Full Text Available The case history and management of a 26 years old adult is reported who presented with an unusual symptom of sexual experience, in the background of symptoms of depression and anxiety; had been given multiple diagnoses at multiple points of time and treated with multiple medications. On establishment of rapport, he revealed details of his unusual experiences, which had been unexplored. When he was about 11 years and ten months, he sat next to a lady; he could perceive a particular experience for the first time in his life. And next time with another lady too he perceived a particular type of smell (“madaka gandha” meaning an intoxicating smell along with the other feelings. He began to have these feelings whenever he was in the vicinity of a female except his mother and sister. The smell reminded him of roses vaguely and was at least ten to 20 times more pleasurable than an orgasm that he got with masturbation. These feelings were more pleasurable than he could ever imagine and happened always with the presence of a female in the vicinity. This was never associated with periods of unresponsiveness or any other history suggestive of seizures. He titled the experience as “anubhoothi”. These experiences occurred on a regular basis for a period of ten months following which there was abrupt cessation of the same, without any intervention. Later he developed all symptoms. A coordinated management plan spearheaded by the multi-disciplinary treatment team could bring down his symptoms as well as make him functional. This case indicates that it is essential to explore abnormalities of experiences to understand the psychopathology and plan management.
of preliminary studies found interesting to set upan EEG composed of representatives from industry and a researcher. Inthe paper some general research methods pertinent to the areaindustrial management is discussed. The EEG concept is introduced andcharacterised in comparison with the other methods. EEG...... activities aredescribed and a tentative coupling to the phases in a research processis proposed. Following this is a discussion of methodological andquality requirements. It is considered how EEG activities couldpossible contribute to an industrial rooted research. The paper endsup looking at future research......The intention of this paper is to clarify if and how an ExperienceExchange Group (EEG) can be involved in a research process in the areaof industrial management. For exemplification of the topic an ongoingresearch in global manufacturing is referred to. In this research itwas after a series...
... brain dead. EEG cannot be used to measure intelligence. Normal Results Brain electrical activity has a certain ... 2018, A.D.A.M., Inc. Duplication for commercial use must be authorized in writing by ADAM ...
Sep 3, 2017 ... However, very few studies have examined the use of EEG in developing countries, including Ni- ... of evoked potentials from brain neurons, referred to as .... Percentage. Gender. Male. 89. 62.7. Female. 53. 37.3. Age. 0-10. 59.
Bozkurt, Gokhan; Ayhan, Selim; Dericioglu, Nese; Saygi, Serap; Akalan, Nejat
The potential complications of the subdural electrode implantation providing identification of the seizure focus and direct stimulation of the cerebral cortex for defining the eloquent cortical areas are epidural and subdural hematoma, cortical contusions, infection, brain edema, raised intracranial pressure, CSF leakage, and venous infarction have been previously reported in the literature. To present the first case of subelectrode hematoma without subdural component that was detected during invasive EEG monitoring after subdural electrode implantation. A 19-year-old female with drug resistant seizures was decided to undergo invasive monitoring with subdural electrodes. While good quality recordings had been initially obtained from all electrodes placed on the right parietal convexity, no cerebral cortical activity could be obtained from one electrode 2 days after the first operation. Explorative surgery revealed a circumscribed subelectrode hematoma without a subdural component. Awareness of the potential complications of subdural electrode implantation and close follow-up of the clinical findings of the patient are of highest value for early detection and successful management.
Full Text Available In the modern world of automation, biological signals, especially Electroencephalogram (EEG is gaining wide attention as a source of biometric information. Eye-blinks and movement of the eyeballs produce electrical signals (contaminate the EEG signals that are collectively known as ocular artifacts. These noise signals are required to be separated from the EEG signals to obtain the accurate results. This paper reports an experiment of ocular artifacts elimination from EEG signal using blind source separation algorithm based on independent component analysis and principal component analysis. EEG signals are recorded on three conditions, which are normal conditions, closed eyes, and blinked eyes. After processing, the dominant frequency of EEG signals in the range of 12-14 Hz either on normal, closed, and blinked eyes conditions is obtained.
of preliminary studies found interesting to set up an EEG composed of representatives from industry and a researcher. In the paper some general research methods pertinent to the area industrial management are discussed. The EEG concept is introduced and characterised in comparison with the other methods. EEG...... activities are described and a tentative coupling to the phases in a research process is proposed. Following this is a discussion of methodological and quality requirements. It is considered how EEG activities could possibly contribute to an industrial rooted research. The paper ends up looking at future......The intention of this paper is to clarify if and how an Experience Exchange Group(EEG) can be involved in a research process in the area of industrial management. For exemplification of the topic an ongoing research in global manufacturing is referred to. In this research it was after a series...
Operational experience of nuclear power plants can be used to great advantage to enhance safety performance provided adequate measures are in place to collect and analyse it and to ensure that the conclusions drawn are acted upon. Feedback of operating experience is thus an extremely important tool to ensure high standards of safety in operational nuclear power plants and to improve the capability to prevent serious accidents and to learn from minor deviations and equipment failures - which can serve as early warnings -to prevent even minor events from occurring. Mechanisms also need to be developed to ensure that operating experience is shared both nationally as well as internationally. The operating experience feedback process needs to be fully and effectively established within the nuclear power plant, the utility, the regulatory organization as well as in other institutions such as technical support organizations and designers. The main purpose of this publication is to reflect the international consensus as to the general principles and practices in the operational safety experience feedback process. The examples of national practices for the whole or for particular parts of the process are given in annexes. The publication complements the IAEA Safety Series No.93 ''Systems for Reporting Unusual Events in Nuclear Power Plants'' (1989) and may also give a general guidance for Member States in fulfilling their obligations stipulated in the Nuclear Safety Convention. Figs, tabs
Operational experience of nuclear power plants can be used to great advantage to enhance safety performance provided adequate measures are in place to collect and analyse it and to ensure that the conclusions drawn are acted upon. Feedback of operating experience is thus an extremely important tool to ensure high standards of safety in operational nuclear power plants and to improve the capability to prevent serious accidents and to learn from minor deviations and equipment failures - which can serve as early warnings -to prevent even minor events from occurring. Mechanisms also need to be developed to ensure that operating experience is shared both nationally as well as internationally. The operating experience feedback process needs to be fully and effectively established within the nuclear power plant, the utility, the regulatory organization as well as in other institutions such as technical support organizations and designers. The main purpose of this publication is to reflect the international consensus as to the general principles and practices in the operational safety experience feedback process. The examples of national practices for the whole or for particular parts of the process are given in annexes. The publication complements the IAEA Safety Series No.93 ``Systems for Reporting Unusual Events in Nuclear Power Plants`` (1989) and may also give a general guidance for Member States in fulfilling their obligations stipulated in the Nuclear Safety Convention. Figs, tabs.
Nežádal, Tomáš; Hovorka, Jiří; Herman, Erik; Němcová, Iveta; Bajaček, Michal; Stichová, Eva
The aim of our study was to assess the number of psychogenic non-epileptic seizures (PNES) in our patients with a refractory seizure disorder, to determine the 'typical' PNES semiology using video-EEG monitoring and describe other PNES parameters. We evaluated prospectively 596 patients with pharmacoresistant seizures. All these patients underwent continuous video-EEG monitoring. In consenting patients, we used suggestive seizure provocation. We assessed seizure semiology, interictal EEG, brain MRI, psychiatric co-morbidities, personality profiles, and seizure outcome. In the sample of 596 monitored patients, we detected 111 (19.3%) patients with PNES. Of the 111 patients with PNES, 86.5% had spontaneous and 76.5% had provoked seizures. The five most typical symptoms were: initially closed eyelids (67.6%), rapid tremor (47.7%), asynchronous limb movement (37.8%), preictal pseudosleep (33.3%), and side-to-side head movement (32.4%). Interictal EEG was rated as abnormal in 46.2% and with epileptiform abnormality in 9%. Brain MRI was abnormal in 32 (28.8%) patients. Personality disorders (46.8%), anxiety (39.6%), and depression (12.6%) were the most frequent additional psychiatric co-morbidities. PNES outcome after at least 2 years is reported; 22.5% patients was seizure-free; one-third had markedly reduced seizure frequency. We have not seen any negative impact of the provocative testing on the seizure outcome. Video-EEG monitoring with suggestive seizure provocation supported by clinical psychiatric and psychological evaluation significantly contributes to the correct PNES diagnosis, while interictal EEG and brain MRI are frequently abnormal. Symptoms typical for PNES, as opposed to epileptic seizures, could be distinguished.
van Loon, Anouk M; Scholte, H Steven; van Gaal, Simon; van der Hoort, Björn J J; Lamme, Victor A F
Consciousness can be manipulated in many ways. Here, we seek to understand whether two such ways, visual masking and pharmacological intervention, share a common pathway in manipulating visual consciousness. We recorded EEG from human participants who performed a backward-masking task in which they
Yang, Liu; Ma, Rui; Zhang, H Michael; Guan, Wei; Jiang, Shixiong
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.
van Elk, M.
In the present EEG study a placebo God Helmet was used to induce spiritual experiences in the lab, by boosting the expectations and suggestibility of participants. At a behavioral level it was found that instructions regarding whether the helmet was turned on or off were not effective, but that
Full Text Available Background: Classical duplications may present along any part of gastrointestinal tract (GIT from mouth to anus. Atypical or unusual rare varieties of GIT duplications may also occur, but with different anatomical features. Materials and Methods: We reviewed our 5-year record (February 2008-January 2013 to describe clinical profile of unusual GIT duplications in neonates and small infants. Results: Three patients with atypical variety of GIT duplications were managed in our department during this tenure. Two were females and one male. Age was ranged between 11 days and 2 months. All patients presented with massive abdominal distension causing respiratory embarrassment in two of them. In all patients, the pre-operative differential diagnoses also included GIT duplication cysts. Computerized tomography (CT scan showed single huge cyst in one and multiple cysts in two patients. In one patient the CT scan also depicted a thoracic cyst in relation to posterior mediastinum. At operation, one patient had colonic tubular duplication cyst along with another isolated duplication cyst, the second case had a tubular duplication cyst of ileum with its segmental dilatation, and in the third case two isolated duplications were found. Duplication cysts were excised along with mucosal stripping in one patient, cyst excision and intestinal resection and anastomosis in one patient, and only cysts excision in one. All patients did well post-operatively. Conclusion: We presented unusual GIT duplications. These duplications are managed on similar lines as classical duplications with good prognosis when dealt early.
Neha A Suman
Full Text Available Foreign body (FB in esophagus is not a very rare entity. The main risks are to the children under 3 years of age. In this age group, the second molars have not yet developed, the child′s grinding and swallowing mechanisms are poor, and glottis closure is immature. Some patients at risk for FB ingestion may not be able to give an accurate medical history of ingestion, either due to age or mental illness. Coins are the most commonly ingested FBs, with button batteries, fish bone, marble, stone, and pieces of meat, etc., being other forms of ingested FB. In the majority of cases, it is accidental in nature, but can be occasionally homicidal, as was probably in one of our patients. Patient can be asymptomatic or can present with dysphagia, drooling of saliva, FB sensation, vomiting or pain. Patients with long-standing esophageal FBs may present with weight loss, aspiration pneumonia, fever, or signs and symptoms of esophageal perforation including crepitus, pneumomediastinum, or gastrointestinal bleeding. Here, we present four case reports of unusual presentation of FB in esophagus that were successfully removed by rigid esophagoscopy without any complication
In many experimental situations, it may not be feasible or even possible to run experiments in a completely randomized fashion as usually recommended. Under these circumstances, split-plot experiments in which certain factors are changed less frequently than the others are often used. Most...
Full Text Available This paper presents classification methods for electroencephalography (EEG signals in imagination of direction measured by a portable EEG headset. In the authorsr previous studies, principal component analysis extracted significant features from EEG signals to construct neural network classifiers. To improve the performance, the authors have implemented a Stacked Autoencoder (SAE for the classification. The SAE carries out feature extraction and classification in a form of multi-layered neural network. Experimental results showed that the SAE outperformed the previous classifiers.
Vznik EEG aktivity v mozku, rozdělení EEG vln podle frekvence, způsob měření EEG, přístroje pro měření EEG. Dále popis biofeedback metody, její možnosti a návrh biofeedback her. Popis zpracování naměřených EEG signálů. EEG generation, brain rhythms, methods of recording EEG, EEG recorder. Description of biofeedback, potentialities of biofeedback, proposal of biofeedback games. Description of processing measured EEG signals. B
van Lutterveld, Remko; Houlihan, Sean D; Pal, Prasanta; Sacchet, Matthew D; McFarlane-Blake, Cinque; Patel, Payal R; Sullivan, John S; Ossadtchi, Alex; Druker, Susan; Bauer, Clemens; Brewer, Judson A
Meditation is increasingly showing beneficial effects for psychiatric disorders. However, learning to meditate is not straightforward as there are no easily discernible outward signs of performance and thus no direct feedback is possible. As meditation has been found to correlate with posterior cingulate cortex (PCC) activity, we tested whether source-space EEG neurofeedback from the PCC followed the subjective experience of effortless awareness (a major component of meditation), and whether participants could volitionally control the signal. Sixteen novice meditators and sixteen experienced meditators participated in the study. Novice meditators were briefly trained to perform a basic meditation practice to induce the subjective experience of effortless awareness in a progressively more challenging neurofeedback test-battery. Experienced meditators performed a self-selected meditation practice to induce this state in the same test-battery. Neurofeedback was provided based on gamma-band (40-57Hz) PCC activity extracted using a beamformer algorithm. Associations between PCC activity and the subjective experience of effortless awareness were assessed by verbal probes. Both groups reported that decreased PCC activity corresponded with effortless awareness (Pneurofeedback to link an objective measure of brain activity with the subjective experience of effortless awareness, and suggest potential utility of this paradigm as a tool for meditation training. Copyright © 2016 Elsevier Inc. All rights reserved.
Villarreal-Garza, Cynthia; Perez-Alvarez, Sandra I.; Gonzalez-Espinoza, Ivan R.; Leon-Rodriguez, Eucario
Background To report location and management of atypical metastases from renal cell carcinoma (RCC) in the Instituto Nacional de Ciencias Medicas e Investigacion Salvador Zubiran (INCMNSZ) in Mexico City. Methods Between 1987 to 2009, 545 patients with RCC were retrospectively identified at the INCMNSZ. Patients with unusual metastases confirmed by histopathology were analyzed. Epidemiological, clinical, diagnosis, treatment and outcome data were reviewed. Results Sixty patients developed 98 unusual metastases secondary to RCC. The group was comprised of 35 men (58.3%), with a median age of 60 years at diagnosis. Metachronous unusual metastases with primary renal cancer were observed in 37 individuals (61.7%). Median time from primary RCC diagnosis to the first unusual metastasis was 16.5 months. Median survival from diagnosis of the first unusual metastasis to death was 5.0 months (CI 95%: 2.8-7.2 months). Patients with an initial solitary metastatic lesion in an unusual site (28.3%) had a better survival compared to patients who primarily presented with multiple metastases, 17.0 (CI 95%: 6.1-27.9) Vs 3.0 months (CI 95%: 0.9-5.1), p = 0.001. Unusual metastasis resection (21 patients) improved survival, 25.0 (CI 95%: 5.1-44.9) Vs 3.0 months (CI 95%: 0.8-5.2), p < 0.0001. No survival difference was observed between localization of unsual metastases (p = 0.72). Conclusions In patients with advanced RCC we suggest an individual diagnostic and surgical approach to achieve complete resection with disease-free margins, even in the presence of unusual metastatic sites, multifocality, or history of metastasectomy. These strategy might provide not only palliation for symptoms, but an opportunity for meaningful disease free and overall survival. PMID:29147198
Kanthiah, W.S.A.; Vaidyan, P.A.O.; Bhowmick, S.C.
During the operation of heavy water plants a number of unusual incidents do occur which are hurdles to the smooth operation of the system. An attempt has been made to give a detailed study of a few cases of unusual occurrences such as rupture of ammonia cracker tubes, water entry in cable junction box through nitrogen line, potassium amide splash on maintenance personnel, booster compressor trip explosion in effluent system, etc. in Heavy Water Plant, Tuticorin. (author). 5 figs
Tilley, Sara; Neale, Chris; Patuano, Agnès; Cinderby, Steve
There are concerns about mental wellbeing in later life in older people as the global population becomes older and more urbanised. Mobility in the built environment has a role to play in improving quality of life and wellbeing, as it facilitates independence and social interaction. Recent studies using neuroimaging methods in environmental psychology research have shown that different types of urban environments may be associated with distinctive patterns of brain activity, suggesting that we interact differently with varying environments. This paper reports on research that explores older people's responses to urban places and their mobility in and around the built environment. The project aim was to understand how older people experience different urban environments using a mixed methods approach including electroencephalography (EEG), self-reported measures, and interview results. We found that older participants experience changing levels of "excitement", "engagement" and "frustration" (as interpreted by proprietary EEG software) whilst walking between a busy built urban environment and an urban green space environment. These changes were further reflected in the qualitative themes that emerged from transcribed interviews undertaken one week post-walk. There has been no research to date that has directly assessed neural responses to an urban environment combined with qualitative interview analysis. A synergy of methods offers a deeper understanding of the changing moods of older people across time whilst walking in city settings.
Full Text Available The electroencephalogram (EEG patterns recorded during general anesthetic-induced coma are closely similar to those seen during slow-wave sleep, the deepest stage of natural sleep; both states show patterns dominated by large amplitude slow waves. Slow oscillations are believed to be important for memory consolidation during natural sleep. Tracking the emergence of slow-wave oscillations during transition to unconsciousness may help us to identify drug-induced alterations of the underlying brain state, and provide insight into the mechanisms of general anesthesia. Although cellular-based mechanisms have been proposed, the origin of the slow oscillation has not yet been unambiguously established. A recent theoretical study by Steyn-Ross et al. [Physical Review X 3(2, 021005 (2013] proposes that the slow oscillation is a network, rather than cellular phenomenon. Modeling anesthesia as a moderate reduction in gap-junction interneuronal coupling, they predict an unconscious state signposted by emergent low-frequency oscillations with chaotic dynamics in space and time. They suggest that anesthetic slow-waves arise from a competitive interaction between symmetry-breaking instabilities in space (Turing and time (Hopf, modulated by gap-junction coupling strength. A significant prediction of their model is that EEG phase coherence will decrease as the cortex transits from Turing--Hopf balance (wake to Hopf-dominated chaotic slow-waves (unconsciousness. Here, we investigate changes in phase coherence during induction of general anesthesia. After examining 128-channel EEG traces recorded from five volunteers undergoing propofol anesthesia, we report a significant drop in sub-delta band (0.05--1.5 Hz slow-wave coherence between frontal, occipital, and frontal-occipital electrode pairs, with the most pronounced wake-versus-unconscious coherence changes occurring at the frontal cortex.
Sumich, Alex; Kumari, Veena; Gordon, Evian; Tunstall, Nigel; Brammer, Michael
Separate dimensions of schizotypy have been differentially associated with electrophysiological measures of brain function, and further shown to be modified by sex/gender. We investigated event-related potential (ERP) correlates of two subdimensions of positive schizotypy, paranormal ideation (PI) and unusual experiences (UEs). Seventy-two individuals with no psychiatric diagnosis (men=36) completed self-report measures of UE and PI and performed an auditory oddball task. Average scores for N100, N200 and P300 amplitudes were calculated for left and right anterior, central and posterior electrode sites. Multiple linear regression was used to examine the relationships between the measures of schizotypy and ERPs across the entire sample, as well as separately according to sex. PI was inversely associated with P300 amplitude at left-central sites across the entire sample, and at right-anterior electrodes in women only. Right-anterior P300 and right-posterior N100 amplitudes were negatively associated with UE in women only. Across the entire sample, UE was negatively associated with left-central N100 amplitude, and positively associated with left-anterior N200 amplitude. These results provide support from electrophysiological measures for the fractionation of the positive dimension of schizotypy into subdimensions of PI and UE, and lend indirect support to dimensional or quasidimensional conceptions of psychosis. More specifically, they suggest that PI may be associated with alteration in contextual updating processes, and that UE may reflect altered sensory/early-attention (N100) mechanisms. The sex differences observed are consistent with those previously observed in individuals with schizophrenia.
Mark A Elliott
Full Text Available BACKGROUND: Since the origin of psychological science a number of studies have reported visual pattern formation in the absence of either physiological stimulation or direct visual-spatial references. Subjective patterns range from simple phosphenes to complex patterns but are highly specific and reported reliably across studies. METHODOLOGY/PRINCIPAL FINDINGS: Using independent-component analysis (ICA we report a reduction in amplitude variance consistent with subjective-pattern formation in ventral posterior areas of the electroencephalogram (EEG. The EEG exhibits significantly increased power at delta/theta and gamma-frequencies (point and circle patterns or a series of high-frequency harmonics of a delta oscillation (spiral patterns. CONCLUSIONS/SIGNIFICANCE: Subjective-pattern formation may be described in a way entirely consistent with identical pattern formation in fluids or granular flows. In this manner, we propose subjective-pattern structure to be represented within a spatio-temporal lattice of harmonic oscillations which bind topographically organized visual-neuronal assemblies by virtue of low frequency modulation.
Angelopoulos, Elias; Koutsoukos, Elias; Maillis, Antonis; Papadimitriou, George N; Stefanis, Costas
Thought blocks (TBs) are characterized by regular interruptions in the stream of thought. Outward signs are abrupt and repeated interruptions in the flow of conversation or actions while subjective experience is that of a total and uncontrollable emptying of the mind. In the very limited bibliography regarding TB, the phenomenon is thought to be conceptualized as a disturbance of consciousness that can be attributed to stoppages of continuous information processing due to an increase in the volume of information to be processed. In an attempt to investigate potential expression of the phenomenon on the functional properties of electroencephalographic (EEG) activity, an EEG study was contacted in schizophrenic patients with persisting auditory verbal hallucinations (AVHs) who additionally exhibited TBs. In this case, we hypothesized that the persistent and dense AVHs could serve the role of an increased information flow that the brain is unable to process, a condition that is perceived by the person as TB. Phase synchronization analyses performed on EEG segments during the experience of TBs showed that synchrony values exhibited a long-range common mode of coupling (grouped behavior) among the left temporal area and the remaining central and frontal brain areas. These common synchrony-fluctuation schemes were observed for 0.5 to 2s and were detected in a 4-s window following the estimated initiation of the phenomenon. The observation was frequency specific and detected in the broad alpha band region (6-12Hz). The introduction of synchrony entropy (SE) analysis applied on the cumulative synchrony distribution showed that TB states were characterized by an explicit preference of the system to be functioned at low values of synchrony, while the synchrony values are broadly distributed during the recovery state. Our results indicate that during TB states, the phase locking of several brain areas were converged uniformly in a narrow band of low synchrony values and in a
... in diagnosing brain disorders, especially epilepsy or another seizure disorder. An EEG might also be helpful for diagnosing ... Sometimes seizures are intentionally triggered in people with epilepsy during the test, but appropriate medical care is ...
Full Text Available There seems to be similarities between schizotypal personality and paranormal experiences, in fact, some of the symptoms of PTSD in DSM- match a number of anomalous/paranormal experiences. Positive schizotypy, including magical thinking, hallucinations and other unusual perceptual experiences, has also been associated with paranormal experiences and beliefs. However, paranormal experiences differ from psychotic experiences in nonclinical populations. In order to establish differences between positive and negative symptoms of schizotypy, we compared a group of believers in the paranormal (N= 121 and a sample of undergraduate students (N= 588. The hypothesis that believers would have higher scores in Schizotypy positive symptoms was confirmed. There was a significant difference in positive symptoms of schizotypy among the group of students with and no experiences, although not significant for negative symptoms
Zampieri, Nicola; Scirè, Gabriella; Zambon, Carla; Ottolenghi, Alberto; Camoglio, Francesco Saverio
Abdominal cystic formations in newborns are relatively common and often diagnostic suspicion arises before birth as a result of ultrasound scans carried out during pregnancy. Prenatal ovarian torsion is a rare condition very difficult to manage in the first days of life. We report and discuss the management of prenatal ovarian torsion with a free-floating abdominal cyst detected on prenatal ultrasound. We recorded the cases of antenatal abdominal cysts detected on ultrasound at the Department of Antenatal Diagnosis between January 2003 and January 2007. Only patients with a free-floating cyst were included in the study. Clinical and surgical findings were then recorded. Two out of 57 patients underwent surgery for a free-floating abdominal cyst during the second day of life. Postnatal ultrasound, Doppler ultrasound, and laparoscopic exploration were useful to identify an unusual presentation of antenatal ovarian torsion with a complete atresia of the Fallopian tube. The cases reported in this study suggest that a good clinical approach to all cases of abdominal cysts detected on prenatal ultrasound scans require postnatal Doppler and abdominal ultrasound with a laparoscopic exploration. Free-floating abdominal cysts are rare but, at the same time, strictly correlated with autoamputation of the ovary/Fallopian tube complex.
Full Text Available Burst suppression (BS is an electroencephalogram (EEG pattern that is characterized by brief bursts of spikes, sharp waves, or slow waves of relatively high amplitude alternating with periods of relatively flat EEG or isoelectric periods. The pattern is usually associated with coma, severe encephalopathy of various etiologies, or general anesthesia. We describe an unusual case of anoxic brain injury in which a BS pattern was seen during behaviorally defined sleep during a routine outpatient EEG study.
Simoes, Marco; Direito, Bruno; Lima, Joao; Castelhano, Joao; Ferreira, Carlos; Couceiro, Ricardo; Carvalho, Paulo; Castelo-Branco, Miguel
The relationship between EEG and fMRI data is poorly covered in the literature. Extensive work has been conducted in resting-state and epileptic activity, highlighting a negative correlation between the alpha power band of the EEG and the BOLD activity in the default-mode-network. The identification of an appropriate task-specific relationship between fMRI and EEG data for predefined regions-of-interest, would allow the transfer of interventional paradigms (such as BOLD-based neurofeedback sessions) from fMRI to EEG, enhancing its application range by lowering its costs and improving its flexibility. In this study, we present an analysis of the correlation between task-specific alpha band fluctuations and BOLD activity in the facial expressions processing network. We characterized the network ROIs through a stringent localizer and identified two clusters on the scalp (one frontal, one parietal-occipital) with marked alpha fluctuations, related to the task. We then check whether such power variations throughout the time correlate with the BOLD activity in the network. Our results show statistically significant negative correlations between the alpha power in both clusters and for all the ROIs of the network. The correlation levels have still not met the requirements for transferring the protocol to an EEG setup, but they pave the way towards a better understand on how frontal and parietal-occipital alpha relates to the activity of the facial expressions processing network.
Kusse, Caroline; Shaffii-LE Bourdiec, Anahita; Schrouff, Jessica; Matarazzo, Luca; Maquet, Pierre
This study characterizes hypnagogic hallucinations reported during a polygraphically recorded 90-min daytime nap following or preceding practice of the computer game Tetris. In the experimental group (N = 16), participants played Tetris in the morning for 2 h during three consecutive days, while in a first control group (N = 13, controlling the effect of experience) participants did not play any game, and in a second control group (N = 14, controlling the effect of anticipation) participants played Tetris after the nap. During afternoon naps, participants were repetitively awakened 15, 45, 75, 120 or 180 s after the onset of S1, and were asked to report their mental content. Reports content was scored by three judges (inter-rater reliability 85%). In the experimental group, 48 out of 485 (10%) sleep-onset reports were Tetris-related. They mostly consisted of images and sounds with very little emotional content. They exactly reproduced Tetris elements or mixed them with other mnemonic components. By contrast, in the first control group, only one report out of 107 was scored as Tetris-related (1%), and in the second control group only three reports out of 112 were scored as Tetris-related (3%; between-groups comparison; P = 0.006). Hypnagogic hallucinations were more consistently induced by experience than by anticipation (P = 0.039), and they were predominantly observed during the transition of wakefulness to sleep. The observed attributes of experience-related hypnagogic hallucinations are consistent with the particular organization of regional brain activity at sleep onset, characterized by high activity in sensory cortices and in the default-mode network. © 2011 European Sleep Research Society.
Wilson, John A; Nordal, Helge J
Coma is a dynamic condition that may have various causes. Important changes may take place rapidly, often with consequences for treatment. The purpose of this article is to provide a brief overview of EEG patterns in comas with various causes, and indicate how EEG contributes in an assessment of the prognosis for coma patients. The article is based on many years of clinical and research-based experience of EEG used for patients in coma. A self-built reference database was supplemented by searches for relevant articles in PubMed. EEG reveals immediate changes in coma, and can provide early information on cause and prognosis. It is the only diagnostic tool for detecting a non-convulsive epileptic status. Locked-in- syndrome may be overseen without EEG. Repeated EEG scans increase diagnostic certainty and make it possible to monitor the development of coma. EEG reflects brain function continuously and therefore holds a key place in the assessment and treatment of coma.
George J. A. Jiang
Full Text Available Electroencephalogram (EEG signals, as it can express the human brain’s activities and reflect awareness, have been widely used in many research and medical equipment to build a noninvasive monitoring index to the depth of anesthesia (DOA. Bispectral (BIS index monitor is one of the famous and important indicators for anesthesiologists primarily using EEG signals when assessing the DOA. In this study, an attempt is made to build a new indicator using EEG signals to provide a more valuable reference to the DOA for clinical researchers. The EEG signals are collected from patients under anesthetic surgery which are filtered using multivariate empirical mode decomposition (MEMD method and analyzed using sample entropy (SampEn analysis. The calculated signals from SampEn are utilized to train an artificial neural network (ANN model through using expert assessment of consciousness level (EACL which is assessed by experienced anesthesiologists as the target to train, validate, and test the ANN. The results that are achieved using the proposed system are compared to BIS index. The proposed system results show that it is not only having similar characteristic to BIS index but also more close to experienced anesthesiologists which illustrates the consciousness level and reflects the DOA successfully.
Funase, Arao; Kuno, Yoshiaki; Okuma, Shigeru; Yagi, Tohru
Our final goal is to establish the model for saccadic eye movement that connects the saccade and the electroencephalogram(EEG). As the first step toward this goal, we recorded and analyzed the saccade-related EEG. In the study recorded in this paper, we tried detecting a certain EEG that is peculiar to the eye movement. In these experiments, each subject was instructed to point their eyes toward visual targets (LEDs) or the direction of the sound sources (buzzers). In the control cases, the EEG was recorded in the case of no eye movemens. As results, in the visual experiments, we found that the potential of EEG changed sharply on the occipital lobe just before eye movement. Furthermore, in the case of the auditory experiments, similar results were observed. In the case of the visual experiments and auditory experiments without eye movement, we could not observed the EEG changed sharply. Moreover, when the subject moved his/her eyes toward a right-side target, a change in EEG potential was found on the right occipital lobe. On the contrary, when the subject moved his/her eyes toward a left-side target, a sharp change in EEG potential was found on the left occipital lobe.
Kheder, Ammar; Bianchi, Matt T.; Westover, M. Brandon
Burst suppression (BS) is an electroencephalogram (EEG) pattern that is characterized by brief bursts of spikes, sharp waves, or slow waves of relatively high amplitude alternating with periods of relatively flat EEG or isoelectric periods. The pattern is usually associated with coma, severe encephalopathy of various etiologies, or general anesthesia. We describe an unusual case of anoxic brain injury in which a BS pattern was seen during behaviorally defined sleep during a routine outpatient...
HAYASHI, Mitsuo; HIBINO, Kenji; HORI, Tadao
The aim of this study is to show the polysomnogram of hypnagogic period. Sixteen subjects slept for two nights. Their EEGs (Fz, Cz, Pz, Oz), horizontal and vertical EOGs, submentalis EMG, thoracic and abdominal respiration were recorded. They pressed a button when pip tones (1000Hz, 50dB, max duration : 5s, ISI : 30-90s) were presented, and reported their psychological experiences, According to Hori et al. (1994), the hypnagogic EEGs just 5s before the pip tones were classified into 9 stages,...
Li, Feng; Li, Jiang; McKenzie, Frederic; Zhang, Guangfan; Wang, Wei; Pepe, Aaron; Xu, Roger; Schnell, Thomas; Anderson, Nick; Heitkamp, Dean
In this paper, we present methods to analyze and improve an EEG-based engagement assessment approach, consisting of data preprocessing, feature extraction and engagement state classification. During data preprocessing, spikes, baseline drift and saturation caused by recording devices in EEG signals are identified and eliminated, and a wavelet based method is utilized to remove ocular and muscular artifacts in the EEG recordings. In feature extraction, power spectrum densities with 1 Hz bin are calculated as features, and these features are analyzed using the Fisher score and the one way ANOVA method. In the classification step, a committee classifier is trained based on the extracted features to assess engagement status. Finally, experiment results showed that there exist significant differences in the extracted features among different subjects, and we have implemented a feature normalization procedure to mitigate the differences and significantly improved the engagement assessment performance.
Previous research on meditation and the EEG is described, and findings relating to EEG patterns during meditation are discussed. Comparisons of meditation with other altered states are reviewed and it is concluded that, on the basis of existing EEG evidence, there is some reason for differentiating between meditation and drowsing. Research on alpha-blocking and habituation of the blocking response during meditation is reviewed, and the effects of meditation on EEG patterns outside of meditati...
Askamp, Jessica; van Putten, Michel Johannes Antonius Maria
The sensitivity of routine EEG recordings for interictal epileptiform discharges in epilepsy is limited. In some patients, inpatient video-EEG may be performed to increase the likelihood of finding abnormalities. Although many agree that home EEG recordings may provide a cost-effective alternative
Ardeshna, Nikesh I
Coma is defined as a state of extreme unresponsiveness, in which a person exhibits no voluntary movement or behavior even to painful stimuli. The utilization of EEG for patients in coma has increased dramatically over the last few years. In fact, many institutions have set protocols for continuous EEG (cEEG) monitoring for patients in coma due to potential causes such as subarachnoid hemorrhage or cardiac arrest. Consequently, EEG plays an important role in diagnosis, managenent, and in some cases even prognosis of coma patients.
Duun-Henriksen, Jonas; Kjaer, Troels W.; Madsen, Rasmus E.
Scalp EEG is the most widely used modality to record the electrical signals of the brain. It is well known that the volume conduction of these brain waves through the brain, cerebrospinal fluid, skull and scalp reduces the spatial resolution and the signal amplitude. So far the volume conduction...... has primarily been investigated by realistic head models or interictal spike analysis. We have set up a novel and more realistic experiment that made it possible to compare the information in the intra- and extracranial EEG. We found that intracranial EEG channels contained correlated patterns when...... placed less than 30 mm apart, that intra- and extracranial channels were partly correlated when placed less than 40 mm apart, and that extracranial channels probably were correlated over larger distances. The underlying cortical area that influences the extracranial EEG is found to be up to 45 cm2...
Lopes da Silva, F.; Mulert, C.; Lemieux, L.
The existence of the electrical activity of the brain (i.e. the electroencephalogram or EEG) was discovered more than a century ago by Caton. After the demonstration that the EEG could be recorded from the human scalp by Berger in the 1920s, it made a slow start before it became accepted as a method
A brain-computer interface (BCI) is a direct link between the brain and a computer. Multi-modal input with BCI forms a promising solution for creating rich gaming experience. Electroencephalography (EEG) measurement is the sole necessary component for a BCI system. EEG signals have the
different conditions are recorded in this experiment. These conditions are the resting state, left finger keyboard press, right finger keyboard...51 4.3.2. Right and Left Finger Keyboard Press Conditions ..................................... 57 4.4. Detection of Hand...solving Gamma 30 Hz and higher Blending of multiple brain functions ; Muscle related artifacts 2.2. EEG Artifacts EEG recordings are intended to
Swee Sim Kok
Full Text Available This paper describes the development of a brainwave controlled wheelchair. The main objective of this project is to construct a wheelchair which can be directly controlled by the brain without requires any physical feedback as controlling input from the user. The method employed in this project is the Brain-computer Interface (BCI, which enables direct communication between the brain and the electrical wheelchair. The best method for recording the brain’s activity is electroencephalogram (EEG. EEG signal is also known as brainwaves signal. The device that used for capturing the EEG signal is the Emotiv EPOC headset. This headset is able to transmit the EEG signal wirelessly via Bluetooth to the PC (personal computer. By using the PC software, the EEG signals are processed and converted into mental command. According to the mental command (e.g. forward, left... obtained, the output electrical signal is sent out to the electrical wheelchair to perform the desired movement. Thus, in this project, a computer software is developed for translating the EEG signal into mental commands and transmitting out the controlling signal wirelessly to the electrical wheelchair.
Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R
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.
Julienne Marie Hill
Doping experiments on La 2 CuO 4 , Sr 2 CuO 3 and SrCu 2 (BO 3 ) 2 were performed with the intent of synthesizing new metallic low-=dimensional cuprate oxide compounds. Magnetic susceptibility χ(T) measurements on a polycrystalline La 2 CuO 4 sample chemically oxidized at room temperature in aqueous NaClO showed superconductivity with a superconducting transition temperature T c of 42.6 K and a Meissner fraction of 26%. They were unable to electrochemically oxidize La 2 CuO 4 in a nonaqueous solution of tetramethylammonium hydroxide (TMAOH) and methanol. Sr 2 CuO 3 was found to decompose upon exposure to air and water. Electron paramagnetic resonance, isothermal magnetization M(H), and χ(T) measurements on the primary decomposition product, Sr 2 Cu(OH) 6 , were consistent with a nearly isolated, spin S = 1/2, local moment model for the Cu +2 spins. From a fit of χ(T) by the Curie-Weiss law and of the M(H) isotherms by a modified Brillouin function, the weakly antiferromagnetic exchange interaction between adjacent Cu +2 spins in Sr 2 Cu(OH) 6 was found to be J/k B = 1.06(4) K. Doping studies on SrCu 2 (BO 3 ) 2 were inconclusive. χ(T) measurements on an undoped polycrystalline sample of SrCu 2 (BO 3 ) 2 , a sample treated with distilled water, and a sample treated with aqueous NaClO showed no qualitative differences between the samples. In addition, χ(T) and M(H, T) studies of the ultra-hard material MgAlB 14 were carried out in search of superconductivity or ferromagnetism in this compound. χ(T) measurements on a powder sample revealed temperature-independent diamagnetism from 1.8 K up to room temperature with a Curie-Weiss impurity concentration equivalent to ∼ 1 mol% of spin-1/2 ions. In contrast, M(H, T) data on hot pressed samples showed evidence of ferromagnetic transitions above ∼ 330 K. Scanning electron microscopy and Auger microprobe analysis of the hot pressed samples indicated that the observed ferromagnetism was likely due to Fe impurities
Hill, Julienne Marie
Doping experiments on La2CuO4, Sr2CuO 3 and SrCu2(BO3)2 were performed with the intent of synthesizing new metallic low-dimensional cuprate oxide compounds. Magnetic susceptibility chi(T) measurements on a polycrystalline La 2CuO4 sample chemically oxidized at room temperature in aqueous NaClO showed superconductivity with a superconducting transition temperature Tc of 42.6 K and a Meissner fraction of 26%. We were unable to electrochemically oxidize La2CuO4 in a nonaqueous solution of tetramethylammonium hydroxide (TMAOH) and methanol. Sr2CuO 3 was found to decompose upon exposure to air and water. Electron paramagnetic resonance, isothermal magnetization M(H) and chi(T) measurements on the primary decomposition product, Sr2Cu(OH)6, were consistent with a nearly isolated, spin S = 1/2, local moment model for the Cu +2 spins. From a fit of chi(T) by the Curie-Weiss law and of the M(H) isotherms by a modified Brillouin function, the weakly antiferromagnetic exchange interaction between adjacent Cu+2 spins in Sr 2Cu(OH)6 was found to be J/kB = 1.06(4) K. Doping studies on SrCu2(BO3)2 were inconclusive. chi(T) measurements on an undoped polycrystalline sample of SrCu2(BO 3)2, a sample treated with distilled water, and a sample treated with aqueous NaClO showed no qualitative differences between the samples. In addition, chi(T) and M(H, T) studies of the ultra-hard material MgAlB14 were carried out in search of superconductivity or ferromagnetism in this compound. chi(T) measurements on a powder sample revealed temperature-independent diamagnetism from 1.8 K up to room temperature with a Curie-Weiss impurity concentration equivalent to ˜1 mol% of spin-1/2 ions. In contrast, M(H, T) data on hot pressed samples showed evidence of ferromagnetic transitions above ˜330 K. Scanning electron microscopy and Auger microprobe analysis of the hot pressed samples indicated that the observed ferromagnetism was likely due to Fe impurities.
Pfabigan, Daniela M; Seidel, Eva-Maria; Sladky, Ronald; Hahn, Andreas; Paul, Katharina; Grahl, Arvina; Küblböck, Martin; Kraus, Christoph; Hummer, Allan; Kranz, Georg S; Windischberger, Christian; Lanzenberger, Rupert; Lamm, Claus
The anticipation of favourable or unfavourable events is a key component in our daily life. However, the temporal dynamics of anticipation processes in relation to brain activation are still not fully understood. A modified version of the monetary incentive delay task was administered during separate functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) sessions in the same 25 participants to assess anticipatory processes with a multi-modal neuroimaging set-up. During fMRI, gain and loss anticipation were both associated with heightened activation in ventral striatum and reward-related areas. EEG revealed most pronounced P300 amplitudes for gain anticipation, whereas CNV amplitudes distinguished neutral from gain and loss anticipation. Importantly, P300, but not CNV amplitudes, were correlated to neural activation in the ventral striatum for both gain and loss anticipation. Larger P300 amplitudes indicated higher ventral striatum blood oxygen level dependent (BOLD) response. Early stimulus evaluation processes indexed by EEG seem to be positively related to higher activation levels in the ventral striatum, indexed by fMRI, which are usually associated with reward processing. The current results, however, point towards a more general motivational mechanism processing salient stimuli during anticipation. Copyright © 2014. Published by Elsevier Inc.
Hayashi, M; Katoh, K; Hori, T
The relationships between hypnagogic imagery and EEG activity were studied. 7 subjects (4 women and 3 men) reported the content of hypnagogic imagery every minute and the hypnagogic EEGs were classified into 5 stages according to Hori's modified criteria. The content of the hypnagogic imagery changed as a function of the hypnagogic EEG stages.
Ruffell, Tamatha; Azis, Matilda; Hassanali, Nedah; Ames, Catherine; Browning, Sophie; Bracegirdle, Karen; Corrigall, Richard; Laurens, Kristin R; Hirsch, Colette; Kuipers, Elizabeth; Maddox, Lucy; Jolley, Suzanne
The psychosocial processes implicated in the development and maintenance of psychosis differ according to both the dimensional attributes (conviction, frequency, associated distress, adverse life impact) and the content or type (e.g. grandiosity, hallucinations, paranoia) of the psychotic symptoms experienced. This has informed the development of 'targeted' cognitive behavioural therapy for psychosis (CBTp): interventions focusing on specific psychological processes in the context of particular symptom presentations. In adults, larger effect sizes for change in primary outcomes are typically reported in trials of targeted interventions, compared to those for trials of generic CBTp approaches with multiple therapeutic foci. We set out to test the theoretical basis for developing targeted CBTp interventions for young people with distressing psychotic-like, or unusual, experiences (UEs). We investigated variations in the psychosocial processes previously associated with self-reported UE severity (reasoning, negative life events, emotional problems) according to UE dimensional attributes and content/type (using an established five-factor model) in a clinically referred sample of 72 young people aged 8-14 years. Regression analyses revealed associations of conviction and grandiosity with reasoning; of frequency, and hallucinations and paranoia, with negative life events; and of distress/adverse life impact, and paranoia and hallucinations, with emotional problems. We conclude that psychological targets for intervention differ according to particular characteristics of childhood UEs in much the same way as for psychotic symptoms in adults. The development of targeted interventions is therefore indicated, and tailoring therapy according to presentation should further improve clinical outcomes for these young people.
Joshua H Balsters
Full Text Available Rising life expectancies coupled with an increasing awareness of age-related cognitive decline have led to the unwarranted use of psychopharmaceuticals, including acetylcholinesterase inhibitors (AChEIs, by significant numbers of healthy older individuals. This trend has developed despite very limited data regarding the effectiveness of such drugs on non-clinical groups and recent work indicates that AChEIs can have negative cognitive effects in healthy populations. For the first time, we use a combination of EEG and simultaneous EEG/fMRI to examine the effects of a commonly prescribed AChEI (donepezil on cognition in healthy older participants. The short- and long-term impact of donepezil was assessed using two double-blind, placebo-controlled trials. In both cases, we utilised cognitive (paired associates learning (CPAL and electrophysiological measures (resting EEG power that have demonstrated high-sensitivity to age-related cognitive decline. Experiment 1 tested the effects of 5 mg/per day dosage on cognitive and EEG markers at 6-hour, 2-week and 4-week follow-ups. In experiment 2, the same markers were further scrutinised using simultaneous EEG/fMRI after a single 5 mg dose. Experiment 1 found significant negative effects of donepezil on CPAL and resting Alpha and Beta band power. Experiment 2 replicated these results and found additional drug-related increases in the Delta band. EEG/fMRI analyses revealed that these oscillatory differences were associated with activity differences in the left hippocampus (Delta, right frontal-parietal network (Alpha, and default-mode network (Beta. We demonstrate the utility of simple cognitive and EEG measures in evaluating drug responses after acute and chronic donepezil administration. The presentation of previously established markers of age-related cognitive decline indicates that AChEIs can impair cognitive function in healthy older individuals. To our knowledge this is the first study to identify
Grant, Arthur C.; Abdel-Baki, Samah G.; Omurtag, Ahmet; Sinert, Richard; Chari, Geetha; Malhotra, Schweta; Weedon, Jeremy; Fenton, Andre A.; Zehtabchi, Shahriar
Measuring the diagnostic accuracy (DA) of an EEG device is unconventional and complicated by imperfect interrater reliability. We sought to compare the DA of a miniature, wireless, battery-powered EEG device (“microEEG”) to a reference EEG machine in emergency department (ED) patients with altered mental status (AMS). 225 ED patients with AMS underwent 3 EEGs. EEG1 (Nicolet Monitor, “reference”) and EEG2 (microEEG) were recorded simultaneously with EEG cup electrodes using a signal splitter. ...
Loibl, Helmut; Maslaton, Martin; Bredow, Hartwig von; Walter, Rene (eds.)
With the EEG 2014, the legislature has created a complete revision of all the RES plants. Specifically for biogas plants fundamental changes have been made with the maximum rated power or a new landscape conservation concept. For new biogas plants the legislator arranges not only a much lower remuneration, but also the direct marketing as a rule, which entails fundamental changes in the overall compensation system by itself. The new edition of this highly regarded standard work revives the extensive practical experience to EEG 2009, 2012 and 2014 in detail and in particular and takes into account the large number of newly issued clearinghouses decisions and judgments. All current legal issues and challenges of biogas plants can be found comprehensively presented here. [German] Mit dem EEG 2014 hat der Gesetzgeber eine komplette Neuregelung fuer alle EEG-Anlagen geschaffen. Speziell fuer Biogasanlagen wurden mit der Hoechstbemessungsleistung oder einem neuen Landschaftspflegebegriff grundlegende Aenderungen vorgenommen. Fuer neue Biogasanlagen ordnet der Gesetzgeber nicht nur eine deutlich geringere Verguetung, sondern zudem die Direktvermarktung als Regelfall an, was grundlegende Veraenderungen des gesamten Verguetungssystems nach sich zieht. Die Neuauflage dieses vielbeachteten Standardwerks greift die umfangreichen Praxiserfahrungen zum EEG 2009, 2012 und 2014 detailliert auf und beruecksichtigt insbesondere auch die Vielzahl der neu ergangenen Clearingstellenentscheidungen und Urteile. Alle aktuellen rechtlichen Themen und Herausforderungen bei Biogasanlagen finden Sie hier umfassend dargestellt.
Glickman, Matthew R.; Tang, Akaysha (University of New Mexico, Albuquerque, NM)
The motivating vision behind Sandia's MENTOR/PAL LDRD project has been that of systems which use real-time psychophysiological data to support and enhance human performance, both individually and of groups. Relevant and significant psychophysiological data being a necessary prerequisite to such systems, this LDRD has focused on identifying and refining such signals. The project has focused in particular on EEG (electroencephalogram) data as a promising candidate signal because it (potentially) provides a broad window on brain activity with relatively low cost and logistical constraints. We report here on two analyses performed on EEG data collected in this project using the SOBI (Second Order Blind Identification) algorithm to identify two independent sources of brain activity: one in the frontal lobe and one in the occipital. The first study looks at directional influences between the two components, while the second study looks at inferring gender based upon the frontal component.
Kaare B. Mikkelsen
Full Text Available We propose and test the keyhole hypothesis—that measurements from low dimensional EEG, such as ear-EEG reflect a broadly distributed set of neural processes. We formulate the keyhole hypothesis in information theoretical terms. The experimental investigation is based on legacy data consisting of 10 subjects exposed to a battery of stimuli, including alpha-attenuation, auditory onset, and mismatch-negativity responses and a new medium-long EEG experiment involving data acquisition during 13 h. Linear models were estimated to lower bound the scalp-to-ear capacity, i.e., predicting ear-EEG data from simultaneously recorded scalp EEG. A cross-validation procedure was employed to ensure unbiased estimates. We present several pieces of evidence in support of the keyhole hypothesis: There is a high mutual information between data acquired at scalp electrodes and through the ear-EEG “keyhole,” furthermore we show that the view—represented as a linear mapping—is stable across both time and mental states. Specifically, we find that ear-EEG data can be predicted reliably from scalp EEG. We also address the reverse view, and demonstrate that large portions of the scalp EEG can be predicted from ear-EEG, with the highest predictability achieved in the temporal regions and when using ear-EEG electrodes with a common reference electrode.
Robertson, R; Langill, L; Wong, P K; Ho, H H
Rett syndrome, a degenerative neurological disorder of girls, has a classical presentation and typical EEG findings. The electroencephalograms (EEGs) of 7 girls whose records have been followed from the onset of symptoms to the age of 5 or more are presented. These findings are tabulated with the Clinical Staging System of Hagberg and Witt-Engerström (1986). The records show a progressive deterioration in background rhythms in waking and sleep. The abnormalities of the background activity may only become evident at 4-5 years of age or during stage 2--the Rapid Destructive Stage. The marked contrast between waking and sleep background may not occur until stage 3--the Pseudostationary Stage. In essence EEG changes appear to lag behind clinical symptomatology by 1-3 years. An unexpected, but frequent, abnormality was central spikes seen in 5 of 7 girls. They appeared to be age related and could be evoked by tactile stimulation in 2 patients. We hypothesize that the prominent 'hand washing' mannerism may be self-stimulating and related to the appearance of central spike discharges.
Meledin, Irina; Abu Tailakh, Muhammad; Gilat, Shlomo; Yogev, Hagai; Golan, Agneta; Novack, Victor; Shany, Eilon
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 continuity and amplitude.
Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun
This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.
Su, Kyung-Min; Hairston, W David; Robbins, Kay
In controlled laboratory EEG experiments, researchers carefully mark events and analyze subject responses time-locked to these events. Unfortunately, such markers may not be available or may come with poor timing resolution for experiments conducted in less-controlled naturalistic environments. We present an integrated event-identification method for identifying particular responses that occur in unlabeled continuously recorded EEG signals based on information from recordings of other subjects potentially performing related tasks. We introduce the idea of timing slack and timing-tolerant performance measures to deal with jitter inherent in such non-time-locked systems. We have developed an implementation available as an open-source MATLAB toolbox (http://github.com/VisLab/EEG-Annotate) and have made test data available in a separate data note. We applied the method to identify visual presentation events (both target and non-target) in data from an unlabeled subject using labeled data from other subjects with good sensitivity and specificity. The method also identified actual visual presentation events in the data that were not previously marked in the experiment. Although the method uses traditional classifiers for initial stages, the problem of identifying events based on the presence of stereotypical EEG responses is the converse of the traditional stimulus-response paradigm and has not been addressed in its current form. In addition to identifying potential events in unlabeled or incompletely labeled EEG, these methods also allow researchers to investigate whether particular stereotypical neural responses are present in other circumstances. Timing-tolerance has the added benefit of accommodating inter- and intra- subject timing variations. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.
Full Text Available Brain is the wonderful organ of human body. It is the agent of information collection and transformation. The neural activity of the human brain starts between the 17th and 23rd week of prenatal development. It is believed that from this early stage and throughout life electrical signals are generated by the brain function but also the status of the whole body. Understanding of neuronal functions and neurophysiologic properties of the brain function together with the mechanisms underlying the generation of signals and their recording is, however, vital for those who deal with these signals for detection, diagnosis, and treatment of brain disorders and the related diseases. This research paper concentrated only on brain tumor detection. Using minimum electrode location the brain tumor possibility is detected. This paper is separated into two parts: the First part deals with electrode location on the scalp and the second part deals with how the fuzzy logic rule based algorithm is applied for estimation of brain tumor from EEG. Basically 8 locations are identified. After acquiring the pure EEG signal Fuzzy Logic Rule is applied to predict the possibility of brain tumor.
Roś, Beata P; Bijma, Fetsje; de Gunst, Mathisca C M; de Munck, Jan C
In this paper we introduce a covariance framework for the analysis of single subject EEG and MEG data that takes into account observed temporal stationarity on small time scales and trial-to-trial variations. We formulate a model for the covariance matrix, which is a Kronecker product of three components that correspond to space, time and epochs/trials, and consider maximum likelihood estimation of the unknown parameter values. An iterative algorithm that finds approximations of the maximum likelihood estimates is proposed. Our covariance model is applicable in a variety of cases where spontaneous EEG or MEG acts as source of noise and realistic noise covariance estimates are needed, such as in evoked activity studies, or where the properties of spontaneous EEG or MEG are themselves the topic of interest, like in combined EEG-fMRI experiments in which the correlation between EEG and fMRI signals is investigated. We use a simulation study to assess the performance of the estimator and investigate the influence of different assumptions about the covariance factors on the estimated covariance matrix and on its components. We apply our method to real EEG and MEG data sets. Copyright © 2015 Elsevier Inc. All rights reserved.
Beer, de N.A.M.; Meurs, van W.L.; Grit, M.B.M.; Good, M.L.; Gravenstein, D.
