3,328 research outputs found
Reading EEGs: a practical approach/ [edited by] L. John Greenfield, Jr., James D. Geyer, Paul R. Carney
No full textIncludes bibliographical references and index"Reading EEGs: A Practical Approach focuses on pattern recognition and pattern comparison. The concepts of pattern recognition are developed in a logical fashion based on appearance rather than disease process. The book teaches waveform recognition so that the reader can generate a differential diagnosis based on that recognition. This book also incorporates a question-and-answer format that is effective for students at multiple levels of training"--Basic Neuroscience of EEG / L. John Greenfield, Jr. -- Electronics of EEG / L. John Greenfield, Jr. and James D. Geyer -- Recording the EEG / L. John Greenfield, Jr. -- Approaching the EEG: An Introduction to Visual Analysis / L. John Greenfield, Jr -- Artifacts and Noise / L. John Greenfield, Jr -- The Normal Adult EEG / L. John Greenfield, Jr -- Normal EEG in the Newborn, Infant, and Adolescent / Paul R. Carney, James D. Geyer and L. John Greenfield, Jr. -- Focal and General Rhythm Abnormalities / James D. Geyer and Paul R. Carney -- Epileptiform Activity, Seizures and Epilepsy Syndromes / Linda M. Selwa -- Pathophysiology of Epileptiform Activity / L. John Greenfield and Sanghun Lee -- Status Epilepticus EEG Patterns in Adults / Emily Johnson and Peter W. Kaplan -- Neonatal and Pediatric Epilepsy Syndromes / James D. Geyer, Paul R. Carney and L. John Greenfield, Jr. -- Video EEG Monitoring and Epilepsy Surgery / Vibhangini S. Wasade and Jules E.C. Constantinou -- Seizure Semiology: Signs of the Seizure / James D. Geyer, Paul R. Carney and L. John Greenfield, Jr. -- Subdural Electrode Corticography / William O. Tatum, Sanjeet Grewal -- Stereotactic Electroencephalography in Epilepsy / Sanjeet Grewal, Karim ReFaey, William O. Tatum -- EEG in Specific Disease States / James D. Geyer, Paul R. Carney and Erasmo A. Passaro -- Introduction to Sleep and Polysomnography / James D. Geyer and Paul R. Carney -- Evoked Potentials and Intraoperative Monitoring / David B MacDonald and Charles Dong -- New Frontiers in EEG: High and Low Frequencies, High Density EEG, Digital Analysis and Magnetoencephalography / David Burdette and Andrew Zillgitt -- Genetics of EEG and Epilepsy / James D. Geyer, Paul R. Carney and L. John Greenfield, Jr. -- Seizure Detection and Advanced Monitoring Techniques / Nicholas Fisher, Sachin Talathi, Alex Cadotte, Stephen Myers, William Ditto, James -- D. Geyer, Emery E. Geyer, and Paul R. Carney -- Non-Epileptic Events / Nicholas J. Beimer and Linda M. Selwa -- EEG Inter-rater Reliability / James D. Geyer and Paul R. Carney1 online resource (xii, 444 pages)
Corneal Shape in Hyperopia
No full textBackground: A trend towards decreased peripheral corneal flattening with increasing myopia has recently been demonstrated. The present study was conducted to determine whether corneal asphericity also varies significantly with hyperopic refractive error.\ud
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Methods: Thirty-five eyes with spherical equivalent refractive error ranging from -0.37 D to +6.00 D were examined. A conicoid equation was fitted to videokeratoscopic (Topographic Modeling System) data and corneal asphericity and apical radius of curvature values were calculated for each subject. Axial length measurements were made using a hand-held biometric ruler. Keratometry was also performed on each eye.\ud
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Results: The relationship between corneal asphericity (Q) and spherical equivalent refractive error was not statistically significant (p = 0.7419). In addition, no association could be demonstrated between Q and corneal radius of curvature or between Q and axial length. Corneal radius of curvature was positively correlated with axial length (r = 0.367, p = 0.0298). Axial length was found to decrease as hyperopic refractive error increased (r = 0.753, p = 0.0001).\ud
