Predicting spike timing of neocortical pyramidal neurons by simple threshold models

Neurons generate spikes reliably with millisecond precision if driven by a fluctuating current--is it then possible to predict the spike timing knowing the input? We determined parameters of an adapting threshold model using data recorded in vitro from 24 layer 5 pyramidal neurons from rat somatosensory cortex, stimulated intracellularly by a fluctuating current simulating synaptic bombardment in vivo. The model generates output spikes whenever the membrane voltage (a filtered version of the input current) reaches a dynamic threshold. We find that for input currents with large fluctuation amplitude, up to 75% of the spike times can be predicted with a precision of +/-2 ms. Some of the intrinsic neuronal unreliability can be accounted for by a noisy threshold mechanism. Our results suggest that, under random current injection into the soma, (i) neuronal behavior in the subthreshold regime can be well approximated by a simple linear filter; and (ii) most of the nonlinearities are captured by a simple threshold process.

Increased proximal urethral sensory threshold after radical pelvic surgery in women

AIM: To identify factors that potentially influence urethral sensitivity in women. PATIENTS AND METHODS: The current perception threshold was measured by double ring electrodes in the proximal and distal urethra in 120 women. Univariate analysis using Kaplan-Meier models and multivariate analysis applying Cox regressions were performed to identify factors influencing urethral sensitivity in women. RESULTS: In univariate and multivariate analysis, women who had undergone radical pelvic surgery (radical cystectomy n = 12, radical rectal surgery n = 4) showed a significantly (log rank test P < 0.0001) increased proximal urethral sensory threshold compared to those without prior surgery (hazard ratio (HR) 4.17, 95% confidence interval (CI) 2.04-8.51), following vaginal hysterectomy (HR 4.95, 95% CI 2.07-11.85), abdominal hysterectomy (HR 5.96, 95% CI 2.68-13.23), or other non-pelvic surgery (HR 4.86, 95% CI 2.24-10.52). However, distal urethral sensitivity was unaffected by any form of prior surgery. Also other variables assessed, including age, concomitant diseases, urodynamic diagnoses, functional urethral length, and maximum urethral closure pressure at rest had no influence on urethral sensitivity in univariate as well as in multivariate analysis. CONCLUSIONS: Increased proximal but unaffected distal urethral sensory threshold after radical pelvic surgery in women suggests that the afferent nerve fibers from the proximal urethra mainly pass through the pelvic plexus which is prone to damage during radical pelvic surgery, whereas the afferent innervation of the distal urethra is provided by the pudendal nerve. Better understanding the innervation of the proximal and distal urethra may help to improve surgical procedures, especially nerve sparing techniques. Neurourol. Urodynam. (c) 2006 Wiley-Liss, Inc.

TRIO LOGIC REGRESSION - DETECTION OF SNP - SNP INTERACTIONS IN CASE-PARENT TRIOS

Statistical approaches to evaluate higher order SNP-SNP and SNP-environment interactions are critical in genetic association studies, as susceptibility to complex disease is likely to be related to the interaction of multiple SNPs and environmental factors. Logic regression (Kooperberg et al., 2001; Ruczinski et al., 2003) is one such approach, where interactions between SNPs and environmental variables are assessed in a regression framework, and interactions become part of the model search space. In this manuscript we extend the logic regression methodology, originally developed for cohort and case-control studies, for studies of trios with affected probands. Trio logic regression accounts for the linkage disequilibrium (LD) structure in the genotype data, and accommodates missing genotypes via haplotype-based imputation. We also derive an efficient algorithm to simulate case-parent trios where genetic risk is determined via epistatic interactions.

Concordance Probability and Discriminatory Power in Proportional Hazards Regression

The concordance probability is used to evaluate the discriminatory power and the predictive accuracy of nonlinear statistical models. We derive an analytic expression for the concordance probability in the Cox proportional hazards model. The proposed estimator is a function of the regression parameters and the covariate distribution only and does not use the observed event and censoring times. For this reason it is asymptotically unbiased, unlike Harrell's c-index based on informative pairs. The asymptotic distribution of the concordance probability estimate is derived using U-statistic theory and the methodology is applied to a predictive model in lung cancer.

