the ADHD children was significantly larger than healthy children over the right anterior and right posterior regions during the cognitive performance. In the ADHD group, complexity of the right hemisphere was higher than that of the left hemisphere, but the complexity of the left hemisphere was higher than that of the right hemisphere in the normal group. Although fronto-striatal dysfunction is considered conclusive evidence for the pathophysiology of ADHD, our arithmetic mental task has provided evidence of structural and functional changes in the posterior regions and probably cerebellum in ADHD.

Reduction in time-to-sleep through EEG based brain state detection and audio stimulation.

PubMed

Zhuo Zhang; Cuntai Guan; Ti Eu Chan; Juanhong Yu; Aung Aung Phyo Wai; Chuanchu Wang; Haihong Zhang

2015-08-01

We developed an EEG- and audio-based sleep sensing and enhancing system, called iSleep (interactive Sleep enhancement apparatus). The system adopts a closed-loop approach which optimizes the audio recording selection based on user's sleep status detected through our online EEG computing algorithm. The iSleep prototype comprises two major parts: 1) a sleeping mask integrated with a single channel EEG electrode and amplifier, a pair of stereo earphones and a microcontroller with wireless circuit for control and data streaming; 2) a mobile app to receive EEG signals for online sleep monitoring and audio playback control. In this study we attempt to validate our hypothesis that appropriate audio stimulation in relation to brain state can induce faster onset of sleep and improve the quality of a nap. We conduct experiments on 28 healthy subjects, each undergoing two nap sessions - one with a quiet background and one with our audio-stimulation. We compare the time-to-sleep in both sessions between two groups of subjects, e.g., fast and slow sleep onset groups. The p-value obtained from Wilcoxon Signed Rank Test is 1.22e-04 for slow onset group, which demonstrates that iSleep can significantly reduce the time-to-sleep for people with difficulty in falling sleep.

Analysis of connectivity in NeuCube spiking neural network models trained on EEG data for the understanding of functional changes in the brain: A case study on opiate dependence treatment.

PubMed

Capecci, Elisa; Kasabov, Nikola; Wang, Grace Y

2015-08-01

The paper presents a methodology for the analysis of functional changes in brain activity across different conditions and different groups of subjects. This analysis is based on the recently proposed NeuCube spiking neural network (SNN) framework and more specifically on the analysis of the connectivity of a NeuCube model trained with electroencephalography (EEG) data. The case study data used to illustrate this method is EEG data collected from three groups-subjects with opiate addiction, patients undertaking methadone maintenance treatment, and non-drug users/healthy control group. The proposed method classifies more accurately the EEG data than traditional statistical and artificial intelligence (AI) methods and can be used to predict response to treatment and dose-related drug effect. But more importantly, the method can be used to compare functional brain activities of different subjects and the changes of these activities as a result of treatment, which is a step towards a better understanding of both the EEG data and the brain processes that generated it. The method can also be used for a wide range of applications, such as a better understanding of disease progression or aging. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed

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

2012-06-14

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

Entropy is more resistant to artifacts than bispectral index in brain-dead organ donors.

PubMed

Wennervirta, Johanna; Salmi, Tapani; Hynynen, Markku; Yli-Hankala, Arvi; Koivusalo, Anna-Maria; Van Gils, Mark; Pöyhiä, Reino; Vakkuri, Anne

2007-01-01

To evaluate the usefulness of entropy and the bispectral index (BIS) in brain-dead subjects. A prospective, open, nonselective, observational study in the university hospital. 16 brain-dead organ donors. Time-domain electroencephalography (EEG), spectral entropy of the EEG, and BIS were recorded during solid organ harvest. State entropy differed significantly from 0 (isoelectric EEG) 28%, response entropy 29%, and BIS 68% of the total recorded time. The median values during the operation were state entropy 0.0, response entropy 0.0, and BIS 3.0. In four of 16 organ donors studied the EEG was not isoelectric, and nonreactive rhythmic activity was noted in time-domain EEG. After excluding the results from subjects with persistent residual EEG activity state entropy, response entropy, and BIS values differed from zero 17%, 18%, and 62% of the recorded time, respectively. Median values were 0.0, 0.0, and 2.0 for state entropy, response entropy, and BIS, respectively. The highest index values in entropy and BIS monitoring were recorded without neuromuscular blockade. The main sources of artifacts were electrocauterization, 50-Hz artifact, handling of the donor, ballistocardiography, electromyography, and electrocardiography. Both entropy and BIS showed nonzero values due to artifacts after brain death diagnosis. BIS was more liable to artifacts than entropy. Neither of these indices are diagnostic tools, and care should be taken when interpreting EEG and EEG-derived indices in the evaluation of brain death.

Wireless and wearable EEG system for evaluating driver vigilance.

PubMed

Lin, Chin-Teng; Chuang, Chun-Hsiang; Huang, Chih-Sheng; Tsai, Shu-Fang; Lu, Shao-Wei; Chen, Yen-Hsuan; Ko, Li-Wei

2014-04-01

Brain activity associated with attention sustained on the task of safe driving has received considerable attention recently in many neurophysiological studies. Those investigations have also accurately estimated shifts in drivers' levels of arousal, fatigue, and vigilance, as evidenced by variations in their task performance, by evaluating electroencephalographic (EEG) changes. However, monitoring the neurophysiological activities of automobile drivers poses a major measurement challenge when using a laboratory-oriented biosensor technology. This work presents a novel dry EEG sensor based mobile wireless EEG system (referred to herein as Mindo) to monitor in real time a driver's vigilance status in order to link the fluctuation of driving performance with changes in brain activities. The proposed Mindo system incorporates the use of a wireless and wearable EEG device to record EEG signals from hairy regions of the driver conveniently. Additionally, the proposed system can process EEG recordings and translate them into the vigilance level. The study compares the system performance between different regression models. Moreover, the proposed system is implemented using JAVA programming language as a mobile application for online analysis. A case study involving 15 study participants assigned a 90 min sustained-attention driving task in an immersive virtual driving environment demonstrates the reliability of the proposed system. Consistent with previous studies, power spectral analysis results confirm that the EEG activities correlate well with the variations in vigilance. Furthermore, the proposed system demonstrated the feasibility of predicting the driver's vigilance in real time.

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

PubMed

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

2016-06-01

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

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

Corticosteroid therapy in regressive autism: a retrospective study of effects on the Frequency Modulated Auditory Evoked Response (FMAER), language, and behavior

PubMed Central

2014-01-01

Background Up to a third of children with Autism Spectrum Disorder (ASD) manifest regressive autism (R-ASD).They show normal early development followed by loss of language and social skills. Absent evidence-based therapies, anecdotal evidence suggests improvement following use of corticosteroids. This study examined the effects of corticosteroids for R-ASD children upon the 4 Hz frequency modulated evoked response (FMAER) arising from language cortex of the superior temporal gyrus (STG) and upon EEG background activity, language, and behavior. An untreated clinical convenience sample of ASD children served as control sample. Methods Twenty steroid-treated R-ASD (STAR) and 24 not-treated ASD patients (NSA), aged 3 - 5 years, were retrospectively identified from a large database. All study participants had two sequential FMAER and EEG studies;Landau-Kleffner syndrome diagnosis was excluded. All subjects’ records contained clinical receptive and expressive language ratings based upon a priori developed metrics. The STAR group additionally was scored behaviorally regarding symptom severity as based on the Diagnostic and Statistical Manual IV (DSM-IV) ASD criteria list. EEGs were visually scored for abnormalities. FMAER responses were assessed quantitatively by spectral analysis. Treated and untreated group means and standard deviations for the FMAER, EEG, language, and behavior, were compared by paired t-test and Fisher’s exact tests. Results The STAR group showed a significant increase in the 4 Hz FMAER spectral response and a significant reduction in response distortion compared to the NSA group. Star group subjects’ language ratings were significantly improved and more STAR than NSA group subjects showed significant language improvement. Most STAR group children showed significant behavioral improvement after treatment. STAR group language and behavior improvement was retained one year after treatment. Groups did not differ in terms of minor EEG abnormalities. Steroid treatment produced no lasting morbidity. Conclusions Steroid treatment was associated with a significantly increased FMAER response magnitude, reduction of FMAER response distortion, and improvement in language and behavior scores. This was not observed in the non-treated group. These pilot findings warrant a prospective randomized validation trial of steroid treatment for R-ASD utilizing FMAER, EEG, and standardized ASD, language and behavior measures, and a longer follow-up period. Please see related article http://www.biomedcentral.com/1741-7015/12/79 PMID:24885033

How many sleep stages do we need for an efficient automatic insomnia diagnosis?

PubMed

Hamida, Sana Tmar-Ben; Glos, Martin; Penzel, Thomas; Ahmed, Beena

2016-08-01

Tools used by clinicians to diagnose and treat insomnia typically include sleep diaries and questionnaires. Overnight polysomnography (PSG) recordings are used when the initial diagnosis is uncertain due to the presence of other sleep disorders or when the treatment, either behavioral or pharmacologic, is unsuccessful. However, the analysis and the scoring of PSG data are time-consuming. To simplify the diagnosis process, in this paper we have proposed an efficient insomnia detection algorithm based on a central single electroencephalographic (EEG) channel (C3) using only deep sleep. We also analyzed several spectral and statistical EEG features of good sleeper controls and subjects suffering from insomnia in different sleep stages to identify the features that offered the best discrimination between the two groups. Our proposed algorithm was evaluated using EEG recordings from 19 patients diagnosed with primary insomnia (11 females, 8 males) and 16 matched control subjects (11 females, 5 males). The sensitivity of our algorithm is 92%, the specificity is 89.9%, the Cohen's kappa is 0.81 and the agreement is 91%, indicating the effectiveness of our proposed method.

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.

A close look at EEG in subacute sclerosing panencephalitis.

PubMed

Demir, Nurhak; Cokar, Ozlem; Bolukbasi, Feray; Demirbilek, Veysi; Yapici, Zuhal; Yalcinkaya, Cengiz; Direskeneli, Guher Saruhan; Yentur, Sibel; Onal, Emel; Yilmaz, Gulden; Dervent, Aysin

2013-08-01

To define atypical clinical and EEG features of patients with subacute sclerosing panencephalitis that may require an overview of differential diagnosis. A total of 66 EEGs belonging to 53 (17 females and 36 males) consecutive patients with serologically confirmed subacute sclerosing panencephalitis were included in this study. Patient files and EEG data were evaluated retrospectively. EEGs included in the study were sleep-waking EEGs and/or sleep-waking video-EEG records with at least 2 hours duration. Cranial MRIs of the patients taken 2 months before or after the EEG records were included. Age range at the onset of the disease was 15 to 192 months (mean age: 80.02 months). Epilepsy was diagnosed in 21 (43%) patients. Among epileptic seizures excluding myoclonic jerks, generalized tonic-clonic type constituted the majority (58%). Tonic seizures were documented during the video-EEG recordings in four patients. Epileptogenic activities were found in 56 (83%) EEG recordings. They were localized mainly in frontal (58%), posterior temporal, parietal, occipital (26%), and centrotemporal (8%) regions. Multiple foci were detected in 26 recordings (39%). Epileptiform activities in the 39 (59%) EEGs appeared as unilateral or bilateral diffuse paroxysmal discharges. Recognition of uncommon clinical and EEG findings of subacute sclerosing panencephalitis, especially in countries where subacute sclerosing panencephalitis has not been eliminated yet, could be helpful in prevention of misdiagnosis and delay in the management of improvable conditions.

Wireless multichannel electroencephalography in the newborn.

PubMed

Ibrahim, Z H; Chari, G; Abdel Baki, S; Bronshtein, V; Kim, M R; Weedon, J; Cracco, J; Aranda, J V

2016-01-01

First, to determine the feasibility of an ultra-compact wireless device (microEEG) to obtain multichannel electroencephalographic (EEG) recording in the Neonatal Intensive Care Unit (NICU). Second, to identify problem areas in order to improve wireless EEG performance. 28 subjects (gestational age 24-30 weeks, postnatal age <30 days) were recruited at 2 sites as part of an ongoing study of neonatal apnea and wireless EEG. Infants underwent 8-9 hour EEG recordings every 2-4 weeks using an electrode cap (ANT-Neuro) connected to the wireless EEG device (Bio-Signal Group). A 23 electrode configuration was used incorporating the International 10-20 System. The device transmitted recordings wirelessly to a laptop computer for bedside assessment. The recordings were assessed by a pediatric neurophysiologist for interpretability. A total of 84 EEGs were recorded from 28 neonates. 61 EEG studies were obtained in infants prior to 35 weeks corrected gestational age (CGA). NICU staff placed all electrode caps and initiated all recordings. Of these recordings 6 (10%) were uninterpretable due to artifacts and one study could not be accessed. The remaining 54 (89%) EEG recordings were acceptable for clinical review and interpretation by a pediatric neurophysiologist. Of the recordings obtained at 35 weeks corrected gestational age or later only 11 out of 23 (48%) were interpretable. Wireless EEG devices can provide practical, continuous, multichannel EEG monitoring in preterm neonates. Their small size and ease of use could overcome obstacles associated with EEG recording and interpretation in the NICU.

Infant polysomnography: reliability and validity of infant arousal assessment.

PubMed

Crowell, David H; Kulp, Thomas D; Kapuniai, Linda E; Hunt, Carl E; Brooks, Lee J; Weese-Mayer, Debra E; Silvestri, Jean; Ward, Sally Davidson; Corwin, Michael; Tinsley, Larry; Peucker, Mark

2002-10-01

Infant arousal scoring based on the Atlas Task Force definition of transient EEG arousal was evaluated to determine (1). whether transient arousals can be identified and assessed reliably in infants and (2). whether arousal and no-arousal epochs scored previously by trained raters can be validated reliably by independent sleep experts. Phase I for inter- and intrarater reliability scoring was based on two datasets of sleep epochs selected randomly from nocturnal polysomnograms of healthy full-term, preterm, idiopathic apparent life-threatening event cases, and siblings of Sudden Infant Death Syndrome infants of 35 to 64 weeks postconceptional age. After training, test set 1 reliability was assessed and discrepancies identified. After retraining, test set 2 was scored by the same raters to determine interrater reliability. Later, three raters from the trained group rescored test set 2 to assess inter- and intrarater reliabilities. Interrater and intrarater reliability kappa's, with 95% confidence intervals, ranged from substantial to almost perfect levels of agreement. Interrater reliabilities for spontaneous arousals were initially moderate and then substantial. During the validation phase, 315 previously scored epochs were presented to four sleep experts to rate as containing arousal or no-arousal events. Interrater expert agreements were diverse and considered as noninterpretable. Concordance in sleep experts' agreements, based on identification of the previously sampled arousal and no-arousal epochs, was used as a secondary evaluative technique. Results showed agreement by two or more experts on 86% of the Collaborative Home Infant Monitoring Evaluation Study arousal scored events. Conversely, only 1% of the Collaborative Home Infant Monitoring Evaluation Study-scored no-arousal epochs were rated as an arousal. In summary, this study presents an empirically tested model with procedures and criteria for attaining improved reliability in transient EEG arousal assessments in infants using the modified Atlas Task Force standards. With training based on specific criteria, substantial inter- and intrarater agreement in identifying infant arousals was demonstrated. Corroborative validation results were too disparate for meaningful interpretation. Alternate evaluation based on concordance agreements supports reliance on infant EEG criteria for assessment. Results mandate additional confirmatory validation studies with specific training on infant EEG arousal assessment criteria.

Diagnostic and therapeutic yield of a patient-controlled portable EEG device with dry electrodes for home-monitoring neurological outpatients-rationale and protocol of the HOMEONE pilot study.

PubMed

Neumann, Thomas; Baum, Anne Katrin; Baum, Ulrike; Deike, Renate; Feistner, Helmut; Hinrichs, Hermann; Stokes, Joseph; Robra, Bernt-Peter

2018-01-01

The HOME ONE study is part of the larger HOME project, which aims to provide evidence of diagnostic and therapeutic yield ("change of management") of a patient-controlled portable EEG device with dry electrodes for the purposes of EEG home-monitoring neurological outpatients. The HOME ONE study is the first step in the process of investigating whether outpatient EEG home-monitoring changes the diagnosis and treatment of patients in comparison to conventional EEG ("change of management"). Both EEG devices (conventional and portable) will be systematically compared via a two-phase intra-individual assessment.In the first phase (pilot study phase), both EEG devices will be used within neurologist practices (all other things being equal). This pilot study (involving 130 patients) will evaluate the technical usability and efficacy of the new portable dry electrode EEG recorder in comparison to conventional EEG devices. Judgements will be based on technical assessments and EEG record examinations of private practitioners and two experienced neurologists (percent of concordant readings and kappa values).The second phase (feasibility study phase) aims to assess patients' acceptability and feasibility of the EEG home-monitoring and will provide insights into the extent diagnostic and therapeutic yields can be expected.For this purpose, a conventional EEG will be recorded in neurologist practices. Thereafter, the practice staff will instruct the patients on how the portable EEG device functions. The patients will subsequently use the devices in their home environment.The evaluation will compare the before and after documented diagnostic findings and the therapeutic consequences of the private practitioners with those of two experienced neurologists. To the best of our knowledge, this will be the first study of its kind to examine new approaches to diagnosing unclear consciousness disorders or other disorders of the CNS or the cardiovascular system through the use of a patient-controlled portable EEG device with dry electrodes for the purpose of home-monitoring neurological outpatients. If the two phases of the HOME ONE study provide sufficient evidence of diagnostic and therapeutic yields, this would justify (indication-specific) full-scale randomized controlled trials or observational studies. DRKS DRKS00012685. Registered 9 August 2017, retrospectively registered.

Investigation of attention deficit hyperactivity disorder (ADHD) sub-types in children via EEG frequency domain analysis.

PubMed

Aldemir, Ramazan; Demirci, Esra; Per, Huseyin; Canpolat, Mehmet; Özmen, Sevgi; Tokmakçı, Mahmut

2018-04-01

To investigate the frequency domain effects and changes in electroencephalography (EEG) signals in children diagnosed with attention deficit hyperactivity disorder (ADHD). The study contains 40 children. All children were between the ages of 7 and 12 years. Participants were classified into four groups which were ADHD (n=20), ADHD-I (ADHD-Inattentive type) (n=10), ADHD-C (ADHD-Combined type) (n=10), and control (n=20) groups. In this study, the frequency domain of EEG signals for ADHD, subtypes and control groups were analyzed and compared using Matlab software. The mean age of the ADHD children's group was 8.7 years and the control group 9.1 years. Spectral analysis of mean power (μV 2 ) and relative-mean power (%) was carried out for four different frequency bands: delta (0--4 Hz), theta (4--8 Hz), alpha (8--13 Hz) and beta (13--32 Hz). The ADHD and subtypes of ADHD-I, and ADHD-C groups had higher average power value of delta and theta band than that of control group. However, this is not the case for alpha and beta bands. Increases in delta/beta ratio and statistical significance were found only between ADHD-I and control group, and in delta/beta, theta/delta ratio statistical significance values were found to exist between ADHD-C and control group. EEG analyzes can be used as an alternative method when ADHD subgroups are identified.

Relationship between prolonged neural suppression and cerebral hemodynamic dysfunction during hypothermia in asphyxiated piglets.

PubMed

Jinnai, Wataru; Nakamura, Shinji; Koyano, Kosuke; Yamato, Satoshi; Wakabayashi, Takayuki; Htun, Yinmon; Nakao, Yasuhiro; Iwase, Takashi; Nakamura, Makoto; Yasuda, Saneyuki; Ueno, Masaki; Miki, Takanori; Kusaka, Takashi

2018-05-19

Hypothermia (HT) improves the outcome of neonatal hypoxic-ischemic encephalopathy. Here, we investigated changes during HT in cortical electrical activity using amplitude-integrated electroencephalography (aEEG) and in cerebral blood volume (CBV) and cerebral hemoglobin oxygen saturation using near-infrared time-resolved spectroscopy (TRS) and compared the results with those obtained during normothermia (NT) after a hypoxic-ischemic (HI) insult in a piglet model of asphyxia. We previously reported that a greater increase in CBV can indicate greater pressure-passive cerebral perfusion due to more severe brain injury and correlates with prolonged neural suppression during NT. We hypothesized that when energy metabolism is suppressed during HT, the cerebral hemodynamics of brains with severe injury would be suppressed to a greater extent, resulting in a greater decrease in CBV during HT that would correlate with prolonged neural suppression after insult. Twenty-six piglets were divided into four groups: control with NT (C-NT, n = 3), control with HT (C-HT, n = 3), HI insult with NT (HI-NT, n = 10), and HI insult with HT (HI-HT, n = 10). TRS and aEEG were performed in all groups until 24 h after the insult. Piglets in the HI-HT group were maintained in a hypothermic state for 24 h after the insult. There was a positive linear correlation between changes in CBV at 1, 3, 6, and 12 h after the insult and low-amplitude aEEG (<5 µV) duration after insult in the HI-NT group, but a negative linear correlation between these two parameters at 6 and 12 h after the insult in the HI-HT group. The aEEG background score and low-amplitude EEG duration after the insult did not differ between these two groups. A longer low-amplitude EEG duration after insult was associated with a greater CBV decrease during HT in the HI-HT group, suggesting that brains with more severe neural suppression could be more prone to HT-induced suppression of cerebral metabolism and circulation. Copyright © 2018 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study.

PubMed

Duffy, Frank H; Als, Heidelise

2012-06-26

The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact. Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls. Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences for the ASD-groups, when compared to the controls. Average spectral loading per factor was wide (10.1 Hz). Classification success suggests a stable coherence loading pattern that differentiates ASD- from C-group subjects. This might constitute an EEG coherence-based phenotype of childhood autism. The predominantly reduced short-distance coherences may indicate poor local network function. The increased long-distance coherences may represent compensatory processes or reduced neural pruning. The wide average spectral range of factor loadings may suggest over-damped neural networks.

Absence of early epileptiform abnormalities predicts lack of seizures on continuous EEG.

PubMed

Shafi, Mouhsin M; Westover, M Brandon; Cole, Andrew J; Kilbride, Ronan D; Hoch, Daniel B; Cash, Sydney S

2012-10-23

To determine whether the absence of early epileptiform abnormalities predicts absence of later seizures on continuous EEG monitoring of hospitalized patients. We retrospectively reviewed 242 consecutive patients without a prior generalized convulsive seizure or active epilepsy who underwent continuous EEG monitoring lasting at least 18 hours for detection of nonconvulsive seizures or evaluation of unexplained altered mental status. The findings on the initial 30-minute screening EEG, subsequent continuous EEG recordings, and baseline clinical data were analyzed. We identified early EEG findings associated with absence of seizures on subsequent continuous EEG. Seizures were detected in 70 (29%) patients. A total of 52 patients had their first seizure in the initial 30 minutes of continuous EEG monitoring. Of the remaining 190 patients, 63 had epileptiform discharges on their initial EEG, 24 had triphasic waves, while 103 had no epileptiform abnormalities. Seizures were later detected in 22% (n = 14) of studies with epileptiform discharges on their initial EEG, vs 3% (n = 3) of the studies without epileptiform abnormalities on initial EEG (p < 0.001). In the 3 patients without epileptiform abnormalities on initial EEG but with subsequent seizures, the first epileptiform discharge or electrographic seizure occurred within the first 4 hours of recording. In patients without epileptiform abnormalities during the first 4 hours of recording, no seizures were subsequently detected. Therefore, EEG features early in the recording may indicate a low risk for seizures, and help determine whether extended monitoring is necessary.

Absence of early epileptiform abnormalities predicts lack of seizures on continuous EEG

PubMed Central

Westover, M. Brandon; Cole, Andrew J.; Kilbride, Ronan D.; Hoch, Daniel B.; Cash, Sydney S.

2012-01-01

Objective: To determine whether the absence of early epileptiform abnormalities predicts absence of later seizures on continuous EEG monitoring of hospitalized patients. Methods: We retrospectively reviewed 242 consecutive patients without a prior generalized convulsive seizure or active epilepsy who underwent continuous EEG monitoring lasting at least 18 hours for detection of nonconvulsive seizures or evaluation of unexplained altered mental status. The findings on the initial 30-minute screening EEG, subsequent continuous EEG recordings, and baseline clinical data were analyzed. We identified early EEG findings associated with absence of seizures on subsequent continuous EEG. Results: Seizures were detected in 70 (29%) patients. A total of 52 patients had their first seizure in the initial 30 minutes of continuous EEG monitoring. Of the remaining 190 patients, 63 had epileptiform discharges on their initial EEG, 24 had triphasic waves, while 103 had no epileptiform abnormalities. Seizures were later detected in 22% (n = 14) of studies with epileptiform discharges on their initial EEG, vs 3% (n = 3) of the studies without epileptiform abnormalities on initial EEG (p < 0.001). In the 3 patients without epileptiform abnormalities on initial EEG but with subsequent seizures, the first epileptiform discharge or electrographic seizure occurred within the first 4 hours of recording. Conclusions: In patients without epileptiform abnormalities during the first 4 hours of recording, no seizures were subsequently detected. Therefore, EEG features early in the recording may indicate a low risk for seizures, and help determine whether extended monitoring is necessary. PMID:23054233

Individual Differences in Cerebral Cortical Activity During Stress: Understanding and Intervention to Enhance Shooting Performance

DTIC Science & Technology

2009-04-30

successfully raised physiological and 15. SUBJECT TERMS brain, cognitive neuroscience, EEG , neurofeedback , competition, stress, neuroendocrine, shooting...efficacy of the Neurofeedback training to elevate frontal EEG asymmetry (F4 minus F3 alpha power) in an attempt to enhance emotion regulation. The...observed a remarkable increase or synchrony of EEG alpha power (i.e., low-alpha) across the general scalp topography for both groups ( neurofeedback

Wearable electroencephalography. What is it, why is it needed, and what does it entail?

PubMed

Casson, Alexander; Yates, David; Smith, Shelagh; Duncan, John; Rodriguez-Villegas, Esther

2010-01-01

The electroencephalogram (EEG) is a classic noninvasive method for measuring a person's brain waves and is used in a large number of fields: from epilepsy and sleep disorder diagnosis to brain-computer interfaces (BCIs). Electrodes are placed on the scalp to detect the microvolt-sized signals that result from synchronized neuronal activity within the brain. Current long-term EEG monitoring is generally either carried out as an inpatient in combination with video recording and long cables to an amplifier and recording unit or is ambulatory. In the latter, the EEG recorder is portable but bulky, and in principle, the subject can go about their normal daily life during the recording. In practice, however, this is rarely the case. It is quite common for people undergoing ambulatory EEG monitoring to take time off work and stay at home rather than be seen in public with such a device. Wearable EEG is envisioned as the evolution of ambulatory EEG units from the bulky, limited lifetime devices available today to small devices present only on the head that can record EEG for days, weeks, or months at a time. Such miniaturized units could enable prolonged monitoring of chronic conditions such as epilepsy and greatly improve the end-user acceptance of BCI systems. In this article, we aim to provide a review and overview of wearable EEG technology, answering the questions: What is it, why is it needed, and what does it entail? We first investigate the requirements of portable EEG systems and then link these to the core applications of wearable EEG technology: epilepsy diagnosis, sleep disorder diagnosis, and BCIs. As a part of our review, we asked 21 neurologists (as a key user group) for their views on wearable EEG. This group highlighted that wearable EEG will be an essential future tool. Our descriptions here will focus mainly on epilepsy and the medical applications of wearable EEG, as this is the historical background of the EEG, our area of expertise, and a core motivating area in itself, but we will also discuss the other application areas. We continue by considering the forthcoming research challenges, principally new electrode technology and lower power electronics, and we outline our approach for dealing with the electronic power issues. We believe that the optimal approach to realizing wearable EEG technology is not to optimize any one part but to find the best set of tradeoffs at both the system and implementation level. In this article, we discuss two of these tradeoffs in detail: investigating the online compression of EEG data to reduce the system power consumption and the optimal method for providing this data compression.

Atypical EEG power correlates with indiscriminately friendly behavior in internationally adopted children.

PubMed

Tarullo, Amanda R; Garvin, Melissa C; Gunnar, Megan R

2011-03-01

While effects of institutional care on behavioral development have been studied extensively, effects on neural systems underlying these socioemotional and attention deficits are only beginning to be examined. The current study assessed electroencephalogram (EEG) power in 18-month-old internationally adopted, postinstitutionalized children (n = 37) and comparison groups of nonadopted children (n = 47) and children internationally adopted from foster care (n = 39). For their age, postinstitutionalized children had an atypical EEG power distribution, with relative power concentrated in lower frequency bands compared with nonadopted children. Both internationally adopted groups had lower absolute alpha power than nonadopted children. EEG power was not related to growth at adoption or to global cognitive ability. Atypical EEG power distribution at 18 months predicted indiscriminate friendliness and poorer inhibitory control at 36 months. Both postinstitutionalized and foster care children were more likely than nonadopted children to exhibit indiscriminate friendliness. Results are consistent with a cortical hypoactivation model of the effects of early deprivation on neural development and provide initial evidence associating this atypical EEG pattern with indiscriminate friendliness. Outcomes observed in the foster care children raise questions about the specificity of institutional rearing as a risk factor and emphasize the need for broader consideration of the effects of early deprivation and disruptions in care. PsycINFO Database Record (c) 2011 APA, all rights reserved.

Atypical EEG Power Correlates With Indiscriminately Friendly Behavior in Internationally Adopted Children

PubMed Central

Tarullo, Amanda R.; Garvin, Melissa C.; Gunnar, Megan R.

2012-01-01

While effects of institutional care on behavioral development have been studied extensively, effects on neural systems underlying these socioemotional and attention deficits are only beginning to be examined. The current study assessed electroencephalogram (EEG) power in 18-month-old internationally adopted, post-institutionalized children (n = 37) and comparison groups of non-adopted children (n = 47) and children internationally adopted from foster care (n = 39). For their age, post-institutionalized children had an atypical EEG power distribution, with relative power concentrated in lower frequency bands compared to non-adopted children. Both internationally adopted groups had lower absolute alpha power than non-adopted children. EEG power was not related to growth at adoption or to global cognitive ability. Atypical EEG power distribution at 18 months predicted indiscriminate friendliness and poorer inhibitory control at 36 months. Both post-institutionalized and foster care children were more likely than non-adopted children to exhibit indiscriminate friendliness. Results are consistent with a cortical hypoactivation model of the effects of early deprivation on neural development and provide initial evidence associating this atypical EEG pattern with indiscriminate friendliness. Outcomes observed in the foster care children raise questions about the specificity of institutional rearing as a risk factor and emphasize the need for broader consideration of the effects of early deprivation and disruptions in care. PMID:21171750

Cerebral hemodynamic changes and electroencephalography during carotid endarterectomy

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

Algotsson, L.; Messeter, K.; Rehncrona, S.

Some patients undergoing endarterectomy for occlusive carotid artery disease run a risk of brain ischemia during cross-clamping of the artery. The present study of 15 patients was undertaken to evaluate changes in cerebral blood flow (CBF), as measured with an intravenous (IV) tracer (133Xenon) technique, and to relate CBF changes to changes in the electroencephalogram (EEG). CBF was measured before and after induction of anesthesia, during cross-clamping of the carotid artery, after release of the clamps, and at 24 hours after the operation. All the patients were anesthetized with methohexitone, fentanyl, and nitrous oxide and oxygen. EEG was continuously recordedmore » during the operation. Carotid artery shunts were not used. In 8 patients, cross-clamping of the carotid artery did not influence the EEG. In this group of patients, induction of anesthesia caused a 38% decrease in CBF, which presumably reflects the normal reaction to the anesthetic agent given. There were no further changes in CBF during cross-clamping. In 7 patients, the EEG showed signs of deterioration during the intraoperative vascular occlusion. In these patients, anesthesia did not cause any CBF change, whereas cross-clamping the artery induced a 33% decrease in CBF. In individual patients, the severity of EEG changes correlated with the decrease in CBF. The absence of a change in CBF by anesthesia and a decrease due to cross-clamping of the carotid artery may be explained by the presence of a more advanced cerebrovascular disease and an insufficiency to maintain CBF during cross-clamping.« less

EEG-based Affect and Workload Recognition in a Virtual Driving Environment for ASD Intervention

PubMed Central

Wade, Joshua W.; Key, Alexandra P.; Warren, Zachary E.; Sarkar, Nilanjan

2017-01-01

objective To build group-level classification models capable of recognizing affective states and mental workload of individuals with autism spectrum disorder (ASD) during driving skill training. Methods Twenty adolescents with ASD participated in a six-session virtual reality driving simulator based experiment, during which their electroencephalogram (EEG) data were recorded alongside driving events and a therapist’s rating of their affective states and mental workload. Five feature generation approaches including statistical features, fractal dimension features, higher order crossings (HOC)-based features, power features from frequency bands, and power features from bins (Δf = 2 Hz) were applied to extract relevant features. Individual differences were removed with a two-step feature calibration method. Finally, binary classification results based on the k-nearest neighbors algorithm and univariate feature selection method were evaluated by leave-one-subject-out nested cross-validation to compare feature types and identify discriminative features. Results The best classification results were achieved using power features from bins for engagement (0.95) and boredom (0.78), and HOC-based features for enjoyment (0.90), frustration (0.88), and workload (0.86). Conclusion Offline EEG-based group-level classification models are feasible for recognizing binary low and high intensity of affect and workload of individuals with ASD in the context of driving. However, while promising the applicability of the models in an online adaptive driving task requires further development. Significance The developed models provide a basis for an EEG-based passive brain computer interface system that has the potential to benefit individuals with ASD with an affect- and workload-based individualized driving skill training intervention. PMID:28422647

Differential oscillatory electroencephalogram between attention-deficit/hyperactivity disorder subtypes and typically developing adolescents.

PubMed

Mazaheri, Ali; Fassbender, Catherine; Coffey-Corina, Sharon; Hartanto, Tadeus A; Schweitzer, Julie B; Mangun, George R

2014-09-01

A neurobiological-based classification of attention-deficit/hyperactivity disorder (ADHD) subtypes has thus far remained elusive. The aim of this study was to use oscillatory changes in the electroencephalogram (EEG) related to informative cue processing, motor preparation, and top-down control to investigate neurophysiological differences between typically developing (TD) adolescents, and those diagnosed with predominantly inattentive (IA) or combined (CB) (associated with symptoms of inattention as well as impulsivity/hyperactivity) subtypes of ADHD. The EEG was recorded from 57 rigorously screened adolescents (12 to 17 years of age; 23 TD, 17 IA, and 17 CB), while they performed a cued flanker task. We examined the oscillatory changes in theta (3-5 Hz), alpha (8-12 Hz), and beta (22-25 Hz) EEG bands after cues that informed participants with which hand they would subsequently be required to respond. Relative to TD adolescents, the IA group showed significantly less postcue alpha suppression, suggesting diminished processing of the cue in the visual cortex, whereas the CB group showed significantly less beta suppression at the electrode contralateral to the cued response hand, suggesting poor motor planning. Finally, both ADHD subtypes showed weak functional connectivity between frontal theta and posterior alpha, suggesting common top-down control impairment. We found both distinct and common task-related neurophysiological impairments in ADHD subtypes. Our results suggest that task-induced changes in EEG oscillations provide an objective measure, which in conjunction with other sources of information might help distinguish between ADHD subtypes and therefore aid in diagnoses and evaluation of treatment. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Assessment of seizure liability of Org 306039, a 5-HT2c agonist, using hippocampal brain slice and rodent EEG telemetry.

PubMed

Markgraf, Carrie G; DeBoer, Erik; Zhai, Jin; Cornelius, Lara; Zhou, Ying Ying; MacSweeney, Cliona

2014-01-01

Evaluation of the seizure potential for a CNS-targeted pharmaceutical compound before it is administered to humans is an important part of development. The current in vitro and in vivo studies were undertaken to characterize the seizure potential of the potent and selective 5-HT2c agonist Org 306039. Rat hippocampal slices (n=5) were prepared and Org 306039 was applied over a concentration range of 0-1000μM. Male Sprague-Dawley rats, implanted with telemetry EEG recording electrodes received either vehicle (n=4) or 100mg/kg Org 306039 (n=4) by oral gavage daily for 10days. EEG was recorded continuously for 22±1h post-dose each day. Post-dose behavior observations were conducted daily for 2h. Body temperature was measured at 1 and 2h post-dose. On Day 7, blood samples were drawn for pharmacokinetic analysis of Org 306039. In hippocampal slice, Org 306039 elicited a concentration-dependent increase in population spike area and number recorded from CA1 area, indicating seizure-genic potential. In telemetered rats, Org 306039 was associated with a decrease in body weight, a decrease in body temperature and the appearance of seizure-related behaviors and pre-seizure waveforms on EEG. One rat exhibited an overt seizure. Plasma concentrations of Org 306039 were similar among the 4 rats in the Org-treated group. Small group size made it difficult to determine a PK-PD relationship. These results indicate that the in vitro and in vivo models complement each other in the characterization of the seizure potential of CNS-targeted compounds such as the 5-HT2c agonist Org 306039. Copyright © 2014 Elsevier Inc. All rights reserved.

EEG biofeedback for autism spectrum disorder: a commentary on Kouijzer et al. (2013).

PubMed

Coben, Robert; Ricca, Rachel

2015-03-01

Research conducted by Kouijzer et al. (Appl Psychophysiol Biofeedback 38(1):17-28, 2013) compared the effects of skin conductance biofeedback and EEG-biofeedback on patients with autistic spectrum disorders to determine their relative efficacy. While they found a difference between treatment and control groups, there was no significant difference on many variables between the two treatment groups. From this, the increase in symptom alleviation from autistic spectrum disorder was attributed to non-specific factors surrounding the study. We now offer alternative explanations for their findings and propose different options for future studies. We hypothesize that the location and type of neurofeedback used adversely impacted the findings. We speculate that had they used a form of EEG-biofeedback that can combat deficiencies in connectivity and also trained the areas of the brain most affected by autism, there may have then been a significant difference between the effectiveness of EEG-biofeedback versus skin conductance biofeedback.

Resting EEG deficits in accused murderers with schizophrenia.

PubMed

Schug, Robert A; Yang, Yaling; Raine, Adrian; Han, Chenbo; Liu, Jianghong; Li, Liejia

2011-10-31

Empirical evidence continues to suggest a biologically distinct violent subtype of schizophrenia. The present study examined whether murderers with schizophrenia would demonstrate resting EEG deficits distinguishing them from both non-violent schizophrenia patients and murderers without schizophrenia. Resting EEG data were collected from five diagnostic groups (normal controls, non-murderers with schizophrenia, murderers with schizophrenia, murderers without schizophrenia, and murderers with psychiatric conditions other than schizophrenia) at a brain hospital in Nanjing, China. Murderers with schizophrenia were characterized by increased left-hemispheric fast-wave EEG activity relative to non-violent schizophrenia patients, while non-violent schizophrenia patients instead demonstrated increased diffuse slow-wave activity compared to all other groups. Results are discussed within the framework of a proposed left-hemispheric over-processing hypothesis specific to violent individuals with schizophrenia, involving left hemispheric hyperarousal deficits, which may lead to a homicidally violent schizophrenia outcome. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Chronic alcohol abuse and the acute sedative and neurophysiologic effects of midazolam.