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Conclusions: For hyperopic eyes, corneal asphericity does not appear to be significantly correlated with refractive error, a finding that is at variance with previous data for myopic eyes showing an association between these two variables. The results suggest that there may be differences between hyperopic and myopic eyes with regard to the anterior segment changes that occur during refractive error development
Estimating the parameters of globular cluster M 30 (NGC 7099) from time-series photometry
No full textAims. We present the analysis of 26 nights of V and I time-series observations from 2011 and 2012 of the globular cluster M 30 (NGC 7099). We used our data to search for variable stars in this cluster and refine the periods of known variables; we then used our variable star light curves to derive values for the cluster's parameters. Methods. We used difference image analysis to reduce our data to obtain high-precision light curves of variable stars. We then estimated the cluster parameters by performing a Fourier decomposition of the light curves of RR Lyrae stars for which a good period estimate was possible. We also derived an estimate for the age of the cluster by fitting theoretical isochrones to our colour-magnitude diagram (CMD). Results. Out of 13 stars previously catalogued as variables, we find that only 4 are bona fide variables. We detect two new RR Lyrae variables, and confirm two additional RR Lyrae candidates from the literature. We also detect four other new variables, including an eclipsing blue straggler system, and an SX Phoenicis star. This amounts to a total number of confirmed variable stars in M 30 of 12. We perform Fourier decomposition of the light curves of the RR Lyrae stars to derive cluster parameters using empirical relations. We find a cluster metallicity [Fe/H]ZW =-2.01 ± 0.04, or [Fe/H]UVES =-2.11 ± 0.06, and a distance of 8.32 ± 0.20 kpc (using RR0 variables), 8.10 kpc (using one RR1 variable), and 8.35 ± 0.42 kpc (using our SX Phoenicis star detection in M 30). Fitting isochrones to the CMD, we estimate an age of 13.0 ± 1.0 Gyr for M 30. © 2013 ESO
Resolving Mechanisms of Toxicity while Pursing Ecotoxicological Relevance. , 51, 635-648.
No full textThrombin enhances T cell proliferative responses and cytokine production
No full textHuman alpha-thrombin, in addition to its procoagulant activity, is a mitogen for fibroblasts and endothelial cells and a chemotactic agent for monocytes. To further understand the complex physiological functions of thrombin, we investigated whether thrombin has any immunoregulatory function with regard to T cell activation. Using highly purified human alpha-thrombin and peripheral blood mononuclear cells (PBMC), we investigated whether thrombin has any effect on cytokine production and/or proliferation induced by different T cell stimuli. At physiological concentrations (1-10 micrograms/ml, 30-300 nM), thrombin significantly enhances T cell proliferation in response to mitogens, superantigens, alloantigens, and anti-CD3 stimulation. Enhanced proliferation was associated with increased IL2 and IL6 production and with an increase in the number of IL2r+ (CD25)-bearing T cells. Thrombin alone was not mitogenic nor did it induce IL2 production or increase the number of IL2r+ T cells. However, PBMC exposed to thrombin alone produced high levels of IL6. Thrombin also enhanced IL2-induced proliferation of murine and human IL2-dependent cell lines. These results suggest that thrombin may play an important role in regulating cell-mediated immunity
