167 research outputs found
Parametric and Nonparametric EEG Analysis for the Evaluation of EEG Activity in Young Children with Controlled Epilepsy
There is an important evidence of differences in the EEG frequency spectrum of control subjects as compared to epileptic subjects. In particular, the study of children presents difficulties due to the early stages of brain development and the various forms of epilepsy indications. In this study, we consider children that developed epileptic crises in the past but without any other clinical, psychological, or visible neurophysiological findings. The aim of the paper is to develop reliable techniques for testing if such controlled epilepsy induces related spectral differences in the EEG. Spectral features extracted by using nonparametric, signal representation techniques (Fourier and wavelet transform) and a parametric, signal modeling technique (ARMA) are compared and their effect on the classification of the two groups is analyzed. The subjects performed two different tasks: a control (rest) task and a relatively difficult math task. The results show that spectral features extracted by modeling the EEG signals recorded from individual channels by an ARMA model give a higher discrimination between the two subject groups for the control task, where classification scores of up to 100% were obtained with a linear discriminant classifier
Review on solving the inverse problem in EEG source analysis
In this primer, we give a review of the inverse problem for EEG source localization.
This is intended for the researchers new in the field to get insight in the
state-of-the-art techniques used to find approximate solutions of the brain sources
giving rise to a scalp potential recording. Furthermore, a review of the performance
results of the different techniques is provided to compare these different inverse
solutions. The authors also include the results of a Monte-Carlo analysis which they
performed to compare four non parametric algorithms and hence contribute to what is
presently recorded in the literature. An extensive list of references to the work of
other researchers is also provided
A decision support framework for the discrimination of children with controlled epilepsy based on EEG analysis
This work was supported in part by the EC-IST project Biopattern, contract no:
508803, by the EC ICT project TUMOR, contract no: 247754, by the University of
Malta grant LBA-73-695, by an internal grant from the Technical University of
Crete, ELKE# 80037 and by the Academy of Finland, project nos: 113572,
118355, 134767 and 213462.Background: In this work we consider hidden signs (biomarkers) in ongoing EEG activity expressing epileptic
tendency, for otherwise normal brain operation. More specifically, this study considers children with controlled
epilepsy where only a few seizures without complications were noted before starting medication and who showed no
clinical or electrophysiological signs of brain dysfunction. We compare EEG recordings from controlled epileptic
children with age-matched control children under two different operations, an eyes closed rest condition and a
mathematical task. The aim of this study is to develop reliable techniques for the extraction of biomarkers from EEG
that indicate the presence of minor neurophysiological signs in cases where no clinical or significant EEG abnormalities
are observed.
Methods: We compare two different approaches for localizing activity differences and retrieving relevant information
for classifying the two groups. The first approach focuses on power spectrum analysis whereas the second approach
analyzes the functional coupling of cortical assemblies using linear synchronization techniques.
Results: Differences could be detected during the control (rest) task, but not on the more demanding mathematical
task. The spectral markers provide better diagnostic ability than their synchronization counterparts, even though a
combination (or fusion) of both is needed for efficient classification of subjects.
Conclusions: Based on these differences, the study proposes concrete biomarkers that can be used in a decision
support system for clinical validation. Fusion of selected biomarkers in the Theta and Alpha bands resulted in an
increase of the classification score up to 80% during the rest condition. No significant discrimination was achieved
during the performance of a mathematical subtraction task.peer-reviewe
Review of the Commission Decision 2010/477/EU concerning MSFD criteria for assessing Good Environmental Status, Descriptor 7
This report represents the result of the scientific and technical review of Commission Decision 2010/477/EU in relation to Descriptor 7. The review has been carried out by the EC JRC together with experts nominated by EU Member States, and has considered contributions from the GES Working Group in accordance with the roadmap set out in the MSFD implementation strategy (agreed on at the 11th CIS MSCG meeting).
The report is one of a series of reports (review manuals) including Descriptor 1, 2, 5, 7, 8, 9, 10 that conclude phase 1 of the review process and, as agreed within the MSFD Common Implementation Strategy, are the basis for review phase 2, towards an eventual revision of the Commission Decision 2010/477/EU.
The report presents the state of the technical discussions as of 30 April 2015 (document version 7.0: ComDecRev_D7_V7.0_FINAL.docx), as some discussions are ongoing, it does not contain agreed conclusions on all issues.