PubMed

Bauer, L O; Gross, J B; Meyer, R E; Greenblatt, D J

1997-10-01

The aim of the present investigation was to examine benzodiazepine sensitivity in abstinent alcoholics. For this purpose, two escalating doses of the benzodiazepine midazolam were i.v. administered to nine alcohol-dependent patients after 2-3 weeks of abstinence and 12 healthy, non-alcoholic volunteers. A variety of dependent measures were examined, including the power spectrum of the resting electroencephalogram (EEG) and evoked EEG responses, saccadic eye movements, self-reported sedation, and vigilance task performance. Analyses revealed a significant association between plasma midazolam levels and changes in EEG beta power, pattern shift visual evoked potential amplitude, heart rate, and saccade amplitude and velocity. The patient and control groups differed significantly in the onset latencies of their saccadic eye movements, and marginally in EEG beta power, both before and after midazolam. However, no differences were detected between the groups in the dose of midazolam required to produce sedation or in midazolam's neurophysiological effects.

Predictive role of brain connectivity for resective surgery in Lennox-Gastaut syndrome.

PubMed

Hur, Yun Jung; Kim, Heung Dong

2016-08-01

Callosotomy can reveal hidden primary epileptogenic areas in Lennox-Gastaut syndrome (LGS). We studied the significance of causal connectivity for identifying hidden epileptogenic areas in preoperative electroencephalography (EEG) and for making a decision regarding resective surgery. We enrolled 18 LGS patients who underwent corpus callosotomy. Eight patients with unilateral epileptogenicity on post-callosotomy EEG underwent resective surgery (group A). Ten patients with independent bilateral epileptogenicity did not undergo resective surgery (group B). We analyzed generalized epileptiform discharges on pre-callosotomy EEG via direct directed transfer function (dDTF) and partial directed coherence (PDC). All regions exhibiting unilaterality in group A and bilaterality identified by dDTF or PDC in group B were concordant with the lateralization of the irritative zone on post-callosotomy EEG and with the localization of the resective areas, except for one patient in group A. The regions identified by dDTF exhibited high concordance rates with the resective areas in patients with good outcomes. Causal connectivity methods showed good concordance with hidden epileptogenic areas, and its concordance was associated with the prognosis of surgical outcome. This study provides evidence that causal connectivity methods can be helpful in deciding which type of surgery will be suitable for an LGS patient. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Hypoglycemia-associated changes in the electroencephalogram in patients with type 1 diabetes and normal hypoglycemia awareness or unawareness.

PubMed

Sejling, Anne-Sophie; Kjær, Troels W; Pedersen-Bjergaard, Ulrik; Diemar, Sarah S; Frandsen, Christian S S; Hilsted, Linda; Faber, Jens; Holst, Jens J; Tarnow, Lise; Nielsen, Martin N; Remvig, Line S; Thorsteinsson, Birger; Juhl, Claus B

2015-05-01

Hypoglycemia is associated with increased activity in the low-frequency bands in the electroencephalogram (EEG). We investigated whether hypoglycemia awareness and unawareness are associated with different hypoglycemia-associated EEG changes in patients with type 1 diabetes. Twenty-four patients participated in the study: 10 with normal hypoglycemia awareness and 14 with hypoglycemia unawareness. The patients were studied at normoglycemia (5-6 mmol/L) and hypoglycemia (2.0-2.5 mmol/L), and during recovery (5-6 mmol/L) by hyperinsulinemic glucose clamp. During each 1-h period, EEG, cognitive function, and hypoglycemia symptom scores were recorded, and the counterregulatory hormonal response was measured. Quantitative EEG analysis showed that the absolute amplitude of the θ band and α-θ band up to doubled during hypoglycemia with no difference between the two groups. In the recovery period, the θ amplitude remained increased. Cognitive function declined equally during hypoglycemia in both groups and during recovery reaction time was still prolonged in a subset of tests. The aware group reported higher hypoglycemia symptom scores and had higher epinephrine and cortisol responses compared with the unaware group. In patients with type 1 diabetes, EEG changes and cognitive performance during hypoglycemia are not affected by awareness status during a single insulin-induced episode with hypoglycemia. © 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

Wake and Sleep EEG in Patients With Huntington Disease: An eLORETA Study and Review of the Literature.

PubMed

Piano, Carla; Mazzucchi, Edoardo; Bentivoglio, Anna Rita; Losurdo, Anna; Calandra Buonaura, Giovanna; Imperatori, Claudio; Cortelli, Pietro; Della Marca, Giacomo

2017-01-01

The aim of the study was to evaluate the EEG modifications in patients with Huntington disease (HD) compared with controls, by means of the exact LOw REsolution Tomography (eLORETA) software. We evaluated EEG changes during wake, non-rapid eye movement (NREM) and rapid eye movement (REM) sleep. Moreover, we reviewed the literature concerning EEG modifications in HD. Twenty-three consecutive adult patients affected by HD were enrolled, 14 women and 9 men, mean age was 57.0 ± 12.4 years. Control subjects were healthy volunteers (mean age 58.2 ± 14.6 years). EEG and polygraphic recordings were performed during wake (before sleep) and during sleep. Sources of EEG activities were determined using the eLORETA software. In wake EEG, significant differences between patients and controls were detected in the delta frequency band (threshold T = ±4.606; P < .01) in the Brodmann areas (BAs) 3, 4, and 6 bilaterally. In NREM sleep, HD patients showed increased alpha power (T = ±4.516; P < .01) in BAs 4 and 6 bilaterally; decreased theta power (T = ±4.516; P < .01) in the BAs 23, 29, and 30; and decreased beta power (T = ±4.516; P < .01) in the left BA 30. During REM, HD patients presented decreased theta and alpha power (threshold T = ±4.640; P < .01) in the BAs 23, 29, 30, and 31 bilaterally. In conclusion, EEG data suggest a motor cortex dysfunction during wake and sleep in HD patients, which correlates with the clinical and polysomnographic evidence of increased motor activity during wake and NREM, and nearly absent motor abnormalities in REM. © EEG and Clinical Neuroscience Society (ECNS) 2016.

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.

DeepIED: An epileptic discharge detector for EEG-fMRI based on deep learning.

PubMed

Hao, Yongfu; Khoo, Hui Ming; von Ellenrieder, Nicolas; Zazubovits, Natalja; Gotman, Jean

2018-01-01

Presurgical evaluation that can precisely delineate the epileptogenic zone (EZ) is one important step for successful surgical resection treatment of refractory epilepsy patients. The noninvasive EEG-fMRI recording technique combined with general linear model (GLM) analysis is considered an important tool for estimating the EZ. However, the manual marking of interictal epileptic discharges (IEDs) needed in this analysis is challenging and time-consuming because the quality of the EEG recorded inside the scanner is greatly deteriorated compared to the usual EEG obtained outside the scanner. This is one of main impediments to the widespread use of EEG-fMRI in epilepsy. We propose a deep learning based semi-automatic IED detector that can find the candidate IEDs in the EEG recorded inside the scanner which resemble sample IEDs marked in the EEG recorded outside the scanner. The manual marking burden is greatly reduced as the expert need only edit candidate IEDs. The model is trained on data from 30 patients. Validation of IEDs detection accuracy on another 37 consecutive patients shows our method can improve the median sensitivity from 50.0% for the previously proposed template-based method to 84.2%, with false positive rate as 5 events/min. Reproducibility validation on 15 patients is applied to evaluate if our method can produce similar hemodynamic response maps compared with the manual marking ground truth results. We explore the concordance between the maximum hemodynamic response and the intracerebral EEG defined EZ and find that both methods produce similar percentage of concordance (76.9%, 10 out of 13 patients, electrode was absent in the maximum hemodynamic response in two patients). This tool will make EEG-fMRI analysis more practical for clinical usage.

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

DTIC Science & Technology

2015-10-01

AWARD NUMBER: W81XWH-12-1-0607 TITLE: "Emotion Regulation Training for Treating Warfighters with Combat-Related PTSD Using Real-Time fMRI and...Related PTSD Using Real-Time fMRI and EEG-Assisted Neurofeedback" 5a. CONTRACT NUMBER W81XWH-12-1-0607 5b. GRANT NUMBER PT110256 5c. PROGRAM ELEMENT...neurofeedback training protocol to evaluate FEA EEG-nf training feasibility in combat-related PTSD. 15. SUBJECT TERMS PTSD; amygdala; fMRI ; EEG

Electronic evaluation for video commercials by impression index.

PubMed

Kong, Wanzeng; Zhao, Xinxin; Hu, Sanqing; Vecchiato, Giovanni; Babiloni, Fabio

2013-12-01

How to evaluate the effect of commercials is significantly important in neuromarketing. In this paper, we proposed an electronic way to evaluate the influence of video commercials on consumers by impression index. The impression index combines both the memorization and attention index during consumers observing video commercials by tracking the EEG activity. It extracts features from scalp EEG to evaluate the effectiveness of video commercials in terms of time-frequency-space domain. And, the general global field power was used as an impression index for evaluation of video commercial scenes as time series. Results of experiment demonstrate that the proposed approach is able to track variations of the cerebral activity related to cognitive task such as observing video commercials, and help to judge whether the scene in video commercials is impressive or not by EEG signals.

Utility of Continuous EEG Monitoring in Noncritically lll Hospitalized Patients.

PubMed

Billakota, Santoshi; Sinha, Saurabh R

2016-10-01

Continuous EEG (cEEG) monitoring is used in the intensive care unit (ICU) setting to detect seizures, especially nonconvulsive seizures and status epilepticus. The utility and impact of such monitoring in non-ICU patients are largely unknown. Hospitalized patients who were not in an ICU and underwent cEEG monitoring in the first half of 2011 and 2014 were identified. Reason for admission, admitting service (neurologic and nonneurologic), indication for cEEG, comorbid conditions, duration of recording, EEG findings, whether an event/seizure was recorded, and impact of EEG findings on management were reviewed. We evaluated the impact of the year of recording, admitting service, indication for cEEG, and neurologic comorbidity on the yield of recordings based on whether an event was captured and/or a change in antiepileptic drug management occurred. Two hundred forty-nine non-ICU patients had cEEG monitoring during these periods. The indication for cEEG was altered mental status (60.6%), observed seizures (26.5%), or observed spells (12.9%); 63.5% were on neuro-related services. The average duration of recording was 1.8 days. EEG findings included interictal epileptiform discharges (14.9%), periodic lateralized discharges (4%), and generalized periodic discharges (1.6%). Clinical events were recorded in 28.1% and seizures in 16.5%. The cEEG led to a change in antiepileptic drug management in 38.6% of patients. There was no impact of type of admitting service; there was no significant impact of indication for cEEG. In non-ICU patients, cEEG monitoring had a relatively high yield of event/seizures (similar to ICU) and impact on management. Temporal trends, admitting service, and indication for cEEG did not alter this.

Automatic identification and removal of ocular artifacts in EEG--improved adaptive predictor filtering for portable applications.

PubMed

Zhao, Qinglin; Hu, Bin; Shi, Yujun; Li, Yang; Moore, Philip; Sun, Minghou; Peng, Hong

2014-06-01

Electroencephalogram (EEG) signals have a long history of use as a noninvasive approach to measure brain function. An essential component in EEG-based applications is the removal of Ocular Artifacts (OA) from the EEG signals. In this paper we propose a hybrid de-noising method combining Discrete Wavelet Transformation (DWT) and an Adaptive Predictor Filter (APF). A particularly novel feature of the proposed method is the use of the APF based on an adaptive autoregressive model for prediction of the waveform of signals in the ocular artifact zones. In our test, based on simulated data, the accuracy of noise removal in the proposed model was significantly increased when compared to existing methods including: Wavelet Packet Transform (WPT) and Independent Component Analysis (ICA), Discrete Wavelet Transform (DWT) and Adaptive Noise Cancellation (ANC). The results demonstrate that the proposed method achieved a lower mean square error and higher correlation between the original and corrected EEG. The proposed method has also been evaluated using data from calibration trials for the Online Predictive Tools for Intervention in Mental Illness (OPTIMI) project. The results of this evaluation indicate an improvement in performance in terms of the recovery of true EEG signals with EEG tracking and computational speed in the analysis. The proposed method is well suited to applications in portable environments where the constraints with respect to acceptable wearable sensor attachments usually dictate single channel devices.

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

PubMed

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

2010-12-01

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

EEG epileptiform abnormalities at admission to a rehabilitation department predict the risk of seizures in disorders of consciousness following a coma.

PubMed

Bagnato, Sergio; Boccagni, Cristina; Sant'Angelo, Antonino; Prestandrea, Caterina; Virgilio, Vittorio; Galardi, Giuseppe

2016-03-01

Seizures affect about a quarter of patients with disorders of consciousness (DOC) after a coma. We investigated whether the presence of epileptiform abnormalities (EAs) in the electroencephalogram (EEG) of patients with DOC may predict the occurrence of seizures. Moreover, we evaluated whether EAs have a prognostic role in these patients. This was a retrospective single-center cohort study of patients hospitalized between January 2005 and December 2014 in a rehabilitation department (mean time from acute brain injury: 46.1 days). We analyzed 30-minute EEGs at admittance for 112 patients with unresponsive wakefulness syndrome (UWS) or in a minimally conscious state (MCS), then compared occurrence of seizures over the following three months across patients with absent, unilateral, and bilateral EAs (generalized or bilateral independent). Outcomes at three months were assessed in the same groups using the Coma Recovery Scale Revised. Epileptiform abnormalities were observed in 38 patients (33.9%). Of these, 25 were unilateral, and 13 were bilateral. Seizures occurred in 84.6% of patients with bilateral EAs, which was significantly higher than in patients without EAs (10.8%, p<0.001) or with unilateral EAs (24%, p=0.001). The presence of EAs was not related to etiology or different DOC and did not significantly affect outcomes at three months. Patients with EAs at admission to a rehabilitation department have an increased risk of seizures. Specifically, most patients with bilateral EAs had seizures within the following 3 months. Evaluation of EAs in EEGs of patients with DOC may give valuable information in the management of antiepileptic drug treatment. Copyright © 2015 Elsevier Inc. All rights reserved.

Subspace techniques to remove artifacts from EEG: a quantitative analysis.

PubMed

Teixeira, A R; Tome, A M; Lang, E W; Martins da Silva, A

2008-01-01

In this work we discuss and apply projective subspace techniques to both multichannel as well as single channel recordings. The single-channel approach is based on singular spectrum analysis(SSA) and the multichannel approach uses the extended infomax algorithm which is implemented in the opensource toolbox EEGLAB. Both approaches will be evaluated using artificial mixtures of a set of selected EEG signals. The latter were selected visually to contain as the dominant activity one of the characteristic bands of an electroencephalogram (EEG). The evaluation is performed both in the time and frequency domain by using correlation coefficients and coherence function, respectively.

Benign childhood epilepsy with centro-temporal spikes: quantitative EEG and the Wechsler intelligence scale for children (WISC-III).

PubMed

Tedrus, Gloria M A S; Fonseca, Lineu C; Tonelotto, Josiane M F; Costa, Rebeca M; Chiodi, Marcelo G

2006-07-01

Benign childhood epilepsy with centro-temporal spikes (BECTS) is a form of focal idiopathic epilepsy, with seizure remission by the age of 18. Recent studies have suggested that some children with BECTS can suffer from deficits of memory, attention and learning ability and in auditory-verbal and performance sub-tests. On the other hand, alterations in the baseline brain electrical activity determined by using the quantitative electroencephalogram (qEEG) have been described. The objective of this study was to evaluate the absolute and relative powers in the delta, theta, alpha and beta bands of the qEEG in children with BECTS, and their relation to IQ measurements (WISC-III). Twenty-six 8 to 11-year-old children with BECTS were studied, paired with a control group of healthy children according to age and gender. It was shown that the absolute delta and theta powers were statistically greater in the children with BECTS than in the control group, at almost all the electrodes. In the children with BECTS, a negative correlation (Pearson's correlation test) was observed at various electrodes between the absolute delta and theta powers and the performance IQ. These data indicate a possible relationship between maturational disturbance in the brain electrical activity development and the tendency for inferior cognitive performance in children with BECTS.

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.

Neuropsychological and neurophysiological evaluation in cirrhotic patients with minimal hepatic encephalopathy undergoing liver transplantation.

PubMed

Senzolo, M; Amodio, P; D'Aloiso, M C; Fagiuoli, S; Del Piccolo, F; Canova, D; Masier, A; Bassanello, M; Zanus, G; Burra, P

2005-03-01

Cirrhotic patients without overt hepatic encephalopathy may have cerebral function alterations called minimal hepatic encephalopathy (MHE). Our goal was to evaluate the role of partial pressure of ammonia (pNH3), neuropsychological, and neurophysiological assessment in detecting cognitive changes in cirrhotic patients awaiting liver transplantation. Fourteen cirrhotic patients listed for liver transplant were studied. All patients underwent the neuropsychological battery called PSE. Neurophysiological assessment including spectral EEG (sEEG), evoked potential P300 and pNH3 and venous and arterial ammonia levels was performed in all patients. Four patients were transplanted. Liver disease etiology was alcoholic in four patients, viral in six mixed in two, and cryptogenic in two. PSE scores revealed MHE in 8 patients; sEEG was altered in 6, and P300 in 1. No correlations were detected between P300, sEEG, and PSE. pNH3 and arterial ammonia levels were significantly higher in the subgroup of patients with altered sEEG and were correlated with theta band increase in sEEG but not with pathological PSE scores or P300 wave abnormalities. The combination of sEEG and PSE, and possibly also pNH3 and arterial ammonia, is useful in detecting cerebral function alterations in cirrhotic patients with no apparent encephalopathy, whereas P300 is not. The diagnosis of MHE obtained using the multimodal approach adopted in this study may enable the adequate treatment of these patients prior to surgery, which includes advising them not to drive and adjusting their priority on the waiting list for OLTx in the light of a condition that cannot be evaluated by Child Pugh score and MELD score.

EEG-Based Brain-Computer Interface for Decoding Motor Imagery Tasks within the Same Hand Using Choi-Williams Time-Frequency Distribution

PubMed Central

Alwanni, Hisham; Baslan, Yara; Alnuman, Nasim; Daoud, Mohammad I.

2017-01-01

This paper presents an EEG-based brain-computer interface system for classifying eleven motor imagery (MI) tasks within the same hand. The proposed system utilizes the Choi-Williams time-frequency distribution (CWD) to construct a time-frequency representation (TFR) of the EEG signals. The constructed TFR is used to extract five categories of time-frequency features (TFFs). The TFFs are processed using a hierarchical classification model to identify the MI task encapsulated within the EEG signals. To evaluate the performance of the proposed approach, EEG data were recorded for eighteen intact subjects and four amputated subjects while imagining to perform each of the eleven hand MI tasks. Two performance evaluation analyses, namely channel- and TFF-based analyses, are conducted to identify the best subset of EEG channels and the TFFs category, respectively, that enable the highest classification accuracy between the MI tasks. In each evaluation analysis, the hierarchical classification model is trained using two training procedures, namely subject-dependent and subject-independent procedures. These two training procedures quantify the capability of the proposed approach to capture both intra- and inter-personal variations in the EEG signals for different MI tasks within the same hand. The results demonstrate the efficacy of the approach for classifying the MI tasks within the same hand. In particular, the classification accuracies obtained for the intact and amputated subjects are as high as 88.8% and 90.2%, respectively, for the subject-dependent training procedure, and 80.8% and 87.8%, respectively, for the subject-independent training procedure. These results suggest the feasibility of applying the proposed approach to control dexterous prosthetic hands, which can be of great benefit for individuals suffering from hand amputations. PMID:28832513

Real-time Neuroimaging and Cognitive Monitoring Using Wearable Dry EEG

PubMed Central

Mullen, Tim R.; Kothe, Christian A.E.; Chi, Mike; Ojeda, Alejandro; Kerth, Trevor; Makeig, Scott; Jung, Tzyy-Ping; Cauwenberghs, Gert

2015-01-01

Goal We present and evaluate a wearable high-density dry electrode EEG system and an open-source software framework for online neuroimaging and state classification. Methods The system integrates a 64-channel dry EEG form-factor with wireless data streaming for online analysis. A real-time software framework is applied, including adaptive artifact rejection, cortical source localization, multivariate effective connectivity inference, data visualization, and cognitive state classification from connectivity features using a constrained logistic regression approach (ProxConn). We evaluate the system identification methods on simulated 64-channel EEG data. Then we evaluate system performance, using ProxConn and a benchmark ERP method, in classifying response errors in 9 subjects using the dry EEG system. Results Simulations yielded high accuracy (AUC=0.97±0.021) for real-time cortical connectivity estimation. Response error classification using cortical effective connectivity (sdDTF) was significantly above chance with similar performance (AUC) for cLORETA (0.74±0.09) and LCMV (0.72±0.08) source localization. Cortical ERP-based classification was equivalent to ProxConn for cLORETA (0.74±0.16) but significantly better for LCMV (0.82±0.12). Conclusion We demonstrated the feasibility for real-time cortical connectivity analysis and cognitive state classification from high-density wearable dry EEG. Significance This paper is the first validated application of these methods to 64-channel dry EEG. The work addresses a need for robust real-time measurement and interpretation of complex brain activity in the dynamic environment of the wearable setting. Such advances can have broad impact in research, medicine, and brain-computer interfaces. The pipelines are made freely available in the open-source SIFT and BCILAB toolboxes. PMID:26415149

Age-Related Differences in Sleep Architecture and Electroencephalogram in Adolescents in the National Consortium on Alcohol and Neurodevelopment in Adolescence Sample.

PubMed

Baker, Fiona C; Willoughby, Adrian R; de Zambotti, Massimiliano; Franzen, Peter L; Prouty, Devin; Javitz, Harold; Hasler, Brant; Clark, Duncan B; Colrain, Ian M

2016-07-01

To investigate age-related differences in polysomnographic and sleep electroencephalographic (EEG) measures, considering sex, pubertal stage, ethnicity, and scalp topography in a large group of adolescents in the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA). Following an adaptation/clinical screening night, 141 healthy adolescents (12-21 y, 64 girls) had polysomnographic recordings, from which sleep staging and EEG measures were derived. The setting was the SRI International Human Sleep Laboratory and University of Pittsburgh Pediatric Sleep Laboratory. Older age was associated with a lower percentage of N3 sleep, accompanied by higher percentages of N2, N1, and rapid eye movement (REM) sleep. Older boys compared with younger boys had more frequent awakenings and wakefulness after sleep onset, effects that were absent in girls. Delta (0.3-4 Hz) EEG power in nonrapid eye movement NREM sleep was lower in older than younger adolescents at all electrode sites, with steeper slopes of decline over the occipital scalp. EEG power in higher frequency bands was also lower in older adolescents than younger adolescents, with equal effects across electrodes. Percent delta power in the first NREM period was similar across age. African Americans had lower EEG power across frequency bands (delta to sigma) compared with Caucasians. Finally, replacing age with pubertal status in the models showed similar relationships. Substantial differences in sleep architecture and EEG were evident across adolescence in this large group, with sex modifying some relationships. Establishment and follow-up of this cohort allows the investigation of sleep EEG-brain structural relationships and the effect of behaviors, such as alcohol and substance use, on sleep EEG maturation. © 2016 Associated Professional Sleep Societies, LLC.

Task-related functional connectivity in autism spectrum conditions: an EEG study using wavelet transform coherence

PubMed Central

2013-01-01

Background Autism Spectrum Conditions (ASC) are a set of pervasive neurodevelopmental conditions characterized by a wide range of lifelong signs and symptoms. Recent explanatory models of autism propose abnormal neural connectivity and are supported by studies showing decreased interhemispheric coherence in individuals with ASC. The first aim of this study was to test the hypothesis of reduced interhemispheric coherence in ASC, and secondly to investigate specific effects of task performance on interhemispheric coherence in ASC. Methods We analyzed electroencephalography (EEG) data from 15 participants with ASC and 15 typical controls, using Wavelet Transform Coherence (WTC) to calculate interhemispheric coherence during face and chair matching tasks, for EEG frequencies from 5 to 40 Hz and during the first 400 ms post-stimulus onset. Results Results demonstrate a reduction of interhemispheric coherence in the ASC group, relative to the control group, in both tasks and for all electrode pairs studied. For both tasks, group differences were generally observed after around 150 ms and at frequencies lower than 13 Hz. Regarding within-group task comparisons, while the control group presented differences in interhemispheric coherence between faces and chairs tasks at various electrode pairs (FT7-FT8, TP7-TP8, P7-P8), such differences were only seen for one electrode pair in the ASC group (T7-T8). No significant differences in EEG power spectra were observed between groups. Conclusions Interhemispheric coherence is reduced in people with ASC, in a time and frequency specific manner, during visual perception and categorization of both social and inanimate stimuli and this reduction in coherence is widely dispersed across the brain. Results of within-group task comparisons may reflect an impairment in task differentiation in people with ASC relative to typically developing individuals. Overall, the results of this research support the value of WTC in examining the time-frequency microstructure of task-related interhemispheric EEG coherence in people with ASC. PMID:23311570

Removing ballistocardiogram (BCG) artifact from full-scalp EEG acquired inside the MR scanner with Orthogonal Matching Pursuit (OMP)

PubMed Central

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

2014-01-01

Ballistocardiogram (BCG) artifact remains a major challenge that renders electroencephalographic (EEG) signals hard to interpret in simultaneous EEG and functional MRI (fMRI) data acquisition. Here, we propose an integrated learning and inference approach that takes advantage of a commercial high-density EEG cap, to estimate the BCG contribution in noisy EEG recordings from inside the MR scanner. To estimate reliably the full-scalp BCG artifacts, a near-optimal subset (20 out of 256) of channels first was identified using a modified recording setup. In subsequent recordings inside the MR scanner, BCG-only signal from this subset of channels was used to generate continuous estimates of the full-scalp BCG artifacts via inference, from which the intended EEG signal was recovered. The reconstruction of the EEG was performed with both a direct subtraction and an optimization scheme. We evaluated the performance on both synthetic and real contaminated recordings, and compared it to the benchmark Optimal Basis Set (OBS) method. In the challenging non-event-related-potential (non-ERP) EEG studies, our reconstruction can yield more than fourteen-fold improvement in reducing the normalized RMS error of EEG signals, compared to OBS. PMID:25120421

Stability of Early EEG Background Patterns After Pediatric Cardiac Arrest.

PubMed

Abend, Nicholas S; Xiao, Rui; Kessler, Sudha Kilaru; Topjian, Alexis A

2018-05-01

We aimed to determine whether EEG background characteristics remain stable across discrete time periods during the acute period after resuscitation from pediatric cardiac arrest. Children resuscitated from cardiac arrest underwent continuous conventional EEG monitoring. The EEG was scored in 12-hour epochs for up to 72 hours after return of circulation by an electroencephalographer using a Background Category with 4 levels (normal, slow-disorganized, discontinuous/burst-suppression, or attenuated-featureless) or 2 levels (normal/slow-disorganized or discontinuous/burst-suppression/attenuated-featureless). Survival analyses and mixed-effects ordinal logistic regression models evaluated whether the EEG remained stable across epochs. EEG monitoring was performed in 89 consecutive children. When EEG was assessed as the 4-level Background Category, 30% of subjects changed category over time. Based on initial Background Category, one quarter of the subjects changed EEG category by 24 hours if the initial EEG was attenuated-featureless, by 36 hours if the initial EEG was discontinuous or burst-suppression, by 48 hours if the initial EEG was slow-disorganized, and never if the initial EEG was normal. However, regression modeling for the 4-level Background Category indicated that the EEG did not change over time (odds ratio = 1.06, 95% confidence interval = 0.96-1.17, P = 0.26). Similarly, when EEG was assessed as the 2-level Background Category, 8% of subjects changed EEG category over time. However, regression modeling for the 2-level category indicated that the EEG did not change over time (odds ratio = 1.02, 95% confidence interval = 0.91-1.13, P = 0.75). The EEG Background Category changes over time whether analyzed as 4 levels (30% of subjects) or 2 levels (8% of subjects), although regression analyses indicated that no significant changes occurred over time for the full cohort. These data indicate that the Background Category is often stable during the acute 72 hours after pediatric cardiac arrest and thus may be a useful EEG assessment metric in future studies, but that some subjects do have EEG changes over time and therefore serial EEG assessments may be informative.

A novel hydrogel electrolyte extender for rapid application of EEG sensors and extended recordings.

PubMed

Kleffner-Canucci, Killian; Luu, Phan; Naleway, John; Tucker, Don M

2012-04-30

Dense-array EEG recordings are now commonplace in research and gaining acceptance in clinical settings. Application of many sensors with traditional electrolytes is time consuming. Saline electrolytes can be used to minimize application time but recording duration is limited due to evaporation. In the present study, we evaluate a NIPAm (N-isopropyl acrylamide:acrylic acid) base electrolyte extender for use with saline electrolytes. Sensor-scalp impedances and EEG data quality acquired with the electrolyte extender are compared with those obtained for saline and an EEG electrolyte commonly used in clinical exams (Elefix). The results show that when used in conjunction with saline, electrode-scalp impedances and data across the EEG spectrum are comparable with those obtained using Elefix EEG paste. When used in conjunction with saline, the electrolyte extender permits rapid application of dense-sensor arrays and stable, high-quality EEG data to be obtained for at least 4.5 h. This is an enabling technology that will make benefits of dense-array EEG recordings practical for clinical applications. Copyright © 2011 Elsevier B.V. All rights reserved.

EEG Characteristic Extraction Method of Listening Music and Objective Estimation Method Based on Latency Structure Model in Individual Characteristics

NASA Astrophysics Data System (ADS)

Ito, Shin-Ichi; Mitsukura, Yasue; Nakamura Miyamura, Hiroko; Saito, Takafumi; Fukumi, Minoru

EEG is characterized by the unique and individual characteristics. Little research has been done to take into account the individual characteristics when analyzing EEG signals. Often the EEG has frequency components which can describe most of the significant characteristics. Then there is the difference of importance between the analyzed frequency components of the EEG. We think that the importance difference shows the individual characteristics. In this paper, we propose a new EEG extraction method of characteristic vector by a latency structure model in individual characteristics (LSMIC). The LSMIC is the latency structure model, which has personal error as the individual characteristics, based on normal distribution. The real-coded genetic algorithms (RGA) are used for specifying the personal error that is unknown parameter. Moreover we propose an objective estimation method that plots the EEG characteristic vector on a visualization space. Finally, the performance of the proposed method is evaluated using a realistic simulation and applied to a real EEG data. The result of our experiment shows the effectiveness of the proposed method.

Application of reminiscence treatment on older people with dementia: a case study in Pingtung, Taiwan.

PubMed

Huang, Song-Lin; Li, Chih-Ming; Yang, Chiu-Yen; Chen, Jia-Jin J

2009-06-01

Reminiscence therapy has been utilized for many years in the treatment of dementia in older people. Purposes of the research included examining different methods of promoting interactivity, social participation, cognitive function improvement in those with dementia, and the effectiveness in reducing symptoms of depression following group treatment. This study used pretest and posttest electroencephalography (EEG) measurements to test reminiscence therapy efficacy on participants. This research organized a social group work with 12 elderly clients with dementia (mild to moderate stage) selected from among 90 residents of an older persons care facility in Pingtung. Eleven agreed to join the study, and 10 completed successfully all treatment sessions. Eight sessions of reminiscence cooking lessons were conducted. The effectiveness of interventions was evaluated by comparing presession and postsession EEG, mental health status, depression scale, and feeling of participation scale scores. Significant differences in values, particularly for EEG, were found between the two sets of scores. The average value of participants' fast waves rose from 43.88 to 55.12, whereas average slow-wave values fell from 56.12 to 44.13. After analysis using the Wilcoxon matched paired signed rank test, significant differences were noted. Findings and suggestions include the following: (a) The rise in Mini-Mental State Examination and reduction in depression scale scores, although noted, were not significant, and (b) the self-achievement, emotional stability, family atmosphere, and physical needs of participants were met. The authors recommend that reminiscence group work be promoted in the home for older persons and that childhood cooking sessions twice each week may be the ideal format for reminiscence group work.

Concurrent Electroconvulsive Therapy and Bupropion Treatment.

PubMed

Takala, Christopher R; Leung, Jonathan G; Murphy, Lauren L; Geske, Jennifer R; Palmer, Brian A

2017-09-01

Bupropion is associated with a dose-dependent increased risk of seizures. Use of concomitant bupropion and electroconvulsive therapy (ECT) remains controversial because of an increased risk of prolonged seizures. This is the first systematic evaluation of the effect of bupropion on ECT. A case group (n = 119), patients treated with concomitant ECT and bupropion, was compared with an age and gender frequency-matched control group (n = 261), treated with only ECT. Electroconvulsive therapy treatment data including seizure length, number of treatments, and concurrent medications were extracted. Longitudinal mixed models examined ECT versus ECT + bupropion group differences over the course of treatments measured by seizure duration (electroencephalogram [EEG] and motor). Multivariable models examined the total number of treatments and first and last seizure duration. All models considered group differences with ECT treatment measures adjusted for age, gender, benzodiazepine treatment, lead placement, and setting. Electroconvulsive therapy treatment with bupropion led to shorter motor seizure duration (0.047) and EEG seizure duration (P = 0.001). The number of ECT treatments (7.3 vs 7.0 treatments; P = 0.23), respectively, or the probability of a prolonged seizure (P = 0.15) was not significantly different. Benzodiazepine use was significantly more common in control subjects (P = 0.01). This is a retrospective analysis limited in part by unavailable variables (seizure threshold, nature of EEG and motor seizure monitoring, type of ECT device, dosing and formulation of bupropion, and duration of the current depressive illness). This study revealed a significantly shorter duration in seizure length with ECT + concomitant bupropion, but not in the number of required treatments in those treated compared with ECT without bupropion. There remains a critical need to reevaluate the efficacy of concomitant use of psychotropic medications + ECT.

Sensitivity of quantitative EEG for seizure identification in the intensive care unit.

PubMed

Haider, Hiba A; Esteller, Rosana; Hahn, Cecil D; Westover, M Brandon; Halford, Jonathan J; Lee, Jong W; Shafi, Mouhsin M; Gaspard, Nicolas; Herman, Susan T; Gerard, Elizabeth E; Hirsch, Lawrence J; Ehrenberg, Joshua A; LaRoche, Suzette M

2016-08-30

To evaluate the sensitivity of quantitative EEG (QEEG) for electrographic seizure identification in the intensive care unit (ICU). Six-hour EEG epochs chosen from 15 patients underwent transformation into QEEG displays. Each epoch was reviewed in 3 formats: raw EEG, QEEG + raw, and QEEG-only. Epochs were also analyzed by a proprietary seizure detection algorithm. Nine neurophysiologists reviewed raw EEGs to identify seizures to serve as the gold standard. Nine other neurophysiologists with experience in QEEG evaluated the epochs in QEEG formats, with and without concomitant raw EEG. Sensitivity and false-positive rates (FPRs) for seizure identification were calculated and median review time assessed. Mean sensitivity for seizure identification ranged from 51% to 67% for QEEG-only and 63%-68% for QEEG + raw. FPRs averaged 1/h for QEEG-only and 0.5/h for QEEG + raw. Mean sensitivity of seizure probability software was 26.2%-26.7%, with FPR of 0.07/h. Epochs with the highest sensitivities contained frequent, intermittent seizures. Lower sensitivities were seen with slow-frequency, low-amplitude seizures and epochs with rhythmic or periodic patterns. Median review times were shorter for QEEG (6 minutes) and QEEG + raw analysis (14.5 minutes) vs raw EEG (19 minutes; p = 0.00003). A panel of QEEG trends can be used by experts to shorten EEG review time for seizure identification with reasonable sensitivity and low FPRs. The prevalence of false detections confirms that raw EEG review must be used in conjunction with QEEG. Studies are needed to identify optimal QEEG trend configurations and the utility of QEEG as a screening tool for non-EEG personnel. This study provides Class II evidence that QEEG + raw interpreted by experts identifies seizures in patients in the ICU with a sensitivity of 63%-68% and FPR of 0.5 seizures per hour. © 2016 American Academy of Neurology.

A Long Short-Term Memory deep learning network for the prediction of epileptic seizures using EEG signals.

PubMed

Tsiouris, Κostas Μ; Pezoulas, Vasileios C; Zervakis, Michalis; Konitsiotis, Spiros; Koutsouris, Dimitrios D; Fotiadis, Dimitrios I

2018-05-17

The electroencephalogram (EEG) is the most prominent means to study epilepsy and capture changes in electrical brain activity that could declare an imminent seizure. In this work, Long Short-Term Memory (LSTM) networks are introduced in epileptic seizure prediction using EEG signals, expanding the use of deep learning algorithms with convolutional neural networks (CNN). A pre-analysis is initially performed to find the optimal architecture of the LSTM network by testing several modules and layers of memory units. Based on these results, a two-layer LSTM network is selected to evaluate seizure prediction performance using four different lengths of preictal windows, ranging from 15 min to 2 h. The LSTM model exploits a wide range of features extracted prior to classification, including time and frequency domain features, between EEG channels cross-correlation and graph theoretic features. The evaluation is performed using long-term EEG recordings from the open CHB-MIT Scalp EEG database, suggest that the proposed methodology is able to predict all 185 seizures, providing high rates of seizure prediction sensitivity and low false prediction rates (FPR) of 0.11-0.02 false alarms per hour, depending on the duration of the preictal window. The proposed LSTM-based methodology delivers a significant increase in seizure prediction performance compared to both traditional machine learning techniques and convolutional neural networks that have been previously evaluated in the literature. Copyright © 2018 Elsevier Ltd. All rights reserved.

Wireless multichannel electroencephalography in the newborn

PubMed Central

Ibrahim, Z.H.; Chari, G.; Abdel Baki, S.; Bronshtein, V.; Kim, M.R.; Weedon, J.; Cracco, J.; Aranda, J.V.

2016-01-01

OBJECTIVES: First, to determine the feasibility of an ultra-compact wireless device (microEEG) to obtain multichannel electroencephalographic (EEG) recording in the Neonatal Intensive Care Unit (NICU). Second, to identify problem areas in order to improve wireless EEG performance. STUDY DESIGN: 28 subjects (gestational age 24–30 weeks, postnatal age <30 days) were recruited at 2 sites as part of an ongoing study of neonatal apnea and wireless EEG. Infants underwent 8-9 hour EEG recordings every 2–4 weeks using an electrode cap (ANT-Neuro) connected to the wireless EEG device (Bio-Signal Group). A 23 electrode configuration was used incorporating the International 10–20 System. The device transmitted recordings wirelessly to a laptop computer for bedside assessment. The recordings were assessed by a pediatric neurophysiologist for interpretability. RESULTS: A total of 84 EEGs were recorded from 28 neonates. 61 EEG studies were obtained in infants prior to 35 weeks corrected gestational age (CGA). NICU staff placed all electrode caps and initiated all recordings. Of these recordings 6 (10%) were uninterpretable due to artifacts and one study could not be accessed. The remaining 54 (89%) EEG recordings were acceptable for clinical review and interpretation by a pediatric neurophysiologist. Of the recordings obtained at 35 weeks corrected gestational age or later only 11 out of 23 (48%) were interpretable. CONCLUSIONS: Wireless EEG devices can provide practical, continuous, multichannel EEG monitoring in preterm neonates. Their small size and ease of use could overcome obstacles associated with EEG recording and interpretation in the NICU. PMID:28009337

Treatment of the alcoholic organic brain syndrome with EMD 21657. A derivative of a pyritinolmetabolite: double-blind clinical, quantitative EEG and psychometric studies.