Characterization of the planetary system Kepler-101 with HARPS-N
No full textWe characterize the planetary system Kepler-101 by performing a combined differential evolution Markov chain Monte Carlo analysis of Kepler data and forty radial velocities obtained with the HARPS-N spectrograph. This system was previously validated and is composed of a hot super-Neptune, Kepler-101b, and an Earth-sized planet, Kepler-101c. These two planets orbit the slightly evolved and metal-rich G-type star in 3.49 and 6.03 days, respectively. With mass Mp = 51.1-4.7+ 5.1 M⊕, radius Rp = 5.77-0.79+ 0.85 R⊕, and density ρp = 1.45-0.48+ 0.83 g cm-3, Kepler-101b is the first fully characterized super-Neptune, and its density suggests that heavy elements make up a significant fraction of its interior; more than 60% of its total mass. Kepler-101c has a radius of 1.25-0.17+ 0.19 R⊕, which implies the absence of any H/He envelope, but its mass could not be determined because of the relative faintness of the parent star for highly precise radial-velocity measurements (Kp = 13.8) and the limited number of radial velocities. The 1σ upper limit, Mp< 3.8 M⊕, excludes a pure iron composition with a probability of 68.3%. The architecture of the planetary system Kepler-101 − containing a close-in giant planet and an outer Earth-sized planet with a period ratio slightly larger than the 3:2 resonance − is certainly of interest for scenarios of planet formation and evolution. This system does not follow thepreviously reported trend that the larger planet has the longer period in the majority of Kepler systems of planet pairs with at least one Neptune-sized or larger planet
Exercise as Medicine for Mental and Substance Use Disorders: A Meta-review of the Benefits for Neuropsychiatric and Cognitive Outcomes
No full textBACKGROUND: Exercise may improve neuropsychiatric and cognitive symptoms in people with mental disorders, but the totality of the evidence is unclear. We conducted a meta-review of exercise in (1) serious mental illness (schizophrenia spectrum, bipolar disorder and major depression (MDD)); (2) anxiety and stress disorders; (3) alcohol and substance use disorders; (4) eating disorders (anorexia nervosa bulimia nervosa, binge eating disorders, and (5) other mental disorders (including ADHD, pre/post-natal depression). METHODS: Systematic searches of major databases from inception until 1/10/2018 were undertaken to identify meta-analyses of randomised controlled trials (RCTs) of exercise in people with clinically diagnosed mental disorders. In the absence of available meta-analyses for a mental disorder, we identified systematic reviews of exercise interventions in people with elevated mental health symptoms that included non-RCTs. Meta-analysis quality was assessed with the AMSTAR/+. RESULTS: Overall, we identified 27 systematic reviews (including 16 meta-analyses representing 152 RCTs). Among those with MDD, we found consistent evidence (meta-analyses = 8) that exercise reduced depression in children, adults and older adults. Evidence also indicates that exercise was more effective than control conditions in reducing anxiety symptoms (meta-analyses = 3), and as an adjunctive treatment for reducing positive and negative symptoms of schizophrenia (meta-analyses = 2). Regarding neurocognitive effects, exercise improved global cognition in schizophrenia (meta-analyses = 1), children with ADHD (meta-analyses = 1), but not in MDD (meta-analyses = 1). Among those with elevated symptoms, positive mental health benefits were observed for exercise in people with pre/post-natal depression, anorexia nervosa/bulimia nervosa, binge eating disorder, post-traumatic stress disorder and alcohol use disorders/substance