The document does not represent an official, formal position of any of the Member States and the views expressed in the document are not to be taken as representing the views of the European Commission.JRC.H.1-Water Resource
Comparison of single trial back-projected independent components with the averaged waveform for the extraction of biomarkers of auditory P300 EPs
The independent components analysis (ICA) of the auditory P300 evoked responses in the EEG of normal subjects is described. The purpose was to identify any features which might provide the basis for biomarkers for diseases, such as Alzheimer’s disease. Single trial P300s were analysed by ICA, the activations were back-projected to scalp electrodes, many artefactual components were removed automatically, and the back-projected independent components (BICs) were first clustered according to their amplitudes and latencies. Then these primary clusters were secondarily clustered according to the columns of their mixing matrices, which clusters together those BICs with the same scalp topographies and, therefore, source locations. The BICs comprising the P300s had simple shapes, approximating half-sinusoids. Trial- to-trial variations in the BICs were found, which explain why different averages have been reported. Both positive- and also negative-going BICs were identified, some associated with known peaks in the P300 waveform. Artefact-free, single trial P300 waveforms could be constructed from the BICs, but these are probably of less interest than the BICs themselves. The findings demonstrate that neither averaged P300s, nor single trial P300s, are reliable as biomarkers, but rather it will be necessary to investigate the BICs present in a number of single trial realizations.peer-reviewe
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Mediterranean Sea response to climate change in an ensemble of twenty first century scenarios
The Mediterranean climate is expected to become warmer and drier during the twenty-first century. Mediterranean Sea response to climate change could be modulated by the choice of the socio-economic scenario as well as the choice of the boundary conditions mainly the Atlantic hydrography, the river runoff and the atmospheric fluxes. To assess and quantify the sensitivity of the Mediterranean Sea to the twenty-first century climate change, a set of numerical experiments was carried out with the regional ocean model NEMOMED8 set up for the Mediterranean Sea. The model is forced by air–sea fluxes derived from the regional climate model ARPEGE-Climate at a 50-km horizontal resolution. Historical simulations representing the climate of the period 1961–2000 were run to obtain a reference state. From this baseline, various sensitivity experiments were performed for the period 2001–2099, following different socio-economic scenarios based on the Special Report on Emissions Scenarios. For the A2 scenario, the main three boundary forcings (river runoff, near-Atlantic water hydrography and air–sea fluxes) were changed one by one to better identify the role of each forcing in the way the ocean responds to climate change. In two additional simulations (A1B, B1), the scenario is changed, allowing to quantify the socio-economic uncertainty. Our 6-member scenario simulations display a warming and saltening of the Mediterranean. For the 2070–2099 period compared to 1961–1990, the sea surface temperature anomalies range from +1.73 to +2.97 °C and the SSS anomalies spread from +0.48 to +0.89. In most of the cases, we found that the future Mediterranean thermohaline circulation (MTHC) tends to reach a situation similar to the eastern Mediterranean Transient. However, this response is varying depending on the chosen boundary conditions and socio-economic scenarios. Our numerical experiments suggest that the choice of the near-Atlantic surface water evolution, which is very uncertain in General Circulation Models, has the largest impact on the evolution of the Mediterranean water masses, followed by the choice of the socio-economic scenario. The choice of river runoff and atmospheric forcing both have a smaller impact. The state of the MTHC during the historical period is found to have a large influence on the transfer of surface anomalies toward depth. Besides, subsurface currents are substantially modified in the Ionian Sea and the Balearic region. Finally, the response of thermosteric sea level ranges from +34 to +49 cm (2070–2099 vs. 1961–1990), mainly depending on the Atlantic forcing
AI in Medical Imaging Informatics: Current Challenges and Future Directions
This paper reviews state-of-the-art research solutions across the spectrum of medical imaging informatics, discusses clinical translation, and provides future directions for advancing clinical practice. More specifically, it summarizes advances in medical imaging acquisition technologies for different modalities, highlighting the necessity for efficient medical data management strategies in the context of AI in big healthcare data analytics. It then provides a synopsis of contemporary and emerging algorithmic methods for disease classification and organ/ tissue segmentation, focusing on AI and deep learning architectures that have already become the de facto approach. The clinical benefits of in-silico modelling advances linked with evolving 3D reconstruction and visualization applications are further documented. Concluding, integrative analytics approaches driven by associate research branches highlighted in this study promise to revolutionize imaging informatics as known today across the healthcare continuum for both radiology and digital pathology applications. The latter, is projected to enable informed, more accurate diagnosis, timely prognosis, and effective treatment planning, underpinning precision medicine
Left atrial giant thrombus infected by Escherichia Coli. Case report
This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens
Habitat Selection and Temporal Abundance Fluctuations of Demersal Cartilaginous Species in the Aegean Sea (Eastern Mediterranean)
Predicting the occurrence of keystone top predators in a multispecies marine environment, such as the Mediterranean Sea, can be of considerable value to the long-term sustainable development of the fishing industry and to the protection of biodiversity. We analysed fisheries independent scientific bottom trawl survey data of two of the most abundant cartilaginous fish species (Scyliorhinus canicula, Raja clavata) in the Aegean Sea covering an 11-year sampling period. The current findings revealed a declining trend in R. clavata and S. canicula abundance from the late ′90 s until 2004. Habitats with the higher probability of finding cartilaginous fish present were those located in intermediate waters (depth: 200–400 m). The present results also indicated a preferential species' clustering in specific geographic and bathymetric regions of the Aegean Sea. Depth appeared to be one of the key determining factors for the selection of habitats for all species examined. With cartilaginous fish species being among the more biologically sensitive fish species taken in European marine fisheries, our findings, which are based on a standardized scientific survey, can contribute to the rational exploitation and management of their stocks by providing important information on temporal abundance trends and habitat preferences
To extract the independent components of the evoked potentials in the EEG using ICA
The aim was to develop a reliable method of extracting the independent components of single trial evoked potential (EP) signals to derive features for the subject’s bioprofile, for diagnostic, prognostic, and monitoring purposes. Single trials are of interest, because conventional averaging conceals trial-to-trial variability and hence information. Independent Components Analysis (ICA) is a technique for Blind Source Separation (BSS) to recover N temporally independent source signals s = {s1(t), ... sN(t)} from N linear mixtures (the observations), x = {x1(t), ... xN(t)} obtained by multiplying the matrix of unknown sources s by an unknown mixing matrix A, (x = A.s). ICA seeks a square unmixing matrix W such that s = W.x. Difficulties arise for short duration, relatively low amplitude EPs, which have sparse ICs. The effectiveness of different algorithms was compared. Problems associated with more sources than measurement electrodes and with the generation by the algorithms of artefactual components were investigated. Ways of extracting the true EP components were considered. Component grouping was applied to obtain reliable groups, which could be explored for any clinical interpretations. Here we describe the recommended approach as developed by our virtual research group.peer-reviewe
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