We describe a model for simulating a spontaneous electroencephalogram (EEG) and for simulating the effects of anesthesia on the EEG, to allow anesthesiologists and EEG technicians to learn and practice intraoperative EEG monitoring. For this purpose, we developed a linear model to manipulate the
Electroencephalogy ( EEG ) Feedback In Decision- Making The goal of this project is to investigate whether Electroencephalogy ( EEG ) can provide useful...feedback when training rapid decision-making. More specifically, EEG will allow us to provide online feedback about the neural decision processes...Electroencephalogy ( EEG ) Feedback In Decision-Making Report Title The goal of this project is to investigate whether Electroencephalogy ( EEG ) can provide useful
Rass, Olga; Ahn, Woo-Young; O'Donnell, Brian F
Resting EEG is sensitive to transient, acute effects of nicotine administration and abstinence, but the chronic effects of smoking on EEG are poorly characterized. This study measures the resting EEG profile of chronic smokers in a non-deprived, non-peak state to test whether differences in smoking behavior and personality traits affect pharmaco-EEG response. Resting EEG, impulsiveness, and personality measures were collected from daily smokers (n=22), nondaily smokers (n=31), and non-smokers (n=30). Daily smokers had reduced resting delta and alpha EEG power and higher impulsiveness (Barratt Impulsiveness Scale) compared to nondaily smokers and non-smokers. Both daily and nondaily smokers discounted delayed rewards more steeply, reported lower conscientiousness (NEO-FFI), and reported greater disinhibition and experience seeking (Sensation Seeking Scale) than non-smokers. Nondaily smokers reported greater sensory hedonia than nonsmokers. Altered resting EEG power in daily smokers demonstrates differences in neural signaling that correlated with greater smoking behavior and dependence. Although nondaily smokers share some characteristics with daily smokers that may predict smoking initiation and maintenance, they differ on measures of impulsiveness and resting EEG power. Resting EEG in non-deprived chronic smokers provides a standard for comparison to peak and trough nicotine states and may serve as a biomarker for nicotine dependence, relapse risk, and recovery. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Rass, Olga; Ahn, Woo-Young; O’Donnell, Brian F.
Objectives Resting EEG is sensitive to transient, acute effects of nicotine administration and abstinence, but the chronic effects smoking on EEG are poorly characterized. This study measures the resting EEG profile of chronic smokers in a non-deprived, non-peak state to test whether differences in smoking behavior and personality traits affect pharmaco-EEG response. Methods Resting EEG, impulsiveness, and personality measures were collected from daily smokers (n=22), nondaily smokers (n=31), and non-smokers (n=30). Results Daily smokers had reduced resting delta and alpha EEG power and higher impulsiveness (Barratt Impulsiveness Scale) compared to nondaily smokers and non-smokers. Both daily and nondaily smokers discounted delayed rewards more steeply, reported lower conscientiousness (NEO-FFI) and reported greater disinhibition and experience seeking (Sensation Seeking Scale) than non-smokers. Nondaily smokers reported greater sensory hedonia than nonsmokers. Conclusions Altered resting EEG power in daily smokers demonstrates differences in neural signaling that correlated with greater smoking behavior and dependence. Although nondaily smokers share some characteristics with daily smokers that may predict smoking initiation and maintenance, they differ on measures of impulsiveness and resting EEG power. Significance Resting EEG in non-deprived chronic smokers provides a standard for comparison to peak and trough nicotine states and may serve as a biomarker for nicotine dependence, relapse risk, and recovery. PMID:26051750
Ouellette, Daniel R.; Parrish, Scott; Browning, Robert F.; Turner, J. Francis; Zarogoulidis, Konstantinos; Kougioumtzi, Ioanna; Dryllis, Georgios; Kioumis, Ioannis; Pitsiou, Georgia; Machairiotis, Nikolaos; Katsikogiannis, Nikolaos; Tsiouda, Theodora; Madesis, Athanasios; Karaiskos, Theodoros
Pneumothorax is divided to primary and secondary. It is a situation that requires immediate treatment, otherwise it could have severe health consequences. Pneumothorax can be treated either by thoracic surgeons, or pulmonary physicians. In our current work, we will focus on unusual cases of pneumothorax. We will provide the etiology and treatment for each case, also a discussion will be made for each situation. PMID:25337394
Rajendra Singh Jain
Full Text Available Lafora body disease (LBD is a form of progressive myoclonic epilepsy, characterized by seizures, myoclonic jerks, cognitive decline, ataxia, and intracellular polyglucosan inclusion bodies (Lafora bodies in the neurons, heart, skeletal muscle, liver, and sweat gland duct cells. Electroencephalogram (EEG findings in LBD may include multiple spikes and wave discharges, photosensitivity, multifocal epileptiform discharges, and progressive slowing in background activity. Periodicity in epileptiform discharges has not been frequently depicted in LBD. We herein report an unusual case of LBD who showed generalized periodic epileptiform discharges in EEG.
Queiroz, Luiz P
Some headache syndromes have few cases reported in the literature. Their clinical characteristics, pathogenesis, and treatment may have not been completely defined. They may not actually be uncommon but rather under-recognized and/or underreported. A literature review of unusual headache syndromes, searching PubMed and ISI Web of Knowledge, was performed. After deciding which disorders to study, relevant publications in scientific journals, including original articles, reviews, meeting abstracts, and letters or correspondences to the editors were searched. This paper reviewed the clinical characteristics, the pathogenesis, the diagnosis, and the treatment of five interesting and unusual headache syndromes: exploding head syndrome, red ear syndrome, neck-tongue syndrome, nummular headache, and cardiac cephalgia. Recognizing some unusual headaches, either primary or secondary, may be a challenge for many non-headache specialist physicians. It is important to study them because the correct diagnosis may result in specific treatments that may improve the quality of life of these patients, and this can even be life saving. © 2013 American Headache Society.
Kappel, Simon L; Looney, David; Mandic, Danilo P; Kidmose, Preben
A problem inherent to recording EEG is the interference arising from noise and artifacts. While in a laboratory environment, artifacts and interference can, to a large extent, be avoided or controlled, in real-life scenarios this is a challenge. Ear-EEG is a concept where EEG is acquired from electrodes in the ear. We present a characterization of physiological artifacts generated in a controlled environment for nine subjects. The influence of the artifacts was quantified in terms of the signal-to-noise ratio (SNR) deterioration of the auditory steady-state response. Alpha band modulation was also studied in an open/closed eyes paradigm. Artifacts related to jaw muscle contractions were present all over the scalp and in the ear, with the highest SNR deteriorations in the gamma band. The SNR deterioration for jaw artifacts were in general higher in the ear compared to the scalp. Whereas eye-blinking did not influence the SNR in the ear, it was significant for all groups of scalps electrodes in the delta and theta bands. Eye movements resulted in statistical significant SNR deterioration in both frontal, temporal and ear electrodes. Recordings of alpha band modulation showed increased power and coherence of the EEG for ear and scalp electrodes in the closed-eyes periods. Ear-EEG is a method developed for unobtrusive and discreet recording over long periods of time and in real-life environments. This study investigated the influence of the most important types of physiological artifacts, and demonstrated that spontaneous activity, in terms of alpha band oscillations, could be recorded from the ear-EEG platform. In its present form ear-EEG was more prone to jaw related artifacts and less prone to eye-blinking artifacts compared to state-of-the-art scalp based systems.
Full Text Available Background: The cardiopulmonary resuscitation (CPR in prone position has been dealt with in 2010 American Heart Association (AHA guidelines but have not been reviewed in 2015 guidelines. The guidelines for patients presenting with cardiac arrest under general anesthesia in lateral decubitus position and regarding resuscitation in confined spaces like airplanes are also not available in AHA guidelines. This article is an attempt to highlight the techniques adopted for resuscitation in these unusual situations. Aims: This study aims to find out the methodology and efficacy in nonconventional CPR approaches such as CPR in prone, CPR in lateral position, and CPR in confined spaces. Methods: We conducted a literature search using MeSH search strings such as CPR + Prone position, CPR + lateral Position, and CPR + confined spaces. Results: No randomized controlled trials are available. The literature search gives a handful of case reports, some simulation- and manikin-based studies but none can qualify for class I evidence. The successful outcome of CPR performed in prone position has shown compressions delivered on the thoracic spine with the same rate and force as they were delivered during supine position. A hard surface is required under the patient to provide uniform force and sternal counter pressure. Two rescuer technique for providing successful chest compression in lateral position has been documented in the few case reports published. Over the head CPR and straddle (STR, CPR has been utilized for CPR in confined spaces. Ventilation in operating rooms was taken care by an advanced airway in situ. Conclusion: A large number of studies of high quality are required to be conducted to determine the efficacy of CPR in such positions.
Barry, Robert J; De Blasio, Frances M
Principal components analysis (PCA) has long been used to decompose the ERP into components, and these mathematical entities are increasingly accepted as meaningful and useful representatives of the electrophysiological components constituting the ERP. A similar expansion appears to be beginning in regard to decomposition of the EEG amplitude spectrum into frequency components via frequency PCA. However, to date, there has been no exploration of the brain's dynamic EEG-ERP linkages using PCA decomposition to assess components in each measure. Here, we recorded intrinsic EEG in both eyes-closed and eyes-open resting conditions, followed by an equiprobable go/no-go task. Frequency PCA of the EEG, including the nontask resting and within-task prestimulus periods, found seven frequency components within the delta to beta range. These differentially predicted PCA-derived go and no-go N1 and P3 ERP components. This demonstration suggests that it may be beneficial in future brain dynamics studies to implement PCA for the derivation of data-driven components from both the ERP and EEG. © 2017 Society for Psychophysiological Research.
Kaminska, A; Cheliout-Heraut, F; Eisermann, M; Touzery de Villepin, A; Lamblin, M D
In pediatrics, EEG recordings are performed on patients from the neonatal period up to young adults. This means adapting techniques to many different conditions, concerning not only the patient's age, the need for asepsis and the patient's behavior, but also the environment (e.g. in the laboratory, at the patient's bedside, or in the neonatal intensive care unit [NICU]). Technical requirements depend on age, indication and the type of examination; in infancy, there should be a minimum of 12 EEG electrodes, ECG and respiration recording. In epileptology, surface EMG is also necessary to characterize the type of seizures and refine the diagnosis of epilepsy syndrome, on which physicians will base their treatment choice. The role of the EEG technician is essential because the quality of the recording, its analysis and conclusion will depend on the quality of the technical set-up and the interaction with the child. Sleep is a systematic part of the study up to the age of 5 years for several reasons: sleep EEG yields information on brain maturation; the EEG tracing during wakefulness can contain too many artefacts; and some grapho-elements, key to the diagnosis, only appear during sleep. The time of the examination must be chosen according to the child's usual nap times, possibly after sleep deprivation. Grapho-elements and spatio-temporal organization of the EEG vary with age, and normal variants and unusual aspects are quite wide for any given age; this is why a physician experienced in pediatric EEG should perform the interpretation. This chapter concerns EEG performed in infants, children and adolescents, its technical aspects according to age and indications (general pediatrics, emergency, epilepsy). Copyright © 2015 Elsevier Masson SAS. All rights reserved.
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
L. Yu. Glukhova
Full Text Available Physiologic patterns of sleep on EEG can sometimes be similar to epileptiform activity and even to the EEG pattern of epileptic seizures, but they have no connection to epilepsy and their incorrect interpretation may lead to overdiagnosis of epilepsy. These sleep patterns include vertex transients, K-complexes, hypnagogic hypersynchrony, 14 and 6 Hz positive bursts, wicket-potentials, etc. The main distinctive features of acute physiological phenomena of sleep unlike epileptiform activity are stereotyped, monomorphic morphology of waves, which frequently has rhythmic, arcuate pattern, often with change of lateralization, mainly dominated in the first stages of sleep (N1-N2, with their reduction in the deeper stages and transition to delta sleep (N3. The correct interpretation of physiological sharp-wave phenomena of sleep on EEG requires considerable training and experience of the physician. Our review includes a variety of physiological sleep patterns, which can mimic epileptiform activity on EEG, their criteria of diagnostic with demonstration of own illustrations of EEG.
Olund, Thomas; Duun-Henriksen, Jonas; Kjaer, Troels W.
Ambulatory EEG monitoring can provide medical doctors important diagnostic information, without hospitalizing the patient. These recordings are however more exposed to noise and artifacts compared to clinically recorded EEG. An automatic artifact detection and classification algorithm for single......-channel EEG is proposed to help identifying these artifacts. Features are extracted from the EEG signal and wavelet subbands. Subsequently a selection algorithm is applied in order to identify the best discriminating features. A non-linear support vector machine is used to discriminate among different...... artifact classes using the selected features. Single-channel (Fp1-F7) EEG recordings are obtained from experiments with 12 healthy subjects performing artifact inducing movements. The dataset was used to construct and validate the model. Both subject-specific and generic implementation, are investigated...
Christensen, Christian Bech; Kidmose, Preben
Recently, a novel electroencephalographic (EEG) method called ear-EEG , that enable recording of auditory evoked potentials (AEPs) from a personalized earpiece was introduced. Initial investigations show that well established AEPs, such as ASSR and P1-N1-P2 complex can be observed from ear-EEG...
Laible, Michael R.
On November 23, 2011 International Space Station Guidance, Navigation, and Control reported unusual pitch rate disturbance. These disturbances were an order of magnitude greater than nominal rates. The Loads and Dynamics team was asked to review and analyze current accelerometer data to investigate this disturbance. This paper will cover the investigation process under taken by the Loads and Dynamics group. It will detail the accelerometers used and analysis performed. The analysis included performing Frequency Fourier Transform of the data to identify the mode of interest. This frequency data is then reviewed with modal analysis of the ISS system model. Once this analysis is complete and the disturbance quantified, a forcing function was produced to replicate the disturbance. This allows the Loads and Dynamics team to report the load limit values for the 100's of interfaces on the ISS.
Luijtelaar, E.L.J.M. van; Verbraak, M.J.P.M.; Bunt, P.M. van den; Keijsers, G.P.J.; Arns, M.W.
The concept of burnout remains enigmatic since it is only determined by behavioral characteristics. Moreover, the differential diagnosis with depression and chronic fatigue syndrome is difficult. EEG-related variables in 13 patients diagnosed with burnout syndrome were compared with 13 healthy
Bao, Forrest Sheng; Liu, Xin; Zhang, Christina
Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction.
Full Text Available The objective of this experiment was to determine the best possible input EEG feature for classification of the workload while designing load balancing logic for an automated operator. The input features compared in this study consisted of spectral features of Electroencephalography, objective scoring and subjective scoring. Method utilizes to identify best EEG feature as an input in Neural Network Classifiers for workload classification, to identify channels which could provide classification with the highest accuracy and for identification of EEG feature which could give discrimination among workload level without adding any classifiers. The result had shown Engagement Index is the best feature for neural network classification.
The aim of this study was to retrospectively audit all electroencephalograms (EEGs) done over a 2-month period in 2009 by the Neurophysiology Department at Cork University Hospital. There were 316 EEGs performed in total, of which 176\\/316 (56%) were done within 24 hours of request. Out of 316 EEGs, 208 (66%) were considered \\'appropriate\\' by SIGN and NICE guidelines; 79\\/208 (38%) had abnormal EEGs and 28 of these abnormal EEGs had epileptiform features. There were 108\\/316 (34%) \\'inappropriate\\' requests for EEG; of these 15\\/108 (14%) were abnormal. Of the 67\\/316 (21%) patients who had EEGs requested based on a history of syncope\\/funny turns: none of these patients had epileptiform abnormalities on their EEGs. Our audit demonstrates that EEGs are inappropriately over-requested in our institution in particular for cases with reported \\'funny turns\\' and syncope. The yield from EEGs in this cohort of patients was low as would be expected.
Hill, Julienne Marie [Iowa State Univ., Ames, IA (United States)
Doping experiments on La2CuO4, Sr2CuO3 and SrCu2(BO3)2 were performed with the intent of synthesizing new metallic low-=dimensional cuprate oxide compounds. Magnetic susceptibility χ(T) measurements on a polycrystalline La2CuO4 sample chemically oxidized at room temperature in aqueous NaClO showed superconductivity with a superconducting transition temperature Tc of 42.6 K and a Meissner fraction of 26%. They were unable to electrochemically oxidize La2CuO4 in a nonaqueous solution of tetramethylammonium hydroxide (TMAOH) and methanol. Sr2CuO3 was found to decompose upon exposure to air and water. Electron paramagnetic resonance, isothermal magnetization M(H), and χ(T) measurements on the primary decomposition product, Sr2Cu(OH)6, were consistent with a nearly isolated, spin S = 1/2, local moment model for the Cu+2 spins. From a fit of χ(T) by the Curie-Weiss law and of the M(H) isotherms by a modified Brillouin function, the weakly antiferromagnetic exchange interaction between adjacent Cu+2 spins in Sr2Cu(OH)6 was found to be J/kB = 1.06(4) K. Doping studies on SrCu2(BO3)2 were inconclusive. χ(T) measurements on an undoped polycrystalline sample of SrCu2(BO3)2, a sample treated with distilled water, and a sample treated with aqueous NaClO showed no qualitative differences between the samples. In addition, χ(T) and M(H, T) studies of the ultra-hard material MgAlB14 were carried out in search of superconductivity or ferromagnetism in this compound. χ(T) measurements on a powder sample revealed temperature-independent diamagnetism from 1.8 K up to room temperature with a Curie-Weiss impurity concentration equivalent to ~ 1 mol% of spin-1/2 ions. In contrast
Full Text Available Brain Computer Interface has a potency to be applied in mechatronics apparatus and vehicles in the future. Compared to the other techniques, EEG is the most preferred for BCI designs. In this paper, a new adaptive neural network classifier of different mental activities from EEG-based P300 signals is proposed. To overcome the over-training that is caused by noisy and non-stationary data, the EEG signals are filtered and extracted using autoregressive models before passed to the adaptive neural networks classifier. To test the improvement in the EEG classification performance with the proposed method, comparative experiments were conducted using Bayesian Linear Discriminant Analysis. The experiment results show that the all subjects achieve a classification accuracy of 100%.
Full Text Available Electroencephalogram (EEG recordings signal provide an important function of brain-computer communication, but the accuracy of their classification is very limited in unforeseeable signal variations relating to artifacts. In this paper, we propose a classification method entailing time-series EEG-P300 signals using backpropagation neural networks to predict the qualitative properties of a subject’s mental tasks by extracting useful information from the highly multivariate non-invasive recordings of brain activity. To test the improvement in the EEG-P300 classification performance (i.e., classification accuracy and transfer rate with the proposed method, comparative experiments were conducted using Bayesian Linear Discriminant Analysis (BLDA. Finally, the result of the experiment showed that the average of the classification accuracy was 97% and the maximum improvement of the average transfer rate is 42.4%, indicating the considerable potential of the using of EEG-P300 for the continuous classification of mental tasks.
Bazán-Prieto, Carlos; Blanco-Velasco, Manuel; Cruz-Roldán, Fernando; Cárdenas-Barrera, Julián
Coding distortion in lossy electroencephalographic (EEG) signal compression methods is evaluated through tractable objective criteria. The percentage root-mean-square difference, which is a global and relative indicator of the quality held by reconstructed waveforms, is the most widely used criterion. However, this parameter does not ensure compliance with clinical standard guidelines that specify limits to allowable noise in EEG recordings. As a result, expert clinicians may have difficulties interpreting the resulting distortion of the EEG for a given value of this parameter. Conversely, the root-mean-square error is an alternative criterion that quantifies distortion in understandable units. In this paper, we demonstrate that the root-mean-square error is better suited to control and to assess the distortion introduced by compression methods. The experiments conducted in this paper show that the use of the root-mean-square error as target parameter in EEG compression allows both clinicians and scientists to infer whether coding error is clinically acceptable or not at no cost for the compression ratio. (paper)
Black, Christopher; Voigts, Jakob; Agrawal, Uday; Ladow, Max; Santoyo, Juan; Moore, Christopher; Jones, Stephanie
Electroencephalography (EEG) offers a unique opportunity to study human neural activity non-invasively with millisecond resolution using minimal equipment in or outside of a lab setting. EEG can be combined with a number of techniques for closed-loop experiments, where external devices are driven by specific neural signals. However, reliable, commercially available EEG systems are expensive, often making them impractical for individual use and research development. Moreover, by design, a majority of these systems cannot be easily altered to the specification needed by the end user. We focused on mitigating these issues by implementing open-source tools to develop a new EEG platform to drive down research costs and promote collaboration and innovation. Here, we present methods to expand the open-source electrophysiology system, Open Ephys (www.openephys.org), to include human EEG recordings. We describe the equipment and protocol necessary to interface various EEG caps with the Open Ephys acquisition board, and detail methods for processing data. We present applications of Open Ephys + EEG as a research tool and discuss how this innovative EEG technology lays a framework for improved closed-loop paradigms and novel brain-computer interface experiments. The Open Ephys + EEG system can record reliable human EEG data, as well as human EMG data. A side-by-side comparison of eyes closed 8-14 Hz activity between the Open Ephys + EEG system and the Brainvision ActiCHamp EEG system showed similar average power and signal to noise. Open Ephys + EEG enables users to acquire high-quality human EEG data comparable to that of commercially available systems, while maintaining the price point and extensibility inherent to open-source systems.
Black, Christopher; Voigts, Jakob; Agrawal, Uday; Ladow, Max; Santoyo, Juan; Moore, Christopher; Jones, Stephanie
Objective. Electroencephalography (EEG) offers a unique opportunity to study human neural activity non-invasively with millisecond resolution using minimal equipment in or outside of a lab setting. EEG can be combined with a number of techniques for closed-loop experiments, where external devices are driven by specific neural signals. However, reliable, commercially available EEG systems are expensive, often making them impractical for individual use and research development. Moreover, by design, a majority of these systems cannot be easily altered to the specification needed by the end user. We focused on mitigating these issues by implementing open-source tools to develop a new EEG platform to drive down research costs and promote collaboration and innovation. Approach. Here, we present methods to expand the open-source electrophysiology system, Open Ephys (www.openephys.org), to include human EEG recordings. We describe the equipment and protocol necessary to interface various EEG caps with the Open Ephys acquisition board, and detail methods for processing data. We present applications of Open Ephys + EEG as a research tool and discuss how this innovative EEG technology lays a framework for improved closed-loop paradigms and novel brain-computer interface experiments. Main results. The Open Ephys + EEG system can record reliable human EEG data, as well as human EMG data. A side-by-side comparison of eyes closed 8-14 Hz activity between the Open Ephys + EEG system and the Brainvision ActiCHamp EEG system showed similar average power and signal to noise. Significance. Open Ephys + EEG enables users to acquire high-quality human EEG data comparable to that of commercially available systems, while maintaining the price point and extensibility inherent to open-source systems.
Shatnawi, Nawaf J.; Bani-Hani, Kamal E.
We herein report our experience regarding unusual causes of bowel obstruction to increase the awareness of surgeons regarding this disease. From 1991 to 2003, we had experience at the University affiliated hospitals, northern Jordan with 24 patients with small bowel obstruction resulting from unusual causes. We retrospectively reviewed the medical records of these patients with regards to the mode of presentation, cause of obstruction, radiological and operative findings, management and outcome. We recorded 15 patients who underwent previous abdominal surgery. Preoperative diagnosis was correct in only one patient with an internal hernia, but the abdominal CT scan suggested the diagnosis in 5 of the 9 patients who had the scan. The final diagnosis was internal hernias in 11 patients, foreign bodies in 5, ischemic strictures in 3, carcinoid tumors in 2, endometriosis in 2, and metastatic deposit from interstitial bladder carcinoma in one patient. Nine of the 12 patients with recurrent obstruction had either short course or recurrence obstruction during the same hospital admission. W carried out bowel resections in 15 patients (5 resections were due to bowel strangulation). Post operative death occurred in 4 patients. Awareness of these rare causes of intestinal obstruction even in patients with previous abdominal operation might improve the outcome. The tentative diagnosis of adhesion obstruction in patients with unusual obstructive etiology might lead to a higher rate of gangrenous complications. Rigorous preoperative evaluation including careful history and early abdominal CT may show the obstructive cause. (author)
Full Text Available Independent component analysis (ICA and blind source separation (BSS methods are increasingly used to separate individual brain and non-brain source signals mixed by volume conduction in electroencephalographic (EEG and other electrophysiological recordings. We compared results of decomposing thirteen 71-channel human scalp EEG datasets by 22 ICA and BSS algorithms, assessing the pairwise mutual information (PMI in scalp channel pairs, the remaining PMI in component pairs, the overall mutual information reduction (MIR effected by each decomposition, and decomposition 'dipolarity' defined as the number of component scalp maps matching the projection of a single equivalent dipole with less than a given residual variance. The least well-performing algorithm was principal component analysis (PCA; best performing were AMICA and other likelihood/mutual information based ICA methods. Though these and other commonly-used decomposition methods returned many similar components, across 18 ICA/BSS algorithms mean dipolarity varied linearly with both MIR and with PMI remaining between the resulting component time courses, a result compatible with an interpretation of many maximally independent EEG components as being volume-conducted projections of partially-synchronous local cortical field activity within single compact cortical domains. To encourage further method comparisons, the data and software used to prepare the results have been made available (http://sccn.ucsd.edu/wiki/BSSComparison.
White, David; Ciorciari, Joseph; Carbis, Colin; Liley, David
The study investigated hypnosis-related electroencephalographic (EEG) coherence and power spectra changes in high and low hypnotizables (Stanford Hypnotic Clinical Scale) induced by a virtual reality hypnosis (VRH) induction system. In this study, the EEG from 17 participants (Mean age = 21.35, SD = 1.58) were compared based on their hypnotizability score. The EEG recording associated with a 2-minute, eyes-closed baseline state was compared to the EEG during a hypnosis-related state. This novel induction system was able to produce EEG findings consistent with previous hypnosis literature. Interactions of significance were found with EEG beta coherence. The high susceptibility group (n = 7) showed decreased coherence, while the low susceptibility group (n = 10) demonstrated an increase in coherence between medial frontal and lateral left prefrontal sites. Methodological and efficacy issues are discussed.
Pedersen, S B; Petersen, K A
We aimed to characterize the clinical profile and EEG features of 43 patients with juvenile myoclonic epilepsy. In a retrospective design we studied the records of, and re-interviewed, 43 patients diagnosed with JME from the epilepsy clinic data base. Furthermore, available EEGs were re...... were sleep deprivation (84%), stress (70%), and alcohol consumption (51%). EEG findings included rapid spike-wave and polyspike-wave....
Pedersen, S B; Petersen, K A
We aimed to characterize the clinical profile and EEG features of 43 patients with juvenile myoclonic epilepsy. In a retrospective design we studied the records of, and re-interviewed, 43 patients diagnosed with JME from the epilepsy clinic data base. Furthermore, available EEGs were re-evaluated...... were sleep deprivation (84%), stress (70%), and alcohol consumption (51%). EEG findings included rapid spike-wave and polyspike-wave....
McEvoy, L. K.; Smith, M. E.; Gevins, A.
OBJECTIVE: Task-related EEG is sensitive to changes in cognitive state produced by increased task difficulty and by transient impairment. If task-related EEG has high test-retest reliability, it could be used as part of a clinical test to assess changes in cognitive function. The aim of this study was to determine the reliability of the EEG recorded during the performance of a working memory (WM) task and a psychomotor vigilance task (PVT). METHODS: EEG was recorded while subjects rested quietly and while they performed the tasks. Within session (test-retest interval of approximately 1 h) and between session (test-retest interval of approximately 7 days) reliability was calculated for four EEG components: frontal midline theta at Fz, posterior theta at Pz, and slow and fast alpha at Pz. RESULTS: Task-related EEG was highly reliable within and between sessions (r0.9 for all components in WM task, and r0.8 for all components in the PVT). Resting EEG also showed high reliability, although the magnitude of the correlation was somewhat smaller than that of the task-related EEG (r0.7 for all 4 components). CONCLUSIONS: These results suggest that under appropriate conditions, task-related EEG has sufficient retest reliability for use in assessing clinical changes in cognitive status.
Lemesle, M; Kubis, N; Sauleau, P; N'Guyen The Tich, S; Touzery-de Villepin, A
EEG recordings can be sent for remote interpretation. This article aims to define the tele-EEG procedures and technical guidelines. Tele-EEG is a complete medical act that needs to be carried out with the same quality requirements as a local one in terms of indications, formulation of the medical request and medical interpretation. It adheres to the same quality requirements for its human resources and materials. It must be part of a medical organization (technical and medical network) and follow all rules and guidelines of good medical practices. The financial model of this organization must include costs related to performing the EEG recording, operating and maintenance of the tele-EEG network and medical fees of the physician interpreting the EEG recording. Implementing this organization must be detailed in a convention between all parties involved: physicians, management of the healthcare structure, and the company providing the tele-EEG service. This convention will set rules for network operation and finance, and also the continuous training of all staff members. The tele-EEG system must respect all rules for safety and confidentiality, and ensure the traceability and storing of all requests and reports. Under these conditions, tele-EEG can optimize the use of human resources and competencies in its zone of utilization and enhance the organization of care management. Copyright © 2015. Published by Elsevier SAS.
Full Text Available The endoscopic retrograde cholangiopancreatography (ERCP is known for its varied diagnostic and therapeutic utility for a variety of disorders. However it has greater likelihood of procedure related complications among the endoscopic procedures of gastrointestinal tract. The extraluminal hemorrhagic complications following ERCP are potentially life threatening though relatively rare. We present a 50 year patient with choledocholithiasis and cholelithiasis developing rare complication of subcapsular hepatic hematoma, following ERCP due to guide wire injury.
Mervaala, Esa; Mäkinen, Riikka; Peltola, Jukka; Eriksson, Kai; Jutila, Leena; Immonen, Arto
Aivosähkötoimintaa mittaava EEG on epilepsian spesifinen tutkimus. Video-EEG:llä (V-EEG) tarkoitetaan EEG:n ja videokuvan samanaikaista tallennusta. Valtaosa epilepsiapotilaista joudutaan diagnosoimaan ilman V-EEG:tä, varsinkin jos kohtauksia on esiintynyt vain muutama. Kohtausten toistuessa tavoite on päästä kohtauksenaikaiseen V-EEG-rekisteröintiin. V-EEG:n käyttöaiheista tärkein on epilepsian diagnostiikka ja erotusdiagnostiikka. V-EEG:llä pystytään erottamaan epileptiset kohtaukset esimer...
Stjerna, Susanna; Voipio, Juha; Metsäranta, Marjo; Kaila, Kai; Vanhatalo, Sampsa
Since its introduction in early 1950s, electroencephalography (EEG) has been widely used in the neonatal intensive care units (NICU) for assessment and monitoring of brain function in preterm and term babies. Most common indications are the diagnosis of epileptic seizures, assessment of brain maturity, and recovery from hypoxic-ischemic events. EEG recording techniques and the understanding of neonatal EEG signals have dramatically improved, but these advances have been slow to penetrate through the clinical traditions. The aim of this presentation is to bring theory and practice of advanced EEG recording available for neonatal units. In the theoretical part, we will present animations to illustrate how a preterm brain gives rise to spontaneous and evoked EEG activities, both of which are unique to this developmental phase, as well as crucial for a proper brain maturation. Recent animal work has shown that the structural brain development is clearly reflected in early EEG activity. Most important structures in this regard are the growing long range connections and the transient cortical structure, subplate. Sensory stimuli in a preterm baby will generate responses that are seen at a single trial level, and they have underpinnings in the subplate-cortex interaction. This brings neonatal EEG readily into a multimodal study, where EEG is not only recording cortical function, but it also tests subplate function via different sensory modalities. Finally, introduction of clinically suitable dense array EEG caps, as well as amplifiers capable of recording low frequencies, have disclosed multitude of brain activities that have as yet been overlooked. In the practical part of this video, we show how a multimodal, dense array EEG study is performed in neonatal intensive care unit from a preterm baby in the incubator. The video demonstrates preparation of the baby and incubator, application of the EEG cap, and performance of the sensory stimulations.
Subject of the paper are the IAEA cooperative patterns of unusual events data treatment and utilization of the operating safety experience feedback. The Incident Reporting System (IRS) and the Analysis of Safety Significant Event Team (ASSET) are discussed. The IRS methodology in collection, handling, assessment and dissemination of data on NPP unusual events (deviations, incidents and accidents) occurring during operations, surveillance and maintenance is outlined by the reports gathering and issuing practice, the experts assessment procedures and the parameters of the system. After 7 years of existence the IAEA-IRS contains over 1000 reports and receives 1.5-4% of the total information on unusual events. The author considers the reports only as detailed technical 'records' of events requiring assessment. The ASSET approaches implying an in-depth occurrences analysis directed towards level-1 PSA utilization are commented on. The experts evaluated root causes for the reported events and some trends are presented. Generally, internal events due to unexpected paths of water in the nuclear installations, occurrences related to the integrity of the primary heat transport systems, events associated with the engineered safety systems and events involving human factor represent the large groups deserving close attention. Personal recommendations on how to use the events related information use for NPP safety improvement are given. 2 tabs (R.Ts)
Koren, J; Herta, J; Draschtak, S; Pötzl, G; Pirker, S; Fürbass, F; Hartmann, M; Kluge, T; Baumgartner, C
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
Full Text Available For controlling the prosthetic hand by only electroencephalogram (EEG, it has become the hot spot in robotics research to set up a direct communication and control channel between human brain and prosthetic hand. In this paper, the EEG signal is analyzed based on multi-complicated hand activities. And then, two methods of EEG pattern recognition are investigated, a neural prosthesis hand system driven by BCI is set up, which can complete four kinds of actions (arm’s free state, arm movement, hand crawl, hand open. Through several times of off-line and on-line experiments, the result shows that the neural prosthesis hand system driven by BCI is reasonable and feasible, the C-support vector classifiers-based method is better than BP neural network on the EEG pattern recognition for multi-complicated hand activities.
Bleichner, Martin G.; Debener, Stefan
Electroencephalography (EEG) is an important clinical tool and frequently used to study the brain-behavior relationship in humans noninvasively. Traditionally, EEG signals are recorded by positioning electrodes on the scalp and keeping them in place with glue, rubber bands, or elastic caps. This setup provides good coverage of the head, but is impractical for EEG acquisition in natural daily-life situations. Here, we propose the transparent EEG concept. Transparent EEG aims for motion tolerant, highly portable, unobtrusive, and near invisible data acquisition with minimum disturbance of a user's daily activities. In recent years several ear-centered EEG solutions that are compatible with the transparent EEG concept have been presented. We discuss work showing that miniature electrodes placed in and around the human ear are a feasible solution, as they are sensitive enough to pick up electrical signals stemming from various brain and non-brain sources. We also describe the cEEGrid flex-printed sensor array, which enables unobtrusive multi-channel EEG acquisition from around the ear. In a number of validation studies we found that the cEEGrid enables the recording of meaningful continuous EEG, event-related potentials and neural oscillations. Here, we explain the rationale underlying the cEEGrid ear-EEG solution, present possible use cases and identify open issues that need to be solved on the way toward transparent EEG. PMID:28439233
Schetinin, Vitaly; Jakaite, Livija; Nyah, Ndifreke; Novakovic, Dusica; Krzanowski, Wojtek
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.
Henriksen, Jonas; Remvig, Line Sofie; Madsen, Rasmus Elsborg
Several different algorithms have been proposed for automatic detection of epileptic seizures based on both scalp and intracranial electroencephalography (sEEG and iEEG). Which modality that renders the best result is hard to assess though. From 16 patients with focal epilepsy, at least 24 hours...... of ictal and non-ictal iEEG were obtained. Characteristics of the seizures are represented by use of wavelet transformation (WT) features and classified by a support vector machine. When implementing a method used for sEEG on iEEG data, a great improvement in performance was obtained when the high...... frequency containing lower levels in the WT were included in the analysis. We were able to obtain a sensitivity of 96.4% and a false detection rate (FDR) of 0.20/h. In general, when implementing an automatic seizure detection algorithm made for sEEG on iEEG, great improvement can be obtained if a frequency...
Full Text Available Objective: Entropy algorithms have been widely used in analyzing EEG signals during anesthesia. However, a systematic comparison of these entropy algorithms in assessing anesthesia drugs’ effect is lacking. In this study, we compare the capability of twelve entropy indices for monitoring depth of anesthesia (DoA and detecting the burst suppression pattern (BSP, in anesthesia induced by GA-BAergic agents.Methods: Twelve indices were investigated, namely Response Entropy (RE and State entropy (SE, three wavelet entropy (WE measures (Shannon WE (SWE, Tsallis WE (TWE and Renyi WE (RWE, Hilbert-Huang spectral entropy (HHSE, approximate entropy (ApEn, sample entropy (SampEn, Fuzzy entropy, and three permutation entropy (PE measures (Shannon PE (SPE, Tsallis PE (TPE and Renyi PE (RPE. Two EEG data sets from sevoflurane-induced and isoflu-rane-induced anesthesia respectively were selected to assess the capability of each entropy index in DoA monitoring and BSP detection. To validate the effectiveness of these entropy algorithms, phar-macokinetic / pharmacodynamic (PK/PD modeling and prediction probability analysis were applied. The multifractal detrended fluctuation analysis (MDFA as a non-entropy measure was compared.Results: All the entropy and MDFA indices could track the changes in EEG pattern during different anesthesia states. Three PE measures outperformed the other entropy indices, with less baseline vari-ability, higher coefficient of determination and prediction probability, and RPE performed best; ApEn and SampEn discriminated BSP best. Additionally, these entropy measures showed an ad-vantage in computation efficiency compared with MDFA.Conclusion: Each entropy index has its advantages and disadvantages in estimating DoA. Overall, it is suggested that the RPE index was a superior measure.Significance: Investigating the advantages and disadvantages of these entropy indices could help improve current clinical indices for monitoring DoA.
Liang, Zhenhu; Wang, Yinghua; Sun, Xue; Li, Duan; Voss, Logan J.; Sleigh, Jamie W.; Hagihira, Satoshi; Li, Xiaoli
Highlights: ► Twelve entropy indices were systematically compared in monitoring depth of anesthesia and detecting burst suppression.► Renyi permutation entropy performed best in tracking EEG changes associated with different anesthesia states.► Approximate Entropy and Sample Entropy performed best in detecting burst suppression. Objective: Entropy algorithms have been widely used in analyzing EEG signals during anesthesia. However, a systematic comparison of these entropy algorithms in assessing anesthesia drugs' effect is lacking. In this study, we compare the capability of 12 entropy indices for monitoring depth of anesthesia (DoA) and detecting the burst suppression pattern (BSP), in anesthesia induced by GABAergic agents. Methods: Twelve indices were investigated, namely Response Entropy (RE) and State entropy (SE), three wavelet entropy (WE) measures [Shannon WE (SWE), Tsallis WE (TWE), and Renyi WE (RWE)], Hilbert-Huang spectral entropy (HHSE), approximate entropy (ApEn), sample entropy (SampEn), Fuzzy entropy, and three permutation entropy (PE) measures [Shannon PE (SPE), Tsallis PE (TPE) and Renyi PE (RPE)]. Two EEG data sets from sevoflurane-induced and isoflurane-induced anesthesia respectively were selected to assess the capability of each entropy index in DoA monitoring and BSP detection. To validate the effectiveness of these entropy algorithms, pharmacokinetic/pharmacodynamic (PK/PD) modeling and prediction probability (Pk) analysis were applied. The multifractal detrended fluctuation analysis (MDFA) as a non-entropy measure was compared. Results: All the entropy and MDFA indices could track the changes in EEG pattern during different anesthesia states. Three PE measures outperformed the other entropy indices, with less baseline variability, higher coefficient of determination (R2) and prediction probability, and RPE performed best; ApEn and SampEn discriminated BSP best. Additionally, these entropy measures showed an advantage in computation
Thompson, Trevor; Steffert, Tony; Ros, Tomas; Leach, Joseph; Gruzelier, John
One approach to understanding processes that underlie skilled performing has been to study electrical brain activity using electroencephalography (EEG). A notorious problem with EEG is that genuine cerebral data is often contaminated by artifacts of non-cerebral origin. Unfortunately, such artifacts tend to be exacerbated when the subject is in motion, meaning that obtaining reliable data during exercise is inherently problematic. These problems may explain the limited number of studies using EEG as a methodological tool in the sports sciences. This paper discusses how empirical studies have generally tackled the problem of movement artifact by adopting alternative paradigms which avoid recording during actual physical exertion. Moreover, the specific challenges that motion presents to obtaining reliable EEG data are discussed along with practical and computational techniques to confront these challenges. Finally, as EEG recording in sports is often underpinned by a desire to optimise performance, a brief review of EEG-biofeedback and peak performance studies is also presented. A knowledge of practical aspects of EEG recording along with the advent of new technology and increasingly sophisticated processing models offer a promising approach to minimising, if perhaps not entirely circumventing, the problem of obtaining reliable EEG data during motion.
Scott, D F; Moffett, A M; Swash, M
Oral tyramine activated pre-existing episodic EEG abnormalities--namely, sharp waves, spike and wave, and localised theta activity--in epileptic patients. Little change was found in the EEGs of migrainous subjects after chocolate or beta-phenylethylamine. The implications of the findings with tyramine are discussed.
Beniczky, Sándor; Lantz, Göran; Rosenzweig, Ivana
Although precise identification of the seizure-onset zone is an essential element of presurgical evaluation, source localization of ictal electroencephalography (EEG) signals has received little attention. The aim of our study was to estimate the accuracy of source localization of rhythmic ictal...... EEG activity using a distributed source model....
Hayashi, Mitsuo; Katoh, Kohichi; Hori, Tadao
The aim of this study is to investigate the relationships between hypnagogic imagery and EEG stages. According to Hori, et al. (1994), the hypnagogic EEGs was classified into 9 stages, those were 1) alpha wave train, 2) alpha wave intermittent (>50%), 3) alpha wave intermittent (
Kondziella, Daniel; Friberg, Christian Kærsmose; Wellwood, Ian
BACKGROUND: Continuous EEG (cEEG) may allow monitoring of patients with aneurysmal subarachnoid hemorrhage (SAH) for delayed cerebral ischemia (DCI) and seizures, including non-convulsive seizures (NCSz), and non-convulsive status epilepticus (NCSE). We aimed to evaluate: (a) the diagnostic...
Varley, James; Wehner, Tim; Sisodiya, Sanjay
In this report, we describe a female patient with trisomy 4p, a rare genetic condition, with unusual seizure semiology. The patient is one of the oldest reported survivors with this condition. This semiology was noted while she was being monitored by inpatient video telemetry. We observed a series of myoclonic shoulder jerks, followed by hiccup-like episodes, and finally an atonic head drop. Corresponding ictal EEG showed semi-rhythmic high-amplitude slow waves with spikes superimposed over the frontotemporal areas. This semiology was confirmed as habitual by her parents. Subsequent hiccup-like episodes had no EEG correlate, and the head drop was again associated with semi-rhythmic high-amplitude slow waves and superimposed spikes, more prominent over the right hemisphere. In addition, we review the several cases in which hiccups have been associated with seizures and how this may relate to the neural pathways involved in the pathophysiology of hiccups. We believe the ictal hiccup-like episodes followed by atonia to be a seizure semiology that has not previously been documented. [Published with video sequence].
Popivanov, D; Mineva, A; Krekule, I
In experiments with EEG accompanying continuous slow goal-directed voluntary movements we found abrupt short-term transients (STs) of the coefficients of EEG time-varying autoregressive (TVAR) model. The onset of STs indicated (i) a positive EEG wave related to an increase of 3-7 Hz oscillations in time period before the movement start, (ii) synchronization of 35-40 Hz prior to movement start and during the movement when the target is nearly reached. Both these phenomena are expressed predominantly over supplementary motor area, premotor and parietal cortices. These patterns were detected after averaging of EEG segments synchronized to the abrupt changes of the TVAR coefficients computed in the time course of EEG single records. The results are discussed regarding the cognitive aspect of organization of goal-directed movements.
Gayet, J.-F.; Mioche, G.; Bugliaro, L.; Protat, A.; Minikin, A.; Wirth, M.; Dörnbrack, A.; Shcherbakov, V.; Mayer, B.; Garnier, A.; Gourbeyre, C.
During the CIRCLE-2 experiment carried out over Western Europe in May 2007, combined in situ and remote sensing observations allowed to describe microphysical and optical properties near-top of an overshooting convective cloud (11 080 m/-58 °C). The airborne measurements were performed with the DLR Falcon aircraft specially equipped with a unique set of instruments for the extensive in situ cloud measurements of microphysical and optical properties (Polar Nephelometer, FSSP-300, Cloud Particle Imager and PMS 2-D-C) and nadir looking remote sensing observations (DLR WALES Lidar). Quasi-simultaneous space observations from MSG/SEVIRI, CALIPSO/CALIOP-WFC-IIR and CloudSat/CPR combined with airborne RASTA radar reflectivity from the French Falcon aircraft flying above the DLR Falcon depict very well convective cells which overshoot by up to 600 m the tropopause level. Unusual high values of the concentration of small ice particles, extinction, ice water content (up to 70 cm-3, 30 km-1 and 0.5 g m-3, respectively) are experienced. The mean effective diameter and the maximum particle size are 43 μm and about 300 μm, respectively. This very dense cloud causes a strong attenuation of the WALES and CALIOP lidar returns. The SEVIRI retrieved parameters confirm the occurrence of small ice crystals at the top of the convective cell. Smooth and featureless phase functions with asymmetry factors of 0.776 indicate fairly uniform optical properties. Due to small ice crystals the power-law relationship between ice water content (IWC) and radar reflectivity appears to be very different from those usually found in cirrus and anvil clouds. For a given equivalent reflectivity factor, IWCs are significantly larger for the overshooting cell than for the cirrus. Assuming the same prevalent microphysical properties over the depth of the overshooting cell, RASTA reflectivity profiles scaled into ice water content show that retrieved IWC up to 1 g m-3 may be observed near the cloud top
Full Text Available During the CIRCLE-2 experiment carried out over Western Europe in May 2007, combined in situ and remote sensing observations allowed to describe microphysical and optical properties near-top of an overshooting convective cloud (11 080 m/−58 °C. The airborne measurements were performed with the DLR Falcon aircraft specially equipped with a unique set of instruments for the extensive in situ cloud measurements of microphysical and optical properties (Polar Nephelometer, FSSP-300, Cloud Particle Imager and PMS 2-D-C and nadir looking remote sensing observations (DLR WALES Lidar. Quasi-simultaneous space observations from MSG/SEVIRI, CALIPSO/CALIOP-WFC-IIR and CloudSat/CPR combined with airborne RASTA radar reflectivity from the French Falcon aircraft flying above the DLR Falcon depict very well convective cells which overshoot by up to 600 m the tropopause level. Unusual high values of the concentration of small ice particles, extinction, ice water content (up to 70 cm−3, 30 km−1 and 0.5 g m−3, respectively are experienced. The mean effective diameter and the maximum particle size are 43 μm and about 300 μm, respectively. This very dense cloud causes a strong attenuation of the WALES and CALIOP lidar returns. The SEVIRI retrieved parameters confirm the occurrence of small ice crystals at the top of the convective cell. Smooth and featureless phase functions with asymmetry factors of 0.776 indicate fairly uniform optical properties. Due to small ice crystals the power-law relationship between ice water content (IWC and radar reflectivity appears to be very different from those usually found in cirrus and anvil clouds. For a given equivalent reflectivity factor, IWCs are significantly larger for the overshooting cell than for the cirrus. Assuming the same prevalent microphysical properties over the depth of the overshooting cell, RASTA reflectivity profiles scaled into ice water content show that retrieved
Miao, Tiejun; Oyama-Higa, Mayumi; Sato, Sadaka; Kojima, Junji; Lin, Juan; Reika, Sato
We studied a relation of chaotic dynamics of finger plethysmogram to complexity of high cerebral center in both theoretical and experimental approaches. We proposed a mathematical model to describe emergence of chaos in finger tip pulse wave, which gave a theoretical prediction indicating increased chaoticity in higher cerebral center leading to an increase of chaos dynamics in plethysmograms. We designed an experiment to observe scalp-EEG and finger plethysmogram using two mental tasks to validate the relationship. We found that scalp-EEG showed an increase of the largest Lyapunov exponents (LLE) during speaking certain voices. Topographical scalp map of LLE showed enhanced arise around occipital and right cerebral area. Whereas there was decreasing tendency during listening music, where LLE scalp map revealed a drop around center cerebral area. The same tendency was found for LLE obtained from finger plethysmograms as ones of EEG under either speaking or listening tasks. The experiment gave results that agreed well with the theoretical relation derived from our proposed model.
The title of the report was intended to reflect the cause of the shutdown and the report to be regarded as a summary of the deficiencies that had been revealed and remedied. No single deficiency was regarded as reportable as an unusual event, but taken together the identified deficiencies deviated from the assumed safety level to the extent that it should be reported. The unusual event report refers to two main documents presenting measures taken to return to reported safety level, one concerning technical and one organizational measures
Paradoxical or "forced" normalization of the EEG of patients with epilepsy was first described by Landolt in 1953. It refers to conditions where disappearance of epileptiform discharge from the routine scalp EEG is accompanied by some kind of behavioral disorder. The best known of these is a paranoid psychotic state in clear consciousness, which is also known as "alternative" psychosis. Thus, the issue is related to much older observations which indicated a "biological antagonism" between productive psychotic symptomatology and epileptic seizures, which led to the therapy of psychoses with artificially induced convulsions. Apart from psychotic episodes, the clinical manifestations of PN comprise dysphoric states, hysterical and hypochondriacal syndromes, affective disorders, and miscellanea. PN can be observed in both generalized and localization-related epilepsies as a rare complication. A subset where it is more frequently seen are in adults with persistent absence seizures when the latter become finally controlled by succinimide therapy. These seem to be the drugs with the highest hazard of precipitation of PN, but all other AEDs have also been suspected. Sleep disturbance by succinimide treatment may play a crucial role, but a variety of other factors are also involved, including psychosocial factors. The pathogenesis of this condition has given rise to some debate but remains still unresolved. Eleven of the most important hypotheses have been discussed and seem to converge into a more comprehensive hypothesis which basically assumes that, during PN, the epilepsy is still active subcortically, perhaps with spread of discharge along unusual pathways. This activity is supposed to provide energy and, possibly, some of the symptoms included in the psychotic syndrome. A critical clinical condition results, usually with a dysphoric symptomatology, where a development towards psychosis is impending but still depends on the presence or absence of a variety of risk
Whittingstall, Kevin; Bartels, Andreas; Singh, Vanessa; Kwon, Soyoung; Logothetis, Nikos K
Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are noninvasive neuroimaging tools which can be used to measure brain activity with excellent temporal and spatial resolution, respectively. By combining the neural and hemodynamic recordings from these modalities, we can gain better insight into how and where the brain processes complex stimuli, which may be especially useful in patients with different neural diseases. However, due to their vastly different spatial and temporal resolutions, the integration of EEG and fMRI recordings is not always straightforward. One fundamental obstacle has been that paradigms used for EEG experiments usually rely on event-related paradigms, while fMRI is not limited in this regard. Therefore, here we ask whether one can reliably localize stimulus-driven EEG activity using the continuously varying feature intensities occurring in natural movie stimuli presented over relatively long periods of time. Specifically, we asked whether stimulus-driven aspects in the EEG signal would be co-localized with the corresponding stimulus-driven BOLD signal during free viewing of a movie. Secondly, we wanted to integrate the EEG signal directly with the BOLD signal, by estimating the underlying impulse response function (IRF) that relates the BOLD signal to the underlying current density in the primary visual area (V1). We made sequential fMRI and 64-channel EEG recordings in seven subjects who passively watched 2-min-long segments of a James Bond movie. To analyze EEG data in this natural setting, we developed a method based on independent component analysis (ICA) to reject EEG artifacts due to blinks, subject movement, etc., in a way unbiased by human judgment. We then calculated the EEG source strength of this artifact-free data at each time point of the movie within the entire brain volume using low-resolution electromagnetic tomography (LORETA). This provided for every voxel in the brain (i.e., in 3D space) an
Nikhil NBA, Natarajan K, Mohanty A, et al. An. Unusual Case of Maydl's Hernia. Int J Cur Res Rev. 2013;5(6):22-5. 11. Ganesaratnam M. Maydl's hernia: Report of a Series of Seven Cases and Review of Literature. Brit J Surg. 1985;72:737-8. 12. Weledji EP, Mokake M, Ngowe MN. A Rare. Presentation of Maydl's Hernia.
Paul, Karel; Krajca, Vladimír; Roth, Zdenek; Melichar, Jan; Petránek, Svojmil
To test the discriminatory topographic potential of a new method of the automatic EEG analysis in neonates. A quantitative description of the neonatal EEG can contribute to the objective assessment of the functional state of the brain, and may improve the precision of diagnosing cerebral dysfunctions manifested by 'disorganization', 'dysrhythmia' or 'dysmaturity'. 21 healthy, full-term newborns were examined polygraphically during sleep (EEG-8 referential derivations, respiration, ECG, EOG, EMG). From each EEG record, two 5-min samples (one from the middle of quiet sleep, the other from the middle of active sleep) were subject to subsequent automatic analysis and were described by 13 variables: spectral features and features describing shape and variability of the signal. The data from individual infants were averaged and the number of variables was reduced by factor analysis. All factors identified by factor analysis were statistically significantly influenced by the location of derivation. A large number of statistically significant differences were also established when comparing the effects of individual derivations on each of the 13 measured variables. Both spectral features and features describing shape and variability of the signal are largely accountable for the topographic differentiation of the neonatal EEG. The presented method of the automatic EEG analysis is capable to assess the topographic characteristics of the neonatal EEG, and it is adequately sensitive and describes the neonatal electroencephalogram with sufficient precision. The discriminatory capability of the used method represents a promise for their application in the clinical practice.
Kucerka, N; Nieh, M P; Marquardt, D; Harroun, T A; Wassail, S R; Katsaras, J
Cholesterol is an essential component of mammalian cells, and is required for building and maintaining cell membranes, regulating their fluidity, and possibly acting as an antioxidant. Cholesterol has also been implicated in cell signaling processes, where it has been suggested that it triggers the formation of lipid rafts in the plasma membrane. Aside from cholesterol's physiological roles, what is also becoming clear is its poor affinity for lipids with unsaturated fatty acids as opposed to saturated lipids, such as sphingomyelin with which it forms rafts. We previously reported the location of cholesterol in membranes with varying degrees of acyl chain unsaturation as determined by neutron diffraction studies (Harroun et al 2006 Biochemistry 45, 1227; Harroun et al 2008 Biochemistry 47, 7090). In bilayers composed of phosphatidylcholine (PC) molecules with a saturated acyl chain at the sn-1 position or a monounsaturated acyl chain at both sn-1 and sn-2 positions, cholesterol was found in its much-accepted 'upright' position. However, in dipolyunsaturated 1,2-diarachidonyl phosphatidylcholine (20:4-20:4PC) membranes the molecule was found sequestered in the center of the bilayers. In further experiments, mixing l-palmitoyl-2-oleoyl phosphatidylcholine (16:0-18:1 PC) with 20:4-20:4PC resulted in cholesterol reverting to its upright orientation at approximately 40 mol% 16:0-18:1 PC. Interestingly, the same effect was achieved with only 5 mol% 1,2-dimyristoyl phosphatidylchoile (14:0-14:0PC).