PubMed

Saletu, B; Grünberger, J; Saletu, M; Mader, R; Volavka, J

1978-01-01

The efficacy of EMD 21657--a derivative of a pyritinolmetabolite--with regard to the improvement of the organic brain syndrome (OBS) of chronic alcoholics was investigated in a double-blind study utilizing clinical, psychometric and quantitative EEG evaluation. Nineteen patients received 3 x 300 mg EMD and 21 patients 3 x 1 dragee placebo for 6 weeks. The groups did not differ in regard to age, sex, weight, height, alcohol anamnesis or IQ. The hospitalized patients were examined before as well as at the end of the second, fourth and sixth week of drug treatment. While the overall evaluation by the psychiatrist and patients at the end of the period of treatment did not show marked intergroup differences, the clinical global impression scale and the OBS rating scale demonstrated that both groups showed a significant reduction in their OBS and that improvement with EMD 21657 therapy was significantly superior to the one with placebo. Psychometric analysis also exhibited a significant superiority of EMD in regard to the general, associative, numeric and total verbal memory, concentration and attention variability. Psychovisual memory and the quantative aspects of attention showed opposite findings. Flickerlight fusion frequency, reaction time and after-image did not change significantly. The psychomotor activity improved significantly more with EMD than placebo; this was especially pronounced in the left hand. Affect and mood improved also more with EMD than placebo. Side effects were observed more frequently under active treatment and were characterized by temporary headaches. Power spectral density analysis of the EEG revealed in both groups a decrease of delta, fast alpha and beta activities and an increase in theta and slow alpha activity, but changes during EMD treatment more frequently reached the level of statistical significance than with placebo. The most consistant finding was the theta augmentation under EMD treatment. It was concluded that EMD 21657 is a CNS-effective drug with pronounced nootropic and slight thymotropic properties.

Predictive value of EEG in postanoxic encephalopathy: A quantitative model-based approach.

PubMed

Efthymiou, Evdokia; Renzel, Roland; Baumann, Christian R; Poryazova, Rositsa; Imbach, Lukas L

2017-10-01

The majority of comatose patients after cardiac arrest do not regain consciousness due to severe postanoxic encephalopathy. Early and accurate outcome prediction is therefore essential in determining further therapeutic interventions. The electroencephalogram is a standardized and commonly available tool used to estimate prognosis in postanoxic patients. The identification of pathological EEG patterns with poor prognosis relies however primarily on visual EEG scoring by experts. We introduced a model-based approach of EEG analysis (state space model) that allows for an objective and quantitative description of spectral EEG variability. We retrospectively analyzed standard EEG recordings in 83 comatose patients after cardiac arrest between 2005 and 2013 in the intensive care unit of the University Hospital Zürich. Neurological outcome was assessed one month after cardiac arrest using the Cerebral Performance Category. For a dynamic and quantitative EEG analysis, we implemented a model-based approach (state space analysis) to quantify EEG background variability independent from visual scoring of EEG epochs. Spectral variability was compared between groups and correlated with clinical outcome parameters and visual EEG patterns. Quantitative assessment of spectral EEG variability (state space velocity) revealed significant differences between patients with poor and good outcome after cardiac arrest: Lower mean velocity in temporal electrodes (T4 and T5) was significantly associated with poor prognostic outcome (p<0.005) and correlated with independently identified visual EEG patterns such as generalized periodic discharges (p<0.02). Receiver operating characteristic (ROC) analysis confirmed the predictive value of lower state space velocity for poor clinical outcome after cardiac arrest (AUC 80.8, 70% sensitivity, 15% false positive rate). Model-based quantitative EEG analysis (state space analysis) provides a novel, complementary marker for prognosis in postanoxic encephalopathy. Copyright © 2017 Elsevier B.V. All rights reserved.

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

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.

Spatially Nonlinear Interdependence of Alpha-Oscillatory Neural Networks under Chan Meditation

PubMed Central

Chang, Chih-Hao

2013-01-01

This paper reports the results of our investigation of the effects of Chan meditation on brain electrophysiological behaviors from the viewpoint of spatially nonlinear interdependence among regional neural networks. Particular emphasis is laid on the alpha-dominated EEG (electroencephalograph). Continuous-time wavelet transform was adopted to detect the epochs containing substantial alpha activities. Nonlinear interdependence quantified by similarity index S(X∣Y), the influence of source signal Y on sink signal X, was applied to the nonlinear dynamical model in phase space reconstructed from multichannel EEG. Experimental group involved ten experienced Chan-Meditation practitioners, while control group included ten healthy subjects within the same age range, yet, without any meditation experience. Nonlinear interdependence among various cortical regions was explored for five local neural-network regions, frontal, posterior, right-temporal, left-temporal, and central regions. In the experimental group, the inter-regional interaction was evaluated for the brain dynamics under three different stages, at rest (stage R, pre-meditation background recording), in Chan meditation (stage M), and the unique Chakra-focusing practice (stage C). Experimental group exhibits stronger interactions among various local neural networks at stages M and C compared with those at stage R. The intergroup comparison demonstrates that Chan-meditation brain possesses better cortical inter-regional interactions than the resting brain of control group. PMID:24489583

Gender differences in association between serotonin transporter gene polymorphism and resting-state EEG activity.

PubMed

Volf, N V; Belousova, L V; Knyazev, G G; Kulikov, A V

2015-01-22

Human brain oscillations represent important features of information processing and are highly heritable. Gender has been observed to affect association between the 5-HTTLPR (serotonin-transporter-linked polymorphic region) polymorphism and various endophenotypes. This study aimed to investigate the effects of 5-HTTLPR on the spontaneous electroencephalography (EEG) activity in healthy male and female subjects. DNA samples extracted from buccal swabs and resting EEG recorded at 60 standard leads were collected from 210 (101 men and 109 women) volunteers. Spectral EEG power estimates and cortical sources of EEG activity were investigated. It was shown that effects of 5-HTTLPR polymorphism on electrical activity of the brain vary as a function of gender. Women with the S/L genotype had greater global EEG power compared to men with the same genotype. In men, current source density was markedly different among genotype groups in only alpha 2 and alpha 3 frequency ranges: S/S allele carriers had higher current source density estimates in the left inferior parietal lobule in comparison with the L/L group. In women, genotype difference in global power asymmetry was found in the central-temporal region. Contrasting L/L and S/L genotype carriers also yielded significant effects in the right hemisphere inferior parietal lobule and the right postcentral gyrus with L/L genotype carriers showing lower current source density estimates than S/L genotype carriers in all but gamma bands. So, in women, the effects of 5-HTTLPR polymorphism were associated with modulation of the EEG activity in a wide range of EEG frequencies. The significance of the results lies in the demonstration of gene by sex interaction with resting EEG that has implications for understanding sex-related differences in affective states, emotion and cognition. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

Neuropsychological study in patients with ALL. Two different CNS prevention therapies--cranial irradiation plus IT methotrexate vs. IT methotrexate alone

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

Pavlovsky, S.; Fisman, N.; Arizaga, R.

Neurological, psychopedagogic, and psychologic long-term sequelae were evaluated in two groups of ALL patients in continuous CR for more than 2 years treated with two different CNS prophylaxis schemes. Group A, 19 patients received cranial irradiation 2400 rads plus IT MTX-DMT, and group B, 23 patients IT MTX-DMT only during induction and maintenance. All the patients were evaluated by performing neurological examination, EEG, EMG with nerve conduction velocity, CT scans, CSF studies, psychometric and psychologic studies, and neuropsychological evaluation. The most important findings were: 11 patients from group A (58%) showed abnormal CT and only one patient from group Bmore » showed CT abnormalities. The neuropsychologic evaluation (performed by L. Bender technique and Picq-Vayer scale) showed more severe impairment (grade 3-4) in eight patients from group A (42%) and none in group B (p less than 0.001). Higher incidence of abnormalities in group A suggests the existence of more severe sequelae in the patients treated with cranial irradiation plus IT MTX-DMT than with IT MTX-DMT alone.« less

A long-term longitudinal follow-up of depressed patients treated with ECT with special focus on development of dementia.

PubMed

Berggren, Åke; Gustafson, Lars; Höglund, Peter; Johanson, Aki

2016-08-01

In this study, the long term effects of ECT on patients with depression were investigated through repeated rCBF and EEG measures as well as clinical characteristics over several years. The aim of the investigation was to establish an association with the eventual development of dementia. A cohort of forty-nine patients (21 men and 28 women) with a mean age of 61 years underwent ECT. A subsequent evaluation from medical records and three rating-scales for diagnosis of Alzheimer´s disease (AD), fronto-temporal dementia (FTD), and for vascular dementia (VaD), revealed that 17 patients (8 men and 9 women), had developed dementia. These cases were compared to the 32 patients (13 men and 19 women), who had not developed dementia. Initially, the dementia group, compared to those without dementia, showed a lower hemispheric CBF (left side; p=.029, right side; p=.033), and a lower mean occipital EEG frequency (p=.048). After the first ECT-series, an increase in general disorientation (p=.015), personal disorientation (p=.009), and subsequently, spatial disorientation (p=.021), were seen in the dementia group. There were no differences in the clinical response or remissions after treatment in the groups. The small sample-size, which did not allow for the comparison of characteristics between different dementias. Depressed older patients who later developed dementia showed lower hemispheric mean level of CBF and EEG mean frequency before ECT and higher personal and spatial disorientation following ECT. Copyright © 2016 Elsevier B.V. All rights reserved.

Power spectral analysis of the sleep electroencephalogram in heartburn patients with or without gastroesophageal reflux disease: a feasibility study.

PubMed

Budhiraja, Rohit; Quan, Stuart F; Punjabi, Naresh M; Drake, Christopher L; Dickman, Ram; Fass, Ronnie

2010-02-01

Determine the feasibility of using power spectrum of the sleep electroencephalogram (EEG) as a more sensitive tool than sleep architecture to evaluate the relationship between gastroesophageal reflux disease (GERD) and sleep. GERD has been shown to adversely affect subjective sleep reports but not necessarily objective sleep parameters. Data were prospectively collected from symptomatic patients with heartburn. All symptomatic patients underwent upper endoscopy. Patients without erosive esophagitis underwent pH testing. Sleep was polygraphically recorded in the laboratory. Spectral analysis was performed to determine the power spectrum in 4 bandwidths: delta (0.8 to 4.0 Hz), theta (4.1 to 8.0 Hz), alpha (8.1 to 13.0 Hz), and beta (13.1 to 20.0 Hz). Eleven heartburn patients were included in the GERD group (erosive esophagitis) and 6 heartburn patients in the functional heartburn group (negative endoscopy, pH test, response to proton pump inhibitors). The GERD patients had evidence of lower average delta-power than functional heartburn patients. Patients with GERD had greater overall alpha-power in the latter half of the night (3 hours after sleep onset) than functional heartburn patients. No significant differences were noted in conventional sleep stage summaries between the 2 groups. Among heartburn patients with GERD, EEG spectral power during sleep is shifted towards higher frequencies compared with heartburn patients without GERD despite similar sleep architecture. This feasibility study demonstrated that EEG spectral power during sleep might be the preferred tool to provide an objective analysis about the effect of GERD on sleep.

Electroencephalographic activity in response to procedural pain in preterm infants born at 28 and 33 weeks gestational age.

PubMed

Maimon, Neta; Grunau, Ruth E; Cepeda, Ivan L; Friger, Michael; Selnovik, Leonel; Gilat, Shlomo; Shany, Eilon

2013-12-01

Preterm infants undergo frequent painful procedures in the neonatal intensive care unit. Electroencephalography (EEG) changes in reaction to invasive procedures have been reported in preterm and full-term neonates. Frontal EEG asymmetry as an index of emotion during tactile stimulation shows inconsistent findings in full-term infants, and has not been examined in the context of pain in preterm infants. Our aim was to examine whether heel lance for blood collection induces changes in right-left frontal asymmetry, suggesting negative emotional response, in preterm neonates at different gestational age (GA) at birth and different duration of stay in the neonatal intensive care unit. Three groups of preterm infants were compared: set 1: group 1 (n=24), born and tested at 28 weeks GA; group 2 (n=22), born at 28 weeks GA and tested at 33 weeks; set 2: group 3 (n=25), born and tested at 33 weeks GA. EEG power was calculated for 30-second artifact-free periods, in standard frequency bandwidths, in 3 phases (baseline, up to 5 min after heel lance, 10 min after heel lance). No significant differences were found in right-left frontal asymmetry, or in ipsilateral or contralateral somatosensory response, across phases. In contrast, the Behavioral Indicators of Infant Pain scores changed across phase (P<0.0001). Infants in group 1 showed lower Behavioral Indicators of Infant Pain scores (P=0.039). There are technical challenges in recording EEG during procedures, as pain induces motor movements. More research is needed to determine the most sensitive approach to measure EEG signals within the context of pain in infancy.

EEG-Based Analysis of the Emotional Effect of Music Therapy on Palliative Care Cancer Patients

PubMed Central

Ramirez, Rafael; Planas, Josep; Escude, Nuria; Mercade, Jordi; Farriols, Cristina

2018-01-01

Music is known to have the power to induce strong emotions. The present study assessed, based on Electroencephalography (EEG) data, the emotional response of terminally ill cancer patients to a music therapy intervention in a randomized controlled trial. A sample of 40 participants from the palliative care unit in the Hospital del Mar in Barcelona was randomly assigned to two groups of 20. The first group [experimental group (EG)] participated in a session of music therapy (MT), and the second group [control group (CG)] was provided with company. Based on our previous work on EEG-based emotion detection, instantaneous emotional indicators in the form of a coordinate in the arousal-valence plane were extracted from the participants’ EEG data. The emotional indicators were analyzed in order to quantify (1) the overall emotional effect of MT on the patients compared to controls, and (2) the relative effect of the different MT techniques applied during each session. During each MT session, five conditions were considered: I (initial patient’s state before MT starts), C1 (passive listening), C2 (active listening), R (relaxation), and F (final patient’s state). EEG data analysis showed a significant increase in valence (p = 0.0004) and arousal (p = 0.003) between I and F in the EG. No significant changes were found in the CG. This results can be interpreted as a positive emotional effect of MT in advanced cancer patients. In addition, according to pre- and post-intervention questionnaire responses, participants in the EG also showed a significant decrease in tiredness, anxiety and breathing difficulties, as well as an increase in levels of well-being. No equivalent changes were observed in the CG. PMID:29551984

Role of ictal baseline shifts and ictal high-frequency oscillations in stereo-electroencephalography analysis of mesial temporal lobe seizures.

PubMed

Wu, Shasha; Kunhi Veedu, Hari Prasad; Lhatoo, Samden D; Koubeissi, Mohamad Z; Miller, Jonathan P; Lüders, Hans O

2014-05-01

To assess the role of ictal baseline shifts (IBS) and ictal high-frequency oscillations (iHFOs) in intracranial electroencephalography (EEG) presurgical evaluation by analysis of the spatial and temporal relationship of IBS, iHFOs with ictal conventional stereo-electroencephalography (icEEG) in mesial temporal lobe seizures (MTLS). We studied 15 adult patients with medically refractory MTLS who underwent monitoring with depth electrodes. Seventy-five ictal EEG recordings at 1,000 Hz sampling rate were studied. Visual comparison of icEEG, IBS, and iHFOs were performed using Nihon-Kohden Neurofax systems (acquisition range 0.016-300 Hz). Each recorded ictal EEG was analyzed with settings appropriate for displaying icEEG, IBS, and iHFOs. IBS and iHFOs were observed in all patients and in 91% and 81% of intracranial seizures, respectively. IBS occurred before (22%), at (57%), or after (21%) icEEG onset. In contrast, iHFOs occurred at (30%) or after (70%) icEEG onset. The onset of iHFOs was 11.5 s later than IBS onset (p < 0.0001). All of the earliest onset of IBS and 70% of the onset of iHFOs overlapped with the ictal onset zone (IOZ). Compared with iHFOs, interictal HFOs (itHFOs) were less correlated with IOZ. In contrast to icEEG, IBS and iHFOs had smaller spatial distributions in 70% and 100% of the seizures, respectively. An IBS dipole was observed in 66% of the seizures. Eighty-seven percent of the dipoles had a negative pole at the anterior/medial part of amygdala/hippocampus complex (A-H complex) and a positive pole at the posterior/lateral part of the A-H complex. The results suggest that evaluation of IBS and iHFOs, in addition to routine icEEG, helps in more accurately defining the IOZ. This study also shows that the onset and the spatial distribution of icEEG, IBS, and iHFOs do not overlap, suggesting that they reflect different cellular or network dynamics. Wiley Periodicals, Inc. © 2014 International League Against Epilepsy.

Time course of EEG background activity level before spontaneous awakening in infants.

PubMed

Zampi, Chiara; Fagioli, Igino; Salzarulo, Piero

2002-12-01

This research aimed to investigate the time course of the cortical activity level preceding spontaneous awakening as a function of age and state. Two groups of infants (1-4 and 9-14 weeks of age) were continuously monitored by polygraphic recording and behavioural observation during the night. The electroencephalographic (EEG) activity recorded by the C3-O1 lead was analysed through an automatic analysis method which provides, for each 30-s epoch, a single measure, time domain based, of the EEG synchronization. The EEG parameter values were computed in the 6 min preceding each awakening out of non-rapid eye movement (NREM) sleep and out of rapid eye movement (REM) sleep. The EEG background activity level did not change in the minutes preceding awakening out of REM sleep. Awakening out of NREM sleep was preceded by a change of EEG activity level in the direction of higher activation with different time course according to the age. Both REM and NREM sleep results suggest that a high level of EEG activity is a prerequisite for the occurrence of a spontaneous awakening.

Effects of CPAP-therapy on brain electrical activity in obstructive sleep apneic patients: a combined EEG study using LORETA and Omega complexity : reversible alterations of brain activity in OSAS.

PubMed

Toth, Marton; Faludi, Bela; Kondakor, Istvan

2012-10-01

Effects of initiation of continuous positive airway pressure (CPAP) therapy on EEG background activity were investigated in patients with obstructive sleep apnea syndrome (OSAS, N = 25) to test possible reversibility of alterations of brain electrical activity caused by chronic hypoxia. Normal control group (N = 14) was also examined. Two EEG examinations were done in each groups: at night and in the next morning. Global and regional (left vs. right, anterior vs. posterior) measures of spatial complexity (Omega complexity) were used to characterize the degree of spatial synchrony of EEG. Low resolution electromagnetic tomography (LORETA) was used to localize generators of EEG activity in separate frequency bands. Before CPAP-treatment, a significantly lower Omega complexity was found globally and over the right hemisphere. Due to CPAP-treatment, these significant differences vanished. Significantly decreased Omega complexity was found in the anterior region after treatment. LORETA showed a decreased activity in all of the beta bands after therapy in the right hippocampus, premotor and temporo-parietal cortex, and bilaterally in the precuneus, paracentral and posterior cingulate cortex. No significant changes were seen in control group. Comparing controls and patients before sleep, an increased alpha2 band activity was seen bilaterally in the precuneus, paracentral and posterior cingulate cortex, while in the morning an increased beta3 band activity in the left precentral and bilateral premotor cortex and a decreased delta band activity in the right temporo-parietal cortex and insula were observed. These findings indicate that effect of sleep on EEG background activity is different in OSAS patients and normal controls. In OSAS patients, significant changes lead to a more normal EEG after a night under CPAP-treatment. Compensatory alterations of brain electrical activity in regions associated with influencing sympathetic outflow, visuospatial abilities, long-term memory and motor performances caused by chronic hypoxia could be reversed by CPAP-therapy.

Increasing Performance of Professional Soccer Players and Elite Track and Field Athletes with Peak Performance Training and Biofeedback: A Pilot Study.

PubMed

Rijken, Noortje H; Soer, Remko; de Maar, Ewold; Prins, Hilco; Teeuw, Wouter B; Peuscher, Jan; Oosterveld, Frits G J

2016-12-01

The aim of this pilot study was to investigate the effects of an intervention consisting of mental coaching combined with either electro encephalogram (EEG) alpha power feedback or heart rate variability (HRV) feedback on HRV, EEG outcomes and self-reported factors related to stress, performance, recovery and sleep quality in elite athletes. A prospective pilot study was performed with two distinct cohorts. Soccer players were provided with four sessions of mental coaching combined with daily HRV biofeedback (Group A); track and field athletes were provided with four sessions of mental coaching in combination with daily neurofeedback (Group B). Measurements were performed at baseline, post intervention and at 5 weeks follow-up. Objective measures: EEG and ECG. Subjective measures: Numeric Rating Scale for performance, Pittsburgh Sleep Quality Index, Rest and Stress Questionnaire and Sports Improvement-60. Group characteristics were too distinct to compare the interventions. Linear mixed models were used to analyze differences within groups over time. In Group A, significant changes over time were present in alpha power at 5 of 7 EEG locations (p < 0.01-0.03). LF/HF ratio significantly increased (p = 0.02) and the concentration (p = 0.02) and emotional scale (p = 0.03) of the SIM-60 increased significantly (p = 0.04). In Group B, the HRV low frequency power and recovery scale of the REST-Q significantly increased (p = 0.02 and <0.01 resp.). Other measures remained stable or improved non-significantly. A mental coaching program combined with either HRV or EEG alpha power feedback may increase HRV and alpha power and may lead to better performance-related outcomes and stress reduction. Further research is needed to elucidate the effects of either type of feedback and to compare effects with a control group.

Behavioural Inhibition System (BIS) sensitivity differentiates EEG theta responses during goal conflict in a continuous monitoring task.

PubMed

Moore, Roger A; Mills, Matthew; Marshman, Paul; Corr, Philip J

2012-08-01

Previous research has revealed that EEG theta oscillations are affected during goal conflict processing. This is consistent with the behavioural inhibition system (BIS) theory of anxiety (Gray & McNaughton, 2000). However, studies have not attempted to relate these BIS-related theta effects to BIS personality measures. Confirmation of such an association would provide further support for BIS theory, especially as it relates to trait differences. EEG was measured (32 electrodes) from extreme groups (low/high trait BIS) engaged in a target detection task. Goal conflicts were introduced throughout the task. Results show that the two groups did not differ in behavioural performance. The major EEG result was that a stepwise discriminant analysis indicated discrimination by 6 variables derived from coherence and power, with 5 of the 6 in the theta range as predicted by BIS theory and one in the beta range. Also, across the whole sample, EEG theta coherence increased at a variety of regions during primary goal conflict and showed a general increase during response execution; EEG theta power, in contrast, was primarily reactive to response execution. This is the first study to reveal a three-way relationship between the induction of goal conflict, the induction of theta power and coherence, and differentiation by psychometrically-defined low/high BIS status. Copyright © 2012 Elsevier B.V. All rights reserved.

Prognostic and diagnostic value of EEG signal coupling measures in coma.

PubMed

Zubler, Frederic; Koenig, Christa; Steimer, Andreas; Jakob, Stephan M; Schindler, Kaspar A; Gast, Heidemarie

2016-08-01

Our aim was to assess the diagnostic and predictive value of several quantitative EEG (qEEG) analysis methods in comatose patients. In 79 patients, coupling between EEG signals on the left-right (inter-hemispheric) axis and on the anterior-posterior (intra-hemispheric) axis was measured with four synchronization measures: relative delta power asymmetry, cross-correlation, symbolic mutual information and transfer entropy directionality. Results were compared with etiology of coma and clinical outcome. Using cross-validation, the predictive value of measure combinations was assessed with a Bayes classifier with mixture of Gaussians. Five of eight measures showed a statistically significant difference between patients grouped according to outcome; one measure revealed differences in patients grouped according to the etiology. Interestingly, a high level of synchrony between the left and right hemisphere was associated with mortality on intensive care unit, whereas higher synchrony between anterior and posterior brain regions was associated with survival. The combination with the best predictive value reached an area-under the curve of 0.875 (for patients with post anoxic encephalopathy: 0.946). EEG synchronization measures can contribute to clinical assessment, and provide new approaches for understanding the pathophysiology of coma. Prognostication in coma remains a challenging task. qEEG could improve current multi-modal approaches. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

[Prognostic value of EEG in acute posttraumatic coma (author's transl)].

PubMed

Walser, H; Friedli, W; Glinz, W

1981-12-01

To evaluate the prognostic power of a single EEG-record, the recordings of 50 patients with posttraumatic coma performed within 48 hours after the injury were compared with the outcome after 6 months. A 5-point scale comprising 2 EEG-patterns being notorious for their dismal prognostic significance (suppression bursts, alpha-coma) and changes of vigilance were used as a mean of visual assessment of the recordings. In 24 out of the 28 patients with a bad outcome, the EEG had shown the patterns of category I, II and III (suppression bursts, alpha coma, no changes of vigilance). Of the 22 patients with a good outcome, the EEG had been classified as IV or V (clearly discernible changes of vigilance, sleep patterns). Further findings of particular dismal prognostic significance were focal epileptic discharges, as 9 out of the 11 patients with this EEG pattern had not survived the posttraumatic coma for more than 6 months.

Material and physical model for evaluation of deep brain activity contribution to EEG recordings

NASA Astrophysics Data System (ADS)

Ye, Yan; Li, Xiaoping; Wu, Tiecheng; Li, Zhe; Xie, Wenwen

2015-12-01

Deep brain activity is conventionally recorded with surgical implantation of electrodes. During the neurosurgery, brain tissue damage and the consequent side effects to patients are inevitably incurred. In order to eliminate undesired risks, we propose that deep brain activity should be measured using the noninvasive scalp electroencephalography (EEG) technique. However, the deeper the neuronal activity is located, the noisier the corresponding scalp EEG signals are. Thus, the present study aims to evaluate whether deep brain activity could be observed from EEG recordings. In the experiment, a three-layer cylindrical head model was constructed to mimic a human head. A single dipole source (sine wave, 10 Hz, altering amplitudes) was embedded inside the model to simulate neuronal activity. When the dipole source was activated, surface potential was measured via electrodes attached on the top surface of the model and raw data were recorded for signal analysis. Results show that the dipole source activity positioned at 66 mm depth in the model, equivalent to the depth of deep brain structures, is clearly observed from surface potential recordings. Therefore, it is highly possible that deep brain activity could be observed from EEG recordings and deep brain activity could be measured using the noninvasive scalp EEG technique.

EEG epochs with less alpha rhythm improve discrimination of mild Alzheimer's.

PubMed

Kanda, Paulo A M; Oliveira, Eliezyer F; Fraga, Francisco J

2017-01-01

Eyes-closed-awake electroencephalogram (EEG) is a useful tool in the diagnosis of Alzheimer's. However, there is eyes-closed-awake EEG with dominant or rare alpha rhythm. In this paper, we show that random selection of EEG epochs disregarding the alpha rhythm will lead to bias concerning EEG-based Alzheimer's Disease diagnosis. We compared EEG epochs with more than 30% and with less than 30% alpha rhythm of mild Alzheimer's Disease patients and healthy elderly. We classified epochs as dominant alpha scenario and rare alpha scenario according to alpha rhythm (8-13 Hz) percentage in O1, O2 and Oz channels. Accordingly, we divided the probands into four groups: 17 dominant alpha scenario controls, 15 mild Alzheimer's patients with dominant alpha scenario epochs, 12 rare alpha scenario healthy elderly and 15 mild Alzheimer's Disease patients with rare alpha scenario epochs. We looked for group differences using one-way ANOVA tests followed by post-hoc multiple comparisons (p < 0.05) over normalized energy values (%) on the other four well-known frequency bands (delta, theta, beta and gamma) using two different electrode configurations (parieto-occipital and central). After carrying out post-hoc multiple comparisons, for both electrode configurations we found significant differences between mild Alzheimer's patients and healthy elderly on beta- and theta-energy (%) only for the rare alpha scenario. No differences were found for the dominant alpha scenario in any of the five frequency bands. This is the first study of Alzheimer's awake-EEG reporting the influence of alpha rhythm on epoch selection, where our results revealed that, contrarily to what was most likely expected, less synchronized EEG epochs (rare alpha scenario) better discriminated mild Alzheimer's than those presenting abundant alpha (dominant alpha scenario). In addition, we find out that epoch selection is a very sensitive issue in qEEG research. Consequently, for Alzheimer's studies dealing with resting state EEG, we propose that epoch selection strategies should always be cautiously designed and thoroughly explained. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

L1 norm based common spatial patterns decomposition for scalp EEG BCI.

PubMed

Li, Peiyang; Xu, Peng; Zhang, Rui; Guo, Lanjin; Yao, Dezhong

2013-08-06

Brain computer interfaces (BCI) is one of the most popular branches in biomedical engineering. It aims at constructing a communication between the disabled persons and the auxiliary equipments in order to improve the patients' life. In motor imagery (MI) based BCI, one of the popular feature extraction strategies is Common Spatial Patterns (CSP). In practical BCI situation, scalp EEG inevitably has the outlier and artifacts introduced by ocular, head motion or the loose contact of electrodes in scalp EEG recordings. Because outlier and artifacts are usually observed with large amplitude, when CSP is solved in view of L2 norm, the effect of outlier and artifacts will be exaggerated due to the imposing of square to outliers, which will finally influence the MI based BCI performance. While L1 norm will lower the outlier effects as proved in other application fields like EEG inverse problem, face recognition, etc. In this paper, we present a new CSP implementation using the L1 norm technique, instead of the L2 norm, to solve the eigen problem for spatial filter estimation with aim to improve the robustness of CSP to outliers. To evaluate the performance of our method, we applied our method as well as the standard CSP and the regularized CSP with Tikhonov regularization (TR-CSP), on both the peer BCI dataset with simulated outliers and the dataset from the MI BCI system developed in our group. The McNemar test is used to investigate whether the difference among the three CSPs is of statistical significance. The results of both the simulation and real BCI datasets consistently reveal that the proposed method has much higher classification accuracies than the conventional CSP and the TR-CSP. By combining L1 norm based Eigen decomposition into Common Spatial Patterns, the proposed approach can effectively improve the robustness of BCI system to EEG outliers and thus be potential for the actual MI BCI application, where outliers are inevitably introduced into EEG recordings.

Automatic detection of sleep apnea based on EEG detrended fluctuation analysis and support vector machine.

PubMed

Zhou, Jing; Wu, Xiao-ming; Zeng, Wei-jie

2015-12-01

Sleep apnea syndrome (SAS) is prevalent in individuals and recently, there are many studies focus on using simple and efficient methods for SAS detection instead of polysomnography. However, not much work has been done on using nonlinear behavior of the electroencephalogram (EEG) signals. The purpose of this study is to find a novel and simpler method for detecting apnea patients and to quantify nonlinear characteristics of the sleep apnea. 30 min EEG scaling exponents that quantify power-law correlations were computed using detrended fluctuation analysis (DFA) and compared between six SAS and six healthy subjects during sleep. The mean scaling exponents were calculated every 30 s and 360 control values and 360 apnea values were obtained. These values were compared between the two groups and support vector machine (SVM) was used to classify apnea patients. Significant difference was found between EEG scaling exponents of the two groups (p < 0.001). SVM was used and obtained high and consistent recognition rate: average classification accuracy reached 95.1% corresponding to the sensitivity 93.2% and specificity 98.6%. DFA of EEG is an efficient and practicable method and is helpful clinically in diagnosis of sleep apnea.

Is 1/f sound more effective than simple resting in reducing stress response?

PubMed

Oh, Eun-Joo; Cho, Il-Young; Park, Soon-Kwon

2014-01-01

It has been previously demonstrated that listening to 1/f sound effectively reduces stress. However, these findings have been inconsistent and further study on the relationship between 1/f sound and the stress response is consequently necessary. The present study examined whether sound with 1/f properties (1/f sound) affects stress-induced electroencephalogram (EEG) changes. Twenty-six subjects who voluntarily participated in the study were randomly assigned to the experimental or control group. Data from four participants were excluded because of EEG artifacts. A mental arithmetic task was used as a stressor. Participants in the experiment group listened to 1/f sound for 5 minutes and 33 seconds, while participants in the control group sat quietly for the same duration. EEG recordings were obtained at various points throughout the experiment. After the experiment, participants completed a questionnaire on the affective impact of the 1/f sound. The results indicated that the mental arithmetic task effectively induced a stress response measurable by EEG. Relative theta power at all electrode sites was significantly lower than baseline in both the control and experimental group. Relative alpha power was significantly lower, and relative beta power was significantly higher in the T3 and T4 areas. Secondly, 1/f sound and simple resting affected task-associated EEG changes in a similar manner. Finally, participants reported in the questionnaire that they experienced a positive feeling in response to the 1/f sound. Our results suggest that a commercialized 1/f sound product is not more effective than simple resting in alleviating the physiological stress response.

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 artifacts due to simultaneous fMRI The algorithms combine a reference layer and adaptive filtering Several evaluation criteria suggest superior effectivity in terms of artifact reduction We demonstrate that physiological EEG components are preserved.

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 introduce new algorithms for reducing EEG artifacts due to simultaneous fMRI The algorithms combine a reference layer and adaptive filtering Several evaluation criteria suggest superior effectivity in terms of artifact reduction We demonstrate that physiological EEG components are preserved

Classification and evaluation of the pharmacodynamics of psychotropic drugs by single-lead pharmaco-EEG, EEG mapping and tomography (LORETA).

PubMed

Saletu, B; Anderer, P; Saletu-Zyhlarz, G M; Arnold, O; Pascual-Marqui, R D

2002-01-01

Utilizing computer-assisted quantitative analyses of human scalp-recorded electroencephalogram (EEG) in combination with certain statistical procedures (quantitative pharmaco-EEG) and mapping techniques (pharmaco-EEG mapping), it is possible to classify psychotropic substances and objectively evaluate their bioavailability at the target organ: the human brain. Specifically, one may determine at an early stage of drug development whether a drug is effective on the central nervous system (CNS) compared with placebo, what its clinical efficacy will be like, at which dosage it acts, when it acts and the equipotent dosages of different galenic formulations. Pharmaco-EEG profiles and maps of neuroleptics, antidepressants, tranquilizers, hypnotics, psychostimulants and nootropics/cognition-enhancing drugs will be described in this paper. Methodological problems, as well as the relationships between acute and chronic drug effects, alterations in normal subjects and patients, CNS effects, therapeutic efficacy and pharmacokinetic and pharmacodynamic data will be discussed. In recent times, imaging of drug effects on the regional brain electrical activity of healthy subjects by means of EEG tomography such as low-resolution electromagnetic tomography (LORETA) has been used for identifying brain areas predominantly involved in psychopharmacological action. This will be demonstrated for the representative drugs of the four main psychopharmacological classes, such as 3 mg haloperidol for neuroleptics, 20 mg citalopram for antidepressants, 2 mg lorazepam for tranquilizers and 20 mg methylphenidate for psychostimulants. LORETA demonstrates that these psychopharmacological classes affect brain structures differently.

Continuous EEG-fMRI in Pre-Surgical Evaluation of a Patient with Symptomatic Seizures: Bold Activation Linked to Interictal Epileptic Discharges Caused by Cavernoma.

PubMed

Avesani, M; Formaggio, E; Milanese, F; Baraldo, A; Gasparini, A; Cerini, R; Bongiovanni, L G; Pozzi Mucelli, R; Fiaschi, A; Manganotti, P

2008-04-07

We used continuous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) to identify the linkage between the "epileptogenic" and the "irritative" area in a patient with symptomatic epilepsy (cavernoma, previously diagnosed and surgically treated), i.e. a patient with a well known "epileptogenic area", and to increase the possibility of a non invasive pre-surgical evaluation of drug-resistant epilepsies. A compatible MRI system was used (EEG with 29 scalp electrodes and two electrodes for ECG and EMG) and signals were recorded with a 1.5 Tesla MRI scanner. After the recording session and MRI artifact removal, EEG data were analyzed offline and used as paradigms in fMRI study. Activation (EEG sequences with interictal slow-spiked-wave activity) and rest (sequences of normal EEG) conditions were compared to identify the potential resulting focal increase in BOLD signal and to consider if this is spatially linked to the interictal focus used as a paradigm and to the lesion. We noted an increase in the BOLD signal in the left neocortical temporal region, laterally and posteriorly to the poro-encephalic cavity (residual of cavernoma previously removed), that is around the "epileptogenic area". In our study "epileptogenic" and "irritative" areas were connected with each other. Combined EEG-fMRI may become routine in clinical practice for a better identification of an irritative and lesional focus in patients with symptomatic drug-resistant epilepsy.

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.

[Control of intelligent car based on electroencephalogram and neurofeedback].

PubMed

Li, Song; Xiong, Xin; Fu, Yunfa

2018-02-01

To improve the performance of brain-controlled intelligent car based on motor imagery (MI), a method based on neurofeedback (NF) with electroencephalogram (EEG) for controlling intelligent car is proposed. A mental strategy of MI in which the energy column diagram of EEG features related to the mental activity is presented to subjects with visual feedback in real time to train them to quickly master the skills of MI and regulate their EEG activity, and combination of multi-features fusion of MI and multi-classifiers decision were used to control the intelligent car online. The average, maximum and minimum accuracy of identifying instructions achieved by the trained group (trained by the designed feedback system before the experiment) were 85.71%, 90.47% and 76.19%, respectively and the corresponding accuracy achieved by the control group (untrained) were 73.32%, 80.95% and 66.67%, respectively. For the trained group, the average, longest and shortest time consuming were 92 s, 101 s, and 85 s, respectively, while for the control group the corresponding time were 115.7 s, 120 s, and 110 s, respectively. According to the results described above, it is expected that this study may provide a new idea for the follow-up development of brain-controlled intelligent robot by the neurofeedback with EEG related to MI.

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.

Spectral F-test power evaluation in the EEG during intermittent photic stimulation.

PubMed

de Sá, Antonio Mauricio F L Miranda; Cagy, Mauricio; Lazarev, Vladimir V; Infantosi, Antonio Fernando C

2006-06-01

Intermittent photic stimulation (IPS) is an important functional test, which can induce the photic driving in the electroencephalogram (EEG). It is capable of enhancing latent oscillations manifestations not present in the resting EEG. However, for adequate quantitative evaluation of the photic driving, these changes should be assessed on a statistical basis. With this aim, the sampling distribution of spectral F test was investigated. On this basis, confidence limits of the SFT-estimate could be obtained for different practical situations, in which the signal-to-noise ratio and the number of epochs used in the estimation may vary. The technique was applied to the EEG of 10 normal subjects during IPS, and allowed detecting responses not only at the fundamental IPS frequency but also at higher harmonics. It also permitted to assess the strength of the photic driving responses and to compare them in different derivations and in different subjects.