use disorders. Adverse events were sparsely reported. CONCLUSION: Our panoramic meta-overview suggests that exercise can be an effective adjunctive treatment for improving symptoms across a broad range of mental disorders.sponsorship: Brendon Stubbs holds a Clinical Lectureship supported by Health Education England and the NIHR Integrated Clinical Academic (ICA) Programme (ICA-CL-2017-03-001). Brendon Stubbs is also part supported by the Maudsley Charity and the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care South London at King's College Hospital NHS Foundation Trust. The views expressed are those of the author[s] and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. John Firth is supported by a Blackmores Institute Fellowship. Rebekah Carney is funded by the Research Capability Fund via Greater Manchester West Mental Health NHS Foundation Trust. Garcia Ashdown-Franks is funded by a Mitacs Globalink Research Award. (Health Education England, NIHR Integrated Clinical Academic (ICA) Programme|ICA-CL-2017-03-001, Maudsley Charity, National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care South London at King's College Hospital NHS Foundation Trust, Blackmores Institute Fellowship, Research Capability Fund via Greater Manchester West Mental Health NHS Foundation Trust, Mitacs Globalink Research Award)status: Publishe
QATAR-2 : a K dwarf orbited by a transiting hot Jupiter and a more massive companion in an outer orbit
No full textWe report the discovery and initial characterization of Qatar-2b, a hot Jupiter transiting a V = 13.3 mag K dwarf in a circular orbit with a short period, P b = 1.34 days. The mass and radius of Qatar-2b are M P = 2.49 M J and R P = 1.14 R J, respectively. Radial-velocity monitoring of Qatar-2 over a span of 153 days revealed the presence of a second companion in an outer orbit. The Systemic Console yielded plausible orbits for the outer companion, with periods on the order of a year and a companion mass of at least several M J. Thus, Qatar-2 joins the short but growing list of systems with a transiting hot Jupiter and an outer companion with a much longer period. This system architecture is in sharp contrast to that found by Kepler for multi-transiting systems, which are dominated by objects smaller than Neptune, usually with tightly spaced orbits that must be nearly coplanar
Surface functionalized gold nanoparticles as attachment inhibitors for heparan sulfate-binding viruses
No full textUnderstanding the abnormal brain activity in epilepsy as a potential predictor of the onset of an epileptic seizure
No full textThe Brain Research Institute (BRI) uses various types of indirect measurements, including EEG and fMRI, to understand and assess brain activity and function. As well as the recovery of generic information about brain function, research also focuses on the utilisation of such data and understanding to study the initiation, dynamics, spread and suppression of epileptic seizures. To assist with the future focussing of this aspect of their research, the BRI asked the MISG 2010 participants to examine how the available EEG and fMRI data and current knowledge about epilepsy should be analysed and interpreted to yield an enhanced understanding about brain activity occurring before, at commencement of, during, and after a seizure. Though the deliberations of the study group were wide ranging in terms of the related matters considered and discussed, considerable progress was made with the following three aspects. (1) The science behind brain activity investigations depends crucially on the quality of the analysis and interpretation of, as well as the recovery of information from, EEG and fMRI measurements. A number of specific methodologies were discussed and formalised, including