Kucerka, N; Nieh, M P; Marquardt, D; Harroun, T A; Wassail, S R; Katsaras, J, E-mail: John.Katsaras@nrc.gc.ca, E-mail: Norbert.Kucerka@nrc.gc.ca
Cholesterol is an essential component of mammalian cells, and is required for building and maintaining cell membranes, regulating their fluidity, and possibly acting as an antioxidant. Cholesterol has also been implicated in cell signaling processes, where it has been suggested that it triggers the formation of lipid rafts in the plasma membrane. Aside from cholesterol's physiological roles, what is also becoming clear is its poor affinity for lipids with unsaturated fatty acids as opposed to saturated lipids, such as sphingomyelin with which it forms rafts. We previously reported the location of cholesterol in membranes with varying degrees of acyl chain unsaturation as determined by neutron diffraction studies (Harroun et al 2006 Biochemistry 45, 1227; Harroun et al 2008 Biochemistry 47, 7090). In bilayers composed of phosphatidylcholine (PC) molecules with a saturated acyl chain at the sn-1 position or a monounsaturated acyl chain at both sn-1 and sn-2 positions, cholesterol was found in its much-accepted 'upright' position. However, in dipolyunsaturated 1,2-diarachidonyl phosphatidylcholine (20:4-20:4PC) membranes the molecule was found sequestered in the center of the bilayers. In further experiments, mixing l-palmitoyl-2-oleoyl phosphatidylcholine (16:0-18:1 PC) with 20:4-20:4PC resulted in cholesterol reverting to its upright orientation at approximately 40 mol% 16:0-18:1 PC. Interestingly, the same effect was achieved with only 5 mol% 1,2-dimyristoyl phosphatidylchoile (14:0-14:0PC).
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
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.
Full Text Available Electroencephalogram (EEG registration as a direct measure of brain activity has unique potentials. It is one of the most reliable and predicative indicators when studying human cognition, evaluating a subject's health condition, or monitoring their mental state. Unfortunately, standard signal acquisition procedures limit the usability of EEG devices and narrow their application outside the lab. Emerging sensor technology allows gel-free EEG registration and wireless signal transmission. Thus, it enables quick and easy application of EEG devices by users themselves. Although a main requirement for the interpretation of an EEG is good signal quality, there is a lack of research on this topic in relation to new devices. In our work, we compared the signal quality of six very different EEG devices. On six consecutive days, 24 subjects wore each device for 60 min and completed tasks and games on the computer. The registered signals were evaluated in the time and frequency domains. In the time domain, we examined the percentage of artifact-contaminated EEG segments and the signal-to-noise ratios. In the frequency domain, we focused on the band power variation in relation to task demands. The results indicated that the signal quality of a mobile, gel-based EEG system could not be surpassed by that of a gel-free system. However, some of the mobile dry-electrode devices offered signals that were almost comparable and were very promising. This study provided a differentiated view of the signal quality of emerging mobile and gel-free EEG recording technology and allowed an assessment of the functionality of the new devices. Hence, it provided a crucial prerequisite for their general application, while simultaneously supporting their further development.
Rotvel, Camilla; Møller, Stine; Nielsen, Rene R
The objective of the current study is to develop a methodology for food ingredient screening based on Electro-Encephalo-Graphy (EEG). EEG measures electrical activity in the central nervous system, allowing assessment of activity in the ascending gustatory pathway from the taste buds on the tongue...... stimulus. The EEG was recorded using a 64 electrode setup, and gustatory evoked potentials (GEP) were estimated by coherent averaging across all 60 stimulations for each concentration. Cortical source localization based on the GEP was performed using a low resolution electromagnetic tomography (LORETA...
Full Text Available The EEG is composed of electrical potentials arising from several sources. Each source (including separate neural clusters, blink artifact or pulse artifact forms a unique topography onto the scalp – ‘scalp map‘. Scalp map may be 2-D or 3-D.These maps are mixed according to the principle of linear superposition. Independent component analysis (ICA attempts to reverse the superposition by separating the EEG into mutually independent scalp maps, or components. MATLAB toolbox and graphic user interface, EEGLAB is used for processing EEG data of any number of channels. Wavelet toolbox has been used for 2-D signal analysis.
Dobson, M.; Wadhwa, S.S.; Mansberg, R.; Fernandes, V.B.
A 59-year-old female with carcinoma of the colon and known liver metastatic disease was referred for bone scan to evaluate for bone metastases. Although no bone metastases were found, there was abnormal uptake noted in the liver corresponding to a metastatic calcified lesion. The only other findings were of degenerative disease in the cervical spine, right shoulder and small joints of the hands. A 69-year-old male with carcinoma of the prostate and right side low back pain was referred for bone scan. No focal abnormalities to suggest metastatic disease were identified; findings within the cervical spine, lumber spine and knees were presumed secondary to degenerative disease. Intermittent pain persisted and the patient was referred for a repeat bone scan six months later. Previous scan findings of degenerative disease and no metastatic disease were confirmed; however, closer inspection revealed an enlarged right kidney with significant retention of tracer in the pelvicalyceal system suggesting possible obstruction. A Retrograde pyelogram was performed, and no obvious obstruction demonstrated. As bone scan findings were very suggestive of obstruction, a DTPA scan with lasix was performed showing a dilated right collecting system with no functional obstruction. Given the degree of dilation, it is possible that the patient experiences intermittent PUJ obstruction causing his symptoms. A 33-year-old male with insulin dependent diabetes mellitus and viral arthritis was referred for a bone scan. A three phase revealed increased uptake in the region of the knee and leR proximal tibia. Delayed whole body images revealed multiple focal areas of osteoblastic activity in the leR tibia. Abnormal uptake was also seen in the upper third of the leR femur. The remainder of the skeletal survey was normal. X-ray correlation of the leR tibia and femoral findings was undertaken. Combinating unilateral changes on bone scan and X-ray although very suggestive of sclerotic polyostotic
Damaševičius, Robertas; Maskeliūnas, Rytis; Kazanavičius, Egidijus; Woźniak, Marcin
Cryptographic frameworks depend on key sharing for ensuring security of data. While the keys in cryptographic frameworks must be correctly reproducible and not unequivocally connected to the identity of a user, in biometric frameworks this is different. Joining cryptography techniques with biometrics can solve these issues. We present a biometric authentication method based on the discrete logarithm problem and Bose-Chaudhuri-Hocquenghem (BCH) codes, perform its security analysis, and demonstrate its security characteristics. We evaluate a biometric cryptosystem using our own dataset of electroencephalography (EEG) data collected from 42 subjects. The experimental results show that the described biometric user authentication system is effective, achieving an Equal Error Rate (ERR) of 0.024.
Bao, Forrest Sheng; Liu, Xin; Zhang, Christina
Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting ...
Dijk, Derk Jan; Beersma, Domien G.M.
In order to test predictions of the 2-process model of sleep regulation, the effects of slow wave sleep (SWS) deprivation by acoustic stimulation during the first part of the sleep period on EEG power density and sleep duration were investigated in 2 experiments. In the first experiment, 8 subjects
Clinical Genetics Department, Human Genetics & Genome Research Division, ... neuroimaging changes of the brain and EEG abnormalities in correlation to the ... level and by developmental changes2. .... for IQ as a confounding factor.30.
Craig, D A; Nguyen, H T; Burchey, H A
This paper presents a real-time electro-encephalogram (EEG) identification system with the goal of achieving hands free control. With two EEG electrodes placed on the scalp of the user, EEG signals are amplified and digitised directly using a ProComp+ encoder and transferred to the host computer through the RS232 interface. Using a real-time multilayer neural network, the actual classification for the control of a powered wheelchair has a very fast response. It can detect changes in the user's thought pattern in 1 second. Using only two EEG electrodes at positions O(1) and C(4) the system can classify three mental commands (forward, left and right) with an accuracy of more than 79 %
J Gordon Millichap
Full Text Available Th value of amplitude-integrated electroencephalography (aEEG in the newborn is explored by researchers at Washington University, St Louis; Wilhelmina Children’s Hospital, Utrecht, Netherlands; and Uppsala University Hospital, Sweden.
Predictive Values of Electroencephalography (EEG) in Epilepsy Patients with Abnormal Behavioural Symptoms. OR Obiako, SO Adeyemi, TL Sheikh, LF Owolabi, MA Majebi, MO Gomina, F Adebayo, EU Iwuozo ...
Jovanov, E.; Starcevic, D.; Samardzic, A.; Marsh, A.; Obrenovic, Z.
Telemedicine creates virtual medical collaborative environments. We propose here a novel concept of virtual medical devices (VMD) for telemedical applications. VMDs provide different views on biomedical recordings and efficient signal analysis. In this paper we present a telemedical EEG analysis
Sakellariou, Dimitris; Koupparis, Andreas M; Kokkinos, Vasileios; Koutroumanidis, Michalis; Kostopoulos, George K
During Non-Rapid Eye Movement sleep (NREM) the brain is relatively disconnected from the environment, while connectedness between brain areas is also decreased. Evidence indicates, that these dynamic connectivity changes are delivered by microstructural elements of sleep: short periods of environmental stimuli evaluation followed by sleep promoting procedures. The connectivity patterns of the latter, among other aspects of sleep microstructure, are still to be fully elucidated. We suggest here a methodology for the assessment and investigation of the connectivity patterns of EEG microstructural elements, such as sleep spindles. The methodology combines techniques in the preprocessing, estimation, error assessing and visualization of results levels in order to allow the detailed examination of the connectivity aspects (levels and directionality of information flow) over frequency and time with notable resolution, while dealing with the volume conduction and EEG reference assessment. The high temporal and frequency resolution of the methodology will allow the association between the microelements and the dynamically forming networks that characterize them, and consequently possibly reveal aspects of the EEG microstructure. The proposed methodology is initially tested on artificially generated signals for proof of concept and subsequently applied to real EEG recordings via a custom built MATLAB-based tool developed for such studies. Preliminary results from 843 fast sleep spindles recorded in whole night sleep of 5 healthy volunteers indicate a prevailing pattern of interactions between centroparietal and frontal regions. We demonstrate hereby, an opening to our knowledge attempt to estimate the scalp EEG connectivity that characterizes fast sleep spindles via an "EEG-element connectivity" methodology we propose. The application of the latter, via a computational tool we developed suggests it is able to investigate the connectivity patterns related to the occurrence
Full Text Available Herein, we report a case of leiomyoma cutis because of its rarity and unusual presentation. The case presented with a solitary leiomyoma lesion which was painless. However, the adjacent normal appearing area was tender. A biopsy of the lesion as well as of a portion of the adjacent normal appearing area was taken, which confirmed the diagnosis of cutaneous leiomyoma. This may suggest the dormant nature of the disease which has not yet become apparent.
Bamford, Cynthia C; Mays, MaryAnn; Tepper, Stewart J
Prevalence of headache lowers with age, and headaches of elderly adults tend to be different than those of the younger population. Secondary headaches, such as headaches associated with vascular disease, head trauma, and neoplasm, are more common. Also, certain headache types tend to be geriatric disorders, such as primary cough headache, hypnic headache, typical aura without headache, exploding head syndrome, and giant cell arteritis. This review provides an overview of some of the major and unusual geriatric headaches, both primary and secondary.
Altrock, Martin; Vollprecht, Jens
On 08.07.2016, the German Bundestag, the German Renewable Energies Act (EEG) in 2017 passed together with the wind-at-sea law. At the same time, the legislature changed 22 other energy legislation, inter alia, also the EnWG. Here, the law de facto a law amending the EEG 2014 is: The EEG is thus not total re-promulgated. Rather essentially part 3 (''Payment of market premium and feed in rate'') of the EEG 2014 renewed, notably Section 3 supplemented by regulations on the newly introduced procurements. But beyond the framework of support is further developed in various details, like the definition of a plant, the promotion of storage facilities and of course, in the again very ambitious and complicated transitional arrangements. Other notable individual changes concern the introduction of regional evidence of directly marketed electricity from renewable sources, the increase of liability for balancing group deviations in paragraph 60 para. 1 EEG 2017 or readjustments in the special equalization scheme, paragraph 64 para. 2 no. 2 EEG. [de
Kanda, Paulo Afonso Medeiros; Aguiar, Aline de Almeida Xavier; Miranda, Jose Lucivan; Falcao, Alexandre Loverde; Andrade, Claudia Suenia; Reis, Luigi Neves Dos Santos; Almeida, Ellen White R Bacelar; Bello, Yanes Brum; Monfredinho, Arthur; Kanda, Rafael Guimaraes
Microcephaly (MC), previously considered rare, is now a health emergency of international concern because of the devastating Zika virus pandemic outbreak of 2015. The authors describe the electroencephalogram (EEG) findings in sleep EEG of epileptic children who were born with microcephaly in areas of Brazil with active Zika virus transmission between 2014 and 2017. The authors reviewed EEGs from 23 children. Nine were females (39.2%), and the age distribution varied from 4 to 48 months. MC was associated with mother positive serology to toxoplasmosis (toxo), rubella (rub), herpes, and dengue (1 case); toxo (1 case); chikungunya virus (CHIKV) (1 case); syphilis (1 case); and Zika virus (ZIKV) (10 cases). In addition, 1 case was associated with perinatal hypoxia and causes of 9 cases remain unknown. The main background EEG abnormality was diffuse slowing (10 cases), followed by classic (3 cases) and modified (5 cases) hypsarrhythmia. A distinct EEG pattern was seen in ZIKV (5 cases), toxo (2 cases), and undetermined cause (1 case). It was characterized by runs of frontocentrotemporal 4.5-13 Hz activity (7 cases) or diffuse and bilateral runs of 18-24 Hz (1 case). In ZIKV, this rhythmic activity was associated with hypsarrhythmia or slow background. Further studies are necessary to determine if this association is suggestive of ZIKV infection. The authors believe that EEG should be included in the investigation of all newly diagnosed congenital MC, especially those occurring in areas of autochthonous transmission of ZIKV.
cause of urethral stricture in this series was traumatic injury The other important cause was post-inflammatory (after gonococcal urethritis) with HIV co-infection. These patients posed a challenge due to our lack of experience and the absence of literature guidelines on the optimal management. The first unusual feature in the ...
Boeijinga, Peter H
High spatial and temporal resolution measurements of neuronal activity are preferably combined. In an overview on how this approach can take shape, multimodal electroencephalography (EEG) is treated in 2 main parts: by experiments without a task and in the experimentally cued working brain. It concentrates first on the alpha rhythm properties and next on data-driven search for patterns such as the default mode network. The high-resolution volumic distributions of neuronal metabolic indices result in distributed cortical regions and possibly relate to numerous nuclei, observable in a non-invasive manner in the central nervous system of humans. The second part deals with paradigms in which nowadays assessment of target-related networks can align level-dependent blood oxygenation, electrical responses and behaviour, taking the temporal resolution advantages of event-related potentials. Evidence-based electrical propagation in serial tasks during performance is now to a large extent attributed to interconnected pathways, particularly chronometry-dependent ones, throughout a chain including a dorsal stream, next ventral cortical areas taking the flow of information towards inferior temporal domains. The influence of aging is documented, and results of the first multimodal studies in neuropharmacology are consistent. Finally a scope on implementation of advanced clinical applications and personalized marker strategies in neuropsychiatry is indicated. © 2016 S. Karger AG, Basel.
Full Text Available The high dependency of the Brain Computer Interface (BCI system performance on the BCI user is a well-known issue of many BCI devices. This contribution presents a new way to overcome this problem using a synergy between a BCI device and an EEG-based biometric algorithm. Using the biometric algorithm, the BCI device automatically identifies its current user and adapts parameters of the classification process and of the BCI protocol to maximize the BCI performance. In addition to this we present an algorithm for EEG-based identification designed to be resistant to variations in EEG recordings between sessions, which is also demonstrated by an experiment with an EEG database containing two sessions recorded one year apart. Further, our algorithm is designed to be compatible with our movement-related BCI device and the evaluation of the algorithm performance took place under conditions of a standard BCI experiment. Estimation of the mu rhythm fundamental frequency using the Frequency Zooming AR modeling is used for EEG feature extraction followed by a classifier based on the regularized Mahalanobis distance. An average subject identification score of 96 % is achieved.
Hansen, Sofie Therese
Electroencephalography (EEG) provides a measure of brain activity and has improved our understanding of the brain immensely. However, there is still much to be learned and the full potential of EEG is yet to be realized. In this thesis we suggest to improve the information gain of EEG using three...... different approaches; 1) by recovery of the EEG sources, 2) by representing and inferring the propagation path of EEG sources, and 3) by combining EEG with functional magnetic resonance imaging (fMRI). The common goal of the methods, and thus of this thesis, is to improve the spatial dimension of EEG...... recovery ability. The forward problem describes the propagation of neuronal activity in the brain to the EEG electrodes on the scalp. The geometry and conductivity of the head layers are normally required to model this path. We propose a framework for inferring forward models which is based on the EEG...
de Vries, Nathalie K. S.; ter Horst, Hendrik J.; Bos, Arend F.
Amplitude-integrated electroencephalograms (aEEGs) recorded by cerebral function monitors (CFMs) are used increasingly to monitor the cerebral activity of newborn infants with encephalopathy. Recently, new CFM devices became available which also reveal the original EEG signals from the same leads.
Frenz, Walter (ed.) [Rheinisch-Westfaelische Technische Hochschule Aachen (Germany). Berg-, Umwelt- und Europarecht
Berlin commentary EEG II: safe through the paraphernalia Like hardly any other law, the Renewable Energies Act (EEG) is subject to constant changes. With the 2014 amendment, the EEG was fundamentally redesigned. This makes the application of the complex rules a challenge even for experts. In addition, the sub-rules contain important statements in the form of numerous annexes and regulations - with the EEG amendment 2014, this has become even more detailed. In it, many calculations are only defined in detail and the legal provisions of the EEG are made more definite and supplemented. The Berlin commentary EEG II accompanies you expertly through this complex matter. Experts explain the widely divergent rules in practice. If necessary for a better understanding, the provisions of the EEG 2014 are also explained. Consistently designed for your practice As a buyer of the work, you also benefit from access to an extensive, regularly updated database. This contains important legal energy regulations of the EU, the federal government and the countries. Even earlier legal positions remain searchable and can be conveniently compared with current versions. So you can see at a glance what has changed. [German] Berliner Kommentar EEG II: sicher durch den Paragrafengeflecht Wie kaum ein anderes Gesetz ist das Erneuerbare-Energien-Gesetz (EEG) staendigen Aenderungen unterworfen. Mit der Novelle 2014 wurde das EEG grundlegend umgestaltet. Dies macht die Anwendung der komplexen Regeln selbst fuer Experten zu einer Herausforderung. Zudem enthaelt auch das untergesetzliche Regelwerk wichtige Aussagen in Form zahlreicher Anlagen und Verordnungen - mit der EEG-Novelle 2014 ist dieses noch ausfuehrlicher geworden. In ihm werden viele Berechnungen erst naeher festgelegt und gesetzliche Bestimmungen des EEG entscheidend konkretisiert und ergaenzt. Der Berliner Kommentar EEG II begleitet Sie fachkundig durch diese komplexe Materie. Experten erlaeutern Ihnen praxisorientiert die
Full Text Available It has frequently been reported that some users of conventional neurofeedback systems can experience only a small portion of the total feedback range due to the large interindividual variability of EEG features. In this study, we proposed a data-driven neurofeedback strategy considering the individual variability of electroencephalography (EEG features to permit users of the neurofeedback system to experience a wider range of auditory or visual feedback without a customization process. The main idea of the proposed strategy is to adjust the ranges of each feedback level using the density in the offline EEG database acquired from a group of individuals. Twenty-two healthy subjects participated in offline experiments to construct an EEG database, and five subjects participated in online experiments to validate the performance of the proposed data-driven user feedback strategy. Using the optimized bin sizes, the number of feedback levels that each individual experienced was significantly increased to 139% and 144% of the original results with uniform bin sizes in the offline and online experiments, respectively. Our results demonstrated that the use of our data-driven neurofeedback strategy could effectively increase the overall range of feedback levels that each individual experienced during neurofeedback training.
Han, Chang-Hee; Lim, Jeong-Hwan; Lee, Jun-Hak; Kim, Kangsan; Im, Chang-Hwan
It has frequently been reported that some users of conventional neurofeedback systems can experience only a small portion of the total feedback range due to the large interindividual variability of EEG features. In this study, we proposed a data-driven neurofeedback strategy considering the individual variability of electroencephalography (EEG) features to permit users of the neurofeedback system to experience a wider range of auditory or visual feedback without a customization process. The main idea of the proposed strategy is to adjust the ranges of each feedback level using the density in the offline EEG database acquired from a group of individuals. Twenty-two healthy subjects participated in offline experiments to construct an EEG database, and five subjects participated in online experiments to validate the performance of the proposed data-driven user feedback strategy. Using the optimized bin sizes, the number of feedback levels that each individual experienced was significantly increased to 139% and 144% of the original results with uniform bin sizes in the offline and online experiments, respectively. Our results demonstrated that the use of our data-driven neurofeedback strategy could effectively increase the overall range of feedback levels that each individual experienced during neurofeedback training.
Prima Dewi Purnamasari
Full Text Available The development of automatic emotion detection systems has recently gained significant attention due to the growing possibility of their implementation in several applications, including affective computing and various fields within biomedical engineering. Use of the electroencephalograph (EEG signal is preferred over facial expression, as people cannot control the EEG signal generated by their brain; the EEG ensures a stronger reliability in the psychological signal. However, because of its uniqueness between individuals and its vulnerability to noise, use of EEG signals can be rather complicated. In this paper, we propose a methodology to conduct EEG-based emotion recognition by using a filtered bispectrum as the feature extraction subsystem and an artificial neural network (ANN as the classifier. The bispectrum is theoretically superior to the power spectrum because it can identify phase coupling between the nonlinear process components of the EEG signal. In the feature extraction process, to extract the information contained in the bispectrum matrices, a 3D pyramid filter is used for sampling and quantifying the bispectrum value. Experiment results show that the mean percentage of the bispectrum value from 5 × 5 non-overlapped 3D pyramid filters produces the highest recognition rate. We found that reducing the number of EEG channels down to only eight in the frontal area of the brain does not significantly affect the recognition rate, and the number of data samples used in the training process is then increased to improve the recognition rate of the system. We have also utilized a probabilistic neural network (PNN as another classifier and compared its recognition rate with that of the back-propagation neural network (BPNN, and the results show that the PNN produces a comparable recognition rate and lower computational costs. Our research shows that the extracted bispectrum values of an EEG signal using 3D filtering as a feature extraction
Full Text Available Electroencephalography (EEG is considered the output of a brain and it is a bioelectrical signal with multiscale and nonlinear properties. Motor Imagery EEG (MI-EEG not only has a close correlation with the human imagination and movement intention but also contains a large amount of physiological or disease information. As a result, it has been fully studied in the field of rehabilitation. To correctly interpret and accurately extract the features of MI-EEG signals, many nonlinear dynamic methods based on entropy, such as Approximate Entropy (ApEn, Sample Entropy (SampEn, Fuzzy Entropy (FE, and Permutation Entropy (PE, have been proposed and exploited continuously in recent years. However, these entropy-based methods can only measure the complexity of MI-EEG based on a single scale and therefore fail to account for the multiscale property inherent in MI-EEG. To solve this problem, Multiscale Sample Entropy (MSE, Multiscale Permutation Entropy (MPE, and Multiscale Fuzzy Entropy (MFE are developed by introducing scale factor. However, MFE has not been widely used in analysis of MI-EEG, and the same parameter values are employed when the MFE method is used to calculate the fuzzy entropy values on multiple scales. Actually, each coarse-grained MI-EEG carries the characteristic information of the original signal on different scale factors. It is necessary to optimize MFE parameters to discover more feature information. In this paper, the parameters of MFE are optimized independently for each scale factor, and the improved MFE (IMFE is applied to the feature extraction of MI-EEG. Based on the event-related desynchronization (ERD/event-related synchronization (ERS phenomenon, IMFE features from multi channels are fused organically to construct the feature vector. Experiments are conducted on a public dataset by using Support Vector Machine (SVM as a classifier. The experiment results of 10-fold cross-validation show that the proposed method yields
González-Rivas, Diego; Lirio, Francisco; Sesma, Julio
Nowadays, sublobar anatomic resections are gaining momentum as a valid alternative for early stage lung cancer. Despite being technically demanding, anatomic segmentectomies can be performed by uniportal video-assisted thoracic surgery (VATS) approach to combine the benefits of minimally invasiveness with the maximum lung sparing. This procedure can be even more complex if a combined resection of multiple segments from different lobes has to be done. Here we report five cases of combined and unusual segmentectomies done by the same experienced surgeon in high volume institutions to show uniportal VATS is a feasible approach for these complex resections and to share an excellent educational resource.
Jequier, S.; Nogrady, M.B.; Wesenberg, R.L.
A newborn baby presented with hyaline membrane disease, interstitial pneumonia, jaundice, hepatosplenomegaly, and unusual bone manifestations with lytic and sclerotic bone lesions and virtually absent periosteal reaction. He subsequently developed intracranial calcifications and mental retardation. The pneumonia and hepatosplenomegaly resolved. At the time of the delivery, a sibling was suffering from a severe undetermined viral infection. The clinical evolution of the disease and the radiologic findings led us to believe that this patient has a prenatal viral infection. The laboratory tests and the histologic picture of the bone biopsy supported the diagnosis.
Jequier, S.; Nogrady, M.B.; Wesenberg, R.L.
A newborn baby presented with hyaline membrane disease, interstitial pneumonia, jaundice, hepatosplenomegaly, and unusual bone manifestations with lytic and sclerotic bone lesions and virtually absent periosteal reaction. He subsequently developed intracranial calcifications and mental retardation. The pneumonia and hepatosplenomegaly resolved. At the time of the delivery, a sibling was suffering from a severe undetermined viral infection. The clinical evolution of the disease and the radiologic findings led us to believe that this patient has a prenatal viral infection. The laboratory tests and the histologic picture of the bone biopsy supported the diagnosis. (orig.)
Francisco J Fraga
Full Text Available Changes in electroencephalography (EEG amplitude modulations have recently been linked with early-stage Alzheimer's disease (AD. Existing tools available to perform such analysis (e.g., detrended fluctuation analysis, however, provide limited gains in discriminability power over traditional spectral based EEG analysis. In this paper, we explore the use of an innovative EEG amplitude modulation analysis technique based on spectro-temporal signal processing. More specifically, full-band EEG signals are first decomposed into the five well-known frequency bands and the envelopes are then extracted via a Hilbert transform. Each of the five envelopes are further decomposed into four so-called modulation bands, which were chosen to coincide with the delta, theta, alpha and beta frequency bands. Experiments on a resting-awake EEG dataset collected from 76 participants (27 healthy controls, 27 diagnosed with mild-AD, and 22 with moderate-AD showed significant differences in amplitude modulations between the three groups. Most notably, i delta modulation of the beta frequency band disappeared with an increase in disease severity (from mild to moderate AD, ii delta modulation of the theta band appeared with an increase in severity, and iii delta modulation of the beta frequency band showed to be a reliable discriminant feature between healthy controls and mild-AD patients. Taken together, it is hoped that the developed tool can be used to assist clinicians not only with early detection of Alzheimer's disease, but also to monitor its progression.
Full Text Available Driver drowsiness is a major cause of mortality in traffic accidents worldwide. Electroencephalographic (EEG signal, which reflects the brain activities, is more directly related to drowsiness. Thus, many Brain-Machine-Interface (BMI systems have been proposed to detect driver drowsiness. However, detecting driver drowsiness at its early stage poses a major practical hurdle when using existing BMI systems. This study proposes a context-aware BMI system aimed to detect driver drowsiness at its early stage by enriching the EEG data with the intensity of head-movements. The proposed system is carefully designed for low-power consumption with on-chip feature extraction and low energy Bluetooth connection. Also, the proposed system is implemented using JAVA programming language as a mobile application for on-line analysis. In total, 266 datasets obtained from six subjects who participated in a one-hour monotonous driving simulation experiment were used to evaluate this system. According to a video-based reference, the proposed system obtained an overall detection accuracy of 82.71% for classifying alert and slightly drowsy events by using EEG data alone and 96.24% by using the hybrid data of head-movement and EEG. These results indicate that the combination of EEG data and head-movement contextual information constitutes a robust solution for the early detection of driver drowsiness.
Hu, Xin; Yu, Jianwen; Song, Mengdi; Yu, Chun; Wang, Fei; Sun, Pei; Wang, Daifa; Zhang, Dan
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.
Shaw, Laxmi; Rahman, Daleef; Routray, Aurobinda
The difficulty associated with processing and understanding the high dimensionality of electroencephalogram (EEG) data requires developing efficient and robust compression algorithms. In this paper, different lossless compression techniques of single and multichannel EEG data, including Huffman coding, arithmetic coding, Markov predictor, linear predictor, context-based error modeling, multivariate autoregression (MVAR), and a low complexity bivariate model have been examined and their performances have been compared. Furthermore, a high compression algorithm named general MVAR and a modified context-based error modeling for multichannel EEG have been proposed. The resulting compression algorithm produces a higher relative compression ratio of 70.64% on average compared with the existing methods, and in some cases, it goes up to 83.06%. The proposed methods are designed to compress a large amount of multichannel EEG data efficiently so that the data storage and transmission bandwidth can be effectively used. These methods have been validated using several experimental multichannel EEG recordings of different subjects and publicly available standard databases. The satisfactory parametric measures of these methods, namely percent-root-mean square distortion, peak signal-to-noise ratio, root-mean-square error, and cross correlation, show their superiority over the state-of-the-art compression methods.
Brokaw, Kate; Tishler, Ward; Manceor, Stephanie; Hamilton, Kelly; Gaulden, Andrew; Parr, Elaine; Wamsley, Erin J
Numerous studies demonstrate that post-training sleep benefits human memory. At the same time, emerging data suggest that other resting states may similarly facilitate consolidation. In order to identify the conditions under which non-sleep resting states benefit memory, we conducted an EEG (electroencephalographic) study of verbal memory retention across 15min of eyes-closed rest. Participants (n=26) listened to a short story and then either rested with their eyes closed, or else completed a distractor task for 15min. A delayed recall test was administered immediately following the rest period. We found, first, that quiet rest enhanced memory for the short story. Improved memory was associated with a particular EEG signature of increased slow oscillatory activity (rest can facilitate memory, and that this may occur via an active process of consolidation supported by slow oscillatory EEG activity and characterized by decreased attention to the external environment. Slow oscillatory EEG rhythms are proposed to facilitate memory consolidation during sleep by promoting hippocampal-cortical communication. Our findings suggest that EEG slow oscillations could play a significant role in memory consolidation during other resting states as well. Copyright © 2016 Elsevier Inc. All rights reserved.
Beres, Anna M
The discovery of electroencephalography (EEG) over a century ago has changed the way we understand brain structure and function, in terms of both clinical and research applications. This paper starts with a short description of EEG and then focuses on the event-related brain potentials (ERPs), and their use in experimental settings. It describes the typical set-up of an ERP experiment. A description of a number of ERP components typically involved in language research is presented. Finally, the advantages and disadvantages of using ERPs in language research are discussed. EEG has an extensive use in today's world, including medical, psychology, or linguistic research. The excellent temporal resolution of EEG information allows one to track a brain response in milliseconds and therefore makes it uniquely suited to research concerning language processing.
Symms, M.R.; Allen, P.J.; Fish, D.R.; Barker, G.J.
We report preliminary experiences using fMRI triggered by EEG to localize the site of interictal epileptiform activity. EEG was recorded in the scanner and monitored on-line; the recording quality was good enough to allow the clear identification of spikes in the EEG. Snap-shot EPI was performed 2-4 s after an epileptiform discharge ('spike') or after at least 10 s of background activity ('rest') was observed. A pixel-by-pixel t-test was performed between the 'rest' and the 'spike' images to determine areas of significant activation. Significant activation was obtained in a patient with epilepsy. To assess the reliability and reproducibility of the technique, the patient was scanned on four separate occasions with similar areas being activated in all the studies, confirming the validity of the result. (author)
Galina V. Portnova
Full Text Available Concurrent EEG and fMRI acquisitions in resting state showed a correlation between EEG power in various bands and spontaneous BOLD fluctuations. However, there is a lack of data on how changes in the complexity of brain dynamics derived from EEG reflect variations in the BOLD signal. The purpose of our study was to correlate both spectral patterns, as linear features of EEG rhythms, and nonlinear EEG dynamic complexity with neuronal activity obtained by fMRI. We examined the relationships between EEG patterns and brain activation obtained by simultaneous EEG-fMRI during the resting state condition in 25 healthy right-handed adult volunteers. Using EEG-derived regressors, we demonstrated a substantial correlation of BOLD signal changes with linear and nonlinear features of EEG. We found the most significant positive correlation of fMRI signal with delta spectral power. Beta and alpha spectral features had no reliable effect on BOLD fluctuation. However, dynamic changes of alpha peak frequency exhibited a significant association with BOLD signal increase in right-hemisphere areas. Additionally, EEG dynamic complexity as measured by the HFD of the 2–20 Hz EEG frequency range significantly correlated with the activation of cortical and subcortical limbic system areas. Our results indicate that both spectral features of EEG frequency bands and nonlinear dynamic properties of spontaneous EEG are strongly associated with fluctuations of the BOLD signal during the resting state condition.
Full Text Available http://dx.doi.org/10.5007/2175-8026.2012n63p69 Experimental studies point that different factors can influence reading comprehension, such as the topic, text type, reading task, and others. The advances in technologies for the past decades have provided researchers with several possibilities to investigate what goes on in one’s brain since their eyes meet the page until comprehension is achieved. Since the mid-80’s, numerous studies have been conducted with the use of the electroencephalogram (EEG to investigate the process of reading, through the analysis of different components – n400, n100 or n1, P2, among others. These components reveal, for example, how the brain integrates the meaning of a specific word in the semantic context of a given sentence. based on previous studies, which demonstrate that different types of words affect cognitive load, this paper aims at investigating how the brain processes function and content words inserted in expository and narrative texts with suitable / unsuitable conclusions. results showed that the type of text and word influence the cognitive load in different scalp areas (midline, right and left hemispheres. The n1s were more pronounced to the content words inserted in narrative texts and to the function words inserted in the expository type of texts, corroborating former studies.
Bellisle, Rachel; Steele, Preston; Bartels, Rachel; Lei Ding; Sunderam, Sridhar; Besio, Walter
Microsaccades are tiny, involuntary eye movements that occur during fixation, and they are necessary to human sight to maintain a sharp image and correct the effects of other fixational movements. Researchers have theorized and studied the effects of microsaccades on electroencephalography (EEG) signals to understand and eliminate the unwanted artifacts from EEG. The tripolar concentric ring electrode (TCRE) sensors are used to acquire TCRE EEG (tEEG). The tEEG detects extremely focal signals from directly below the TCRE sensor. We have noticed a slow wave frequency found in some tEEG recordings. Therefore, we conducted the current work to determine if there was a correlation between the slow wave in the tEEG and the microsaccades. This was done by analyzing the coherence of the frequency spectrums of both tEEG and eye movement in recordings where microsaccades are present. Our preliminary findings show that there is a correlation between the two.
Waterman, D.; Woestenburg, J.C.; Elton, M.; Hofman, W.; Kok, A.
The present report concerns the first study in which electrooculographic (EOG) contamination of electroencephalographic (EEG) recordings in rapid eye movement (REM) sleep is systematically investigated. Contamination of REM sleep EEG recordings in six subjects was evaluated in the frequency domain.
Kjaer, T. W.; Remvig, L. S.; Henriksen, J.
Objective: We implemented and tested an existing seizure detection algorithm for scalp EEG (sEEG) with the purpose of improving it to intracranial EEG (iEEG) recordings. Method: iEEG was obtained from 16 patients with focal epilepsy undergoing work up for resective epilepsy surgery. Each patient...... had 4 or 5 recorded seizures and 24 hours of non-ictal data were used for evaluation. Data from three electrodes placed at the ictal focus were used for the analysis. A wavelet based feature extraction algorithm delivered input to a support vector machine (SVM) classifier for distinction between ictal...... and non-ictal iEEG. We compare our results to a method published by Shoeb in 2004. While the original method on sEEG was optimal with the use of only four subbands in the wavelet analysis, we found that better seizure detection could be made if all subbands were used for iEEG. Results: When using...
Full Text Available Three unusual clinical forms of sporotrichosis described in this paper will be a primer for the clinicians for an early diagnosis and treatment, especially in its unusual presentations. Case 1, a 52-year-old man, developed sporotrichosis over pre-existing facial nodulo-ulcerative basal cell carcinoma of seven-year duration, due to its contamination perhaps from topical herbal pastes and lymphocutaneous sporotrichosis over right hand/forearm from facial lesion/herbal paste. Case 2, a 25-year-old woman, presented with disseminated systemic-cutaneous, osteoarticular and possibly pleural (effusion sporotrichosis. There was no laboratory evidence of tuberculosis and treatment with anti-tuberculosis drugs (ATT did not benefit. Both these cases were diagnosed by histopathology/culture of S. schenckii from tissue specimens. Case 3, a 20-year-old girl, had multiple intensely pruritic, nodular lesions over/around left knee of two-year duration. She was diagnosed clinically as a case of prurigo nodularis and histologically as cutaneous tuberculosis, albeit, other laboratory investigations and treatment with ATT did not support the diagnosis. All the three patients responded well to saturated solution of potassium iodide (SSKI therapy. A high clinical suspicion is important in early diagnosis and treatment to prevent chronicity and morbidity in these patients. SSKI is fairly safe and effective when itraconazole is not affordable/ available.
Wieselmann, G; Grabmair, W; Logar, C; Permann, R; Moser, F
EEG recordings were carried out on 36 patients with the verified diagnosis of bruxism and unilateral headache. Occlusal splints were applied in the long-term management of these patients. Initial EEG recordings showed pathological changes in 56% of the patients. The EEG recordings were repeated two and six weeks later in these patients and following improvement in the clinical symptomatology pathological EEG patterns were detected in only 22% of all cases. This decrease is of statistical significance.
Gatzke-Kopp, L M; Raine, A; Buchsbaum, M; LaCasse, L
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.
Verrusio, Walter; Ettorre, Evaristo; Vicenzini, Edoardo; Vanacore, Nicola; Cacciafesta, Mauro; Mecarelli, Oriano
The aim of this study is to investigate the influence of Mozart's music on brain activity through spectral analysis of the EEG in young healthy adults (Adults), in healthy elderly (Elderly) and in elderly with Mild Cognitive Impairment (MCI). EEG recording was performed at basal rest conditions and after listening to Mozart's K448 or "Fur Elise" Beethoven's sonatas. After listening to Mozart, an increase of alpha band and median frequency index of background alpha rhythm activity (a pattern of brain wave activity linked to memory, cognition and open mind to problem solving) was observed both in Adults and in Elderly. No changes were observed in MCI. After listening to Beethoven, no changes in EEG activity were detected. This results may be representative of the fact that said Mozart's music is able to "activate" neuronal cortical circuits related to attentive and cognitive functions. Copyright © 2015 Elsevier Inc. All rights reserved.
Fingelkurts, Andrew A; Fingelkurts, Alexander A; Kallio-Tamminen, Tarja
The therapeutic potential of meditation for physical and mental well-being is well documented, however the possibility of adverse effects warrants further discussion of the suitability of any particular meditation practice for every given participant. This concern highlights the need for a personalized approach in the meditation practice adjusted for a concrete individual. This can be done by using an objective screening procedure that detects the weak and strong cognitive skills in brain function, thus helping design a tailored meditation training protocol. Quantitative electroencephalogram (qEEG) is a suitable tool that allows identification of individual neurophysiological types. Using qEEG screening can aid developing a meditation training program that maximizes results and minimizes risk of potential negative effects. This brief theoretical-conceptual review provides a discussion of the problem and presents some illustrative results on the usage of qEEG screening for the guidance of mediation personalization. Copyright © 2015 Elsevier Ltd. All rights reserved.
Full Text Available Electroencephalography (EEG source localization approaches are often used to disentangle the spatial patterns mixed up in scalp EEG recordings. However, approaches differ substantially between experiments, may be strongly parameter-dependent, and results are not necessarily meaningful. In this paper we provide a pipeline for EEG source estimation, from raw EEG data pre-processing using EEGLAB functions up to source-level analysis as implemented in Brainstorm. The pipeline is tested using a data set of 10 individuals performing an auditory attention task. The analysis approach estimates sources of 64-channel EEG data without the prerequisite of individual anatomies or individually digitized sensor positions. First, we show advanced EEG pre-processing using EEGLAB, which includes artifact attenuation using independent component analysis (ICA. ICA is a linear decomposition technique that aims to reveal the underlying statistical sources of mixed signals and is further a powerful tool to attenuate stereotypical artifacts (e.g., eye movements or heartbeat. Data submitted to ICA are pre-processed to facilitate good-quality decompositions. Aiming toward an objective approach on component identification, the semi-automatic CORRMAP algorithm is applied for the identification of components representing prominent and stereotypic artifacts. Second, we present a step-wise approach to estimate active sources of auditory cortex event-related processing, on a single subject level. The presented approach assumes that no individual anatomy is available and therefore the default anatomy ICBM152, as implemented in Brainstorm, is used for all individuals. Individual noise modeling in this dataset is based on the pre-stimulus baseline period. For EEG source modeling we use the OpenMEEG algorithm as the underlying forward model based on the symmetric Boundary Element Method (BEM. We then apply the method of dynamical statistical parametric mapping (dSPM to obtain
Full Text Available Bispectral analysis is a signal processing technique that makes it possible to capture the non-linear and non-Gaussian properties of the EEG signals. It has found various applications in EEG research and clinical practice, including the assessment of anesthetic depth, the identification of epileptic seizures, and more recently, the evaluation of non-linear cross-frequency brain functional connectivity. However, the validity and reliability of the indices drawn from bispectral analysis of EEG signals are potentially biased by the use of a non-neutral EEG reference. The present study aims at investigating the effects of the reference choice on the analysis of the non-linear features of EEG signals through bicoherence, as well as on the estimation of cross-frequency EEG connectivity through two different non-linear measures, i.e., the cross-bicoherence and the antisymmetric cross-bicoherence. To this end, four commonly used reference schemes were considered: the vertex electrode (Cz, the digitally linked mastoids, the average reference, and the Reference Electrode Standardization Technique (REST. The reference effects were assessed both in simulations and in a real EEG experiment. The simulations allowed to investigated: (i the effects of the electrode density on the performance of the above references in the estimation of bispectral measures; and (ii the effects of the head model accuracy in the performance of the REST. For real data, the EEG signals recorded from 10 subjects during eyes open resting state were examined, and the distortions induced by the reference choice in the patterns of alpha-beta bicoherence, cross-bicoherence, and antisymmetric cross-bicoherence were assessed. The results showed significant differences in the findings depending on the chosen reference, with the REST providing superior performance than all the other references in approximating the ideal neutral reference. In conclusion, this study highlights the importance of
Full Text Available The process by which the brain transitions into an epileptic seizure is unknown. In this study, we investigated whether the transition to seizure is associated with changes in brain dynamics detectable in the wideband EEG, and whether differences exist across underlying pathologies. Depth electrode ictal EEG recordings from 40 consecutive patients with pharmacoresistant lesional focal epilepsy were low-pass filtered at 500 Hz and sampled at 2,000 Hz. Predefined EEG sections were selected immediately before (immediate preictal, and 30 seconds before the earliest EEG sign suggestive of seizure activity (baseline. Spectral analysis, visual inspection and discrete wavelet transform were used to detect standard (delta, theta, alpha, beta and gamma and high-frequency bands (ripples and fast ripples. At the group level, each EEG frequency band activity increased significantly from baseline to the immediate preictal section, mostly in a progressive manner and independently of any modification in the state of vigilance. Preictal increases in each frequency band activity were widespread, being observed in the seizure-onset zone and lesional tissue, as well as in remote regions. These changes occurred in all the investigated pathologies (mesial temporal atrophy/sclerosis, local/regional cortical atrophy, and malformations of cortical development, but were more pronounced in mesial temporal atrophy/sclerosis. Our findings indicate that a brain state change with distinctive features, in the form of unidirectional changes across the entire EEG bandwidth, occurs immediately prior to seizure onset. We postulate that these changes might reflect a facilitating state of the brain which enables a susceptible region to generate seizures.
Frenz, Walter [Rheinisch-Westfaelische Technische Hochschule (RWTH), Aachen (Germany). Lehr- und Forschungsgebiet Berg-, Umwelt- und Europarecht; Mueggenborg, Hans-Juergen (eds.) [Kassel Univ. (Germany)
Like hardly any other law, the Renewable Energy Sources Law (EEG) is a subject to continuing modifications. This makes the application of the already complicated regulations even for experts to a special challenge. With the proven Berliner comment EEG, now a reliable companion through the bureaucratic jungle is available. All regulations of the EEG are commented precisely and easily to understand by profound experts. An extensive selection of terminology enables a rapid orientation within this book. In addition to the excursions to renewable energy technologies, this book also describes the structural aspects in the establishment of a photovoltaic system.
van Putten, Michel Johannes Antonius Maria
This article presents a method to transform routine clinical EEG recordings to an alternative visual domain. The method is intended to support the classic visual interpretation of the EEG background pattern and to facilitate communication about relevant EEG characteristics. In addition, it provides
A comparison of EEG spectral entropy with conventional quantitative EEG at varying depths of sevoflurane anaesthesia. PR Bartel, FJ Smith, PJ Becker. Abstract. Background and Aim: Recently an electroencephalographic (EEG) spectral entropy module (M-ENTROPY) for an anaesthetic monitor has become commercially ...
Full Text Available Objective. EEG has great potential as a cost-effective screening tool for Alzheimer's disease (AD. However, the specificity of EEG is not yet sufficient to be used in clinical practice. In an earlier study, we presented preliminary results suggesting improved specificity of EEG to early stages of Alzheimer's disease. The key to this improvement is a new method for extracting sparse oscillatory events from EEG signals in the time-frequency domain. Here we provide a more detailed analysis, demonstrating improved EEG specificity for clinical screening of MCI (mild cognitive impairment patients. Methods. EEG data was recorded of MCI patients and age-matched control subjects, in rest condition with eyes closed. EEG frequency bands of interest were θ (3.5–7.5 Hz, α1 (7.5–9.5 Hz, α2 (9.5–12.5 Hz, and β (12.5–25 Hz. The EEG signals were transformed in the time-frequency domain using complex Morlet wavelets; the resulting time-frequency maps are represented by sparse bump models. Results. Enhanced EEG power in the θ range is more easily detected through sparse bump modeling; this phenomenon explains the improved EEG specificity obtained in our previous studies. Conclusions. Sparse bump modeling yields informative features in EEG signal. These features increase the specificity of EEG for diagnosing AD.
McHugh, J C
Non-convulsive seizures and status epilepticus are common in brain-injured patients in intensive care units. Continuous electroencephalography (cEEG) monitoring is the most sensitive means of their detection. In centres where cEEG is unavailable, routine EEG is often utilized for diagnosis although its sensitivity is lower.
Martel, Adrien; Dähne, Sven; Blankertz, Benjamin
Objective. The present study addressed the question whether neurophysiological signals exhibit characteristic modulations preceding a miss in a covert vigilant attention task which mimics a natural environment in which critical stimuli may appear in the periphery of the visual field. Approach. Subjective, behavioural and encephalographic (EEG) data of 12 participants performing a modified Mackworth Clock task were obtained and analysed offline. The stimulus consisted of a pointer performing regular ticks in a clockwise sequence across 42 dots arranged in a circle. Participants were requested to covertly attend to the pointer and press a response button as quickly as possible in the event of a jump, a rare and random event. Main results. Significant increases in response latencies and decreases in the detection rates were found as a function of time-on-task, a characteristic effect of sustained attention tasks known as the vigilance decrement. Subjective sleepiness showed a significant increase over the duration of the experiment. Increased activity in the α-frequency range (8-14 Hz) was observed emerging and gradually accumulating 10 s before a missed target. Additionally, a significant gradual attenuation of the P3 event-related component was found to antecede misses by 5 s. Significance. The results corroborate recent findings that behavioural errors are presaged by specific neurophysiological activity and demonstrate that lapses of attention can be predicted in a covert setting up to 10 s in advance reinforcing the prospective use of brain-computer interface (BCI) technology for the detection of waning vigilance in real-world scenarios. Combining these findings with real-time single-trial analysis from BCI may pave the way for cognitive states monitoring systems able to determine the current, and predict the near-future development of the brain's attentional processes.
Jul 17, 2013 ... Case Study: An unusual coexistence of Addison's disease and phaeochromocytoma. 164 ... strongly positive. ... Department of Endocrinology and Metabolism, Ondokuz Mayis University Medical School, Samsun, Turkey.
Aspinall, Peter; Mavros, Panagiotis; Coyne, Richard; Roe, Jenny
Researchers in environmental psychology, health studies and urban design are interested in the relationship between the environment, behaviour settings and emotions. In particular, happiness, or the presence of positive emotional mindsets, broadens an individual's thought-action repertoire with positive benefits to physical and intellectual activities, and to social and psychological resources. This occurs through play, exploration or similar activities. In addition, a body of restorative literature focuses on the potential benefits to emotional recovery from stress offered by green space and 'soft fascination'. However, access to the cortical correlates of emotional states of a person actively engaged within an environment has not been possible until recently. This study investigates the use of mobile electroencephalography (EEG) as a method to record and analyse the emotional experience of a group of walkers in three types of urban environment including a green space setting. Using Emotiv EPOC, a low-cost mobile EEG recorder, participants took part in a 25 min walk through three different areas of Edinburgh. The areas (of approximately equal length) were labelled zone 1 (urban shopping street), zone 2 (path through green space) and zone 3 (street in a busy commercial district). The equipment provided continuous recordings from five channels, labelled excitement (short-term), frustration, engagement, long-term excitement (or arousal) and meditation. A new form of high-dimensional correlated component logistic regression analysis showed evidence of lower frustration, engagement and arousal, and higher meditation when moving into the green space zone; and higher engagement when moving out of it. Systematic differences in EEG recordings were found between three urban areas in line with restoration theory. This has implications for promoting urban green space as a mood-enhancing environment for walking or for other forms of physical or reflective activity. Published
Full Text Available Leptospirosis has protean clinical manifestations. The classical presentation of the disease is an acute biphasic febrile illness with or without jaundice. Unusual clinical manifestations may result from involvement of pulmonary, cardiovascular, neural, gastrointestinal, ocular and other systems. Immunological phenomena secondary to antigenic mimicry may also be an important component of many clinical features and may be responsible for reactive arthritis. Leptospirosis in early pregnancy may lead to fetal loss. There are a few reports of leptospirosis in HIV- infected individuals but no generalisation can be made due to paucity of data. It is important to bear in mind that leptospiral illness may be a significant component in cases of dual infections or in simultaneous infections with more than two pathogens.
Vaginal tumours are uncommon and this is a particularly rare case of a vaginal haemangioendothelioma in a 38-year-old woman. Initial presentation consisted of symptoms similar to uterovaginal prolapse with "something coming down". Examination under anaesthesia demonstrated a necrotic anterior vaginal wall tumour. Histology of the lesion revealed a haemangioendothelioma which had some features of haemangiopericytoma. While the natural history of vaginal haemangioendothelioma is uncertain, as a group, they have a propensity for local recurrence. To our knowledge this is the third reported case of a vaginal haemangioendothelioma. Management of this tumour is challenging given the paucity of literature on this tumour. There is a need to add rare tumours to our "knowledge bank" to guide management of these unusual tumours.
Full Text Available We report a case of partial intrasubstance tear of popliteus tendon as an unusual cause of pseudolocking of the knee. A 13-year-old semiprofessional soccer player applied to our clinic with a locked right knee in spite of the therapy applied (cold pack, NSAID, and immobilization in another institution 20 days after the injury. Significant extension loss was observed in his right knee with 30∘–90∘ ROM. Magnetic resonance imaging (MRI and arthroscopy confirmed the intrasubstance tear of popliteus tendon and synovitis. The ruptured part of the tendon was debrided, and the inflammatory tissue around the tendon, which may lead to pseudolocking, was gently removed with a shaver in order to regain the normal ROM. The patient was discharged with full ROM and weight bearing first day after the surgery. To our knowledge, this is the first case demonstrating intrasubstance tear of popliteus tendon causing pseudolocking of the knee.
Wooi Ch'ng, Tong; Umpaichitra, Vatcharapan
Mild degree of clitoromegaly can be associated with patient with polycystic ovarian syndrome (PCOS). We describe an unusually significant clitoromegaly in a patient with PCOS. An 18-year old non-obese female referred for clitoromegaly. Her genitalia exam showed significant clitoral enlargement with a well-formed glans, clitoris measured at 35 mm for length and 10 mm for width. Pelvic ultrasound showed left ovarian cyst. Testosterone level ranged from 28.8 to 64.1 ng/dl (normal: 8.4-48.1 ng/dl) with normal sex hormone binding globulin. Other ovarian hormones were in acceptable ranges. This case demonstrates the coexistence of significant clitoromegaly, PCOS, and non-functioning ovarian cyst. Copyright © 2018. Published by Elsevier Inc.
Imperatori, Claudio; Brunetti, Riccardo; Farina, Benedetto; Speranza, Anna Maria; Losurdo, Anna; Testani, Elisa; Contardi, Anna; Della Marca, Giacomo
The aim of the present study was to explore the modifications of scalp EEG power spectra and EEG connectivity during the autobiographical memory test (AM-T) and during the retrieval of an autobiographical event (the high school final examination, Task 2). Seventeen healthy volunteers were enrolled (9 women and 8 men, mean age 23.4 ± 2.8 years, range 19-30). EEG was recorded at baseline and while performing the autobiographical memory (AM) tasks, by means of 19 surface electrodes and a nasopharyngeal electrode. EEG analysis was conducted by means of the standardized LOw Resolution Electric Tomography (sLORETA) software. Power spectra and lagged EEG coherence were compared between EEG acquired during the memory tasks and baseline recording. The frequency bands considered were as follows: delta (0.5-4 Hz); theta (4.5-7.5 Hz); alpha (8-12.5 Hz); beta1 (13-17.5 Hz); beta2 (18-30 Hz); gamma (30.5-60 Hz). During AM-T, we observed a significant delta power increase in left frontal and midline cortices (T = 3.554; p < 0.05) and increased EEG connectivity in delta band in prefrontal, temporal, parietal, and occipital areas, and for gamma bands in the left temporo-parietal regions (T = 4.154; p < 0.05). In Task 2, we measured an increased power in the gamma band located in the left posterior midline areas (T = 3.960; p < 0.05) and a significant increase in delta band connectivity in the prefrontal, temporal, parietal, and occipital areas, and in the gamma band involving right temporo-parietal areas (T = 4.579; p < 0.05). These results indicate that AM retrieval engages in a complex network which is mediated by both low- (delta) and high-frequency (gamma) EEG bands.