A machine learning approach using EEG data to predict response to SSRI treatment for major depressive disorder.

PubMed

Khodayari-Rostamabad, Ahmad; Reilly, James P; Hasey, Gary M; de Bruin, Hubert; Maccrimmon, Duncan J

2013-10-01

The problem of identifying, in advance, the most effective treatment agent for various psychiatric conditions remains an elusive goal. To address this challenge, we investigate the performance of the proposed machine learning (ML) methodology (based on the pre-treatment electroencephalogram (EEG)) for prediction of response to treatment with a selective serotonin reuptake inhibitor (SSRI) medication in subjects suffering from major depressive disorder (MDD). A relatively small number of most discriminating features are selected from a large group of candidate features extracted from the subject's pre-treatment EEG, using a machine learning procedure for feature selection. The selected features are fed into a classifier, which was realized as a mixture of factor analysis (MFA) model, whose output is the predicted response in the form of a likelihood value. This likelihood indicates the extent to which the subject belongs to the responder vs. non-responder classes. The overall method was evaluated using a "leave-n-out" randomized permutation cross-validation procedure. A list of discriminating EEG biomarkers (features) was found. The specificity of the proposed method is 80.9% while sensitivity is 94.9%, for an overall prediction accuracy of 87.9%. There is a 98.76% confidence that the estimated prediction rate is within the interval [75%, 100%]. These results indicate that the proposed ML method holds considerable promise in predicting the efficacy of SSRI antidepressant therapy for MDD, based on a simple and cost-effective pre-treatment EEG. The proposed approach offers the potential to improve the treatment of major depression and to reduce health care costs. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

ARTIST: A fully automated artifact rejection algorithm for single-pulse TMS-EEG data.

PubMed

Wu, Wei; Keller, Corey J; Rogasch, Nigel C; Longwell, Parker; Shpigel, Emmanuel; Rolle, Camarin E; Etkin, Amit

2018-04-01

Concurrent single-pulse TMS-EEG (spTMS-EEG) is an emerging noninvasive tool for probing causal brain dynamics in humans. However, in addition to the common artifacts in standard EEG data, spTMS-EEG data suffer from enormous stimulation-induced artifacts, posing significant challenges to the extraction of neural information. Typically, neural signals are analyzed after a manual time-intensive and often subjective process of artifact rejection. Here we describe a fully automated algorithm for spTMS-EEG artifact rejection. A key step of this algorithm is to decompose the spTMS-EEG data into statistically independent components (ICs), and then train a pattern classifier to automatically identify artifact components based on knowledge of the spatio-temporal profile of both neural and artefactual activities. The autocleaned and hand-cleaned data yield qualitatively similar group evoked potential waveforms. The algorithm achieves a 95% IC classification accuracy referenced to expert artifact rejection performance, and does so across a large number of spTMS-EEG data sets (n = 90 stimulation sites), retains high accuracy across stimulation sites/subjects/populations/montages, and outperforms current automated algorithms. Moreover, the algorithm was superior to the artifact rejection performance of relatively novice individuals, who would be the likely users of spTMS-EEG as the technique becomes more broadly disseminated. In summary, our algorithm provides an automated, fast, objective, and accurate method for cleaning spTMS-EEG data, which can increase the utility of TMS-EEG in both clinical and basic neuroscience settings. © 2018 Wiley Periodicals, Inc.

A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study

PubMed Central

2012-01-01

Background The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact. Methods Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls. Results Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences for the ASD-groups, when compared to the controls. Average spectral loading per factor was wide (10.1 Hz). Conclusions Classification success suggests a stable coherence loading pattern that differentiates ASD- from C-group subjects. This might constitute an EEG coherence-based phenotype of childhood autism. The predominantly reduced short-distance coherences may indicate poor local network function. The increased long-distance coherences may represent compensatory processes or reduced neural pruning. The wide average spectral range of factor loadings may suggest over-damped neural networks. PMID:22730909

Naloxone fails to prolong seizure length in ECT.

PubMed

Rasmussen, K G; Pandurangi, A K

1999-12-01

Electroconvulsive shock (ECS) in animals has been shown to enhance endogenous opiate systems. The anticonvulsant effects of ECS are also partially blocked by the opiate receptor antagonist naloxone, leading some investigators to postulate that the anticonvulsant effects of ECS are mediated by activation of endogenous opiates. If such a phenomenon occurs in humans, then naloxone might prolong seizure length in electroconvulsive therapy (ECT). In the present study, nine patients were given 2.0 mg intravenous (i.v.) naloxone 2 minutes prior to one-half of their ECT treatments. Motor seizure length was measured via the cuff technique. EEG tracings were read by an investigator blind to naloxone status. There was no difference between the two groups in either EEG or nonblindly evaluated motor seizure length. It is concluded that a dose of 2 mg naloxone does not effectively increase seizure length in ECT.

Experimental characterization and analysis of the BITalino platforms against a reference device.

PubMed

Batista, Diana; Silva, Hugo; Fred, Ana

2017-07-01

Low-cost hardware platforms for biomedical engineering are becoming increasingly available, which empower the research community in the development of new projects in a wide range of areas related with physiological data acquisition. Building upon previous work by our group, this work compares the quality of the data acquired by means of two different versions of the multimodal physiological computing platform BITalino, with a device that can be considered a reference. We acquired data from 5 sensors, namely Accelerometry (ACC), Electrocardiography (ECG), Electroencephalography (EEG), Electrodermal Activity (EDA) and Electromyography (EMG). Experimental evaluation shows that ACC, ECG and EDA data are highly correlated with the reference in what concerns the raw waveforms. When compared by means of their commonly used features, EEG and EMG data are also quite similar across the different devices.

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

Application of Independent Component Analysis for the Data Mining of Simultaneous EEG-fMRI: Preliminary Experience on Sleep Onset

PubMed Central

Lee, Jong-Hwan; Oh, Sungsuk; Jolesz, Ferenc A.; Park, Hyunwook; Yoo, Seung-Schik

2010-01-01

The simultaneous acquisition of electroencephalogram (EEG) and functional MRI (fMRI) signals is potentially advantageous because of the superior resolution that is achieved in both the temporal and spatial domains, respectively. However, ballistocardiographic artifacts along with the ocular artifacts are a major obstacle for the detection of the EEG signatures of interest. Since the sources corresponding to these artifacts are independent from those producing the EEG signatures, we applied the Infomax-based independent component analysis (ICA) technique to separate the EEG signatures from the artifacts. The isolated EEG signatures were further utilized to model the canonical hemodynamic response functions (HRFs). Subsequently, the brain areas from which these EEG signatures originated were identified as locales of activation patterns from the analysis of fMRI data. Upon the identification and subsequent evaluation of brain areas generating interictal epileptic discharge (IED) spikes from an epileptic subject, the presented method was successfully applied to detect the theta- and alpha-rhythms that are sleep onset related EEG signatures along with the subsequent neural circuitries from a sleep deprived volunteer. These results suggest that the ICA technique may be useful for the preprocessing of simultaneous EEG-fMRI acquisitions, especially when a reference paradigm is unavailable. PMID:19922343

Application of independent component analysis for the data mining of simultaneous Eeg-fMRI: preliminary experience on sleep onset.

PubMed

Lee, Jong-Hwan; Oh, Sungsuk; Jolesz, Ferenc A; Park, Hyunwook; Yoo, Seung-Schik

2009-01-01

The simultaneous acquisition of electroencephalogram (EEG) and functional MRI (fMRI) signals is potentially advantageous because of the superior resolution that is achieved in both the temporal and spatial domains, respectively. However, ballistocardiographic artifacts along with ocular artifacts are a major obstacle for the detection of the EEG signatures of interest. Since the sources corresponding to these artifacts are independent from those producing the EEG signatures, we applied the Infomax-based independent component analysis (ICA) technique to separate the EEG signatures from the artifacts. The isolated EEG signatures were further utilized to model the canonical hemodynamic response functions (HRFs). Subsequently, the brain areas from which these EEG signatures originated were identified as locales of activation patterns from the analysis of fMRI data. Upon the identification and subsequent evaluation of brain areas generating interictal epileptic discharge (IED) spikes from an epileptic subject, the presented method was successfully applied to detect the theta and alpha rhythms that are sleep onset-related EEG signatures along with the subsequent neural circuitries from a sleep-deprived volunteer. These results suggest that the ICA technique may be useful for the preprocessing of simultaneous EEG-fMRI acquisitions, especially when a reference paradigm is unavailable.

An EEG should not be obtained routinely after first unprovoked seizure in childhood.

PubMed

Gilbert, D L; Buncher, C R

2000-02-08

To quantify and analyze the value of expected information from an EEG after first unprovoked seizure in childhood. An EEG is often recommended as part of the standard diagnostic evaluation after first seizure. A MEDLINE search from 1980 to 1998 was performed. From eligible studies, data on EEG results and seizure recurrence risk in children were abstracted, and sensitivity, specificity, and positive and negative predictive values of EEG in predicting recurrence were calculated. Linear information theory was used to quantify and compare the expected information from the EEG in all studies. Standard test-treat decision analysis with a treatment threshold at 80% recurrence risk was used to determine the range of pretest recurrence probabilities over which testing affects treatment decisions. Four studies involving 831 children were eligible for analysis. At best, the EEG had a sensitivity of 61%, a specificity of 71%, and an expected information of 0.16 out of a possible 0.50. The pretest probability of recurrence was less than the lower limit of the range for rational testing in all studies. In this analysis, the quantity of expected information from the EEG was too low to affect treatment recommendations in most patients. EEG should be ordered selectively, not routinely, after first unprovoked seizure in childhood.

Contribution of EEG in transient neurological deficits.

PubMed

Lozeron, Pierre; Tcheumeni, Nadine Carole; Turki, Sahar; Amiel, Hélène; Meppiel, Elodie; Masmoudi, Sana; Roos, Caroline; Crassard, Isabelle; Plaisance, Patrick; Benbetka, Houria; Guichard, Jean-Pierre; Houdart, Emmanuel; Baudoin, Hélène; Kubis, Nathalie

2018-01-01

Identification of stroke mimics and 'chameleons' among transient neurological deficits (TND) is critical. Diagnostic workup consists of a brain imaging study, for a vascular disease or a brain tumour and EEG, for epileptiform discharges. The precise role of EEG in this diagnostic workup has, however, never been clearly delineated. However, this could be crucial in cases of atypical or incomplete presentation with consequences on disease management and treatment. We analysed the EEG patterns on 95 consecutive patients referred for an EEG within 7 days of a TND with diagnostic uncertainty. Patients were classified at the discharge or the 3-month follow-up visit as: 'ischemic origin', 'migraine aura', 'focal seizure', and 'other'. All patients had a brain imaging study. EEG characteristics were correlated to the TND symptoms, imaging study, and final diagnosis. Sixty four (67%) were of acute onset. Median symptom duration was 45 min. Thirty two % were 'ischemic', 14% 'migraine aura', 19% 'focal seizure', and 36% 'other' cause. EEGs were recorded with a median delay of 1.6 day after symptoms onset. Forty EEGs (42%) were abnormal. Focal slow waves were the most common finding (43%), also in the ischemic group (43%), whether patients had a typical presentation or not. Epileptiform discharges were found in three patients, one with focal seizure and two with migraine aura. Non-specific EEG focal slowing is commonly found in TND, and may last several days. We found no difference in EEG presentation between stroke mimics and stroke chameleons, and between other diagnoses.

Neural complexity in patients with poststroke depression: A resting EEG study.

PubMed

Zhang, Ying; Wang, Chunfang; Sun, Changcheng; Zhang, Xi; Wang, Yongjun; Qi, Hongzhi; He, Feng; Zhao, Xin; Wan, Baikun; Du, Jingang; Ming, Dong

2015-12-01

Poststroke depression (PSD) is one of the most common emotional disorders affecting post-stroke patients. However, the neurophysiological mechanism remains elusive. This study was aimed to study the relationship between complexity of neural electrical activity and PSD. Resting state eye-closed electroencephalogram (EEG) signals of 16 electrodes were recorded in 21 ischemic poststroke depression (PSD) patients, 22 ischemic poststroke non-depression (PSND) patients and 15 healthy controls (CONT). Lempel-Ziv Complexity (LZC) was used to evaluate changes in EEG complexity in PSD patients. Statistical analysis was performed to explore difference among different groups and electrodes. Correlation between the severity of depression (HDRS) and EEG complexity was determined with pearson correlation coefficients. Receiver operating characteristic (ROC) and binary logistic regression analysis were conducted to estimate the discriminating ability of LZC for PSD in specificity, sensitivity and accuracy. PSD patients showed lower neural complexity compared with PSND and CONT subjects in the whole brain regions. There was no significant difference among different brain regions, and no interactions between group and electrodes. None of the LZC significantly correlated with overall depression severity or differentiated symptom severity of 7 items in PSD patients, but in stroke patients, significant correlation was found between HDRS and LZC in the whole brain regions, especially in frontal and temporal. LZC parameters used for PSD recognition possessed more than 85% in specificity, sensitivity and accuracy, suggesting the feasibility of LZC to serve as screening indicators for PSD. Increased slow wave rhythms were found in PSD patients and clearly correlation was confirmed between neuronal complexity and spectral power of the four EEG rhythms. Lesion location of stroke patients in the study distributed in different brain regions, and most of the PSD patients were mild or moderate in depressive severity. Compared with conventional spectral analysis, complexity of neural activity using LZC was more sensitive and stationary in the measurement of abnormal brain activity in PSD patients and may offer a potential approach to facilitate clinical screening of this disease. Copyright © 2015 The Authors. Published by Elsevier B.V. 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.

Effect of passive concentration as instructional set for training enhancement of EEG alpha.

PubMed

Knox, S S

1980-12-01

The technique of passive concentration, employed by autogenic training and Transcendental Meditation for achieving relaxation, was tested here as a technique for enhancing EEG alpha. Of 30 subjects displaying between 15% and 74% alpha in their resting EEGs recruited, 10 had to be eliminated. The remaining 20 constituted two groups. One was instructed only to attempt to maintain a tone indicating alpha but given no information about technique (control group). The other was given additional instructions in passive concentration (experimental group). Both were given four 5-min. trials a day for 4 consecutive days. Heart rate and skin conductance were measured to monitor autonomic arousal. The group receiving instructions in passive concentration had significantly less alpha than the control group, which did not increase amount of alpha above baseline. The reduction of alpha in the experimental group was interpreted as resulting from beginning long training periods (20 min. per day), a practice advocated by Transcendental Meditation but discouraged by autogenic training. It was concluded that the relevance of passive concentration for alpha enhancement is doubtful.

Beta phase synchronization in the frontal-temporal-cerebellar network during auditory-to-motor rhythm learning.

PubMed

Edagawa, Kouki; Kawasaki, Masahiro

2017-02-22

Rhythm is an essential element of dancing and music. To investigate the neural mechanisms underlying how rhythm is learned, we recorded electroencephalographic (EEG) data during a rhythm-reproducing task that asked participants to memorize an auditory stimulus and reproduce it via tapping. Based on the behavioral results, we divided the participants into Learning and No-learning groups. EEG analysis showed that error-related negativity (ERN) in the Learning group was larger than in the No-learning group. Time-frequency analysis of the EEG data showed that the beta power in right and left temporal area at the late learning stage was smaller than at the early learning stage in the Learning group. Additionally, the beta power in the temporal and cerebellar areas in the Learning group when learning to reproduce the rhythm were larger than in the No Learning group. Moreover, phase synchronization between frontal and temporal regions and between temporal and cerebellar regions at late stages of learning were larger than at early stages. These results indicate that the frontal-temporal-cerebellar beta neural circuits might be related to auditory-motor rhythm learning.

Changes in functional brain networks following sports-related concussion in adolescents.

PubMed

Virji-Babul, Naznin; Hilderman, Courtney G E; Makan, Nadia; Liu, Aiping; Smith-Forrester, Jenna; Franks, Chris; Wang, Z J

2014-12-01

Sports-related concussion is a major public health issue; however, little is known about the underlying changes in functional brain networks in adolescents following injury. Our aim was to use the tools from graph theory to evaluate the changes in brain network properties following concussion in adolescent athletes. We recorded resting state electroencephalography (EEG) in 33 healthy adolescent athletes and 9 adolescent athletes with a clinical diagnosis of subacute concussion. Graph theory analysis was applied to these data to evaluate changes in brain networks. Global and local metrics of the structural properties of the graph were calculated for each group and correlated with Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) scores. Brain networks of both groups showed small-world topology with no statistically significant differences in the global metrics; however, significant differences were found in the local metrics. Specifically, in the concussed group, we noted: 1) increased values of betweenness and degree in frontal electrode sites corresponding to the (R) dorsolateral prefrontal cortex and the (R) inferior frontal gyrus and 2) decreased values of degree in the region corresponding to the (R) frontopolar prefrontal cortex. In addition, there was significant negative correlation between degree and hub value, with total symptom score at the electrode site corresponding to the (R) prefrontal cortex. This preliminary report in adolescent athletes shows for the first time that resting-state EEG combined with graph theoretical analysis may provide an objective method of evaluating changes in brain networks following concussion. This approach may be useful in identifying individuals at risk for future injury.

3 Tesla MRI-negative focal epilepsies: Presurgical evaluation, postoperative outcome and predictive factors.

PubMed

Kogias, Evangelos; Klingler, Jan-Helge; Urbach, Horst; Scheiwe, Christian; Schmeiser, Barbara; Doostkam, Soroush; Zentner, Josef; Altenmüller, Dirk-Matthias

2017-12-01

To investigate presurgical diagnostic modalities, clinical and seizure outcome as well as predictive factors after resective epilepsy surgery in 3 Tesla MRI-negative focal epilepsies. This retrospective study comprises 26 patients (11 males/15 females, mean age 34±12years, range 13-50 years) with 3 Tesla MRI-negative focal epilepsies who underwent resective epilepsy surgery. Non-invasive and invasive presurgical diagnostic modalities, type and localization of resection, clinical and epileptological outcome with a minimum follow-up of 1year (range 1-11 years, mean 2.5±2.3years) after surgery as well as outcome predictors were evaluated. All patients underwent invasive video-EEG monitoring after implantation of intracerebral depth and/or subdural electrodes. Ten patients received temporal and 16 extratemporal or multilobar (n=4) resections. There was no perioperative death or permanent morbidity. Overall, 12 of 26 patients (46%) were completely seizure-free (Engel IA) and 65% had a favorable outcome (Engel I-II). In particular, seizure-free ratio was 40% in the temporal and 50% in the extratemporal group. In the temporal group, long duration of epilepsy correlated with poor seizure outcome, whereas congruent unilateral FDG-PET hypometabolism correlated with a favorable outcome. In almost two thirds of temporal and extratemporal epilepsies defined as "non-lesional" by 3 Tesla MRI criteria, a favorable postoperative seizure outcome (Engel I-II) can be achieved with accurate multimodal presurgical evaluation including intracranial EEG recordings. In the temporal group, most favorable results were obtained when FDG-PET displayed congruent unilateral hypometabolism. Copyright © 2017 Elsevier B.V. All rights reserved.

A new wavelet transform to sparsely represent cortical current densities for EEG/MEG inverse problems.

PubMed

Liao, Ke; Zhu, Min; Ding, Lei

2013-08-01

The present study investigated the use of transform sparseness of cortical current density on human brain surface to improve electroencephalography/magnetoencephalography (EEG/MEG) inverse solutions. Transform sparseness was assessed by evaluating compressibility of cortical current densities in transform domains. To do that, a structure compression method from computer graphics was first adopted to compress cortical surface structure, either regular or irregular, into hierarchical multi-resolution meshes. Then, a new face-based wavelet method based on generated multi-resolution meshes was proposed to compress current density functions defined on cortical surfaces. Twelve cortical surface models were built by three EEG/MEG softwares and their structural compressibility was evaluated and compared by the proposed method. Monte Carlo simulations were implemented to evaluate the performance of the proposed wavelet method in compressing various cortical current density distributions as compared to other two available vertex-based wavelet methods. The present results indicate that the face-based wavelet method can achieve higher transform sparseness than vertex-based wavelet methods. Furthermore, basis functions from the face-based wavelet method have lower coherence against typical EEG and MEG measurement systems than vertex-based wavelet methods. Both high transform sparseness and low coherent measurements suggest that the proposed face-based wavelet method can improve the performance of L1-norm regularized EEG/MEG inverse solutions, which was further demonstrated in simulations and experimental setups using MEG data. Thus, this new transform on complicated cortical structure is promising to significantly advance EEG/MEG inverse source imaging technologies. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Analysis of bioelectric records and fabrication of phototype sleep analysis equipment

NASA Technical Reports Server (NTRS)

Kellaway, P.

1972-01-01

A computer-analysis technique was used to evaluate the changes in the waking EEGs of 5 normal subjects which occurred during the oral administration of flurazepam hydrochloride (Dalmane). While the subjects were receiving the drug, there was an increase in the amount of beta (14-38 c/sec) activity in fronto-central EEG leads in all 5 subjects. This increase in beta activity was characterized by a highly consistent increase in the number of waves that occurred during an EEG recording interval of fixed duration and by a less consistent increase in average wave amplitude. There was no detectable change in mean EEG wavelength (frequency) within the beta frequency range. The EEG patterns reverted to their baseline condition during 2-3 weeks after withdrawal of the drug. Analysis of the alpha, theta and delta components of the EEG indicated no changes during or following administration of the drug. This study clearly illustrates the usefulness of specific computer-analysis techniques in the characterization and quantification of sleep-promoting drugs upon the EEG of the normal young adults in the waking state. Two preamplifiers and 150 EEG monitoring caps with electrodes were delivered to MSC.

Neurophysiological tools to investigate consumer's gender differences during the observation of TV commercials.

PubMed

Vecchiato, Giovanni; Maglione, Anton Giulio; Cherubino, Patrizia; Wasikowska, Barbara; Wawrzyniak, Agata; Latuszynska, Anna; Latuszynska, Malgorzata; Nermend, Kesra; Graziani, Ilenia; Leucci, Maria Rita; Trettel, Arianna; Babiloni, Fabio

2014-01-01

Neuromarketing is a multidisciplinary field of research whose aim is to investigate the consumers' reaction to advertisements from a neuroscientific perspective. In particular, the neuroscience field is thought to be able to reveal information about consumer preferences which are unobtainable through conventional methods, including submitting questionnaires to large samples of consumers or performing psychological personal or group interviews. In this scenario, we performed an experiment in order to investigate cognitive and emotional changes of cerebral activity evaluated by neurophysiologic indices during the observation of TV commercials. In particular, we recorded the electroencephalographic (EEG), galvanic skin response (GSR), and heart rate (HR) in a group of 28 healthy subjects during the observation of a series of TV advertisements that have been grouped by commercial categories. Comparisons of cerebral indices have been performed to highlight gender differences between commercial categories and scenes of interest of two specific commercials. Findings show how EEG methodologies, along with the measurements of autonomic variables, could be used to obtain hidden information to marketers not obtainable otherwise. Most importantly, it was suggested how these tools could help to analyse the perception of TV advertisements and differentiate their production according to the consumer's gender.

Neurophysiological Tools to Investigate Consumer's Gender Differences during the Observation of TV Commercials

PubMed Central

Maglione, Anton Giulio; Wasikowska, Barbara; Wawrzyniak, Agata; Graziani, Ilenia; Trettel, Arianna

2014-01-01

Neuromarketing is a multidisciplinary field of research whose aim is to investigate the consumers' reaction to advertisements from a neuroscientific perspective. In particular, the neuroscience field is thought to be able to reveal information about consumer preferences which are unobtainable through conventional methods, including submitting questionnaires to large samples of consumers or performing psychological personal or group interviews. In this scenario, we performed an experiment in order to investigate cognitive and emotional changes of cerebral activity evaluated by neurophysiologic indices during the observation of TV commercials. In particular, we recorded the electroencephalographic (EEG), galvanic skin response (GSR), and heart rate (HR) in a group of 28 healthy subjects during the observation of a series of TV advertisements that have been grouped by commercial categories. Comparisons of cerebral indices have been performed to highlight gender differences between commercial categories and scenes of interest of two specific commercials. Findings show how EEG methodologies, along with the measurements of autonomic variables, could be used to obtain hidden information to marketers not obtainable otherwise. Most importantly, it was suggested how these tools could help to analyse the perception of TV advertisements and differentiate their production according to the consumer's gender. PMID:25147579

Task complexity modulates pilot electroencephalographic activity during real flights.

PubMed

Di Stasi, Leandro L; Diaz-Piedra, Carolina; Suárez, Juan; McCamy, Michael B; Martinez-Conde, Susana; Roca-Dorda, Joaquín; Catena, Andrés

2015-07-01

Most research connecting task performance and neural activity to date has been conducted in laboratory conditions. Thus, field studies remain scarce, especially in extreme conditions such as during real flights. Here, we investigated the effects of flight procedures of varied complexity on the in-flight EEG activity of military helicopter pilots. Flight procedural complexity modulated the EEG power spectrum: highly demanding procedures (i.e., takeoff and landing) were associated with higher EEG power in the higher frequency bands, whereas less demanding procedures (i.e., flight exercises) were associated with lower EEG power over the same frequency bands. These results suggest that EEG recordings may help to evaluate an operator's cognitive performance in challenging real-life scenarios, and thus could aid in the prevention of catastrophic events. © 2015 Society for Psychophysiological Research.

Multimodal Spatial Calibration for Accurately Registering EEG Sensor Positions

PubMed Central

Chen, Shengyong; Xiao, Gang; Li, Xiaoli

2014-01-01

This paper proposes a fast and accurate calibration method to calibrate multiple multimodal sensors using a novel photogrammetry system for fast localization of EEG sensors. The EEG sensors are placed on human head and multimodal sensors are installed around the head to simultaneously obtain all EEG sensor positions. A multiple views' calibration process is implemented to obtain the transformations of multiple views. We first develop an efficient local repair algorithm to improve the depth map, and then a special calibration body is designed. Based on them, accurate and robust calibration results can be achieved. We evaluate the proposed method by corners of a chessboard calibration plate. Experimental results demonstrate that the proposed method can achieve good performance, which can be further applied to EEG source localization applications on human brain. PMID:24803954

Adaptive noise canceling of electrocardiogram artifacts in single channel electroencephalogram.

PubMed

Cho, Sung Pil; Song, Mi Hye; Park, Young Cheol; Choi, Ho Seon; Lee, Kyoung Joung

2007-01-01

A new method for estimating and eliminating electrocardiogram (ECG) artifacts from single channel scalp electroencephalogram (EEG) is proposed. The proposed method consists of emphasis of QRS complex from EEG using least squares acceleration (LSA) filter, generation of synchronized pulse with R-peak and ECG artifacts estimation and elimination using adaptive filter. The performance of the proposed method was evaluated using simulated and real EEG recordings, we found that the ECG artifacts were successfully estimated and eliminated in comparison with the conventional multi-channel techniques, which are independent component analysis (ICA) and ensemble average (EA) method. From this we can conclude that the proposed method is useful for the detecting and eliminating the ECG artifacts from single channel EEG and simple to use for ambulatory/portable EEG monitoring system.

Neuroimaging Study of Alpha and Beta EEG Biofeedback Effects on Neural Networks.

PubMed

Shtark, Mark B; Kozlova, Lyudmila I; Bezmaternykh, Dmitriy D; Mel'nikov, Mikhail Ye; Savelov, Andrey A; Sokhadze, Estate M

2018-06-01

Neural networks interaction was studied in healthy men (20-35 years old) who underwent 20 sessions of EEG biofeedback training outside the MRI scanner, with concurrent fMRI-EEG scans at the beginning, middle, and end of the course. The study recruited 35 subjects for EEG biofeedback, but only 18 of them were considered as "successful" in self-regulation of target EEG bands during the whole course of training. Results of fMRI analysis during EEG biofeedback are reported only for these "successful" trainees. The experimental group (N = 23 total, N = 13 "successful") upregulated the power of alpha rhythm, while the control group (N = 12 total, N = 5 "successful") beta rhythm, with the protocol instructions being as for alpha training in both. The acquisition of the stable skills of alpha self-regulation was followed by the weakening of the irrelevant links between the cerebellum and visuospatial network (VSN), as well as between the VSN, the right executive control network (RECN), and the cuneus. It was also found formation of a stable complex based on the interaction of the precuneus, the cuneus, the VSN, and the high level visuospatial network (HVN), along with the strengthening of the interaction of the anterior salience network (ASN) with the precuneus. In the control group, beta enhancement training was accompanied by weakening of interaction between the precuneus and the default mode network, and a decrease in connectivity between the cuneus and the primary visual network (PVN). The differences between the alpha training group and the control group increased successively during training. Alpha training was characterized by a less pronounced interaction of the network formed by the PVN and the HVN, as well as by an increased interaction of the cerebellum with the precuneus and the RECN. The study demonstrated the differences in the structure and interaction of neural networks involved into alpha and beta generating systems forming and functioning, which should be taken into account during planning neurofeedback interventions. Possibility of using fMRI-guided biofeedback organized according to the described neural networks interaction may advance more accurate targeting specific symptoms during neurotherapy.

Magnetoencephalography for the Detection of Intervention Effects of a Specific Nutrient Combination in Patients with Mild Alzheimer’s Disease: Results from an Exploratory Double-Blind, Randomized, Controlled Study

PubMed Central

van Straaten, Elisabeth C. W.; de Waal, Hanneke; Lansbergen, Marieke M.; Scheltens, Philip; Maestu, Fernando; Nowak, Rafal; Hillebrand, Arjan; Stam, Cornelis J.

2016-01-01

Synaptic loss is an early pathological finding in Alzheimer’s disease (AD) and correlates with memory impairment. Changes in macroscopic brain activity measured with electro- and magnetoencephalography (EEG and MEG) in AD indicate synaptic changes and may therefore serve as markers of intervention effects in clinical trials. EEG peak frequency and functional networks have shown, in addition to improved memory performance, to be sensitive to detect an intervention effect in mild AD patients of the medical food Souvenaid containing the specific nutrient combination Fortasyn® Connect, which is designed to enhance synapse formation and function. Here, we explore the value of MEG, with higher spatial resolution than EEG, in identifying intervention effects of the nutrient combination by comparing MEG spectral measures, functional connectivity, and networks between an intervention and a control group. Quantitative markers describing spectral properties, functional connectivity, and graph theoretical aspects of MEG from the exploratory 24-week, double-blind, randomized, controlled Souvenir II MEG sub-study (NTR1975, http://www.trialregister.nl) in drug naïve patients with mild AD were compared between a test group (n = 27), receiving Souvenaid, and a control group (n = 28), receiving an isocaloric control product. The groups were unbalanced at screening with respect to Mini-Mental State Examination. Peak frequencies of MEG were compared with EEG peak frequencies, recorded in the same patients at similar time points, were compared with respect to sensitivity to intervention effects. No consistent statistically significant intervention effects were detected. In addition, we found no difference in sensitivity between MEG and EEG peak frequency. This exploratory study could not unequivocally establish the value of MEG in detecting interventional effects on brain activity, possibly due to small sample size and unbalanced study groups. We found no indication that the difference could be attributed to a lack of sensitivity of MEG compared with EEG. MEG in randomized controlled trials is feasible but its value to disclose intervention effects of Souvenaid in mild AD patients needs to be studied further. PMID:27799918

Magnetoencephalography for the Detection of Intervention Effects of a Specific Nutrient Combination in Patients with Mild Alzheimer's Disease: Results from an Exploratory Double-Blind, Randomized, Controlled Study.

PubMed

van Straaten, Elisabeth C W; de Waal, Hanneke; Lansbergen, Marieke M; Scheltens, Philip; Maestu, Fernando; Nowak, Rafal; Hillebrand, Arjan; Stam, Cornelis J

2016-01-01

Synaptic loss is an early pathological finding in Alzheimer's disease (AD) and correlates with memory impairment. Changes in macroscopic brain activity measured with electro- and magnetoencephalography (EEG and MEG) in AD indicate synaptic changes and may therefore serve as markers of intervention effects in clinical trials. EEG peak frequency and functional networks have shown, in addition to improved memory performance, to be sensitive to detect an intervention effect in mild AD patients of the medical food Souvenaid containing the specific nutrient combination Fortasyn ® Connect, which is designed to enhance synapse formation and function. Here, we explore the value of MEG, with higher spatial resolution than EEG, in identifying intervention effects of the nutrient combination by comparing MEG spectral measures, functional connectivity, and networks between an intervention and a control group. Quantitative markers describing spectral properties, functional connectivity, and graph theoretical aspects of MEG from the exploratory 24-week, double-blind, randomized, controlled Souvenir II MEG sub-study (NTR1975, http://www.trialregister.nl) in drug naïve patients with mild AD were compared between a test group ( n  = 27), receiving Souvenaid, and a control group ( n  = 28), receiving an isocaloric control product. The groups were unbalanced at screening with respect to Mini-Mental State Examination. Peak frequencies of MEG were compared with EEG peak frequencies, recorded in the same patients at similar time points, were compared with respect to sensitivity to intervention effects. No consistent statistically significant intervention effects were detected. In addition, we found no difference in sensitivity between MEG and EEG peak frequency. This exploratory study could not unequivocally establish the value of MEG in detecting interventional effects on brain activity, possibly due to small sample size and unbalanced study groups. We found no indication that the difference could be attributed to a lack of sensitivity of MEG compared with EEG. MEG in randomized controlled trials is feasible but its value to disclose intervention effects of Souvenaid in mild AD patients needs to be studied further.

EEG functional network topology is associated with disability in patients with amyotrophic lateral sclerosis

NASA Astrophysics Data System (ADS)

Fraschini, Matteo; Demuru, Matteo; Hillebrand, Arjan; Cuccu, Lorenza; Porcu, Silvia; di Stefano, Francesca; Puligheddu, Monica; Floris, Gianluca; Borghero, Giuseppe; Marrosu, Francesco

2016-12-01

Amyotrophic Lateral Sclerosis (ALS) is one of the most severe neurodegenerative diseases, which is known to affect upper and lower motor neurons. In contrast to the classical tenet that ALS represents the outcome of extensive and progressive impairment of a fixed set of motor connections, recent neuroimaging findings suggest that the disease spreads along vast non-motor connections. Here, we hypothesised that functional network topology is perturbed in ALS, and that this reorganization is associated with disability. We tested this hypothesis in 21 patients affected by ALS at several stages of impairment using resting-state electroencephalography (EEG) and compared the results to 16 age-matched healthy controls. We estimated functional connectivity using the Phase Lag Index (PLI), and characterized the network topology using the minimum spanning tree (MST). We found a significant difference between groups in terms of MST dissimilarity and MST leaf fraction in the beta band. Moreover, some MST parameters (leaf, hierarchy and kappa) significantly correlated with disability. These findings suggest that the topology of resting-state functional networks in ALS is affected by the disease in relation to disability. EEG network analysis may be of help in monitoring and evaluating the clinical status of ALS patients.

Visuospatial Working Memory in Toddlers with a History of Periventricular Leukomalacia: An EEG Narrow-Band Power Analysis

PubMed Central

García-Gomar, María Luisa; Santiago-Rodríguez, Efraín; Rodríguez-Camacho, Mario; Harmony, Thalía

2013-01-01

Background Periventricular Leukomalacia (PVL) affects white matter, but grey matter injuries have also been reported, particularly in the dorsomedial nucleus and the cortex. Both structures have been related to working memory (WM) processes. The aim of this study was to compare behavioral performances and EEG power spectra during a visuospatial working memory task (VSWMT) of toddlers with a history of PVL and healthy toddlers. Methodology/Principal Findings A prospective, comparative study of WM was conducted in toddlers with a history of PVL and healthy toddlers. The task responses and the EEG narrow-band power spectra during a VSWMT were compared in both groups. The EEG absolute power was analyzed during the following three conditions: baseline, attention and WM retention. The number of correct responses was higher in the healthy group (20.5±5.0) compared to the PVL group (16.1±3.9) (p = 0.04). The healthy group had absolute power EEG increases (p≤0.05) during WM compared to the attention condition in the bilateral frontal and right temporal, parietal and occipital regions in frequencies ranging from 1.17 to 2.34 Hz and in the right temporal, parietal and occipital regions in frequencies ranging from 14.06 to 15.23 Hz. In contrast, the PVL group had absolute power increases (p≤0.05) in the bilateral fronto-parietal, left central and occipital regions in frequencies that ranged from 1.17 to 3.52 Hz and in the bilateral frontal and right temporal regions in frequencies ranging from 9.37 to 19.14 Hz. Conclusions/Significance This study provides evidence that PVL toddlers have visuospatial WM deficits and a very different pattern of absolute power increases compared to a healthy group of toddlers, with greater absolute power in the low frequency range and widespread neuronal networks in the WM retention phase. PMID:23922816

Visuospatial working memory in toddlers with a history of periventricular Leukomalacia: an EEG narrow-band power analysis.

PubMed

García-Gomar, María Luisa; Santiago-Rodríguez, Efraín; Rodríguez-Camacho, Mario; Harmony, Thalía

2013-01-01

Periventricular Leukomalacia (PVL) affects white matter, but grey matter injuries have also been reported, particularly in the dorsomedial nucleus and the cortex. Both structures have been related to working memory (WM) processes. The aim of this study was to compare behavioral performances and EEG power spectra during a visuospatial working memory task (VSWMT) of toddlers with a history of PVL and healthy toddlers. A prospective, comparative study of WM was conducted in toddlers with a history of PVL and healthy toddlers. The task responses and the EEG narrow-band power spectra during a VSWMT were compared in both groups. The EEG absolute power was analyzed during the following three conditions: baseline, attention and WM retention. The number of correct responses was higher in the healthy group (20.5 ± 5.0) compared to the PVL group (16.1 ± 3.9) (p = 0.04). The healthy group had absolute power EEG increases (p ≤ 0.05) during WM compared to the attention condition in the bilateral frontal and right temporal, parietal and occipital regions in frequencies ranging from 1.17 to 2.34 Hz and in the right temporal, parietal and occipital regions in frequencies ranging from 14.06 to 15.23 Hz. In contrast, the PVL group had absolute power increases (p ≤ 0.05) in the bilateral fronto-parietal, left central and occipital regions in frequencies that ranged from 1.17 to 3.52 Hz and in the bilateral frontal and right temporal regions in frequencies ranging from 9.37 to 19.14 Hz. This study provides evidence that PVL toddlers have visuospatial WM deficits and a very different pattern of absolute power increases compared to a healthy group of toddlers, with greater absolute power in the low frequency range and widespread neuronal networks in the WM retention phase.

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

Differences of brain electrical activity between moderate and severe obstructive sleep apneic patients: a LORETA study.