independent component analysis, principal component analysis, profile monitoring and change point analysis (hidden Markov modelling, time series analysis, discontinuity identification). (2) Even though EEG measurements accurately and very sensitively record the onset of an epileptic event or seizure, they are, from the perspective of understanding the internal initiation and localisation, of limited utility. They only record neuronal activity in the cortical (surface layer) neurons of the brain, which is a direct reflection of the type of electrical activity they have been designed to record. Because fMRI records, through the monitoring of blood flow activity, the location of localised brain activity within the brain, the possibility of combining fMRI measurements with EEG, as a joint inversion activity, was discussed and examined in detail. (3) A major goal for the BRI is to improve understanding about ``when'' (at what time) an epileptic seizure actually commenced before it is identified on an eeg recording, ``where'' the source of this initiation is located in the brain, and ``what'' is the initiator. Because of the general agreement in the literature that, in one way or another, epileptic events and seizures represent abnormal synchronisations of localised and/or global brain activity the modelling of synchronisations was examined in some detail. References C. M. Michel, G. Thut, S. Morand, A. Khateb, A. J. Pegna, R. Grave de Peralta, S. Gonzalez, M. Seeck and T. Landis, Electric source imaging of human brain functions, Brain Res. Rev. , 36 (2--3), 2001, 108--118. doi:10.1016/S0165-0173(01)00086-8 S. Ogawa, R. S. Menon, S. G. Kim and K. Ugurbil, On the characteristics of functional magnetic resonance imaging of the brain, Annu. Rev. Bioph. Biom. , 27 , 1998, 447--474. doi:10.1146/annurev.biophys.27.1.447 C. D. Binnie and H. Stefan, Modern electroencephalography: its role in epilepsy management, Clin. Neurophysiol. , 110 (10), 1999, 1671--1697. doi:10.1016/S1388-2457(99)00125-X J. X. Tao, A. Ray, S. Hawes-Ebersole and J. S. Ebersole, Intracranial eeg substrates of scalp eeg interictal spikes, Epilepsia , 46 (5), 2005, 669--76. doi:10.1111/j.1528-1167.2005.11404.x S. Ogawa, D. W. Tank, R. Menon, J. M. Ellermann, S. G. Kim, H. Merkle and K. Ugurbil, Intrinsic signal changes accompanying sensory stimulation: Functional brain mapping with magnetic resonance imaging, P. Natl. Acad. Sci. USA , 89 (13), 1992, 5951--5955. doi:10.1073/pnas.89.13.5951 J. Engel Jr., Report of the ilae classification core group, Epilepsia , 47 (9), 2006, 1558--1568. doi:10.1111/j.1528-1167.2006.00215.x L. Lemieux, A. Salek-Haddadi, O. Josephs, P. Allen, N. Toms, C. Scott, K. Krakow, R. Turner and D. R. Fish, Event-related fmri with simultaneous and continuous eeg: description of the method and initial case r port, NeuroImage , 14 (3), 2001, 780--7. doi:10.1006/nimg.2001.0853 P. Federico, D. F. Abbott, R. S. Briellmann, A. S. Harvey and G. D. Jackson, Functional mri of the pre-ictal state, Brain , 128 (8), 2005, 1811-7. doi:10.1093/brain/awh533 C. S. Hawco, A. P. Bagshaw, Y. Lu, F. Dubeau and J. Gotman, bold changes occur prior to epileptic spikes seen on scalp eeg, NeuroImage , 35 (4), 2007, 1450--1458. doi:10.1016/j.neuroimage.2006.12.042 F. Moeller, H. R. Siebner, S. Wolff, H. Muhle, R. Boor, O. Granert, O. Jansen, U. Stephani and M. Siniatchkin, Changes in activity of striato-thalamo-cortical network precede generalized spike wave discharges, NeuroImage , 39 (4), 2008, 1839--1849. doi:10.1016/j.neuroimage.2007.10.058 V. Osharina, E. Ponchel, A. Aarabi, R. Grebe and F. Wallois, Local haemodynamic changes preceding interictal spikes: A simultaneous electrocorticography (ecog) and near-infrared spectroscopy (nirs) analysis in rats, NeuroImage , 50 (2), 2010, 