Frenz, Walter [RWTH Aachen Univ. (Germany). Lehr- und Forschungsgebiet Berg-, Umwelt- und Europarecht; Mueggenborg, Hans-Juergen [Technische Hochschule Aachen (Germany); Kassel Univ. (Germany); Cosack, Tilman [Hochschule Trier, Umwelt-Campus Birkenfeld (Germany). IREK - Inst. fuer das Recht der Erneuerbaren Energien, Energieeffizienzrecht und Klimaschutzrecht; Ekardt, Felix (ed.) [Forschungsstelle Nachhaltigkeit und Klimapolitik, Leipzig (Germany)
Unlike any other Act, the Renewable Energy Sources Act (EEG) changes continuously. Recently it has been fundamentally transformed with the amendment 2014. Comprehensive, readable and practice-oriented. The proven Berliner comment EEG is your reliable companion through the new regulatory regime. All provisions of the EEG 2014 thorough and easy to understand commented by experts of the matter. 2. The EEG Amending Act of 29.6.2015 has already been considered. A detailed introduction and contributions to the relevant European law and the antitrust aspects of the renewable energy sources to guarantee you a broad understanding of the rules. Valuable background information you provide, the digressions of the most important renewable energy technologies, will explain the pictures thanks to numerous the scientific and technical foundations. Moreover you the construction law aspects in the construction of photovoltaic and wind turbines are explained clearly. [German] Wie kaum ein anderes Gesetz veraendert sich das Erneuerbare-Energien-Gesetz (EEG) laufend. Zuletzt wurde es mit der Novelle 2014 grundlegend umgestaltet. Umfassend, verstaendlich und praxisgerecht Der bewaehrte Berliner Kommentar EEG ist Ihr verlaesslicher Begleiter durch das neue Regelungsregime. Alle Vorschriften des EEG 2014 werden gruendlich und leicht verstaendlich von Kennern der Materie kommentiert. Das 2. EEG-Aenderungsgesetz vom 29.06.2015 ist bereits beruecksichtigt. Eine ausfuehrliche Einleitung sowie Beitraege zum einschlaegigen europaeischen Recht und zu den kartellrechtlichen Aspekten der erneuerbaren Energien verhelfen Ihnen zu einem breiten Verstaendnis der Vorschriften. Wertvolles Hintergrundwissen liefern Ihnen auch die Exkurse zu den wichtigsten Erneuerbare-Energien-Technologien, die Ihnen dank zahlreicher Abbildungen die naturwissenschaftlich-technischen Grundlagen erlaeutern. Zudem werden Ihnen die baurechtlichen Aspekte bei der Errichtung von Photovoltaik- und Windenergieanlagen
Low, Yin Fen; Strauss, Daniel J
We propose a novel tool to evaluate the electroencephalograph (EEG) phase reset due to auditory attention by utilizing an inverse analysis of the instantaneous phase for the first time. EEGs were acquired through auditory attention experiments with a maximum entropy stimulation paradigm. We examined single sweeps of auditory late response (ALR) with the complex continuous wavelet transform. The phase in the frequency band that is associated with auditory attention (6–10 Hz, termed as theta–alpha border) was reset to the mean phase of the averaged EEGs. The inverse transform was applied to reconstruct the phase-modified signal. We found significant enhancement of the N100 wave in the reconstructed signal. Analysis of the phase noise shows the effects of phase jittering on the generation of the N100 wave implying that a preferred phase is necessary to generate the event-related potential (ERP). Power spectrum analysis shows a remarkable increase of evoked power but little change of total power after stabilizing the phase of EEGs. Furthermore, by resetting the phase only at the theta border of no attention data to the mean phase of attention data yields a result that resembles attention data. These results show strong connections between EEGs and ERP, in particular, we suggest that the presentation of an auditory stimulus triggers the phase reset process at the theta–alpha border which leads to the emergence of the N100 wave. It is concluded that our study reinforces other studies on the importance of the EEG in ERP genesis
Mishra, Vikas; Gautier, Nicole M; Glasscock, Edward
In epilepsy, seizures can evoke cardiac rhythm disturbances such as heart rate changes, conduction blocks, asystoles, and arrhythmias, which can potentially increase risk of sudden unexpected death in epilepsy (SUDEP). Electroencephalography (EEG) and electrocardiography (ECG) are widely used clinical diagnostic tools to monitor for abnormal brain and cardiac rhythms in patients. Here, a technique to simultaneously record video, EEG, and ECG in mice to measure behavior, brain, and cardiac activities, respectively, is described. The technique described herein utilizes a tethered (i.e., wired) recording configuration in which the implanted electrode on the head of the mouse is hard-wired to the recording equipment. Compared to wireless telemetry recording systems, the tethered arrangement possesses several technical advantages such as a greater possible number of channels for recording EEG or other biopotentials; lower electrode costs; and greater frequency bandwidth (i.e., sampling rate) of recordings. The basics of this technique can also be easily modified to accommodate recording other biosignals, such as electromyography (EMG) or plethysmography for assessment of muscle and respiratory activity, respectively. In addition to describing how to perform the EEG-ECG recordings, we also detail methods to quantify the resulting data for seizures, EEG spectral power, cardiac function, and heart rate variability, which we demonstrate in an example experiment using a mouse with epilepsy due to Kcna1 gene deletion. Video-EEG-ECG monitoring in mouse models of epilepsy or other neurological disease provides a powerful tool to identify dysfunction at the level of the brain, heart, or brain-heart interactions.
Sadeh, Boaz; Yovel, Galit
Transcranial Magnetic Stimulation (TMS) is an effective method for establishing a causal link between a cortical area and cognitive/neurophysiological effects. Specifically, by creating a transient interference with the normal activity of a target region and measuring changes in an electrophysiological signal, we can establish a causal link between the stimulated brain area or network and the electrophysiological signal that we record. If target brain areas are functionally defined with prior fMRI scan, TMS could be used to link the fMRI activations with evoked potentials recorded. However, conducting such experiments presents significant technical challenges given the high amplitude artifacts introduced into the EEG signal by the magnetic pulse, and the difficulty to successfully target areas that were functionally defined by fMRI. Here we describe a methodology for combining these three common tools: TMS, EEG, and fMRI. We explain how to guide the stimulator's coil to the desired target area using anatomical or functional MRI data, how to record EEG during concurrent TMS, how to design an ERP study suitable for EEG-TMS combination and how to extract reliable ERP from the recorded data. We will provide representative results from a previously published study, in which fMRI-guided TMS was used concurrently with EEG to show that the face-selective N1 and the body-selective N1 component of the ERP are associated with distinct neural networks in extrastriate cortex. This method allows us to combine the high spatial resolution of fMRI with the high temporal resolution of TMS and EEG and therefore obtain a comprehensive understanding of the neural basis of various cognitive processes. PMID:24893706
Sadeh, Boaz; Yovel, Galit
Transcranial Magnetic Stimulation (TMS) is an effective method for establishing a causal link between a cortical area and cognitive/neurophysiological effects. Specifically, by creating a transient interference with the normal activity of a target region and measuring changes in an electrophysiological signal, we can establish a causal link between the stimulated brain area or network and the electrophysiological signal that we record. If target brain areas are functionally defined with prior fMRI scan, TMS could be used to link the fMRI activations with evoked potentials recorded. However, conducting such experiments presents significant technical challenges given the high amplitude artifacts introduced into the EEG signal by the magnetic pulse, and the difficulty to successfully target areas that were functionally defined by fMRI. Here we describe a methodology for combining these three common tools: TMS, EEG, and fMRI. We explain how to guide the stimulator's coil to the desired target area using anatomical or functional MRI data, how to record EEG during concurrent TMS, how to design an ERP study suitable for EEG-TMS combination and how to extract reliable ERP from the recorded data. We will provide representative results from a previously published study, in which fMRI-guided TMS was used concurrently with EEG to show that the face-selective N1 and the body-selective N1 component of the ERP are associated with distinct neural networks in extrastriate cortex. This method allows us to combine the high spatial resolution of fMRI with the high temporal resolution of TMS and EEG and therefore obtain a comprehensive understanding of the neural basis of various cognitive processes.
Low, Yin Fen; Strauss, Daniel J
We propose a novel tool to evaluate the electroencephalograph (EEG) phase reset due to auditory attention by utilizing an inverse analysis of the instantaneous phase for the first time. EEGs were acquired through auditory attention experiments with a maximum entropy stimulation paradigm. We examined single sweeps of auditory late response (ALR) with the complex continuous wavelet transform. The phase in the frequency band that is associated with auditory attention (6-10 Hz, termed as theta-alpha border) was reset to the mean phase of the averaged EEGs. The inverse transform was applied to reconstruct the phase-modified signal. We found significant enhancement of the N100 wave in the reconstructed signal. Analysis of the phase noise shows the effects of phase jittering on the generation of the N100 wave implying that a preferred phase is necessary to generate the event-related potential (ERP). Power spectrum analysis shows a remarkable increase of evoked power but little change of total power after stabilizing the phase of EEGs. Furthermore, by resetting the phase only at the theta border of no attention data to the mean phase of attention data yields a result that resembles attention data. These results show strong connections between EEGs and ERP, in particular, we suggest that the presentation of an auditory stimulus triggers the phase reset process at the theta-alpha border which leads to the emergence of the N100 wave. It is concluded that our study reinforces other studies on the importance of the EEG in ERP genesis.
Roč. 91, - (2003), s. 198104-1 - 198104-4 ISSN 0031-9007 R&D Projects: GA ČR GA202/02/0088 Institutional research plan: CEZ:AV0Z1010914 Keywords : random matrix theory * EEG signal Subject RIV: BE - Theoretical Physics Impact factor: 7.035, year: 2003
Park, Jin Young; Min, Byoung-Kyong; Jung, Young-Chul; Pak, Hyensou; Jeong, Yeon-Hong; Kim, Eosu
Illumination conditions appear to influence working efficacy in everyday life. In the present study, we obtained electroencephalogram (EEG) correlates of working-memory load, and investigated how these waveforms are modulated by illumination conditions. We hypothesized that illumination conditions may affect cognitive performance. We designed an EEG study to monitor and record participants' EEG during the Sternberg working memory task under four different illumination conditions. Illumination conditions were generated with a factorial design of two color-temperatures (3000 and 7100 K) by two illuminance levels (150 and 700 lx). During a working memory task, we observed that high illuminance led to significantly lower frontal EEG theta activity than did low illuminance. These differences persisted despite no significant difference in task performance between illumination conditions. We found that the latency of an early event-related potential component, such as N1, was significantly modulated by the illumination condition. The fact that the illumination condition affects brain activity but not behavioral performance suggests that the lighting conditions used in the present study did not influence the performance stage of behavioral processing. Nevertheless, our findings provide objective evidence that illumination conditions modulate brain activity. Further studies are necessary to refine the optimal lighting parameters for facilitating working memory. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.
Dyrholm, Mads; Sajda, Paul
the method for predicting the handedness of a subject’s button press given multivariate EEG data. We show that our method learns multitapers sensitive to oscillatory activity in the 8–12 Hz range with spatial filters selective for lateralized motor cortex. This finding is consistent with the well-known mu...
Lazo, M.; Tsoneva, T.; Garcia Molina, G.
Steady-State Visual Evoked Potential (SSVEP) is an oscillatory electrical response appearing in the electroencephalogram (EEG) in response to flicker stimulation. The SSVEP manifests more prominently in electrodes located near the visual cortex and has oscillatory components at the stimulation
Faber, Pascal L; Lehmann, Dietrich; Tei, Shisei; Tsujiuchi, Takuya; Kumano, Hiroaki; Pascual-Marqui, Roberto D; Kochi, Kieko
Experienced Qigong meditators who regularly perform the exercises "Thinking of Nothing" and "Qigong" were studied with multichannel EEG source imaging during their meditations. The intracerebral localization of brain electric activity during the two meditation conditions was compared using sLORETA functional EEG tomography. Differences between conditions were assessed using t statistics (corrected for multiple testing) on the normalized and log-transformed current density values of the sLORETA images. In the EEG alpha-2 frequency, 125 voxels differed significantly; all were more active during "Qigong" than "Thinking of Nothing," forming a single cluster in parietal Brodmann areas 5, 7, 31, and 40, all in the right hemisphere. In the EEG beta-1 frequency, 37 voxels differed significantly; all were more active during "Thinking of Nothing" than "Qigong," forming a single cluster in prefrontal Brodmann areas 6, 8, and 9, all in the left hemisphere. Compared to combined initial-final no-task resting, "Qigong" showed activation in posterior areas whereas "Thinking of Nothing" showed activation in anterior areas. The stronger activity of posterior (right) parietal areas during "Qigong" and anterior (left) prefrontal areas during "Thinking of Nothing" may reflect a predominance of self-reference, attention and input-centered processing in the "Qigong" meditation, and of control-centered processing in the "Thinking of Nothing" meditation.
Krachunov, Sammy; Casson, Alexander J
Electroencephalography (EEG) is a procedure that records brain activity in a non-invasive manner. The cost and size of EEG devices has decreased in recent years, facilitating a growing interest in wearable EEG that can be used out-of-the-lab for a wide range of applications, from epilepsy diagnosis, to stroke rehabilitation, to Brain-Computer Interfaces (BCI). A major obstacle for these emerging applications is the wet electrodes, which are used as part of the EEG setup. These electrodes are attached to the human scalp using a conductive gel, which can be uncomfortable to the subject, causes skin irritation, and some gels have poor long-term stability. A solution to this problem is to use dry electrodes, which do not require conductive gel, but tend to have a higher noise floor. This paper presents a novel methodology for the design and manufacture of such dry electrodes. We manufacture the electrodes using low cost desktop 3D printers and off-the-shelf components for the first time. This allows quick and inexpensive electrode manufacturing and opens the possibility of creating electrodes that are customized for each individual user. Our 3D printed electrodes are compared against standard wet electrodes, and the performance of the proposed electrodes is suitable for BCI applications, despite the presence of additional noise.
Full Text Available Electroencephalography (EEG is a procedure that records brain activity in a non-invasive manner. The cost and size of EEG devices has decreased in recent years, facilitating a growing interest in wearable EEG that can be used out-of-the-lab for a wide range of applications, from epilepsy diagnosis, to stroke rehabilitation, to Brain-Computer Interfaces (BCI. A major obstacle for these emerging applications is the wet electrodes, which are used as part of the EEG setup. These electrodes are attached to the human scalp using a conductive gel, which can be uncomfortable to the subject, causes skin irritation, and some gels have poor long-term stability. A solution to this problem is to use dry electrodes, which do not require conductive gel, but tend to have a higher noise floor. This paper presents a novel methodology for the design and manufacture of such dry electrodes. We manufacture the electrodes using low cost desktop 3D printers and off-the-shelf components for the first time. This allows quick and inexpensive electrode manufacturing and opens the possibility of creating electrodes that are customized for each individual user. Our 3D printed electrodes are compared against standard wet electrodes, and the performance of the proposed electrodes is suitable for BCI applications, despite the presence of additional noise.
for neurodevelopmental problem in conditions such as hypoxic-ischemic encephalopathy (HIE, prematurity, neonatal seizures, central nervous system infection, metabolic disorders, intraventricular or intracranial bleeding and brain malformation. This article gives an overview about aEEG and its role in newborn.
Lüttge, Regina; van Nieuwkasteele-Bystrova, Svetlana Nikolajevna; van Putten, Michel Johannes Antonius Maria; Vander Sloten, Jos; Verdonck, Pascal; Nyssen, Marc; Haueisen, Jens
Microneedle array electrodes for EEG significantly reduce the mounting time, particularly by circumvention of the need for skin preparation by scrubbing. We designed a new replication process for numerous types of microneedle arrays. Here, polymer microneedle array electrodes with 64 microneedles,
Hill, Aron T; Briggs, Belinda A; Seneviratne, Udaya
To investigate the usefulness of adjunctive electromyographic (EMG) polygraphy in the diagnosis of clinical events captured during long-term video-EEG monitoring. A total of 40 patients (21 women, 19 men) aged between 19 and 72 years (mean 43) investigated using video-EEG monitoring were studied. Electromyographic activity was simultaneously recorded with EEG in four patients selected on clinical grounds. In these patients, surface EMG electrodes were placed over muscles suspected to be activated during a typical clinical event. Of the 40 patients investigated, 24 (60%) were given a diagnosis, whereas 16 (40%) remained undiagnosed. All four patients receiving adjunctive EMG polygraphy obtained a diagnosis, with three of these diagnoses being exclusively reliant on the EMG recordings. Specifically, one patient was diagnosed with propriospinal myoclonus, another patient was diagnosed with facio-mandibular myoclonus, and a third patient was found to have bruxism and periodic leg movements of sleep. The information obtained from surface EMG recordings aided the diagnosis of clinical events captured during video-EEG monitoring in 7.5% of the total cohort. This study suggests that EEG-EMG polygraphy may be used as a technique of improving the diagnostic yield of video-EEG monitoring in selected cases.
Ueda, Jun; Kawamoto, Michi; Hikiami, Ryota; Ishii, Junko; Yoshimura, Hajime; Matsumoto, Riki; Kohara, Nobuo
Anti-NMDA receptor encephalitis is a paraneoplastic encephalitis characterised by psychiatric features, involuntary movement, and autonomic instability. Various EEG findings in patients with anti-NMDA receptor encephalitis have been reported, however, the correlation between the EEG findings and clinical course of anti-NMDA receptor encephalitis remains unclear. We describe a patient with anti-NMDA receptor encephalitis with a focus on EEG findings, which included: status epilepticus, generalised rhythmic delta activity, excess beta activity, extreme delta brush, and paroxysmal alpha activity upon arousal from sleep, which we term"arousal alpha pattern". Initially, status epilepticus was observed on the EEG when the patient was comatose with conjugate deviation. The EEG then indicated excess beta activity, followed by the emergence of continuous slow activity, including generalised rhythmic delta activity and extreme delta brush, in the most severe phase. Slow activity gradually faded in parallel with clinical amelioration. Excess beta activity persisted, even after the patient became almost independent in daily activities, and finally disappeared with full recovery. In summary, our patient with anti-NMDA receptor encephalitis demonstrated slow activity on the EEG, including extreme delta brush during the most severe phase, which gradually faded in parallel with clinical amelioration, with excess beta activity persisting into the recovery phase.
Mayes, Susan Dickerson; Calhoun, Susan L.; Aggarwal, Richa; Baker, Courtney; Mathapati, Santosh; Molitoris, Sarah; Mayes, Rebecca D.
Unusual fears have long been recognized as common in autism, but little research exists. In our sample of 1033 children with autism, unusual fears were reported by parents of 421 (41%) of the children, representing 92 different fears. Many additional children had common childhood fears (e.g., dogs, bugs, and the dark). More than half of children…
Westhall, Erik; Rosén, Ingmar; Rossetti, Andrea O
OBJECTIVE: EEG is widely used to predict outcome in comatose cardiac arrest patients, but its value has been limited by lack of a uniform classification. We used the EEG terminology proposed by the American Clinical Neurophysiology Society (ACNS) to assess interrater variability in a cohort...... who were blinded for patient outcome. Percent agreement and kappa (κ) for the categories in the ACNS EEG terminology and for prespecified malignant EEG-patterns were calculated. RESULTS: There was substantial interrater agreement (κ 0.71) for highly malignant patterns and moderate agreement (κ 0.......42) for malignant patterns. Substantial agreement was found for malignant periodic or rhythmic patterns (κ 0.72) while agreement for identifying an unreactive EEG was fair (κ 0.26). CONCLUSIONS: The ACNS EEG terminology can be used to identify highly malignant EEG-patterns in post cardiac arrest patients...
Kraus, Adam L.; Hillenbrand, Lynne A.
We describe an astrometric and spectroscopic campaign to confirm the youth and association of a complete sample of candidate wide companions in Taurus and Upper Sco. Our survey found 15 new binary systems (three in Taurus and 12 in Upper Sco) with separations of 3''-30'' (500-5000 AU) among all of the known members with masses of 2.5-0.012 M sun . The total sample of 49 wide systems in these two regions conforms to only some expectations from field multiplicity surveys. Higher mass stars have a higher frequency of wide binary companions, and there is a marked paucity of wide binary systems near the substellar regime. However, the separation distribution appears to be log-flat, rather than declining as in the field, and the mass ratio distribution is more biased toward similar-mass companions than the initial mass function or the field G-dwarf distribution. The maximum separation also shows no evidence of a limit at ∼ sun . We attribute this result to the post-natal dynamical sculpting that occurs for most field systems; our binary systems will escape to the field intact, but most field stars are formed in denser clusters and undergo significant dynamical evolution. In summary, only wide binary systems with total masses ∼ sun appear to be 'unusually wide'.
science of binaural beats . Retrieved from http://binauralbrains.com/the-science-of- binaural - beats / Biosignal. (2016). MicroEEG. Retrieved from http...Cap. Source: Binaural Brains (n.d.). ....................................4 Figure 3. EEG Machine. Source: Refine Medical Technology (n.d...EEG. Figures 2, 3, and 4 display images of a standard EEG cap, EEG machine, and an EEG recording. Figure 2. Standard EEG Cap. Source: Binaural Brains
Chaohui Lisa Zhao
Full Text Available High-grade papillary urothelial carcinoma regularly invades the bladder wall, adjacent prostate, seminal vesicles, ureters, vagina, rectum, retroperitoneum, and regional lymph nodes. In advanced stages, it may disseminate to the liver, lungs, and bone marrow. On rare occasions, unusual metastatic foci like skin have been reported. The incidence of urothelial carcinoma has increased with associated rise in variants of urothelial carcinoma and unusual metastatic foci. It is imperative that urologists and pathologists are aware of the unusual variants and unusual metastatic locations to expedite the diagnostic process. Hereby we report an unusual case of secondary involvement of spinal nerve by conventional urothelial carcinoma. Also a second case of rhabdoid variant of urothelial carcinoma showing synchronous involvement of bladder and subcutaneous tissue of upper extremity is presented.
Gutiérrez, David; Ramírez-Moreno, Mauricio A
We propose to assess the process of learning a task using electroencephalographic (EEG) measurements. In particular, we quantify changes in brain activity associated to the progression of the learning experience through the functional analysis-of-variances (FANOVA) estimators of the EEG power spectral density (PSD). Such functional estimators provide a sense of the effect of training in the EEG dynamics. For that purpose, we implemented an experiment to monitor the process of learning to type using the Colemak keyboard layout during a twelve-lessons training. Hence, our aim is to identify statistically significant changes in PSD of various EEG rhythms at different stages and difficulty levels of the learning process. Those changes are taken into account only when a probabilistic measure of the cognitive state ensures the high engagement of the volunteer to the training. Based on this, a series of statistical tests are performed in order to determine the personalized frequencies and sensors at which changes in PSD occur, then the FANOVA estimates are computed and analyzed. Our experimental results showed a significant decrease in the power of [Formula: see text] and [Formula: see text] rhythms for ten volunteers during the learning process, and such decrease happens regardless of the difficulty of the lesson. These results are in agreement with previous reports of changes in PSD being associated to feature binding and memory encoding.
Spiegelhalder, Kai; Regen, Wolfram; Feige, Bernd; Holz, Johannes; Piosczyk, Hannah; Baglioni, Chiara; Riemann, Dieter; Nissen, Christoph
The hyperarousal model of primary insomnia suggests that a deficit of attenuating arousal during sleep might cause the experience of non-restorative sleep. In the current study, we examined EEG spectral power values for standard frequency bands as indices of cortical arousal and sleep protecting mechanisms during sleep in 25 patients with primary insomnia and 29 good sleeper controls. Patients with primary insomnia demonstrated significantly elevated spectral power values in the EEG beta and sigma frequency band during NREM stage 2 sleep. No differences were observed in other frequency bands or during REM sleep. Based on prior studies suggesting that EEG beta activity represents a marker of cortical arousal and EEG sleep spindle (sigma) activity is an index of sleep protective mechanisms, our findings may provide further evidence for the concept that a simultaneous activation of wake-promoting and sleep-protecting neural activity patterns contributes to the experience of non-restorative sleep in primary insomnia. Copyright © 2012 Elsevier B.V. All rights reserved.
Guger, C; Schlögl, A; Neuper, C; Walterspacher, D; Strein, T; Pfurtscheller, G
The electroencephalogram (EEG) is modified by motor imagery and can be used by patients with severe motor impairments (e.g., late stage of amyotrophic lateral sclerosis) to communicate with their environment. Such a direct connection between the brain and the computer is known as an EEG-based brain-computer interface (BCI). This paper describes a new type of BCI system that uses rapid prototyping to enable a fast transition of various types of parameter estimation and classification algorithms to real-time implementation and testing. Rapid prototyping is possible by using Matlab, Simulink, and the Real-Time Workshop. It is shown how to automate real-time experiments and perform the interplay between on-line experiments and offline analysis. The system is able to process multiple EEG channels on-line and operates under Windows 95 in real-time on a standard PC without an additional digital signal processor (DSP) board. The BCI can be controlled over the Internet, LAN or modem. This BCI was tested on 3 subjects whose task it was to imagine either left or right hand movement. A classification accuracy between 70% and 95% could be achieved with two EEG channels after some sessions with feedback using an adaptive autoregressive (AAR) model and linear discriminant analysis (LDA).
Zhang, Wenchang; Sun, Fuchun; Tan, Chuanqi; Liu, Shaobo
The common spatial pattern (CSP) and other spatiospectral feature extraction methods have become the most effective and successful approaches to solve the problem of motor imagery electroencephalography (MI-EEG) pattern recognition from multichannel neural activity in recent years. However, these methods need a lot of preprocessing and postprocessing such as filtering, demean, and spatiospectral feature fusion, which influence the classification accuracy easily. In this paper, we utilize linear dynamical systems (LDSs) for EEG signals feature extraction and classification. LDSs model has lots of advantages such as simultaneous spatial and temporal feature matrix generation, free of preprocessing or postprocessing, and low cost. Furthermore, a low-rank matrix decomposition approach is introduced to get rid of noise and resting state component in order to improve the robustness of the system. Then, we propose a low-rank LDSs algorithm to decompose feature subspace of LDSs on finite Grassmannian and obtain a better performance. Extensive experiments are carried out on public dataset from "BCI Competition III Dataset IVa" and "BCI Competition IV Database 2a." The results show that our proposed three methods yield higher accuracies compared with prevailing approaches such as CSP and CSSP.
Full Text Available 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.
Wu, Junjie; Zhang, Junsong; Liu, Chu; Liu, Dongwei; Ding, Xiaojun; Zhou, Changle
The present study evaluated the effect of music on large-scale structure of functional brain networks using graph theoretical concepts. While most studies on music perception used Western music as an acoustic stimulus, Guqin music, representative of Eastern music, was selected for this experiment to increase our knowledge of music perception. Electroencephalography (EEG) was recorded from non-musician volunteers in three conditions: Guqin music, noise and silence backgrounds. Phase coherence was calculated in the alpha band and between all pairs of EEG channels to construct correlation matrices. Each resulting matrix was converted into a weighted graph using a threshold, and two network measures: the clustering coefficient and characteristic path length were calculated. Music perception was found to display a higher level mean phase coherence. Over the whole range of thresholds, the clustering coefficient was larger while listening to music, whereas the path length was smaller. Networks in music background still had a shorter characteristic path length even after the correction for differences in mean synchronization level among background conditions. This topological change indicated a more optimal structure under music perception. Thus, prominent small-world properties are confirmed in functional brain networks. Furthermore, music perception shows an increase of functional connectivity and an enhancement of small-world network organizations. Copyright © 2012 Elsevier B.V. All rights reserved.
Mensen, Armand; Riedner, Brady; Tononi, Giulio
Analysis of individual slow waves in EEG recording during sleep provides both greater sensitivity and specificity compared to spectral power measures. However, parameters for detection and analysis have not been widely explored and validated. We present a new, open-source, Matlab based, toolbox for the automatic detection and analysis of slow waves; with adjustable parameter settings, as well as manual correction and exploration of the results using a multi-faceted visualization tool. We explore a large search space of parameter settings for slow wave detection and measure their effects on a selection of outcome parameters. Every choice of parameter setting had some effect on at least one outcome parameter. In general, the largest effect sizes were found when choosing the EEG reference, type of canonical waveform, and amplitude thresholding. Previously published methods accurately detect large, global waves but are conservative and miss the detection of smaller amplitude, local slow waves. The toolbox has additional benefits in terms of speed, user-interface, and visualization options to compare and contrast slow waves. The exploration of parameter settings in the toolbox highlights the importance of careful selection of detection METHODS: The sensitivity and specificity of the automated detection can be improved by manually adding or deleting entire waves and or specific channels using the toolbox visualization functions. The toolbox standardizes the detection procedure, sets the stage for reliable results and comparisons and is easy to use without previous programming experience. Copyright © 2016 Elsevier B.V. All rights reserved.
Zibrandtsen, I C; Kidmose, P; Christensen, C B; Kjaer, T W
Ear-EEG is recording of electroencephalography from a small device in the ear. This is the first study to compare ictal and interictal abnormalities recorded with ear-EEG and simultaneous scalp-EEG in an epilepsy monitoring unit. We recorded and compared simultaneous ear-EEG and scalp-EEG from 15 patients with suspected temporal lobe epilepsy. EEGs were compared visually by independent neurophysiologists. Correlation and time-frequency analysis was used to quantify the similarity between ear and scalp electrodes. Spike-averages were used to assess similarity of interictal spikes. There were no differences in sensitivity or specificity for seizure detection. Mean correlation coefficient between ear-EEG and nearest scalp electrode was above 0.6 with a statistically significant decreasing trend with increasing distance away from the ear. Ictal morphology and frequency dynamics can be observed from visual inspection and time-frequency analysis. Spike averages derived from ear-EEG electrodes yield a recognizable spike appearance. Our results suggest that ear-EEG can reliably detect electroencephalographic patterns associated with focal temporal lobe seizures. Interictal spike morphology from sufficiently large temporal spike sources can be sampled using ear-EEG. Ear-EEG is likely to become an important tool in clinical epilepsy monitoring and diagnosis. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
Vaudano, Anna Elisabetta; Avanzini, Pietro; Tassi, Laura; Ruggieri, Andrea; Cantalupo, Gaetano; Benuzzi, Francesca; Nichelli, Paolo; Lemieux, Louis; Meletti, Stefano
Accurate localization of the Seizure Onset Zone (SOZ) is crucial in patients with drug-resistance focal epilepsy. EEG with fMRI recording (EEG-fMRI) has been proposed as a complementary non-invasive tool, which can give useful additional information in the pre-surgical work-up. However, fMRI maps related to interictal epileptiform activities (IED) often show multiple regions of signal change, or "networks," rather than highly focal ones. Effective connectivity approaches like Dynamic Causal Modeling (DCM) applied to fMRI data potentially offers a framework to address which brain regions drives the generation of seizures and IED within an epileptic network. Here, we present a first attempt to validate DCM on EEG-fMRI data in one patient affected by frontal lobe epilepsy. Pre-surgical EEG-fMRI demonstrated two distinct clusters of blood oxygenation level dependent (BOLD) signal increases linked to IED, one located in the left frontal pole and the other in the ipsilateral dorso-lateral frontal cortex. DCM of the IED-related BOLD signal favored a model corresponding to the left dorso-lateral frontal cortex as driver of changes in the fronto-polar region. The validity of DCM was supported by: (a) the results of two different non-invasive analysis obtained on the same dataset: EEG source imaging (ESI), and "psycho-physiological interaction" analysis; (b) the failure of a first surgical intervention limited to the fronto-polar region; (c) the results of the intracranial EEG monitoring performed after the first surgical intervention confirming a SOZ located over the dorso-lateral frontal cortex. These results add evidence that EEG-fMRI together with advanced methods of BOLD signal analysis is a promising tool that can give relevant information within the epilepsy surgery diagnostic work-up.
Anna Elisabetta eVaudano
Full Text Available Accurate localization of the Seizure Onset Zone (SOZ is crucial in patients with drug-resistance focal epilepsy. EEG with fMRI recording (EEG-fMRI has been proposed as a complementary non-invasive tool, which can give useful additional information in the pre-surgical workup. However, fMRI maps related to interictal epileptiform activities (IED often show multiple regions of signal change, or networks, rather than highly focal ones. Effective connectivity approaches like Dynamic Causal Modelling (DCM applied to fMRI data potentially offers a framework to address which brain regions drives the generation of seizures and IED within an epileptic network. Here we present a first attempt to validate DCM on EEG-fMRI data in one patient affected by frontal lobe epilepsy. Pre-surgical EEG-fMRI demonstrated two distinct clusters of BOLD signal increases linked to IED, one located in the left frontal pole and the other in the ipsilateral dorso-lateral frontal cortex. DCM of the IED-related BOLD signal favoured a model corresponding to the left dorsolateral frontal cortex as driver of changes in the fronto-polar region. The validity of DCM was supported by: (a the results of two different non-invasive analysis obtained on the same dataset: EEG source imaging (ESI, and psychophysiological interaction analysis (PPI; (b the failure of a first surgical intervention limited to the fronto-polar region; (c the results of the intracranial EEG monitoring performed after the first surgical intervention confirming a SOZ located over the dorso-lateral frontal cortex. These results add evidence that EEG-fMRI together with advanced methods of BOLD signal analysis is a promising tool that can give relevant information within the epilepsy surgery diagnostic work-up.
Clark, Jonathan B.; Riley, Terrence
As clinical aerospace neurologists we do not favor using screening EEG in pilot selection on unselected and otherwise asymptomatic individuals. The role of EEG in aviation screening should be as an adjunct to diagnosis, and the decision to disqualify a pilot should never be based solely on the EEG. Although a policy of using a screening EEG in an unselected population might detect an individual with a potentially increased relative risk, it would needlessly exclude many applicants who would probably never have a seizure. A diagnostic test performed on an asymptomatic individual without clinical indications, in a population with a low prevalence of disease (seizure) may be of limited or possibly detrimental value. We feel that rather than do EEGs on all candidates, a better approach would be to perform an EEG for a specific indication, such as family history of seizure, single convulsion (seizure) , history of unexplained loss of consciousness or head injury. Routine screening EEGs in unselected aviation applications are not done without clinical indication in the U.S. Air Force, Navy, or NASA. The USAF discontinued routine screening EEGs for selection in 1978, the U.S. Navy discontinued it in 1981 , and NASA discontinued it in 1995. EEG as an aeromedical screening tool in the US Navy dates back to 1939. The US Navy routinely used EEGs to screen all aeromedical personnel from 1961 to 1981. The incidence of epileptiform activity on EEG in asymptomatic flight candidates ranges from 0.11 to 2.5%. In 3 studies of asymptomatic flight candidates with epileptiform activity on EEG followed for 2 to 15 years, 1 of 31 (3.2%), 1 of 30 (3.3%), and 0 of 14 (0%) developed a seizure, for a cumulative risk of an individual with an epileptiform EEG developing a seizure of 2.67% (2 in 75). Of 28,658 student naval aviation personnel screened 31 had spikes and/or slow waves on EEG, and only 1 later developed a seizure. Of the 28,627 who had a normal EEG, 4 later developed seizures, or
O'Sullivan, S S
BACKGROUND: The EEG is a commonly requested test on patients attending psychiatric services, predominantly to investigate for a possible organic brain syndrome causing behavioural changes. AIMS: To assess referrals for EEG from psychiatric services in comparison with those from other sources. We determine which clinical factors were associated with an abnormal EEG in patients referred from psychiatric sources. METHODS: A retrospective review of EEG requests in a 1-year period was performed. Analysis of referral reasons for psychiatric patients was undertaken, and outcome of patients referred from psychiatric services post-EEG was reviewed. RESULTS: One thousand four hundred and seventy EEGs were reviewed, of which 91 (6.2%) were referred from psychiatry. Neurology service referrals had detection rates of abnormal EEGs of 27%, with psychiatric referrals having the lowest abnormality detection rate of 17.6% (p < 0.1). In psychiatric-referred patients the only significant predictors found of an abnormal EEG were a known history of epilepsy (p < 0.001), being on clozapine (p < 0.05), and a possible convulsive seizure (RR = 6.51). Follow-up data of 53 patients did not reveal a significant clinical impact of EEG results on patient management. CONCLUSIONS: Many patients are referred for EEG from psychiatric sources despite a relatively low index of suspicion of an organic brain disorders, based on reasons for referral documented, with an unsurprising low clinical yield.
Lu, Na; Li, Tengfei; Pan, Jinjin; Ren, Xiaodong; Feng, Zuren; Miao, Hongyu
Electroencephalogram (EEG) provides a non-invasive approach to measure the electrical activities of brain neurons and has long been employed for the development of brain-computer interface (BCI). For this purpose, various patterns/features of EEG data need to be extracted and associated with specific events like cue-paced motor imagery. However, this is a challenging task since EEG data are usually non-stationary time series with a low signal-to-noise ratio. In this study, we propose a novel method, called structure constrained semi-nonnegative matrix factorization (SCS-NMF), to extract the key patterns of EEG data in time domain by imposing the mean envelopes of event-related potentials (ERPs) as constraints on the semi-NMF procedure. The proposed method is applicable to general EEG time series, and the extracted temporal features by SCS-NMF can also be combined with other features in frequency domain to improve the performance of motor imagery classification. Real data experiments have been performed using the SCS-NMF approach for motor imagery classification, and the results clearly suggest the superiority of the proposed method. Comparison experiments have also been conducted. The compared methods include ICA, PCA, Semi-NMF, Wavelets, EMD and CSP, which further verified the effectivity of SCS-NMF. The SCS-NMF method could obtain better or competitive performance over the state of the art methods, which provides a novel solution for brain pattern analysis from the perspective of structure constraint. Copyright © 2015 Elsevier Ltd. All rights reserved.
Full Text Available Abstract Background Two different Human-Machine Interfaces (HMIs were developed, both based on electro-biological signals. One is based on the EMG signal and the other is based on the EEG signal. Two major features of such interfaces are their relatively simple data acquisition and processing systems, which need just a few hardware and software resources, so that they are, computationally and financially speaking, low cost solutions. Both interfaces were applied to robotic systems, and their performances are analyzed here. The EMG-based HMI was tested in a mobile robot, while the EEG-based HMI was tested in a mobile robot and a robotic manipulator as well. Results Experiments using the EMG-based HMI were carried out by eight individuals, who were asked to accomplish ten eye blinks with each eye, in order to test the eye blink detection algorithm. An average rightness rate of about 95% reached by individuals with the ability to blink both eyes allowed to conclude that the system could be used to command devices. Experiments with EEG consisted of inviting 25 people (some of them had suffered cases of meningitis and epilepsy to test the system. All of them managed to deal with the HMI in only one training session. Most of them learnt how to use such HMI in less than 15 minutes. The minimum and maximum training times observed were 3 and 50 minutes, respectively. Conclusion Such works are the initial parts of a system to help people with neuromotor diseases, including those with severe dysfunctions. The next steps are to convert a commercial wheelchair in an autonomous mobile vehicle; to implement the HMI onboard the autonomous wheelchair thus obtained to assist people with motor diseases, and to explore the potentiality of EEG signals, making the EEG-based HMI more robust and faster, aiming at using it to help individuals with severe motor dysfunctions.
Fingelkurts, Andrew; Fingelkurts, Alexander; Krause, Christina; Kaplan, Alexander; Borisov, Sergei; Sams, Mikko
Memory paradigms are often used in psycho-physiological experiments in order to understand the neural basis underlying cognitive processes. One of the fundamental problems encountered in memory research is how specific and complementary cortical structures interact with each other during episodic encoding and retrieval. A key aspect of the research described below was estimating the coupling of rapid transition processes (in terms of EEG description) which occur in separate cortical areas rather than estimating the routine phase-frequency synchrony in terms of correlation and coherency. It is assumed that these rapid transition processes in the EEG amplitude correspond to the "switching on/off" of brain elemental operations. By making a quantitative estimate of the EEG structural synchrony of alpha-band power between different EEG channels, it was shown that short-term memory has the emergent property of a multiregional neuronal network, and is not the product of strictly hierarchical processing based on convergence through association regions. Moreover, it was demonstrated that the dynamic temporal structure of alpha activity is strongly correlated to the dynamic structure of working memory.
DelPozo-Banos, Marcos; Travieso, Carlos M.; Weidemann, Christoph T.; Alonso, Jesús B.
Objective. Although interest in using electroencephalogram (EEG) activity for subject identification has grown in recent years, the state of the art still lacks a comprehensive exploration of the discriminant information within it. This work aims to fill this gap, and in particular, it focuses on the time-frequency representation of the EEG. Approach. We executed qualitative and quantitative analyses of six publicly available data sets following a sequential experimentation approach. This approach was divided in three blocks analysing the configuration of the power spectrum density, the representation of the data and the properties of the discriminant information. A total of ten experiments were applied. Main results. Results show that EEG information below 40 Hz is unique enough to discriminate across subjects (a maximum of 100 subjects were evaluated here), regardless of the recorded cognitive task or the sensor location. Moreover, the discriminative power of rhythms follows a W-like shape between 1 and 40 Hz, with the central peak located at the posterior rhythm (around 10 Hz). This information is maximized with segments of around 2 s, and it proved to be moderately constant across montages and time. Significance. Therefore, we characterize how EEG activity differs across individuals and detail the optimal conditions to detect subject-specific information. This work helps to clarify the results of previous studies and to solve some unanswered questions. Ultimately, it will serve as guide for the design of future biometric systems.
Full Text Available EEG signals had been widely used to detect liars recent years. To overcome the shortcomings of current signals processing, kernel principal component analysis (KPCA and extreme learning machine (ELM was combined to detect liars. We recorded the EEG signals at Pz from 30 randomly divided guilty and innocent subjects. Each five Probe responses were averaged within subject and then extracted wavelet features. KPCA was employed to select feature subset with deduced dimensions based on initial wavelet features, which was fed into ELM. To date, there is no perfect solution for the number of its hidden nodes (NHN. We used grid searching algorithm to select simultaneously the optimal values of the dimension of feature subset and NHN based on cross- validation method. The best classification mode was decided with the optimal searching values. Experimental results show that for EEG signals from the experiment of lie detection, KPCA_ELM has higher classification accuracy with faster training speed than other widely-used classification modes, which is especially suitable for online EEG signals processing system.
Li, Xiaowei; Hu, Bin; Shen, Ji; Xu, Tingting; Retcliffe, Martyn
Depression is a common mental disorder with growing prevalence; however current diagnoses of depression face the problem of patient denial, clinical experience and subjective biases from self-report. By using a combination of linear and nonlinear EEG features in our research, we aim to develop a more accurate and objective approach to depression detection that supports the process of diagnosis and assists the monitoring of risk factors. By classifying EEG features during free viewing task, an accuracy of 99.1%, which is the highest to our knowledge by far, was achieved using kNN classifier to discriminate depressed and non-depressed subjects. Furthermore, through correlation analysis, comparisons of performance on each electrode were discussed on the availability of single channel EEG recording depression detection system. Combined with wearable EEG collecting devices, our method offers the possibility of cost effective wearable ubiquitous system for doctors to monitor their patients with depression, and for normal people to understand their mental states in time.
Attaheri, Adam; Kikuchi, Yukiko; Milne, Alice E; Wilson, Benjamin; Alter, Kai; Petkov, Christopher I
Electroencephalography (EEG) has identified human brain potentials elicited by Artificial Grammar (AG) learning paradigms, which present participants with rule-based sequences of stimuli. Nonhuman animals are sensitive to certain AGs; therefore, evaluating which EEG Event Related Potentials (ERPs) are associated with AG learning in nonhuman animals could identify evolutionarily conserved processes. We recorded EEG potentials during an auditory AG learning experiment in two Rhesus macaques. The animals were first exposed to sequences of nonsense words generated by the AG. Then surface-based ERPs were recorded in response to sequences that were 'consistent' with the AG and 'violation' sequences containing illegal transitions. The AG violations strongly modulated an early component, potentially homologous to the Mismatch Negativity (mMMN), a P200 and a late frontal positivity (P500). The macaque P500 is similar in polarity and time of occurrence to a late EEG positivity reported in human AG learning studies but might differ in functional role. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
Full Text Available Motor Imagery (MI electroencephalography (EEG is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features, which not only create an additional overhead of managing the space complexity, but also might include outliers, thereby reducing classification accuracy. The firefly algorithm (FA can adaptively select the best subset of features, and improve classification accuracy. However, the FA is easily entrapped in a local optimum. To solve this problem, this paper proposes a method of combining the firefly algorithm and learning automata (LA to optimize feature selection for motor imagery EEG. We employed a method of combining common spatial pattern (CSP and local characteristic-scale decomposition (LCD algorithms to obtain a high dimensional feature set, and classified it by using the spectral regression discriminant analysis (SRDA classifier. Both the fourth brain–computer interface competition data and real-time data acquired in our designed experiments were used to verify the validation of the proposed method. Compared with genetic and adaptive weight particle swarm optimization algorithms, the experimental results show that our proposed method effectively eliminates redundant features, and improves the classification accuracy of MI EEG signals. In addition, a real-time brain–computer interface system was implemented to verify the feasibility of our proposed methods being applied in practical brain–computer interface systems.
Liu, Ning-Han; Chiang, Cheng-Yu; Chu, Hsuan-Chin
During the learning process, whether students remain attentive throughout instruction generally influences their learning efficacy. If teachers can instantly identify whether students are attentive they can be suitably reminded to remain focused, thereby improving their learning effects. Traditional teaching methods generally require that teachers observe students' expressions to determine whether they are attentively learning. However, this method is often inaccurate and increases the burden on teachers. With the development of electroencephalography (EEG) detection tools, mobile brainwave sensors have become mature and affordable equipment. Therefore, in this study, whether students are attentive or inattentive during instruction is determined by observing their EEG signals. Because distinguishing between attentiveness and inattentiveness is challenging, two scenarios were developed for this study to measure the subjects' EEG signals when attentive and inattentive. After collecting EEG data using mobile sensors, various common features were extracted from the raw data. A support vector machine (SVM) classifier was used to calculate and analyze these features to identify the combination of features that best indicates whether students are attentive. Based on the experiment results, the method proposed in this study provides a classification accuracy of up to 76.82%. The study results can be used as a reference for learning system designs in the future.
Liu, Aiming; Chen, Kun; Liu, Quan; Ai, Qingsong; Xie, Yi; Chen, Anqi
Motor Imagery (MI) electroencephalography (EEG) is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features, which not only create an additional overhead of managing the space complexity, but also might include outliers, thereby reducing classification accuracy. The firefly algorithm (FA) can adaptively select the best subset of features, and improve classification accuracy. However, the FA is easily entrapped in a local optimum. To solve this problem, this paper proposes a method of combining the firefly algorithm and learning automata (LA) to optimize feature selection for motor imagery EEG. We employed a method of combining common spatial pattern (CSP) and local characteristic-scale decomposition (LCD) algorithms to obtain a high dimensional feature set, and classified it by using the spectral regression discriminant analysis (SRDA) classifier. Both the fourth brain-computer interface competition data and real-time data acquired in our designed experiments were used to verify the validation of the proposed method. Compared with genetic and adaptive weight particle swarm optimization algorithms, the experimental results show that our proposed method effectively eliminates redundant features, and improves the classification accuracy of MI EEG signals. In addition, a real-time brain-computer interface system was implemented to verify the feasibility of our proposed methods being applied in practical brain-computer interface systems.
Zhuo Zhang; Cuntai Guan; Ti Eu Chan; Juanhong Yu; Aung Aung Phyo Wai; Chuanchu Wang; Haihong Zhang
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.
Full Text Available People often make decisions based on sensitivity rather than rationality. In the field of biological information processing, methods are available for analyzing biological information directly based on electroencephalogram: EEG to determine the pleasant/unpleasant reactions of users. In this study, we propose a sensitivity filtering technique for discriminating preferences (pleasant/unpleasant for images using a sensitivity image filtering system based on EEG. Using a set of images retrieved by similarity retrieval, we perform the sensitivity-based pleasant/unpleasant classification of images based on the affective features extracted from images with the maximum entropy method: MEM. In the present study, the affective features comprised cross-correlation features obtained from EEGs produced when an individual observed an image. However, it is difficult to measure the EEG when a subject visualizes an unknown image. Thus, we propose a solution where a linear regression method based on canonical correlation is used to estimate the cross-correlation features from image features. Experiments were conducted to evaluate the validity of sensitivity filtering compared with image similarity retrieval methods based on image features. We found that sensitivity filtering using color correlograms was suitable for the classification of preferred images, while sensitivity filtering using local binary patterns was suitable for the classification of unpleasant images. Moreover, sensitivity filtering using local binary patterns for unpleasant images had a 90% success rate. Thus, we conclude that the proposed method is efficient for filtering unpleasant images.
Hosseinifard, Behshad; Moradi, Mohammad Hassan; Rostami, Reza
Diagnosing depression in the early curable stages is very important and may even save the life of a patient. In this paper, we study nonlinear analysis of EEG signal for discriminating depression patients and normal controls. Forty-five unmedicated depressed patients and 45 normal subjects were participated in this study. Power of four EEG bands and four nonlinear features including detrended fluctuation analysis (DFA), higuchi fractal, correlation dimension and lyapunov exponent were extracted from EEG signal. For discriminating the two groups, k-nearest neighbor, linear discriminant analysis and logistic regression as the classifiers are then used. Highest classification accuracy of 83.3% is obtained by correlation dimension and LR classifier among other nonlinear features. For further improvement, all nonlinear features are combined and applied to classifiers. A classification accuracy of 90% is achieved by all nonlinear features and LR classifier. In all experiments, genetic algorithm is employed to select the most important features. The proposed technique is compared and contrasted with the other reported methods and it is demonstrated that by combining nonlinear features, the performance is enhanced. This study shows that nonlinear analysis of EEG can be a useful method for discriminating depressed patients and normal subjects. It is suggested that this analysis may be a complementary tool to help psychiatrists for diagnosing depressed patients. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Barua, Shaibal; Ahmed, Mobyen Uddin; Begum, Shahina
A growing traffic safety issue is the effect of cognitive loading activities on traffic safety and driving performance. To monitor drivers' mental state, understanding cognitive load is important since while driving, performing cognitively loading secondary tasks, for example talking on the phone, can affect the performance in the primary task, i.e. driving. Electroencephalography (EEG) is one of the reliable measures of cognitive load that can detect the changes in instantaneous load and effect of cognitively loading secondary task. In this driving simulator study, 1-back task is carried out while the driver performs three different simulated driving scenarios. This paper presents an EEG based approach to classify a drivers' level of cognitive load using Case-Based Reasoning (CBR). The results show that for each individual scenario as well as using data combined from the different scenarios, CBR based system achieved approximately over 70% of classification accuracy.
Kapoor, R.P.; Srinivasan, G.; Ellappan, T.R.; Ramalingam, P.V.; Vasudevan, A.T.; Iyer, M.A.K.; Lee, S.M.; Bhoje, S.B.
Fast Breeder Test Reactor (FBTR) is a 40 MWt/13.2 MWe sodium cooled mixed carbide fuelled reactor. Its main aim is to generate experience in the design, construction and operation of fast reactors including sodium systems and to serve as an irradiation facility for the development of fuel and structural materials for future fast reactors. It achieved first criticality in Oct 85 with Mark I core (70% PuC - 30% UC). Steam generator was put in service in Jan 93 and power was raised to 10.5 MWt in Dec 93. Turbine generator was synchronised to the grid in Jul 97. The indigenously developed mixed carbide fuel has achieved a burnup of 44,000 MW-d/t max at a linear heat rating of 320 W/cm max without any fuel clad failure. The commissioning and operation of sodium systems and components have been smooth and performance of major components, viz., sodium pumps, intermediate heat exchangers and once through sodium heated steam generators (SG) have been excellent. There have been three minor incidents of Na/NaK leaks during the past 14 years, which are described in the paper. There have been no incident of a tube leak in SG. However, three incidents of water leaks from water / steam headers have been detailed. The plant has encountered some unusual occurrences, which were critically analysed and remedial measures, in terms of system and procedural modifications, incorporated to prevent recurrence. This paper describes unusual occurrences of fuel handling incident of May 1987, main boiler feed pump seizure in Apr 1992, reactivity transients in Nov 1994 and Apr 1995, and malfunctioning of the core cover plate mechanism in Jul 1995. These incidents have resulted in long plant shutdowns. During the course of investigation, various theoretical and experimental studies were carried out for better understanding of the phenomena and several inspection techniques and tools were developed resulting in enriching the technology of sodium cooled reactors. FBTR has 36 neutronic and process
Full Text Available Malignant peripheral nerve sheath tumor (MPNST is a rare soft tissue sarcoma. Most arise in association with major nerve trunks. Their most common anatomical sites are the proximal portions of the upper and lower extremities and the trunk. MPNSTs have rarely been reported in literature to occur in other unusual body parts. We review all such cases reported till now in terms of site of origin, surgical treatment, adjuvant therapy and outcome and shortly describe our experience with two of these cases. Both of our case presented with lump at unusual sites resembling neurofibroma, one at orbitotemporal area and other in the paraspinal region with characteristic feature of neurofibroma with the exception that both had very short history of progression. They underwent gross total removal of the tumor with adjuvant radiotherapy postoperatively. At 6-month follow-up both are doing well with no evidence of recurrence.
Lazo, M.; Tsoneva, T.; Garcia Molina, G.
Steady-State Visual Evoked Potential (SSVEP) is an oscillatory electrical response appearing in the electroencephalogram (EEG) in response to flicker stimulation. The SSVEP manifests more prominently in electrodes located near the visual cortex and has oscillatory components at the stimulation frequency and/or harmonics. The phase and amplitude of the SSVEP are sensitive to stimulus parameters such as frequency, modu-lation depth, and spatial frequency. Research related to SSVEP and the human...
hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and...some conditions, an automation feature was implemented to help the participants find the HVT. When the HVT was within the sensor footprint, a tone...EEG Data Investigation Using Only Artifacts 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 1 Chelsey
Graffigna, Juan P; Gómez, M Eugenia; Bustos, José J
This paper presents a method to detect 128 EEG electrodes in image study and to merge with the Nuclear Magnetic Resonance volume for better diagnosis. First we propose three hypotheses to define a specific acquisition protocol in order to recognize the electrodes and to avoid distortions in the image. In the second instance we describe a method for segmenting the electrodes. Finally, registration is performed between volume of the electrodes and NMR.
Schroeder, Eric D.; Walker, Nicholas; Danko, Amanda S.
Brain-computer interfaces (BCIs) measuring electrical activity via electroencephalogram (EEG) have evolved beyond clinical applications to become wireless consumer products. Typically marketed for meditation and neu- rotherapy, these devices are limited in scope and currently too obtrusive to be a ubiquitous wearable. Stemming from recent advancements made in hearing aid technology, wearables have been shrinking to the point that the necessary sensors, circuitry, and batteries can be fit into a small in-ear wearable device. In this work, an ear-EEG device is created with a novel system for artifact removal and signal interpretation. The small, compact, cost-effective, and discreet device is demonstrated against existing consumer electronics in this space for its signal quality, comfort, and usability. A custom mobile application is developed to process raw EEG from each device and display interpreted data to the user. Artifact removal and signal classification is accomplished via a combination of support matrix machines (SMMs) and soft thresholding of relevant statistical properties.