Large Sample Theory for Semiparametric Regression Models with Two-Phase, Outcome Dependent Sampling

Outcome-dependent, two-phase sampling designs can dramatically reduce the costs of observational studies by judicious selection of the most informative subjects for purposes of detailed covariate measurement. Here we derive asymptotic information bounds and the form of the efficient score and influence functions for the semiparametric regression models studied by Lawless, Kalbfleisch, and Wild (1999) under two-phase sampling designs. We show that the maximum likelihood estimators for both the parametric and nonparametric parts of the model are asymptotically normal and efficient. The efficient influence function for the parametric part aggress with the more general information bound calculations of Robins, Hsieh, and Newey (1995). By verifying the conditions of Murphy and Van der Vaart (2000) for a least favorable parametric submodel, we provide asymptotic justification for statistical inference based on profile likelihood.

Ondansetron does not reduce the shivering threshold in healthy volunteers

BACKGROUND: Ondansetron, a serotonin-3 receptor antagonist, reduces postoperative shivering. Drugs that reduce shivering usually impair central thermoregulatory control, and may thus be useful for preventing shivering during induction of therapeutic hypothermia. We determined, therefore, whether ondansetron reduces the major autonomic thermoregulatory response thresholds (triggering core temperatures) in humans. METHODS: Control (placebo) and ondansetron infusions at the target plasma concentration of 250 ng ml(-1) were studied in healthy volunteers on two different days. Each day, skin and core temperatures were increased to provoke sweating; then reduced to elicit peripheral vasoconstriction and shivering. We determined the core-temperature sweating, vasoconstriction and shivering thresholds after compensating for changes in mean-skin temperature. Data were analysed using t-tests and presented as means (sds); P<0.05 was taken as significant. RESULTS: Ondensetron plasma concentrations were 278 (57), 234 (55) and 243 (58) ng ml(-1) at the sweating, vasoconstriction and shivering thresholds, respectively; these corresponded to approximately 50 mg of ondansetron which is approximately 10 times the dose used for postoperative nausea and vomiting. Ondansetron did not change the sweating (control 37.4 (0.4) degrees C, ondansetron 37.6 (0.3) degrees C, P=0.16), vasoconstriction (37.0 (0.5) degrees C vs 37.1 (0.3) degrees C; P=0.70), or shivering threshold (36.3 (0.5) degrees C vs 36.3 (0.6) degrees C; P=0.76). No sedation was observed on either study day. CONCLUSIONS: /b>. Ondansetron appears to have little potential for facilitating induction of therapeutic hypothermia.

Detection of approximal caries with a new laser fluorescence device

The laser device DIAGNOdent developed for the detection of occlusal caries has limited value on approximal surfaces. The aim of this study was to develop and to test a new laser fluorescence (LF) device for the detection of approximal caries. Light with a wavelength of 655 nm was transported to the approximal surface using two different sapphire fibre tips. Seventy-five teeth were selected from a pool of extracted permanent human molars, frozen at -20 degrees C until use. Before being measured, they were defrosted, cleaned and calculus was removed with a scaler. The molars were set in blocks simulating the contact area of adults. Bitewing radiographs were obtained using Kodak Insight films. After two independent assessments with the new LF device, the teeth were histologically prepared, and assessed for caries extension. Using the laser, specificity values for D1 threshold (outer half of enamel), D2 threshold (inner half of enamel), D3 threshold (dentine) ranged between 0.81 and 0.93, sensitivity between 0.84 and 0.92 with no difference between the two tips. Bitewing radiography showed an inferior performance compared to LF (p<0.05). Intraex aminer reproducibility was high (kappa>.74). The new LF system might be a useful additional tool in detecting approximal caries. Because of its good reproducibility, it could be used to monitor caries regression or progression on approximal surfaces.

The Importance of Scale for Spatial-confounding Bias and Precision of Spatial Regression Estimators

Increasingly, regression models are used when residuals are spatially correlated. Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants. I consider the effects of residual spatial structure on the bias and precision of regression coefficients, developing a simple framework in which to understand the key issues and derive informative analytic results. When the spatial residual is induced by an unmeasured confounder, regression models with spatial random effects and closely-related models such as kriging and penalized splines are biased, even when the residual variance components are known. Analytic and simulation results show how the bias depends on the spatial scales of the covariate and the residual; bias is reduced only when there is variation in the covariate at a scale smaller than the scale of the unmeasured confounding. I also discuss how the scales of the residual and the covariate affect efficiency and uncertainty estimation when the residuals can be considered independent of the covariate. In an application on the association between black carbon particulate matter air pollution and birth weight, controlling for large-scale spatial variation appears to reduce bias from unmeasured confounders, while increasing uncertainty in the estimated pollution effect.