600--607. doi:10.1016/j.neuroimage.2010.01.009 R. S. Fisher, W. Boas, W. Blume, C. Elger, P. Genton, P. Lee and J. Engel, Epileptic seizures and epilepsy: Definitions proposed by the international league against epilepsy (ilae) and the international bureau for epilepsy (ibe), Epilepsia , 46 (4), 2005, 470--472. doi:10.1111/j.0013-9580.2005.66104.x H. Berger, Electroencephalogram in humans, Arch. Psychiat. Nerven. , 87 , 1929, 527--570. C. M. Michel, M. M. Murray, G. Lantz, S. Gonzalez, L. Spinelli and R. G. de Peralta, eeg source imaging, Clin. Neurophysiol. , 115 (10), 2004, 2195--2222. doi:10.1016/j.clinph.2004.06.001 P. L. Nunez and R. B. Silberstein, On the relationship of synaptic activity to macroscopic measurements: Does co-registration of eeg with fmri make sense?, Brain Topogr. , 13 (2), 2000, 79--96. doi:10.1023/A:1026683200895 S. Ogawa, T. M. Lee, A. R. Kay and D. W. Tank, Brain magnetic resonance imaging with contrast dependent on blood oxygenation, P. Natl. Acad. Sci. USA , 87 (24), 1990, 9868--9872. doi:10.1073/pnas.87.24.9868 J. S. Gati, R. S. Menon, K. Ugurbil and B. K. Rutt, Experimental determination of the bold field strength dependence in vessels and tissue, Magn. Reson. Med. , 38 (2), 1997, 296--302. doi:10.1002/mrm.1910380220 P. A. Bandettini, E. C. Wong, R. S. Hinks, R. S. Tikofsky and J. S. Hyde, Time course EPI of human brain function during task activation, Magn. Reson. Med. , 25 (2), 1992, 390--397. K. K. Kwong, J. W. Belliveau, D. A. Chesler, I. E. Goldberg, R. M. Weisskoff, B. P. Poncelet, D. N. Kennedy, B. E. Hoppelm, M. S. Cohen and R. Turner, Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation, P. Natl. Acad. Sci. USA , 89 (12), 1992, 5675--5679. doi:10.1073/pnas.89.12.5675 J. Frahm, K. D. Merboldt and W. Hnicke, Functional mri of human brain activation at high spatial resolution, Magn. Reson. Med. , 29 (1), 1993, 139--144. P. A. Bandettini, A. Jesmanowicz, E. C. Wong and J. S. Hyde, Processing strategies for time-course data sets in functional MRI of the human brain, Magn. Reson. Med. , 30 (2), 1993, 161--173. K. J. Friston, P. Jezzard and R. Turner, Analysis of functional MRI time-series, Hum. Brain Mapp. , 1 (2), 1994, 153--171. B. Biswal, F. Z. Yetkin, V. M. Haughton and J. S. Hyde, Functional connectivity in the motor cortex of resting human brain using echo-planar mri, Mag. Reson. Med. , 34 (4), 1995, 537--541. doi:10.1002/mrm.1910340409 K. J. Friston, J. Ashburner, C. D. Frith, J. Poline, J. D. Heather and R. S. J. Frackowiak, Spatial registration and normalization of images, Hum. Brain Mapp. , 3 (3), 1995, 165--189. K. J. Friston, S. Williams, R. Howard, R. S. Frackowiak and R. Turner, Movement-related effects in fmri time-series, Magn. Reson. Med. , 35 (3), 1996, 346--355. G. H. Glover, T. Q. Li and D. Ress, Image-based method for retrospective correction of physiological motion effects in fmri: Retroicor, Magn. Reson. Med. , 44 (1), 2000, 162--167. doi:10.1002/1522-2594(200007)44:13.0.CO;2-E K. J. Friston, O. Josephs, G. Rees and R. Turner, Nonlinear event-related responses in fmri, Magn. Reson. Med. , 39 (1), 1998, 41--52. doi:10.1002/mrm.1910390109 K. Ugurbil, L. Toth and D. Kim, How accurate is magnetic resonance imaging of brain function?, Trends Neurosci. , 26 (2), 2003, 108--114. doi:10.1016/S0166-2236(02)00039-5 D. S. Kim, I. Ronen, C. Olman, S. G. Kim, K. Ugurbil and L. J. Toth, Spatial relationship between neuronal activity and bold functional mri, NeuroImage , 21 (3), 2004, 876--885. doi:10.1016/j.neuroimage.2003.10.018 A. Connelly, G. D. Jackson, R. S. Frackowiak, J. W. Belliveau, F. Vargha-Khadem and D. G. Gadian, Functional mapping of activated human primary cortex with a clinical mr imaging system, Radiology , 188 (1), 1993, 125--130. L. Allison, Hidden Markov Models, Technical Report , School of Computer and Software Engineering, Monash University, 2000. R. J. Elliott, L. Aggoun and J.B. Moore, Hidden Markov Models: Estimation and Control, Appl. Math.