Seizure states identification in experimental epilepsy using gabor atom analysis

Background: Epileptic seizures evolve through several states, and in the process the brain signals may change dramatically. Signals from different states share similar features, making it difficult to distinguish them from a time series; the goal of this work is to build a classifier capable of identifying seizure statesbased on time frequency features taken from short signal segments.Methods: There are different amounts of frequency components within each Time Frequency window foreach seizure state, referred to as the Gabor atom density. Taking short signal segments from the differentstates and decomposing them into their atoms, the present paper suggests that is possible to identifyeach seizure state based on the Gabor atom density. The brain signals used in this work were taken for a database of intracranial recorded seizures from the Kindling model.Results: The findings suggest that short signal segments have enough information to be used to derivea classifier able to identify the seizure states with reasonable confidence, particularly when used withseizures from the same subject. Achieving average sensitivity values between 0.82 and 0.97, and areaunder the curve values between 0.5 and 0.9. Conclusions: The experimental results suggest that seizure states can be revealed by the Gabor atom density; and combining this feature with the epoch s energy produces an improved classifier. These results are comparable with the recently published on state identification. In addition, considering that the order of seizure states is unlikely to change, these results are promising for automatic seizure state classification.Thanks are extended to the Hospital Universitario de Valencia, for sharing their signal database and to Francisco Sancho for his support. Finally, thanks are given to Dr. Luis N. Coria for his support and the proofreading support. Partial funding for this work was provided by CONACYT Basic Science Research Project No. 178323, DGEST (Mexico) Research Projects No. 5149.13-P, 5414.14-P and TIJ-ING-2012-110, and IRSES project ACoBSEC financed by the European Commission.Sotelo Orozco, A.; Guijarro Estelles, ED.; Trujillo, L. (2015). Seizure states identification in experimental epilepsy using gabor atom analysis. Journal of Neuroscience Methods. 241:121-131. https://doi.org/10.1016/j.jneumeth.2014.12.001S12113124

Controversies in epilepsy: Debates held during the Fourth International Workshop on Seizure Prediction

Debates on six controversial topics were held during the Fourth International Workshop on Seizure Prediction (IWSP4) convened in Kansas City, KS, USA, July 4–7, 2009. The topics were (1) Ictogenesis: Focus versus Network? (2) Spikes and Seizures: Step-relatives or Siblings? (3) Ictogenesis: A Result of Hyposynchrony? (4) Can Focal Seizures Be Caused by Excessive Inhibition? (5) Do High-Frequency Oscillations Provide Relevant Independent Information? (6) Phase Synchronization: Is It Worthwhile as Measured? This article, written by the IWSP4 organizing committee and the debaters, summarizes the arguments presented during the debates

On the methodological unification in electroencephalography

BACKGROUND: This paper presents results of a pursuit of a repeatable and objective methodology of analysis of the electroencephalographic (EEG) time series. METHODS: Adaptive time-frequency approximations of EEG are discussed in the light of the available experimental and theoretical evidence, and applicability in various experimental and clinical setups. RESULTS: Four lemmas and three conjectures support the following conclusion. CONCLUSION: Adaptive time-frequency approximations of signals unify most of the univariate computational approaches to EEG analysis, and offer compatibility with its traditional (visual) analysis, used in clinical applications

Coupling N2 and CO2 in H2O to synthesize urea under ambient conditions

© 2020, The Author(s), under exclusive licence to Springer Nature Limited. The use of nitrogen fertilizers has been estimated to have supported 27% of the world’s population over the past century. Urea (CO(NH2)2) is conventionally synthesized through two consecutive industrial processes, N2 + H2 → NH3 followed by NH3 + CO2 → urea. Both reactions operate under harsh conditions and consume more than 2% of the world’s energy. Urea synthesis consumes approximately 80% of the NH3 produced globally. Here we directly coupled N2 and CO2 in H2O to produce urea under ambient conditions. The process was carried out using an electrocatalyst consisting of PdCu alloy nanoparticles on TiO2 nanosheets. This coupling reaction occurs through the formation of C–N bonds via the thermodynamically spontaneous reaction between *N=N* and CO. Products were identified and quantified using isotope labelling and the mechanism investigated using isotope-labelled operando synchrotron-radiation Fourier transform infrared spectroscopy. A high rate of urea formation of 3.36 mmol g–1 h–1 and corresponding Faradic efficiency of 8.92% were measured at –0.4 V versus reversible hydrogen electrode. [Figure not available: see fulltext.