PubMed

Toth, Marton; Kondakor, Istvan; Faludi, Bela

2016-10-01

The effects of initiation of continuous positive airway pressure (CPAP) therapy on electroencephalographic (EEG) background activity were investigated in patients exhibiting both moderate (n = 13) and severe (n = 12) obstructive sleep apnea syndromes in the testing of the potential differences of alterations of brain electrical activity caused by chronic hypoxia between these two groups. A normal control group (n = 14) was also examined. Two EEG examinations were achieved in each group: before and after first-time CPAP therapy. Low-resolution electromagnetic tomography (LORETA) was implemented towards localizing the generators of EEG activity in separate frequency bands. Prior to CPAP treatment, as a common direction of change, analysis with LORETA demonstrated increased activity in comparison with the patient and control groups. In the moderate group, significant changes were detected in the alpha2 band in the posterior cingulate cortex as well as in the beta1 band in the right posterior parietal cortex and the left supramarginal gyrus. In the severe group, significant changes were found in theta and alpha1 bands in the posterior cingulate cortex. Following CPAP treatment, these significant differences vanished in the severe group. In the moderate group, significantly decreased activity was seen in the beta3 band in the right fusiform gyrus. These findings potentially suggest a normalizing effect of CPAP therapy on EEG background activity in both groups of obstructive sleep apnea syndrome patients. Compensatory alterations of brain electrical activity in regions associated with influencing successful memory retrieval, emotional perception, default mode network, anorexia and fear network caused by chronic intermittent hypoxia could possibly be reversed with the use of CPAP therapy. © 2016 European Sleep Research Society.

Unified Bayesian Estimator of EEG Reference at Infinity: rREST (Regularized Reference Electrode Standardization Technique)

PubMed Central

Hu, Shiang; Yao, Dezhong; Valdes-Sosa, Pedro A.

2018-01-01

The choice of reference for the electroencephalogram (EEG) is a long-lasting unsolved issue resulting in inconsistent usages and endless debates. Currently, both the average reference (AR) and the reference electrode standardization technique (REST) are two primary, apparently irreconcilable contenders. We propose a theoretical framework to resolve this reference issue by formulating both (a) estimation of potentials at infinity, and (b) determination of the reference, as a unified Bayesian linear inverse problem, which can be solved by maximum a posterior estimation. We find that AR and REST are very particular cases of this unified framework: AR results from biophysically non-informative prior; while REST utilizes the prior based on the EEG generative model. To allow for simultaneous denoising and reference estimation, we develop the regularized versions of AR and REST, named rAR and rREST, respectively. Both depend on a regularization parameter that is the noise to signal variance ratio. Traditional and new estimators are evaluated with this framework, by both simulations and analysis of real resting EEGs. Toward this end, we leverage the MRI and EEG data from 89 subjects which participated in the Cuban Human Brain Mapping Project. Generated artificial EEGs—with a known ground truth, show that relative error in estimating the EEG potentials at infinity is lowest for rREST. It also reveals that realistic volume conductor models improve the performances of REST and rREST. Importantly, for practical applications, it is shown that an average lead field gives the results comparable to the individual lead field. Finally, it is shown that the selection of the regularization parameter with Generalized Cross-Validation (GCV) is close to the “oracle” choice based on the ground truth. When evaluated with the real 89 resting state EEGs, rREST consistently yields the lowest GCV. This study provides a novel perspective to the EEG reference problem by means of a unified inverse solution framework. It may allow additional principled theoretical formulations and numerical evaluation of performance. PMID:29780302

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.

A review of channel selection algorithms for EEG signal processing

NASA Astrophysics Data System (ADS)

Alotaiby, Turky; El-Samie, Fathi E. Abd; Alshebeili, Saleh A.; Ahmad, Ishtiaq

2015-12-01

Digital processing of electroencephalography (EEG) signals has now been popularly used in a wide variety of applications such as seizure detection/prediction, motor imagery classification, mental task classification, emotion classification, sleep state classification, and drug effects diagnosis. With the large number of EEG channels acquired, it has become apparent that efficient channel selection algorithms are needed with varying importance from one application to another. The main purpose of the channel selection process is threefold: (i) to reduce the computational complexity of any processing task performed on EEG signals by selecting the relevant channels and hence extracting the features of major importance, (ii) to reduce the amount of overfitting that may arise due to the utilization of unnecessary channels, for the purpose of improving the performance, and (iii) to reduce the setup time in some applications. Signal processing tools such as time-domain analysis, power spectral estimation, and wavelet transform have been used for feature extraction and hence for channel selection in most of channel selection algorithms. In addition, different evaluation approaches such as filtering, wrapper, embedded, hybrid, and human-based techniques have been widely used for the evaluation of the selected subset of channels. In this paper, we survey the recent developments in the field of EEG channel selection methods along with their applications and classify these methods according to the evaluation approach.

Retrospective multicenter evaluation of the "fly-catching syndrome" in 24 dogs: EEG, BAER, MRI, CSF findings and response to antiepileptic and antidepressant treatment.

PubMed

Wrzosek, Marcin; Płonek, Marta; Nicpoń, Józef; Cizinauskas, Sigitas; Pakozdy, Akos

2015-12-01

The fly-catching syndrome (FCS) is a rare canine condition of sudden, occasional, or constant episodes of biting the air. It may be accompanied by jumping, licking, and swallowing. The etiology of FCS is unknown and controversial. Various explanations for its occurrence have included epileptoid disorders such as visual cortex epileptiform disturbances and simple and complex partial seizures as well as compulsive disorders, hallucinatory behavior, and stereotypy. A retrospective multicenter analysis of 24 dogs with clinical symptoms of FCS is presented. Clinical signs at the time of presentation, the mean age at onset of the disease, the response to treatment, and the clinical outcome were recorded and analyzed in all patients. All dogs underwent clinical, neurological, and otoscopic examinations. Complete blood cell counts (CBCs) and serum chemistry panels were obtained from each dog. Diagnostic testing included MRI and EEG examinations in 21 cases, BAER in 19 cases, and CSF analysis in 20 cases. The EEG revealed spike activity in 8 (38%) of the 21 cases, 7 of which had activity in the occipital lobes. The brainstem auditory evoked response (BAER) revealed three cases of bilateral deafness. The MRI revealed six cases of Chiari malformation (CM), one case of syringohydromyelia (SM), and one case of a falx cerebri meningioma. The dogs were divided into groups according to their treatment protocol. Group A included dogs treated with phenobarbital (PB), and group B consisted of dogs treated with fluoxetine (FLX). Thirty-six percent of the dogs in group A responded to PB, while 100% of the dogs in group B responded to FLX. The results suggest that FCS is more responsive to FLX than PB. However, the etiology of this behavior remains unclear in most cases. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Evoked potentials recorded during routine EEG predict outcome after perinatal asphyxia.

PubMed

Nevalainen, Päivi; Marchi, Viviana; Metsäranta, Marjo; Lönnqvist, Tuula; Toiviainen-Salo, Sanna; Vanhatalo, Sampsa; Lauronen, Leena

2017-07-01

To evaluate the added value of somatosensory (SEPs) and visual evoked potentials (VEPs) recorded simultaneously with routine EEG in early outcome prediction of newborns with hypoxic-ischemic encephalopathy under modern intensive care. We simultaneously recorded multichannel EEG, median nerve SEPs, and flash VEPs during the first few postnatal days in 50 term newborns with hypoxic-ischemic encephalopathy. EEG background was scored into five grades and the worst two grades were considered to indicate poor cerebral recovery. Evoked potentials were classified as absent or present. Clinical outcome was determined from the medical records at a median age of 21months. Unfavorable outcome included cerebral palsy, severe mental retardation, severe epilepsy, or death. The accuracy of outcome prediction was 98% with SEPs compared to 90% with EEG. EEG alone always predicted unfavorable outcome when it was inactive (n=9), and favorable outcome when it was normal or only mildly abnormal (n=17). However, newborns with moderate or severe EEG background abnormality could have either favorable or unfavorable outcome, which was correctly predicted by SEP in all but one newborn (accuracy in this subgroup 96%). Absent VEPs were always associated with an inactive EEG, and an unfavorable outcome. However, presence of VEPs did not guarantee a favorable outcome. SEPs accurately predict clinical outcomes in newborns with hypoxic-ischemic encephalopathy and improve the EEG-based prediction particularly in those newborns with severely or moderately abnormal EEG findings. SEPs should be added to routine EEG recordings for early bedside assessment of newborns with hypoxic-ischemic encephalopathy. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

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

Fast entrainment of human electroencephalogram to a theta-band photic flicker during successful memory encoding.

PubMed

Sato, Naoyuki

2013-01-01

Theta band power (4-8 Hz) in the scalp electroencephalogram (EEG) is thought to be stronger during memory encoding for subsequently remembered items than for forgotten items. According to simultaneous EEG-functional magnetic resonance imaging (fMRI) measurements, the memory-dependent EEG theta is associated with multiple regions of the brain. This suggests that the multiple regions cooperate with EEG theta synchronization during successful memory encoding. However, a question still remains: What kind of neural dynamic organizes such a memory-dependent global network? In this study, the modulation of the EEG theta entrainment property during successful encoding was hypothesized to lead to EEG theta synchronization among a distributed network. Then, a transient response of EEG theta to a theta-band photic flicker with a short duration was evaluated during memory encoding. In the results, flicker-induced EEG power increased and decreased with a time constant of several hundred milliseconds following the onset and the offset of the flicker, respectively. Importantly, the offset response of EEG power was found to be significantly decreased during successful encoding. Moreover, the offset response of the phase locking index was also found to associate with memory performance. According to computational simulations, the results are interpreted as a smaller time constant (i.e., faster response) of a driven harmonic oscillator rather than a change in the spontaneous oscillatory input. This suggests that the fast response of EEG theta forms a global EEG theta network among memory-related regions during successful encoding, and it contributes to a flexible formation of the network along the time course.

Real-time fMRI neurofeedback of the mediodorsal and anterior thalamus enhances correlation between thalamic BOLD activity and alpha EEG rhythm.

PubMed

Zotev, Vadim; Misaki, Masaya; Phillips, Raquel; Wong, Chung Ki; Bodurka, Jerzy

2018-02-01

Real-time fMRI neurofeedback (rtfMRI-nf) with simultaneous EEG allows volitional modulation of BOLD activity of target brain regions and investigation of related electrophysiological activity. We applied this approach to study correlations between thalamic BOLD activity and alpha EEG rhythm. Healthy volunteers in the experimental group (EG, n = 15) learned to upregulate BOLD activity of the target region consisting of the mediodorsal (MD) and anterior (AN) thalamic nuclei using rtfMRI-nf during retrieval of happy autobiographical memories. Healthy subjects in the control group (CG, n = 14) were provided with a sham feedback. The EG participants were able to significantly increase BOLD activities of the MD and AN. Functional connectivity between the MD and the inferior precuneus was significantly enhanced during the rtfMRI-nf task. Average individual changes in the occipital alpha EEG power significantly correlated with the average MD BOLD activity levels for the EG. Temporal correlations between the occipital alpha EEG power and BOLD activities of the MD and AN were significantly enhanced, during the rtfMRI-nf task, for the EG compared to the CG. Temporal correlations with the alpha power were also significantly enhanced for the posterior nodes of the default mode network, including the precuneus/posterior cingulate, and for the dorsal striatum. Our findings suggest that the temporal correlation between the MD BOLD activity and posterior alpha EEG power is modulated by the interaction between the MD and the inferior precuneus, reflected in their functional connectivity. Our results demonstrate the potential of the rtfMRI-nf with simultaneous EEG for noninvasive neuromodulation studies of human brain function. © 2017 Wiley Periodicals, Inc.

Resting-state sensorimotor rhythm (SMR) power predicts the ability to up-regulate SMR in an EEG-instrumental conditioning paradigm.

PubMed

Reichert, Johanna Louise; Kober, Silvia Erika; Neuper, Christa; Wood, Guilherme

2015-11-01

Instrumental conditioning of EEG activity (EEG-IC) is a promising method for improvement and rehabilitation of cognitive functions. However, it has been found that even healthy adults are not always able to learn how to regulate their brain activity during EEG-IC. In the present study, the role of a neurophysiological predictor of EEG-IC learning performance, the resting-state power of sensorimotor rhythm (rs-SMR, 12-15Hz), was investigated. Eyes-open and eyes-closed rs-SMR power was assessed before N=28 healthy adults underwent 10 training sessions of instrumental SMR conditioning (ISC), in which participants should learn to voluntarily increase their SMR power by means of audio-visual feedback. A control group of N=19 participants received gamma (40-43Hz) or sham EEG-IC. N=19 of the ISC participants could be classified as "responders" as they were able to increase SMR power during training sessions, while N=9 participants ("non-responders") were not able to increase SMR power. Rs-SMR power in responders before start of ISC was higher in widespread parieto-occipital areas than in non-responders. A discriminant analysis indicated that eyes-open rs-SMR power in a central brain region specifically predicted later ISC performance, but not an increase of SMR in the control group. Together, these findings indicate that rs-SMR power is a specific and easy-to-measure predictor of later ISC learning performance. The assessment of factors that influence the ability to regulate brain activity is of high relevance, as it could be used to avoid potentially frustrating and expensive EEG-IC training sessions for participants who have a low chance of success. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Single-trial EEG-informed fMRI reveals spatial dependency of BOLD signal on early and late IC-ERP amplitudes during face recognition.

PubMed

Wirsich, Jonathan; Bénar, Christian; Ranjeva, Jean-Philippe; Descoins, Médéric; Soulier, Elisabeth; Le Troter, Arnaud; Confort-Gouny, Sylviane; Liégeois-Chauvel, Catherine; Guye, Maxime

2014-10-15

Simultaneous EEG-fMRI has opened up new avenues for improving the spatio-temporal resolution of functional brain studies. However, this method usually suffers from poor EEG quality, especially for evoked potentials (ERPs), due to specific artifacts. As such, the use of EEG-informed fMRI analysis in the context of cognitive studies has particularly focused on optimizing narrow ERP time windows of interest, which ignores the rich diverse temporal information of the EEG signal. Here, we propose to use simultaneous EEG-fMRI to investigate the neural cascade occurring during face recognition in 14 healthy volunteers by using the successive ERP peaks recorded during the cognitive part of this process. N170, N400 and P600 peaks, commonly associated with face recognition, were successfully and reproducibly identified for each trial and each subject by using a group independent component analysis (ICA). For the first time we use this group ICA to extract several independent components (IC) corresponding to the sequence of activation and used single-trial peaks as modulation parameters in a general linear model (GLM) of fMRI data. We obtained an occipital-temporal-frontal stream of BOLD signal modulation, in accordance with the three successive IC-ERPs providing an unprecedented spatio-temporal characterization of the whole cognitive process as defined by BOLD signal modulation. By using this approach, the pattern of EEG-informed BOLD modulation provided improved characterization of the network involved than the fMRI-only analysis or the source reconstruction of the three ERPs; the latter techniques showing only two regions in common localized in the occipital lobe. Copyright © 2014 Elsevier Inc. All rights reserved.

Occurrence of epileptiform discharges and sleep during EEG recordings in children after melatonin intake versus sleep-deprivation.

PubMed

Gustafsson, Greta; Broström, Anders; Ulander, Martin; Vrethem, Magnus; Svanborg, Eva

2015-08-01

To determine if melatonin is equally efficient as partial sleep deprivation in inducing sleep without interfering with epileptiform discharges in EEG recordings in children 1-16 years old. We retrospectively analysed 129 EEGs recorded after melatonin intake and 113 EEGs recorded after partial sleep deprivation. Comparisons were made concerning occurrence of epileptiform discharges, the number of children who fell asleep and the technical quality of EEG recordings. Comparison between different age groups was also made. No significant differences were found regarding occurrence of epileptiform discharges (33% after melatonin intake, 36% after sleep deprivation), or proportion of unsuccessful EEGs (8% and 10%, respectively). Melatonin and sleep deprivation were equally efficient in inducing sleep (70% in both groups). Significantly more children aged 1-4 years obtained sleep after melatonin intake in comparison to sleep deprivation (82% vs. 58%, p⩽0.01), and in comparison to older children with melatonin induced sleep (58-67%, p⩽0.05). Sleep deprived children 9-12 years old had higher percentage of epileptiform discharges (62%, p⩽0.05) compared to younger sleep deprived children. Melatonin is equally efficient as partial sleep deprivation to induce sleep and does not affect the occurrence of epileptiform discharges in the EEG recording. Sleep deprivation could still be preferable in older children as melatonin probably has less sleep inducing effect. Melatonin induced sleep have advantages, especially in younger children as they fall asleep easier than after sleep deprivation. The procedure is easier for the parents than keeping a young child awake for half the night. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Interactive effects of age and gender on EEG power and coherence during a short-term memory task in middle-aged adults.

PubMed

Kober, Silvia Erika; Reichert, Johanna Louise; Neuper, Christa; Wood, Guilherme

2016-04-01

The effects of age and gender on electroencephalographic (EEG) activity during a short-term memory task were assessed in a group of 40 healthy participants aged 22-63 years. Multi-channel EEG was recorded in 20 younger (mean = 24.65-year-old, 10 male) and 20 middle-aged participants (mean = 46.40-year-old, 10 male) during performance of a Sternberg task. EEG power and coherence measures were analyzed in different frequency bands. Significant interactions emerged between age and gender in memory performance and concomitant EEG parameters, suggesting that the aging process differentially influences men and women. Middle-aged women showed a lower short-term memory performance compared to young women, which was accompanied by decreasing delta and theta power and increasing brain connectivity with age in women. In contrast, men showed no age-related decline in short-term memory performance and no changes in EEG parameters. These results provide first evidence of age-related alterations in EEG activity underlying memory processes, which were already evident in the middle years of life in women but not in men. Copyright © 2016 Elsevier Inc. All rights reserved.

Meanings of Waves: Electroencephalography and Society in Mexico City, 1940-1950.

PubMed

Pérez, Nuria Valverde

2016-12-01

Argument This paper focuses on the uses of electroencephalograms (EEGs) in Mexico during their introductory decade from 1940 to 1950. Following Borck (2006), I argue that EEGs adapted to fit local circumstances and that this adjustment led to the consolidation of different ways of making science and the emergence of new objects of study and social types. I also maintain that the way EEGs were introduced into the institutional networks of Mexico entangled them in discussions about the objective and juridical definitions of social groups, thereby preempting concerns about their technical and epistemic limitations. This ultimately enabled the use of EEGs as normative machines and dispositifs. To this end, the paper follows the arrival of EEGs and the creation of institutional networks then analyzes the extent to which the styles of thinking behind the uses of EEGs and attempts to reify a notion of normal electrical brain behavior-particularly by applying EEGs to a community of Otomí Indians-correlated with the difficulties of defining the socio-anthropological notions that articulated legal and disciplinary projects of the time. Finally, it unveils the shortcomings of alternative attempts to define a brain model and to resist the production of ontological determinations.

Ballistocardiogram Artifact Removal with a Reference Layer and Standard EEG Cap

PubMed Central

Luo, Qingfei; Huang, Xiaoshan; Glover, Gary H.

2014-01-01

Background In simultaneous EEG-fMRI, the EEG recordings are severely contaminated by ballistocardiogram (BCG) artifacts, which are caused by cardiac pulsations. To reconstruct and remove the BCG artifacts, one promising method is to measure the artifacts in the absence of EEG signal by placing a group of electrodes (BCG electrodes) on a conductive layer (reference layer) insulated from the scalp. However, current BCG reference layer (BRL) methods either use a customized EEG cap composed of electrode pairs, or need to construct the custom reference layer through additional model-building experiments for each EEG-fMRI experiment. These requirements have limited the versatility and efficiency of BRL. The aim of this study is to propose a more practical and efficient BRL method and compare its performance with the most popular BCG removal method, the optimal basis sets (OBS) algorithm. New Method By designing the reference layer as a permanent and reusable cap, the new BRL method is able to be used with a standard EEG cap, and no extra experiments and preparations are needed to use the BRL in an EEG-fMRI experiment. Results The BRL method effectively removed the BCG artifacts from both oscillatory and evoked potential scalp recordings and recovered the EEG signal. Comparison with Existing Method Compared to the OBS, this new BRL method improved the contrast-to-noise ratios of the alpha-wave, visual, and auditory evoked potential signals by 101%, 76%, and 75% respectively, employing 160 BCG electrodes. Using only 20 BCG electrodes, the BRL improved the EEG signal by 74%/26%/41% respectively. Conclusion The proposed method can substantially improve the EEG signal quality compared with traditional methods. PMID:24960423

Using recurrence plot for determinism analysis of EEG recordings in genetic absence epilepsy rats.

PubMed

Ouyang, Gaoxiang; Li, Xiaoli; Dang, Chuangyin; Richards, Douglas A

2008-08-01

Understanding the transition of brain activity towards an absence seizure is a challenging task. In this paper, we use recurrence quantification analysis to indicate the deterministic dynamics of EEG series at the seizure-free, pre-seizure and seizure states in genetic absence epilepsy rats. The determinism measure, DET, based on recurrence plot, was applied to analyse these three EEG datasets, each dataset containing 300 single-channel EEG epochs of 5-s duration. Then, statistical analysis of the DET values in each dataset was carried out to determine whether their distributions over the three groups were significantly different. Furthermore, a surrogate technique was applied to calculate the significance level of determinism measures in EEG recordings. The mean (+/-SD) DET of EEG was 0.177+/-0.045 in pre-seizure intervals. The DET values of pre-seizure EEG data are significantly higher than those of seizure-free intervals, 0.123+/-0.023, (P<0.01), but lower than those of seizure intervals, 0.392+/-0.110, (P<0.01). Using surrogate data methods, the significance of determinism in EEG epochs was present in 25 of 300 (8.3%), 181 of 300 (60.3%) and 289 of 300 (96.3%) in seizure-free, pre-seizure and seizure intervals, respectively. Results provide some first indications that EEG epochs during pre-seizure intervals exhibit a higher degree of determinism than seizure-free EEG epochs, but lower than those in seizure EEG epochs in absence epilepsy. The proposed methods have the potential of detecting the transition between normal brain activity and the absence seizure state, thus opening up the possibility of intervention, whether electrical or pharmacological, to prevent the oncoming seizure.

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

PubMed

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

2016-10-01

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

Seizure clusters and adverse events during pre-surgical video-EEG monitoring with a slow anti-epileptic drug (AED) taper.

PubMed

Di Gennaro, Giancarlo; Picardi, Angelo; Sparano, Antonio; Mascia, Addolorata; Meldolesi, Giulio N; Grammaldo, Liliana G; Esposito, Vincenzo; Quarato, Pier P

2012-03-01

To evaluate the efficiency and safety of pre-surgical video-EEG monitoring with a slow anti-epileptic drug (AED) taper and a rescue benzodiazepine protocol. Fifty-four consecutive patients with refractory focal epilepsy who underwent pre-surgical video-electroencephalography (EEG) monitoring during the year 2010 were included in the study. Time to first seizure, duration of monitoring, incidence of 4-h and 24-h seizure clustering, secondarily generalised tonic-clonic seizures (sGTCS), status epilepticus, falls and cardiac asystole were evaluated. A total of 190 seizures were recorded. Six (11%) patients had 4-h clusters and 21 (39%) patients had 24-h clusters. While 15 sGTCS were recorded in 14 patients (26%), status epilepticus did not occur and no seizure was complicated with cardiac asystole. Epileptic falls with no significant injuries occurred in three patients. The mean time to first seizure was 3.3days and the time to conclude video-EEG monitoring averaged 6days. Seizure clustering was common during pre-surgical video-EEG monitoring, although serious adverse events were rare with a slow AED tapering and a rescue benzodiazepine protocol. Slow AED taper pre-surgical video-EEG monitoring is fairly safe when performed in a highly specialised and supervised hospital setting. Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Automatic interpretation and writing report of the adult waking electroencephalogram.

PubMed

Shibasaki, Hiroshi; Nakamura, Masatoshi; Sugi, Takenao; Nishida, Shigeto; Nagamine, Takashi; Ikeda, Akio

2014-06-01

Automatic interpretation of the EEG has so far been faced with significant difficulties because of a large amount of spatial as well as temporal information contained in the EEG, continuous fluctuation of the background activity depending on changes in the subject's vigilance and attention level, the occurrence of paroxysmal activities such as spikes and spike-and-slow-waves, contamination of the EEG with a variety of artefacts and the use of different recording electrodes and montages. Therefore, previous attempts of automatic EEG interpretation have been focussed only on a specific EEG feature such as paroxysmal abnormalities, delta waves, sleep stages and artefact detection. As a result of a long-standing cooperation between clinical neurophysiologists and system engineers, we report for the first time on a comprehensive, computer-assisted, automatic interpretation of the adult waking EEG. This system analyses the background activity, intermittent abnormalities, artefacts and the level of vigilance and attention of the subject, and automatically presents its report in written form. Besides, it also detects paroxysmal abnormalities and evaluates the effects of intermittent photic stimulation and hyperventilation on the EEG. This system of automatic EEG interpretation was formed by adopting the strategy that the qualified EEGers employ for the systematic visual inspection. This system can be used as a supplementary tool for the EEGer's visual inspection, and for educating EEG trainees and EEG technicians. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Diffusion spectral imaging modules correlate with EEG LORETA neuroimaging modules.

PubMed

Thatcher, Robert W; North, Duane M; Biver, Carl J

2012-05-01

The purpose of this study was to test the hypothesis that the highest temporal correlations between 3-dimensional EEG current source density corresponds to anatomical Modules of high synaptic connectivity. Eyes closed and eyes open EEG was recorded from 19 scalp locations with a linked ears reference from 71 subjects age 13-42 years. LORETA was computed from 1 to 30 Hz in 2,394 cortical gray matter voxels that were grouped into six anatomical Modules corresponding to the ROIs in the Hagmann et al.'s [2008] diffusion spectral imaging (DSI) study. All possible cross-correlations between voxels within a DSI Module were compared with the correlations between Modules. The Hagmann et al. [ 2008] Module correlation structure was replicated in the correlation structure of EEG three-dimensional current source density. EEG Temporal correlation between brain regions is related to synaptic density as measured by diffusion spectral imaging. Copyright © 2011 Wiley-Liss, Inc.

Attachment classification, psychophysiology and frontal EEG asymmetry across the lifespan: a review

PubMed Central

Gander, Manuela; Buchheim, Anna

2015-01-01

In recent years research on physiological response and frontal electroencephalographic (EEG) asymmetry in different patterns of infant and adult attachment has increased. We review research findings regarding associations between attachment classifications and frontal EEG asymmetry, the autonomic nervous system (ANS) and the hypothalamic-pituitary-adrenocortical axis (HPA). Studies indicate that insecure attachment is related to a heightened adrenocortical activity, heart rate and skin conductance in response to stress, which is consistent with the hypothesis that attachment insecurity leads to impaired emotion regulation. Research on frontal EEG asymmetry also shows a clear difference in the emotional arousal between the attachment groups evidenced by specific frontal asymmetry changes. Furthermore, we discuss neurophysiological evidence of attachment organization and present up-to-date findings of EEG-research with adults. Based on the overall patterns of results presented in this article we identify some major areas of interest and directions for future research. PMID:25745393

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.

Predicting Clinical Gains and Side Effects of Stimulant Medication in Pediatric Attention-Deficit/Hyperactivity Disorder by Combining Measures From qEEG and ERPs in a Cued GO/NOGO Task.

PubMed

Ogrim, Geir; Kropotov, Juri D

2018-06-01

The study aim was to develop 2 scales: predicting clinical gains and risk of acute side effects of stimulant medication in pediatric attention-deficit/hyperactivity disorder (ADHD), combining measures from EEG spectra, event-related potentials (ERPs), and a cued visual GO/NOGO task. Based on 4-week systematic medication trials, 87 ADHD patients aged 8 to 17 years were classified as responders (REs, n = 62) or non-REs (n = 25), and belonging to the side effects (SEs, n = 42) or no-SEs (n = 45) groups. Before starting the trial, a 19-channel EEG was registered twice: Test 1 (T1) without medication and T2 on a single dose of stimulant medication a few days before the trial. EEG was registered T1 and T2: 3 minutes eyes-closed, 3 minutes eyes-open, and 20 minutes cued GO/NOGO. EEG spectra, ERPs, omissions, commissions, reaction time (RT), and RT variability were computed. Groups were compared at T1 and T2 on quantitative EEG (qEEG), ERPs and behavioral parameters; effect sizes ( d) were estimated. Variables with d > 0.5 were converted to quartiles, multiplied by corresponding d, and summed to obtain 2 global scales. Six variables differed significantly between REs and non-REs (T1: theta/alpha ratio, P3NOGO amplitude. Differences T2-T1: Omissions, RT variability, P3NOGO, contingent negative variation [CNV]). The global scale d was 1.86. Accuracy (receiver operating characteristic) was 0.92. SEs and no-SEs differed significantly on 4 variables. (T1: RT, T2: novelty component and alpha peak frequency, and RT changes. Global scale d = 1.08 and accuracy = 0.78. Gains and side effects of stimulants in pediatric ADHD can be predicted with high accuracy by combining EEG spectra, ERPs, and behavior from baseline and single-dose tests. ClinicalTrials.gov identifier: NCT02695355.

Resting State EEG in Children With Learning Disabilities: An Independent Component Analysis Approach.

PubMed

Jäncke, Lutz; Alahmadi, Nsreen

2016-01-01

In this study, the neurophysiological underpinnings of learning disabilities (LD) in children are examined using resting state EEG. We were particularly interested in the neurophysiological differences between children with learning disabilities not otherwise specified (LD-NOS), learning disabilities with verbal disabilities (LD-Verbal), and healthy control (HC) children. We applied 2 different approaches to examine the differences between the different groups. First, we calculated theta/beta and theta/alpha ratios in order to quantify the relationship between slow and fast EEG oscillations. Second, we used a recently developed method for analyzing spectral EEG, namely the group independent component analysis (gICA) model. Using these measures, we identified substantial differences between LD and HC children and between LD-NOS and LD-Verbal children in terms of their spectral EEG profiles. We obtained the following findings: (a) theta/beta and theta/alpha ratios were substantially larger in LD than in HC children, with no difference between LD-NOS and LD-Verbal children; (b) there was substantial slowing of EEG oscillations, especially for gICs located in frontal scalp positions, with LD-NOS children demonstrating the strongest slowing; (c) the estimated intracortical sources of these gICs were mostly located in brain areas involved in the control of executive functions, attention, planning, and language; and (d) the LD-Verbal children demonstrated substantial differences in EEG oscillations compared with LD-NOS children, and these differences were localized in language-related brain areas. The general pattern of atypical neurophysiological activation found in LD children suggests that they suffer from neurophysiological dysfunction in brain areas involved with the control of attention, executive functions, planning, and language functions. LD-Verbal children also demonstrate atypical activation, especially in language-related brain areas. These atypical neurophysiological activation patterns might provide a helpful guide for rehabilitation strategies to treat the deficiencies in these children with LD. © EEG and Clinical Neuroscience Society (ECNS) 2015.

Single Trial EEG Patterns for the Prediction of Individual Differences in Fluid Intelligence.

PubMed

Qazi, Emad-Ul-Haq; Hussain, Muhammad; Aboalsamh, Hatim; Malik, Aamir Saeed; Amin, Hafeez Ullah; Bamatraf, Saeed

2016-01-01

Assessing a person's intelligence level is required in many situations, such as career counseling and clinical applications. EEG evoked potentials in oddball task and fluid intelligence score are correlated because both reflect the cognitive processing and attention. A system for prediction of an individual's fluid intelligence level using single trial Electroencephalography (EEG) signals has been proposed. For this purpose, we employed 2D and 3D contents and 34 subjects each for 2D and 3D, which were divided into low-ability (LA) and high-ability (HA) groups using Raven's Advanced Progressive Matrices (RAPM) test. Using visual oddball cognitive task, neural activity of each group was measured and analyzed over three midline electrodes (Fz, Cz, and Pz). To predict whether an individual belongs to LA or HA group, features were extracted using wavelet decomposition of EEG signals recorded in visual oddball task and support vector machine (SVM) was used as a classifier. Two different types of Haar wavelet transform based features have been extracted from the band (0.3 to 30 Hz) of EEG signals. Statistical wavelet features and wavelet coefficient features from the frequency bands 0.0-1.875 Hz (delta low) and 1.875-3.75 Hz (delta high), resulted in the 100 and 98% prediction accuracies, respectively, both for 2D and 3D contents. The analysis of these frequency bands showed clear difference between LA and HA groups. Further, discriminative values of the features have been validated using statistical significance tests and inter-class and intra-class variation analysis. Also, statistical test showed that there was no effect of 2D and 3D content on the assessment of fluid intelligence level. Comparisons with state-of-the-art techniques showed the superiority of the proposed system.

[The evaluation of patients with ischemic cerebral lesions by CT, SPECT and qEEG in acute, subacute and chronic phases].

PubMed

Sánchez-Chávez, J J; Barroso, E; Cubero, L; González-González, J; Farach, M

1998-08-01

SPECT, EEG AND CT scan offer information with several pathophysiologic meanings. Their results vary with time and according to the vascular affected territory. We wanted to study how the sensibility varies and the relationship with the clinic of SPECT, qEEG and CT scan in the acute, subacute and chronic stages and according to the vascular affected territory. We also wanted to analyze the several pathophysiologic aspects of the cerebral ischemia. Thirty-six patients with symptoms of hemispheric stroke were evaluated with CT scan, qEEG, SPECT99mTc-HMPAO during the acute (0-5 days), subacute (0-15 days) and chronic (16 days to 1 year) stages. The decrease of ipsilateral CBF depend on the time (p = 0.0061), being not very frequent during the two first weeks. The qEEG was the most sensitive study in the first phase, its sensibility did not depend on the vascular affected territory and was dependent on the time (p = 0.0011), diminishing in the chronic phase. The slow activity was habitually ipsilateral. The CT scan was the less sensitive study. After 24 hours and until the second week, there is habitually an increase of the ipsilateral rCBF. The luxury perfusion could explain the fogging effect in the CT scan. The slow activity of the qEEG represents the alteration of the oxygen metabolism. The interpretation of the variation of the CBF and the qEEG allow us to define oligemia of the ischemia and between reactive hyperemia and the increase of CBF due to the necrotic tissue.

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

PubMed Central

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

2016-01-01

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

Performance and brain electrical activity during prolonged confinement.

PubMed

Lorenz, B; Lorenz, J; Manzey, D

1996-01-01

A subset of the AGARD-STRES battery including memory search, unstable tracking, and a combination of both tasks (dual-task), was applied repeatedly to the four chamber crew members before, during, and after the 60-day isolation period of EXEMSI. Five ground control group members served as a control group. A subjective state questionnaire was also included. The results were subjected to a quantitative single-subject analysis. Electroencephalograms (EEG) were recorded to permit correlation of changes in task performance with changes in the physiological state. Evaluation of the EEG focused on spectral parameters of spontaneous EEG waves. No physiological data were collected from the control group. Significant decrements in tracking ability were observed in the chamber crew. The time course of these effects followed a triphasic pattern with initial deterioration, intermediate recovery to pre-isolation baseline scores after the first half of the isolation period, and a second deterioration towards the end. None of the control group subjects displayed such an effect. Memory search (speed and accuracy) was only occasionally impaired during isolation, but the control group displayed a similar pattern of changes. It is suggested that a state of decreased alertness causes tracking deterioration, which leads to a reduced efficiency of sustained cue utilization. The assumption of low alertness was further substantiated by higher fatigue ratings by the chamber crew compared to those of the control group. Analysis of the continuous EEG recordings revealed that only two subjects produced reliable alpha wave activity (8-12 Hz) over Pz and, to a much smaller extent, Fz-theta wave activity (5-7 Hz) during task performance. In both subjects Pz-alpha power decreased consistently under task conditions involving single-task and dual-task tracking. Fz-theta activity was increased more by single-task and dual-task memory search than by single-task tracking. The alpha attenuation appears to be associated with an increasing demand on perceptual cue utilization required by the tracking performance. In one subject marked attenuation of alpha power occurred during the first half of the confinement period, where he also scored the highest fatigue ratings. A striking increase in fronto-central theta activity was observed in the same subject after six weeks of isolation. The change was associated with an efficient rather than a degraded task performance, and a high rating of the item "concentrated" and a low rating of the item "fatigued." This finding supports the hypothesis that the activation state associated with increased fronto-central theta activity accompanies efficient performance of demanding mental tasks. The usefulness of standardized laboratory tasks as monitoring instruments is demonstrated by the direct comparability with results of studies obtained from other relevant research applications using the same tasks. The feasibility of a self-administered integrated psychophysiological assessment of the individual state was illustrated by the nearly complete collection of data. The large number of individual data collected over the entire period permitted application of quantitative single-subject analysis, allowing reliable determination of changes in the individual state in the course of time. It thus appears that this assessment technique can be adapted for in-flight monitoring of astronauts during prolonged spaceflights. Parallel EEG recording can provide relevant supplementary information for diagnosing the individual activation state associated with task performance. The existence of large individual differences in the generation of task-sensitive EEG rhythms forms an important issue for further studies.

Automatic removal of eye-movement and blink artifacts from EEG signals.

PubMed

Gao, Jun Feng; Yang, Yong; Lin, Pan; Wang, Pei; Zheng, Chong Xun

2010-03-01

Frequent occurrence of electrooculography (EOG) artifacts leads to serious problems in interpreting and analyzing the electroencephalogram (EEG). In this paper, a robust method is presented to automatically eliminate eye-movement and eye-blink artifacts from EEG signals. Independent Component Analysis (ICA) is used to decompose EEG signals into independent components. Moreover, the features of topographies and power spectral densities of those components are extracted to identify eye-movement artifact components, and a support vector machine (SVM) classifier is adopted because it has higher performance than several other classifiers. The classification results show that feature-extraction methods are unsuitable for identifying eye-blink artifact components, and then a novel peak detection algorithm of independent component (PDAIC) is proposed to identify eye-blink artifact components. Finally, the artifact removal method proposed here is evaluated by the comparisons of EEG data before and after artifact removal. The results indicate that the method proposed could remove EOG artifacts effectively from EEG signals with little distortion of the underlying brain signals.

[Temporary disappearance of EEG activity during reversible respiratory failure in rabbits and cats].

PubMed

Jurco, M; Tomori, Z; Tkácová, R; Calfa, J

1989-02-01

The dynamics of changes of EEG activity was studied on the model of reversible respiratory failure in rabbits and cats in pentobarbital anesthesia. During N2 inhalation, apnea of 60 second duration, and subsequent resuscitation the electrocorticogram in bifrontal and bioccipital connection was recorded. Evaluation of 19 episodes of apnea in 7 rabbits and of 25 episodes in 8 cats yielded the following results: 1. During hyperventilation induced by N2 inhalation a certain activation of the EEG was observed (spindles more pronounced, increased occurrence rate of discharges of the reticular activation system). 2. At the onset of apnea the EEG was still distinct, suggesting that primary apnea is presumably not caused by anoxia and the accompanying electric silence of the structures that control respiration. 3. Disappearance of EEG occurred within 50 seconds from the onset of apnea in rabbits and within 30 seconds in cats. 4. After repeated episodes of apnea lasting for 60 sec., artificial ventilation mostly resulted in normalization of EEG.