Melman, Tamar; Victor, Jonathan D
Typical electroencephalogram (EEG) recordings often contain substantial artifact. These artifacts, often large and intermittent, can interfere with quantification of the EEG via its power spectrum. To reduce the impact of artifact, EEG records are typically cleaned by a preprocessing stage that removes individual segments or components of the recording. However, such preprocessing can introduce bias, discard available signal, and be labor-intensive. With this motivation, we present a method that uses robust statistics to reduce dependence on preprocessing by minimizing the effect of large intermittent outliers on the spectral estimates. Using the multitaper method (Thomson, 1982) as a starting point, we replaced the final step of the standard power spectrum calculation with a quantile-based estimator, and the Jackknife approach to confidence intervals with a Bayesian approach. The method is implemented in provided MATLAB modules, which extend the widely used Chronux toolbox. Using both simulated and human data, we show that in the presence of large intermittent outliers, the robust method produces improved estimates of the power spectrum, and that the Bayesian confidence intervals yield close-to-veridical coverage factors. The robust method, as compared to the standard method, is less affected by artifact: inclusion of outliers produces fewer changes in the shape of the power spectrum as well as in the coverage factor. In the presence of large intermittent outliers, the robust method can reduce dependence on data preprocessing as compared to standard methods of spectral estimation. Copyright © 2016 Elsevier B.V. All rights reserved.
Full Text Available The study of cognitive processes is regarded to be more effective if it combines a psychological approach with a neurophysiological one. This approach makes it possible to come closer to understanding of the basic mechanisms of different cognitive processes, to describe the patterns of forming these mechanisms in ontogenesis, to investigate the origin of cognitive impairments, and to develop intervention techniques. The promising way of investigating the mechanisms of cognitive functions is the electroencephalography (EEG. This is a non-invasive, safe, and relatively cheap method of research of the functional condition of the brain. The characteristics of EEG rhythms, recorded with different cognitive loads, reflect the processes of functional modulation of neural network activity of the cortex, which serves the neurophysiologic basis for attention, memory and other cognitive processes. The article provides an overview of works containing the analysis of the alpha and theta rhythms’ dynamics in various states of wakefulness. It also introduces the substantiation of methodology of functional regulatory approach to the interpretation of behaviors of EEG rhythms.
Hansen, Sofie Therese; Hauberg, Søren; Hansen, Lars Kai
Electroencephalography (EEG) is a flexible and accessible tool with excellent temporal resolution but with a spatial resolution hampered by volume conduction. Reconstruction of the cortical sources of measured EEG activity partly alleviates this problem and effectively turns EEG into a brain......-of-concept study, we show that, even when anatomical knowledge is unavailable, a suitable forward model can be estimated directly from the EEG. We propose a data-driven approach that provides a low-dimensional parametrization of head geometry and compartment conductivities, built using a corpus of forward models....... Combined with only a recorded EEG signal, we are able to estimate both the brain sources and a person-specific forward model by optimizing this parametrization. We thus not only solve an inverse problem, but also optimize over its specification. Our work demonstrates that personalized EEG brain imaging...
Farina, Benedetto; Speranza, Anna Maria; Dittoni, Serena; Gnoni, Valentina; Trentini, Cristina; Vergano, Carola Maggiora; Liotti, Giovanni; Brunetti, Riccardo; Testani, Elisa; Della Marca, Giacomo
In this study, we evaluated cortical connectivity modifications by electroencephalography (EEG) lagged coherence analysis, in subjects with dissociative disorders and in controls, after retrieval of attachment memories. We asked thirteen patients with dissociative disorders and thirteen age- and sex-matched healthy controls to retrieve personal attachment-related autobiographical memories through adult attachment interviews (AAI). EEG was recorded in the closed eyes resting state before and after the AAI. EEG lagged coherence before and after AAI was compared in all subjects. In the control group, memories of attachment promoted a widespread increase in EEG connectivity, in particular in the high-frequency EEG bands. Compared to controls, dissociative patients did not show an increase in EEG connectivity after the AAI. Conclusions: These results shed light on the neurophysiology of the disintegrative effect of retrieval of traumatic attachment memories in dissociative patients.
Corsi-Cabrera, M; Juárez, J; Ponce-de-León, M; Ramos, J; Velázquez, P N
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.
... more information). Unusual Cancers of the Head and Neck Nasopharyngeal Cancer See the PDQ summary on Childhood ... of PDQ documents can be used freely as text. It cannot be identified as an NCI PDQ ...
Full Text Available Simultaneous EEG-fMRI recordings have seen growing application in the evaluation of epilepsy, namely in the characterization of brain networks related to epileptic activity. In EEG-correlated fMRI studies, epileptic events are usually described as boxcar signals based on the timing information retrieved from the EEG, and subsequently convolved with a heamodynamic response function to model the associated BOLD changes. Although more flexible approaches may allow a higher degree of complexity for the haemodynamics, the issue of how to model these dynamics based on the EEG remains an open question. In this work, a new methodology for the integration of simultaneous EEG-fMRI data in epilepsy is proposed, which incorporates a transfer function from the EEG to the BOLD signal. Independent component analysis (ICA of the EEG is performed, and a number of metrics expressing different models of the EEG-BOLD transfer function are extracted from the resulting time courses. These metrics are then used to predict the fMRI data and to identify brain areas associated with the EEG epileptic activity. The methodology was tested on both ictal and interictal EEG-fMRI recordings from one patient with a hypothalamic hamartoma. When compared to the conventional analysis approach, plausible, consistent and more significant activations were obtained. Importantly, frequency-weighted EEG metrics yielded superior results than those weighted solely on the EEG power, which comes in agreement with previous literature. Reproducibility, specificity and sensitivity should be addressed in an extended group of patients in order to further validate the proposed methodology and generalize the presented proof of concept.
Full Text Available Note onsets in music are acoustic landmarks providing auditory cues that underlie the perception of more complex phenomena such as beat, rhythm, and meter. For naturalistic ongoing sounds a detailed view on the neural representation of onset structure is hard to obtain, since, typically, stimulus-related EEG signatures are derived by averaging a high number of identical stimulus presentations. Here, we propose a novel multivariate regression-based method extracting onset-related brain responses from the ongoing EEG. We analyse EEG recordings of nine subjects who passively listened to stimuli from various sound categories encompassing simple tone sequences, full-length romantic piano pieces and natural (non-music soundscapes. The regression approach reduces the 61-channel EEG to one time course optimally reflecting note onsets. The neural signatures derived by this procedure indeed resemble canonical onset-related ERPs, such as the N1-P2 complex. This EEG projection was then utilized to determine the Cortico-Acoustic Correlation (CACor, a measure of synchronization between EEG signal and stimulus. We demonstrate that a significant CACor (i can be detected in an individual listener's EEG of a single presentation of a full-length complex naturalistic music stimulus, and (ii it co-varies with the stimuli's average magnitudes of sharpness, spectral centroid, and rhythmic complexity. In particular, the subset of stimuli eliciting a strong CACor also produces strongly coordinated tension ratings obtained from an independent listener group in a separate behavioral experiment. Thus musical features that lead to a marked physiological reflection of tone onsets also contribute to perceived tension in music.
Kubany, Adam; Mhabary, Ziv; Gontar, Vladimir
Research highlights: → ANN of 2D interconnected chaotic oscillators is explored for EEG simulation. → An inverse problem solution (PRCGA) is proposed. → Good matching between the simulated and experimental EEG signals has been achieved. - Abstract: An artificial neuronal network composed by 2D interconnected chaotic oscillators is explored for brain waves (EEG) simulation. For the inverse problem solution a parallel real-coded genetic algorithm (PRCGA) is proposed. In order to conduct thorough comparison between the simulated and target signal characteristics, a spectrum analysis of the signals is undertaken. A good matching between the theoretical and experimental EEG signals has been achieved. Numerical results of calculations are presented and discussed.
EEG (Electroencephalograph), as a noninvasive testing method, plays a key role in the diagnosing diseases, and is useful for both physiological research and medical applications. Wavelet transform (WT...
Panischev, O Yu; Demin, S A; Muhametshin, I G; Yu Demina, N
In paper we apply the method based on the Flicker-Noise Spectroscopy (FNS) to determine the differences in frequency-phase synchronization of the cortical electroencephalographic (EEG) activities in patients with bipolar disorder (BD). We found that for healthy subjects the frequency-phase synchronization of EEGs from long-range electrodes was significantly better for BD patients. In BD patients a high synchronization of EEGs was observed only for short-range electrodes. Thus, the FNS is a simple graphical method for qualitative analysis can be applied to identify the synchronization effects in EEG activity and, probably, may be used for the diagnosis of this syndrome. (paper)
Panischev, O. Yu; Demin, S. A.; Muhametshin, I. G.; Demina, N. Yu
In paper we apply the method based on the Flicker-Noise Spectroscopy (FNS) to determine the differences in frequency-phase synchronization of the cortical electroencephalographic (EEG) activities in patients with bipolar disorder (BD). We found that for healthy subjects the frequency-phase synchronization of EEGs from long-range electrodes was significantly better for BD patients. In BD patients a high synchronization of EEGs was observed only for short-range electrodes. Thus, the FNS is a simple graphical method for qualitative analysis can be applied to identify the synchronization effects in EEG activity and, probably, may be used for the diagnosis of this syndrome.
Antoniades, Andreas; Spyrou, Loukianos; Martin-Lopez, David; Valentin, Antonio; Alarcon, Gonzalo; Sanei, Saeid; Took, Clive Cheong
Data is often plagued by noise which encumbers machine learning of clinically useful biomarkers and electroencephalogram (EEG) data is no exemption. Intracranial EEG (iEEG) data enhances the training of deep learning models of the human brain, yet is often prohibitive due to the invasive recording process. A more convenient alternative is to record brain activity using scalp electrodes. However, the inherent noise associated with scalp EEG data often impedes the learning process of neural models, achieving substandard performance. Here, an ensemble deep learning architecture for nonlinearly mapping scalp to iEEG data is proposed. The proposed architecture exploits the information from a limited number of joint scalp-intracranial recording to establish a novel methodology for detecting the epileptic discharges from the sEEG of a general population of subjects. Statistical tests and qualitative analysis have revealed that the generated pseudo-intracranial data are highly correlated with the true intracranial data. This facilitated the detection of IEDs from the scalp recordings where such waveforms are not often visible. As a real-world clinical application, these pseudo-iEEGs are then used by a convolutional neural network for the automated classification of intracranial epileptic discharges (IEDs) and non-IED of trials in the context of epilepsy analysis. Although the aim of this work was to circumvent the unavailability of iEEG and the limitations of sEEG, we have achieved a classification accuracy of 68% an increase of 6% over the previously proposed linear regression mapping.
Kubany, Adam, E-mail: email@example.com [Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, P.O. Box 653, Beer-Sheva 84105 (Israel); Mhabary, Ziv; Gontar, Vladimir [Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, P.O. Box 653, Beer-Sheva 84105 (Israel)
Research highlights: ANN of 2D interconnected chaotic oscillators is explored for EEG simulation. An inverse problem solution (PRCGA) is proposed. Good matching between the simulated and experimental EEG signals has been achieved. - Abstract: An artificial neuronal network composed by 2D interconnected chaotic oscillators is explored for brain waves (EEG) simulation. For the inverse problem solution a parallel real-coded genetic algorithm (PRCGA) is proposed. In order to conduct thorough comparison between the simulated and target signal characteristics, a spectrum analysis of the signals is undertaken. A good matching between the theoretical and experimental EEG signals has been achieved. Numerical results of calculations are presented and discussed.
Vries, M. de; Wilder-Smith, O.H.G.; Jongsma, M.L.A.; Broeke, E.N. van den; Arns, M.W.; Goor, H. van; Rijn, C.M. van
OBJECTIVES: Electroencephalography (EEG) may be a promising source of physiological biomarkers accompanying chronic pain. Several studies in patients with chronic neuropathic pain have reported alterations in central pain processing, manifested as slowed EEG rhythmicity and increased EEG power in
Vries, M. de; Wilder-Smith, O.H.G.; Jongsma, M.L.A.; Broeke, E.N. van den; Arns, M.W.; Goor, H. van; Rijn, C.M. van
Objectives: Electroencephalography (EEG) may be a promising source of physiological biomarkers accompanying chronic pain. Several studies in patients with chronic neuropathic pain have reported alterations in central pain processing, manifested as slowed EEG rhythmicity and increased EEG power in
Full Text Available Abstract Background The subjects in EEG-Brain computer interface (BCI system experience difficulties when attempting to obtain the consistent performance of the actual movement by motor imagery alone. It is necessary to find the optimal conditions and stimuli combinations that affect the performance factors of the EEG-BCI system to guarantee equipment safety and trust through the performance evaluation of using motor imagery characteristics that can be utilized in the EEG-BCI testing environment. Methods The experiment was carried out with 10 experienced subjects and 32 naive subjects on an EEG-BCI system. There were 3 experiments: The experienced homogeneous experiment, the naive homogeneous experiment and the naive heterogeneous experiment. Each experiment was compared in terms of the six audio-visual cue combinations and consisted of 50 trials. The EEG data was classified using the least square linear classifier in case of the naive subjects through the common spatial pattern filter. The accuracy was calculated using the training and test data set. The p-value of the accuracy was obtained through the statistical significance test. Results In the case in which a naive subject was trained by a heterogeneous combined cue and tested by a visual cue, the result was not only the highest accuracy (p Conclusions We propose the use of this measuring methodology of a heterogeneous combined cue for training data and a visual cue for test data by the typical EEG-BCI algorithm on the EEG-BCI system to achieve effectiveness in terms of consistence, stability, cost, time, and resources management without the need for a trial and error process.
Folgieri, Raffaella; Lucchiari, Claudio; Marini, Daniele
The research project intends to demonstrate how EEG detection through BCI device can improve the analysis and the interpretation of colours-driven cognitive processes through the combined approach of cognitive science and information technology methods. To this end, firstly it was decided to design an experiment based on comparing the results of the traditional (qualitative and quantitative) cognitive analysis approach with the EEG signal analysis of the evoked potentials. In our case, the sensorial stimulus is represented by the colours, while the cognitive task consists in remembering the words appearing on the screen, with different combination of foreground (words) and background colours. In this work we analysed data collected from a sample of students involved in a learning process during which they received visual stimuli based on colour variation. The stimuli concerned both the background of the text to learn and the colour of the characters. The experiment indicated some interesting results concerning the use of primary (RGB) and complementary (CMY) colours.
Full Text Available This paper introduces the neural correlates of phrase rhythm. In short, phrase rhythm is the rhythmic aspect of phrase construction and the relationships between phrases. For the sake of establishing the neural correlates, a musical experiment has been designed to induce music-evoked stimuli related to phrase rhythm. Brain activity is monitored through electroencephalography (EEG by using a brain–computer interface. The power spectral value of each EEG channel is estimated to obtain how power variance distributes as a function of frequency. Our experiment shows statistical differences in theta and alpha bands in the phrase rhythm variations of two classical sonatas, one in bipartite form and the other in rondo form.
Full Text Available Purpose: Driving fatigue has become one of the important causes of road accidents, there are many researches to analyze driver fatigue. EEG is becoming increasingly useful in the measuring fatigue state. Manual interpretation of EEG signals is impossible, so an effective method for automatic detection of EEG signals is crucial needed.Method: In order to evaluate the complex, unstable, and non-linear characteristics of EEG signals, four feature sets were computed from EEG signals, in which fuzzy entropy (FE, sample entropy (SE, approximate Entropy (AE, spectral entropy (PE, and combined entropies (FE + SE + AE + PE were included. All these feature sets were used as the input vectors of AdaBoost classifier, a boosting method which is fast and highly accurate. To assess our method, several experiments including parameter setting and classifier comparison were conducted on 28 subjects. For comparison, Decision Trees (DT, Support Vector Machine (SVM and Naive Bayes (NB classifiers are used.Results: The proposed method (combination of FE and AdaBoost yields superior performance than other schemes. Using FE feature extractor, AdaBoost achieves improved area (AUC under the receiver operating curve of 0.994, error rate (ERR of 0.024, Precision of 0.969, Recall of 0.984, F1 score of 0.976, and Matthews correlation coefficient (MCC of 0.952, compared to SVM (ERR at 0.035, Precision of 0.957, Recall of 0.974, F1 score of 0.966, and MCC of 0.930 with AUC of 0.990, DT (ERR at 0.142, Precision of 0.857, Recall of 0.859, F1 score of 0.966, and MCC of 0.716 with AUC of 0.916 and NB (ERR at 0.405, Precision of 0.646, Recall of 0.434, F1 score of 0.519, and MCC of 0.203 with AUC of 0.606. It shows that the FE feature set and combined feature set outperform other feature sets. AdaBoost seems to have better robustness against changes of ratio of test samples for all samples and number of subjects, which might therefore aid in the real-time detection of driver
Nasseroleslami, Bahman; Lakany, Heba; Conway, Bernard A
The electroencephalographic (EEG) activity patterns in humans during motor behaviour provide insight into normal motor control processes and for diagnostic and rehabilitation applications. While the patterns preceding brisk voluntary movements, and especially movement execution, are well described, there are few EEG studies that address the cortical activation patterns seen in isometric exertions and their planning. In this paper, we report on time and time-frequency EEG signatures in experiments in normal subjects (n=8), using multichannel EEG during motor preparation, planning and execution of directional centre-out arm isometric exertions performed at the wrist in the horizontal plane, in response to instruction-delay visual cues. Our observations suggest that isometric force exertions are accompanied by transient and sustained event-related potentials (ERP) and event-related (de-)synchronisations (ERD/ERS), comparable to those of a movement task. Furthermore, the ERPs and ERD/ERS are also observed during preparation and planning of the isometric task. Comparison of ear-lobe-referenced and surface Laplacian ERPs indicates the contribution of superficial sources in supplementary and pre-motor (FC(z)), parietal (CP(z)) and primary motor cortical areas (C₁ and FC₁) to ERPs (primarily negative peaks in frontal and positive peaks in parietal areas), but contribution of deep sources to sustained time-domain potentials (negativity in planning and positivity in execution). Transient and sustained ERD patterns in μ and β frequency bands of ear-lobe-referenced and surface Laplacian EEG indicate the contribution of both superficial and deep sources to ERD/ERS. As no physical displacement happens during the task, we can infer that the underlying mechanisms of motor-related ERPs and ERD/ERS patterns do not only depend on change in limb coordinate or muscle-length-dependent ascending sensory information and are primary generated by motor preparation, direction
Full Text Available In America, sixty percent of adults reported that they have driven a motor vehicle while feeling drowsy, and at least 15-20% of fatal car accidents are fatigue-related. This study translates previous laboratory-oriented neurophysiological research to design, develop, and test an On-line Closed-loop Lapse Detection and Mitigation (OCLDM System featuring a mobile wireless dry-sensor EEG headgear and a cell-phone based real-time EEG processing platform. Eleven subjects participated in an event-related lane-keeping task, in which they were instructed to manipulate a randomly deviated, fixed-speed cruising car on a 4-lane highway. This was simulated in a 1st person view with an 8-screen and 8-projector immersive virtual-realty environment. When the subjects experienced lapses or failed to respond to events during the experiment, auditory feedback was delivered to rectify the performance decrements. However, the arousing auditory signals were not always effective. The EEG spectra exhibited statistically significant differences between effective and ineffective arousing signals, suggesting that EEG spectra could be used as a countermeasure of the efficacy of arousing signals. In this on-line pilot study, the proposed OCLDM System was able to continuously detect EEG signatures of fatigue, deliver arousing feedback to subjects suffering momentary cognitive lapses, and assess the efficacy of the feedback in near real-time to rectify cognitive lapses. The on-line testing results of the OCLDM System validated the efficacy of the arousing signals in improving subjects' response times to the subsequent lane-departure events. This study may lead to a practical on-line lapse detection and mitigation system in real-world environments.
Zhang, Zhongnan; Wen, Tingxi; Huang, Wei; Wang, Meihong; Li, Chunfeng
Epilepsy is a chronic disease with transient brain dysfunction that results from the sudden abnormal discharge of neurons in the brain. Since electroencephalogram (EEG) is a harmless and noninvasive detection method, it plays an important role in the detection of neurological diseases. However, the process of analyzing EEG to detect neurological diseases is often difficult because the brain electrical signals are random, non-stationary and nonlinear. In order to overcome such difficulty, this study aims to develop a new computer-aided scheme for automatic epileptic seizure detection in EEGs based on multi-fractal detrended fluctuation analysis (MF-DFA) and support vector machine (SVM). New scheme first extracts features from EEG by MF-DFA during the first stage. Then, the scheme applies a genetic algorithm (GA) to calculate parameters used in SVM and classify the training data according to the selected features using SVM. Finally, the trained SVM classifier is exploited to detect neurological diseases. The algorithm utilizes MLlib from library of SPARK and runs on cloud platform. Applying to a public dataset for experiment, the study results show that the new feature extraction method and scheme can detect signals with less features and the accuracy of the classification reached up to 99%. MF-DFA is a promising approach to extract features for analyzing EEG, because of its simple algorithm procedure and less parameters. The features obtained by MF-DFA can represent samples as well as traditional wavelet transform and Lyapunov exponents. GA can always find useful parameters for SVM with enough execution time. The results illustrate that the classification model can achieve comparable accuracy, which means that it is effective in epileptic seizure detection.
Wang, Yu-Te; Huang, Kuan-Chih; Wei, Chun-Shu; Huang, Teng-Yi; Ko, Li-Wei; Lin, Chin-Teng; Cheng, Chung-Kuan; Jung, Tzyy-Ping
In America, 60% of adults reported that they have driven a motor vehicle while feeling drowsy, and at least 15-20% of fatal car accidents are fatigue-related. This study translates previous laboratory-oriented neurophysiological research to design, develop, and test an On-line Closed-loop Lapse Detection and Mitigation (OCLDM) System featuring a mobile wireless dry-sensor EEG headgear and a cell-phone based real-time EEG processing platform. Eleven subjects participated in an event-related lane-keeping task, in which they were instructed to manipulate a randomly deviated, fixed-speed cruising car on a 4-lane highway. This was simulated in a 1st person view with an 8-screen and 8-projector immersive virtual-reality environment. When the subjects experienced lapses or failed to respond to events during the experiment, auditory warning was delivered to rectify the performance decrements. However, the arousing auditory signals were not always effective. The EEG spectra exhibited statistically significant differences between effective and ineffective arousing signals, suggesting that EEG spectra could be used as a countermeasure of the efficacy of arousing signals. In this on-line pilot study, the proposed OCLDM System was able to continuously detect EEG signatures of fatigue, deliver arousing warning to subjects suffering momentary cognitive lapses, and assess the efficacy of the warning in near real-time to rectify cognitive lapses. The on-line testing results of the OCLDM System validated the efficacy of the arousing signals in improving subjects' response times to the subsequent lane-departure events. This study may lead to a practical on-line lapse detection and mitigation system in real-world environments.
Suh, Mi Chung; Schultz, David J; Ohlrogge, John B
Unusual monounsaturated fatty acids are major constituents (greater than 80%) in seeds of Coriandrum sativum L. (coriander) and Thunbergia alata Bojer, as well as in glandular trichomes (greater than 80% derived products) of Pelargonium x hortorum (geranium). These diverged fatty acid structures are produced via distinct plastidial acyl-acyl carrier protein (ACP) desaturases. When expressed in Arabidopsis thaliana (L.) Heynh. under strong seed-specific promoters the unusual acyl-ACP desaturases resulted in accumulation of unusual monoene fatty acids at 1-15% of seed fatty acid mass. In this study, we have examined several factors that potentially limit higher production of unusual monoenes in transgenic oilseeds. (i) Immunoblots indicated that the introduced desaturases were expressed at levels equivalent to or higher than the endogenous delta9 18:0-ACP desaturase. However, the level of unusual fatty acid produced in transgenic plants was not correlated with the level of desaturase expression. (ii) The unusual desaturases were expressed in several backgrounds, including antisense 18:0-ACP desaturase plants, in fab1 mutants, and co-expressed with specialized ACP or ferredoxin isoforms. None of these experiments led to high production of expected products. (iii) No evidence was found for degradation of the unusual fatty acids during seed development. (iv) Petroselinic acid added to developing seeds was incorporated into triacylglycerol as readily as oleic acid, suggesting no major barriers to its metabolism by enzymes of glycerolipid assembly. (v) In vitro and in situ assay of acyl-ACP desaturases revealed a large discrepancy of activity when comparing unusual acyl-ACP desaturases with the endogenous delta9 18:0-ACP desaturase. The combined results, coupled with the sensitivity of acyl-ACP desaturase activity to centrifugation and low salt or detergent suggests low production of unusual monoenes in transgenic plants may be due to the lack of, or incorrect assemble of
Mookgo S. Kgatle
Full Text Available This article reflects and makes recommendations on the recent unusual practices within some Neo-Pentecostal churches in South Africa. Neo-Pentecostal churches in South Africa refer to churches that have crossed denominational boundaries. These churches idolise the miraculous, healing, deliverance and enactment of bizarre church performances often performed by charismatic and highly influential spiritual leaders. There have been unusual practices within some Neo-Pentecostal churches that include, among others, the eating of grass, eating of snakes, drinking of petrol, spraying of Doom on the congregants and other experiences. There are many possible theological, psychological and socio-economic explanations for these unusual practices. Given the facts that many South Africans experience various socio-economic challenges, it is argued here that the socio-economic factor is the main explanation for the support of these unusual practices. The unusual practices within some Neo-Pentecostal churches in South Africa are critically unpacked by looking at various churches where the incidents happened. The possible theological, psychological and socio-economic explanations for such practices are outlined in detail. Recommendations are made based on the scientific findings on the unusual practices.
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
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
Full Text Available The present study investigated 24 individuals suffering from chronic tinnitus (TI and 24 nonaffected controls (CO. We recorded resting-state EEG and collected psychometric data to obtain information about how chronic tinnitus experience affects the cognitive and emotional state of TI. The study was meant to disentangle TI with high distress from those who suffer less from persistent tinnitus based on both neurophysiological and behavioral data. A principal component analysis of psychometric data uncovers two distinct independent dimensions characterizing the individual tinnitus experience. These independent states are distress and presence, the latter is described as the perceived intensity of sound experience that increases with tinnitus duration devoid of any considerable emotional burden. Neuroplastic changes correlate with the two independent components. TI with high distress display increased EEG activity in the oscillatory range around 25 Hz (upper β-band that agglomerates over frontal recording sites. TI with high presence show enhanced EEG signal strength in the δ-, α-, and lower γ-bands (30–40 Hz over bilateral temporal and left perisylvian electrodes. Based on these differential patterns we suggest that the two dimensions, namely, distress and presence, should be considered as independent dimensions of chronic subjective tinnitus.
Oyama, Katsunori; Sakatani, Kaoru
Simultaneous monitoring of brain activity with near-infrared spectroscopy and electroencephalography allows spatiotemporal reconstruction of the hemodynamic response regarding the concentration changes in oxyhemoglobin and deoxyhemoglobin that are associated with recorded brain activity such as cognitive functions. However, the accuracy of state estimation during mental arithmetic tasks is often different depending on the length of the segment for sampling of NIRS and EEG signals. This study compared the results of a self-organizing map and ANOVA, which were both used to assess the accuracy of state estimation. We conducted an experiment with a mental arithmetic task performed by 10 participants. The lengths of the segment in each time frame for observation of NIRS and EEG signals were compared with the 30-s, 1-min, and 2-min segment lengths. The optimal segment lengths were different for NIRS and EEG signals in the case of classification of feature vectors into the states of performing a mental arithmetic task and being at rest.
Wang, Chun-mei; Zhang, Chong-ming; Zou, Jun-zhong; Zhang, Jian
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.
Geut, I.; Weenink, S.; Knottnerus, I.L.H.; van Putten, Michel J.A.M.
Purpose Uncertainty about recurrence after a first unprovoked seizure is a significant psychological burden for patients, and motivates the need for diagnostic tools with high sensitivity and specificity to assess recurrence risk. As the sensitivity of a routine EEG after a first unprovoked seizure
Arnolds, D.E.A.T.; Lopes da Silva, F.H.; Aitink, J.W.; Kamp, A.
It was shown that rewarding spectral shifts (i.e. increase in amplitude or peak frequency of the hippocampal EEG) causes a solitary dog to show increased motor behaviour. Rewarded spectral shifts concurred with a variety of behavioural transitions. It was found that statistically significant
Students' cognitive states can reflect a learning experience that results in engagement in an activity. In this study, we used electroencephalography (EEG) physiologically based methodology to evaluate students' levels of attention and relaxation, as well as their learning performance within a traditional and game-based learning context. While no…
Full Text Available Behavioral and neuroimaging studies have demonstrated that people process preferentially self-related information such as an image of their own face. Furthermore, people rapidly incorporate stimuli into their self-representation even if these stimuli do not have an intrinsic relation to self. In the present study, we investigated the time course of the processes involved in preferential processing of self-related information. In two EEG experiments three unfamiliar faces were identified with verbal labels as either the participant, a friend, or a stranger. Afterwards, participants judged whether two stimuli presented in succession (ISI = 1500ms matched. In experiment 1, faces were followed by verbal labels and in experiment 2, labels were followed by faces. Both experiments showed the same pattern of behavioral and electrophysiological results. If the first stimulus (face or label was associated with self, reaction times were faster and the late frontal positivity following the first stimulus was more pronounced. The self-association of the second stimulus (label or face did not affect response times. However, the central-parietal P3 following presentation of the second stimulus was more pronounced when the second stimulus was preceded by self-related first stimulus. These results indicate that even unfamiliar faces that are associated to self can activate a self-representation. Once the self-representation has been activated the processing of ensuing stimuli is facilitated, irrespective of whether they are associated with the self.
Rodolico, Carmelo; Parisi, Daniela; Portaro, Simona; Biasini, Fiammetta; Sinicropi, Stefano; Ciranni, Annamaria; Toscano, Antonio; Messina, Sonia; Musumeci, Olimpia; Vita, Giuseppe; Girlanda, Paolo
Myasthenia gravis (MG) is an autoimmune disorder presenting with fluctuating, fatigable muscle weakness. Initial symptoms classically involve ocular and proximal limb muscles. Rarely, MG may onset with unusual features, so it can be misdiagnosed with other neuromuscular diseases. To describe unusual and atypical presentations of MG in a large cohort of patients, considering and discussing diagnostic difficulties and pitfalls. We report on 21 out of 508 MG patients, coming to our department in the last 27 years and presenting with atypical or unusual features. The diagnosis was achieved performing a careful clinical examination, a proper neurophysiological assessment, the neostigmine test, the AChR and MuSK antibodies assay and chest CT-scan. Patients with atypical/unusual MG onset were the 4.4% of all MG patients population. We describe seven different clinical categories: asymmetric distal upper limbs weakness, foot drop, isolated triceps brachii weakness and foot drop, post exertional axial weakness with dropped head, acute facial dyplegia, limb-girdle MG and MG with sudden lower limbs weakness and recurrent falls. Atypical and unusual presentations may increase the risk to misdiagnose or delay MG diagnosis. Isolated limb-girdle presentation is the most frequent atypical form in our series.
Schwarz, Andreas; Ofner, Patrick; Pereira, Joana; Ioana Sburlea, Andreea; Müller-Putz, Gernot R.
Objective. Despite the high number of degrees of freedom of the human hand, most actions of daily life can be executed incorporating only palmar, pincer and lateral grasp. In this study we attempt to discriminate these three different executed reach-and-grasp actions utilizing their EEG neural correlates. Approach. In a cue-guided experiment, 15 healthy individuals were asked to perform these actions using daily life objects. We recorded 72 trials for each reach-and-grasp condition and from a no-movement condition. Main results. Using low-frequency time domain features from 0.3 to 3 Hz, we achieved binary classification accuracies of 72.4%, STD ± 5.8% between grasp types, for grasps versus no-movement condition peak performances of 93.5%, STD ± 4.6% could be reached. In an offline multiclass classification scenario which incorporated not only all reach-and-grasp actions but also the no-movement condition, the highest performance could be reached using a window of 1000 ms for feature extraction. Classification performance peaked at 65.9%, STD ± 8.1%. Underlying neural correlates of the reach-and-grasp actions, investigated over the primary motor cortex, showed significant differences starting from approximately 800 ms to 1200 ms after the movement onset which is also the same time frame where classification performance reached its maximum. Significance. We could show that it is possible to discriminate three executed reach-and-grasp actions prominent in people’s everyday use from non-invasive EEG. Underlying neural correlates showed significant differences between all tested conditions. These findings will eventually contribute to our attempt of controlling a neuroprosthesis in a natural and intuitive way, which could ultimately benefit motor impaired end users in their daily life actions.
Archana K Singh
Full Text Available There is growing interest in understanding how the brain utilizes synchronized oscillatory activity to integrate information across functionally connected regions. Computing phase-locking values (PLV between EEG signals is a popular method for quantifying such synchronizations and elucidating their role in cognitive tasks. However, high-dimensionality in PLV data incurs a serious multiple testing problem. Standard multiple testing methods in neuroimaging research (e.g., false discovery rate, FDR suffer severe loss of power, because they fail to exploit complex dependence structure between hypotheses that vary in spectral, temporal and spatial dimension. Previously, we showed that a hierarchical FDR and optimal discovery procedures could be effectively applied for PLV analysis to provide better power than FDR. In this article, we revisit the multiple comparison problem from a new Empirical Bayes perspective and propose the application of the local FDR method (locFDR; Efron, 2001 for PLV synchrony analysis to compute FDR as a posterior probability that an observed statistic belongs to a null hypothesis. We demonstrate the application of Efron's Empirical Bayes approach for PLV synchrony analysis for the first time. We use simulations to validate the specificity and sensitivity of locFDR and a real EEG dataset from a visual search study for experimental validation. We also compare locFDR with hierarchical FDR and optimal discovery procedures in both simulation and experimental analyses. Our simulation results showed that the locFDR can effectively control false positives without compromising on the power of PLV synchrony inference. Our results from the application locFDR on experiment data detected more significant discoveries than our previously proposed methods whereas the standard FDR method failed to detect any significant discoveries.
Singh, Archana K; Asoh, Hideki; Takeda, Yuji; Phillips, Steven
There is growing interest in understanding how the brain utilizes synchronized oscillatory activity to integrate information across functionally connected regions. Computing phase-locking values (PLV) between EEG signals is a popular method for quantifying such synchronizations and elucidating their role in cognitive tasks. However, high-dimensionality in PLV data incurs a serious multiple testing problem. Standard multiple testing methods in neuroimaging research (e.g., false discovery rate, FDR) suffer severe loss of power, because they fail to exploit complex dependence structure between hypotheses that vary in spectral, temporal and spatial dimension. Previously, we showed that a hierarchical FDR and optimal discovery procedures could be effectively applied for PLV analysis to provide better power than FDR. In this article, we revisit the multiple comparison problem from a new Empirical Bayes perspective and propose the application of the local FDR method (locFDR; Efron, 2001) for PLV synchrony analysis to compute FDR as a posterior probability that an observed statistic belongs to a null hypothesis. We demonstrate the application of Efron's Empirical Bayes approach for PLV synchrony analysis for the first time. We use simulations to validate the specificity and sensitivity of locFDR and a real EEG dataset from a visual search study for experimental validation. We also compare locFDR with hierarchical FDR and optimal discovery procedures in both simulation and experimental analyses. Our simulation results showed that the locFDR can effectively control false positives without compromising on the power of PLV synchrony inference. Our results from the application locFDR on experiment data detected more significant discoveries than our previously proposed methods whereas the standard FDR method failed to detect any significant discoveries.
Montavont, A; Kaminska, A; Soufflet, C; Taussig, D
Long-term video-EEG corresponds to a recording ranging from 1 to 24 h or even longer. It is indicated in the following situations: diagnosis of epileptic syndromes or unclassified epilepsy, pre-surgical evaluation for drug-resistant epilepsy, follow-up of epilepsy or in cases of paroxysmal symptoms whose etiology remains uncertain. There are some specificities related to paediatric care: a dedicated pediatric unit; continuous monitoring covering at least a full 24-hour period, especially in the context of pre-surgical evaluation; the requirement of presence by the parents, technician or nurse; and stronger attachment of electrodes (cup electrodes), the number of which is adapted to the age of the child. The chosen duration of the monitoring also depends on the frequency of seizures or paroxysmal events. The polygraphy must be adapted to the type and topography of movements. It is essential to have at least an electrocardiography (ECG) channel, respiratory sensor and electromyography (EMG) on both deltoids. There is no age limit for performing long-term video-EEG even in newborns and infants; nevertheless because of scalp fragility, strict surveillance of the baby's skin condition is required. In the specific context of pre-surgical evaluation, long-term video-EEG must record all types of seizures observed in the child. This monitoring is essential in order to develop hypotheses regarding the seizure onset zone, based on electroclinical correlations, which should be adapted to the child's age and the psychomotor development. Copyright © 2015. Published by Elsevier SAS.
Sawan, Mohamad; Salam, Muhammad T; Le Lan, Jérôme; Kassab, Amal; Gelinas, Sébastien; Vannasing, Phetsamone; Lesage, Frédéric; Lassonde, Maryse; Nguyen, Dang K
In this paper, we present the design and implementation of a wireless wearable electronic system dedicated to remote data recording for brain monitoring. The reported wireless recording system is used for a) simultaneous near-infrared spectrometry (NIRS) and scalp electro-encephalography (EEG) for noninvasive monitoring and b) intracerebral EEG (icEEG) for invasive monitoring. Bluetooth and dual radio links were introduced for these recordings. The Bluetooth-based device was embedded in a noninvasive multichannel EEG-NIRS system for easy portability and long-term monitoring. On the other hand, the 32-channel implantable recording device offers 24-bit resolution, tunable features, and a sampling frequency up to 2 kHz per channel. The analog front-end preamplifier presents low input-referred noise of 5 μ VRMS and a signal-to-noise ratio of 112 dB. The communication link is implemented using a dual-band radio frequency transceiver offering a half-duplex 800 kb/s data rate, 16.5 mW power consumption and less than 10(-10) post-correction Bit-Error Rate (BER). The designed system can be accessed and controlled by a computer with a user-friendly graphical interface. The proposed wireless implantable recording device was tested in vitro using real icEEG signals from two patients with refractory epilepsy. The wirelessly recorded signals were compared to the original signals recorded using wired-connection, and measured normalized root-mean square deviation was under 2%.
Westhall, Erik; Rossetti, Andrea O.; van Rootselaar, Anne-Fleur; Wesenberg Kjaer, Troels; Horn, Janneke; Ullén, Susann; Friberg, Hans; Nielsen, Niklas; Rosén, Ingmar; Åneman, Anders; Erlinge, David; Gasche, Yvan; Hassager, Christian; Hovdenes, Jan; Kjaergaard, Jesper; Kuiper, Michael; Pellis, Tommaso; Stammet, Pascal; Wanscher, Michael; Wetterslev, Jørn; Wise, Matt P.; Cronberg, Tobias; Saxena, Manoj; Miller, Jennene; Inskip, Deborah; Macken, Lewis; Finfer, Simon; Eatough, Noel; Hammond, Naomi; Bass, Frances; Yarad, Elizabeth; O'Connor, Anne; Bird, Simon; Jewell, Timothy; Davies, Gareth; Ng, Karl; Coward, Sharon; Stewart, Antony; Micallef, Sharon; Parker, Sharyn; Cortado, Dennis; Gould, Ann; Harward, Meg; Thompson, Kelly; Glass, Parisa; Myburgh, John; Smid, Ondrej; Belholavek, Jan; Juffermans, Nicole P.; Boerma, EC
To identify reliable predictors of outcome in comatose patients after cardiac arrest using a single routine EEG and standardized interpretation according to the terminology proposed by the American Clinical Neurophysiology Society. In this cohort study, 4 EEG specialists, blinded to outcome,
Dyrholm, Mads; Makeig, Scott; Hansen, Lars Kai
in the convolutive model can be correctly detected using Bayesian model selection. We demonstrate a framework for deconvolving an EEG ICA subspace. Initial results suggest that in some cases convolutive mixing may be a more realistic model for EEG signals than the instantaneous ICA model....
Bell, Martha Ann; Cuevas, Kimberly
Developmental research is enhanced by use of multiple methodologies for examining psychological processes. The electroencephalogram (EEG) is an efficient and relatively inexpensive method for the study of developmental changes in brain-behavior relations. In this review, we highlight some of the challenges for using EEG in cognitive development…
Roth, B.; Nevsimalova, S.; Kvicala, V.
The results were compared of electroencephalography (EEG) and computerized tomography (CT) examinations of 250 patients with different brain affections. In intracranial expansive processes the pre-operative CT findings were positive in 100% cases, the EEG findings in 89.7% of cases. In severe traumatic affections the EEG and CT findings were positive in all cases, in mild injuries and post-traumatic conditions the EEG findings were more frequently positive than the CT. In focal and diffuse vascular affections the EEG and CT findings were consistent, in transitory ischemic conditions the EEG findings were more frequently positive. In inflammatory cerebral affections and in paroxymal diseases the EEG findings were positive more frequently than the CT. The same applies for demyelinating and degenerative affections. Findings of other authors were confirmed to the effect that CT very reliably reveals morphological changes in cerebral tissue while EEG records the functional state of the central nervous system and its changes. The two methods are complementary. (author)
Ma, Zhanyu; Tan, Zheng-Hua; Prasad, Swati
Classification of the Electroencephalogram (EEG) signal is a challengeable task in the brain-computer interface systems. The marginalized discrete wavelet transform (mDWT) coefficients extracted from the EEG signals have been frequently used in researches since they reveal features related...
Engedal, Knut; Snaedal, Jon; Hoegh, Peter
BACKGROUND/AIM: The aim of this study was to examine the discriminatory power of quantitative EEG (qEEG) applying the statistical pattern recognition (SPR) method to separate Alzheimer's disease (AD) patients from elderly individuals without dementia and from other dementia patients. METHODS...
Kropveld, D.; Chamuleau, R. A.; Popken, R. J.; Smith, J.
The experimental setup, including instrumentation and software packaging, is described for the use of a minicomputer as an on-line analyzing system of the EEG in rats. Complete fast Fourier transformation of the EEG sampled in 15 episodes of 10 s each is plotted out within 7 min after the start of
Kendirli, Mustafa Tansel; Aparci, Mustafa; Kendirli, Nurten; Tekeli, Hakan; Karaoglan, Mustafa; Senol, Mehmet Guney; Togrol, Erdem
Arrhythmia is not uncommon in the etiology of syncope which mimics epilepsy. Data about the epilepsy induced vagal tonus abnormalities have being increasingly reported. So we aimed to evaluate what a neurologist may gain by a simultaneous electrocardiogram (ECG) and electroencephalogram (EEG) recording in the patients who underwent EEG testing due to prediagnosis of epilepsy. We retrospectively evaluated and detected ECG abnormalities in 68 (18%) of 376 patients who underwent EEG testing. A minimum of 20 of minutes artifact-free recording were required for each patient. Standard 1-channel ECG was simultaneously recorded in conjunction with the EEG. In all, 28% of females and 14% of males had ECG abnormalities. Females (mean age 49 years, range 18-88 years) were older compared with the male group (mean age 28 years, range 16-83 years). Atrial fibrillation was more frequent in female group whereas bradycardia and respiratory sinus arrhythmia was higher in male group. One case had been detected a critical asystole indicating sick sinus syndrome in the female group and treated with a pacemaker implantation in the following period. Simultaneous ECG recording in conjunction with EEG testing is a clinical prerequisite to detect and to clarify the coexisting ECG and EEG abnormalities and their clinical relevance. Potentially rare lethal causes of syncope that mimic seizure or those that could cause resistance to antiepileptic therapy could effectively be distinguished by detecting ECG abnormalities coinciding with the signs and abnormalities during EEG recording. © EEG and Clinical Neuroscience Society (ECNS) 2014.
and decrease with increasing depth of anaesthesia. Spectral en- tropy yields two scales: Response Entropy (RE), ranging between. 0 to100, is an amalgam of EEG and frontal muscle activity while. State Entropy (SE), consisting mainly of EEG activity in a lower frequency band, ranges from 0 to 91.2 Initial reports have pro-.
Background Although it has been considered that sedation in children undergoing EEG tests is effective and safe and complications are infrequent, occasionally adverse sedation-related events are presented. Objective The aim of this work was to determine if it is possible to carry out EEG in children up to 4 years old ...
Zhang, Cheng; Lv, Jun; Zhou, Junhong; Su, Li; Feng, Liping; Ma, Jing; Wang, Guangfa; Zhang, Jue
Continuous positive airway pressure (CPAP) is currently the most effective treatment method for obstructive sleep apnea syndrome (OSAS). The purpose of this study was to compare the sleep electroencephalogram (EEG) changes before and after the application of CPAP to OSAS patients. A retrospective study was conducted and 45 sequential patients who received both polysomnography (PSG) and CPAP titration were included. The raw data of sleep EEG were extracted and analyzed by engineers using two main factors: fractal dimension (FD) and the zero-crossing rate of detrended FD (zDFD). FD was an effective indicator reflecting the EEG complexity and zDFD was useful to reflect the variability of the EEG complexity. The FD and zDFD indexes of sleep EEG of 45 OSAS patients before and after CPAP titration were analyzed. The age of 45 OSAS patients was 52.7 ± 5.6 years old and the patients include 12 females and 33 males. After CPAP treatment, FD of EEG in non-rapid eye movement (NREM) sleep decreased significantly (P CPAP therapy (P CPAP therapy had a significant influence on sleep EEG in patients with OSAHS, which lead to a more stable EEG pattern. This may be one of the mechanisms that CPAP could improve sleep quality and brain function of OSAS patients.
An unanticipated cardiac arrest and unusual post-resuscitation psycho-behavioural phenomena/near death experience in a patient with pregnancy induced hypertension and twin pregnancy undergoing elective lower segment caesarean section
Mridul M Panditrao
Full Text Available A case report of a primigravida, who was admitted with severe pregnancy induced hypertension (BP 160/122 mmHg and twin pregnancy, is presented here. Antihypertensive therapy was initiated. Elective LSCS under general anaesthesia was planned. After the birth of both the babies, intramyometrial injections of Carboprost and Pitocin were administered. Immediately, she suffered cardiac arrest. Cardio pulmonary resucitation (CPR was started and within 3 minutes, she was successfully resuscitated. The patient initially showed peculiar psychological changes and with passage of time, certain psycho-behavioural patterns emerged which could be attributed to near death experiences, as described in this case report.
Soto Ares, G.; Hamon-Kerautret, M.; Leclerc, X.; Pruvo, J.P.; Houlette, C.; Godefroy, O.
We report unusual MRI patterns in patients with grey matter heterotopia. Standard T1- and T2-weighted spin-echo and inversion-recovery sequences were used in 22 patients presenting with seizures or developmental delay. The images were reviewed for signal change surrounding white matter and for atypical size, morphology or topography. We found 10 cases of subependymal heterotopias 11 of focal subcortical heterotopia and of diffuse subcortical heterotopia. On clinical or MRI grounds, 8 cases were considered unusual: 2 of the subependymal type, 2 of focal subcortical heterotopia with white matter abnormalities, 2 of focal subcortical heterotopia with no clinicoradiological correlation 1 of extensive hemispheric subcortical heterotopia and 1 of diffuse subcortical heterotopia confined to the frontal lobe. The classical classification of heterotopia enables easy radiological diagnosis even in cases with unusual patterns. In some cases, heterogeneity and high signal in surrounding white matter can be found. Cortical dysplasia is the most frequent associated malformation. (orig.)
Ellis, D.H.; Craig, T.; Craig, E.; Postupalsky, S.; LaRue, C.T.; Nelson, R.W.; Anderson, D.W.; Henny, C.J.; Watson, J.; Millsap, B.A.; Dawson, J.W.; Cole, K.L.; Martin, E.M.; Margalida, A.; Kung, P.
From surveys in many countries, we report raptors using unusual nesting materials (e.g., paper money, rags, metal, antlers, and large bones) and unusual nesting situations. For example, we documented nests of Steppe Eagles Aquila nipalensis and Upland Buzzards Buteo hemilasius on the ground beside well-traveled roads, Saker Falcon Falco cherrug eyries in attics and a cistern, and Osprey Pandion haliaetus nests on the masts of boats and on a suspended automobile. Other records include a Golden Eagle A. chrysaetos nest 7.0 m in height, believed to be the tallest nest ever described, and, for the same species, we report nesting in rudimentary nests. Some nest sites are within a few meters of known predators or competitors. These unusual observations may be important in revealing the plasticity of a species' behavioral repertoire. ?? 2009 The Raptor Research Foundation, Inc.
Beniczky, Sandor; H, Aurlien,; JC, Brøgger,
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...... 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....... 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....
Juan, Elsa; Kaplan, Peter W; Oddo, Mauro; Rossetti, Andrea O
Postanoxic coma after cardiac arrest is one of the most serious acute cerebral conditions and a frequent cause of admission to critical care units. Given substantial improvement of outcome over the recent years, a reliable and timely assessment of clinical evolution and prognosis is essential in this context, but may be challenging. In addition to the classic neurologic examination, EEG is increasingly emerging as an important tool to assess cerebral functions noninvasively. Although targeted temperature management and related sedation may delay clinical assessment, EEG provides accurate prognostic information in the early phase of coma. Here, the most frequently encountered EEG patterns in postanoxic coma are summarized and their relations with outcome prediction are discussed. This article also addresses the influence of targeted temperature management on brain signals and the implication of the evolution of EEG patterns over time. Finally, the article ends with a view of the future prospects for EEG in postanoxic management and prognostication.
Full Text Available We describe the EEG findings from an ex-preterm neonate at term equivalent age who presented with intermittent but prolonged apneic episodes which were presumed to be seizures. A total of 8 apneic episodes were captured (duration 23–376 seconds during EEG monitoring. The baseline EEG activity was appropriate for corrected gestational age and no electrographic seizure activity was recorded. The average baseline heart rate was 168 beats per minute (bpm and the baseline oxygen saturation level was in the mid-nineties. Periods of complete EEG suppression lasting 68 and 179 seconds, respectively, were recorded during 2 of these 8 apneic episodes. Both episodes were accompanied by bradycardia less than 70 bpm and oxygen saturation levels of less than 20%. Short but severe episodes of apnea can cause complete EEG suppression in the neonate.
Coan, James A; Allen, John J B
Frontal EEG asymmetry appears to serve as (1) an individual difference variable related to emotional responding and emotional disorders, and (2) a state-dependent concomitant of emotional responding. Such findings, highlighted in this review, suggest that frontal EEG asymmetry may serve as both a moderator and a mediator of emotion- and motivation-related constructs. Unequivocal evidence supporting frontal EEG asymmetry as a moderator and/or mediator of emotion is lacking, as insufficient attention has been given to analyzing the frontal EEG asymmetries in terms of moderators and mediators. The present report reviews the frontal EEG asymmetry literature from the framework of moderators and mediators, and overviews data analytic strategies that would support claims of moderation and mediation.
Sfondouris, John L; Quebedeaux, Tabitha M; Holdgraf, Chris; Musto, Alberto E
Epileptogenesis is a dynamic process producing increased seizure susceptibility. Electroencephalography (EEG) data provides information critical in understanding the evolution of epileptiform changes throughout epileptic foci. We designed an algorithm to facilitate efficient large-scale EEG analysis via linked automation of multiple data processing steps. Using EEG recordings obtained from electrical stimulation studies, the following steps of EEG analysis were automated: (1) alignment and isolation of pre- and post-stimulation intervals, (2) generation of user-defined band frequency waveforms, (3) spike-sorting, (4) quantification of spike and burst data and (5) power spectral density analysis. This algorithm allows for quicker, more efficient EEG analysis. Copyright © 2011 Elsevier Ltd. All rights reserved.
Full Text Available AbstractPre-implant disease is an inflammatory process, which can affect the surrounding tissues of a functional Osseointegrated implant that is usually as a result of a disequilibrium between the micro-flora and the body defense system.This case reports a 57 years old male with unusual bone loss around dental implants.This was an unusual case of peri-implantitis which occurred only in the implants on one side of the mouth although they all were unloaded implants.
Rodriguez, E.; Pombo, F.; Cao, I.; Fernandez, R.; Riba da, M.
The purpose of this study is to present selected computed tomography (CT) images showing unusual causes of obstructive jaundice. We reviewed retrospectively the Ct findings of obstructive jaundice in 227 patients. The most common causes of biliary obstruction were adenocarcinoma of the pancreatic head (n=77) and cholangiocarcinoma (n=65). In 13 cases (5.7%), the etiology of obstructive jaundice was unusual or exceptional: tuberculous adenitis (n=3), obstruction of afferent loop (n=2)signet ring cell adenocarcinoma (n=3); in duodenum, gallbladder and papilla of Water), Mirizzi syndrome (n=1), adenocarcinoma of the hepatic flexure (n=1), choledochal cyst (n=1) and pancreatic lymphoma (n=1). (Author) 13 refs
Frederic von Wegner
Full Text Available We present an open-source Python package to compute information-theoretical quantities for electroencephalographic data. Electroencephalography (EEG measures the electrical potential generated by the cerebral cortex and the set of spatial patterns projected by the brain's electrical potential on the scalp surface can be clustered into a set of representative maps called EEG microstates. Microstate time series are obtained by competitively fitting the microstate maps back into the EEG data set, i.e., by substituting the EEG data at a given time with the label of the microstate that has the highest similarity with the actual EEG topography. As microstate sequences consist of non-metric random variables, e.g., the letters A–D, we recently introduced information-theoretical measures to quantify these time series. In wakeful resting state EEG recordings, we found new characteristics of microstate sequences such as periodicities related to EEG frequency bands. The algorithms used are here provided as an open-source package and their use is explained in a tutorial style. The package is self-contained and the programming style is procedural, focusing on code intelligibility and easy portability. Using a sample EEG file, we demonstrate how to perform EEG microstate segmentation using the modified K-means approach, and how to compute and visualize the recently introduced information-theoretical tests and quantities. The time-lagged mutual information function is derived as a discrete symbolic alternative to the autocorrelation function for metric time series and confidence intervals are computed from Markov chain surrogate data. The software package provides an open-source extension to the existing implementations of the microstate transform and is specifically designed to analyze resting state EEG recordings.
