Claudia Lizbeth Martínez-González

Fractal Analysis of EEG Signals in the Brain of Epileptic Rats, with and without Biocompatible Implanted Neuroreservoirs

Current epilepsy rates in Mexico are 4% (SERSAME-Health Ministry), of which 80% correspond to Temporal Lobe Epilepsy (TLE). Antiepileptic drug administration is systemic, meaning that 90% of the active agent is lost between administration and delivery to the epileptic focus in the brain. Severe toxic secondary effects may occur as a result. The present study is aimed at developing an alternative antiepileptic drug delivery system. In this study, a sol-gel nanostructured titania device, in which valproic acid (VPA) has been encapsulated. This is a nanoparticulate device, which is biocompatible with brain tissue. Stereotactic surgery was used to implant the reservoirs in the temporal lobe of Wistar rats, using chemical kindling, which was used to induce epilepsy. The reservoir was designed to release the drug at a constant rate over a period of at least one year. A functional study was performed on the efficiency of drug delivery in order to evaluate the effect on spontaneous and induced neuron electrical activity. A new discovery, which is presented here, shows that in the case of damaged brain tissue, as is the case in epilepsy, the accumulation of red globules, oxygen transportation results in the formation of calcium carbonate crystals which surround the epileptic focus. Because these crystals have a specific polarization, we propose to characterize their influence on the EEG using statistical methods. The electrical activity was measured by electroencephalography using 5 healthy rats without and 5 rats with an implanted VPA/device. Cerebral signals describe the complex behavior of the brain dynamics as a function of time. Fractal algorithms are sensitive to fluctuations and lead to the analysis and characterization of this kind of complex phenomena. A systematic study of these EEG’s was made in order to observe the variation of signals during seizures and on the controlled rate of release of VPA. We have estimated the Hurst exponent (H) to measure long range-dependence. Preliminary results show that for the control group, signal behavior is persistent (H>0.5), while for the epileptic group antipersistency was observed (H<0.5), with variations due seizure stages. During the protection period using VPA, preliminary results show that values tend to reach original behavior, as the crisis is stabilized.

Effect of Heterogeneity in Initial Geographic Distribution on Opinions’ Competitiveness

Spin dynamics on networks allows us to understand how a global consensus emerges out of individual opinions. Here, we are interested in the effect of heterogeneity in the initial geographic distribution of a competing opinion on the competitiveness of its own opinion. Accordingly, in this work, we studied the effect of spatial heterogeneity on the majority rule dynamics using a three-state spin model, in which one state is neutral. Monte Carlo simulations were performed on square lattices divided into square blocks (cells). Accordingly, one competing opinion was distributed uniformly among cells, whereas the spatial distribution of the rival opinion was varied from the uniform to heterogeneous, with the median-to-mean ratio in the range from 1 to 0. When the size of discussion group is odd, the uncommitted agents disappear completely after 3.30 ± 0.05 update cycles, and then the system evolves in a two-state regime with complementary spatial distributions of two competing opinions. Even so, the initial heterogeneity in the spatial distribution of one of the competing opinions causes a decrease of this opinion competitiveness. That is, the opinion with initially heterogeneous spatial distribution has less probability to win, than the opinion with the initially uniform spatial distribution, even when the initial concentrations of both opinions are equal. We found that although the time to consensus , the opinion’s recession rate is determined during the first 3.3 update cycles. On the other hand, we found that the initial heterogeneity of the opinion spatial distribution assists the formation of quasi-stable regions, in which this opinion is dominant. The results of Monte Carlo simulations are discussed with regard to the electoral competition of political parties.

Behavioral and electroencephalographic evaluation of the anticonvulsive activity of Moringa oleifera leaf non-polar extracts and one metabolite in PTZ-induced seizures