Music training is associated with cortical synchronization reflected in EEG coherence during verbal memory encoding.

PubMed

Cheung, Mei-Chun; Chan, Agnes S; Liu, Ying; Law, Derry; Wong, Christina W Y

2017-01-01

Music training can improve cognitive functions. Previous studies have shown that children and adults with music training demonstrate better verbal learning and memory performance than those without such training. Although prior studies have shown an association between music training and changes in the structural and functional organization of the brain, there is no concrete evidence of the underlying neural correlates of the verbal memory encoding phase involved in such enhanced memory performance. Therefore, we carried out an electroencephalography (EEG) study to investigate how music training was associated with brain activity during the verbal memory encoding phase. Sixty participants were recruited, 30 of whom had received music training for at least one year (the MT group) and 30 of whom had never received music training (the NMT group). The participants in the two groups were matched for age, education, gender distribution, and cognitive capability. Their verbal and visual memory functions were assessed using standardized neuropsychological tests and EEG was used to record their brain activity during the verbal memory encoding phase. Consistent with previous studies, the MT group demonstrated better verbal memory than the NMT group during both the learning and the delayed recall trials in the paper-and-pencil tests. The MT group also exhibited greater learning capacity during the learning trials. Compared with the NMT group, the MT group showed an increase in long-range left and right intrahemispheric EEG coherence in the theta frequency band during the verbal memory encoding phase. In addition, their event-related left intrahemispheric theta coherence was positively associated with subsequent verbal memory performance as measured by discrimination scores. These results suggest that music training may modulate the cortical synchronization of the neural networks involved in verbal memory formation.

Music training is associated with cortical synchronization reflected in EEG coherence during verbal memory encoding

PubMed Central

Cheung, Mei-chun; Chan, Agnes S.; Liu, Ying; Law, Derry; Wong, Christina W. Y.

2017-01-01

Music training can improve cognitive functions. Previous studies have shown that children and adults with music training demonstrate better verbal learning and memory performance than those without such training. Although prior studies have shown an association between music training and changes in the structural and functional organization of the brain, there is no concrete evidence of the underlying neural correlates of the verbal memory encoding phase involved in such enhanced memory performance. Therefore, we carried out an electroencephalography (EEG) study to investigate how music training was associated with brain activity during the verbal memory encoding phase. Sixty participants were recruited, 30 of whom had received music training for at least one year (the MT group) and 30 of whom had never received music training (the NMT group). The participants in the two groups were matched for age, education, gender distribution, and cognitive capability. Their verbal and visual memory functions were assessed using standardized neuropsychological tests and EEG was used to record their brain activity during the verbal memory encoding phase. Consistent with previous studies, the MT group demonstrated better verbal memory than the NMT group during both the learning and the delayed recall trials in the paper-and-pencil tests. The MT group also exhibited greater learning capacity during the learning trials. Compared with the NMT group, the MT group showed an increase in long-range left and right intrahemispheric EEG coherence in the theta frequency band during the verbal memory encoding phase. In addition, their event-related left intrahemispheric theta coherence was positively associated with subsequent verbal memory performance as measured by discrimination scores. These results suggest that music training may modulate the cortical synchronization of the neural networks involved in verbal memory formation. PMID:28358852

A simple method for EEG guided transcranial electrical stimulation without models.

PubMed

Cancelli, Andrea; Cottone, Carlo; Tecchio, Franca; Truong, Dennis Q; Dmochowski, Jacek; Bikson, Marom

2016-06-01

There is longstanding interest in using EEG measurements to inform transcranial Electrical Stimulation (tES) but adoption is lacking because users need a simple and adaptable recipe. The conventional approach is to use anatomical head-models for both source localization (the EEG inverse problem) and current flow modeling (the tES forward model), but this approach is computationally demanding, requires an anatomical MRI, and strict assumptions about the target brain regions. We evaluate techniques whereby tES dose is derived from EEG without the need for an anatomical head model, target assumptions, difficult case-by-case conjecture, or many stimulation electrodes. We developed a simple two-step approach to EEG-guided tES that based on the topography of the EEG: (1) selects locations to be used for stimulation; (2) determines current applied to each electrode. Each step is performed based solely on the EEG with no need for head models or source localization. Cortical dipoles represent idealized brain targets. EEG-guided tES strategies are verified using a finite element method simulation of the EEG generated by a dipole, oriented either tangential or radial to the scalp surface, and then simulating the tES-generated electric field produced by each model-free technique. These model-free approaches are compared to a 'gold standard' numerically optimized dose of tES that assumes perfect understanding of the dipole location and head anatomy. We vary the number of electrodes from a few to over three hundred, with focality or intensity as optimization criterion. Model-free approaches evaluated include (1) voltage-to-voltage, (2) voltage-to-current; (3) Laplacian; and two Ad-Hoc techniques (4) dipole sink-to-sink; and (5) sink to concentric. Our results demonstrate that simple ad hoc approaches can achieve reasonable targeting for the case of a cortical dipole, remarkably with only 2-8 electrodes and no need for a model of the head. Our approach is verified directly only for a theoretically localized source, but may be potentially applied to an arbitrary EEG topography. For its simplicity and linearity, our recipe for model-free EEG guided tES lends itself to broad adoption and can be applied to static (tDCS), time-variant (e.g., tACS, tRNS, tPCS), or closed-loop tES.

A simple method for EEG guided transcranial electrical stimulation without models

NASA Astrophysics Data System (ADS)

Cancelli, Andrea; Cottone, Carlo; Tecchio, Franca; Truong, Dennis Q.; Dmochowski, Jacek; Bikson, Marom

2016-06-01

Objective. There is longstanding interest in using EEG measurements to inform transcranial Electrical Stimulation (tES) but adoption is lacking because users need a simple and adaptable recipe. The conventional approach is to use anatomical head-models for both source localization (the EEG inverse problem) and current flow modeling (the tES forward model), but this approach is computationally demanding, requires an anatomical MRI, and strict assumptions about the target brain regions. We evaluate techniques whereby tES dose is derived from EEG without the need for an anatomical head model, target assumptions, difficult case-by-case conjecture, or many stimulation electrodes. Approach. We developed a simple two-step approach to EEG-guided tES that based on the topography of the EEG: (1) selects locations to be used for stimulation; (2) determines current applied to each electrode. Each step is performed based solely on the EEG with no need for head models or source localization. Cortical dipoles represent idealized brain targets. EEG-guided tES strategies are verified using a finite element method simulation of the EEG generated by a dipole, oriented either tangential or radial to the scalp surface, and then simulating the tES-generated electric field produced by each model-free technique. These model-free approaches are compared to a ‘gold standard’ numerically optimized dose of tES that assumes perfect understanding of the dipole location and head anatomy. We vary the number of electrodes from a few to over three hundred, with focality or intensity as optimization criterion. Main results. Model-free approaches evaluated include (1) voltage-to-voltage, (2) voltage-to-current; (3) Laplacian; and two Ad-Hoc techniques (4) dipole sink-to-sink; and (5) sink to concentric. Our results demonstrate that simple ad hoc approaches can achieve reasonable targeting for the case of a cortical dipole, remarkably with only 2-8 electrodes and no need for a model of the head. Significance. Our approach is verified directly only for a theoretically localized source, but may be potentially applied to an arbitrary EEG topography. For its simplicity and linearity, our recipe for model-free EEG guided tES lends itself to broad adoption and can be applied to static (tDCS), time-variant (e.g., tACS, tRNS, tPCS), or closed-loop tES.

Evaluation of EEG based determination of unconsciousness vs. loss of posture in broilers.

PubMed

Benson, E R; Alphin, R L; Rankin, M K; Caputo, M P; Kinney, C A; Johnson, A L

2012-10-01

Evaluation of the loss of consciousness in poultry is an essential component in evaluating bird welfare under a variety of situations and applications. Many current approaches to evaluating loss of consciousness are qualitative and require observation of the bird. This study outlines a quantitative method for determining the point at which a bird loses consciousness. In this study, commercial broilers were individually anesthetized and the brain activity recorded as the bird became unconscious. A wireless EEG transmitter was surgically implanted and the bird anesthetized after a 24-48 h recovery. Each bird was monitored during treatment with isoflurane anesthesia and EEG data was evaluated using a frequency based approach. The alpha/delta (A/D) ratio and loss of posture (LOP) were used to determine the point at which the birds went unconscious. There was no statistically significant difference between time to unconsciousness as measured by A/D ratio or LOP. Copyright © 2011 Elsevier Ltd. All rights reserved.

EEG, PET, SPET and MRI in intractable childhood epilepsies: possible surgical correlations.

PubMed

Fois, A; Farnetani, M A; Balestri, P; Buoni, S; Di Cosmo, G; Vattimo, A; Guazzelli, M; Guzzardi, R; Salvadori, P A

1995-12-01

Magnetic resonance imaging (MRI), single photon emission tomography (SPET), and positron emission tomography (PET) using [18F]fluorodeoxyglucose were used in combination with scalp and scalp-video EEGs in a group of 30 pediatric patients with drug resistant epilepsy (DRE) in order to identify patients who could benefit from neurosurgical approach. Seizures were classified according to the consensus criteria of The International League Against Epilepsy. In three patients infantile spasms (IS) were diagnosed; 13 subjects were affected by different types of generalized seizures, associated with complex partial seizures (CPS) in three. In the other 14 patients partial seizures, either simple (SPS) or complex, were present. A localized abnormality was demonstrated in one patient with IS and in three patients with generalized seizures. Of the group of 14 subjects with CPS, MRI and CT were normal in 7, but SPET or PET indicated focal hypoperfusion or hypometabolism concordant with the localization of the EEG abnormalities. In 5 of the other 7 patients anatomical and functional imaging and EEG findings were concordant for a localized abnormality. It can be concluded that functional imaging combined with scalp EEGs appears to be superior to the use of only CT and MRI for selecting children with epilepsy in whom a surgical approach can be considered, in particular when CPS resistant to therapy are present.

Establishment of a rhesus monkey model of chronic temporal lobe epilepsy using repetitive unilateral intra-amygdala kainic acid injections.

PubMed

Chi, Yajie; Wu, Bolin; Guan, Jianwei; Xiao, Kuntai; Lu, Ziming; Li, Xiao; Xu, Yuting; Xue, Shan; Xu, Qiang; Rao, Junhua; Guo, Yanwu

2017-09-01

Temporal lobe epilepsy (TLE) is a common type of acquired epilepsy refractory to medical treatment. As such, establishing animal models of this disease is critical to developing new and effective treatment modalities. Because of their small head size, rodents are not suitable for comprehensive electroencephalography (EEG) evaluation via scalp or subdural electrodes. Therefore, a larger primate model that closely recapitulates signs of TLE is needed; here we describe a rhesus monkey model resembling chronic TLE. Eight monkeys were divided into two groups: kainic acid (KA) group (n=6) and saline control group (n=2). Intra-amygdala KA injections were performed biweekly via an Ommaya device until obvious epileptiform discharges were recorded. Video-EEG recording was conducted intermittently throughout the experiment using both scalp and subdural electrodes. Brains were then analyzed for Nissl and glial fibrillary acid protein (GFAP) immunostaining. After 2-4 injections of KA (approximately 1.2-2.4mg, 0.12-0.24mg/kg), interictal epileptiform discharges (IEDs) were recorded in all KA-treated animals. Spontaneous recurrent seizures (SRSs) accompanied by symptoms mimicking temporal lobe absence (undetectable without EEG recording), but few mild motor signs, were recorded in 66.7% (four of six) KA-treated animals. Both IEDs and seizures indicated a primary epileptic zone in the right temporal region and contralateral discharges were later detected. Segmental pyramidal cell loss and gliosis were detected in the brain of a KA-treated monkey. Through a modified protocol of unilateral repetitive intra-amygdala KA injections, a rhesus monkey model with similar behavioral and brain electrical features as TLE was developed. Copyright © 2017 Elsevier Inc. All rights reserved.

Postictal in situ MRS brain lactate in the rat kindling model.

PubMed

Maton, B M; Najm, I M; Wang, Y; Lüders, H O; Ng, T C

1999-12-10

To determine the temporal and spatial extent of the lactate (Lact) changes as correlated with seizure characteristics and EEG changes in the rat kindling model. Prior studies using MRS have detected cerebral Lact postictally in animal models of seizures and in patients with intractable focal epilepsy. We performed MRS in sham control rats (n = 4) and in rats stimulated in the right hippocampus at two different stages of the kindling and at three time points after the seizures: <2 hours (n = 8 and 5, stage 0 and stage 5), 2 to 3 hours (n = 5 and 6), and >3 hours (n = 4 and 2). Lact/creatine (Cr) and N-acetylaspartate (NAA)/Cr ratios were measured in six contiguous voxels (three left, three right) covering the hippocampi, anterior and posterior regions, and compared with EEG and ictal behavior. Lact/Cr ratios were measured at a very low level in the sham control rats and in the >3-hour group. In the <2-hour group, Lact/Cr increase was higher in stage-5 rats as compared with stage-0 rats (p = 0.001, unpaired t-test) and sham control rats when all the voxels were considered. Lact/Cr ratios were higher in the stimulated area as compared with all other brain areas in stage-0 rats (p = 0.05, paired t-test) but not in the stage-5 rats. Similar results with more inter-animal variability were measured in the 2- to 3-hour group. NAA/Cr ratios increased significantly after stage-0 kindling in the stimulated hippocampus but not after stage-5 kindling. Postictal Lact increase as assayed by MRS correlates with EEG and behavioral seizures and suggests that it would be an additional noninvasive technique for seizure localization during the presurgical evaluation of patients with intractable focal epilepsy.

Portable wireless neurofeedback system of EEG alpha rhythm enhances memory.

PubMed

Wei, Ting-Ying; Chang, Da-Wei; Liu, You-De; Liu, Chen-Wei; Young, Chung-Ping; Liang, Sheng-Fu; Shaw, Fu-Zen

2017-11-13

Effect of neurofeedback training (NFT) on enhancement of cognitive function or amelioration of clinical symptoms is inconclusive. The trainability of brain rhythm using a neurofeedback system is uncertainty because various experimental designs are used in previous studies. The current study aimed to develop a portable wireless NFT system for alpha rhythm and to validate effect of the NFT system on memory with a sham-controlled group. The proposed system contained an EEG signal analysis device and a smartphone with wireless Bluetooth low-energy technology. Instantaneous 1-s EEG power and contiguous 5-min EEG power throughout the training were developed as feedback information. The training performance and its progression were kept to boost usability of our device. Participants were blinded and randomly assigned into either the control group receiving random 4-Hz power or Alpha group receiving 8-12-Hz power. Working memory and episodic memory were assessed by the backward digital span task and word-pair task, respectively. The portable neurofeedback system had advantages of a tiny size and long-term recording and demonstrated trainability of alpha rhythm in terms of significant increase of power and duration of 8-12 Hz. Moreover, accuracies of the backward digital span task and word-pair task showed significant enhancement in the Alpha group after training compared to the control group. Our tiny portable device demonstrated success trainability of alpha rhythm and enhanced two kinds of memories. The present study suggest that the portable neurofeedback system provides an alternative intervention for memory enhancement.

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

PubMed

Mumtaz, Wajid; Malik, Aamir Saeed

2018-06-02

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

Integration of an EEG biomarker with a clinician's ADHD evaluation

PubMed Central

Snyder, Steven M; Rugino, Thomas A; Hornig, Mady; Stein, Mark A

2015-01-01

Background This study is the first to evaluate an assessment aid for attention-deficit/hyperactivity disorder (ADHD) according to both Class-I evidence standards of American Academy of Neurology and De Novo requirements of US Food and Drug Administration. The assessment aid involves a method to integrate an electroencephalographic (EEG) biomarker, theta/beta ratio (TBR), with a clinician's ADHD evaluation. The integration method is intended as a step to help improve certainty with criterion E (i.e., whether symptoms are better explained by another condition). Methods To evaluate the assessment aid, investigators conducted a prospective, triple-blinded, 13-site, clinical cohort study. Comprehensive clinical evaluation data were obtained from 275 children and adolescents presenting with attentional and behavioral concerns. A qualified clinician at each site performed differential diagnosis. EEG was collected by separate teams. The reference standard was consensus diagnosis by an independent, multidisciplinary team (psychiatrist, psychologist, and neurodevelopmental pediatrician), which is well-suited to evaluate criterion E in a complex clinical population. Results Of 209 patients meeting ADHD criteria per a site clinician's judgment, 93 were separately found by the multidisciplinary team to be less likely to meet criterion E, implying possible overdiagnosis by clinicians in 34% of the total clinical sample (93/275). Of those 93, 91% were also identified by EEG, showing a relatively lower TBR (85/93). Further, the integration method was in 97% agreement with the multidisciplinary team in the resolution of a clinician's uncertain cases (35/36). TBR showed statistical power specific to supporting certainty of criterion E per the multidisciplinary team (Cohen's d, 1.53). Patients with relatively lower TBR were more likely to have other conditions that could affect criterion E certainty (10 significant results; P ≤ 0.05). Integration of this information with a clinician's ADHD evaluation could help improve diagnostic accuracy from 61% to 88%. Conclusions The EEG-based assessment aid may help improve accuracy of ADHD diagnosis by supporting greater criterion E certainty. PMID:25798338

Comparison of Medical and Consumer Wireless EEG Systems for Use in Clinical Trials.

PubMed

Ratti, Elena; Waninger, Shani; Berka, Chris; Ruffini, Giulio; Verma, Ajay

2017-01-01

Objectives: To compare quantitative EEG signal and test-retest reliability of medical grade and consumer EEG systems. Methods: Resting state EEG was acquired by two medical grade (B-Alert, Enobio) and two consumer (Muse, Mindwave) EEG systems in five healthy subjects during two study visits. EEG patterns, power spectral densities (PSDs) and test/retest reliability in eyes closed and eyes open conditions were compared across the four systems, focusing on Fp1, the only common electrode. Fp1 PSDs were obtained using Welch's modified periodogram method and averaged for the five subjects for each visit. The test/retest results were calculated as a ratio of Visit 1/Visit 2 Fp1 channel PSD at each 1 s epoch. Results: B-Alert, Enobio, and Mindwave Fp1 power spectra were similar. Muse showed a broadband increase in power spectra and the highest relative variation across test-retest acquisitions. Consumer systems were more prone to artifact due to eye blinks and muscle movement in the frontal region. Conclusions: EEG data can be successfully collected from all four systems tested. Although there was slightly more time required for application, medical systems offer clear advantages in data quality, reliability, and depth of analysis over the consumer systems. Significance: This evaluation provides evidence for informed selection of EEG systemsappropriate for clinical trials.

Intelligence measures and stage 2 sleep in typically-developing and autistic children.

PubMed

Tessier, Sophie; Lambert, Andréane; Chicoine, Marjolaine; Scherzer, Peter; Soulières, Isabelle; Godbout, Roger

2015-07-01

The relationship between intelligence measures and 2 EEG measures of non-rapid eye movement sleep, sleep spindles and Sigma activity, was examined in 13 typically-developing (TD) and 13 autistic children with normal IQ and no complaints of poor sleep. Sleep spindles and Sigma EEG activity were computed for frontal (Fp1, Fp2) and central (C3, C4) recording sites. Time in stage 2 sleep and IQ was similar in both groups. Autistic children presented less spindles at Fp2 compared to the TD children. TD children showed negative correlation between verbal IQ and sleep spindle density at Fp2. In the autistic group, verbal and full-scale IQ scores correlated negatively with C3 sleep spindle density. The duration of sleep spindles at Fp1 was shorter in the autistic group than in the TD children. The duration of sleep spindles at C4 was positively correlated with verbal IQ only in the TD group. Fast Sigma EEG activity (13.25-15.75 Hz) was lower at C3 and C4 in autistic children compared to the TD children, particularly in the latter part of the night. Only the TD group showed positive correlation between performance IQ and latter part of the night fast Sigma activity at C4. These results are consistent with a relationship between EEG activity during sleep and cognitive processing in children. The difference between TD and autistic children could derive from dissimilar cortical organization and information processing in these 2 groups. Copyright © 2015. Published by Elsevier B.V.

Computer EEG-monitoring of laserotherapy effects in patients with asteno-depressive syndrome.

PubMed

Omelchenko, V P; Baranchook, I S; Dmitriev, M N

1999-01-01

Nowadays the low-intensive laserotherapy is shown to be an effective and non-hazardous method of asteno-depressive syndrome treatment. The differences of EEG-reactions to laser influences have been revealed in patients of different age groups. And the close negative correlation between the therapy effect, on the one hand, and the patient's age and the disease duration, on the other hand, has been shown. No significant changes of the patient's state or integrative EEG-indices have been evoked by a placebo application. The results showed the advantages of the low-intensive laserotherapy in asteno-depressive syndrome treatment and confirmed the significance of computer EEG-monitoring for prediction, control and correction of the state of the patient.

Neuromodulation integrating rTMS and neurofeedback for the treatment of autism spectrum disorder: an exploratory study.

PubMed

Sokhadze, Estate M; El-Baz, Ayman S; Tasman, Allan; Sears, Lonnie L; Wang, Yao; Lamina, Eva V; Casanova, Manuel F

2014-12-01

Autism spectrum disorder (ASD) is a pervasive developmental disorder characterized by deficits in social interaction, language, stereotyped behaviors, and restricted range of interests. In previous studies low frequency repetitive transcranial magnetic stimulation (rTMS) has been used, with positive behavioral and electrophysiological results, for the experimental treatment in ASD. In this study we combined prefrontal rTMS sessions with electroencephalographic (EEG) neurofeedback (NFB) to prolong and reinforce TMS-induced EEG changes. The pilot trial recruited 42 children with ASD (~14.5 years). Outcome measures included behavioral evaluations and reaction time test with event-related potential (ERP) recording. For the main goal of this exploratory study we used rTMS-neurofeedback combination (TMS-NFB, N = 20) and waitlist (WTL, N = 22) groups to examine effects of 18 sessions of integrated rTMS-NFB treatment or wait period) on behavioral responses, stimulus and response-locked ERPs, and other functional and clinical outcomes. The underlying hypothesis was that combined TMS-NFB will improve executive functions in autistic patients as compared to the WTL group. Behavioral and ERP outcomes were collected in pre- and post-treatment tests in both groups. Results of the study supported our hypothesis by demonstration of positive effects of combined TMS-NFB neurotherapy in active treatment group as compared to control WTL group, as the TMS-NFB group showed significant improvements in behavioral and functional outcomes as compared to the WTL group.

Neuromodulation integrating rTMS and neurofeedback for the treatment of autism spectrum disorder: An exploratory study

PubMed Central

Sokhadze, Estate M.; El-Baz, Ayman S.; Tasman, Allan; Sears, Lonnie L.; Wang, Yao; Lamina, Eva V.; Casanova, Manuel F.

2014-01-01

Autism spectrum disorder (ASD) is a pervasive developmental disorder characterized by deficits in social interaction, language, stereotyped behaviors, and restricted range of interests. In previous studies low frequency repetitive transcranial magnetic stimulation (rTMS) has been used, with positive behavioral and electrophysiological results, for the experimental treatment in ASD. In this study we combined prefrontal rTMS sessions with electroencephalographic (EEG) neurofeedback (NFB) to prolong and reinforce TMS-induced EEG changes. The pilot trial recruited 42 children with ASD (~14.5 yrs). Outcome measures included behavioral evaluations and reaction time test with event-related potential (ERP) recording. For the main goal of this exploratory study we used rTMS-neurofeedback combination (TMS-NFB, N=20) and waitlist (WTL, N=22) groups to examine effects of 18 sessions of integrated rTMS-NFB treatment or wait period) on behavioral responses, stimulus and response-locked ERPs, and other functional and clinical outcomes. The underlying hypothesis was that combined TMS-NFB will improve executive functions in autistic patients as compared to the waitlist group. Behavioral and ERP outcomes were collected in pre- and post-treatment tests in both groups. Results of the study supported our hypothesis by demonstration of positive effects of combined TMS-NFB neurotherapy in active treatment group as compared to control waitlist group, as the TMS-NFB group showed significant improvements in behavioral and functional outcomes as compared to the waitlist group. PMID:25267414

Electrophysiological Measures of Regional Neural Interactive Coupling (Linear and Nonlinear Dependence Relationships Among Multiple Channel Electroencephalographic (EEG) Recordings),

DTIC Science & Technology

1980-01-01

clinical intervention . SG1CUDING CCMENL’ In evaluating the EEGs of subjects it is important to not that . ~major differences in EEG waveshape across...studies in dyslexia . In A.L. Benton and D. Pearl (Fs.), Dyslexia : An Appraisal of Current Knowledge. New York: Oxford University Press, 1978. 4...Electroencephalo- graphy and Clinical Neurophysio !. Oct., 67, 23(4):306-19. 6) Duffy, F.H., Denckla, M.B., Bartels, P.H., and Sandini, G. Dyslexia

Systems, Subjects, Sessions: To What Extent Do These Factors Influence EEG Data?

PubMed

Melnik, Andrew; Legkov, Petr; Izdebski, Krzysztof; Kärcher, Silke M; Hairston, W David; Ferris, Daniel P; König, Peter

2017-01-01

Lab-based electroencephalography (EEG) techniques have matured over decades of research and can produce high-quality scientific data. It is often assumed that the specific choice of EEG system has limited impact on the data and does not add variance to the results. However, many low cost and mobile EEG systems are now available, and there is some doubt as to the how EEG data vary across these newer systems. We sought to determine how variance across systems compares to variance across subjects or repeated sessions. We tested four EEG systems: two standard research-grade systems, one system designed for mobile use with dry electrodes, and an affordable mobile system with a lower channel count. We recorded four subjects three times with each of the four EEG systems. This setup allowed us to assess the influence of all three factors on the variance of data. Subjects performed a battery of six short standard EEG paradigms based on event-related potentials (ERPs) and steady-state visually evoked potential (SSVEP). Results demonstrated that subjects account for 32% of the variance, systems for 9% of the variance, and repeated sessions for each subject-system combination for 1% of the variance. In most lab-based EEG research, the number of subjects per study typically ranges from 10 to 20, and error of uncertainty in estimates of the mean (like ERP) will improve by the square root of the number of subjects. As a result, the variance due to EEG system (9%) is of the same order of magnitude as variance due to subjects (32%/sqrt(16) = 8%) with a pool of 16 subjects. The two standard research-grade EEG systems had no significantly different means from each other across all paradigms. However, the two other EEG systems demonstrated different mean values from one or both of the two standard research-grade EEG systems in at least half of the paradigms. In addition to providing specific estimates of the variability across EEG systems, subjects, and repeated sessions, we also propose a benchmark to evaluate new mobile EEG systems by means of ERP responses.

Systems, Subjects, Sessions: To What Extent Do These Factors Influence EEG Data?

PubMed Central

Melnik, Andrew; Legkov, Petr; Izdebski, Krzysztof; Kärcher, Silke M.; Hairston, W. David; Ferris, Daniel P.; König, Peter

2017-01-01

Lab-based electroencephalography (EEG) techniques have matured over decades of research and can produce high-quality scientific data. It is often assumed that the specific choice of EEG system has limited impact on the data and does not add variance to the results. However, many low cost and mobile EEG systems are now available, and there is some doubt as to the how EEG data vary across these newer systems. We sought to determine how variance across systems compares to variance across subjects or repeated sessions. We tested four EEG systems: two standard research-grade systems, one system designed for mobile use with dry electrodes, and an affordable mobile system with a lower channel count. We recorded four subjects three times with each of the four EEG systems. This setup allowed us to assess the influence of all three factors on the variance of data. Subjects performed a battery of six short standard EEG paradigms based on event-related potentials (ERPs) and steady-state visually evoked potential (SSVEP). Results demonstrated that subjects account for 32% of the variance, systems for 9% of the variance, and repeated sessions for each subject-system combination for 1% of the variance. In most lab-based EEG research, the number of subjects per study typically ranges from 10 to 20, and error of uncertainty in estimates of the mean (like ERP) will improve by the square root of the number of subjects. As a result, the variance due to EEG system (9%) is of the same order of magnitude as variance due to subjects (32%/sqrt(16) = 8%) with a pool of 16 subjects. The two standard research-grade EEG systems had no significantly different means from each other across all paradigms. However, the two other EEG systems demonstrated different mean values from one or both of the two standard research-grade EEG systems in at least half of the paradigms. In addition to providing specific estimates of the variability across EEG systems, subjects, and repeated sessions, we also propose a benchmark to evaluate new mobile EEG systems by means of ERP responses. PMID:28424600

Singular spectrum analysis of sleep EEG in insomnia.

PubMed

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

2011-08-01

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

EEG Correlates of Ten Positive Emotions.

PubMed

Hu, Xin; Yu, Jianwen; Song, Mengdi; Yu, Chun; Wang, Fei; Sun, Pei; Wang, Daifa; Zhang, Dan

2017-01-01

Compared with the well documented neurophysiological findings on negative emotions, much less is known about positive emotions. In the present study, we explored the EEG correlates of ten different positive emotions (joy, gratitude, serenity, interest, hope, pride, amusement, inspiration, awe, and love). A group of 20 participants were invited to watch 30 short film clips with their EEGs simultaneously recorded. Distinct topographical patterns for different positive emotions were found for the correlation coefficients between the subjective ratings on the ten positive emotions per film clip and the corresponding EEG spectral powers in different frequency bands. Based on the similarities of the participants' ratings on the ten positive emotions, these emotions were further clustered into three representative clusters, as 'encouragement' for awe, gratitude, hope, inspiration, pride, 'playfulness' for amusement, joy, interest, and 'harmony' for love, serenity. Using the EEG spectral powers as features, both the binary classification on the higher and lower ratings on these positive emotions and the binary classification between the three positive emotion clusters, achieved accuracies of approximately 80% and above. To our knowledge, our study provides the first piece of evidence on the EEG correlates of different positive emotions.

The Harvard Automated Processing Pipeline for Electroencephalography (HAPPE): Standardized Processing Software for Developmental and High-Artifact Data.

PubMed

Gabard-Durnam, Laurel J; Mendez Leal, Adriana S; Wilkinson, Carol L; Levin, April R

2018-01-01

Electroenchephalography (EEG) recordings collected with developmental populations present particular challenges from a data processing perspective. These EEGs have a high degree of artifact contamination and often short recording lengths. As both sample sizes and EEG channel densities increase, traditional processing approaches like manual data rejection are becoming unsustainable. Moreover, such subjective approaches preclude standardized metrics of data quality, despite the heightened importance of such measures for EEGs with high rates of initial artifact contamination. There is presently a paucity of automated resources for processing these EEG data and no consistent reporting of data quality measures. To address these challenges, we propose the Harvard Automated Processing Pipeline for EEG (HAPPE) as a standardized, automated pipeline compatible with EEG recordings of variable lengths and artifact contamination levels, including high-artifact and short EEG recordings from young children or those with neurodevelopmental disorders. HAPPE processes event-related and resting-state EEG data from raw files through a series of filtering, artifact rejection, and re-referencing steps to processed EEG suitable for time-frequency-domain analyses. HAPPE also includes a post-processing report of data quality metrics to facilitate the evaluation and reporting of data quality in a standardized manner. Here, we describe each processing step in HAPPE, perform an example analysis with EEG files we have made freely available, and show that HAPPE outperforms seven alternative, widely-used processing approaches. HAPPE removes more artifact than all alternative approaches while simultaneously preserving greater or equivalent amounts of EEG signal in almost all instances. We also provide distributions of HAPPE's data quality metrics in an 867 file dataset as a reference distribution and in support of HAPPE's performance across EEG data with variable artifact contamination and recording lengths. HAPPE software is freely available under the terms of the GNU General Public License at https://github.com/lcnhappe/happe.

The Harvard Automated Processing Pipeline for Electroencephalography (HAPPE): Standardized Processing Software for Developmental and High-Artifact Data

PubMed Central

Gabard-Durnam, Laurel J.; Mendez Leal, Adriana S.; Wilkinson, Carol L.; Levin, April R.

2018-01-01

Electroenchephalography (EEG) recordings collected with developmental populations present particular challenges from a data processing perspective. These EEGs have a high degree of artifact contamination and often short recording lengths. As both sample sizes and EEG channel densities increase, traditional processing approaches like manual data rejection are becoming unsustainable. Moreover, such subjective approaches preclude standardized metrics of data quality, despite the heightened importance of such measures for EEGs with high rates of initial artifact contamination. There is presently a paucity of automated resources for processing these EEG data and no consistent reporting of data quality measures. To address these challenges, we propose the Harvard Automated Processing Pipeline for EEG (HAPPE) as a standardized, automated pipeline compatible with EEG recordings of variable lengths and artifact contamination levels, including high-artifact and short EEG recordings from young children or those with neurodevelopmental disorders. HAPPE processes event-related and resting-state EEG data from raw files through a series of filtering, artifact rejection, and re-referencing steps to processed EEG suitable for time-frequency-domain analyses. HAPPE also includes a post-processing report of data quality metrics to facilitate the evaluation and reporting of data quality in a standardized manner. Here, we describe each processing step in HAPPE, perform an example analysis with EEG files we have made freely available, and show that HAPPE outperforms seven alternative, widely-used processing approaches. HAPPE removes more artifact than all alternative approaches while simultaneously preserving greater or equivalent amounts of EEG signal in almost all instances. We also provide distributions of HAPPE's data quality metrics in an 867 file dataset as a reference distribution and in support of HAPPE's performance across EEG data with variable artifact contamination and recording lengths. HAPPE software is freely available under the terms of the GNU General Public License at https://github.com/lcnhappe/happe. PMID:29535597

INDUCED EEG GAMMA OSCILLATION ALIGNMENT IMPROVES DIFFERENTIATION BETWEEN AUTISM AND ADHD GROUP RESPONSES IN A FACIAL CATEGORIZATION TASK

PubMed Central

Gross, Eric; El-Baz, Ayman S.; Sokhadze, Guela E.; Sears, Lonnie; Casanova, Manuel F.; Sokhadze, Estate M.

2012-01-01

Introduction Children diagnosed with an autism spectrum disorder (ASD) often lack the ability to recognize and properly respond to emotional stimuli. Emotional deficits also characterize children with attention deficit/hyperactivity disorder (ADHD), in addition to exhibiting limited attention span. These abnormalities may effect a difference in the induced EEG gamma wave burst (35–45 Hz) peaked approximately 300–400 milliseconds following an emotional stimulus. Because induced gamma oscillations are not fixed at a definite point in time post-stimulus, analysis of averaged EEG data with traditional methods may result in an attenuated gamma burst power. Methods We used a data alignment technique to improve the averaged data, making it a better representation of the individual induced EEG gamma oscillations. A study was designed to test the response of a subject to emotional stimuli, presented in the form of emotional facial expression images. In a four part experiment, the subjects were instructed to identify gender in the first two blocks of the test, followed by differentiating between basic emotions in the final two blocks (i.e. anger vs. disgust). EEG data was collected from ASD (n=10), ADHD (n=9), and control (n=11) subjects via a 128 channel EGI system, and processed through a continuous wavelet transform and bandpass filter to isolate the gamma frequencies. A custom MATLAB code was used to align the data from individual trials between 200–600 ms post-stimulus, EEG site, and condition by maximizing the Pearson product-moment correlation coefficient between trials. The gamma power for the 400 ms window of maximum induced gamma burst was then calculated and compared between subject groups. Results and Conclusion Condition (anger/disgust recognition, gender recognition) × Alignment × Group (ADHD, ASD, Controls) interaction was significant at most of parietal topographies (e.g., P3–P4, P7–P8). These interactions were better manifested in the aligned data set. Our results show that alignment of the induced gamma oscillations improves sensitivity of this measure in differentiation of EEG responses to emotional facial stimuli in ADHD and ASD. PMID:22754277

INDUCED EEG GAMMA OSCILLATION ALIGNMENT IMPROVES DIFFERENTIATION BETWEEN AUTISM AND ADHD GROUP RESPONSES IN A FACIAL CATEGORIZATION TASK.

PubMed

Gross, Eric; El-Baz, Ayman S; Sokhadze, Guela E; Sears, Lonnie; Casanova, Manuel F; Sokhadze, Estate M

2012-01-01

INTRODUCTION: Children diagnosed with an autism spectrum disorder (ASD) often lack the ability to recognize and properly respond to emotional stimuli. Emotional deficits also characterize children with attention deficit/hyperactivity disorder (ADHD), in addition to exhibiting limited attention span. These abnormalities may effect a difference in the induced EEG gamma wave burst (35-45 Hz) peaked approximately 300-400 milliseconds following an emotional stimulus. Because induced gamma oscillations are not fixed at a definite point in time post-stimulus, analysis of averaged EEG data with traditional methods may result in an attenuated gamma burst power. METHODS: We used a data alignment technique to improve the averaged data, making it a better representation of the individual induced EEG gamma oscillations. A study was designed to test the response of a subject to emotional stimuli, presented in the form of emotional facial expression images. In a four part experiment, the subjects were instructed to identify gender in the first two blocks of the test, followed by differentiating between basic emotions in the final two blocks (i.e. anger vs. disgust). EEG data was collected from ASD (n=10), ADHD (n=9), and control (n=11) subjects via a 128 channel EGI system, and processed through a continuous wavelet transform and bandpass filter to isolate the gamma frequencies. A custom MATLAB code was used to align the data from individual trials between 200-600 ms post-stimulus, EEG site, and condition by maximizing the Pearson product-moment correlation coefficient between trials. The gamma power for the 400 ms window of maximum induced gamma burst was then calculated and compared between subject groups. RESULTS AND CONCLUSION: Condition (anger/disgust recognition, gender recognition) × Alignment × Group (ADHD, ASD, Controls) interaction was significant at most of parietal topographies (e.g., P3-P4, P7-P8). These interactions were better manifested in the aligned data set. Our results show that alignment of the induced gamma oscillations improves sensitivity of this measure in differentiation of EEG responses to emotional facial stimuli in ADHD and ASD.

[EEG markers of spontaneous recovery of vertical posture in patients with consequences of severe traumatic brain injury].

PubMed

Zhavoronkova, L A; Zharikova, A V; Maksakova, O A

2014-01-01

9 patients (mean age 23.6 +/- 3.15 y.o.) with severe traumatic brain injury (TBI) and impairment of vertical posture were included in complex clinical and EEG study during spontaneous recovery of vertical posture (VP). Patients were included in three different groups according to severity of deficit according to MPAI, FIM and MMSE scales. EEG data have been compared to those of 10 healthy volunteers (mean age 22.8 +/- 0.67 yo.). In patients with moderate brain impairment and fast recovery of VP (over 2 weeks) change of posture from sitting to standup has been accompanied by EEG-signs similar to those of healthy people. These included predominant increase of coherence in right hemisphere for majority of frequency bands, although in more complex conditions EEG of these patients showed pathological signs. In patients with more severe deficit spontaneous recovery of VP has been accompanied by "hyper-reactive" change of EEG for all frequency bands without local specificity. This finding didn't depend on side ofbrain impairment and could be considered as marker of positive dynamics of VP restoration. In patients with most severe brain impairment and deficit of functions VP didn't recover after 3 month of observation. EEG-investigation has revealed absence of reactive change of EEG during passive verticalisation. This finding can be used as marker of negative prognosis.