Wu, Shun Chi; Swindlehurst, A Lee
In this paper, we propose novel matching pursuit (MP)-based algorithms for EEG/MEG dipole source localization and parameter estimation for multiple measurement vectors with constant sparsity. The algorithms combine the ideas of MP for sparse signal recovery and source deflation, as employed in estimation via alternating projections. The source-deflated matching pursuit (SDMP) approach mitigates the problem of residual interference inherent in sequential MP-based methods or recursively applied (RAP)-MUSIC. Furthermore, unlike prior methods based on alternating projection, SDMP allows one to efficiently estimate the dipole orientation in addition to its location. Simulations show that the proposed algorithms outperform existing techniques under various conditions, including those with highly correlated sources. Results using real EEG data from auditory experiments are also presented to illustrate the performance of these algorithms.
Full Text Available Abstract Background By enabling individuals to self-regulate their brainwave activity in the field of optimal performance in healthy individuals, neurofeedback has been found to improve cognitive and artistic performance. Here we assessed whether two distinct EEG neurofeedback protocols could develop surgical skill, given the important role this skill plays in medicine. Results National Health Service trainee ophthalmic microsurgeons (N = 20 were randomly assigned to either Sensory Motor Rhythm-Theta (SMR or Alpha-Theta (AT groups, a randomized subset of which were also part of a wait-list 'no-treatment' control group (N = 8. Neurofeedback groups received eight 30-minute sessions of EEG training. Pre-post assessment included a skills lab surgical procedure with timed measures and expert ratings from video-recordings by consultant surgeons, together with state/trait anxiety self-reports. SMR training demonstrated advantages absent in the control group, with improvements in surgical skill according to 1 the expert ratings: overall technique (d = 0.6, p Conclusion SMR-Theta neurofeedback training provided significant improvement in surgical technique whilst considerably reducing time on task by 26%. There was also evidence that AT training marginally reduced total surgery time, despite suboptimal training efficacies. Overall, the data set provides encouraging evidence of optimised learning of a complex medical specialty via neurofeedback training.
Kline, John P; Blackhart, Ginette C; Williams, William C
The opponent process theory of emotion [Solomon, R.L., and Corbit, J.D. (1974). An opponent-process theory of motivation: I. Temporal dynamics of affect. Psychological Review, 81, 119-143.] predicts a temporary reversal of emotional valence during the recovery from emotional stimulation. We hypothesized that this affective contrast would be apparent in asymmetrical activity patterns in the frontal lobes, and would be more apparent for left frontally active individuals. The present study tested this prediction by examining EEG asymmetries during and after blocked presentations of aversive pictures selected from the International Affective Picture System (IAPS). 12 neutral images, 12 aversive images, and 24 neutral images were presented in blocks. Participants who were right frontally active at baseline did not show changes in EEG asymmetry while viewing aversive slides or after cessation. Participants left frontally active at baseline, however, exhibited greater relative left frontal activity after aversive stimulation than before stimulation. Asymmetrical activity patterns in the frontal lobes may relate to affect regulatory processes, including contrasting opponent after-reactions to aversive stimuli.
Full Text Available This paper deals with the problem of relatively young type of hotel that is increasingly attracting the attention of the modern tourist. Unusual hotels are very interesting phenomenon, not only for tourists and hospitality professionals, but also for people who are (currently out of the tourist flows. These are facilities with untypical architectural design, non-standard equipped or with services that are not common in the hospitality industry. They often contribute to the attractiveness of the area in which they are located. However, business sustainability of unusual hotels, as well as any other hotel, depends on guests, i.e. number of overnight stays.We present the results of research conducted among tourists in Serbia. The main task is to examined whether tourists are interested in the potential developing of unusual hotels. If so, which subtypes of unusual hotel would be best suited for the territory of Serbia. In order to compare experiences and operating results, parallel survey was conducted among owners of unusual hotels around the world. The results suggest a conclusion - with a favourable investment climate, unusual hotels should have a future in Serbia.
Full Text Available Odontomas are the most common of the odontogenic tumors of the jaws, which are benign, slow growing, and nonaggressive. They are usually asymptomatic and found in routine dental radiographic examination. Odontomas are usually associated with tooth eruption disturbances. Eruption of odontoma in oral cavity is rare entity. Here we report a case of an unusual erupted compound odontoma.
Ruelle, A.; Pisani, R.; Andrioli, G.
The authors report a case of sphenoid sinus mucocele which exhibited unusual MRI features. However a review of the literature shows that these lesions may present with different MRI appearances probably related to the variability of the cyst content. Further series are needed for a better definition of the MRI behaviour of the lesions. (orig.)
Xanthogranulomatous endometritis is an unusual pathological entity mimicking endometrial carcinoma. This shows sheets of foamy histiocytes alongwith other inflammatory cells. We, hereby, report a case of 45 year multigravida female with irregular menstrual history, clinically diagnosed as carcinoma and ...
This podcast discusses a study about the probable unusual transmission of Zika Virus Infection from a scientist to his wife, published in the May 2011 issue of Emerging Infectious Diseases. Dr. Brian Foy, Associate Professor at Colorado State University, shares details of this event.
D'Souza, D.L.; Heinze, S.B.; Dowling, R.J.
Lung cancer is not commonly known to metastasise to the perirenal space, with only five such cases previously published. We present an unusual case of perirenal lung metastases manifesting as diffuse perinephric stranding which to our knowledge has not been described before Copyright (2006) Blackwell Publishing Asia Pty Ltd
Palmer, H; Weston, J T
All childhood deaths which occurred in New Mexico during 1974 and 1975 were reviewed. Nine fatal instances of abuse were identified representing the entire spectrum of physical abuse: neglect, abuse in a single episode of injury, repetitive abuse, or sexual abuse. Several cases are summarized. These are unusual either in the distribution of pathologic findings or in the problems encountered in court presentation.
A case report of a 57-year old woman who presented with signs and symptoms of intracranial mass. Computed tomographic (CT) and clinical features were unusual and suggestive of a parasaggital Meningioma. However an accurate diagnosis of a tuberculoma was made at surgery and histopathological examination.
Fialkov, M J; Robins, A H
A variant of the Capgras syndrome is described in a 43-year-old woman who had vitiligo and multinodular goitre. The unusual feature of the case was that the patient not only misidentified members of her own family but also claimed that she herself had been replaced by a double.
Sabir, Anas Ahmad; Sada, Kabiru; Yusuf, Bashir O.; Aliyu, Idris
Thyroid storm is a rare life-threatening emergency due to thyrotoxicosis. A 30-year-old female presented with restlessness, tachycardia and vomiting but with normothermia which is an unusual presentation. There is the need for clinicians to be aware of atypical clinical features that can make the diagnosis of thyroid storm difficult. PMID:27540465
It was relieved by lying flat. She had pre- viously been admitted to King Edward VIII Hospital in. May 1969 with a cough, chest and abdominal pain, ... foot and cranium may be the sites of skeletal involvement. Our case shows several unusual features. Sickle-cell anaemia and haemoglobinopathy were absent. Although.
K C Shah
Full Text Available Cutaneous manifestations are found in 60 to 70% cases of tuberous sclerosis and consist of adenoma sebaceum, periungual fibromatas, cafe au lait spots, shagreen patches and white macules. Our patient showed unusual skin manifestations like spotty pigmentation on the chest, back and abdomen and hyperkeratosis palmaris et plantaris.
Full Text Available The choice of different reference electrodes plays an important role in deciphering the functional meaning of electroencephalography (EEG signals. In recent years, the infinity zero reference using the reference electrode standard technique (REST has been increasingly applied, while the average reference (AR was generally advocated as the best available reference option in previous classical EEG studies. Here, we designed EEG experiments and performed a direct comparison between the influences of REST and AR on EEG-revealed brain activity features for three typical brain behavior states (eyes-closed, eyes-open and music-listening. The analysis results revealed the following observations: (1 there is no significant difference in the alpha-wave-blocking effect during the eyes-open state compared with the eyes-closed state for both REST and AR references; (2 there was clear frontal EEG asymmetry during the resting state, and the degree of lateralization under REST was higher than that under AR; (3 the global brain functional connectivity density (FCD and local FCD have higher values for REST than for AR under different behavior states; and (4 the value of the small-world network characteristic in the eyes-closed state is significantly (in full, alpha, beta and gamma frequency bands higher than that in the eyes-open state, and the small-world effect under the REST reference is higher than that under AR. In addition, the music-listening state has a higher small-world network effect than the eyes-closed state. The above results suggest that typical EEG features might be more clearly presented by applying the REST reference than by applying AR when using a 64-channel recording.
Lin, Chin-Teng; Chuang, Chun-Hsiang; Huang, Chih-Sheng; Tsai, Shu-Fang; Lu, Shao-Wei; Chen, Yen-Hsuan; Ko, Li-Wei
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.
Beniczky, Sándor; Aurlien, Harald; Brøgger, Jan C.
Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted in the se......Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted...... in the second, revised version of SCORE (Standardized Computer-based Organized Reporting of EEG), which is presented in this paper. The revised terminology was implemented in a software package (SCORE EEG), which was tested in clinical practice on 12,160 EEG recordings. Standardized terms implemented in SCORE....... In the end, the diagnostic significance is scored, using a standardized list of terms. SCORE has specific modules for scoring seizures (including seizure semiology and ictal EEG patterns), neonatal recordings (including features specific for this age group), and for Critical Care EEG Terminology. SCORE...
Singh, Yogesh; Singh, Jayvardhan; Sharma, Ratna; Talwar, Anjana
The EEG is considered as building block of functional signaling in the brain. The role of EEG oscillations in human information processing has been intensively investigated. To study the quantitative EEG correlates of short term memory load as assessed through Sternberg memory test. The study was conducted on 34 healthy male student volunteers. The intervention consisted of Sternberg memory test, which runs on a version of the Sternberg memory scanning paradigm software on a computer. Electroencephalography (EEG) was recorded from 19 scalp locations according to 10-20 international system of electrode placement. EEG signals were analyzed offline. To overcome the problems of fixed band system, individual alpha frequency (IAF) based frequency band selection method was adopted. The outcome measures were FFT transformed absolute powers in the six bands at 19 electrode positions. Sternberg memory test served as model of short term memory load. Correlation analysis of EEG during memory task was reflected as decreased absolute power in Upper alpha band in nearly all the electrode positions; increased power in Theta band at Fronto-Temporal region and Lower 1 alpha band at Fronto-Central region. Lower 2 alpha, Beta and Gamma band power remained unchanged. Short term memory load has distinct electroencephalographic correlates resembling the mentally stressed state. This is evident from decreased power in Upper alpha band (corresponding to Alpha band of traditional EEG system) which is representative band of relaxed mental state. Fronto-temporal Theta power changes may reflect the encoding and execution of memory task.
Full Text Available The fundamental nature of the brain's electrical activities recorded as electroencephalogram (EEG remains unknown. Linear stochastic models and spectral estimates are the most common methods for the analysis of EEG because of their robustness, simplicity of interpretation, and apparent association with rhythmic behavioral patterns in nature. In this paper, we extend the use of higher-order spectrum in order to indicate the hidden characteristics of EEG signals that simply do not arise from random processes. The higher-order spectrum is an extension Fourier spectrum that uses higher moments for spectral estimates. This essentially nullifies all Gaussian random effects, therefore, can reveal non-Gaussian and nonlinear characteristics in the complex patterns of EEG time series. The paper demonstrates the distinguishing features of bispectral analysis for chaotic systems, filtered noises, and normal background EEG activity. The bispectrum analysis detects nonlinear interactions; however, it does not quantify the coupling strength. The squared bicoherence in the nonredundant region has been estimated to demonstrate nonlinear coupling. The bicoherence values are minimal for white Gaussian noises (WGNs and filtered noises. Higher bicoherence values in chaotic time series and normal background EEG activities are indicative of nonlinear coupling in these systems. The paper shows utility of bispectral methods as an analytical tool in understanding neural process underlying human EEG patterns.
Grieder, Matthias; Koenig, Thomas; Kinoshita, Toshihiko; Utsunomiya, Keita; Wahlund, Lars-Olof; Dierks, Thomas; Nishida, Keiichiro
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.
Ying, Xiaoguo; Lin, Han; Hui, Guohua
Electroencephalogram (EEG) is the recording of electrical activity along the scalp. EEG measures voltage fluctuations generating from ionic current flows within the neurons of the brain. EEG signal is looked as one of the most important factors that will be focused in the next 20 years. In this paper, EEG signal discrimination based on non-linear bistable dynamical model was proposed. EEG signals were processed by non-linear bistable dynamical model, and features of EEG signals were characterized by coherence index. Experimental results showed that the proposed method could properly extract the features of different EEG signals.
Full Text Available Studies of visual aesthetic preference have shown that people without art training generally prefer representational paintings to abstract paintings. This, however, is not always the case: preferences can sometimes go against this usual tendency. We aimed to explore this issue, investigating the relationship between ‘unusual responses’ and reaction time in an aesthetic appreciation task. Results of a behavioural experiment confirmed the trend for laypeople to consider as beautiful mostly representational stimuli and as not beautiful mostly abstract ones (‘usual response’. Furthermore, when participants gave unusual responses, they needed longer time, especially when considering abstract stimuli as beautiful. We interpreted this longer time as greater involvement of the cognitive mastering and evaluation stages during the unusual responses. Results of an fMRI experiment indicated that the anterior cingulate, orbitofrontal cortex and insula were the main structures involved in this effect. We discuss the possible role of these areas in an aesthetic appreciation task.
Zachary B. Loris
Full Text Available Electrocorticographic (ECoG signals represent cortical electrical dipoles generated by synchronous local field potentials that result from simultaneous firing of neurons at distinct frequencies (brain waves. Since different brain waves correlate to different behavioral states, ECoG signals presents a novel strategy to detect complex behaviors. We developed a program, EEG Detection Analysis for Behavioral States (EEG-DABS that advances Fast Fourier Transforms through ECoG signals time series, separating it into (user defined frequency bands and normalizes them to reduce variability. EEG-DABS determines events if segments of an experimental ECoG record have significantly different power bands than a selected control pattern of EEG. Events are identified at every epoch and frequency band and then are displayed as output graphs by the program. Certain patterns of events correspond to specific behaviors. Once a predetermined pattern was selected for a behavioral state, EEG-DABS correctly identified the desired behavioral event. The selection of frequency band combinations for detection of the behavior affects accuracy of the method. All instances of certain behaviors, such as freezing, were correctly identified from the event patterns generated with EEG-DABS. Detecting behaviors is typically achieved by visually discerning unique animal phenotypes, a process that is time consuming, unreliable, and subjective. EEG-DABS removes variability by using defined parameters of EEG/ECoG for a desired behavior over chronic recordings. EEG-DABS presents a simple and automated approach to quantify different behavioral states from ECoG signals.
Full Text Available BACKGROUND Migraine is one of the common causes of headache in children. Migraine and epilepsy are both common episodic neurological disorders. The comorbidity of these two conditions is well known. Many researcher have pointed out that neuronal hyperexcitability is the initiating event for occurrence of migraine attack. The aim of the paper was to evaluate the EEG in children with migraine. MATERIALS AND METHODS We retrospectively analysed records of children who attended our paediatric outpatient department with diagnoses as suffering from migraine based on International Headache Society (IHS diagnostic criteria. Apart from detailed clinical history, EEG of every patient was collected and analysed. EEG was performed interictally at least 24 hours after the last episode of headache attack in all the cases. RESULTS 56 children (age range, 4-14 years constituted our study group. 64.3% children had migraine without aura (common type and in 23.2% cases had migraine with aura (classic type other were with migraine variants. Abnormal EEG was reported in 30.3% children. 17% of children with migraine without history of seizure had abnormal EEG. Sixty one percent of patients with aura had abnormal EEG. History of either febrile fits or afebrile fits was present in total 17.1% of cases. The type of paroxysmal discharges we came across was- a Sharp waves, b Spikes and c Spike and slow wave complexes. Abnormal paroxysmal sharp and spike-wave complexes (also called spike-and-slow-wave complexes were the most common EEG abnormality. CONCLUSION EEG abnormality was found in significant number of children with migraine both with and without history of seizure in our study. This indicates neuronal hyperexcitability during episodes of migraine. So, EEG should be considered in patients with clinical diagnoses of migraine to exclude association of any seizure activity.
Phneah, Swee Wu; Nisar, Humaira
The aim of this paper is to develop a preliminary neurofeedback system to improve the mood of the subjects using audio signals by enhancing their alpha brainwaves. Assessment of the effect of music on the human subjects is performed using three methods; subjective assessment of mood with the help of a questionnaire, the effect on brain by analysing EEG signals, and the effect on body by physiological assessment. In this study, two experiments have been designed. The first experiment was to determine the short-term effect of music on soothing human subjects, whereas the second experiment was to determine its long-term effect. Two types of music were used in the first experiment, the favourite music selected by the participants and a relaxing music with alpha wave binaural beats. The research findings showed that the relaxing music has a better soothing effect on the participants psychologically and physiologically. However, the one-way analysis of variance (ANOVA) results showed that the short-term soothing effect of both favourite music and relaxing music was not significant in changing the mean alpha absolute power and mean physiological measures (blood pressure and heart rate) at the significance level of 0.05. The second experiment was somewhat similar to an alpha neurofeedback training whereby the participants trained their brains to produce more alpha brainwaves by listening to the relaxing music with alpha wave binaural beats for a duration of 30 min daily. The results showed that the relaxing music has a long-term psychological and physiological effect on soothing the participants, as can be observed from the increase in alpha power and decrease in physiological measures after each session of training. The training was found to be effective in increasing the alpha power significantly [F(2,12) = 11.5458 and p = 0.0016], but no significant reduction in physiological measures was observed at the significance level of 0.05.
1 AWARD NUMBER: W81XWH-14-1-0582 TITLE: Brain Functional Connectivity in MS: An EEG -NIRS Study PRINCIPAL INVESTIGATOR: Heather Wishart...Functional Connectivity in MS: An EEG -NIRS Study 5b. GRANT NUMBER W81XWH-14-1-0582 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER Heather...electrical ( EEG ) and blood volume and blood oxygen-based (NIRS and fMRI) signals, and to use the results to help optimize blood oxygen level
Nguyen, Hoang-Anh T.; Musson, John; Li, Jiang; McKenzie, Frederick; Zhang, Guangfan; Xu, Roger; Richey, Carl; Schnell, Tom
!n this paper we developed a wavelet neural network. (WNN) algorithm for Electroencephalogram (EEG) artifact removal without electrooculographic (EOG) recordings. The algorithm combines the universal approximation characteristics of neural network and the time/frequency property of wavelet. We. compared the WNN algorithm with .the ICA technique ,and a wavelet thresholding method, which was realized by using the Stein's unbiased risk estimate (SURE) with an adaptive gradient-based optimal threshold. Experimental results on a driving test data set show that WNN can remove EEG artifacts effectively without diminishing useful EEG information even for very noisy data.
EEG Clearing Office strengthened by EEG 2012. Alternative dispute resolution in the renewable energies industry; Aufwertung der Clearingstelle EEG durch das EEG 2012. Alternative Dispute Resolution im Bereich der Erneuerbaren Energien
Chatzinerantzis, Alexandros; Fach, Martin [Linklaters LLP, Frankfurt am Main (Germany). Praxisgruppe Litigation and Arbitration
The EEG Clearing Office is a special arbitration forum for the purpose of facilitating quick and inexpensive out-of-court dispute resolutions and resolving cases of legal uncertainty in connection with the regulations of the EEG (Renewable Energy Law). The Clearing Office has developed dynamically over the past years, as the numbers of newly registered potential and ongoing procedures impressively show. In the 2012 amendment to the EEG the legislature has fundamentally revised and substantially widened the legal basis for the work of the Clearing Office. This provides the motivation for presenting the Clearing Office and its procedural rules in the following article.
Bach Justesen, Anders; Eskelund Johansen, Ann Berit; Martinussen, Noomi Ida
Objective To investigate the diagnostic added value of supplementing the 10–20 EEG array with six electrodes in the inferior temporal chain. Methods EEGs were recorded with 25 electrodes: 19 positions of the 10–20 system, and six additional electrodes in the inferior temporal chain (F9/10, T9/10, P...... in the inferior chain) and 6% (only seen at the inferior chain). Conclusions Adding six electrodes in the inferior temporal electrode chain to the 10–20 array improves the localization and identification of EEG abnormalities, especially those located in the temporal region. Significance Our results suggest...
The advent of digital EEG has provided greater flexibility and more opportunities in data analysis to optimize the diagnostic yield. Changing the filter settings, sensitivity, montages, and time-base are possible rational manipulations to achieve this goal. The options to use polygraphy, video, and quantification are additional useful features. Aliasing and loss of data are potential pitfalls in the use of digital EEG. This review illustrates some common clinical scenarios where rational manipulations can enhance the diagnostic EEG yield and potential pitfalls in the process.
Koopman, D. C.
A study was undertaken to identify and clarify examples of unusual rheological behavior in Defense Waste Processing Facility (DWPF) simulant slurry samples. Identification was accomplished by reviewing sludge, Sludge Receipt and Adjustment Tank (SRAT) product, and Slurry Mix Evaporator (SME) product simulant rheological results from the prior year. Clarification of unusual rheological behavior was achieved by developing and implementing new measurement techniques. Development of these new methods is covered in a separate report, WSRC-TR-2004-00334. This report includes a review of recent literature on unusual rheological behavior, followed by a summary of the rheological measurement results obtained on a set of unusual simulant samples. Shifts in rheological behavior of slurries as the wt. % total solids changed have been observed in numerous systems. The main finding of the experimental work was that the various unusual DWPF simulant slurry samples exhibit some degree of time dependent behavior. When a given shear rate is applied to a sample, the apparent viscosity of the slurry changes with time rather than remaining constant. These unusual simulant samples are more rheologically complex than Newtonian liquids or more simple slurries, neither of which shows significant time dependence. The study concludes that the unusual rheological behavior that has been observed is being caused by time dependent rheological properties in the slurries being measured. Most of the changes are due to the effect of time under shear, but SB3 SME products were also changing properties while stored in sample bottles. The most likely source of this shear-related time dependence for sludge is in the simulant preparation. More than a single source of time dependence was inferred for the simulant SME product slurries based on the range of phenomena observed. Rheological property changes were observed on the time-scale of a single measurement (minutes) as well as on a time scale of hours
Chen, Xun; Liu, Aiping; Peng, Hu; Ward, Rabab K.
Electroencephalogram (EEG) recordings are often contaminated with muscular artifacts that strongly obscure the EEG signals and complicates their analysis. For the conventional case, where the EEG recordings are obtained simultaneously over many EEG channels, there exists a considerable range of methods for removing muscular artifacts. In recent years, there has been an increasing trend to use EEG information in ambulatory healthcare and related physiological signal monitoring systems. For pra...
Jensen, Camilla Birgitte Falk; Petersen, Michael Kai; Larsen, Jakob Eg
susceptible to noise if captured in a mobile context. Hypothesizing that retrieval of emotional responses in mobile usage scenarios could be enhanced through spatial filtering, we compare a standard EEG electrode based analysis against an approach based on independent component analysis (ICA). By clustering...... or unpleasant images; early posterior negativity (EPN) and late positive potential (LPP). Recent studies suggest that several time course components may be modulated by emotional content in images or text. However these neural signatures are characterized by small voltage changes that would be highly...... by emotional content. We propose that similar approaches to spatial filtering might allow us to retrieve more robust signals in real life mobile usage scenarios, and potentially facilitate design of cognitive interfaces that adapt the selection of media to our emotional responses....
Hosseini, Mohammad-Parsa; Pompili, Dario; Elisevich, Kost; Soltanian-Zadeh, Hamid
Real-time detection of seizure activity in epilepsy patients is critical in averting seizure activity and improving patients' quality of life. Accurate evaluation, presurgical assessment, seizure prevention, and emergency alerts all depend on the rapid detection of seizure onset. A new method of feature selection and classification for rapid and precise seizure detection is discussed wherein informative components of electroencephalogram (EEG)-derived data are extracted and an automatic method is presented using infinite independent component analysis (I-ICA) to select independent features. The feature space is divided into subspaces via random selection and multichannel support vector machines (SVMs) are used to classify these subspaces. The result of each classifier is then combined by majority voting to establish the final output. In addition, a random subspace ensemble using a combination of SVM, multilayer perceptron (MLP) neural network and an extended k-nearest neighbors (k-NN), called extended nearest neighbor (ENN), is developed for the EEG and electrocorticography (ECoG) big data problem. To evaluate the solution, a benchmark ECoG of eight patients with temporal and extratemporal epilepsy was implemented in a distributed computing framework as a multitier cloud-computing architecture. Using leave-one-out cross-validation, the accuracy, sensitivity, specificity, and both false positive and false negative ratios of the proposed method were found to be 0.97, 0.98, 0.96, 0.04, and 0.02, respectively. Application of the solution to cases under investigation with ECoG has also been effected to demonstrate its utility. Copyright © 2017 Elsevier B.V. All rights reserved.
Kaida, Kosuke; Takahashi, Masaya; Akerstedt, Torbjörn; Nakata, Akinori; Otsuka, Yasumasa; Haratani, Takashi; Fukasawa, Kenji
The Karolinska sleepiness scale (KSS) is frequently used for evaluating subjective sleepiness. The main aim of the present study was to investigate the validity and reliability of the KSS with electroencephalographic, behavioral and other subjective indicators of sleepiness. Participants were 16 healthy females aged 33-43 (38.1+/-2.68) years. The experiment involved 8 measurement sessions per day for 3 consecutive days. Each session contained the psychomotor vigilance task (PVT), the Karolinska drowsiness test (KDT-EEG alpha & theta power), the alpha attenuation test (AAT-alpha power ratio open/closed eyes) and the KSS. Median reaction time, number of lapses, alpha and theta power density and the alpha attenuation coefficients (AAC) showed highly significant increase with increasing KSS. The same variables were also significantly correlated with KSS, with a mean value for lapses (r=0.56). The KSS was closely related to EEG and behavioral variables, indicating a high validity in measuring sleepiness. KSS ratings may be a useful proxy for EEG or behavioral indicators of sleepiness.
Im, Chang-Hwan; Jung, Hyun-Kyo; Fujimaki, Norio
This paper proposes an alternative approach to enhance localization accuracy of MEG and EEG focal sources. The proposed approach assumes anatomically constrained spatio-temporal dipoles, initial positions of which are estimated from local peak positions of distributed sources obtained from a pre-execution of distributed source reconstruction. The positions of the dipoles are then adjusted on the cortical surface using a novel updating scheme named cortical surface scanning. The proposed approach has many advantages over the conventional ones: (1) as the cortical surface scanning algorithm uses spatio-temporal dipoles, it is robust with respect to noise; (2) it requires no a priori information on the numbers and initial locations of the activations; (3) as the locations of dipoles are restricted only on a tessellated cortical surface, it is physiologically more plausible than the conventional ECD model. To verify the proposed approach, it was applied to several realistic MEG/EEG simulations and practical experiments. From the several case studies, it is concluded that the anatomically constrained dipole adjustment (ANACONDA) approach will be a very promising technique to enhance accuracy of focal source localization which is essential in many clinical and neurological applications of MEG and EEG.
Im, Chang-Hwan; Jung, Hyun-Kyo; Fujimaki, Norio
This paper proposes an alternative approach to enhance localization accuracy of MEG and EEG focal sources. The proposed approach assumes anatomically constrained spatio-temporal dipoles, initial positions of which are estimated from local peak positions of distributed sources obtained from a pre-execution of distributed source reconstruction. The positions of the dipoles are then adjusted on the cortical surface using a novel updating scheme named cortical surface scanning. The proposed approach has many advantages over the conventional ones: (1) as the cortical surface scanning algorithm uses spatio-temporal dipoles, it is robust with respect to noise; (2) it requires no a priori information on the numbers and initial locations of the activations; (3) as the locations of dipoles are restricted only on a tessellated cortical surface, it is physiologically more plausible than the conventional ECD model. To verify the proposed approach, it was applied to several realistic MEG/EEG simulations and practical experiments. From the several case studies, it is concluded that the anatomically constrained dipole adjustment (ANACONDA) approach will be a very promising technique to enhance accuracy of focal source localization which is essential in many clinical and neurological applications of MEG and EEG
Ji, Hongfei; Li, Jie; Lu, Rongrong; Gu, Rong; Cao, Lei; Gong, Xiaoliang
Electroencephalogram- (EEG-) based brain-computer interface (BCI) systems usually utilize one type of changes in the dynamics of brain oscillations for control, such as event-related desynchronization/synchronization (ERD/ERS), steady state visual evoked potential (SSVEP), and P300 evoked potentials. There is a recent trend to detect more than one of these signals in one system to create a hybrid BCI. However, in this case, EEG data were always divided into groups and analyzed by the separate processing procedures. As a result, the interactive effects were ignored when different types of BCI tasks were executed simultaneously. In this work, we propose an improved tensor based multiclass multimodal scheme especially for hybrid BCI, in which EEG signals are denoted as multiway tensors, a nonredundant rank-one tensor decomposition model is proposed to obtain nonredundant tensor components, a weighted fisher criterion is designed to select multimodal discriminative patterns without ignoring the interactive effects, and support vector machine (SVM) is extended to multiclass classification. Experiment results suggest that the proposed scheme can not only identify the different changes in the dynamics of brain oscillations induced by different types of tasks but also capture the interactive effects of simultaneous tasks properly. Therefore, it has great potential use for hybrid BCI.
Alessio Paolo Buccino
Full Text Available Non-invasive Brain-Computer Interfaces (BCI have demonstrated great promise for neuroprosthetics and assistive devices. Here we aim to investigate methods to combine Electroencephalography (EEG and functional Near-Infrared Spectroscopy (fNIRS in an asynchronous Sensory Motor rhythm (SMR-based BCI. We attempted to classify 4 different executed movements, namely, Right-Arm-Left-Arm-Right-Hand-Left-Hand tasks. Previous studies demonstrated the benefit of EEG-fNIRS combination. However, since normally fNIRS hemodynamic response shows a long delay, we investigated new features, involving slope indicators, in order to immediately detect changes in the signals. Moreover, Common Spatial Patterns (CSPs have been applied to both EEG and fNIRS signals. 15 healthy subjects took part in the experiments and since 25 trials per class were available, CSPs have been regularized with information from the entire population of participants and optimized using genetic algorithms. The different features have been compared in terms of performance and the dynamic accuracy over trials shows that the introduced methods diminish the fNIRS delay in the detection of changes.
Dan'ko, S G; Boĭtsova, Iu A; Kachalova, L M
Group 1 (N = 30) and group 2 (N = 22) of healthy volunteers participated in the experiment. EEG registration took place while the examinees were in the resting states: with closed eyes; with opened eyes; with opened eyes and being under exposure to TV channel noises (white noise). Group 1 had also to fulfill a task to count randomly appearing symbols on a screen and group 2 had to fulfill a task to find an image in the noises. Averaged values of EEG power in each of the derivations in each of the derivations were calculated for an every examinee and for each of the states. The estimations were done in delta, theta, alpha1, alpha2, beta1, beta2, gamma frequency bands. The received results demonstrate that exposure to unstructured non-informative video noise can lead to significant changes of EEG power in a variety of frequency bands which are most prominent in the band alpha2. The changes are topically widespread, reflecting systemic changes in corresponding brain mechanisms, but are much less intensive if compared to changes between resting states with opened and closed eyes.
Melinscak, Filip; Montesano, Luis; Minguez, Javier
Objective. Attention is known to modulate the plasticity of the motor cortex, and plasticity is crucial for recovery in motor rehabilitation. This study addresses the possibility of using an EEG-based brain-computer interface (BCI) to detect kinesthetic attention to movement. Approach. A novel experiment emulating physical rehabilitation was designed to study kinesthetic attention. The protocol involved continuous mobilization of lower limbs during which participants reported levels of attention to movement—from focused kinesthetic attention to mind wandering. For this protocol an asynchronous BCI detector of kinesthetic attention and deliberate mind wandering was designed. Main results. EEG analysis showed significant differences in theta, alpha, and beta bands, related to the attentional state. These changes were further pinpointed to bands relative to the frequency of the individual alpha peak. The accuracy of the designed BCI ranged between 60.8% and 68.4% (significantly above chance level), depending on the used analysis window length, i.e. acceptable detection delay. Significance. This study shows it is possible to use self-reporting to study attention-related changes in EEG during continuous mobilization. Such a protocol is used to develop an asynchronous BCI detector of kinesthetic attention, with potential applications to motor rehabilitation.
Adam, Asrul; Ibrahim, Zuwairie; Mokhtar, Norrima; Shapiai, Mohd Ibrahim; Mubin, Marizan; Saad, Ismail
In the existing electroencephalogram (EEG) signals peak classification research, the existing models, such as Dumpala, Acir, Liu, and Dingle peak models, employ different set of features. However, all these models may not be able to offer good performance for various applications and it is found to be problem dependent. Therefore, the objective of this study is to combine all the associated features from the existing models before selecting the best combination of features. A new optimization algorithm, namely as angle modulated simulated Kalman filter (AMSKF) will be employed as feature selector. Also, the neural network random weight method is utilized in the proposed AMSKF technique as a classifier. In the conducted experiment, 11,781 samples of peak candidate are employed in this study for the validation purpose. The samples are collected from three different peak event-related EEG signals of 30 healthy subjects; (1) single eye blink, (2) double eye blink, and (3) eye movement signals. The experimental results have shown that the proposed AMSKF feature selector is able to find the best combination of features and performs at par with the existing related studies of epileptic EEG events classification.
Cona, F; Zavaglia, M; Massimini, M; Rosanova, M; Ursino, M
Knowledge of cortical rhythms represents an important aspect of modern neuroscience, to understand how the brain realizes its functions. Recent data suggest that different regions in the brain may exhibit distinct electroencephalogram (EEG) rhythms when perturbed by Transcranial Magnetic Stimulation (TMS) and that these rhythms can change due to the connectivity among regions. In this context, in silico simulations may help the validation of these hypotheses that would be difficult to be verified in vivo. Neural mass models can be very useful to simulate specific aspects of electrical brain activity and, above all, to analyze and identify the overall frequency content of EEG in a cortical region of interest (ROI). In this work we implemented a model of connectivity among cortical regions to fit the impulse responses in three ROIs recorded during a series of TMS/EEG experiments performed in five subjects and using three different impulse intensities. In particular we investigated Brodmann Area (BA) 19 (occipital lobe), BA 7 (parietal lobe) and BA 6 (frontal lobe). Results show that the model can reproduce the natural rhythms of the three regions quite well, acting on a few internal parameters. Moreover, the model can explain most rhythm changes induced by stimulation of another region, and inter-subject variability, by estimating just a few long-range connectivity parameters among ROIs. Copyright © 2011 Elsevier Inc. All rights reserved.
Full Text Available We present the evaluation of two well-known, low-cost consumer-grade EEG devices: the Emotiv EPOC and the Neurosky MindWave. Problems with using the consumer-grade EEG devices (BCI illiteracy, poor technical characteristics, and adverse EEG artefacts are discussed. The experimental evaluation of the devices, performed with 10 subjects asked to perform concentration/relaxation and blinking recognition tasks, is given. The results of statistical analysis show that both devices exhibit high variability and non-normality of attention and meditation data, which makes each of them difficult to use as an input to control tasks. BCI illiteracy may be a significant problem, as well as setting up of the proper environment of the experiment. The results of blinking recognition show that using the Neurosky device means recognition accuracy is less than 50%, while the Emotiv device has achieved a recognition accuracy of more than 75%; for tasks that require concentration and relaxation of subjects, the Emotiv EPOC device has performed better (as measured by the recognition accuracy by ∼9%. Therefore, the Emotiv EPOC device may be more suitable for control tasks using the attention/meditation level or eye blinking than the Neurosky MindWave device.
Full Text Available Brain-machine interfaces (BMI rely on the accurate classification of event-related potentials (ERPs and their performance greatly depends on the appropriate selection of classifier parameters and features from dense-array electroencephalography (EEG signals. Moreover, in order to achieve a portable and more compact BMI for practical applications, it is also desirable to use a system capable of accurate classification using information from as few EEG channels as possible. In the present work, we propose a method for classifying P300 ERPs using a combination of Fisher Discriminant Analysis (FDA and a multiobjective hybrid real-binary Particle Swarm Optimization (MHPSO algorithm. Specifically, the algorithm searches for the set of EEG channels and classifier parameters that simultaneously maximize the classification accuracy and minimize the number of used channels. The performance of the method is assessed through offline analyses on datasets of auditory ERPs from sound discrimination experiments. The proposed method achieved a higher classification accuracy than that achieved by traditional methods while also using fewer channels. It was also found that the number of channels used for classification can be significantly reduced without greatly compromising the classification accuracy.
Full Text Available The human brain naturally recognizes a change of environment or atmosphere without great effort, and this is essential for interactive communication in social life and a specific reaction in an emergency situation. Most studies have investigated change detection of the brain with conditional experimental paradigms rather than the performance of everyday tasks. However, naturally occurring sensory stimuli are multimodal and dynamic. In an effort to study the relationship between users' induced physiological responses and changes of environment and atmosphere under more naturalistic and ecological conditions, we performed a basic experiment using audio-visual movies and electroencephalogram (EEG measurement. 8 healthy subjects were asked to watch a television sitcom without any responses, and their EEG signals were recorded simultaneously with 126 electrodes mounted in an elastic electrode cap. Time-frequency analysis of EEG revealed distinctive neural oscillations at the point of story change in the movie. This result could be used for applications in brain-computer interfaces, and provides a reference to cognitive impairment studies such as Attention Deficit Disorder (ADD or Attention-Deficit/Hyperactivity Disorder (ADHD.
Trunk, Attila; Stefanics, Gábor; Zentai, Norbert; Kovács-Bálint, Zsófia; Thuróczy, György; Hernádi, István
Potential effects of a 30 min exposure to third generation (3G) Universal Mobile Telecommunications System (UMTS) mobile phone-like electromagnetic fields (EMFs) were investigated on human brain electrical activity in two experiments. In the first experiment, spontaneous electroencephalography (sEEG) was analyzed (n = 17); in the second experiment, auditory event-related potentials (ERPs) and automatic deviance detection processes reflected by mismatch negativity (MMN) were investigated in a passive oddball paradigm (n = 26). Both sEEG and ERP experiments followed a double-blind protocol where subjects were exposed to either genuine or sham irradiation in two separate sessions. In both experiments, electroencephalograms (EEG) were recorded at midline electrode sites before and after exposure while subjects were watching a silent documentary. Spectral power of sEEG data was analyzed in the delta, theta, alpha, and beta frequency bands. In the ERP experiment, subjects were presented with a random series of standard (90%) and frequency-deviant (10%) tones in a passive binaural oddball paradigm. The amplitude and latency of the P50, N100, P200, MMN, and P3a components were analyzed. We found no measurable effects of a 30 min 3G mobile phone irradiation on the EEG spectral power in any frequency band studied. Also, we found no significant effects of EMF irradiation on the amplitude and latency of any of the ERP components. In summary, the present results do not support the notion that a 30 min unilateral 3G EMF exposure interferes with human sEEG activity, auditory evoked potentials or automatic deviance detection indexed by MMN. Copyright © 2012 Wiley Periodicals, Inc.
Nicolaou, Nicoletta; Malik, Asad; Daly, Ian; Weaver, James; Hwang, Faustina; Kirke, Alexis; Roesch, Etienne B; Williams, Duncan; Miranda, Eduardo R; Nasuto, Slawomir J
Beat perception is fundamental to how we experience music, and yet the mechanism behind this spontaneous building of the internal beat representation is largely unknown. Existing findings support links between the tempo (speed) of the beat and enhancement of electroencephalogram (EEG) activity at tempo-related frequencies, but there are no studies looking at how tempo may affect the underlying long-range interactions between EEG activity at different electrodes. The present study investigates these long-range interactions using EEG activity recorded from 21 volunteers listening to music stimuli played at 4 different tempi (50, 100, 150 and 200 beats per minute). The music stimuli consisted of piano excerpts designed to convey the emotion of "peacefulness". Noise stimuli with an identical acoustic content to the music excerpts were also presented for comparison purposes. The brain activity interactions were characterized with the imaginary part of coherence (iCOH) in the frequency range 1.5-18 Hz (δ, θ, α and lower β) between all pairs of EEG electrodes for the four tempi and the music/noise conditions, as well as a baseline resting state (RS) condition obtained at the start of the experimental task. Our findings can be summarized as follows: (a) there was an ongoing long-range interaction in the RS engaging fronto-posterior areas; (b) this interaction was maintained in both music and noise, but its strength and directionality were modulated as a result of acoustic stimulation; (c) the topological patterns of iCOH were similar for music, noise and RS, however statistically significant differences in strength and direction of iCOH were identified; and (d) tempo had an effect on the direction and strength of motor-auditory interactions. Our findings are in line with existing literature and illustrate a part of the mechanism by which musical stimuli with different tempi can entrain changes in cortical activity.
Paz-Linares, Deirel; Vega-Hernández, Mayrim; Rojas-López, Pedro A; Valdés-Hernández, Pedro A; Martínez-Montes, Eduardo; Valdés-Sosa, Pedro A
The estimation of EEG generating sources constitutes an Inverse Problem (IP) in Neuroscience. This is an ill-posed problem due to the non-uniqueness of the solution and regularization or prior information is needed to undertake Electrophysiology Source Imaging. Structured Sparsity priors can be attained through combinations of (L1 norm-based) and (L2 norm-based) constraints such as the Elastic Net (ENET) and Elitist Lasso (ELASSO) models. The former model is used to find solutions with a small number of smooth nonzero patches, while the latter imposes different degrees of sparsity simultaneously along different dimensions of the spatio-temporal matrix solutions. Both models have been addressed within the penalized regression approach, where the regularization parameters are selected heuristically, leading usually to non-optimal and computationally expensive solutions. The existing Bayesian formulation of ENET allows hyperparameter learning, but using the computationally intensive Monte Carlo/Expectation Maximization methods, which makes impractical its application to the EEG IP. While the ELASSO have not been considered before into the Bayesian context. In this work, we attempt to solve the EEG IP using a Bayesian framework for ENET and ELASSO models. We propose a Structured Sparse Bayesian Learning algorithm based on combining the Empirical Bayes and the iterative coordinate descent procedures to estimate both the parameters and hyperparameters. Using realistic simulations and avoiding the inverse crime we illustrate that our methods are able to recover complicated source setups more accurately and with a more robust estimation of the hyperparameters and behavior under different sparsity scenarios than classical LORETA, ENET and LASSO Fusion solutions. We also solve the EEG IP using data from a visual attention experiment, finding more interpretable neurophysiological patterns with our methods. The Matlab codes used in this work, including Simulations, Methods
Full Text Available Beat perception is fundamental to how we experience music, and yet the mechanism behind this spontaneous building of the internal beat representation is largely unknown. Existing findings support links between the tempo (speed of the beat and enhancement of electroencephalogram (EEG activity at tempo-related frequencies, but there are no studies looking at how tempo may affect the underlying long-range interactions between EEG activity at different electrodes. The present study investigates these long-range interactions using EEG activity recorded from 21 volunteers listening to music stimuli played at 4 different tempi (50, 100, 150 and 200 beats per minute. The music stimuli consisted of piano excerpts designed to convey the emotion of “peacefulness”. Noise stimuli with an identical acoustic content to the music excerpts were also presented for comparison purposes. The brain activity interactions were characterized with the imaginary part of coherence (iCOH in the frequency range 1.5–18 Hz (δ, θ, α and lower β between all pairs of EEG electrodes for the four tempi and the music/noise conditions, as well as a baseline resting state (RS condition obtained at the start of the experimental task. Our findings can be summarized as follows: (a there was an ongoing long-range interaction in the RS engaging fronto-posterior areas; (b this interaction was maintained in both music and noise, but its strength and directionality were modulated as a result of acoustic stimulation; (c the topological patterns of iCOH were similar for music, noise and RS, however statistically significant differences in strength and direction of iCOH were identified; and (d tempo had an effect on the direction and strength of motor-auditory interactions. Our findings are in line with existing literature and illustrate a part of the mechanism by which musical stimuli with different tempi can entrain changes in cortical activity.
Nicolaou, Nicoletta; Malik, Asad; Daly, Ian; Weaver, James; Hwang, Faustina; Kirke, Alexis; Roesch, Etienne B.; Williams, Duncan; Miranda, Eduardo R.; Nasuto, Slawomir J.
Beat perception is fundamental to how we experience music, and yet the mechanism behind this spontaneous building of the internal beat representation is largely unknown. Existing findings support links between the tempo (speed) of the beat and enhancement of electroencephalogram (EEG) activity at tempo-related frequencies, but there are no studies looking at how tempo may affect the underlying long-range interactions between EEG activity at different electrodes. The present study investigates these long-range interactions using EEG activity recorded from 21 volunteers listening to music stimuli played at 4 different tempi (50, 100, 150 and 200 beats per minute). The music stimuli consisted of piano excerpts designed to convey the emotion of “peacefulness”. Noise stimuli with an identical acoustic content to the music excerpts were also presented for comparison purposes. The brain activity interactions were characterized with the imaginary part of coherence (iCOH) in the frequency range 1.5–18 Hz (δ, θ, α and lower β) between all pairs of EEG electrodes for the four tempi and the music/noise conditions, as well as a baseline resting state (RS) condition obtained at the start of the experimental task. Our findings can be summarized as follows: (a) there was an ongoing long-range interaction in the RS engaging fronto-posterior areas; (b) this interaction was maintained in both music and noise, but its strength and directionality were modulated as a result of acoustic stimulation; (c) the topological patterns of iCOH were similar for music, noise and RS, however statistically significant differences in strength and direction of iCOH were identified; and (d) tempo had an effect on the direction and strength of motor-auditory interactions. Our findings are in line with existing literature and illustrate a part of the mechanism by which musical stimuli with different tempi can entrain changes in cortical activity. PMID:29093672
Routine electroencephalogram (EEG) is an important test in aiding the diagnosis of patients with suspected epilepsy. These recordings typically last 20-40 minutes, during which signs of abnormal activity (spikes, sharp waves) are looked for in the EEG trace. It is essential that events of short duration are detected during the routine EEG test. The work presented in this paper examines the effect of changing a range of input values to the detection system on its ability to distinguish between normal and abnormal EEG activity. It is shown that the length of analysis window in the range of 0.5s to 1s are well suited to the task. Additionally, it is reported that patient specific systems should be used where possible due to their better performance.
Frenz, Walter; Cosack, Tilman
Unlike any other Act, the Renewable Energy Sources Act (EEG) changes continuously. Recently it has been fundamentally transformed with the amendment 2014. Comprehensive, readable and practice-oriented. The proven Berliner comment EEG is your reliable companion through the new regulatory regime. All provisions of the EEG 2014 thorough and easy to understand commented by experts of the matter. 2. The EEG Amending Act of 29.6.2015 has already been considered. A detailed introduction and contributions to the relevant European law and the antitrust aspects of the renewable energy sources to guarantee you a broad understanding of the rules. Valuable background information you provide, the digressions of the most important renewable energy technologies, will explain the pictures thanks to numerous the scientific and technical foundations. Moreover you the construction law aspects in the construction of photovoltaic and wind turbines are explained clearly. [de
Chakrabarti, Dhritiman; Bansal, Sonia
Entropy™ is a proprietary algorithm which uses spectral entropy analysis of electroencephalographic (EEG) signals to produce indices which are used as a measure of depth of hypnosis. We describe a report of electrocardiographic (ECG) contamination of EEG signals leading to fluctuating erroneous Entropy values. An explanation is provided for mechanism behind this observation by describing the spread of ECG signals in head and neck and its influence on EEG/Entropy by correlating the observation with the published Entropy algorithm. While the Entropy algorithm has been well conceived, there are still instances in which it can produce erroneous values. Such erroneous values and their cause may be identified by close scrutiny of the EEG waveform if Entropy values seem out of sync with that expected at given anaesthetic levels.
Full Text Available Neurosyphilis is a recognized cause of epileptic seizures and cognitive impairment, but is not usually associated with the finding of generalized periodic activity in the EEG. We report two similar cases characterized by progressive cognitive impairment followed by partial complex seizures, in whom the EEG showed generalized periodic activity. Both cerebrospinal fluid and the response to penicillin therapy confirmed the diagnoses of neurosyphilis in the two cases. The finding of EEG generalized periodic activity in patients with cognitive or behavioral disorders is usually associated with Creutzfeldt-Jakob disease, although there are other conditions, some of them potentially reversible, which may also present this EEG abnormality. Neurosyphilis has tended not to be included among them, and our present findings support the importance of first ruling out neurosyphilis in those patients with cognitive or behavioral disorders associated with generalized periodic epileptiform discharges.
Surinder K Singhal
Full Text Available We report a rare case of an unusually long foreign body (Datun impacted in the esophagus of a 56 year-old gentleman. He was literate, without any psychiatric illness and had been using “Neem” (Azadirachta indica stick for cleaning his teeth for the past twenty years. Neem sticks are used for brushing teeth, perhaps one of the earliest and very effective dental care. On closer questioning he revealed his habit of passing the Neem stick into his throat with the aim of cleaning it too while cleaning his teeth. He presented to our emergency early in the morning with this strange long foreign body impacted in his esophagus which was removed successfully using a Jackson’s adult rigid oesophagoscope. We believe this to be the first case of such an unusually long foreign body to be reported in the literature.
... 48 Federal Acquisition Regulations System 1 2010-10-01 2010-10-01 false Unusual contract financing... CONTRACTING REQUIREMENTS CONTRACT FINANCING Non-Commercial Item Purchase Financing 32.114 Unusual contract financing. Any contract financing arrangement that deviates from this part is unusual contract financing...
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... 48 Federal Acquisition Regulations System 5 2010-10-01 2010-10-01 false Unusual contract financing... CONTRACTING REQUIREMENTS CONTRACT FINANCING Non-Commercial Item Purchase Financing 1332.114 Unusual contract financing. The designee authorized to approve unusual contract financing arrangements is set forth in CAM...
The presentation shows how a victim of fall from height in the bush can sustain a penetrating chest injury on a dry stick of a shrub. Applications on the principles of management of penetrating chest injury is needed despite the grotesque clinical appearance. [Jnl College of Medicine Vol.7(1) 2002: 40-42] ...
Bhattacharyya, Sourya; Biswas, Arunava; Mukherjee, Jayanta; Majumdar, Arun Kumar; Majumdar, Bandana; Mukherjee, Suchandra; Singh, Arun Kumar
Detection of non-cerebral activities or artifacts, intermixed within the background EEG, is essential to discard them from subsequent pattern analysis. The problem is much harder in neonatal EEG, where the background EEG contains spikes, waves, and rapid fluctuations in amplitude and frequency. Existing artifact detection methods are mostly limited to detect only a subset of artifacts such as ocular, muscle or power line artifacts. Few methods integrate different modules, each for detection of one specific category of artifact. Furthermore, most of the reference approaches are implemented and tested on adult EEG recordings. Direct application of those methods on neonatal EEG causes performance deterioration, due to greater pattern variation and inherent complexity. A method for detection of a wide range of artifact categories in neonatal EEG is thus required. At the same time, the method should be specific enough to preserve the background EEG information. The current study describes a feature based classification approach to detect both repetitive (generated from ECG, EMG, pulse, respiration, etc.) and transient (generated from eye blinking, eye movement, patient movement, etc.) artifacts. It focuses on artifact detection within high energy burst patterns, instead of detecting artifacts within the complete background EEG with wide pattern variation. The objective is to find true burst patterns, which can later be used to identify the Burst-Suppression (BS) pattern, which is commonly observed during newborn seizure. Such selective artifact detection is proven to be more sensitive to artifacts and specific to bursts, compared to the existing artifact detection approaches applied on the complete background EEG. Several time domain, frequency domain, statistical features, and features generated by wavelet decomposition are analyzed to model the proposed bi-classification between burst and artifact segments. A feature selection method is also applied to select the
Glomus tumours are benign, soft tissue tumours, usually of fingertips. Classically they present with severe pain, temperature sensitivity and localised tenderness. The diagnosis is often delayed due to sometimes non-specific symptoms and rarity of the disorder. While usually a clinical diagnosis, imaging may be necessary for diagnosis and localisation. We present a case of glomus tumour of the fingertip with an unusual history.
Turgut, Ahmet Tuncay [Department of Radiology, Ankara Training and Research Hospital, Ankara (Turkey)]. E-mail: firstname.lastname@example.org; Altin, Levent [Department of Radiology, Numune Training and Research Hospital, Ankara (Turkey); Topcu, Salih [Department of Thoracic Surgery, Faculty of Medicine, Kocaeli University, Izmit (Turkey); Kilicoglu, Buelent [Department of 4th General Surgery, Ankara Training and Research Hospital, Ankara (Turkey); Altinok, Tamer [Department of Thoracic Surgery, Meram Faculty of Medicine, Selcuk University, Konya (Turkey); Kaptanoglu, Erkan [Department of Neurosurgery, Numune Training and Research Hospital, Ankara (Turkey); Karademir, Alp [Department of Radiology, Numune Training and Research Hospital, Ankara (Turkey); Kosar, Ugur [Department of Radiology, Ankara Training and Research Hospital, Ankara (Turkey)
Hydatid disease, a worldwide zoonosis, is caused by the larval stage of the Echinococcus tapeworm. Although the liver and the lungs are the most frequently involved organs in the body, hydatid cysts of other organs are unusual. Radiologically, they usually demonstrate typical imaging findings, but unusual imaging characteristics of complicated cyst of hydatid disease, associated with high morbidity and mortality, are rarely described in the literature. The purpose of this study is to review the general features of hydatidosis and to discuss atypical imaging characteristics of the complicated hydatid disease in the human, with an emphasis on structure and rupture of the cystic lesion as well as ultrasonography (USG), computed tomography (CT), and magnetic resonance imaging (MRI) features of the disease. In our study, the available literature and images of the cases with complicated hydatidosis involving liver, lung, brain, spine and orbit were reviewed retrospectively. In hydatid disease, there are many potential local and systemic complications due to secondary involvement in almost any anatomic location in humans. Radiologically, in addition to the presence of atypical findings such as perifocal edema, non-homogenous contrast enhancement, multiplicity or septations and calcification, various unusual manifestations due to rupture or infection of the cyst have been observed in our cases with complicated hydatid disease. To prevent subsequent acute catastrophic results and the development of recurrences in various organs, it should be kept in mind that complicated hydatid cysts can cause unusual USG, CT, and MRI findings, in addition to typical ones, in endemic areas. Therefore, familiarity with atypical radiological appearances of complicated hydatid disease may be valuable in making a correct diagnosis and treatment.
Full Text Available Solitary rectal ulcer syndrome (SRUS is a benign disease that is often misdiagnosed. It is characterized by a combination of symptoms, endoscopic findings and histology. Patients present with constipation, rectal bleeding, mucous discharge, pain and a sensation of incomplete defecation. There are many different manifestations of this disease, with or without rectal prolapse. We report an unusual presentation of SRUS as a circular stenosis in a middle-aged male.
George, P.; Mathew, P.; Pawar, B.; Calton, N.