-Czech. , 2004. B. Bhavnagri, Discontinuities of plane functions projected from a surface with methods for finding these , Technical Report, 2009. B. Bhavnagri, Computer Vision using Shape Spaces , Technical Report,1996, University of Adelaide. B. Bhavnagri, A method for representing shape based on an equivalence relation on polygons, Pattern Recogn. , 27 (2), 1994, 247--260. doi:10.1016/0031-3203(94)90057-4 D. F. Abbott, A. B. Waites, A. S. Harvey and G. D. Jackson, Exploring epileptic seizure onset with fmri, NeuroImage , 36(S1) (344TH-PM), 2007. M. C. Mackey and L. Glass, Oscillation and chaos in physiological control systems, Science , 197 , 1977, 287--289. S. H. Strogatz, SYNC - The Emerging Science of Spontaneous Order , Theia, New York, 2003. J. W. Kim, J. A. Roberts and P. A. Robinson, Dynamics of epileptic seizures: Evolution, spreading, and suppression, J. Theor. Biol. , 257 (4), 2009, 527--532. doi:10.1016/j.jtbi.2008.12.009 Y. Kuramoto, T. Aoyagi, I. Nishikawa, T. Chawanya T and K. Okuda, Neural network model carrying phase information with application to collective dynamics, J. Theor. Phys. , 87 (5), 1992, 1119--1126. V. B. Mountcastle, The columnar organization of the neocortex, Brain , 120 (4), 1997, 701. doi:10.1093/brain/120.4.701 F. L. Silva, W. Blanes, S. N. Kalitzin, J. Parra, P. Suffczynski and D. N. Velis, Epilepsies as dynamical diseases of brain systems: Basic models of the transition between normal and epileptic activity, Epilepsia , 44 (12), 2003, 72--83. F. H. Lopes da Silva, W. Blanes, S. N. Kalitzin, J. Parra, P. Suffczynski and D. N. Velis, Dynamical diseases of brain systems: different routes to epileptic seizures, ieee T. Bio-Med. Eng. , 50 (5), 2003, 540. L.D. Iasemidis, Epileptic seizure prediction and control, ieee T. Bio-Med. Eng. , 50 (5), 2003, 549--558. L. D. Iasemidis, D. S. Shiau, W. Chaovalitwongse, J. C. Sackellares, P. M. Pardalos, J. C. Principe, P. R. Carney, A. Prasad, B. Veeramani, and K. Tsakalis, Adaptive epileptic seizure prediction system, ieee T. Bio-Med. Eng. , 50 (5), 2003, 616--627. K. Lehnertz, F. Mormann, T. Kreuz, R.G. Andrzejak, C. Rieke, P. David and C. E. Elger, Seizure prediction by nonlinear eeg analysis, ieee Eng. Med. Biol. , 22 (1), 2003, 57--63. doi:10.1109/MEMB.2003.1191451 K. Lehnertz, R. G. Andrzejak, J. Arnhold, T. Kreuz, F. Mormann, C. Rieke, G. Widman and C. E. Elger, Nonlinear eeg analysis in epilepsy: Its possible use for interictal focus localization, seizure anticipation, and prevention, J. Clin. Neurophysiol. , 18 (3), 2001, 209. B. Litt and K. Lehnertz, Seizure prediction and the preseizure period, Curr. Opin. Neurol. , 15 (2), 2002, 173. doi:10.1097/00019052-200204000-00008 B. Litt and J. Echauz, Prediction of epileptic seizures, Lancet Neurol. , 1 (1), 2002, 22--30. doi:10.1016/S1474-4422(02)00003-0 M. M{a}kiranta, J. Ruohonen, K Suominen, J. Niinim{a}ki, E. Sonkaj{a}rvi, V. Kiviniemi, T. Sepp{a}nen, S. Alahuhta, V. J{a}ntti and O. Tervonen, {bold} signal increase preceeds eeg spike activity--a dynamic penicillin induced focal epilepsy in deep anesthesia, NeuroImage , 27 (4), 2005, 715--724. doi:10.1016/j.neuroimage.2005.05.025 K. Lehnertz, F. Mormann, H. Osterhage, A. M{u}ller, J. Prusseit, A. Chernihovskyi, M. Staniek, D. Krug, S. Bialonski and C. E. Elger, State-of-the-art of seizure prediction, J. Clin. Neurophysiol. , 24 (2), 2007, 147. doi:10.1097/WNP.0b013e3180336f16 F. Mormann, T. Kreuz, C. Rieke, R. G. Andrzejak, A. Kraskov, P. David, C. E. Elger and K. Lehnertz, On the predictability of epileptic seizures, Clin. Neurophysiol. , 116 (3), 2005, 