Performance evaluation for epileptic electroencephalogram (EEG) detection by using Neyman-Pearson criteria and a support vector machine

NASA Astrophysics Data System (ADS)

Wang, Chun-mei; Zhang, Chong-ming; Zou, Jun-zhong; Zhang, Jian

2012-02-01

The diagnosis of several neurological disorders is based on the detection of typical pathological patterns in electroencephalograms (EEGs). This is a time-consuming task requiring significant training and experience. A lot of effort has been devoted to developing automatic detection techniques which might help not only in accelerating this process but also in avoiding the disagreement among readers of the same record. In this work, Neyman-Pearson criteria and a support vector machine (SVM) are applied for detecting an epileptic EEG. Decision making is performed in two stages: feature extraction by computing the wavelet coefficients and the approximate entropy (ApEn) and detection by using Neyman-Pearson criteria and an SVM. Then the detection performance of the proposed method is evaluated. Simulation results demonstrate that the wavelet coefficients and the ApEn are features that represent the EEG signals well. By comparison with Neyman-Pearson criteria, an SVM applied on these features achieved higher detection accuracies.

Sample entropy analysis for the estimating depth of anaesthesia through human EEG signal at different levels of unconsciousness during surgeries.

PubMed

Liu, Quan; Ma, Li; Fan, Shou-Zen; Abbod, Maysam F; Shieh, Jiann-Shing

2018-01-01

Estimating the depth of anaesthesia (DoA) in operations has always been a challenging issue due to the underlying complexity of the brain mechanisms. Electroencephalogram (EEG) signals are undoubtedly the most widely used signals for measuring DoA. In this paper, a novel EEG-based index is proposed to evaluate DoA for 24 patients receiving general anaesthesia with different levels of unconsciousness. Sample Entropy (SampEn) algorithm was utilised in order to acquire the chaotic features of the signals. After calculating the SampEn from the EEG signals, Random Forest was utilised for developing learning regression models with Bispectral index (BIS) as the target. Correlation coefficient, mean absolute error, and area under the curve (AUC) were used to verify the perioperative performance of the proposed method. Validation comparisons with typical nonstationary signal analysis methods (i.e., recurrence analysis and permutation entropy) and regression methods (i.e., neural network and support vector machine) were conducted. To further verify the accuracy and validity of the proposed methodology, the data is divided into four unconsciousness-level groups on the basis of BIS levels. Subsequently, analysis of variance (ANOVA) was applied to the corresponding index (i.e., regression output). Results indicate that the correlation coefficient improved to 0.72 ± 0.09 after filtering and to 0.90 ± 0.05 after regression from the initial values of 0.51 ± 0.17. Similarly, the final mean absolute error dramatically declined to 5.22 ± 2.12. In addition, the ultimate AUC increased to 0.98 ± 0.02, and the ANOVA analysis indicates that each of the four groups of different anaesthetic levels demonstrated significant difference from the nearest levels. Furthermore, the Random Forest output was extensively linear in relation to BIS, thus with better DoA prediction accuracy. In conclusion, the proposed method provides a concrete basis for monitoring patients' anaesthetic level during surgeries.

Therapeutic Effects of Rivastigmine and Alfa-Lipoic Acid Combination in the Charles Bonnet Syndrome: Electroencephalography Correlates.

PubMed

Hanoglu, Lutfu; Yildiz, Sultan; Polat, Burcu; Demirci, Sema; Tavli, Ahmet Mithat; Yilmaz, Nesrin; Yulug, Burak

2016-01-01

Charles Bonnet Syndrome (CBS) is a rare clinical condition which is characterized by complex hallucinations in visually impaired patients. The pathophysiology of this disorder remains largely unknown, and there is still no proven treatment for this disease. In our study, we aimed to investigate the neural activity through Electroencephalography (EEG) power and evaluate the effect of rivastigmine in combination with alpha-lipoic acid on hallucination in two CBS patients with diabetic retinopathy. EEG data was recorded with standard routine EEG protocols for both patients in our electrophysiological research laboratory (REMER Clinical Electrophysiology and Neuromodulation Research and Application Laboratory) with Brain Vision Recorder (Brainproduct, Munich, Germany). All spectral analyses were processed by BrainVision Analyzer 2 (Brainproduct, Munich, Germany, 2.0.4 Version) in 128 Hz sample rates and the EEG recording and analysis was performed before the administration of rivastigmine (4.5 mg/daily and five patch daily for the first and second patients, respectively) in combination with alpha-lipoic acid (600 mg/daily) for both patients while they were not hallucinated during the time period recordings. Based on our measurement protocol, we have compared the patients in the study group with the three control subjects who were found to be normal except of visual disturbances secondary to significant diabetic retinopathy. Highest theta power values were found in right occipital and left temporo-parietal regions for first and second CBS patients, respectively. Additionally, power spectra were lower in two cases as compared to their control groups in the alpha band for all electrodes. We have also shown that acid rivastigmine in combination with alpha-lipoic exerted significant anti-hallucinatory efficiency. Our present findings could support the hypothesis that increased activation of specific areas in the source monitoring system plays an important role in the pathogenesis of CBS. In addition, rivastigmine in combination with alpha-lipoic acid could be a new valuable option for CBS patients.

Improved cognitive morning performance in healthy older adults following blue-enriched light exposure on the previous evening.

PubMed

Scheuermaier, Karine; Münch, Mirjam; Ronda, Joseph M; Duffy, Jeanne F

2018-04-21

Exposure to light can have acute alerting and circadian phase-shifting effects. This study investigated the effects of evening exposure to blue-enriched polychromatic white (BEL) vs. polychromatic white light (WL) on sleep inertia dissipation the following morning in older adults. Ten healthy older adults (average age = 63.3 yrs; 6F) participated in a 13-day study comprising three baseline days, an initial circadian phase assessment, four days with 2-h evening light exposures, a post light exposure circadian phase assessment and three recovery days. Participants were randomized to either BEL or WL of the same irradiance for the four evening light exposures. On the next mornings at 2, 12, 22 and 32 min after each wake time, the participants completed a 90-s digit-symbol substitution test (DSST) to assess working memory, and objective alertness was assessed using a wake EEG recording. DSST and power density from the wake EEG recordings were compared between the two groups. DSST performance improved with time awake (p < 0.0001) and across study days in both light exposure groups (p < 0.0001). There was no main effect of group, although we observed a significant day x group interaction (p = 0.0004), whereby participants exposed to BEL performed significantly better on the first two mornings after light exposures than participants in WL (post-hoc, p < 0.05). On those days, the BEL group showed higher EEG activity in some of the frequency bins in the sigma and beta range (p < 0.05) on the wake EEG. Exposure to blue-enriched white light in the evening significantly improved DSST performance the following morning when compared to polychromatic white light. This was associated with a higher level of objective alertness on the wake EEG, but not with changes in sleep or circadian timing. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

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

PubMed

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

2014-03-01

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

Computer-aided diagnosis of alcoholism-related EEG signals.

PubMed

Acharya, U Rajendra; S, Vidya; Bhat, Shreya; Adeli, Hojjat; Adeli, Amir

2014-12-01

Alcoholism is a severe disorder that affects the functionality of neurons in the central nervous system (CNS) and alters the behavior of the affected person. Electroencephalogram (EEG) signals can be used as a diagnostic tool in the evaluation of subjects with alcoholism. The neurophysiological interpretation of EEG signals in persons with alcoholism (PWA) is based on observation and interpretation of the frequency and power in their EEGs compared to EEG signals from persons without alcoholism. This paper presents a review of the known features of EEGs obtained from PWA and proposes that the impact of alcoholism on the brain can be determined by computer-aided analysis of EEGs through extracting the minute variations in the EEG signals that can differentiate the EEGs of PWA from those of nonaffected persons. The authors advance the idea of automated computer-aided diagnosis (CAD) of alcoholism by employing the EEG signals. This is achieved through judicious combination of signal processing techniques such as wavelet, nonlinear dynamics, and chaos theory and pattern recognition and classification techniques. A CAD system is cost-effective and efficient and can be used as a decision support system by physicians in the diagnosis and treatment of alcoholism especially those who do not specialize in alcoholism or neurophysiology. It can also be of great value to rehabilitation centers to assess PWA over time and to monitor the impact of treatment aimed at minimizing or reversing the effects of the disease on the brain. A CAD system can be used to determine the extent of alcoholism-related changes in EEG signals (low, medium, high) and the effectiveness of therapeutic plans. Copyright © 2014 Elsevier Inc. All rights reserved.

Hyperventilation in Patients With Focal Epilepsy: Electromagnetic Tomography, Functional Connectivity and Graph Theory - A Possible Tool in Epilepsy Diagnosis?

PubMed

Mazzucchi, Edoardo; Vollono, Catello; Losurdo, Anna; Testani, Elisa; Gnoni, Valentina; Di Blasi, Chiara; Giannantoni, Nadia M; Lapenta, Leonardo; Brunetti, Valerio; Della Marca, Giacomo

2017-01-01

Hyperventilation (HV) is a commonly used electroencephalogram activation method. We analyzed EEG recordings in 22 normal subjects and 22 patients with focal epilepsy of unknown cause. We selected segments before (PRE), during (HYPER), and 5 minutes after (POST) HV. To analyze the neural generators of EEG signal, we used standard low-resolution electromagnetic tomography (sLORETA software). We then computed EEG lagged coherence, an index of functional connectivity, between 19 regions of interest. A weighted graph was built for each band in every subject, and characteristic path length (L) and clustering coefficient (C) have been computed. Statistical comparisons were performed by means of analysis of variance (Group X Condition X Band) for mean lagged coherence, L and C. Hyperventilation significantly increases EEG neural generators (P < 0.001); the effect is particularly evident in cingulate cortex. Functional connectivity was increased by HV in delta, theta, alpha, and beta bands in the Epileptic group (P < 0.01) and only in theta band in Control group. Intergroup analysis of mean lagged coherence, C and L, showed significant differences for Group (P < 0.001), Condition (P < 0.001), and Band (P < 0.001). Analysis of variance for L also showed significant interactions: Group X Condition (P = 0.003) and Group X Band (P < 0.001). In our relatively small group of epileptic patients, HV is associated with activation of cingulate cortex; moreover, it modifies brain connectivity. The significant differences in mean lagged coherence, path length, and clustering coefficient permit to hypothesize that this activation method leads to different brain connectivity patterns in patients with epilepsy when compared with normal subjects. If confirmed by other studies involving larger populations, this analysis could become a diagnostic tool in epilepsy.

Autoregressive model in the Lp norm space for EEG analysis.

PubMed

Li, Peiyang; Wang, Xurui; Li, Fali; Zhang, Rui; Ma, Teng; Peng, Yueheng; Lei, Xu; Tian, Yin; Guo, Daqing; Liu, Tiejun; Yao, Dezhong; Xu, Peng

2015-01-30

The autoregressive (AR) model is widely used in electroencephalogram (EEG) analyses such as waveform fitting, spectrum estimation, and system identification. In real applications, EEGs are inevitably contaminated with unexpected outlier artifacts, and this must be overcome. However, most of the current AR models are based on the L2 norm structure, which exaggerates the outlier effect due to the square property of the L2 norm. In this paper, a novel AR object function is constructed in the Lp (p≤1) norm space with the aim to compress the outlier effects on EEG analysis, and a fast iteration procedure is developed to solve this new AR model. The quantitative evaluation using simulated EEGs with outliers proves that the proposed Lp (p≤1) AR can estimate the AR parameters more robustly than the Yule-Walker, Burg and LS methods, under various simulated outlier conditions. The actual application to the resting EEG recording with ocular artifacts also demonstrates that Lp (p≤1) AR can effectively address the outliers and recover a resting EEG power spectrum that is more consistent with its physiological basis. Copyright © 2014 Elsevier B.V. All rights reserved.

Joint Maximum Likelihood Time Delay Estimation of Unknown Event-Related Potential Signals for EEG Sensor Signal Quality Enhancement

PubMed Central

Kim, Kyungsoo; Lim, Sung-Ho; Lee, Jaeseok; Kang, Won-Seok; Moon, Cheil; Choi, Ji-Woong

2016-01-01

Electroencephalograms (EEGs) measure a brain signal that contains abundant information about the human brain function and health. For this reason, recent clinical brain research and brain computer interface (BCI) studies use EEG signals in many applications. Due to the significant noise in EEG traces, signal processing to enhance the signal to noise power ratio (SNR) is necessary for EEG analysis, especially for non-invasive EEG. A typical method to improve the SNR is averaging many trials of event related potential (ERP) signal that represents a brain’s response to a particular stimulus or a task. The averaging, however, is very sensitive to variable delays. In this study, we propose two time delay estimation (TDE) schemes based on a joint maximum likelihood (ML) criterion to compensate the uncertain delays which may be different in each trial. We evaluate the performance for different types of signals such as random, deterministic, and real EEG signals. The results show that the proposed schemes provide better performance than other conventional schemes employing averaged signal as a reference, e.g., up to 4 dB gain at the expected delay error of 10°. PMID:27322267

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

Automated Identification of Abnormal Adult EEGs

PubMed Central

López, S.; Suarez, G.; Jungreis, D.; Obeid, I.; Picone, J.

2016-01-01

The interpretation of electroencephalograms (EEGs) is a process that is still dependent on the subjective analysis of the examiners. Though interrater agreement on critical events such as seizures is high, it is much lower on subtler events (e.g., when there are benign variants). The process used by an expert to interpret an EEG is quite subjective and hard to replicate by machine. The performance of machine learning technology is far from human performance. We have been developing an interpretation system, AutoEEG, with a goal of exceeding human performance on this task. In this work, we are focusing on one of the early decisions made in this process – whether an EEG is normal or abnormal. We explore two baseline classification algorithms: k-Nearest Neighbor (kNN) and Random Forest Ensemble Learning (RF). A subset of the TUH EEG Corpus was used to evaluate performance. Principal Components Analysis (PCA) was used to reduce the dimensionality of the data. kNN achieved a 41.8% detection error rate while RF achieved an error rate of 31.7%. These error rates are significantly lower than those obtained by random guessing based on priors (49.5%). The majority of the errors were related to misclassification of normal EEGs. PMID:27195311

Ongoing slow oscillatory phase modulates speech intelligibility in cooperation with motor cortical activity.

PubMed

Onojima, Takayuki; Kitajo, Keiichi; Mizuhara, Hiroaki

2017-01-01

Neural oscillation is attracting attention as an underlying mechanism for speech recognition. Speech intelligibility is enhanced by the synchronization of speech rhythms and slow neural oscillation, which is typically observed as human scalp electroencephalography (EEG). In addition to the effect of neural oscillation, it has been proposed that speech recognition is enhanced by the identification of a speaker's motor signals, which are used for speech production. To verify the relationship between the effect of neural oscillation and motor cortical activity, we measured scalp EEG, and simultaneous EEG and functional magnetic resonance imaging (fMRI) during a speech recognition task in which participants were required to recognize spoken words embedded in noise sound. We proposed an index to quantitatively evaluate the EEG phase effect on behavioral performance. The results showed that the delta and theta EEG phase before speech inputs modulated the participant's response time when conducting speech recognition tasks. The simultaneous EEG-fMRI experiment showed that slow EEG activity was correlated with motor cortical activity. These results suggested that the effect of the slow oscillatory phase was associated with the activity of the motor cortex during speech recognition.

Desynchronization of Theta-Phase Gamma-Amplitude Coupling during a Mental Arithmetic Task in Children with Attention Deficit/Hyperactivity Disorder.

PubMed

Kim, Jun Won; Kim, Bung-Nyun; Lee, Jaewon; Na, Chul; Kee, Baik Seok; Min, Kyung Joon; Han, Doug Hyun; Kim, Johanna Inhyang; Lee, Young Sik

2016-01-01

Theta-phase gamma-amplitude coupling (TGC) measurement has recently received attention as a feasible method of assessing brain functions such as neuronal interactions. The purpose of this electroencephalographic (EEG) study is to understand the mechanisms underlying the deficits in attentional control in children with attention deficit/hyperactivity disorder (ADHD) by comparing the power spectra and TGC at rest and during a mental arithmetic task. Nineteen-channel EEGs were recorded from 97 volunteers (including 53 subjects with ADHD) from a camp for hyperactive children under two conditions (rest and task performance). The EEG power spectra and the TGC data were analyzed. Correlation analyses between the Intermediate Visual and Auditory (IVA) continuous performance test (CPT) scores and EEG parameters were performed. No significant difference in the power spectra was detected between the groups at rest and during task performance. However, TGC was reduced during the arithmetic task in the ADHD group compared with the normal group (F = 16.70, p < 0.001). The TGC values positively correlated with the IVA CPT scores but negatively correlated with theta power. Our findings suggest that desynchronization of TGC occurred during the arithmetic task in ADHD children. TGC in ADHD children is expected to serve as a promising neurophysiological marker of network deactivation during attention-demanding tasks.

P300 speller BCI with a mobile EEG system: comparison to a traditional amplifier

NASA Astrophysics Data System (ADS)

De Vos, Maarten; Kroesen, Markus; Emkes, Reiner; Debener, Stefan

2014-06-01

Objective. In a previous study, we presented a low-cost, small and wireless EEG system enabling the recording of single-trial P300 amplitudes in a truly mobile, outdoor walking condition (Debener et al (2012 Psychophysiology 49 1449-53)). Small and wireless mobile EEG systems have substantial practical advantages as they allow for brain activity recordings in natural environments, but these systems may compromise the EEG signal quality. In this study, we aim to evaluate the EEG signal quality that can be obtained with the mobile system. Approach. We compared our mobile 14-channel EEG system with a state-of-the-art wired laboratory EEG system in a popular brain-computer interface (BCI) application. N = 13 individuals repeatedly performed a 6 × 6 matrix P300 spelling task. Between conditions, only the amplifier was changed, while electrode placement and electrode preparation, recording conditions, experimental stimulation and signal processing were identical. Main results. Analysis of training and testing accuracies and information transfer rate (ITR) revealed that the wireless mobile EEG amplifier performed as good as the wired laboratory EEG system. A very high correlation for testing ITR between both amplifiers was evident (r = 0.92). Moreover the P300 topographies and amplitudes were very similar for both devices, as reflected by high degrees of association (r > = 0.77). Significance. We conclude that efficient P300 spelling with a small, lightweight and quick to set up mobile EEG amplifier is possible. This technology facilitates the transfer of BCI applications from the laboratory to natural daily life environments, one of the key challenges in current BCI research.

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.

Prospective Cohort Study Evaluating the Prognostic Value of Simple EEG Parameters in Postanoxic Coma.

PubMed

Azabou, Eric; Fischer, Catherine; Mauguiere, François; Vaugier, Isabelle; Annane, Djillali; Sharshar, Tarek; Lofaso, Fréderic

2016-01-01

We prospectively studied early bedside standard EEG characteristics in 61 acute postanoxic coma patients. Five simple EEG features, namely, isoelectric, discontinuous, nonreactive to intense auditory and nociceptive stimuli, dominant delta frequency, and occurrence of paroxysms were classified yes or no. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristic curve (AUC) of each of these variables for predicting an unfavorable outcome, defined as death, persistent vegetative state, minimally conscious state, or severe neurological disability, as assessed 1 year after coma onset were computed as well as Synek's score. The outcome was unfavorable in 56 (91.8%) patients. Sensitivity, specificity, PPV, NPV, and AUC of nonreactive EEG for predicting an unfavorable outcome were 84%, 80%, 98%, 31%, and 0.82, respectively; and were all very close to the ones of Synek score>3, which were 82%, 80%, 98%, 29%, and 0.81, respectively. Specificities for predicting an unfavorable outcome were 100% for isoelectric, discontinuous, or dominant delta activity EEG. These 3 last features were constantly associated to unfavorable outcome. Absent EEG reactivity strongly predicted an unfavorable outcome in postanoxic coma, and performed as accurate as a Synek score>3. Analyzing characteristics of some simple EEG features may easily help nonneurophysiologist physicians to investigate prognostic issue of postanoxic coma patient. In this study (a) discontinuous, isoelectric, or delta-dominant EEG were constantly associated with unfavorable outcome and (b) nonreactive EEG performed prognostic as accurate as a Synek score>3. © EEG and Clinical Neuroscience Society (ECNS) 2015.

Characteristics of EEG Interpreters Associated With Higher Interrater Agreement.

PubMed

Halford, Jonathan J; Arain, Amir; Kalamangalam, Giridhar P; LaRoche, Suzette M; Leonardo, Bonilha; Basha, Maysaa; Azar, Nabil J; Kutluay, Ekrem; Martz, Gabriel U; Bethany, Wolf J; Waters, Chad G; Dean, Brian C

2017-03-01

The goal of the project is to determine characteristics of academic neurophysiologist EEG interpreters (EEGers), which predict good interrater agreement (IRA) and to determine the number of EEGers needed to develop an ideal standardized testing and training data set for epileptiform transient (ET) detection algorithms. A three-phase scoring method was used. In phase 1, 19 EEGers marked the location of ETs in two hundred 30-second segments of EEG from 200 different patients. In phase 2, EEG events marked by at least 2 EEGers were annotated by 18 EEGers on a 5-point scale to indicate whether they were ETs. In phase 3, a third opinion was obtained from EEGers on any inconsistencies between phase 1 and phase 2 scoring. The IRA for the 18 EEGers was only fair. A select group of the EEGers had good IRA and the other EEGers had low IRA. Board certification by the American Board of Clinical Neurophysiology was associated with better IRA performance but other board certifications, years of fellowship training, and years of practice were not. As the number of EEGers used for scoring is increased, the amount of change in the consensus opinion decreases steadily and is quite low as the group size approaches 10. The IRA among EEGers varies considerably. The EEGers must be tested before use as scorers for ET annotation research projects. The American Board of Clinical Neurophysiology certification is associated with improved performance. The optimal size for a group of experts scoring ETs in EEG is probably in the 6 to 10 range.

Slower EEG alpha generation, synchronization and "flow"-possible biomarkers of cognitive impairment and neuropathology of minor stroke.

PubMed

Petrovic, Jelena; Milosevic, Vuk; Zivkovic, Miroslava; Stojanov, Dragan; Milojkovic, Olga; Kalauzi, Aleksandar; Saponjic, Jasna

2017-01-01

We investigated EEG rhythms, particularly alpha activity, and their relationship to post-stroke neuropathology and cognitive functions in the subacute and chronic stages of minor strokes. We included 10 patients with right middle cerebral artery (MCA) ischemic strokes and 11 healthy controls. All the assessments of stroke patients were done both in the subacute and chronic stages. Neurological impairment was measured using the National Institute of Health Stroke Scale (NIHSS), whereas cognitive functions were assessed using the Montreal Cognitive Assessment (MoCA) and MoCA memory index (MoCA-MIS). The EEG was recorded using a 19 channel EEG system with standard EEG electrode placement. In particular, we analyzed the EEGs derived from the four lateral frontal (F3, F7, F4, F8), and corresponding lateral posterior (P3, P4, T5, T6) electrodes. Quantitative EEG analysis included: the group FFT spectra, the weighted average of alpha frequency (αAVG), the group probability density distributions of all conventional EEG frequency band relative amplitudes (EEG microstructure), the inter- and intra-hemispheric coherences, and the topographic distribution of alpha carrier frequency phase potentials (PPs). Statistical analysis was done using a Kruskal-Wallis ANOVA with a post-hoc Mann-Whitney U two-tailed test, and Spearman's correlation. We demonstrated transient cognitive impairment alongside a slower alpha frequency ( α AVG) in the subacute right MCA stroke patients vs. the controls. This slower alpha frequency showed no amplitude change, but was highly synchronized intra-hemispherically, overlying the ipsi-lesional hemisphere, and inter-hemispherically, overlying the frontal cortex. In addition, the disturbances in EEG alpha activity in subacute stroke patients were expressed as a decrease in alpha PPs over the frontal cortex and an altered "alpha flow", indicating the sustained augmentation of inter-hemispheric interactions. Although the stroke induced slower alpha was a transient phenomenon, the increased alpha intra-hemispheric synchronization, overlying the ipsi-lesional hemisphere, the increased alpha F3-F4 inter-hemispheric synchronization, the delayed alpha waves, and the newly established inter-hemispheric "alpha flow" within the frontal cortex, remained as a permanent consequence of the minor stroke. This newly established frontal inter-hemispheric "alpha flow" represented a permanent consequence of the "hidden" stroke neuropathology, despite the fact that cognitive impairment has been returned to the control values. All the detected permanent changes at the EEG level with no cognitive impairment after a minor stroke could be a way for the brain to compensate for the lesion and restore the lost function. Our study indicates slower EEG alpha generation, synchronization and "flow" as potential biomarkers of cognitive impairment onset and/or compensatory post-stroke re-organizational processes.

Early seizure detection in an animal model of temporal lobe epilepsy

NASA Astrophysics Data System (ADS)

Talathi, Sachin S.; Hwang, Dong-Uk; Ditto, William; Carney, Paul R.

2007-11-01

The performance of five seizure detection schemes, i.e., Nonlinear embedding delay, Hurst scaling, Wavelet Scale, autocorrelation and gradient of accumulated energy, in their ability to detect EEG seizures close to the seizure onset time were evaluated to determine the feasibility of their application in the development of a real time closed loop seizure intervention program (RCLSIP). The criteria chosen for the performance evaluation were, high statistical robustness as determined through the predictability index, the sensitivity and the specificity of a given measure to detect an EEG seizure, the lag in seizure detection with respect to the EEG seizure onset time, as determined through visual inspection and the computational efficiency for each detection measure. An optimality function was designed to evaluate the overall performance of each measure dependent on the criteria chosen. While each of the above measures analyzed for seizure detection performed very well in terms of the statistical parameters, the nonlinear embedding delay measure was found to have the highest optimality index due to its ability to detect seizure very close to the EEG seizure onset time, thereby making it the most suitable dynamical measure in the development of RCLSIP in rat model with chronic limbic epilepsy.

Characteristics of Human Brain Activity during the Evaluation of Service-to-Service Brand Extension

PubMed Central

Yang, Taeyang; Lee, Seungji; Seomoon, Eunbi; Kim, Sung-Phil

2018-01-01

Brand extension is a marketing strategy to apply the previously established brand name into new goods or service. A number of studies have reported the characteristics of human event-related potentials (ERPs) in response to the evaluation of goods-to-goods brand extension. In contrast, human brain responses to the evaluation of service extension are relatively unexplored. The aim of this study was investigating cognitive processes underlying the evaluation of service-to-service brand extension with electroencephalography (EEG). A total of 56 text stimuli composed of service brand name (S1) followed by extended service name (S2) were presented to participants. The EEG of participants was recorded while participants were asked to evaluate whether a given brand extension was acceptable or not. The behavioral results revealed that participants could evaluate brand extension though they had little knowledge about the extended services, indicating the role of brand in the evaluation of the services. Additionally, we developed a method of grouping brand extension stimuli according to the fit levels obtained from behavioral responses, instead of grouping of stimuli a priori. The ERP analysis identified three components during the evaluation of brand extension: N2, P300, and N400. No difference in the N2 amplitude was found among the different levels of a fit between S1 and S2. The P300 amplitude for the low level of fit was greater than those for higher levels (p < 0.05). The N400 amplitude was more negative for the mid- and high-level fits than the low level. The ERP results of P300 and N400 indicate that the early stage of brain extension evaluation might first detect low-fit brand extension as an improbable target followed by the late stage of the integration of S2 into S1. Along with previous findings, our results demonstrate different cognitive evaluation of service-to-service brand extension from goods-to-goods. PMID:29479313

Characteristics of Human Brain Activity during the Evaluation of Service-to-Service Brand Extension.

PubMed

Yang, Taeyang; Lee, Seungji; Seomoon, Eunbi; Kim, Sung-Phil

2018-01-01

Brand extension is a marketing strategy to apply the previously established brand name into new goods or service. A number of studies have reported the characteristics of human event-related potentials (ERPs) in response to the evaluation of goods-to-goods brand extension. In contrast, human brain responses to the evaluation of service extension are relatively unexplored. The aim of this study was investigating cognitive processes underlying the evaluation of service-to-service brand extension with electroencephalography (EEG). A total of 56 text stimuli composed of service brand name (S1) followed by extended service name (S2) were presented to participants. The EEG of participants was recorded while participants were asked to evaluate whether a given brand extension was acceptable or not. The behavioral results revealed that participants could evaluate brand extension though they had little knowledge about the extended services, indicating the role of brand in the evaluation of the services. Additionally, we developed a method of grouping brand extension stimuli according to the fit levels obtained from behavioral responses, instead of grouping of stimuli a priori . The ERP analysis identified three components during the evaluation of brand extension: N2, P300, and N400. No difference in the N2 amplitude was found among the different levels of a fit between S1 and S2. The P300 amplitude for the low level of fit was greater than those for higher levels ( p < 0.05). The N400 amplitude was more negative for the mid- and high-level fits than the low level. The ERP results of P300 and N400 indicate that the early stage of brain extension evaluation might first detect low-fit brand extension as an improbable target followed by the late stage of the integration of S2 into S1. Along with previous findings, our results demonstrate different cognitive evaluation of service-to-service brand extension from goods-to-goods.

Resting-state EEG coupling analysis of amnestic mild cognitive impairment with type 2 diabetes mellitus by using permutation conditional mutual information.

PubMed

Wen, Dong; Bian, Zhijie; Li, Qiuli; Wang, Lei; Lu, Chengbiao; Li, Xiaoli

2016-01-01

This study was meant to explore whether the coupling strength and direction of resting-state electroencephalogram (rsEEG) could be used as an indicator to distinguish the patients of type 2 diabetes mellitus (T2DM) with or without amnestic mild cognitive impairment (aMCI). Permutation conditional mutual information (PCMI) was used to calculate the coupling strength and direction of rsEEG signals between different brain areas of 19 aMCI and 20 normal control (NC) with T2DM on 7 frequency bands: Delta, Theta, Alpha1, Alpha2, Beta1, Beta2 and Gamma. The difference in coupling strength or direction of rsEEG between two groups was calculated. The correlation between coupling strength or direction of rsEEG and score of different neuropsychology scales were also calculated. We have demonstrated that PCMI can calculate effectively the coupling strength and directionality of EEG signals between different brain regions. The significant difference in coupling strength and directionality of EEG signals was found between the patients of aMCI and NC with T2DM on different brain regions. There also existed significant correlation between sex or age and coupling strength or coupling directionality of EEG signals between a few different brain regions from all subjects. The coupling strength or directionality of EEG signals calculated by PCMI are significantly different between aMCI and NC with T2DM. These results showed that the coupling strength or directionality of EEG signals calculated by PCMI might be used as a biomarker in distinguishing the aMCI from NC with T2DM. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

EEG complexity as a biomarker for autism spectrum disorder risk

PubMed Central

2011-01-01

Background Complex neurodevelopmental disorders may be characterized by subtle brain function signatures early in life before behavioral symptoms are apparent. Such endophenotypes may be measurable biomarkers for later cognitive impairments. The nonlinear complexity of electroencephalography (EEG) signals is believed to contain information about the architecture of the neural networks in the brain on many scales. Early detection of abnormalities in EEG signals may be an early biomarker for developmental cognitive disorders. The goal of this paper is to demonstrate that the modified multiscale entropy (mMSE) computed on the basis of resting state EEG data can be used as a biomarker of normal brain development and distinguish typically developing children from a group of infants at high risk for autism spectrum disorder (ASD), defined on the basis of an older sibling with ASD. Methods Using mMSE as a feature vector, a multiclass support vector machine algorithm was used to classify typically developing and high-risk groups. Classification was computed separately within each age group from 6 to 24 months. Results Multiscale entropy appears to go through a different developmental trajectory in infants at high risk for autism (HRA) than it does in typically developing controls. Differences appear to be greatest at ages 9 to 12 months. Using several machine learning algorithms with mMSE as a feature vector, infants were classified with over 80% accuracy into control and HRA groups at age 9 months. Classification accuracy for boys was close to 100% at age 9 months and remains high (70% to 90%) at ages 12 and 18 months. For girls, classification accuracy was highest at age 6 months, but declines thereafter. Conclusions This proof-of-principle study suggests that mMSE computed from resting state EEG signals may be a useful biomarker for early detection of risk for ASD and abnormalities in cognitive development in infants. To our knowledge, this is the first demonstration of an information theoretic analysis of EEG data for biomarkers in infants at risk for a complex neurodevelopmental disorder. PMID:21342500

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.

Understanding Cognitive Performance During Robot-Assisted Surgery.

PubMed

Guru, Khurshid A; Shafiei, Somayeh B; Khan, Atif; Hussein, Ahmed A; Sharif, Mohamed; Esfahani, Ehsan T

2015-10-01

To understand cognitive function of an expert surgeon in various surgical scenarios while performing robot-assisted surgery. In an Internal Review Board approved study, National Aeronautics and Space Administration-Task Load Index (NASA-TLX) questionnaire with surgical field notes were simultaneously completed. A wireless electroencephalography (EEG) headset was used to monitor brain activity during all procedures. Three key portions were evaluated: lysis of adhesions, extended lymph node dissection, and urethro-vesical anastomosis (UVA). Cognitive metrics extracted were distraction, mental workload, and mental state. In evaluating lysis of adhesions, mental state (EEG) was associated with better performance (NASA-TLX). Utilizing more mental resources resulted in better performance as self-reported. Outcomes of lysis were highly dependent on cognitive function and decision-making skills. In evaluating extended lymph node dissection, there was a negative correlation between distraction level (EEG) and mental demand, physical demand and effort (NASA-TLX). Similar to lysis of adhesion, utilizing more mental resources resulted in better performance (NASA-TLX). Lastly, with UVA, workload (EEG) negatively correlated with mental and temporal demand and was associated with better performance (NASA-TLX). The EEG recorded workload as seen here was a combination of both cognitive performance (finding solution) and motor workload (execution). Majority of workload was contributed by motor workload of an expert surgeon. During UVA, muscle memory and motor skills of expert are keys to completing the UVA. Cognitive analysis shows that expert surgeons utilized different mental resources based on their need. Copyright © 2015 Elsevier Inc. All rights reserved.

Evaluation of a Dry EEG System for Application of Passive Brain-Computer Interfaces in Autonomous Driving

PubMed Central

Zander, Thorsten O.; Andreessen, Lena M.; Berg, Angela; Bleuel, Maurice; Pawlitzki, Juliane; Zawallich, Lars; Krol, Laurens R.; Gramann, Klaus

2017-01-01

We tested the applicability and signal quality of a 16 channel dry electroencephalography (EEG) system in a laboratory environment and in a car under controlled, realistic conditions. The aim of our investigation was an estimation how well a passive Brain-Computer Interface (pBCI) can work in an autonomous driving scenario. The evaluation considered speed and accuracy of self-applicability by an untrained person, quality of recorded EEG data, shifts of electrode positions on the head after driving-related movements, usability, and complexity of the system as such and wearing comfort over time. An experiment was conducted inside and outside of a stationary vehicle with running engine, air-conditioning, and muted radio. Signal quality was sufficient for standard EEG analysis in the time and frequency domain as well as for the use in pBCIs. While the influence of vehicle-induced interferences to data quality was insignificant, driving-related movements led to strong shifts in electrode positions. In general, the EEG system used allowed for a fast self-applicability of cap and electrodes. The assessed usability of the system was still acceptable while the wearing comfort decreased strongly over time due to friction and pressure to the head. From these results we conclude that the evaluated system should provide the essential requirements for an application in an autonomous driving context. Nevertheless, further refinement is suggested to reduce shifts of the system due to body movements and increase the headset's usability and wearing comfort. PMID:28293184

Evaluation of a Dry EEG System for Application of Passive Brain-Computer Interfaces in Autonomous Driving.

PubMed

Zander, Thorsten O; Andreessen, Lena M; Berg, Angela; Bleuel, Maurice; Pawlitzki, Juliane; Zawallich, Lars; Krol, Laurens R; Gramann, Klaus

2017-01-01

We tested the applicability and signal quality of a 16 channel dry electroencephalography (EEG) system in a laboratory environment and in a car under controlled, realistic conditions. The aim of our investigation was an estimation how well a passive Brain-Computer Interface (pBCI) can work in an autonomous driving scenario. The evaluation considered speed and accuracy of self-applicability by an untrained person, quality of recorded EEG data, shifts of electrode positions on the head after driving-related movements, usability, and complexity of the system as such and wearing comfort over time. An experiment was conducted inside and outside of a stationary vehicle with running engine, air-conditioning, and muted radio. Signal quality was sufficient for standard EEG analysis in the time and frequency domain as well as for the use in pBCIs. While the influence of vehicle-induced interferences to data quality was insignificant, driving-related movements led to strong shifts in electrode positions. In general, the EEG system used allowed for a fast self-applicability of cap and electrodes. The assessed usability of the system was still acceptable while the wearing comfort decreased strongly over time due to friction and pressure to the head. From these results we conclude that the evaluated system should provide the essential requirements for an application in an autonomous driving context. Nevertheless, further refinement is suggested to reduce shifts of the system due to body movements and increase the headset's usability and wearing comfort.

Comparison of quantitative EEG characteristics of quiet and active sleep in newborns.

PubMed

Paul, Karel; Krajca, Vladimír; Roth, Zdenek; Melichar, Jan; Petránek, Svojmil

2003-11-01

The aim of the present study was to verify whether the proposed method of computer-supported EEG analysis is able to differentiate the EEG activity in quiet sleep (QS) from that in active sleep (AS) in newborns. A quantitative description of the neonatal EEG may contribute to a more exact evaluation of the functional state of the brain, as well as to a refinement of diagnostics of brain dysfunction manifesting itself frequently as 'dysrhythmia' or 'dysmaturity'. Twenty-one healthy newborns (10 full-term and 11 pre-term) were examined polygraphically (EEG-eight channels, respiration, ECG, EOG and EMG) in the course of sleep. From each EEG record, two 5-min samples (one from QS and one from AS) were subject to an off-line computerized analysis. The obtained data were averaged with respect to the sleep state and to the conceptional age. The number of variables was reduced by means of factor analysis. All factors identified by factor analysis were highly significantly influenced by sleep states in both developmental periods. Likewise, a comparison of the measured variables between QS and AS revealed many statistically significant differences. The variables describing (a) the number and length of quasi-stationary segments, (b) voltage and (c) power in delta and theta bands contributed to the greatest degree to the differentiation of EEGs between both sleep states. The presented method of the computerized EEG analysis which has good discriminative potential is adequately sensitive and describes the neonatal EEG with convenient accuracy.