Wasp stings are not uncommon especially in populations living in theproximity of forested area-s all over the world. Local manifestationsfollowing stings are common and unusually life threatening anaphylaxis mayoccur, requiring prompt treatment. Multi organ failure and acute renalfailure following wasp stings are rare and histological evaluation suggestacute tubular necrosis secondary to hemolysis, rhabdomyolysis and directvenom toxicity. A rare complication of a patient following multiple waspstings with disseminated intravascular coagulation, acute renal failure andthrombotic microangiopathy is presented. (author)
Full Text Available Pseudoepitheliomatous hyperplasia is an extremely rare condition presenting as a lesion on the glans penis in older men. Physical exam without biopsy cannot differentiate malignant from nonmalignant growth. We report a case of large penile mass in an elderly male with a history of lichen sclerosis, highly suspicious for malignancy. Subsequent surgical removal and biopsy demonstrated pseudoepitheliomatous hyperplasia, an unusual benign histopathologic diagnosis with unclear prognosis. We review the literature and discuss options for treatment and surveillance.
Abdelwahab, Ibrahim F. [Coney Island Hospital, Department of Radiology, New York, NY (United States); Hoch, Benjamin [Mount Sinai School of Medicine, CUNY, Department of Pathology, New York, NY (United States); Hermann, George [Mount Sinai School of Medicine, CUNY, Department of Radiology, New York, NY (United States); Bianchi, Stefano [Clinique et Fondation des Grangettes, Geneva (Switzerland); Klein, Michael J. [UAB School of Medicine, Department of Pathology, Birmingham, AL (United States); Springfield, Dempsey S. [Mount Sinai School of Medicine, CUNY, Department of Orthopedics, New York, NY (United States)
We describe a primary periosteal lymphoma that involved only the periosteum without affecting the adjacent medulla or the regional lymph nodes. No other lymphomatous foci were found in either the distant lymph nodes or viscera. This unusual presentation simulates the imaging appearance of surface lesions of bone, namely benign and malignant tumors, and departs from the typical appearance of primary lymphoma of bone. Therefore, this rare type of lymphoma should be considered in the differential diagnosis of surface bone lesions. (orig.)
Full Text Available The incidence of juvenile lupus varies widely ranging between 4 and 250 per 100,000 population. Most common organ involvement in juvenile lupus is kidney. Neurological, cutaneous and hematological involvements are also involved. Skeletal muscle involvement in the form of myositis is rare. Myositis as presenting manifestation in juvenile lupus is also unusual. Herein, we report one such case wherein myositis preceded the onset of lupus nephritis
Turgut, Ahmet Tuncay; Altin, Levent; Topcu, Salih; Kilicoglu, Buelent; Altinok, Tamer; Kaptanoglu, Erkan; Karademir, Alp; Kosar, Ugur
Hydatid disease, a worldwide zoonosis, is caused by the larval stage of the Echinococcus tapeworm. Although the liver and the lungs are the most frequently involved organs in the body, hydatid cysts of other organs are unusual. Radiologically, they usually demonstrate typical imaging findings, but unusual imaging characteristics of complicated cyst of hydatid disease, associated with high morbidity and mortality, are rarely described in the literature. The purpose of this study is to review the general features of hydatidosis and to discuss atypical imaging characteristics of the complicated hydatid disease in the human, with an emphasis on structure and rupture of the cystic lesion as well as ultrasonography (USG), computed tomography (CT), and magnetic resonance imaging (MRI) features of the disease. In our study, the available literature and images of the cases with complicated hydatidosis involving liver, lung, brain, spine and orbit were reviewed retrospectively. In hydatid disease, there are many potential local and systemic complications due to secondary involvement in almost any anatomic location in humans. Radiologically, in addition to the presence of atypical findings such as perifocal edema, non-homogenous contrast enhancement, multiplicity or septations and calcification, various unusual manifestations due to rupture or infection of the cyst have been observed in our cases with complicated hydatid disease. To prevent subsequent acute catastrophic results and the development of recurrences in various organs, it should be kept in mind that complicated hydatid cysts can cause unusual USG, CT, and MRI findings, in addition to typical ones, in endemic areas. Therefore, familiarity with atypical radiological appearances of complicated hydatid disease may be valuable in making a correct diagnosis and treatment
Full Text Available The accidental aspiration of a foreign body is a frequent domestic accident among children but a rare occurrence in adults. The laryngeal impaction of a coin is an unusual accident; only a few cases have been reported in the literature. Diagnosis is mostly achieved by clinicoradiological examinations. The authors report an uncommon case of laryngeal impaction of a coin in a 21-year-old patient, presenting with dysphonia without dyspnea or stridor. The extraction was performed by endoscopy.
Ndiaye, Cire; Regonne, Eric Joel; Ahmed, Houra; Diom, Evelyne Siga; Deguenonvo, Richard Edouard Alain; Mbaye, Aminata; Zemene, Yilkal; Ndiaye, Issa Cheikh
The accidental aspiration of a foreign body is a frequent domestic accident among children but a rare occurrence in adults. The laryngeal impaction of a coin is an unusual accident; only a few cases have been reported in the literature. Diagnosis is mostly achieved by clinicoradiological examinations. The authors report an uncommon case of laryngeal impaction of a coin in a 21-year-old patient, presenting with dysphonia without dyspnea or stridor. The extraction was performed by endoscopy.
Ndiaye, Cire; Regonne, Eric Joel; Ahmed, Houra; Diom, Evelyne Siga; Deguenonvo, Richard Edouard Alain; Mbaye, Aminata; Zemene, Yilkal; Ndiaye, Issa Cheikh
The accidental aspiration of a foreign body is a frequent domestic accident among children but a rare occurrence in adults. The laryngeal impaction of a coin is an unusual accident; only a few cases have been reported in the literature. Diagnosis is mostly achieved by clinicoradiological examinations. The authors report an uncommon case of laryngeal impaction of a coin in a 21-year-old patient, presenting with dysphonia without dyspnea or stridor. The extraction was performed by endoscopy.
Kapetanakis, Stylianos; Papathanasiou, Jiannis; Dermon, Antonios; Dimitrakopoulou, Alexandra; Ververidis, Athanasios; Chloropoulou, Pelagia; Kazakos, Konstantinos
Lipomas are common soft tissue tumors usually located under the skin. Nevertheless, intramuscular lipomas of deltoid muscle are unusual tumors. We present a case of 74-year-old woman with an intramuscular like clepsydra lipoma of deltoid muscle. The lesion was a palpable soft mass at the lateral side of the humerus. The patient had no previous history of trauma. The main symptom was pain only in abduction and extension. Imaging, pathological findings and surgical excision are discussed.
Full Text Available A 12-hour-old male infant presented with prolapsed abdominal content through a defect on left side of chest wall with respiratory distress. A thorough clinical examination suggested absence of ectopia cordis, abdominal wall defect, and any bony anomaly. The child expired after 6 hours of admission because of respiratory distress and electrolyte imbalance. Is congenital defect of chest wall associated with diaphragmatic hernia without ectopia cordis and omphalocele, an unusual variant of Cantrell′s pentalogy?
This podcast discusses a study about the probable unusual transmission of Zika Virus Infection from a scientist to his wife, published in the May 2011 issue of Emerging Infectious Diseases. Dr. Brian Foy, Associate Professor at Colorado State University, shares details of this event. Created: 5/23/2011 by National Center for Emerging Zoonotic and Infectious Diseases (NCEZID). Date Released: 5/25/2011.
Sanjeev Kumar Sharma
Full Text Available The authors present here an interesting case of recent onset anemia that was associated with an encephalopathy of the unusual cause.Although severe anemia can theoretically result in anemic hypoxia and can then lead to hypoxic encephalopathy, it is not a primary cause of encephalopathy. More frequently anemia can contribute together with other multiple causes of encephalopathy, such as infections, metabolic abnormalities, trauma, hepatic dysfunction, hypertension, toxins.
Wong, Chung-Ki; Zotev, Vadim; Misaki, Masaya; Phillips, Raquel; Luo, Qingfei; Bodurka, Jerzy
Head motions during functional magnetic resonance imaging (fMRI) impair fMRI data quality and introduce systematic artifacts that can affect interpretation of fMRI results. Electroencephalography (EEG) recordings performed simultaneously with fMRI provide high-temporal-resolution information about ongoing brain activity as well as head movements. Recently, an EEG-assisted retrospective motion correction (E-REMCOR) method was introduced. E-REMCOR utilizes EEG motion artifacts to correct the effects of head movements in simultaneously acquired fMRI data on a slice-by-slice basis. While E-REMCOR is an efficient motion correction approach, it involves an independent component analysis (ICA) of the EEG data and identification of motion-related ICs. Here we report an automated implementation of E-REMCOR, referred to as aE-REMCOR, which we developed to facilitate the application of E-REMCOR in large-scale EEG-fMRI studies. The aE-REMCOR algorithm, implemented in MATLAB, enables an automated preprocessing of the EEG data, an ICA decomposition, and, importantly, an automatic identification of motion-related ICs. aE-REMCOR has been used to perform retrospective motion correction for 305 fMRI datasets from 16 subjects, who participated in EEG-fMRI experiments conducted on a 3T MRI scanner. Performance of aE-REMCOR has been evaluated based on improvement in temporal signal-to-noise ratio (TSNR) of the fMRI data, as well as correction efficiency defined in terms of spike reduction in fMRI motion parameters. The results show that aE-REMCOR is capable of substantially reducing head motion artifacts in fMRI data. In particular, when there are significant rapid head movements during the scan, a large TSNR improvement and high correction efficiency can be achieved. Depending on a subject's motion, an average TSNR improvement over the brain upon the application of aE-REMCOR can be as high as 27%, with top ten percent of the TSNR improvement values exceeding 55%. The average
de Munck, J.C.; van Houdt, P.J.; Goncalves, S.I.; van Wegen, E.E.H.; Ossenblok, P.P.W.
Co-registered EEG and functional MRI (EEG/fMRI) is a potential clinical tool for planning invasive EEG in patients with epilepsy. In addition, the analysis of EEG/fMRI data provides a fundamental insight into the precise physiological meaning of both fMRI and EEG data. Routine application of
Sterman, M. B.
Electrophysiological changes in the sensorimotor pathways were found to accompany the effect of rhythmic EEG patterns in the sensorimotor cortex. Additionally, several striking behavioral changes were seen, including in particular an enhancement of sleep and an elevation of seizure threshold to epileptogenic agents. This raised the possibility that human seizure disorders might be influenced therapeutically by similar training. Our objective in human EEG feedback training became not only the facilitation of normal rhythmic patterns, but also the suppression of abnormal activity, thus requiring complex contingencies directed to the normalization of the sensorimotor EEG. To achieve this, a multicomponent frequency analysis was developed to extract and separate normal and abnormal elements of the EEG signal. Each of these elements was transduced to a specific component of a visual display system, and these were combined through logic circuits to present the subject with a symbolic display. Variable criteria provided for the gradual shaping of EEG elements towards the desired normal pattern. Some 50-70% of patients with poorly controlled seizure disorders experienced therapeutic benefits from this approach in our laboratory, and subsequently in many others. A more recent application of this approach to the modification of human brain function in our lab has been directed to the dichotomous problems of task overload and underload in the contemporary aviation environment. At least 70% of all aviation accidents have been attributed to the impact of these kinds of problems on crew performance. The use of EEG in this context has required many technical innovations and the application of the latest advances in EEG signal analysis. Our first goal has been the identification of relevant EEG characteristics. Additionally, we have developed a portable recording and analysis system for application in this context. Findings from laboratory and in-flight studies suggest that we
Poulsen, Andreas Trier; Kamronn, Simon Due; Dmochowski, Jacek
We performed simultaneous recordings of electroencephalography (EEG) from multiple students in a classroom, and measured the inter-subject correlation (ISC) of activity evoked by a common video stimulus. The neural reliability, as quantified by ISC, has been linked to engagement and attentional......-evoked neural responses, known to be modulated by attention, can be tracked for groups of students with synchronized EEG acquisition. This is a step towards real-time inference of engagement in the classroom....
Poulsen, Andreas Trier; Kamronn, Simon Due; Parra, Lucas
We propose a probabilistic generative multi-view model to test the representational universality of human information processing. The model is tested in simulated data and in a well-established benchmark EEG dataset.......We propose a probabilistic generative multi-view model to test the representational universality of human information processing. The model is tested in simulated data and in a well-established benchmark EEG dataset....
Pavlov, Alexey N.; Maksimenko, Vladimir A.; Runnova, Anastasiya E.; Khramova, Marina V.; Pisarchik, Alexander N.
We study abilities of the wavelet-based multifractal analysis in recognition specific dynamics of electrical brain activity associated with real and imaginary movements. Based on the singularity spectra we analyze electroencephalograms (EEGs) acquired in untrained humans (operators) during imagination of hands movements, and show a possibility to distinguish between the related EEG patterns and the recordings performed during real movements or the background electrical brain activity. We discuss how such recognition depends on the selected brain region.
Khaburzania, M; Beridze, M
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; pEEG patterns' association with coma outcome only in hemorrhagic and traumatic coma (chi-sqr.=12.95; pEEG patterns and coma outcome. Low amplitude decreased power delta and theta frequencies correlated with SND in survived coma patients (r=+0.21; pEEG 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
Tarokh L; Carskadon M A; Achermann P
Adolescence represents a time of significant cortical restructuring. Current theories posit that during this period connections between frequently utilized neural networks are strengthened while underutilized synaptic connections are discarded. The aim of the present study was to examine the developmental evolution of connectivity between brain regions using the sleep EEG. All night sleep EEG recordings in two longitudinal cohorts (children and teens) followed at 1.5 3 year intervals and one ...
Tanaka, H; Hayashi, M; Hori, T
The purpose of the present study was to identify the dominant topographic components of electroencephalographs (EEG) and their behavior during the waking-sleeping transition period. Somnography of nocturnal sleep was recorded on 10 male subjects. Each recording, from "lights-off" to 5 minutes after the appearance of the first sleep spindle, was analyzed. The typical EEG patterns during hypnagogic period were classified into nine EEG stages. Topographic maps demonstrated that the dominant areas of alpha-band activity moved from the posterior areas to anterior areas along the midline of the scalp. In delta-, theta-, and sigma-band activities, the differences of EEG amplitude between the focus areas (the dominant areas) and the surrounding areas increased as a function of EEG stage. To identify the dominant topographic components, a principal component analysis was carried out on a 12-channel EEG data set for each of six frequency bands. The dominant areas of alpha 2- (9.6-11.4 Hz) and alpha 3- (11.6-13.4 Hz) band activities moved from the posterior to anterior areas, respectively. The distribution of alpha 2-band activity on the scalp clearly changed just after EEG stage 3 (alpha intermittent, < 50%). On the other hand, alpha 3-band activity became dominant in anterior areas after the appearance of vertex sharp-wave bursts (EEG stage 7). For the sigma band, the amplitude of extensive areas from the frontal pole to the parietal showed a rapid rise after the onset of stage 7 (the appearance of vertex sharp-wave bursts). Based on the results, sleep onset process probably started before the onset of sleep stage 1 in standard criteria. On the other hand, the basic sleep process may start before the onset of sleep stage 2 or the manually scored spindles.
Cheron, Guy; Petit, Géraldine; Cheron, Julian; Leroy, Axelle; Cebolla, Anita; Cevallos, Carlos; Petieau, Mathieu; Hoellinger, Thomas; Zarka, David; Clarinval, Anne-Marie; Dan, Bernard
Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The non-invasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical a...
Guy eCheron; Guy eCheron; Geraldine ePetit; Julian eCheron; Axelle eLeroy; Axelle eLeroy; Ana Maria Cebolla; Carlos eCevallos; Mathieu ePetieau; David eZarka; Thomas eHoellinger; Anne-Marie eClarinval; Bernard eDan; Bernard eDan
Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The noninvasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical ap...
Hsu, David A; Rayer, Katherine; Jackson, Daren C; Stafstrom, Carl E; Hsu, Murielle; Ferrazzano, Peter A; Dabbs, Kevin; Worrell, Gregory A; Jones, Jana E; Hermann, Bruce P
To determine correlations of the EEG frequency spectrum with neuropsychological status in children with idiopathic epilepsy. Forty-six children ages 8-18 years old with idiopathic epilepsy were retrospectively identified and analyzed for correlations between EEG spectra and neuropsychological status using multivariate linear regression. In addition, the theta/beta ratio, which has been suggested as a clinically useful EEG marker of attention-deficit hyperactivity disorder (ADHD), and an EEG spike count were calculated for each subject. Neuropsychological status was highly correlated with posterior alpha (8-15 Hz) EEG activity in a complex way, with both positive and negative correlations at lower and higher alpha frequency sub-bands for each cognitive task in a pattern that depends on the specific cognitive task. In addition, the theta/beta ratio was a specific but insensitive indicator of ADHD status in children with epilepsy; most children both with and without epilepsy have normal theta/beta ratios. The spike count showed no correlations with neuropsychological status. (1) The alpha rhythm may have at least two sub-bands which serve different purposes. (2) The theta/beta ratio is not a sensitive indicator of ADHD status in children with epilepsy. (3) The EEG frequency spectrum correlates more robustly with neuropsychological status than spike count analysis in children with idiopathic epilepsy. (1) The role of posterior alpha rhythms in cognition is complex and can be overlooked if EEG spectral resolution is too coarse or if neuropsychological status is assessed too narrowly. (2) ADHD in children with idiopathic epilepsy may involve different mechanisms from those in children without epilepsy. (3) Reliable correlations with neuropsychological status require longer EEG samples when using spike count analysis than when using frequency spectra. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights
Melia, Umberto Sergio Pio; Guaita, Marc; Vallverdú Ferrer, Montserrat; Embid, Cristina; Vilaseca, I; Salamero, Manuel; Santamaria, Joan
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 lat...
Cole, Rebecca A.; Franson, J. Christian; Boere, Gerard C.; Galbraith, Colin A.; Stroud, David A.
Over the last decade, the National Wildlife Health Center of the United States Geological Survey has documented various largescale mortalities of birds caused by infectious and non-infectious disease agents. Some of these mortality events have unusual or unidentified etiologies and have been recurring. While some of the causes of mortalities have been elucidated, others remain in various stages of investigation and identification. Two examples are discussed: 1) Leyogonimus polyoon (Class: Trematoda), not found in the New World until 1999, causes severe enteritis and has killed over 15 000 American Coot Fulica americana in the upper mid-western United States. The geographic range of this parasite within North America is predicted to be limited to the Great Lakes Basin. 2) In the early 1990s, estimates of up to 6% of the North American population of the Eared Grebe Podiceps nigricollis died at Salton Sea, California, with smaller mortalities occurring throughout the 1990s. Birds were observed to have unusual preening behaviour, and to congregate at freshwater drains and move onto land. Suggested etiologies included interactions of contaminants, immuno-suppression, an unusual form of a bacterial disease, and an unknown biotoxin. During studies carried out from 2000 to 2003, Eared Grebe mortality did not approach the level seen in the early 1990s and, although bacteria were identified as minor factors, the principal cause of mortality remains undetermined. The potential population impact of these emerging and novel disease agents is currently unknown.
Akanda, A. S.; Palash, W.; Hasan, M. A.; Nusrat, F.
Driven primarily by the South Asian Monsoon, the Ganges-Brahmaputra-Meghna (GBM) river basin system collectively drains intense precipitation for an area of more than 1.5 million square kilometers during the wet summer season. Bangladesh, being the lowest riparian country in the system, experiences recurrent floods and immense suffering to its population. The 2017 monsoon season was quite unusual in terms of the characteristics of the precipitation received in the basin. The monsoon was spread out over a much larger time span (April-October) compared to the average monsoon season (June-September). Although the monsoon does not typically start until June in Bangladesh, the 2017 season started much earlier in April with unusually heavy precipitation in the Meghna basin region and caused major damage to agriculture in northeastern Bangladesh. The rainfall continued in several record-breaking pulses, compared to the typical one or two large waves. One of the largest pulses occurred in early August with very high in intensity and volume, causing ECMWF to issue a major warning about widespread flooding in Bangladesh, Northern India, and Eastern Nepal. This record flood event impacted over 40 million people in the above regions, causing major damage to life and infrastructure. Although the Brahmaputra rose above the danger level several times this season, the Ganges was unusually low, thus sparing downstream areas from disastrous floods. However, heavy precipitation continued until October, causing urban flooding in Dhaka and Chittagong - and worsening sanitation and public health conditions in southern Bangladesh - currently undergoing a terrible humanitarian crisis involving Rohingya refugees from the Myanmar. Despite marked improvement in flood forecasting systems in recent years, the 2017 floods identified critical gaps in our understanding of the flooding phenomena and limitations of dissemination in these regions. In this study, we investigate 1) the unusual
Chouvarda, I; Maglaveras, N; Mendez, M O; Rosso, V; Parrino, L; Grassi, A; Terzano, M; Bianchi, A M; Cerutti, S
This work investigates the relation between the complexity of electroencephalography (EEG) signal, as measured by fractal dimension (FD), and normal sleep structure in terms of its macrostructure and microstructure. Sleep features are defined, encoding sleep stage and cyclic alternating pattern (CAP) related information, both in short and long term. The relevance of each sleep feature to the EEG FD is investigated, and the most informative ones are depicted. In order to quantitatively assess the relation between sleep characteristics and EEG dynamics, a modeling approach is proposed which employs subsets of the sleep macrostructure and microstructure features as input variables and predicts EEG FD based on these features of sleep micro/macrostructure. Different sleep feature sets are investigated along with linear and nonlinear models. Findings suggest that the EEG FD time series is best predicted by a nonlinear support vector machine (SVM) model, employing both sleep stage/transitions and CAP features at different time scales depending on the EEG activation subtype. This combination of features suggests that short-term and long-term history of macro and micro sleep events interact in a complex manner toward generating the dynamics of sleep
Beniczky, Sándor; Aurlien, Harald; Brøgger, Jan C.
Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted in the se......Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted...... in the second, revised version of SCORE (Standardized Computer-based Organized Reporting of EEG), which is presented in this paper. The revised terminology was implemented in a software package (SCORE EEG), which was tested in clinical practice on 12,160 EEG recordings. Standardized terms implemented in SCORE...... are used to report the features of clinical relevance, extracted while assessing the EEGs. Selection of the terms is context sensitive: initial choices determine the subsequently presented sets of additional choices. This process automatically generates a report and feeds these features into a database...
Garcés Correa, A.; Laciar, E.; Patiño, H. D.; Valentinuzzi, M. E.
Artifacts in EEG (electroencephalogram) records are caused by various factors, like line interference, EOG (electro-oculogram) and ECG (electrocardiogram). These noise sources increase the difficulty in analyzing the EEG and to obtaining clinical information. For this reason, it is necessary to design specific filters to decrease such artifacts in EEG records. In this paper, a cascade of three adaptive filters based on a least mean squares (LMS) algorithm is proposed. The first one eliminates line interference, the second adaptive filter removes the ECG artifacts and the last one cancels EOG spikes. Each stage uses a finite impulse response (FIR) filter, which adjusts its coefficients to produce an output similar to the artifacts present in the EEG. The proposed cascade adaptive filter was tested in five real EEG records acquired in polysomnographic studies. In all cases, line-frequency, ECG and EOG artifacts were attenuated. It is concluded that the proposed filter reduces the common artifacts present in EEG signals without removing significant information embedded in these records.
Garces Correa, A; Laciar, E; Patino, H D; Valentinuzzi, M E
Artifacts in EEG (electroencephalogram) records are caused by various factors, like line interference, EOG (electro-oculogram) and ECG (electrocardiogram). These noise sources increase the difficulty in analyzing the EEG and to obtaining clinical information. For this reason, it is necessary to design specific filters to decrease such artifacts in EEG records. In this paper, a cascade of three adaptive filters based on a least mean squares (LMS) algorithm is proposed. The first one eliminates line interference, the second adaptive filter removes the ECG artifacts and the last one cancels EOG spikes. Each stage uses a finite impulse response (FIR) filter, which adjusts its coefficients to produce an output similar to the artifacts present in the EEG. The proposed cascade adaptive filter was tested in five real EEG records acquired in polysomnographic studies. In all cases, line-frequency, ECG and EOG artifacts were attenuated. It is concluded that the proposed filter reduces the common artifacts present in EEG signals without removing significant information embedded in these records
Zhavoronkova, L A; Zharikova, A V; Kushnir, E M; Mikhalkova, A A
In 10 healthy persons (22.8 +/- 0.67 years) spectral-coherence parameters of EEG were analyzed in different steps of verticalizations--from gorizontal position to seat and stand one. Maximal changes of all EEG parameters were observed in state with absence of visual control. We observed an increase of power for fast spectral bands of EEG (beta- and gamma-bands) in all conditions and additional increase of these EEG parameters was observed at situation of complication of conditions of vertical pose supporting. Results of EEG coherent analysis in conditions of human verticalization showed specific increase of coherence for the majority of rhythm ranges in the right hemisphere especially in the central-frontal and in occipital-parietal areas and for interhemispheric pairs for these leads. This fact can reflect participation of cortical as well as subcortical structures in these processes. In conditions of complicate conditions of vertical pose supporting the additional increase of EEG coherence in fast bands (beta-rhythm) was observed at the frontal areas. This fact can testify about increasing of executive functions in this conditions.
Full Text Available EEG involves recording, analysis, and interpretation of voltages recorded on the human scalp originating from brain grey matter. EEG is one of the favorite methods to study and understand processes that underlie behavior. This is so, because EEG is relatively cheap, easy to wear, light weight and has high temporal resolution. In terms of behavior, this encompasses actions, such as movements, that are performed in response to the environment. However, there are methodological difficulties when recording EEG during movement such as movement artifacts. Thus, most studies about the human brain have examined activations during static conditions. This article attempts to compile and describe relevant methodological solutions that emerged in order to measure body and brain dynamics during motion. These descriptions cover suggestions of how to avoid and reduce motion artifacts, hardware, software and techniques for synchronously recording EEG, EMG, kinematics, kinetics and eye movements during motion. Additionally, we present various recording systems, EEG electrodes, caps and methods for determination of real/custom electrode positions. In the end we will conclude that it is possible to record and analyze synchronized brain and body dynamics related to movement or exercise tasks.
Full Text Available Recent advances in neuroscience have raised the hypothesis that the underlying pattern of neuronal activation which results in electroencephalography (EEG signals is via power-law distributed neuronal avalanches, while EEG signals are nonstationary. Therefore, spectral analysis of EEG may miss many properties inherent in such signals. A complete understanding of such dynamical systems requires knowledge of the underlying nonequilibrium thermodynamics. In recent work by Fielitz and Borchardt (2011, 2014, the concept of information equilibrium (IE in information transfer processes has successfully characterized many different systems far from thermodynamic equilibrium. We utilized a publicly available database of polysomnogram EEG data from fourteen subjects with eight different one-minute tracings of sleep stage 2 and waking and an overlapping set of eleven subjects with eight different one-minute tracings of sleep stage 3. We applied principles of IE to model EEG as a system that transfers (equilibrates information from the time domain to scalp-recorded voltages. We find that waking consciousness is readily distinguished from sleep stages 2 and 3 by several differences in mean information transfer constants. Principles of IE applied to EEG may therefore prove to be useful in the study of changes in brain function more generally.
Næss, Solveig; Chintaluri, Chaitanya; Ness, Torbjørn V; Dale, Anders M; Einevoll, Gaute T; Wójcik, Daniel K
The EEG signal is generated by electrical brain cell activity, often described in terms of current dipoles. By applying EEG forward models we can compute the contribution from such dipoles to the electrical potential recorded by EEG electrodes. Forward models are key both for generating understanding and intuition about the neural origin of EEG signals as well as inverse modeling, i.e., the estimation of the underlying dipole sources from recorded EEG signals. Different models of varying complexity and biological detail are used in the field. One such analytical model is the four-sphere model which assumes a four-layered spherical head where the layers represent brain tissue, cerebrospinal fluid (CSF), skull, and scalp, respectively. While conceptually clear, the mathematical expression for the electric potentials in the four-sphere model is cumbersome, and we observed that the formulas presented in the literature contain errors. Here, we derive and present the correct analytical formulas with a detailed derivation. A useful application of the analytical four-sphere model is that it can serve as ground truth to test the accuracy of numerical schemes such as the Finite Element Method (FEM). We performed FEM simulations of the four-sphere head model and showed that they were consistent with the corrected analytical formulas. For future reference we provide scripts for computing EEG potentials with the four-sphere model, both by means of the correct analytical formulas and numerical FEM simulations.
Full Text Available The EEG signal is generated by electrical brain cell activity, often described in terms of current dipoles. By applying EEG forward models we can compute the contribution from such dipoles to the electrical potential recorded by EEG electrodes. Forward models are key both for generating understanding and intuition about the neural origin of EEG signals as well as inverse modeling, i.e., the estimation of the underlying dipole sources from recorded EEG signals. Different models of varying complexity and biological detail are used in the field. One such analytical model is the four-sphere model which assumes a four-layered spherical head where the layers represent brain tissue, cerebrospinal fluid (CSF, skull, and scalp, respectively. While conceptually clear, the mathematical expression for the electric potentials in the four-sphere model is cumbersome, and we observed that the formulas presented in the literature contain errors. Here, we derive and present the correct analytical formulas with a detailed derivation. A useful application of the analytical four-sphere model is that it can serve as ground truth to test the accuracy of numerical schemes such as the Finite Element Method (FEM. We performed FEM simulations of the four-sphere head model and showed that they were consistent with the corrected analytical formulas. For future reference we provide scripts for computing EEG potentials with the four-sphere model, both by means of the correct analytical formulas and numerical FEM simulations.
Anthony D. Bateson
Full Text Available Researchers are increasingly attempting to undertake electroencephalography (EEG recordings in novel environments and contexts outside of the traditional static laboratory setting. The term “mobile EEG,” although commonly used to describe many of these undertakings, is ambiguous, since it attempts to encompass a wide range of EEG device mobility, participant mobility, and system specifications used across investigations. To provide quantitative parameters for “mobile EEG,” we developed a Categorisation of Mobile EEG (CoME scheme based upon scoring of device mobility (D, from 0, off-body, to 5, head-mounted with no additional equipment, participant mobility (P, from 0, static, to 5, unconstrained running, system specification (S, from 4, lowest, to 20, highest, and number of channels (C used. The CoME scheme was applied to twenty-nine published mobile EEG studies. Device mobility scores ranged from 0D to 4D, participant mobility scores from 0P to 4P, and system specification scores from 6S to 17S. The format of the scores for the four parameters is given, for example, as (2D, 4P, 17S, 32C and readily enables comparisons across studies. Our CoME scheme enables researchers to quantify the degree of device mobility, participant mobility, and system specification used in their “mobile EEG” investigations in a standardised way.
Garces Correa, A [Gabinete de TecnologIa Medica, Facultad de Ingenieria, Universidad Nacional de San Juan (Argentina); Laciar, E [Gabinete de TecnologIa Medica, Facultad de Ingenieria, Universidad Nacional de San Juan (Argentina); Patino, H D [Instituto de Automatica, Facultad de Ingenieria, Universidad Nacional de San Juan (Argentina); Valentinuzzi, M E [Instituto Superior de Investigaciones Biologicas (INSIBIO), UNT-CONICET, Tucuman (Argentina)
Artifacts in EEG (electroencephalogram) records are caused by various factors, like line interference, EOG (electro-oculogram) and ECG (electrocardiogram). These noise sources increase the difficulty in analyzing the EEG and to obtaining clinical information. For this reason, it is necessary to design specific filters to decrease such artifacts in EEG records. In this paper, a cascade of three adaptive filters based on a least mean squares (LMS) algorithm is proposed. The first one eliminates line interference, the second adaptive filter removes the ECG artifacts and the last one cancels EOG spikes. Each stage uses a finite impulse response (FIR) filter, which adjusts its coefficients to produce an output similar to the artifacts present in the EEG. The proposed cascade adaptive filter was tested in five real EEG records acquired in polysomnographic studies. In all cases, line-frequency, ECG and EOG artifacts were attenuated. It is concluded that the proposed filter reduces the common artifacts present in EEG signals without removing significant information embedded in these records.
Kafashan, MohammadMehdi; Ryu, Shoko; Hargis, Mitchell J; Laurido-Soto, Osvaldo; Roberts, Debra E; Thontakudi, Akshay; Eisenman, Lawrence; Kummer, Terrance T; Ching, ShiNung
Rapidly determining the causes of a depressed level of consciousness (DLOC) including coma is a common clinical challenge. Quantitative analysis of the electroencephalogram (EEG) has the potential to improve DLOC assessment by providing readily deployable, temporally detailed characterization of brain activity in such patients. While used commonly for seizure detection, EEG-based assessment of DLOC etiology is less well-established. As a first step towards etiological diagnosis, we sought to distinguish focal and diffuse causes of DLOC through assessment of temporal dynamics within EEG signals. We retrospectively analyzed EEG recordings from 40 patients with DLOC with consensus focal or diffuse culprit pathology. For each recording, we performed a suite of time-series analyses, then used a statistical framework to identify which analyses (features) could be used to distinguish between focal and diffuse cases. Using cross-validation approaches, we identified several spectral and non-spectral EEG features that were significantly different between DLOC patients with focal vs. diffuse etiologies, enabling EEG-based classification with an accuracy of 76%. Our findings suggest that DLOC due to focal vs. diffuse injuries differ along several electrophysiological parameters. These results may form the basis of future classification strategies for DLOC and coma that are more etiologically-specific and therefore therapeutically-relevant.
Bach Justesen, Anders; Eskelund Johansen, Ann Berit; Martinussen, Noomi Ida; Wasserman, Danielle; Terney, Daniella; Meritam, Pirgit; Gardella, Elena; Beniczky, Sándor
To investigate the diagnostic added value of supplementing the 10-20 EEG array with six electrodes in the inferior temporal chain. EEGs were recorded with 25 electrodes: 19 positions of the 10-20 system, and six additional electrodes in the inferior temporal chain (F9/10, T9/10, P9/10). Five-hundred consecutive standard and sleep EEG recordings were reviewed using the 10-20 array and the extended array. We identified the recordings with EEG abnormalities that had peak negativities at the inferior temporal electrodes, and those that only were visible at the inferior temporal electrodes. From the 286 abnormal recordings, the peak negativity was at the inferior temporal electrodes in 81 cases (28.3%) and only visible at the inferior temporal electrodes in eight cases (2.8%). In the sub-group of patients with temporal abnormalities (n = 134), these represented 59% (peak in the inferior chain) and 6% (only seen at the inferior chain). Adding six electrodes in the inferior temporal electrode chain to the 10-20 array improves the localization and identification of EEG abnormalities, especially those located in the temporal region. Our results suggest that inferior temporal electrodes should be added to the EEG array, to increase the diagnostic yield of the recordings. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
Pastena, Lucio; Formaggio, Emanuela; Faralli, Fabio; Melucci, Massimo; Rossi, Marco; Gagliardi, Riccardo; Ricciardi, Lucio; Storti, Silvia F
Recording biological signals inside a hyperbaric chamber poses technical challenges (the steel walls enclosing it greatly attenuate or completely block the signals as in a Faraday cage), practical (lengthy cables creating eddy currents), and safety (sparks hazard from power supply to the electronic apparatus inside the chamber) which can be overcome with new wireless technologies. In this technical report we present the design and implementation of a Bluetooth system for electroencephalographic (EEG) recording inside a hyperbaric chamber and describe the feasibility of EEG signal transmission outside the chamber. Differently from older systems, this technology allows the online recording of amplified signals, without interference from eddy currents. In an application of this technology, we measured EEG activity in professional divers under three experimental conditions in a hyperbaric chamber to determine how oxygen, assumed at a constant hyperbaric pressure of 2.8 ATA , affects the bioelectrical activity. The EEG spectral power estimated by fast Fourier transform and the cortical sources of the EEG rhythms estimated by low-resolution brain electromagnetic analysis were analyzed in three different EEG acquisitions: breathing air at sea level; breathing oxygen at a simulated depth of 18 msw, and breathing air at sea level after decompression.
Full Text Available Sonification refers to a process by which data are converted into sound, providing an auditory alternative to visual display. Currently, the prevalent method for diagnosing seizures in epilepsy is by visually reading a patient’s electroencephalogram (EEG. However, sonification of the EEG data provides certain advantages due to the nature of human auditory perception. We hypothesized that human listeners will be able to identify seizures from EEGs using the auditory modality alone, and that accuracy of seizure identification will increase after a short training session. Here we describe an algorithm we have used to sonify EEGs of both seizure and non-seizure activity, followed by a training study in which subjects listened to short clips of sonified EEGs and determine whether each clip was of seizure or normal activity, both before and after a short training session. Results show that before training subjects performed at chance level in differentiating seizures vs. non-seizures, but there was a significant improvement of accuracy after the training session. After training, subjects successfully distinguished seizures from non-seizures using the auditory modality alone. Further analyses using signal detection theory demonstrated improvement in sensitivity and reduction in response bias as a result of training. This study demonstrates the potential of sonified EEGs to be used for the detection of seizures. Future studies will attempt to increase accuracy using novel training and sonification modifications, with the goals of managing, predicting, and ultimately controlling seizures using sonification as a possible biofeedback-based intervention for epilepsy.
Chiarelli, Antonio Maria; Croce, Pierpaolo; Merla, Arcangelo; Zappasodi, Filippo
Objective. Brain–computer interface (BCI) refers to procedures that link the central nervous system to a device. BCI was historically performed using electroencephalography (EEG). In the last years, encouraging results were obtained by combining EEG with other neuroimaging technologies, such as functional near infrared spectroscopy (fNIRS). A crucial step of BCI is brain state classification from recorded signal features. Deep artificial neural networks (DNNs) recently reached unprecedented complex classification outcomes. These performances were achieved through increased computational power, efficient learning algorithms, valuable activation functions, and restricted or back-fed neurons connections. By expecting significant overall BCI performances, we investigated the capabilities of combining EEG and fNIRS recordings with state-of-the-art deep learning procedures. Approach. We performed a guided left and right hand motor imagery task on 15 subjects with a fixed classification response time of 1 s and overall experiment length of 10 min. Left versus right classification accuracy of a DNN in the multi-modal recording modality was estimated and it was compared to standalone EEG and fNIRS and other classifiers. Main results. At a group level we obtained significant increase in performance when considering multi-modal recordings and DNN classifier with synergistic effect. Significance. BCI performances can be significantly improved by employing multi-modal recordings that provide electrical and hemodynamic brain activity information, in combination with advanced non-linear deep learning classification procedures.
Koo, Bonkon; Lee, Hwan-Gon; Nam, Yunjun; Kang, Hyohyeong; Koh, Chin Su; Shin, Hyung-Cheul; Choi, Seungjin
For a self-paced motor imagery based brain-computer interface (BCI), the system should be able to recognize the occurrence of a motor imagery, as well as the type of the motor imagery. However, because of the difficulty of detecting the occurrence of a motor imagery, general motor imagery based BCI studies have been focusing on the cued motor imagery paradigm. In this paper, we present a novel hybrid BCI system that uses near infrared spectroscopy (NIRS) and electroencephalography (EEG) systems together to achieve online self-paced motor imagery based BCI. We designed a unique sensor frame that records NIRS and EEG simultaneously for the realization of our system. Based on this hybrid system, we proposed a novel analysis method that detects the occurrence of a motor imagery with the NIRS system, and classifies its type with the EEG system. An online experiment demonstrated that our hybrid system had a true positive rate of about 88%, a false positive rate of 7% with an average response time of 10.36 s. As far as we know, there is no report that explored hemodynamic brain switch for self-paced motor imagery based BCI with hybrid EEG and NIRS system. From our experimental results, our hybrid system showed enough reliability for using in a practical self-paced motor imagery based BCI. Copyright © 2014 Elsevier B.V. All rights reserved.
Zander, Thorsten O; Andreessen, Lena M; Berg, Angela; Bleuel, Maurice; Pawlitzki, Juliane; Zawallich, Lars; Krol, Laurens R; Gramann, Klaus
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.
Full Text Available The advertising industry depends on an effective assessment of the impact of advertising as a key performance metric for their products. However, current assessment methods have relied on either indirect inference from observing changes in consumer behavior after the launch of an advertising campaign, which has long cycle times and requires an ad campaign to have already have been launched (often meaning costs having been sunk. Or through surveys or focus groups, which have a potential for experimental biases, peer pressure, and other psychological and sociological phenomena that can reduce the effectiveness of the study. In this paper, we investigate a new approach to assess the impact of advertisement by utilizing low-cost EEG headbands to record and assess the measurable impact of advertising on the brain. Our evaluation shows the desired performance of our method based on user experiment with 30 recruited subjects after watching 220 different advertisements. We believe the proposed SVM method can be further developed to a general and scalable methodology that can enable advertising agencies to assess impact rapidly, quantitatively, and without bias.
Wei, Zhen; Wu, Chao; Wang, Xiaoyi; Supratak, Akara; Wang, Pan; Guo, Yike
The advertising industry depends on an effective assessment of the impact of advertising as a key performance metric for their products. However, current assessment methods have relied on either indirect inference from observing changes in consumer behavior after the launch of an advertising campaign, which has long cycle times and requires an ad campaign to have already have been launched (often meaning costs having been sunk). Or through surveys or focus groups, which have a potential for experimental biases, peer pressure, and other psychological and sociological phenomena that can reduce the effectiveness of the study. In this paper, we investigate a new approach to assess the impact of advertisement by utilizing low-cost EEG headbands to record and assess the measurable impact of advertising on the brain. Our evaluation shows the desired performance of our method based on user experiment with 30 recruited subjects after watching 220 different advertisements. We believe the proposed SVM method can be further developed to a general and scalable methodology that can enable advertising agencies to assess impact rapidly, quantitatively, and without bias.
Aziz, Fayeem; Arof, Hamzah; Mokhtar, Norrima; Mubin, Marizan
This paper presents a wheelchair navigation system based on a hidden Markov model (HMM), which we developed to assist those with restricted mobility. The semi-autonomous system is equipped with obstacle/collision avoidance sensors and it takes the electrooculography (EOG) signal traces from the user as commands to maneuver the wheelchair. The EOG traces originate from eyeball and eyelid movements and they are embedded in EEG signals collected from the scalp of the user at three different locations. Features extracted from the EOG traces are used to determine whether the eyes are open or closed, and whether the eyes are gazing to the right, center, or left. These features are utilized as inputs to a few support vector machine (SVM) classifiers, whose outputs are regarded as observations to an HMM. The HMM determines the state of the system and generates commands for navigating the wheelchair accordingly. The use of simple features and the implementation of a sliding window that captures important signatures in the EOG traces result in a fast execution time and high classification rates. The wheelchair is equipped with a proximity sensor and it can move forward and backward in three directions. The asynchronous system achieved an average classification rate of 98% when tested with online data while its average execution time was less than 1 s. It was also tested in a navigation experiment where all of the participants managed to complete the tasks successfully without collisions.
Full Text Available Recent years have witnessed a rapid development of brain-computer interface (BCI technology. An independent BCI is a communication system for controlling a device by human intension, e.g., a computer, a wheelchair or a neuroprosthes is, not depending on the brain’s normal output pathways of peripheral nerves and muscles, but on detectable signals that represent responsive or intentional brain activities. This paper presents a comparative study of the usage of the linear discriminant analysis (LDA and the naive Bayes (NB classifiers on describing both right- and left-hand movement through electroencephalographic signal (EEG acquisition. For the analysis, we considered the following input features: the energy of the segments of a band pass-filtered signal with the frequency band in sensorimotor rhythms and the components of the spectral energy obtained through the Welch method. We also used the common spatial pattern (CSP filter, so as to increase the discriminatory activity among movement classes. By using the database generated by this experiment, we obtained hit rates up to 70%. The results are compatible with previous studies.
Rakshasbhuvankar, Abhijeet; Rao, Shripada; Palumbo, Linda; Ghosh, Soumya; Nagarajan, Lakshmi
This diagnostic accuracy study compared the accuracy of seizure detection by amplitude-integrated electroencephalography with the criterion standard conventional video EEG in term and near-term infants at risk of seizures. Simultaneous recording of amplitude-integrated EEG (2-channel amplitude-integrated EEG with raw trace) and video EEG was done for 24 hours for each infant. Amplitude-integrated EEG was interpreted by a neonatologist; video EEG was interpreted by a neurologist independently. Thirty-five infants were included in the analysis. In the 7 infants with seizures on video EEG, there were 169 seizure episodes on video EEG, of which only 57 were identified by amplitude-integrated EEG. Amplitude-integrated EEG had a sensitivity of 33.7% for individual seizure detection. Amplitude-integrated EEG had an 86% sensitivity for detection of babies with seizures; however, it was nonspecific, in that 50% of infants with seizures detected by amplitude-integrated EEG did not have true seizures by video EEG. In conclusion, our study suggests that amplitude-integrated EEG is a poor screening tool for neonatal seizures.
Giorgi, Filippo S; Perini, Daria; Maestri, Michelangelo; Guida, Melania; Pizzanelli, Chiara; Caserta, Anna; Iudice, Alfonso; Bonanni, Enrica
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.
Design of liquid metal cooled fast reactors (LMFRs) is still in evolution, and only a small number of LMFRs are in operation around the world. Specialists operating these LMFRs have gained valuable experience from incidents, failures, and other events that took place in the reactors. These unusual occurrences, lessons learned and measures undertaken to prevent recurrences are often either not reported in the literature, or reported only briefly and without sufficient detail. Hence there is a need for specialists designing and operating LMFRs to share their knowledge on unusual occurrences. Considerable experimental and theoretical knowledge in this field were collected by several Member states over the past decades. The needs in generalisation, review and documentation of fundamental knowledge in liquid metal cooled reactor technology were a major consideration in the recommendation by the International Working group on fast reactors for the IAEA to convene this Technical Committee meeting on the subject of unusual occurrences during LMFR operation and the consequences for reactor systems
Full Text Available Flow experience is a subjective state experienced during holistic involvement in a certain activity, which has been reported to function as a factor promoting motivation, skill development, and better performance in the activity. To verify the positive effects of flow and develop a method to utilize it, the establishment of a reliable measurement of the flow state is essential. The present study utilized an electroencephalogram (EEG during an experimentally evoked flow state and examined the possibility of objective measurement of immediate flow. A total of 16 participants (10 males, 6 females participated in the experiment that employed a mental arithmetic task developed in a previous study. Post-trial self-report of the flow state and EEG during task execution were measured and compared among three conditions (Boredom, Flow, and Overload that had different levels of task difficulty. Furthermore, the correlations between subjective flow items and EEG activity were examined. As expected, the ratings on the subjective evaluation items representing the flow state were the highest in the Flow condition. Regarding the EEG data, theta activities in the frontal areas were higher in the Flow and the Overload conditions than in the Boredom condition, and alpha activity in the frontal areas and the right central area gradually increased depending on the task difficulty. These EEG activities correlated with self-reported flow experience, especially items related to the concentration on the task and task difficulty. From the results, the flow state was characterized by increased theta activities in the frontal areas and moderate alpha activities in the frontal and central areas. The former may be related to a high level of cognitive control and immersion in task, and the latter suggests that the load on the working memory was not excessive. The findings of this study suggest the possibility of distinguishing the flow state from other states using multiple
Katahira, Kenji; Yamazaki, Yoichi; Yamaoka, Chiaki; Ozaki, Hiroaki; Nakagawa, Sayaka; Nagata, Noriko
Flow experience is a subjective state experienced during holistic involvement in a certain activity, which has been reported to function as a factor promoting motivation, skill development, and better performance in the activity. To verify the positive effects of flow and develop a method to utilize it, the establishment of a reliable measurement of the flow state is essential. The present study utilized an electroencephalogram (EEG) during an experimentally evoked flow state and examined the possibility of objective measurement of immediate flow. A total of 16 participants (10 males, 6 females) participated in the experiment that employed a mental arithmetic task developed in a previous study. Post-trial self-report of the flow state and EEG during task execution were measured and compared among three conditions (Boredom, Flow, and Overload) that had different levels of task difficulty. Furthermore, the correlations between subjective flow items and EEG activity were examined. As expected, the ratings on the subjective evaluation items representing the flow state were the highest in the Flow condition. Regarding the EEG data, theta activities in the frontal areas were higher in the Flow and the Overload conditions than in the Boredom condition, and alpha activity in the frontal areas and the right central area gradually increased depending on the task difficulty. These EEG activities correlated with self-reported flow experience, especially items related to the concentration on the task and task difficulty. From the results, the flow state was characterized by increased theta activities in the frontal areas and moderate alpha activities in the frontal and central areas. The former may be related to a high level of cognitive control and immersion in task, and the latter suggests that the load on the working memory was not excessive. The findings of this study suggest the possibility of distinguishing the flow state from other states using multiple EEG activities
Loreck, Charlotte; Matthes, Felix C.; Hermann, Hauke; Jung, Frederieke; Emele, Lukas
At 15th October, 2012 the transmission system operators had published the EEG apportionment (EEG - Energy Economy Law). For the year 2013. This apportionment amounts 5,277 ct/kWh for non-privileged consumers in comparison to 3,59 ct/kWh for the year 2012. The ongoing enhancement of the renewable energies increases the EEG apportionment by an amount of 0.74 ct/kWh. With 0.26 ct/kWh the photovoltaics has the largest proportion in comparison to photovoltaics. The power generation from biomass as well as from wind energy at onshore sites contribute with 0.21 ct/kWh to the EEG apportionment. The greatest item of 0.48 ct/kWh is the debit balancing of the EEG account. The liquidity reserve for the year 2013 will be enhanced to 10% of the budget deficit. The expansion of the privileged status of the power consumption increases the EEG apportionment by 0.12 ct/kWh.
Gao, Lin; Cheng, Wei; Zhang, Jinhua; Wang, Jue
Brain-computer interface (BCI) systems provide an alternative communication and control approach for people with limited motor function. Therefore, the feature extraction and classification approach should differentiate the relative unusual state of motion intention from a common resting state. In this paper, we sought a novel approach for multi-class classification in BCI applications. We collected electroencephalographic (EEG) signals registered by electrodes placed over the scalp during left hand motor imagery, right hand motor imagery, and resting state for ten healthy human subjects. We proposed using the Kolmogorov complexity (Kc) for feature extraction and a multi-class Adaboost classifier with extreme learning machine as base classifier for classification, in order to classify the three-class EEG samples. An average classification accuracy of 79.5% was obtained for ten subjects, which greatly outperformed commonly used approaches. Thus, it is concluded that the proposed method could improve the performance for classification of motor imagery tasks for multi-class samples. It could be applied in further studies to generate the control commands to initiate the movement of a robotic exoskeleton or orthosis, which finally facilitates the rehabilitation of disabled people.
Marics, Gábor; Csekő, Anna; Vásárhelyi, Barna; Zakariás, Dávid; Schuster, György; Szabó, Miklós
Background Amplitude-integrated electroencephalography (aEEG) is a useful tool to determine the severity of neonatal hypoxic-ischemic encephalopathy (HIE). Our aim was to assess the prevalence and study the origin of false normal aEEG recordings based on 85 aEEG recordings registered before six hours of age. Methods Raw EEG recordings were reevaluated retrospectively with Fourier analysis to identify and describe the frequency patterns of the raw EEG signal, in cases with inconsistent aEEG re...
Runnova, Anastasiya E.; Grubov, Vadim V.; Khramova, Marina V.; Hramov, Alexander E.
In the paper we propose the new method for removing noise and physiological artifacts in human EEG recordings based on empirical mode decomposition (Hilbert-Huang transform). As physiological artifacts we consider specific oscillatory patterns that cause problems during EEG analysis and can be detected with additional signals recorded simultaneously with EEG (ECG, EMG, EOG, etc.) We introduce the algorithm of the proposed method with steps including empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing these empirical modes and reconstructing of initial EEG signal. We show the efficiency of the method on the example of filtration of human EEG signal from eye-moving artifacts.
Hansen, Sofie Therese; Hansen, Lars Kai
the functional dynamics of the brain. Solving the inverse problem of EEG is however highly ill-posed as there are many more potential locations of the EEG generators than EEG measurement points. Several well-known properties of brain dynamics can be exploited to alleviate this problem. More short ranging......Electroencephalography (EEG) can capture brain dynamics in high temporal resolution. By projecting the scalp EEG signal back to its origin in the brain also high spatial resolution can be achieved. Source localized EEG therefore has potential to be a very powerful tool for understanding...
Treder, Matthias S.; Purwins, Hendrik; Miklody, Daniel
. Here, we explore polyphonic music as a novel stimulation approach for future use in a brain-computer interface. In a musical oddball experiment, we had participants shift selective attention to one out of three different instruments in music audio clips, with each instrument occasionally playing one...... 11 participants. This is a proof of concept that attention paid to a particular instrument in polyphonic music can be inferred from ongoing EEG, a finding that is potentially relevant for both brain-computer interface and music research....
Ogawa, Yutaro; Ikeda, Akira; Kotani, Kiyoshi; Jimbo, Yasuhiko
In this study, we propose the EEG phase synchronization analysis including not only the average strength of the synchronization but also the distribution and directions under the conditions that evoked emotion by musical stimuli. The experiment is performed with the two different musical stimuli that evoke happiness or sadness for 150 seconds. It is found that the average strength of synchronization indicates no difference between the right side and the left side of the frontal lobe during the happy stimulus, the distribution and directions indicate significant differences. Therefore, proposed analysis is useful for detecting emotional condition because it provides information that cannot be obtained only by the average strength of synchronization.
Snyder, Adam C.