BACKGORUND Moringa oleifera Lamarck is a species that has long been used in high demand in folk medicine, including for the treatment of epilepsy. Nevertheless, scientific studies demonstrating its anticonvulsant properties and the nature of the bioactive constituents are lacking. HYPOTHESIS/AIM The aim of this study was to evaluate the anticonvulsant activities of the Moringa oleifera leaves in non-polar vs. polar extracts using behavioral and electroencephalographic (EEG) analyses in rodents. METHODS First, PTZ (80 mg/kg, i.p.)-induced tonic-clonic seizures were assayed via a dose-response (100, 200 and 300 mg/kg, i.p.) evaluation in mice. Then, a dosage of the extracts (100 or 300 mg/kg) and one metabolite (30 mg/kg, i.p.) was selected to evaluate its effect on PTZ (35 mg/kg, i.p.)-induced EEG paroxystic activities in rats compared to the effects of ethosuximide (reference anticonvulsant drug, 100 mg/kg, i.p.). Latent onset of the first paroxystic spike, first seizure and frequency as well as seizure severity, were determined using Racines scale. RESULTS Moringa oleifera ethanol and hexane extracts produced a delay in the seizure latency in mice and rats; this effect was improved in the presence of the hexane extract containing the active metabolite hexadecanoic acid. The anticonvulsant effects were corroborated in the spectral analysis by the potency of the EEG due to a reduction in the spike frequency and amplitude, as well as in the duration and severity of the seizures. The effects of the hexane extract resembled those observed in the reference antiepileptic drug ethosuximide. CONCLUSION Moringa oleifera leaves possess anticonvulsant activities due to the complementary of the non-polar and polar constituents. However, the non-polar constituents appear to exert an important influence via the partial participation of fatty acids, providing evidence of the effects of this plant in epilepsy therapy.

\({\mathrm {CB_{p}F}}\)-IQA: Using Contrast Band-Pass Filtering as Main Axis of Visual Image Quality Assessment

Our proposal is to present a Blind and Reference Image Quality Assessment or CBPF-IQA. Thus, the main proposal of this paper is to propose an Interface, which contains not only a Full-Reference Image Quality Assessment (IQA) but also a No-Reference or Blind IQA applying perceptual concepts by means of Contrast Band-Pass Filtering (CBPF). Then, this proposal consists, in contrast, a degraded input image with the filtered versions of several distances by a CBPF, which computes some of the Human Visual System (HVS) variables. If CBPF-IQA detects only one input, it performs a Blind Image Quality Assessment, on the contrary, if CBPF-IQA detects two inputs, it considers that a Reference Image Quality Assessment will be computed. Thus, we first define a Full-Reference IQA and then a No-Reference IQA, which correlation is important when is contrasted with the psychophysical results performed by several observers. CBPF-IQA weights the Peak Signal-to-Noise Ratio by using an algorithm that estimates some properties of the Human Visual System. Then, we compare \({\mathrm {CB_{p}F}}\)-IQA algorithm not only with the mainstream estimator in IQA and PSNR but also state-of-the-art IQA algorithms, such as Structural SIMilarity (SSIM), Mean Structural SIMilarity (MSSIM), and Visual Information Fidelity (VIF). Our experiments show that the correlation of CBPF-IQA correlated with PSNR is important, but this proposal does not need imperatively the reference image in order to estimate the quality of the recovered image.

Evaluation of dynamic scaling of growing interfaces in EEG fluctuations of seizures in animal model of temporal lobe epilepsy

Epileptic seizures, as a dynamic phenomenon in brain behavior, obey a scale-free behavior, frequently analyzed by electrical activity recording. This recording can be seen as a surface that roughens with time. Dynamic scaling studies roughening processes or growing interfaces. In this theory, a set of exponents -obtained from scale invariance properties- characterize rough interfaces growth. The aim of the present study was to investigate scaling behavior in EEG time series fluctuations of a chemical animal model of temporal lobe epilepsy, with dynamic scaling to detect changes on seizure onset. We analyzed local variables in different sampling intervals and estimated rough, scaling and dynamic exponents. Results exhibited long-range correlations in interictal activity. Results of renormalization and data collapsing confirmed that each epoch of EEG fluctuations for interictal, preictal and postictal collapse in a curve in different scales, each segment independently; remarkably, we found non-scaling behavior in seizures epochs. Data for the different sampling intervals for ictal period do not collapse in one curve, which implies that ictal activity does not exhibit the same scaling behavior than the other epochs. Statistical significant differences of growth exponent were found between interictal and ictal segment, while for scaling exponent, significant differences were found between interictal and postictal segment. These results confirm the potential of scaling exponents as characteristic parameters to detect changes on seizure onset, which suggests their use as inputs for analysis methods for seizure detection in long-term recordings, while changes in growth exponent are potentially useful for prediction purposes.