A new ICA-based fingerprint method for the automatic removal of physiological artifacts from EEG recordings.

PubMed

Tamburro, Gabriella; Fiedler, Patrique; Stone, David; Haueisen, Jens; Comani, Silvia

2018-01-01

EEG may be affected by artefacts hindering the analysis of brain signals. Data-driven methods like independent component analysis (ICA) are successful approaches to remove artefacts from the EEG. However, the ICA-based methods developed so far are often affected by limitations, such as: the need for visual inspection of the separated independent components (subjectivity problem) and, in some cases, for the independent and simultaneous recording of the inspected artefacts to identify the artefactual independent components; a potentially heavy manipulation of the EEG signals; the use of linear classification methods; the use of simulated artefacts to validate the methods; no testing in dry electrode or high-density EEG datasets; applications limited to specific conditions and electrode layouts. Our fingerprint method automatically identifies EEG ICs containing eyeblinks, eye movements, myogenic artefacts and cardiac interference by evaluating 14 temporal, spatial, spectral, and statistical features composing the IC fingerprint. Sixty-two real EEG datasets containing cued artefacts are recorded with wet and dry electrodes (128 wet and 97 dry channels). For each artefact, 10 nonlinear SVM classifiers are trained on fingerprints of expert-classified ICs. Training groups include randomly chosen wet and dry datasets decomposed in 80 ICs. The classifiers are tested on the IC-fingerprints of different datasets decomposed into 20, 50, or 80 ICs. The SVM performance is assessed in terms of accuracy, False Omission Rate (FOR), Hit Rate (HR), False Alarm Rate (FAR), and sensitivity ( p ). For each artefact, the quality of the artefact-free EEG reconstructed using the classification of the best SVM is assessed by visual inspection and SNR. The best SVM classifier for each artefact type achieved average accuracy of 1 (eyeblink), 0.98 (cardiac interference), and 0.97 (eye movement and myogenic artefact). Average classification sensitivity (p) was 1 (eyeblink), 0.997 (myogenic artefact), 0.98 (eye movement), and 0.48 (cardiac interference). Average artefact reduction ranged from a maximum of 82% for eyeblinks to a minimum of 33% for cardiac interference, depending on the effectiveness of the proposed method and the amplitude of the removed artefact. The performance of the SVM classifiers did not depend on the electrode type, whereas it was better for lower decomposition levels (50 and 20 ICs). Apart from cardiac interference, SVM performance and average artefact reduction indicate that the fingerprint method has an excellent overall performance in the automatic detection of eyeblinks, eye movements and myogenic artefacts, which is comparable to that of existing methods. Being also independent from simultaneous artefact recording, electrode number, type and layout, and decomposition level, the proposed fingerprint method can have useful applications in clinical and experimental EEG settings.

A new ICA-based fingerprint method for the automatic removal of physiological artifacts from EEG recordings

PubMed Central

Tamburro, Gabriella; Fiedler, Patrique; Stone, David; Haueisen, Jens

2018-01-01

Background EEG may be affected by artefacts hindering the analysis of brain signals. Data-driven methods like independent component analysis (ICA) are successful approaches to remove artefacts from the EEG. However, the ICA-based methods developed so far are often affected by limitations, such as: the need for visual inspection of the separated independent components (subjectivity problem) and, in some cases, for the independent and simultaneous recording of the inspected artefacts to identify the artefactual independent components; a potentially heavy manipulation of the EEG signals; the use of linear classification methods; the use of simulated artefacts to validate the methods; no testing in dry electrode or high-density EEG datasets; applications limited to specific conditions and electrode layouts. Methods Our fingerprint method automatically identifies EEG ICs containing eyeblinks, eye movements, myogenic artefacts and cardiac interference by evaluating 14 temporal, spatial, spectral, and statistical features composing the IC fingerprint. Sixty-two real EEG datasets containing cued artefacts are recorded with wet and dry electrodes (128 wet and 97 dry channels). For each artefact, 10 nonlinear SVM classifiers are trained on fingerprints of expert-classified ICs. Training groups include randomly chosen wet and dry datasets decomposed in 80 ICs. The classifiers are tested on the IC-fingerprints of different datasets decomposed into 20, 50, or 80 ICs. The SVM performance is assessed in terms of accuracy, False Omission Rate (FOR), Hit Rate (HR), False Alarm Rate (FAR), and sensitivity (p). For each artefact, the quality of the artefact-free EEG reconstructed using the classification of the best SVM is assessed by visual inspection and SNR. Results The best SVM classifier for each artefact type achieved average accuracy of 1 (eyeblink), 0.98 (cardiac interference), and 0.97 (eye movement and myogenic artefact). Average classification sensitivity (p) was 1 (eyeblink), 0.997 (myogenic artefact), 0.98 (eye movement), and 0.48 (cardiac interference). Average artefact reduction ranged from a maximum of 82% for eyeblinks to a minimum of 33% for cardiac interference, depending on the effectiveness of the proposed method and the amplitude of the removed artefact. The performance of the SVM classifiers did not depend on the electrode type, whereas it was better for lower decomposition levels (50 and 20 ICs). Discussion Apart from cardiac interference, SVM performance and average artefact reduction indicate that the fingerprint method has an excellent overall performance in the automatic detection of eyeblinks, eye movements and myogenic artefacts, which is comparable to that of existing methods. Being also independent from simultaneous artefact recording, electrode number, type and layout, and decomposition level, the proposed fingerprint method can have useful applications in clinical and experimental EEG settings. PMID:29492336

Electroencephalogram–Electromyography Coupling Analysis in Stroke Based on Symbolic Transfer Entropy

PubMed Central

Gao, Yunyuan; Ren, Leilei; Li, Rihui; Zhang, Yingchun

2018-01-01

The coupling strength between electroencephalogram (EEG) and electromyography (EMG) signals during motion control reflects the interaction between the cerebral motor cortex and muscles. Therefore, neuromuscular coupling characterization is instructive in assessing motor function. In this study, to overcome the limitation of losing the characteristics of signals in conventional time series symbolization methods, a variable scale symbolic transfer entropy (VS-STE) analysis approach was proposed for corticomuscular coupling evaluation. Post-stroke patients (n = 5) and healthy volunteers (n = 7) were recruited and participated in various tasks (left and right hand gripping, elbow bending). The proposed VS-STE was employed to evaluate the corticomuscular coupling strength between the EEG signal measured from the motor cortex and EMG signal measured from the upper limb in both the time-domain and frequency-domain. Results showed a greater strength of the bi-directional (EEG-to-EMG and EMG-to-EEG) VS-STE in post-stroke patients compared to healthy controls. In addition, the strongest EEG–EMG coupling strength was observed in the beta frequency band (15–35 Hz) during the upper limb movement. The predefined coupling strength of EMG-to-EEG in the affected side of the patient was larger than that of EEG-to-EMG. In conclusion, the results suggested that the corticomuscular coupling is bi-directional, and the proposed VS-STE can be used to quantitatively characterize the non-linear synchronization characteristics and information interaction between the primary motor cortex and muscles. PMID:29354091

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.

Feature Extraction with GMDH-Type Neural Networks for EEG-Based Person Identification.

PubMed

Schetinin, Vitaly; Jakaite, Livija; Nyah, Ndifreke; Novakovic, Dusica; Krzanowski, Wojtek

2018-08-01

The brain activity observed on EEG electrodes is influenced by volume conduction and functional connectivity of a person performing a task. When the task is a biometric test the EEG signals represent the unique "brain print", which is defined by the functional connectivity that is represented by the interactions between electrodes, whilst the conduction components cause trivial correlations. Orthogonalization using autoregressive modeling minimizes the conduction components, and then the residuals are related to features correlated with the functional connectivity. However, the orthogonalization can be unreliable for high-dimensional EEG data. We have found that the dimensionality can be significantly reduced if the baselines required for estimating the residuals can be modeled by using relevant electrodes. In our approach, the required models are learnt by a Group Method of Data Handling (GMDH) algorithm which we have made capable of discovering reliable models from multidimensional EEG data. In our experiments on the EEG-MMI benchmark data which include 109 participants, the proposed method has correctly identified all the subjects and provided a statistically significant ([Formula: see text]) improvement of the identification accuracy. The experiments have shown that the proposed GMDH method can learn new features from multi-electrode EEG data, which are capable to improve the accuracy of biometric identification.

Intracranial EEG fluctuates over months after implanting electrodes in human brain

NASA Astrophysics Data System (ADS)

Ung, Hoameng; Baldassano, Steven N.; Bink, Hank; Krieger, Abba M.; Williams, Shawniqua; Vitale, Flavia; Wu, Chengyuan; Freestone, Dean; Nurse, Ewan; Leyde, Kent; Davis, Kathryn A.; Cook, Mark; Litt, Brian

2017-10-01

Objective. Implanting subdural and penetrating electrodes in the brain causes acute trauma and inflammation that affect intracranial electroencephalographic (iEEG) recordings. This behavior and its potential impact on clinical decision-making and algorithms for implanted devices have not been assessed in detail. In this study we aim to characterize the temporal and spatial variability of continuous, prolonged human iEEG recordings. Approach. Intracranial electroencephalography from 15 patients with drug-refractory epilepsy, each implanted with 16 subdural electrodes and continuously monitored for an average of 18 months, was included in this study. Time and spectral domain features were computed each day for each channel for the duration of each patient’s recording. Metrics to capture post-implantation feature changes and inflexion points were computed on group and individual levels. A linear mixed model was used to characterize transient group-level changes in feature values post-implantation and independent linear models were used to describe individual variability. Main results. A significant decline in features important to seizure detection and prediction algorithms (mean line length, energy, and half-wave), as well as mean power in the Berger and high gamma bands, was observed in many patients over 100 d following implantation. In addition, spatial variability across electrodes declines post-implantation following a similar timeframe. All selected features decreased by 14-50% in the initial 75 d of recording on the group level, and at least one feature demonstrated this pattern in 13 of the 15 patients. Our findings indicate that iEEG signal features demonstrate increased variability following implantation, most notably in the weeks immediately post-implant. Significance. These findings suggest that conclusions drawn from iEEG, both clinically and for research, should account for spatiotemporal signal variability and that properly assessing the iEEG in patients, depending upon the application, may require extended monitoring.

Role of Glutamate Release and Metabotropic Autoreceptors in Seizureogenic Actions of Cholinomimetic Agents

DTIC Science & Technology

2001-10-01

produced by centrally-active cholinomimetic agents and to evaluate possible palliative treatments for central cholinomimetic toxicity. The scope of...REPORT: 10/01/00-09/30/01 AWARD NUMBER: DAMD17-98-1-8617 evaluation of the effects by intracerebral infusion of the organophosphate agent paraoxon on EEG...agents. Previously, we had reported successful induction of seizure-like changes in EEG activity of anesthetized rats following intracerebral infusion

Neurodiagnostic techniques in neonatal critical care.

PubMed

Chang, Taeun; du Plessis, Adre

2012-04-01

This article reviews recent advances in the neurodiagnostic tools available to clinicians practicing in neonatal critical care. The advent of induced mild hypothermia for acute neonatal hypoxic-ischemic encephalopathy in 2005 has been responsible for renewed urgency in the development of precise and reliable neonatal neurodiagnostic techniques. Traditional evaluations of bedside head ultrasounds, head computed tomography scans, and routine electroencephalograms (EEGs) have been upgraded in most tertiary pediatric centers to incorporate protocols for MRI, continuous EEG monitoring with remote bedside access, amplitude-integrated EEG, and near-infrared spectroscopy. Meanwhile, recent studies supporting the association between placental pathology and neonatal brain injury highlight the need for closer examination of the placenta in the neurodiagnostic evaluation of the acutely ill newborn. As the pursuit of more effective neuroprotection moves into the "hypothermia plus" era, the identification, evaluation, and treatment of the neurologically affected newborn in the neonatal intensive care unit has increasing significance.

Mental Stress: Neurophysiology and Its Regulation by Sudarshan Kriya Yoga.

PubMed

Chandra, Sushil; Jaiswal, Amit Kumar; Singh, Ram; Jha, Devendra; Mittal, Alok Prakash

2017-01-01

The present study focuses on analyzing the effects of Sudarshan Kriya yoga (SKY) on EEG as well as ECG signals for stress regulation. To envision the regulation of stress Determination Test (DT) has been used. We have chosen a control group for contriving a cogent comparison that could be corroborated using statistical tests. A total of 20 subjects were taken in the study, of which 10 were allotted to a control group. Electroencephalograph was taken during a DT task, before and after SKY the sky session with 30 days of SKY session given to the experimental group. No SKY was given to the control group. We quantified mental stress using EEG, ECG and DT synergistically and used SKY to regulate it. We observed that alpha band power decreases in the frontal lobe of the brain with increasing mental stress while frontal brain asymmetry decreases with increasing stress tolerance. These EEG, ECG and DT shows a significant decrement in mental stress and improvement in cognitive performance after SKY, indicating SKY as a good alternative of medication for stress management.

Effects of ellagic acid pretreatment on renal functions disturbances induced by global cerebral ischemic-reperfusion in rat.

PubMed

Nejad, Khojasteh Hoseiny; Gharib-Naseri, Mohammad Kazem; Sarkaki, Alireza; Dianat, Mahin; Badavi, Mohammad; Farbood, Yaghoub

2017-01-01

Global cerebral ischemia-reperfusion (GCIR) causes disturbances in brain functions as well as other organs such as kidney. Our aim was to evaluate the protective effects of ellagic acid (EA) on certain renal disfunction after GCIR. Adult male Wistar rats (n=32, 250-300 g) were used. GCIR was induced by bilateral vertebral and common carotid arteries occlusion (4-VO). Animal groups were: 1) received DMSO/saline (10%) as solvent of EA, 2) solvent + GCIR, 3) EA + GCIR, and 4) EA. Under anesthesia with ketamine/xylazine, GCIR was induced (20 and 30 min respectively) in related groups. EA (100 mg/kg, dissolved in DMSO/saline (10%) or solvent was administered (1.5 ml/kg) orally for 10 consecutive days to the related groups. EEG was recorded from NTS in GCIR treated groups. Our data showed that: a) EEG in GCIR treated groups was flattened. b) GCIR reduced GFR ( P <0.01) and pretreatment with EA attenuated this reduction. c) BUN was increased by GCIR ( P <0.001) and pretreatment with EA improved the BUN to normal level. d) Serum creatinine concentration was elevated by GCIR but not significantly, however, in EA+GCIR group serum creatinine was reduced ( P <0.05). e) GCIR induced proteinuria ( P <0.05) but, EA was unable to reduced proteinuria. Results indicate that GCIR impairs certain renal functions and EA as an antioxidant can improve these functions. Our results suggest the possible usefulness of ellagic acid in patients with brain stroke.

The antinociceptive effects of Monechma ciliatum and changes in EEG waves following oral and intrathecal administration in rats

NASA Astrophysics Data System (ADS)

Meraiyebu, Ajibola B.; Adelaiye, Alexander B.; O, Odeh S.

2010-02-01

The research work was carried out to study the effect of Oral and Intrathecal Monechma Ciliatum on antinociception and EEG readings in Wistar Rats. Traditionally the extract is given to women in labour believed to reduce pain and ease parturition, though past works show that it has oesteogenic and oxytotic effects. The rats were divided into 5 major groups. Group 1 served as oral control group while groups 2 and 3 served as oral experimental groups and were treated with 500mg/kg and 1000mg/kg monechma ciliatum respectively. Group 4 served as intrathecal control group treated with intrathecal dextrose and group 5 received 1000mg/kg Monechma Ciliatrum intrathecally. The antinociceptive effect was analysed using a Von Frey's aesthesiometer. Monechma Ciliatum showed significant antinociceptive effect both orally and intrathecally, although it had a greater effect orally and during the first 15 minutes of intrathecal administration. EEG readings were also taken for all the groups and there was a decrease in amplitude and an increase in frequency for high dose (1000mg/ml) experimental groups and the mid brain electrodes produced a change from theta waves (3.5 - 7 waves per second) to alpha waves (7.5 - 13 waves per second) as seen in relaxed persons and caused decreased amplitudes and change in distribution seen in beta waves. Properties similarly accentuated by sedativehypnotic drugs.

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.

Topographic Brain Mapping: A Window on Brain Function?

ERIC Educational Resources Information Center

Karniski, Walt M.

1989-01-01

The article reviews the method of topographic mapping of the brain's electrical activity. Multiple electroencephalogram (EEG) electrodes and computerized analysis of the EEG signal are used to generate maps of frequency and voltage (evoked potential). This relatively new technique holds promise in the evaluation of children with behavioral and…

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 spatiotemporal characteristics of sources located in the epileptic focus. The results were validated by standard methods, ensuring good spatial resolution by MRI and SPECT and optimal temporal resolution by intracerebral EEG. Surface EEG can be used to identify different spike clusters and sources of the successive epileptic states. The method that was used in this study will provide physicians with a better understanding of the pathophysiological characteristics of epileptic activities. In particular, this method may be useful for more effective positioning of implantable intracerebral electrodes. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

EEG deficits in chronic marijuana abusers during monitored abstinence: preliminary findings.

PubMed

Herning, Ronald I; Better, Warren; Tate, Kimberly; Cadet, Jean L

2003-05-01

Cognitive, cerebrovascular, and psychiatric impairments have been documented with chronic marijuana users. To better understand the nature and duration of these neurocognitive changes in marijuana abusers, we recorded the resting EEG of 29 abstinent chronic marijuana abusers and 21 control subjects. The marijuana abusers were tested twice: the first evaluation occurred within 72 hours of admission to the inpatient research unit; the second evaluation occurred after 28 to 30 days of monitored abstinence. A three-minute period of EEG was recorded during resting eyes-closed conditions from eight electrodes (F(3), C(3), P(3), O(1), F(4), C(4), P(4), and O(2)). The artifacted EEG was converted to six frequency bands (delta, theta, alpha(1), alpha(2), beta(1), and beta(2)) using a fast Fourier transform. During early abstinence, absolute power was significantly lower (p < 0.05) for the marijuana abusers than for the control subjects for the theta and alpha(1) bands. These reductions in theta and alpha(1) power persisted for 28 days of monitored abstinence. These EEG changes, together with cerebral blood flow deficits, might underlie the cognitive alterations observed in marijuana abusers. Additional research is needed to determine how long these deficits persist during abstinence and if treatment with neuroprotective agents may reverse them.

Study of quadrature FIR filters for extraction of low-frequency instantaneous information in biophysical signals

NASA Astrophysics Data System (ADS)

Arce-Guevara, Valdemar E.; Alba-Cadena, Alfonso; Mendez, Martín O.

Quadrature bandpass filters take a real-valued signal and output an analytic signal from which the instantaneous amplitude and phase can be computed. For this reason, they represent a useful tool to extract time-varying, narrow-band information from electrophysiological signals such as electroencephalogram (EEG) or electrocardiogram. One of the defining characteristics of quadrature filters is its null response to negative frequencies. However, when the frequency band of interest is close to 0 Hz, a careless filter design could let through negative frequencies, producing distortions in the amplitude and phase of the output. In this work, three types of quadrature filters (Ideal, Gabor and Sinusoidal) have been evaluated using both artificial and real EEG signals. For the artificial signals, the performance of each filter was measured in terms of the distortion in amplitude and phase, and sensitivity to noise and bandwidth selection. For the real EEG signals, a qualitative evaluation of the dynamics of the synchronization between two EEG channels was performed. The results suggest that, while all filters under study behave similarly under noise, they differ in terms of their sensitivity to bandwidth choice. In this study, the Sinusoidal filter showed clear advantages for the estimation of low-frequency EEG synchronization.

[Magnetoencephalography in the presurgical evaluation of patients with drug-resistant epilepsy].

PubMed

Koptelova, A M; Arkhipova, N A; Golovteev, A L; Chadaev, V A; Grinenko, O A; Kozlova, A B; Novikova, S I; Stepanenko, A Iu; Melikian, A G; Stroganova, T A

2013-01-01

Magnetoencephalography (MEG) in combination with structural MRI (magnetic source imaging, MSI) plays an increasingly important role as one of the tools for presurgical evaluation of medically intractable focal epilepsy. The aim of the study was to compare the MSI and commonly used video EEG monitoring method (vEEG) in their sensitivity to interictal epileptic discharges (IED) in 22 patients with drug resistant epilepsy. Furthermore, the detection and localization results obtained by both methods were verified using the data of electrocorticography (ECoG) and postsurgical outcome in 13 patients who underwent invasive EEG monitoring and surgery. The results showed that MSI was superior to vEEC in terms of sensitivity to IED with difference in sensitivity of 22%. The data also suggested that MSI superiority to vEEG in detecting epileptic discharges might, at least partly, arise from better MEG responsiveness to epileptic events coming from the medial, opercular and basal aspects of cortical lobes. MSI localization estimates were in the same cortical lobe and at the same lobar aspects as the epileptic foci detected by ECoG in all patients. Thus, magnetic source imaging can provide critical localization information that is not available when other noninvasive methods, such as vEEG and MRI, are used.

Wake High-Density Electroencephalographic Spatiospectral Signatures of Insomnia

PubMed Central

Colombo, Michele A.; Ramautar, Jennifer R.; Wei, Yishul; Gomez-Herrero, Germán; Stoffers, Diederick; Wassing, Rick; Benjamins, Jeroen S.; Tagliazucchi, Enzo; van der Werf, Ysbrand D.; Cajochen, Christian; Van Someren, Eus J.W.

2016-01-01

Study Objectives: Although daytime complaints are a defining characteristic of insomnia, most EEG studies evaluated sleep only. We used high-density electroencephalography to investigate wake resting state oscillations characteristic of insomnia disorder (ID) at a fine-grained spatiospectral resolution. Methods: A case-control assessment during eyes open (EO) and eyes closed (EC) was performed in a laboratory for human physiology. Participants (n = 94, 74 female, 21–70 y) were recruited through www.sleepregistry.nl: 51 with ID, according to DSM-5 and 43 matched controls. Exclusion criteria were any somatic, neurological or psychiatric condition. Group differences in the spectral power topographies across multiple frequencies (1.5 to 40 Hz) were evaluated using permutation-based inference with Threshold-Free Cluster-Enhancement, to correct for multiple comparisons. Results: As compared to controls, participants with ID showed less power in a narrow upper alpha band (11–12.7 Hz, peak: 11.7 Hz) over bilateral frontal and left temporal regions during EO, and more power in a broad beta frequency range (16.3–40 Hz, peak: 19 Hz) globally during EC. Source estimates suggested global rather than cortically localized group differences. Conclusions: The widespread high power in a broad beta band reported previously during sleep in insomnia is present as well during eyes closed wakefulness, suggestive of a round-the-clock hyperarousal. Low power in the upper alpha band during eyes open is consistent with low cortical inhibition and attentional filtering. The fine-grained HD-EEG findings suggest that, while more feasible than PSG, wake EEG of short duration with a few well-chosen electrodes and frequency bands, can provide valuable features of insomnia. Citation: Colombo MA, Ramautar JR, Wei Y, Gomez-Herrero G, Stoffers D, Wassing R, Benjamins JS, Tagliazucchi E, van der Werf YD, Cajochen C, Van Someren EJW. Wake high-density electroencephalographic spatiospectral signatures of insomnia. SLEEP 2016;39(5):1015–1027. PMID:26951395

The role of virtual reality in improving motor performance as revealed by EEG: a randomized clinical trial.

PubMed

Calabrò, Rocco Salvatore; Naro, Antonino; Russo, Margherita; Leo, Antonino; De Luca, Rosaria; Balletta, Tina; Buda, Antonio; La Rosa, Gianluca; Bramanti, Alessia; Bramanti, Placido

2017-06-07

Many studies have demonstrated the usefulness of repetitive task practice by using robotic-assisted gait training (RAGT) devices, including Lokomat, for the treatment of lower limb paresis. Virtual reality (VR) has proved to be a valuable tool to improve neurorehabilitation training. The aim of our pilot randomized clinical trial was to understand the neurophysiological basis of motor function recovery induced by the association between RAGT (by using Lokomat device) and VR (an animated avatar in a 2D VR) by studying electroencephalographic (EEG) oscillations. Twenty-four patients suffering from a first unilateral ischemic stroke in the chronic phase were randomized into two groups. One group performed 40 sessions of Lokomat with VR (RAGT + VR), whereas the other group underwent Lokomat without VR (RAGT-VR). The outcomes (clinical, kinematic, and EEG) were measured before and after the robotic intervention. As compared to the RAGT-VR group, all the patients of the RAGT + VR group improved in the Rivermead Mobility Index and Tinetti Performance Oriented Mobility Assessment. Moreover, they showed stronger event-related spectral perturbations in the high-γ and β bands and larger fronto-central cortical activations in the affected hemisphere. The robotic-based rehabilitation combined with VR in patients with chronic hemiparesis induced an improvement in gait and balance. EEG data suggest that the use of VR may entrain several brain areas (probably encompassing the mirror neuron system) involved in motor planning and learning, thus leading to an enhanced motor performance. Retrospectively registered in Clinical Trials on 21-11-2016, n. NCT02971371 .

Evaluating the event-related synchronization and desynchronization by means of a statistical frequency test.

PubMed

Miranda de Sá, Antonio Mauricio F L; Infantosi, Antonio Fernando C; Lazarev, Vladimir V

2007-01-01

In the present work, a commonly used index for evaluating the Event-Related Synchronization and Desynchronization (ERS/ERD) in the EEG was expressed as a function of the Spectral F-Test (SFT), which is a statistical test for assessing if two sample spectra are from populations with identical theoretical spectra. The sampling distribution of SFT has been derived, allowing hence ERS/ERD to be evaluated under a statistical basis. An example of the technique was also provided in the EEG signals from 10 normal subjects during intermittent photic stimulation.

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.

Hybrid ICA-Regression: Automatic Identification and Removal of Ocular Artifacts from Electroencephalographic Signals.

PubMed

Mannan, Malik M Naeem; Jeong, Myung Y; Kamran, Muhammad A

2016-01-01

Electroencephalography (EEG) is a portable brain-imaging technique with the advantage of high-temporal resolution that can be used to record electrical activity of the brain. However, it is difficult to analyze EEG signals due to the contamination of ocular artifacts, and which potentially results in misleading conclusions. Also, it is a proven fact that the contamination of ocular artifacts cause to reduce the classification accuracy of a brain-computer interface (BCI). It is therefore very important to remove/reduce these artifacts before the analysis of EEG signals for applications like BCI. In this paper, a hybrid framework that combines independent component analysis (ICA), regression and high-order statistics has been proposed to identify and eliminate artifactual activities from EEG data. We used simulated, experimental and standard EEG signals to evaluate and analyze the effectiveness of the proposed method. Results demonstrate that the proposed method can effectively remove ocular artifacts as well as it can preserve the neuronal signals present in EEG data. A comparison with four methods from literature namely ICA, regression analysis, wavelet-ICA (wICA), and regression-ICA (REGICA) confirms the significantly enhanced performance and effectiveness of the proposed method for removal of ocular activities from EEG, in terms of lower mean square error and mean absolute error values and higher mutual information between reconstructed and original EEG.

Hybrid ICA—Regression: Automatic Identification and Removal of Ocular Artifacts from Electroencephalographic Signals

PubMed Central

Mannan, Malik M. Naeem; Jeong, Myung Y.; Kamran, Muhammad A.

2016-01-01

Electroencephalography (EEG) is a portable brain-imaging technique with the advantage of high-temporal resolution that can be used to record electrical activity of the brain. However, it is difficult to analyze EEG signals due to the contamination of ocular artifacts, and which potentially results in misleading conclusions. Also, it is a proven fact that the contamination of ocular artifacts cause to reduce the classification accuracy of a brain-computer interface (BCI). It is therefore very important to remove/reduce these artifacts before the analysis of EEG signals for applications like BCI. In this paper, a hybrid framework that combines independent component analysis (ICA), regression and high-order statistics has been proposed to identify and eliminate artifactual activities from EEG data. We used simulated, experimental and standard EEG signals to evaluate and analyze the effectiveness of the proposed method. Results demonstrate that the proposed method can effectively remove ocular artifacts as well as it can preserve the neuronal signals present in EEG data. A comparison with four methods from literature namely ICA, regression analysis, wavelet-ICA (wICA), and regression-ICA (REGICA) confirms the significantly enhanced performance and effectiveness of the proposed method for removal of ocular activities from EEG, in terms of lower mean square error and mean absolute error values and higher mutual information between reconstructed and original EEG. PMID:27199714

Epileptic seizure detection in EEG signal using machine learning techniques.

PubMed

Jaiswal, Abeg Kumar; Banka, Haider

2018-03-01

Epilepsy is a well-known nervous system disorder characterized by seizures. Electroencephalograms (EEGs), which capture brain neural activity, can detect epilepsy. Traditional methods for analyzing an EEG signal for epileptic seizure detection are time-consuming. Recently, several automated seizure detection frameworks using machine learning technique have been proposed to replace these traditional methods. The two basic steps involved in machine learning are feature extraction and classification. Feature extraction reduces the input pattern space by keeping informative features and the classifier assigns the appropriate class label. In this paper, we propose two effective approaches involving subpattern based PCA (SpPCA) and cross-subpattern correlation-based PCA (SubXPCA) with Support Vector Machine (SVM) for automated seizure detection in EEG signals. Feature extraction was performed using SpPCA and SubXPCA. Both techniques explore the subpattern correlation of EEG signals, which helps in decision-making process. SVM is used for classification of seizure and non-seizure EEG signals. The SVM was trained with radial basis kernel. All the experiments have been carried out on the benchmark epilepsy EEG dataset. The entire dataset consists of 500 EEG signals recorded under different scenarios. Seven different experimental cases for classification have been conducted. The classification accuracy was evaluated using tenfold cross validation. The classification results of the proposed approaches have been compared with the results of some of existing techniques proposed in the literature to establish the claim.

Quantitative change of EEG and respiration signals during mindfulness meditation.

PubMed

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

2014-05-14

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

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

Electroencephalographic reactivity testing in unconscious patients: a systematic review of methods and definitions.

PubMed

Admiraal, M M; van Rootselaar, A-F; Horn, J

2017-02-01

Electroencephalographic (EEG) reactivity testing is often presented as a clear-cut element of electrophysiological testing. Absence of EEG reactivity is generally considered an indicator of poor outcome, especially in patients after cardiac arrest. However, guidelines do not clearly describe how to test for reactivity and how to evaluate the results. In a quest for clear guidelines, we performed a systematic review aimed at identifying testing methods and definitions of EEG reactivity. We systematically searched the literature between 1970 and May 2016. Methodological quality of the studies was assessed using the QUality In Prognostic Studies tool. Quality of the descriptions of stimulus protocol and reactivity definition was rated on a four-category grading scale based on reproducibility. We found that protocols for EEG reactivity testing vary greatly and descriptions of protocols are almost never replicable. Furthermore, replicable definitions of presence or absence of EEG reactivity are never provided. In order to draw firm conclusions on EEG reactivity as a prognostic factor, future studies should include a precise stimulation protocol and reactivity definition to facilitate guideline formation. © 2016 EAN.

Quantitative change of EEG and respiration signals during mindfulness meditation

PubMed Central

2014-01-01

Background This study investigates measures of mindfulness meditation (MM) as a mental practice, in which a resting but alert state of mind is maintained. A population of older people with high stress level participated in this study, while electroencephalographic (EEG) and respiration signals were recorded during a MM intervention. The physiological signals during meditation and control conditions were analyzed with signal processing. Methods EEG and respiration data were collected and analyzed on 34 novice meditators after a 6-week meditation intervention. Collected data were analyzed with spectral analysis, phase analysis and classification to evaluate an objective marker for meditation. Results Different frequency bands showed differences in meditation and control conditions. Furthermore, we established a classifier using EEG and respiration signals with a higher accuracy (85%) at discriminating between meditation and control conditions than a classifier using the EEG signal only (78%). Conclusion Support vector machine (SVM) classifier with EEG and respiration feature vector is a viable objective marker for meditation ability. This classifier should be able to quantify different levels of meditation depth and meditation experience in future studies. PMID:24939519

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.

The Discontinuous Galerkin Finite Element Method for Solving the MEG and the Combined MEG/EEG Forward Problem

PubMed Central

Piastra, Maria Carla; Nüßing, Andreas; Vorwerk, Johannes; Bornfleth, Harald; Oostenveld, Robert; Engwer, Christian; Wolters, Carsten H.

2018-01-01

In Electro- (EEG) and Magnetoencephalography (MEG), one important requirement of source reconstruction is the forward model. The continuous Galerkin finite element method (CG-FEM) has become one of the dominant approaches for solving the forward problem over the last decades. Recently, a discontinuous Galerkin FEM (DG-FEM) EEG forward approach has been proposed as an alternative to CG-FEM (Engwer et al., 2017). It was shown that DG-FEM preserves the property of conservation of charge and that it can, in certain situations such as the so-called skull leakages, be superior to the standard CG-FEM approach. In this paper, we developed, implemented, and evaluated two DG-FEM approaches for the MEG forward problem, namely a conservative and a non-conservative one. The subtraction approach was used as source model. The validation and evaluation work was done in statistical investigations in multi-layer homogeneous sphere models, where an analytic solution exists, and in a six-compartment realistically shaped head volume conductor model. In agreement with the theory, the conservative DG-FEM approach was found to be superior to the non-conservative DG-FEM implementation. This approach also showed convergence with increasing resolution of the hexahedral meshes. While in the EEG case, in presence of skull leakages, DG-FEM outperformed CG-FEM, in MEG, DG-FEM achieved similar numerical errors as the CG-FEM approach, i.e., skull leakages do not play a role for the MEG modality. In particular, for the finest mesh resolution of 1 mm sources with a distance of 1.59 mm from the brain-CSF surface, DG-FEM yielded mean topographical errors (relative difference measure, RDM%) of 1.5% and mean magnitude errors (MAG%) of 0.1% for the magnetic field. However, if the goal is a combined source analysis of EEG and MEG data, then it is highly desirable to employ the same forward model for both EEG and MEG data. Based on these results, we conclude that the newly presented conservative DG-FEM can at least complement and in some scenarios even outperform the established CG-FEM approaches in EEG or combined MEG/EEG source analysis scenarios, which motivates a further evaluation of DG-FEM for applications in bioelectromagnetism. PMID:29456487

Psychogenic seizures and frontal disconnection: EEG synchronisation study.

PubMed

Knyazeva, Maria G; Jalili, Mahdi; Frackowiak, Richard S; Rossetti, Andrea O

2011-05-01

Psychogenic non-epileptic seizures (PNES) are paroxysmal events that, in contrast to epileptic seizures, are related to psychological causes without the presence of epileptiform EEG changes. Recent models suggest a multifactorial basis for PNES. A potentially paramount, but currently poorly understood factor is the interplay between psychiatric features and a specific vulnerability of the brain leading to a clinical picture that resembles epilepsy. Hypothesising that functional cerebral network abnormalities may predispose to the clinical phenotype, the authors undertook a characterisation of the functional connectivity in PNES patients. The authors analysed the whole-head surface topography of multivariate phase synchronisation (MPS) in interictal high-density EEG of 13 PNES patients as compared with 13 age- and sex-matched controls. MPS mapping reduces the wealth of dynamic data obtained from high-density EEG to easily readable synchronisation maps, which provide an unbiased overview of any changes in functional connectivity associated with distributed cortical abnormalities. The authors computed MPS maps for both Laplacian and common-average-reference EEGs. In a between-group comparison, only patchy, non-uniform changes in MPS survived conservative statistical testing. However, against the background of these unimpressive group results, the authors found widespread inverse correlations between individual PNES frequency and MPS within the prefrontal and parietal cortices. PNES appears to be associated with decreased prefrontal and parietal synchronisation, possibly reflecting dysfunction of networks within these regions.

[EEG-adjusted target-controlled infusion : Propofol target concentration with different doses of remifentanil].

PubMed

Büttner, N; Schultz, B; Grouven, U; Schultz, A

2010-02-01

The aim of this study was to examine to what extent the use of electroencephalography (EEG) monitoring leads to an adaptation of the target-controlled infusion (TCI) concentration of propofol during propofol anaesthesia with different doses of remifentanil. With ethics committee approval 60 patients (27-69 years old) with American Society of Anesthesiologists classification (ASA) I-III received anaesthestics with propofol (TCI, Diprifusor, AstraZeneca, Wedel, Deutschland) and 0.2, 0.4, or 0.6 microg/kg body weight remifentanil, respectively (groups 1-3). Anaesthesia was maintained at a level of deep hypnosis (EEG stages D(2)/E(0), EEG monitor: Narcotrend, version 2.0/5.0, manufacturer: MT MonitorTechnik, Bad Bramstedt, Germany). During the steady state the propofol concentration in groups 1-3 was 3.02+/-0.86, 1.93+/-0.53 and 1.60+/-0.55 microg/ml, respectively (p<0.001). Women had a higher propofol consumption than men (p<0.05). Dreams during anaesthesia were more often reported by women than by men (p<0.05). The need for postoperative analgesia decreased with an increasing intraoperative remifentanil dose (p<0.05). The study demonstrates that remifentanil has both analgetic and hypnotic effects. With increasing remifentanil dose the propofol requirement decreased and in this context EEG monitoring is useful to adapt the target concentrations of propofol to the patients' age and gender.

Plastic changes following imitation-based speech and language therapy for aphasia: a high-density sleep EEG study.

PubMed

Sarasso, Simone; Määttä, Sara; Ferrarelli, Fabio; Poryazova, Rositsa; Tononi, Giulio; Small, Steven L

2014-02-01

BACKGROUND OBJECTIVE: measurement of plastic brain changes induced by a novel rehabilitative approach is a key requirement for validating its biological rationale linking the potential therapeutic gains to the changes in brain physiology. Based on an emerging notion linking cortical plastic changes to EEG sleep slow-wave activity (SWA) regulation, we aimed to assess the acute plastic changes induced by an imitation-based speech therapy in individuals with aphasia by comparing sleep SWA changes before and after therapy. A total of 13 left-hemispheric stroke patients underwent language assessment with the Western Aphasia Battery (WAB) before and after 2 consecutive high-density (hd) EEG sleep recordings interleaved by a daytime session of imitation-based speech therapy (Intensive Mouth Imitation and Talking for Aphasia Therapeutic Effects [IMITATE]). This protocol is thought to stimulate bilateral connections between the inferior parietal lobule and the ventral premotor areas. A single exposure to IMITATE resulted in increases in local EEG SWA during subsequent sleep over the same regions predicted by the therapeutic rationale, particularly over the right hemisphere (unaffected by the lesion). Furthermore, changes in SWA over the left-precentral areas predicted changes in WAB repetition scores in our group, supporting the role of perilesional areas in predicting positive functional responses. Our results suggest that SWA changes occurring in brain areas activated during imitation-based aphasia therapy may reflect the acute plastic changes induced by this intervention. Further testing will be needed to evaluate SWA as a non-invasive assessment of changes induced by the therapy and as a predictor of positive long-term clinical outcome.