The development and refinement of noninvasive techniques for imaging neural activity is of paramount importance for human neuroscience. Currently, the most accessible and popular technique is electroencephalography (EEG). However, nearly all of what we know about the neural events that underlie EEG signals is based on inference, because of the dearth of studies that have simultaneously paired EEG recordings with direct recordings of single neurons. From the perspective of electrophysiologists there is growing interest in understanding how spiking activity coordinates with large-scale cortical networks. Evidence from recordings at both scales highlights that sensory neurons operate in very distinct states during spontaneous and visually evoked activity, which appear to form extremes in a continuum of coordination in neural networks. We hypothesized that individual neurons have idiosyncratic relationships to large-scale network activity indexed by EEG signals, owing to the neurons' distinct computational roles within the local circuitry. We tested this by recording neuronal populations in visual area V4 of rhesus macaques while we simultaneously recorded EEG. We found substantial heterogeneity in the timing and strength of spike-EEG relationships and that these relationships became more diverse during visual stimulation compared with the spontaneous state. The visual stimulus apparently shifts V4 neurons from a state in which they are relatively uniformly embedded in large-scale network activity to a state in which their distinct roles within the local population are more prominent, suggesting that the specific way in which individual neurons relate to EEG signals may hold clues regarding their computational roles. PMID:26108954
Hsu, Sheng-Hsiou; Jung, Tzyy-Ping
Objective. As a human brain performs various cognitive functions within ever-changing environments, states of the brain characterized by recorded brain activities such as electroencephalogram (EEG) are inevitably nonstationary. The challenges of analyzing the nonstationary EEG signals include finding neurocognitive sources that underlie different brain states and using EEG data to quantitatively assess the state changes. Approach. This study hypothesizes that brain activities under different states, e.g. levels of alertness, can be modeled as distinct compositions of statistically independent sources using independent component analysis (ICA). This study presents a framework to quantitatively assess the EEG source nonstationarity and estimate levels of alertness. The framework was tested against EEG data collected from 10 subjects performing a sustained-attention task in a driving simulator. Main results. Empirical results illustrate that EEG signals under alert versus drowsy states, indexed by reaction speeds to driving challenges, can be characterized by distinct ICA models. By quantifying the goodness-of-fit of each ICA model to the EEG data using the model deviation index (MDI), we found that MDIs were significantly correlated with the reaction speeds (r = -0.390 with alertness models and r = 0.449 with drowsiness models) and the opposite correlations indicated that the two models accounted for sources in the alert and drowsy states, respectively. Based on the observed source nonstationarity, this study also proposes an online framework using a subject-specific ICA model trained with an initial (alert) state to track the level of alertness. For classification of alert against drowsy states, the proposed online framework achieved an averaged area-under-curve of 0.745 and compared favorably with a classic power-based approach. Significance. This ICA-based framework provides a new way to study changes of brain states and can be applied to
Cho, Hohyun; Ahn, Minkyu; Ahn, Sangtae; Kwon, Moonyoung; Jun, Sung Chan
Most investigators of brain-computer interface (BCI) research believe that BCI can be achieved through induced neuronal activity from the cortex, but not by evoked neuronal activity. Motor imagery (MI)-based BCI is one of the standard concepts of BCI, in that the user can generate induced activity by imagining motor movements. However, variations in performance over sessions and subjects are too severe to overcome easily; therefore, a basic understanding and investigation of BCI performance variation is necessary to find critical evidence of performance variation. Here we present not only EEG datasets for MI BCI from 52 subjects, but also the results of a psychological and physiological questionnaire, EMG datasets, the locations of 3D EEG electrodes, and EEGs for non-task-related states. We validated our EEG datasets by using the percentage of bad trials, event-related desynchronization/synchronization (ERD/ERS) analysis, and classification analysis. After conventional rejection of bad trials, we showed contralateral ERD and ipsilateral ERS in the somatosensory area, which are well-known patterns of MI. Finally, we showed that 73.08% of datasets (38 subjects) included reasonably discriminative information. Our EEG datasets included the information necessary to determine statistical significance; they consisted of well-discriminated datasets (38 subjects) and less-discriminative datasets. These may provide researchers with opportunities to investigate human factors related to MI BCI performance variation, and may also achieve subject-to-subject transfer by using metadata, including a questionnaire, EEG coordinates, and EEGs for non-task-related states. © The Authors 2017. Published by Oxford University Press.
Herbert P von Schroeder
Full Text Available A healthy male farm employee developed an unusual infection caused by Pasteurella multocida. Atypical features included the chronic nature of the infection, the development of osteomyelitis of the tibia without direct animal inoculation, and lack of fever and leukocytosis. Radiographic appearance of P multocida osteomyelitis may be the result of osteoclast activation and can be confused with musculoskeletal tumour. P multocida infection requires a high degree of suspicion, and should be considered in cases of farm- or animal-related injuries even if there is no history of direct animal contact.
Full Text Available Extraskeletal chondrosarcoma in anterior mediastinum is very rare. A 45-year-old male patient was admitted to the hospital with precordial chest pain. A large and well-shaped mass in the anterior mediastinum was seen radiologically, and there was a clearly compression of the heart by the mass. The lesion was totally resected, and extraskeletal mediastinal chondrosarcoma was histopathologically diagnosed. We aimed to present and discuss the radiologic, clinic, and histopathologic features of unusual presentation of extraskeletal chondrosarcoma in a case.
Orrapin, Saranat; Arworn, Supapong; Wisetborisut, Anawat
Hypothenar hammer syndrome (HHS) is a rare occupational disease. The risk group of HHS is patient whose dominate hand used as a hammer. Our study report unusually cases in Chiang Mai University Hospital. 19 year-old basketball player had right ulnar artery aneurysm for two months. After operation, his symptom was relieved and returned to play basketball again. 65 year-old housekeeper had non-dominated hand ulnar artery aneurysm for two years. After operation she still had hand claudication due to poor run-off vessel. HHS is previously state in risk group. But from our report there was a risk in different occupation.
Reis, Brisa Dondoni; Cobucci, Fernanda Oliveira; Zacaron, Luciana Helena; D'Acri, Antonio Macedo; Lima, Ricardo Barbosa; Martins, Carlos José
Sporotrichosis is the most common subcutaneous mycosis. It is caused by the dimorphic fungus Sporothrix schenckii, and the infection is usually acquired by traumatic inoculation. We describe a case of sporotrichosis in an uncommon location with an unusual mode of transmission. A 49-year-old female patient who lived in an urban area of Rio de Janeiro presented with involvement of the left ear. No history of contact with soil, plants or animals was elicited. The suspected source of infection was a pair of handmade wooden earrings. The delay in the diagnosis and treatment resulted in higher morbidity, unsightly scarring and loss of ear lobe. PMID:26312682
Blaskovich, Mark A T
Unusual amino acids are fundamental building blocks of modern medicinal chemistry. The combination of readily functionalized amine and carboxyl groups attached to a chiral central core along with one or two potentially diverse side chains provides a unique three-dimensional structure with a high degree of functionality. This makes them invaluable as starting materials for syntheses of complex molecules, highly diverse elements for SAR campaigns, integral components of peptidomimetic drugs, and potential drugs on their own. This Perspective highlights the diversity of unnatural amino acid structures found in hit-to-lead and lead optimization campaigns and clinical stage and approved drugs, reflecting their increasingly important role in medicinal chemistry.
Bachrach, S.M.; Ritchie, J.P.
We have applied the topological method to a number of organolithium compounds. The wavefunctions were determined with GAUSSIAN-82 using 3-21G basis set and fully optimized geometries. Gradient paths were obtained using the RHODER package and critical points were located using EXTREME. These results indicate the unusual nature of organolithium compounds. The strange bond paths arise mainly from the ionic nature of the C-Li interaction. We suggest that the term ''bond path'' may best be suited for covalent bonds. 4 figs., 1 tab
Full Text Available Lymphatic filariasis is a major public health problem in tropical countries and India is endemic for it. However, lymphatic filariasis presenting as pleural effusion is an unusual manifestation and finding microfilaria in pleural effusion without any lung pathology is rare. We report a case of pleural effusion without any underlying lung pathology and normal blood picture. Clinical cure occurred after treatment with diethyl-carbamazepine. Filariasis should be kept in view while considering the differential diagnosis of idiopathic pleural effusion, especially in endemic countries.
Kristin N. Fiorino
Full Text Available A 10-year-old boy presented with a 3-day history of worsening abdominal pain, fever, emesis and melena. Abdominal ultrasound revealed a right upper quadrant mass that was confirmed by computed tomography angiogram (CTA, which showed an 8 cm well-defined retroperitoneal vascular mass. 123Iodine metaiodobenzylguanidine (123MIBG scan indicated uptake only in the abdominal mass. Subsequent biopsy revealed a paraganglioma that was treated with chemotherapy. This case represents an unusual presentation of a paraganglioma associated with gastrointestinal (GI bleeding and highlights the utility of CTA and 123MIBG in evaluation and treatment.
Kimberly M. Thornton
Full Text Available We present an unusual case of hyperbilirubinemia with rapid early progression leading to bilirubin encephalopathy in a term neonate. Despite early recognition and intervention, the total serum bilirubin reached a maximum level of 39 mg/dL at 32 hours of life. Prior to an emergent exchange transfusion, the patient’s diagnostic evaluation was significant for Coombs-negative microangiopathic hemolytic anemia and thrombocytopenia. Further testing revealed a deficiency of ADAMTS13 protein, or von Willebrand factor-cleaving protease, a finding diagnostic of congenital thrombotic thrombocytopenic purpura, or Upshaw-Schulman syndrome. This rare disease is often misdiagnosed, especially in the newborn period.
Full Text Available The odontoameloblastoma (OA, also known as ameloblastic odontoma, is a very rare odontogenic tumor that is similar to ameloblastoma in its locally aggressive behavior. OA includes odontogenic ectomesenchyme in addition to odontogenic epithelium that resembles an ameloblastoma both in structure and in behavior. Its clinical presentation, however, often mimics the more innocuous odontoma, and hence, the recognition of its aggressive nature is commonly only ascertained after its histopathologic diagnosis following enucleation. This paper presents a rare case of OA with unusual clinical and radiological features.
Amin, M.U.; Rahan, T.; Haq, A.U.; Aftab, P.
A case of testicular choriocarcinoma is reported in which blood mixed stools and haemoptysis were the presenting manifestations as the patient never told about the testicular swelling to his parents. Orchidectomy was performed but the patient presented again with massive hematemesis due to gastric perforation secondary to gastric metastasis. The size of the testis at diagnosis was approximately 12 x 7cm. This was also unusual as testicular choriocarcinoma presents as a small mass. The patient eventually died of the complications within one month of diagnosis. (author)
Reber, T P; Do Lam, A T A; Axmacher, N; Elger, C E; Helmstaedter, C; Henke, K; Fell, J
Drawing inferences from past experiences enables adaptive behavior in future situations. Inference has been shown to depend on hippocampal processes. Usually, inference is considered a deliberate and effortful mental act which happens during retrieval, and requires the focus of our awareness. Recent fMRI studies hint at the possibility that some forms of hippocampus-dependent inference can also occur during encoding and possibly also outside of awareness. Here, we sought to further explore the feasibility of hippocampal implicit inference, and specifically address the temporal evolution of implicit inference using intracranial EEG. Presurgical epilepsy patients with hippocampal depth electrodes viewed a sequence of word pairs, and judged the semantic fit between two words in each pair. Some of the word pairs entailed a common word (e.g., "winter-red," "red-cat") such that an indirect relation was established in following word pairs (e.g., "winter-cat"). The behavioral results suggested that drawing inference implicitly from past experience is feasible because indirect relations seemed to foster "fit" judgments while the absence of indirect relations fostered "do not fit" judgments, even though the participants were unaware of the indirect relations. A event-related potential (ERP) difference emerging 400 ms post-stimulus was evident in the hippocampus during encoding, suggesting that indirect relations were already established automatically during encoding of the overlapping word pairs. Further ERP differences emerged later post-stimulus (1,500 ms), were modulated by the participants' responses and were evident during encoding and test. Furthermore, response-locked ERP effects were evident at test. These ERP effects could hence be a correlate of the interaction of implicit memory with decision-making. Together, the data map out a time-course in which the hippocampus automatically integrates memories from discrete but related episodes to implicitly influence future
Clausner, Tommy; Dalal, Sarang S; Crespo-García, Maité
The performance of EEG source reconstruction has benefited from the increasing use of advanced head modeling techniques that take advantage of MRI together with the precise positions of the recording electrodes. The prevailing technique for registering EEG electrode coordinates involves electromagnetic digitization. However, the procedure adds several minutes to experiment preparation and typical digitizers may not be accurate enough for optimal source reconstruction performance (Dalal et al., 2014). Here, we present a rapid, accurate, and cost-effective alternative method to register EEG electrode positions, using a single digital SLR camera, photogrammetry software, and computer vision techniques implemented in our open-source toolbox, janus3D . Our approach uses photogrammetry to construct 3D models from multiple photographs of the participant's head wearing the EEG electrode cap. Electrodes are detected automatically or semi-automatically using a template. The rigid facial features from these photo-based models are then surface-matched to MRI-based head reconstructions to facilitate coregistration to MRI space. This method yields a final electrode coregistration error of 0.8 mm, while a standard technique using an electromagnetic digitizer yielded an error of 6.1 mm. The technique furthermore reduces preparation time, and could be extended to a multi-camera array, which would make the procedure virtually instantaneous. In addition to EEG, the technique could likewise capture the position of the fiducial markers used in magnetoencephalography systems to register head position.
Schwartz, G E; Bell, I R; Dikman, Z V; Fernandez, M; Kline, J P; Peterson, J M; Wright, K P
Recent studies from the University of Arizona indicate that normal subjects, both college students and the elderly, can register the presence of low-intensity odors in the electroencephalogram (EEG) in the absence of conscious awareness of the odors. The experimental paradigm involves subjects sniffing pairs of bottles, one containing an odorant (e.g. isoamyl acetate) dissolved in an odorless solvent (water or liquid silicone), the other containing just the solvent, while 19 channels of EEG are continuously recorded. For the low-intensity odor conditions, concentrations are adjusted downward (decreased) until subjects correctly identify the odor bottle at chance (50%). The order of odorants, concentrations, and hand holding the control bottle, are counterbalanced within and across subjects. Three previous experiments found that alpha activity (8-12 hz) decreased in midline and posterior regions when subjects sniffed the low-intensity odors. The most recent study suggests that decreased theta activity (4-8 hz) may reflect sensory registration and decreased alpha activity may reflect perceptual registration. In a just completed experiment involving college students who were selected based on combinations of high and low scores on a scale measuring cacosmia (chemical odor intolerance) and high and low scores on a scale measuring depression, cacosmic subjects (independent of depression) showed greater decreases in low-frequency alpha (8-10 hz) and greater increases in low-frequency beta (12-16 hz) to the solvent propylene glycol compared to an empty bottle. Topographic EEG mapping to low-intensity odorants may provide a useful tool for investigating possible increased sensitivity to specific chemicals in chemically sensitive individuals.
Full Text Available Functional brain networks of human have been revealed to have small-world properties by both analyzing electroencephalogram (EEG and functional magnetic resonance imaging (fMRI time series.In our study, by using graph theoretical analysis, we attempted to investigate the changes of paralimbic-limbic cortex between wake and sleep states. Ten healthy young people were recruited to our experiment. Data from 2 subjects were excluded for the reason that they had not fallen asleep during the experiment. For each subject, blood oxygen level dependency (BOLD images were acquired to analyze brain network, and peripheral pulse signals were obtained continuously to identify if the subject was in sleep periods. Results of fMRI showed that brain networks exhibited stronger small-world characteristics during sleep state as compared to wake state, which was in consistent with previous studies using EEG synchronization. Moreover, we observed that compared with wake state, paralimbic-limbic cortex had less connectivity with neocortical system and centrencephalic structure in sleep.In conclusion, this is the first study, to our knowledge, has observed that small-world properties of brain functional networks altered when human sleeps without EEG synchronization. Moreover, we speculate that paralimbic-limbic cortex organization owns an efficient defense mechanism responsible for suppressing the external environment interference when humans sleep, which is consistent with the hypothesis that the paralimbic-limbic cortex may be functionally disconnected from brain regions which directly mediate their interactions with the external environment. Our findings also provide a reasonable explanation why stable sleep exhibits homeostasis which is far less susceptible to outside world.
Full Text Available Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The noninvasive nature of high-density electroencephalography (EEG recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP in sport. In this context, the hypotheses of unified brain rhythms and continuity between wake and sleep states should provide a functional template for EEG biomarkers in sport. The oscillations in the thalamo-cortical and hippocampal circuitry including the physiology of the place cells and the grid cells provide a frame of reference for the analysis of delta, theta, beta, alpha (incl.mu and gamma oscillations recorded in the space field of human performance. Based on recent neuronal models facilitating the distinction between the different dynamic regimes (selective gating and binding in these different oscillations we suggest an integrated approach articulating together the classical biomechanical factors (3D movements and EMG and the high-density EEG and ERP signals to allow finer mathematical analysis to optimize sport performance, such as microstates, coherency/directionality analysis and neural generators.
Cheron, Guy; Petit, Géraldine; Cheron, Julian; Leroy, Axelle; Cebolla, Anita; Cevallos, Carlos; Petieau, Mathieu; Hoellinger, Thomas; Zarka, David; Clarinval, Anne-Marie; Dan, Bernard
Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The non-invasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP) in sport. In this context, the hypotheses of unified brain rhythms and continuity between wake and sleep states should provide a functional template for EEG biomarkers in sport. The oscillations in the thalamo-cortical and hippocampal circuitry including the physiology of the place cells and the grid cells provide a frame of reference for the analysis of delta, theta, beta, alpha (incl.mu), and gamma oscillations recorded in the space field of human performance. Based on recent neuronal models facilitating the distinction between the different dynamic regimes (selective gating and binding) in these different oscillations we suggest an integrated approach articulating together the classical biomechanical factors (3D movements and EMG) and the high-density EEG and ERP signals to allow finer mathematical analysis to optimize sport performance, such as microstates, coherency/directionality analysis and neural generators. PMID:26955362
Full Text Available Recent Mobile Brain/Body Imaging (MoBI techniques based on active electrode scalp electroencephalogram (EEG allow the acquisition and real-time analysis of brain dynamics during active unrestrained motor behavior involving whole body movements such as treadmill walking, over-ground walking and other locomotive and non-locomotive tasks. Unfortunately, MoBI protocols are prone to physiological and non-physiological artifacts, including motion artifacts that may contaminate the EEG recordings. A few attempts have been made to quantify these artifacts during locomotion tasks but with inconclusive results due in part to methodological pitfalls. In this paper, we investigate the potential contributions of motion artifacts in scalp EEG during treadmill walking at three different speeds (1.5, 3.0, and 4.5 km/h using a wireless 64 channel active EEG system and a wireless inertial sensor attached to the subject’s head. The experimental setup was designed according to good measurement practices using state-of-the-art commercially-available instruments, and the measurements were analyzed using Fourier analysis and wavelet coherence approaches. Contrary to prior claims, the subjects’ motion did not significantly affect their EEG during treadmill walking although precaution should be taken when gait speeds approach 4.5 km/h. Overall, these findings suggest how MoBI methods may be safely deployed in neural, cognitive, and rehabilitation engineering applications.
Leblhuber, F.; Olschowski, A.; Deisenhammer, E.; Hammer, B.; Knauer, W.
The purpose of this study was to find out the value of postoperative EEG controls in the early detection of recurrence of supratentorial gliomas (the majority being astrocytomas, stage II to IV). 29 cases with verified tumour recurrence were examined and in all but one the EEG showed a reactivation of the focus in accordance with the development of the glioma. At least one of the following parameters had to be established: 1. a further spreading of the focal changes, 2. a reduction in frequency, 3. an increase in amplitudes and 4. focal depression and amplitudes. At least 3 postoperative EEG controls were made in each case. The duration of tumour treatment was 3 to 59 months. In 3 cases temporary focus activation was found without evidence of tumour recurrence; in one of these cases the activation was preceded by an epileptic seizure. Epileptic seizures, thus, seem to have a focus activating effect. Focus activation as a result of radiotherapy or cytostatic treatment was not observed. On the basis of our findings it appears that regularly conducted postoperative EEG controls seem to be highly suited as a non-invasive and economical method for the early detection of recurrence of this type of tumour. In the case of malignant types of gliomas involving rapid growth EEG controls should be made monthly. (Author)
Miskon, Azizi; A/L Thanakodi, Suresh; Raihan Mazlan, Mohd; Mohd Haziq Azhar, Satria; Nooraya Mohd Tawil, Siti
This project presents the development of an artificial hand controlled by Electroencephalograph (EEG) signal datasets for the prosthetic application. The EEG signal datasets were used as to improvise the way to control the prosthetic hand compared to the Electromyograph (EMG). The EMG has disadvantages to a person, who has not used the muscle for a long time and also to person with degenerative issues due to age factor. Thus, the EEG datasets found to be an alternative for EMG. The datasets used in this work were taken from Brain Computer Interface (BCI) Project. The datasets were already classified for open, close and combined movement operations. It served the purpose as an input to control the prosthetic hand by using an Interface system between Microsoft Visual Studio and Arduino. The obtained results reveal the prosthetic hand to be more efficient and faster in response to the EEG datasets with an additional LiPo (Lithium Polymer) battery attached to the prosthetic. Some limitations were also identified in terms of the hand movements, weight of the prosthetic, and the suggestions to improve were concluded in this paper. Overall, the objective of this paper were achieved when the prosthetic hand found to be feasible in operation utilizing the EEG datasets.
Cheron, Guy; Petit, Géraldine; Cheron, Julian; Leroy, Axelle; Cebolla, Anita; Cevallos, Carlos; Petieau, Mathieu; Hoellinger, Thomas; Zarka, David; Clarinval, Anne-Marie; Dan, Bernard
Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The non-invasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP) in sport. In this context, the hypotheses of unified brain rhythms and continuity between wake and sleep states should provide a functional template for EEG biomarkers in sport. The oscillations in the thalamo-cortical and hippocampal circuitry including the physiology of the place cells and the grid cells provide a frame of reference for the analysis of delta, theta, beta, alpha (incl.mu), and gamma oscillations recorded in the space field of human performance. Based on recent neuronal models facilitating the distinction between the different dynamic regimes (selective gating and binding) in these different oscillations we suggest an integrated approach articulating together the classical biomechanical factors (3D movements and EMG) and the high-density EEG and ERP signals to allow finer mathematical analysis to optimize sport performance, such as microstates, coherency/directionality analysis and neural generators.
This study was aimed at clarifying the EEG difference between chronic schizophrenic patients and normal controls by using the EEG method of spectral analyses. Twelve comparatively homogenous chronic schizophrenic patients and the 10 healthy controls were subjected to EEG investigations. 1) The EEG of schizophrenic patients had a slowing tendency of the frequency in the frontal pole, anterior temporal and central regions of the scalp compared with control subjects. 2) There was a decrease of mutual relation among the five electrodes' peak frequency in the schizophrenic patients. 3) The EEG of schizophrenic patients had more fast waves of β 1 and β 2 band than that of control subjects. 4) A slowing tendency of the frequency in the first half regions of the scalp was not found in 3 chronic schizophrenic patients which showed defective functions in the frontal area by positron emission tomography. 5) When mental arithmetic was given, the schizophrenic patients showed an increase of fast wave in the central, posterior temporal and occipital regions of the scalp. 6) When they opened their eyes, attenuation in the α band was not so marked in the schizophrenic patients. (author)
Andrew, C. M.
The univariate method of event-related desynchronization (ERD) analysis, which quantifies the temporal evolution of power within specific frequency bands from electroencephalographic (EEG) data recorded during a task or event, is extended to an event related multivariate spectral analysis method. With this method, time courses of cross-spectra, phase spectra, coherence spectra, band-averaged coherence values (event-related coherence, ERCoh), partial power spectra and partial coherence spectra are estimated from an ensemble of multivariate event-related EEG trials. This provides a means of investigating relationships between EEG signals recorded over different scalp areas during the performance of a task or the occurrence of an event. The multivariate spectral analysis method is applied to EEG data recorded during three different movement-related studies involving discrete right index finger movements. The first study investigates the impact of the EEG derivation type on the temporal evolution of interhemispheric coherence between activity recorded at electrodes overlying the left and right sensorimotor hand areas during cued finger movement. The question results whether changes in coherence necessarily reflect changes in functional coupling of the cortical structures underlying the recording electrodes. The method is applied to data recorded during voluntary finger movement and a hypothesis, based on an existing global/local model of neocortical dynamics, is formulated to explain the coherence results. The third study applies partial spectral analysis too, and investigates phase relationships of, movement-related data recorded from a full head montage, thereby providing further results strengthening the global/local hypothesis. (author)
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.
Full Text Available The present mini-review was aimed at exploring the frontal EEG asymmetry of mood. With respect to emotion, interpreted as a discrete affective process, mood is more controllable, more nebulous, and more related to mind/cognition; in addition, causes are less well-defined than those eliciting emotion. Therefore, firstly, the rational for the distinction between emotion and mood was provided. Then, the main frontal EEG asymmetry models were presented, such as the motivational approach/withdrawal, valence/arousal, capability, and inhibition asymmetric models. Afterward, the frontal EEG asymmetry of mood was investigated following three research lines, that is considering studies involving different mood induction procedures, dispositional mood (positive and negative affect, and mood alterations in both healthy and clinical populations. In general, results were found to be contradictory, no model is unequivocally supported regardless the research line considered. Different methodological issues were raised, such as: the composition of samples used across studies, in particular, gender and age were found to be critical variables that should be better addressed in future studies; the importance of third variables that might mediate the relationship between frontal EEG asymmetries and mood, for example bodily states and hormonal responses; the role of cognition, namely the interplay between mood and executive functions. In light of these issues, future research directions were proposed. Amongst others, the need to explore the neural connectivity that underpins EEG asymmetries, and the need to include both positive and negative mood conditions in the experimental designs have been highlighted.
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
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.
Aydın, Serap; Saraoǧlu, Hamdi Melih; Kara, Sadık
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.
Full Text Available Increasing evidence indicates that the phase pattern and power of the low frequency oscillations of brain electroencephalograms (EEG contain significant information during the human cognition of sensory signals such as auditory and visual stimuli. Here, we investigate whether and how the letters of the alphabet can be directly decoded from EEG phase and power data. In addition, we investigate how different band oscillations contribute to the classification and determine the critical time periods. An English letter recognition task was assigned, and statistical analyses were conducted to decode the EEG signal corresponding to each letter visualized on a computer screen. We applied support vector machine (SVM with gradient descent method to learn the potential features for classification. It was observed that the EEG phase signals have a higher decoding accuracy than the oscillation power information. Low-frequency theta and alpha oscillations have phase information with higher accuracy than do other bands. The decoding performance was best when the analysis period began from 180 to 380 ms after stimulus presentation, especially in the lateral occipital and posterior temporal scalp regions (PO7 and PO8. These results may provide a new approach for brain-computer interface techniques (BCI and may deepen our understanding of EEG oscillations in cognition.
Full Text Available The overall aim of our research is to develop a monitoring system for neonatal intensive care units. Long-term EEG monitoring in newborns require that the electrodes don’t harm the sensitive skin of the baby, an especially relevant feature for premature babies. Our approach to EEG monitoring is based on several electrodes distributed over the head of the baby, and since the weight of the head always will be on some of them, any type of hard electrode will inevitably cause a pressure-point that can irritate the skin. Therefore, we propose the use of soft conductive textiles as EEG electrodes, primarily for neonates, but also for other kinds of unobtrusive long-term monitoring. In this paper we have tested two types of textile electrodes on five healthy adults and compared them to standard high quality electrodes. The acquired signals were compared with respect to morphology, frequency distribution, spectral coherence, correlation and power line interference sensitivity, and the signals were found to be similar in most respects. The good measurement performance exhibited by the textile electrodes indicates that they are feasible candidates for EEG recording, opening the door for long-term EEG monitoring applications.
Melia, Umberto; Guaita, Marc; Vallverdú, Montserrat; Embid, Cristina; Vilaseca, Isabel; Salamero, Manel; Santamaria, Joan
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 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.
Birjandtalab, Javad; Pouyan, Maziyar Baran; Nourani, Mehrdad
Epilepsy is a neurological disorder which can, if not controlled, potentially cause unexpected death. It is extremely crucial to have accurate automatic pattern recognition and data mining techniques to detect the onset of seizures and inform care-givers to help the patients. EEG signals are the preferred biosignals for diagnosis of epileptic patients. Most of the existing pattern recognition techniques used in EEG analysis leverage the notion of supervised machine learning algorithms. Since seizure data are heavily under-represented, such techniques are not always practical particularly when the labeled data is not sufficiently available or when disease progression is rapid and the corresponding EEG footprint pattern will not be robust. Furthermore, EEG pattern change is highly individual dependent and requires experienced specialists to annotate the seizure and non-seizure events. In this work, we present an unsupervised technique to discriminate seizures and non-seizures events. We employ power spectral density of EEG signals in different frequency bands that are informative features to accurately cluster seizure and non-seizure events. The experimental results tried so far indicate achieving more than 90% accuracy in clustering seizure and non-seizure events without having any prior knowledge on patient's history.
van Klink, Nicole; Mol, Arjen; Ferrier, Cyrille; Hillebrand, Arjan; Huiskamp, Geertjan; Zijlmans, Maeike
Surface EEG can show epileptiform ripples in people with focal epilepsy, but identification is impeded by the low signal-to-noise ratio of the electrode recordings. We used beamformer-based virtual electrodes to improve ripple identification. We analyzed ten minutes of interictal EEG of nine patients with refractory focal epilepsy. EEGs with more than 60 channels and 20 spikes were included. We computed ∼79 virtual electrodes using a scalar beamformer and marked ripples (80-250 Hz) co-occurring with spikes in physical and virtual electrodes. Ripple numbers in physical and virtual electrodes were compared, and sensitivity and specificity of ripples for the region of interest (ROI; based on clinical information) were determined. Five patients had ripples in the physical electrodes and eight in the virtual electrodes, with more ripples in virtual than in physical electrodes (101 vs. 57, p = .007). Ripples in virtual electrodes predicted the ROI better than physical electrodes (AUC 0.65 vs. 0.56, p = .03). Beamforming increased ripple visibility in surface EEG. Virtual ripples predicted the ROI better than physical ripples, although sensitivity was still poor. Beamforming can facilitate ripple identification in EEG. Ripple localization needs to be improved to enable its use for presurgical evaluation in people with epilepsy. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
Unusually high indoor radon concentrations were reported in a small village in western Tyrol, Austria. The authors have measured the seasonal course of indoor radon concentrations in 390 houses of this village. 71% of houses in winter and 33% in summer, showed radon values on the ground floor above the Austrian action level of 400 Bq/cm 3 . This proportion results in an unusually high indoor radon exposure of the population. The radon source was an 8,700-year-old rock slide of granite gneiss, the largest of the alpine crystalline rocks. It has a strong emanating power because its rocks are heavily fractured and show a slightly increased uranium content. Previous reports show increased lung cancer mortality, myeloid leukemia, kidney cancer, melanoma, and prostate cancer resulting from indoor radon exposure. However, many studies fail to provide accurate information on indoor radon concentrations, classifying them merely as low, intermediate, and high, or they record only minor increases in indoor radon concentrations. Mortality data for 1970-91 were used to calculate age and sex standardized mortality rates (SMR) for 51 sites of carcinoma. The total population of Tyrol were controls. A significantly higher risk was recorded for lung cancer. The high SMR for lung cancer in female subjects is especially striking. Because the numbers were low for the other cancer sites, these were combined in one group to calculate the SMR. No significant increase in SMR was found for this group
Hanson, Roger J.
The actual motions of a sinusoidally driven vibrating string can be very complex due to nonlinear effects resulting from varying tension and longitudinal motion not included in simple linear theory. Commonly observed effects are: generation of motion perpendicular to the driving force, sudden jumps in amplitude, hysteresis, and generation of higher harmonics. In addition, these effects are profoundly influenced by wire asymmetries which in a brass harpsichord wire can cause a small splitting of each natural frequency of free vibration into two closely spaced frequencies (relative separation ~0.2% to 2%), each associated with transverse motion along two orthogonal characteristic wire axes. Some unusual resulting patterns of complex motions of a point on the wire are exhibited on videotape. Examples include: sudden changes of harmonic content, generation of subharmonics, and motion which appears nearly chaotic but which has a pattern period of over 10 s. Another unusual phenomenon due to entirely different causes can occur when a violin string is bowed with a higher than normal force resulting in sounds ranging from about a musical third to a twelfth lower than the sound produced when the string is plucked.
Full Text Available A total of 23500 Extensive Air Showers (EAS with energies above ∼ 1016 eV have been detected during the ∼3500 hours of the Horizon-T (HT detectors system operations before Aug. 2016. Among these EAS, more than a thousand had an unusual spatial and temporary structure that showed pulses with several maxima (modals or modes from several detection points of the HT at the same time. These modes are separated in time from each other starting from tens to thousands of ns. These EAS have been called multi-modal. Analysis shows that the multi-modal EAS that have been detected by Horizon-T have the following properties: 1. Multi-modal EAS have energy above ∼1017 eV. 2. Pulses with several modes are located at large distances from the EAS axis. An overview of the collected data will be provided. General comments about the unusual structure of the multi-modal EAS will be presented.
Caat, Michael ten; Maurits, Natasha M.; Roerdink, Jos B.T.M.
A typical data- driven visualization of electroencephalography ( EEG) coherence is a graph layout, with vertices representing electrodes and edges representing significant coherences between electrode signals. A drawback of this layout is its visual clutter for multichannel EEG. To reduce clutter,
Grubov, Vadim V.; Runnova, Anastasiya E.; Khramova, Marina V.
In the paper we propose the new method for dealing with noise and physiological artifacts in experimental human EEG recordings. The method is based on analysis of EEG signals with empirical mode decomposition (Hilbert-Huang transform). We consider noises and physiological artifacts on EEG as specific oscillatory patterns that cause problems during EEG analysis and can be detected with additional signals recorded simultaneously with EEG (ECG, EMG, EOG, etc.) We introduce the algorithm of the method with following steps: empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing empirical modes with artifacts, reconstruction of the initial EEG signal. We test the method on filtration of experimental human EEG signals from eye-moving artifacts and show high efficiency of the method.
Sarrigiannis, Ptolemaios G; Zhao, Yifan; Wei, Hua-Liang; Billings, Stephen A; Fotheringham, Jayne; Hadjivassiliou, Marios
To introduce a new method of quantitative EEG analysis in the time domain, the error reduction ratio (ERR)-causality test. To compare performance against cross-correlation and coherence with phase measures. A simulation example was used as a gold standard to assess the performance of ERR-causality, against cross-correlation and coherence. The methods were then applied to real EEG data. Analysis of both simulated and real EEG data demonstrates that ERR-causality successfully detects dynamically evolving changes between two signals, with very high time resolution, dependent on the sampling rate of the data. Our method can properly detect both linear and non-linear effects, encountered during analysis of focal and generalised seizures. We introduce a new quantitative EEG method of analysis. It detects real time levels of synchronisation in the linear and non-linear domains. It computes directionality of information flow with corresponding time lags. This novel dynamic real time EEG signal analysis unveils hidden neural network interactions with a very high time resolution. These interactions cannot be adequately resolved by the traditional methods of coherence and cross-correlation, which provide limited results in the presence of non-linear effects and lack fidelity for changes appearing over small periods of time. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Fatmawati, Ester; Prawito, Prawito; Wijaya, Sastra Kusuma
Design modeling has been done post-stroke therapy arm by utilizing command brain signals generated by Electroencephalography (EEG). EEG signals provides a lot of information, one of which is motor information. Every body moving describe the unique form of brain signals. In conditions paralysis, motor information on the EEG signals will still be found when someone tries to move his limbs. The basic concepts of this study are the EEG signal acquisition using the Emotiv EPOC +, controling signal...
Panischev, O Yu; Demin, S A; Zinatullin, E M
In this work we apply a new method to determine the differences in characteristics of the cortical electroencephalographic (EEG) activity, measured during interictal stage (i.e., period between seizures), between healthy subjects and patients with epilepsy. To analyze the dynamical and spectral properties of bioelectric activity we use power spectra and phase portraits which are introduced on the basis of the Memory Function Formalism (MFF). We discover the significant differences in the types of power spectra of the EEG for healthy subjects and patients. We reveal the cerebral cortex areas for which the EEG activity of considered groups of subjects has a different structure of the phase portraits. The proposed approach can be used as an additional method for diagnosis of epilepsy during interictal stage. (paper)
Xu, Peng; Lei, Xu; Hu, Xiao; Yao, Dezhong
l(0) norm is an effective constraint used to solve EEG inverse problem for a sparse solution. However, due to the discontinuous and un-differentiable properties, it is an open issue to solve the l(0) norm constrained problem, which is usually instead solved by using some alternative functions like l(1) norm to approximate l(0) norm. In this paper, a continuous and differentiable function having the same form as the transfer function of Butterworth low-pass filter is introduced to approximate l(0) norm constraint involved in EEG inverse problem. The new approximation based approach was compared with l(1) norm and LORETA solutions on a realistic head model using simulated sources. The preliminary results show that this alternative approximation to l(0) norm is promising for the estimation of EEG sources with sparse distribution.
Lappalainen, R.; Liewendahl, K.; Nikkinen, P.; Sainio, K.; Riikonen, R.S.
Thirteen patients (mean age 8.4 + 5.3 years) with Rett syndrome (RS) were studied with EEG and 99m Tc-HMPAO SPECT. Eleven patients had background abnormalities and 10 patients paroxysmal activity in EEG. Hypoperfusion of varying severity was detected in 11 patients, 7 patients having multiple lesions. Bifrontal hypoperfusion, observed in 6 patients, was the most distinctive finding. Hypoperfusion was observed also in other cortical regions, except for the occipital lobes. There was no correlation between severity of the background abnormality or presence of paroxysmal activity in EEG and grade of hypoperfusion. There was, however, an association between the severity of hypoperfusion and early manifestation of symptoms in patients with RS. Whether this early-onset group of patients represents a different disease entity or only reflects disease variability the basic pathology being the same, is a possibility that deserves further clarification. (au) 37 refs
James, C J; Hagan, M T; Jones, R D; Bones, P J; Carroll, G J
The technique of multireference adaptive noise canceling (MRANC) is applied to enhance transient nonstationarities in the electroeancephalogram (EEG), with the adaptation implemented by means of a multilayer-perception artificial neural network (ANN). The method was applied to recorded EEG segments and the performance on documented nonstationarities recorded. The results show that the neural network (nonlinear) gives an improvement in performance (i.e., signal-to-noise ratio (SNR) of the nonstationarities) compared to a linear implementation of MRANC. In both cases an improvement in the SNR was obtained. The advantage of the spatial filtering aspect of MRANC is highlighted when the performance of MRANC is compared to that of the inverse auto-regressive filtering of the EEG, a purely temporal filter.
Schug, Robert A; Yang, Yaling; Raine, Adrian; Han, Chenbo; Liu, Jianghong; Li, Liejia
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.
Huster, René J; Mokom, Zacharais N; Enriquez-Geppert, Stefanie; Herrmann, Christoph S
Neurofeedback training procedures designed to alter a person's brain activity have been in use for nearly four decades now and represent one of the earliest applications of brain-computer interfaces (BCI). The majority of studies using neurofeedback technology relies on recordings of the electroencephalogram (EEG) and applies neurofeedback in clinical contexts, exploring its potential as treatment for psychopathological syndromes. This clinical focus significantly affects the technology behind neurofeedback BCIs. For example, in contrast to other BCI applications, neurofeedback BCIs usually rely on EEG-derived features with only a minimum of additional processing steps being employed. Here, we highlight the peculiarities of EEG-based neurofeedback BCIs and consider their relevance for software implementations. Having reviewed already existing packages for the implementation of BCIs, we introduce our own solution which specifically considers the relevance of multi-subject handling for experimental and clinical trials, for example by implementing ready-to-use solutions for pseudo-/sham-neurofeedback. © 2013.
Papadelis, Christos; Kourtidou-Papadeli, Chrysoula; Bamidis, Panagiotis D; Maglaveras, Nikos; Pappas, Konstantinos
The objective of this study was the development and evaluation of nonlinear electroencephalography parameters which assess hypoxia-induced EEG alterations, and describe the temporal characteristics of different hypoxic levels' residual effect upon the brain electrical activity. Multichannel EEG, pO2, pCO2, ECG, and respiration measurements were recorded from 10 subjects exposed to three experimental conditions (100% oxygen, hypoxia, recovery) at three-levels of reduced barometric pressure. The mean spectral power of EEG under each session and altitude were estimated for the standard bands. Approximate Entropy (ApEn) of EEG segments was calculated, and the ApEn's time-courses were smoothed by a moving average filter. On the smoothed diagrams, parameters were defined. A significant increase in total power and power of theta and alpha bands was observed during hypoxia. Visual interpretation of ApEn time-courses revealed a characteristic pattern (decreasing during hypoxia and recovering after oxygen re-administration). The introduced qEEG parameters S1 and K1 distinguished successfully the three hypoxic conditions. The introduced parameters based on ApEn time-courses are assessing reliably and effectively the different hypoxic levels. ApEn decrease may be explained by neurons' functional isolation due to hypoxia since decreased complexity corresponds to greater autonomy of components, although this interpretation should be further supported by electrocorticographic animal studies. The introduced qEEG parameters seem to be appropriate for assessing the hypoxia-related neurophysiological state of patients in the hyperbaric chambers in the treatment of decompression sickness, carbon dioxide poisoning, and mountaineering.
Akalin Acar, Zeynep; Acar, Can E; Makeig, Scott
Accurate electroencephalographic (EEG) source localization requires an electrical head model incorporating accurate geometries and conductivity values for the major head tissues. While consistent conductivity values have been reported for scalp, brain, and cerebrospinal fluid, measured brain-to-skull conductivity ratio (BSCR) estimates have varied between 8 and 80, likely reflecting both inter-subject and measurement method differences. In simulations, mis-estimation of skull conductivity can produce source localization errors as large as 3cm. Here, we describe an iterative gradient-based approach to Simultaneous tissue Conductivity And source Location Estimation (SCALE). The scalp projection maps used by SCALE are obtained from near-dipolar effective EEG sources found by adequate independent component analysis (ICA) decomposition of sufficient high-density EEG data. We applied SCALE to simulated scalp projections of 15cm(2)-scale cortical patch sources in an MR image-based electrical head model with simulated BSCR of 30. Initialized either with a BSCR of 80 or 20, SCALE estimated BSCR as 32.6. In Adaptive Mixture ICA (AMICA) decompositions of (45-min, 128-channel) EEG data from two young adults we identified sets of 13 independent components having near-dipolar scalp maps compatible with a single cortical source patch. Again initialized with either BSCR 80 or 25, SCALE gave BSCR estimates of 34 and 54 for the two subjects respectively. The ability to accurately estimate skull conductivity non-invasively from any well-recorded EEG data in combination with a stable and non-invasively acquired MR imaging-derived electrical head model could remove a critical barrier to using EEG as a sub-cm(2)-scale accurate 3-D functional cortical imaging modality. Copyright © 2015 Elsevier Inc. All rights reserved.
Kamp, A.; Arnolds, D.E.A.T.; Lopes da Silva, F.H.; Boeijinga, P.; Aitink, W.
In cat the relation between various behaviours and the spectral properties of the hippocampal EEG was investigated. Both EEG and behaviour were quantified and results were evaluated statistically. Significant relationships were found between the properties of the hippocampal EEG and motor acts
Swatzyna, Ronald J; Kozlowski, Gerald P; Tarnow, Jay D
Pharmaco-electroencephalography (Pharmaco-EEG) studies using clinical EEG and quantitative EEG (qEEG) technologies have existed for more than 4 decades. This is a promising area that could improve psychotropic intervention using neurological data. One of the objectives in our clinical practice has been to collect EEG and quantitative EEG (qEEG) data. In the past 5 years, we have identified a subset of refractory cases (n = 386) found to contain commonalities of a small number of electrophysiological features in the following diagnostic categories: mood, anxiety, autistic spectrum, and attention deficit disorders, Four abnormalities were noted in the majority of medication failure cases and these abnormalities did not appear to significantly align with their diagnoses. Those were the following: encephalopathy, focal slowing, beta spindles, and transient discharges. To analyze the relationship noted, they were tested for association with the assigned diagnoses. Fisher's exact test and binary logistics regression found very little (6%) association between particular EEG/qEEG abnormalities and diagnoses. Findings from studies of this type suggest that EEG/qEEG provides individualized understanding of pharmacotherapy failures and has the potential to improve medication selection. © EEG and Clinical Neuroscience Society (ECNS) 2014.
Efthymiou, Evdokia; Renzel, Roland; Baumann, Christian R; Poryazova, Rositsa; Imbach, Lukas L
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 (pEEG patterns such as generalized periodic discharges (pEEG analysis (state space analysis) provides a novel, complementary marker for prognosis in postanoxic encephalopathy. Copyright © 2017 Elsevier B.V. All rights reserved.
Doudoux, Hannah; Skaare, Kristina; Geay, Thomas; Kahane, Philippe; Bosson, Jean L; Sabourdy, Cécile; Vercueil, Laurent
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.
Beuchat, I.; Solari, D.; Novy, J.; Oddo, M.; Rossetti, A.O.
Standardized EEG patterns according to the American Clinical Neurophysiology Society (ACNS) ("highly malignant", "malignant" and "benign") demonstrated good correlation with outcome after cardiac arrest (CA). However, this approach relates to EEGs after target temperature management (TTM), and correlation to other recognized outcome predictors remains unknown. To investigate the relationship between categorized EEG and other outcome predictors, during and after TTM, at different temperatur...
Paulina A. Toso
Conclusions: in infants with encephalopathy or other severe illness, aEEG disturbances occur frequently. aEEG provided a better classification of the severity of encephalopathy, detectedearly subclinical seizures, and allowed for monitoring of the response to treatment. aEEG was a useful tool at the neonatal intensive care unit for predicting poor short-term neurologicaloutcomes for all sick newborn.
The literature review presents an explanation of biofeedback and a critical evaluation of the research pertaining to electroencephalographic (EEG) biofeedback training for the hyperactive and/or learning disabled child. Three hypotheses are examined: whether EEG biofeedback training is efficacious; whether EEG biofeedback training is more…
Kouijzer, M.E.J.; Schie, H.T. van; Gerrits, B.J.L.; Buitelaar, J.K.; Moor, J.M.H. de
EEG-biofeedback has been reported to reduce symptoms of autism spectrum disorders (ASD) in several studies. However, these studies did not control for nonspecific effects of EEG-biofeedback and did not distinguish between participants who succeeded in influencing their own EEG activity and
Cloostermans, M.C.; de Vos, Cecilia Cecilia Clementine; van Putten, Michel Johannes Antonius Maria
Objective The implementation of a computer assisted system for real-time classification of the electroencephalogram (EEG) in critically ill patients. Methods Eight quantitative features were extracted from the raw EEG and combined into a single classifier. The system was trained with 41 EEG
Henriksen, Jonas; Kjær, Troels; Thomsen, Carsten E.
Purpose: The current project evaluated the feasibility of providing an algorithm that could warn a patient of a forthcoming seizure based on iEEG recordings. Method: The mean phase coherence (MPC) feature (Mormann F et al. Phys Nonlinear Phenom 2000;3-4:358-369.) was implemented and tested...... in a rigorously, out-of-sample manner. The MPC-feature is based on the synchronization measure, explained through the analytic signal approach where the Hilbert transform is used to find the instantaneous phase of an arbitrary signal. By a relative comparison between two different iEEG channels the phase...
Grubov, Vadim V.; Sitnikova, Evgenia Yu.; Nedaivozov, Vladimir O.; Koronovskii, Alexey A.
In this paper we study specific oscillatory patterns on EEG signals of WAG/Rij rats. These patterns are known as proepileptic because they occur in time period during the development of absence-epilepsy before fully-formed epileptic seizures. In the paper we analyze EEG signals of WAG/Rij rats with continuous wavelet transform and empirical mode decomposition in order to find particular features of epileptic spike-wave discharges and nonepileptic sleep spindles. Then we introduce proepileptic activity as patterns that combine features of epileptic and non-epileptic activity. We analyze proepileptic activity in order to specify its features and time-frequency structure.
Krishnan, N Murali; Mariappan, Muralindran; Muthukaruppan, Karthigayan; Hijazi, Mohd Hanafi Ahmad; Kitt, Wong Wei
Recently, EEG based control in assistive robot usage has been gradually increasing in the area of biomedical field for giving quality and stress free life for disabled and elderly people. This study reviews the deployment of EGG based control in assistive robots, especially for those who in need and neurologically disabled. The main objective of this paper is to describe the methods used for (i) EEG data acquisition and signal preprocessing, (ii) feature extraction and (iii) signal classification methods. Besides that, this study presents the specific research challenges in the designing of these control systems and future research directions. (paper)
Neill, R.H.; Chaturvedi, L.; Lee, W.W.L.
Since 1978, the New Mexico Environmental Evaluation Group (EEG) has provided an independent technical evaluation of the Waste Isolation Pilot Plant (WIPP) to ensure protection of the public health and safety of New Mexicans and protection of the environment in New Mexico. Through its technical competence and continuity, the EEG has had a major influence on the course of the WIPP. This paper summarizes our views on the 1993 repromulgation of the general environmental standards for high-level and transuranic waste disposal and the certification for compliance with the standard
Müller, M M; Gruber, T; Keil, A
Here we present a series of four studies aimed to investigate the link between induced gamma band activity in the human EEG and visual information processing. We demonstrated and validated the modulation of spectral gamma band power by spatial selective visual attention. When subjects attended to a certain stimulus, spectral power was increased as compared to when the same stimulus was ignored. In addition, we showed a shift in spectral gamma band power increase to the contralateral hemisphere when subjects shifted their attention to one visual hemifield. The following study investigated induced gamma band activity and the perception of a Gestalt. Ambiguous rotating figures were used to operationalize the law of good figure (gute Gestalt). We found increased gamma band power at posterior electrode sites when subjects perceived an object. In the last experiment we demonstrated a differential hemispheric gamma band activation when subjects were confronted with emotional pictures. Results of the present experiments in combination with other studies presented in this volume are supportive for the notion that induced gamma band activity in the human EEG is closely related to visual information processing and attentional perceptual mechanisms.
Hasenstab, Kyle; Scheffler, Aaron; Telesca, Donatello; Sugar, Catherine A; Jeste, Shafali; DiStefano, Charlotte; Şentürk, Damla
The electroencephalography (EEG) data created in event-related potential (ERP) experiments have a complex high-dimensional structure. Each stimulus presentation, or trial, generates an ERP waveform which is an instance of functional data. The experiments are made up of sequences of multiple trials, resulting in longitudinal functional data and moreover, responses are recorded at multiple electrodes on the scalp, adding an electrode dimension. Traditional EEG analyses involve multiple simplifications of this structure to increase the signal-to-noise ratio, effectively collapsing the functional and longitudinal components by identifying key features of the ERPs and averaging them across trials. Motivated by an implicit learning paradigm used in autism research in which the functional, longitudinal, and electrode components all have critical interpretations, we propose a multidimensional functional principal components analysis (MD-FPCA) technique which does not collapse any of the dimensions of the ERP data. The proposed decomposition is based on separation of the total variation into subject and subunit level variation which are further decomposed in a two-stage functional principal components analysis. The proposed methodology is shown to be useful for modeling longitudinal trends in the ERP functions, leading to novel insights into the learning patterns of children with Autism Spectrum Disorder (ASD) and their typically developing peers as well as comparisons between the two groups. Finite sample properties of MD-FPCA are further studied via extensive simulations. © 2017, The International Biometric Society.
Drinkenburg, Wilhelmus H I M; Ahnaou, Abdallah; Ruigt, Gé S F
Current research on the effects of pharmacological agents on human neurophysiology finds its roots in animal research, which is also reflected in contemporary animal pharmaco-electroencephalography (p-EEG) applications. The contributions, present value and translational appreciation of animal p-EEG-based applications are strongly interlinked with progress in recording and neuroscience analysis methodology. After the pioneering years in the late 19th and early 20th century, animal p-EEG research flourished in the pharmaceutical industry in the early 1980s. However, around the turn of the millennium the emergence of structurally and functionally revealing imaging techniques and the increasing application of molecular biology caused a temporary reduction in the use of EEG as a window into the brain for the prediction of drug efficacy. Today, animal p-EEG is applied again for its biomarker potential - extensive databases of p-EEG and polysomnography studies in rats and mice hold EEG signatures of a broad collection of psychoactive reference and test compounds. A multitude of functional EEG measures has been investigated, ranging from simple spectral power and sleep-wake parameters to advanced neuronal connectivity and plasticity parameters. Compared to clinical p-EEG studies, where the level of vigilance can be well controlled, changes in sleep-waking behaviour are generally a prominent confounding variable in animal p-EEG studies and need to be dealt with. Contributions of rodent pharmaco-sleep EEG research are outlined to illustrate the value and limitations of such preclinical p-EEG data for pharmacodynamic and chronopharmacological drug profiling. Contemporary applications of p-EEG and pharmaco-sleep EEG recordings in animals provide a common and relatively inexpensive window into the functional brain early in the preclinical and clinical development of psychoactive drugs in comparison to other brain imaging techniques. They provide information on the impact of
C. A. Pistolese
Full Text Available Idiopathic granulomatous mastitis (IGM is an uncommon benign disorder of the breast. At clinical examination, IGM is characterized by an inflammatory process of the breast, usually unilateral. Possible clinical findings are palpable mass with erythematous skin, pain, sterile abscesses, fistula and nipple retraction. Mammography and ultrasound findings are not specific for IGM. Magnetic resonance imaging (MRI is a useful tool for the differential diagnosis; it is also necessary to delineate the exact extension of the disease and to plan the correct treatment. Final diagnosis is histological. We described an unusual case of IGM with bilateral involvement in a patient with history of pacemaker implantation and IGM typical clinical symptoms. Mammography, ultrasound, and MRI examinations were performed to identify the inflammatory disorder and to plan the correct therapy. Imaging features were correlated with final histological diagnosis of IGM.
Full Text Available The leishmaniases are parasitic diseases that are transmitted to humans by infected female sandflies. Cutaneous leishmaniasis (CL is one of 3 main forms of the disease. CL is the most common form of the disease and is endemic in many urban and rural parts of Iran and usually caused by two species of Leishmania: L. major and L. tropica. We report a case of unusual leishmaniasis with 25 lesions on exposed parts of the body and right eyelid involvement (ocular leishmaniasis. The patient was a 75-year-old male farmer referred to health care center in Aran va Bidgol city. The disease was diagnosed by direct smear, culture, and PCR from the lesions. PCR was positive for Leishmania major.
Ramesh, Venkat; Acharya, Vishak; Pai, Narasimha; Krishnan, Ananda
A 37-year-old man presented with a history of episodic wheeze and breathlessness of 3 years’ duration refractory to treatment. Physical examination revealed diffuse expiratory polyphonic rhonchi while the remainder of the examination including the cardiac examination was reported as normal. Pulmonary function testing revealed mild obstruction with bronchodilator reversibility. The patient was discharged on a 6-month course of antitubercular treatment (ATT) as bronchial brush cytology (obtained via bronchoscopy) was positive for acid-fast bacilli. The patient presented after completing 6 months of ATT with persistent symptoms, a loud S1 and a mid-diastolic murmur at the apex. High-resolution CT of the chest showed bilateral dependent ground glass opacities. An echocardiogram revealed a left atrial myxoma, and normal RV size and pressures. The patient underwent successful surgical removal of the same, and made a complete recovery. Refractory wheeze is a very unusual presentation of a left atrial myxoma. PMID:25733086
Theresa A. Zesiewicz
Full Text Available Background: Tremors may be difficult to classify.Case Report: An 83‐year‐old male presented with an unusual left wrist tremor. The tremor could be reproducibly elicited by making a fist or carrying a weighted object (e.g., a shopping bag, bottle of water of approximately 1 lb or more, and it intensified with heavier weights. The tremor was difficult to classify, although it shared features with isometric tremor.Discussion: This specific presentation of tremor has not been reported previously. We hope that the detailed description we provide will aid other neurologists who encounter this or similar tremors in their clinics.