569--587. doi:10.1016/j.clinph.2004.08.025 F. Mormann, R. G. Andrzejak, C. E. Elger and K. Lehnertz, Seizure prediction: the long and winding road, Brain , 130 (2), 2007, 314--333. doi:10.1093/brain/awl241 Z. Rogowski, I. Gath and E. Bental, On the prediction of epileptic seizures, Biol. Cybern. , 42 (1), 1981, 9--15. Y. Salant, I. Gath, O. Henriksen, Prediction of epileptic seizures from two-channel eeg, Med. Biol. Eng. Comput. , 36 (5), 1998, 549--556. doi:10.1007/BF02524422 J. Gotman and D.J. Koffler, Interictal spiking increases after seizures but does not after decrease in medication, Evoked Potential , 72 (1), 1989, 7--15. J. Gotman and M. G. Marciani, Electroencephalographic spiking activity, drug levels, and seizure occurence in epileptic patients, Ann. Neurol. , 17 (6), 1985, 59--603. A. Katz, D. A. Marks, G. McCarthy and S. S. Spencer, Does interictal spiking change prior to seizures?, Electroen. Clin. Neuro. , 79 (2), 1991, 153--156. A. Granada, R. M. Hennig, B. Ronacher, A. Kramer and H. Herzel, Phase Response Curves: Elucidating the dynamics of couples oscillators, Method Enzymol. , 454 (A), 2009, 1--27. doi:10.1016/S0076-6879(08)03801-9 doi:10.1016/S0076-6879(08)03801-9 H. Kantz and T. Schreiber, Nonlinear time series analysis , 2004, Cambridge Univ Press. M. V. L. Bennett and R. S Zukin, Electrical coupling and neuronal synchronization in the mammalian brain, Neuron , 41 (4), 2004, 495 --511. doi:10.1016/S0896-6273(04)00043-1 L.D. Iasemidis, J. Chris Sackellares, H. P. Zaveri and W. J. Williams, Phase space topography and the Lyapunov exponent of electrocorticograms in partial seizures, Brain Topogr. , 2 (3), 1990, 187--201. doi:10.1007/BF01140588 M. Le Van Quyen, J. Martinerie, V. Navarro, M. Baulac and F. J. Varela, Characterizing neurodynamic changes before seizures, J. Clin. Neurophysiol. , 18 (3), 2001, 191. J. Martinerie, C. Adam, M. Le Van Quyen, M. Baulac, S. Clemenceau, B. Renault and F. J. Varela, Epileptic seizures can be anticipated by non-linear analysis, Nat. Med. , 4 (10), 1998, 1173--1176. doi:10.1038/2667 A. Pikovsky, M. Rosenblum, J. Kurths and R. C. Hilborn, Synchronization: A universal concept in nonlinear science, Amer. J. Phys. , 70 , 2002, 655. H. R. Wilson and J. D. Cowan, Excitatory and inhibitory interactions in localized populations of model neurons, Biophys. J. , 12 (1), 1972, 1--24. D. Cumin and C. P. Unsworth, Generalising the Kuramoto model for the study of neuronal synchronisation in the brain, Physica D , 226 (2), 2007, 181--196. doi:10.1016/j.physd.2006.12.004 F. K. Skinner, H. Bazzazi and S. A. Campbell, Two-cell to N-cell heterogeneous, inhibitory networks: Precise linking of multistable and coherent properties, J. Comput. Neurosci. , 18 (3), 2005, 343--352. doi:10.1007/s10827-005-0331-1 W. W. Lytton, Computer modelling of epilepsy, Nat. Rev. Neurosci. , 9 (8), 2008, 626--637. doi:10.1038/nrn2416 R. D. Traub, A. Bibbig, F. E. N. LeBeau, E. H. Buhl and M. A. Whittington, Cellular mechanisms of neuronal population oscillations in the hippocampus in vitro, Ann. Rev. , 2004. R. D. Traub, A. Draguhn, M. A. Whittington, T. Baldeweg, A. Bibbig, E. H. Buhl and D. Schmitz, Axonal gap junc ions between principal neurons: A novel source of network oscillations, and perhaps epileptogenesis., Rev. Neuroscience , 13 (1), 2002, 1. doi:10.1146/annurev.neuro.27.070203.144303 M. Scheffer, J. Bascompte, W. A. Brock, V. Brovkin, S. R. Carpenter, V. Dakos, H. Held, E. H. van Nes, M. Rietkerk and G. Sugihara, Early-warning signals for critical transitions, Nature , 461 (7260), 2009, 53--59. doi:10.1038/nature08227 K. Murphy, A Brief Introduction to Graphical Models and Bayesian Networks , 2008, http://www.cs.ubc.ca/murphyk/Bayes/bnintro.html . R. C. Bradley, An elementar
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