Epileptic high-frequency network activity in a model of non-lesional temporal lobe epilepsy

High-frequency cortical activity, particularly in the 250–600 Hz (fast ripple) band, has been implicated in playing a crucial role in epileptogenesis and seizure generation. Fast ripples are highly specific for the seizure initiation zone. However, evidence for the association of fast ripples with epileptic foci depends on animal models and human cases with substantial lesions in the form of hippocampal sclerosis, which suggests that neuronal loss may be required for fast ripples. In the present work, we tested whether cell loss is a necessary prerequisite for the generation of fast ripples, using a non-lesional model of temporal lobe epilepsy that lacks hippocampal sclerosis. The model is induced by unilateral intrahippocampal injection of tetanus toxin. Recordings from the hippocampi of freely-moving epileptic rats revealed high-frequency activity (4100 Hz), including fast ripples. High-frequency activity was present both during interictal discharges and seizure onset. Interictal fast ripples proved a significantly more reliable marker of the primary epileptogenic zone than the presence of either interictal discharges or ripples (100–250 Hz). These results suggest that fast ripple activity should be considered for its potential value in the pre-surgical workup of non-lesional temporal lobe epilepsy

Defining the Problem and Searching for Solutions: Insurers, Employers, and State Government

Panel discussion: Some solutions to the uninsured problem happening right here in Cleveland. The Health Policy Coalition is a group which presents health insurance reform ideas to Congress. Charles Weller talked about the Coalition. Powell Woods described the Cleveland Health Quality Choice Program as follows: Cleveland Health Quality Choice is based upon the principle that if we figure out a way to reward high quality and cost efficiency as the twin lynch pins of reimbursement in our health purchasing system, we can drive both quality and efficiency gains in the system which can help produce savings which will in turn help underwrite the problem of coverage for the uninsured. E. John Polk discussed employee health insurance programs offered by the Council of Smaller Enterprises (COSE). Kenneth Seminatore represented Blue Cross and Blue Shield of Ohio. He proposed that the price escalation problem be solved by well-managed competition, such as that created by the 1987 of Senate Bill 124, the Health Insurance Reform Act. Mr. Seminatore also mentioned the problem of mandated benefits, stating, A study by Dr. John Goodman of Dallas indicates that perhaps 20 percent of the uninsured nationally are uninsured because they\u27re priced out of the market by mandated benefits they neither want, their insurance companies don\u27t want to offer, and they can\u27t afford. He also proposed Medicaid buy-in for the working poor

Defining the Problem and Searching for Solutions: Insurers, Employers, and State Government

Panel discussion: Some solutions to the uninsured problem happening right here in Cleveland. The Health Policy Coalition is a group which presents health insurance reform ideas to Congress. Charles Weller talked about the Coalition. Powell Woods described the Cleveland Health Quality Choice Program as follows: Cleveland Health Quality Choice is based upon the principle that if we figure out a way to reward high quality and cost efficiency as the twin lynch pins of reimbursement in our health purchasing system, we can drive both quality and efficiency gains in the system which can help produce savings which will in turn help underwrite the problem of coverage for the uninsured. E. John Polk discussed employee health insurance programs offered by the Council of Smaller Enterprises (COSE). Kenneth Seminatore represented Blue Cross and Blue Shield of Ohio. He proposed that the price escalation problem be solved by well-managed competition, such as that created by the 1987 of Senate Bill 124, the Health Insurance Reform Act. Mr. Seminatore also mentioned the problem of mandated benefits, stating, A study by Dr. John Goodman of Dallas indicates that perhaps 20 percent of the uninsured nationally are uninsured because they\u27re priced out of the market by mandated benefits they neither want, their insurance companies don\u27t want to offer, and they can\u27t afford. He also proposed Medicaid buy-in for the working poor

2013-14 Guest Artist Series: American Brass Quintet

Kennesaw State University School of Music presents the American Brass Quintet.https://digitalcommons.kennesaw.edu/musicprograms/1385/thumbnail.jp

2011-2012 Collaborative Spotlight: The American Brass Quintet

Past Collaborative Spotlight Concerts 2011 - Duo Pianists Leonard and Shenhttps://spiral.lynn.edu/conservatory_otherseasonalconcerts/1017/thumbnail.jp

Streambed scour and fill in low‐order dryland channels

Reproduced with permission of the publisher. ©2005. American Geophysical UnionDistributions of scour and fill depths recorded in three low‐order sand bed dryland rivers were compared with the Weibull, gamma, exponential, and lognormal probability density functions to determine which model best describes the reach‐scale variability in scour and fill. Goodness of fit tests confirm that the majority of scour distributions conform to the one‐parameter exponential model at the 95% significance level. The positive relationship between exponential model parameters and flow strength provides a means to estimate streambed scour depths, at least to a first approximation, in comparable streams. In contrast, the majority of the fill distributions do not conform to the exponential model even though depths of scour and fill are broadly similar. The disparities between the distributions of scour and fill raise questions about notions of channel equilibrium and about the role of scour and fill in effecting channel change

Genetic Population Structure of Mule Deer Odocoileus Hemionus Across Montana

We conducted a genetic assessment of mule deer (Odocoileus hemionus) population structure across Montana in an effort to understand dispersal routes across the landscape. To assess genetic structure we genotyped 14 microsatellite loci in 359 individuals sampled primarily within Montana. Smaller samples were included from Wyoming, Colorado and Utah in order to provide a regional context for the levels of population structure observed within Montana. Additionally, we sequenced the control region of the mitochondrial genome of 76 individuals subsampled from our original samples across Montana. To avoid potential influences of a priori population designations, individual based analyses were used to test relatedness across the landscape. Weak isolation by distance characterized mule deer individuals across this region. In addition, we did not detect any evidence of spatial autocorrelation in discrete distance classes as small as 10 km. Female mule deer had higher average individual pairwise genetic distances than males, indicating the presence of a contemporary male bias in dispersal rates. Mitochondrial DNA indicated the potential for either reduced overall or female-specific dispersal between a subset of the sampling regions within Montana. Finally, we were unable to detect a genetic signature of past translocations of mule deer across Montana. Taken together these results indicate that within this landscape mule deer populations are characterized by high levels of connectivity and experience few, if any, barriers to dispersal

Robust artificial neural networks and outlier detection. Technical report

Large outliers break down linear and nonlinear regression models. Robust regression methods allow one to filter out the outliers when building a model. By replacing the traditional least squares criterion with the least trimmed squares criterion, in which half of data is treated as potential outliers, one can fit accurate regression models to strongly contaminated data. High-breakdown methods have become very well established in linear regression, but have started being applied for non-linear regression only recently. In this work, we examine the problem of fitting artificial neural networks to contaminated data using least trimmed squares criterion. We introduce a penalized least trimmed squares criterion which prevents unnecessary removal of valid data. Training of ANNs leads to a challenging non-smooth global optimization problem. We compare the efficiency of several derivative-free optimization methods in solving it, and show that our approach identifies the outliers correctly when ANNs are used for nonlinear regression