How behavioral constraints may determine optimal sensory representations

The sensory-triggered activity of a neuron is typically characterized in terms of a tuning curve, which describes the neuron's average response as a function of a parameter that characterizes a physical stimulus. What determines the shapes of tuning curves in a neuronal population? Previous theoretical studies and related experiments suggest that many response characteristics of sensory neurons are optimal for encoding stimulus-related information. This notion, however, does not explain the two general types of tuning profiles that are commonly observed: unimodal and monotonic. Here I quantify the efficacy of a set of tuning curves according to the possible downstream motor responses that can be constructed from them. Curves that are optimal in this sense may have monotonic or nonmonotonic profiles, where the proportion of monotonic curves and the optimal tuning-curve width depend on the general properties of the target downstream functions. This dependence explains intriguing features of visual cells that are sensitive to binocular disparity and of neurons tuned to echo delay in bats. The numerical results suggest that optimal sensory tuning curves are shaped not only by stimulus statistics and signal-to-noise properties but also according to their impact on downstream neural circuits and, ultimately, on behavior.     

The relationship between virologic and immunologic responses in AIDS clinical research using mixed-effects varying-coefficient models with measurement error

In this article we study the relationship between virologic and immunologic responses in AIDS clinical trials. Since plasma HIV RNA copies (viral load) and CD4+ cell counts are crucial virologic and immunologic markers for HIV infection, it is important to study their relationship during HIV/AIDS treatment. We propose a mixed-effects varying-coefficient model based on an exploratory analysis of data from a clinical trial. Since both viral load and CD4+ cell counts are subject to measurement error, we also consider the measurement error problem in covariates in our model. The regression spline method is proposed for inference for parameters in the proposed model. The regression spline method transforms the unknown nonparametric components into parametric functions. It is relatively simple to implement using readily available software, and parameter inference can be developed from standard parametric models. We apply the proposed models and methods to an AIDS clinical study. From this study, we find an interesting relationship between viral load and CD4+ cell counts during antiviral treatments. Biological interpretations and clinical implications are discussed.     

Kernel estimates of dose response

A nonparametric method for analyzing quantal response data from an indirect bioassay experiment is proposed. Kernel estimates of the dose-response curve are used to develop approximate confidence intervals for (i) the optimal combination dose of a drug with therapeutic effects at low doses and toxic effects at high doses, and (ii) the lethal dose levels of a toxic chemical. This nonparametric procedure was implemented on real and simulated data. The confidence interval for problem (i) has high coverage probabilities when the dose-response curve is symmetric about the optima. However, the coverage probabilities are adversely affected by asymmetry about the optima and consequently are not reliable unless the sample sizes are large. The use of kernel estimators with higher-order kernels may alleviate this sensitivity to asymmetry. The confidence interval for problem (ii) has high coverage probabilities robust with respect to the shape or symmetry of the underlying dose-response curve.     

Competition-similarity relationships and the nonlinearity of competitive effects in consumer-resource systems

Much previous ecological and evolutionary theory about exploitative competition for a continuous spectrum of resources has used the Lotka-Volterra model with competition coefficients given by a Gaussian function of niche separation. Using explicit consumer-resource models, we show that the Lotka-Volterra model and the assumption of a Gaussian competition-similarity relationship both fail to reflect the impact of strong resource depletion, which typically reduces the influence of the most heavily used resources on the competitive interaction. Taking proper account of resource depletion reveals that strong exploitative competition between efficient consumers is usually a highly nonlinear interaction, implying that a single measure is no longer sufficient to characterize the process. The nonlinearity usually entails weak coupling of competing species when their abundances are high and equal. Rare invaders are likely to have effects on abundant residents much larger than those of the resident on the invader. Asymmetrical utilization curves often produce asymmetrical competition coefficients. Competition coefficients are typically non-Gaussian and are often nonmonotonic functions of niche separation. Utilization curve shape and resource growth functions can have major effects on competition-similarity relationships. A variety of previous theoretical findings need to be reassessed in light of these results.     

The mammary gland response to estradiol: monotonic at the cellular level, non-monotonic at the tissue-level of organization?

The role of hormones in mammary gland development has been studied in detail using surgical and genetic models. These studies have indicated roles for estrogen in ductal elongation and terminal end bud formation. However, no comprehensive study has quantified how different doses of estrogen affect morphological parameters of mammary gland development. Additionally, comparisons between the estrogen-responsiveness of the mammary gland and uterus, the model organ for estrogen action are incomplete. In this study, immature mice were ovariectomized and implanted with osmotic pumps releasing one of eight doses of 17β-estradiol for 10 days. As expected from the classical uterotrophic assay, the uterus showed a monotonic dose–response curve for all measured endpoints. In contrast, the mammary gland showed a non-monotonic, inverted-U shaped response to estrogen with regard to morphometric parameters, and a monotonic response with regard to gene expression parameters. These results indicate that estrogen has opposing effects in mammary gland morphogenesis depending on estrogen dose, i.e. low to moderate doses induce terminal end bud formation and ductal elongation while higher doses inhibit these processes. This non-monotonic dose–response in the mammary gland may reflect complex interactions, where estrogen can act on multiple targets either as an agonist or antagonist.     

An In-Depth Comparison of Latent HIV-1 Reactivation in Multiple Cell Model Systems and Resting CD4+ T Cells from Aviremic Patients

The possibility of HIV-1 eradication has been limited by the existence of latently infected cellular reservoirs. Studies to examine control of HIV latency and potential reactivation have been hindered by the small numbers of latently infected cells found in vivo. Major conceptual leaps have been facilitated by the use of latently infected T cell lines and primary cells. However, notable differences exist among cell model systems. Furthermore, screening efforts in specific cell models have identified drug candidates for “anti-latency” therapy, which often fail to reactivate HIV uniformly across different models. Therefore, the activity of a given drug candidate, demonstrated in a particular cellular model, cannot reliably predict its activity in other cell model systems or in infected patient cells, tested ex vivo. This situation represents a critical knowledge gap that adversely affects our ability to identify promising treatment compounds and hinders the advancement of drug testing into relevant animal models and clinical trials. To begin to understand the biological characteristics that are inherent to each HIV-1 latency model, we compared the response properties of five primary T cell models, four J-Lat cell models and those obtained with a viral outgrowth assay using patient-derived infected cells. A panel of thirteen stimuli that are known to reactivate HIV by defined mechanisms of action was selected and tested in parallel in all models. Our results indicate that no single in vitro cell model alone is able to capture accurately the ex vivo response characteristics of latently infected T cells from patients. Most cell models demonstrated that sensitivity to HIV reactivation was skewed toward or against specific drug classes. Protein kinase C agonists and PHA reactivated latent HIV uniformly across models, although drugs in most other classes did not.     

不同时程弱前掩蔽声对小鼠下丘神经元声反应的选择性抑制

自由声场条件下,以强度为神经元最小阈值阈上5dB,时程分别为40、60、80和100ms的纯音作为前掩蔽声,观察和记录了不同时程弱前掩蔽声对小鼠（Musmusculus Km）下丘神经元发放和声强处理的影响。实验记录到154个神经元,对其中的104个神经元做了不同时程掩蔽声影响的测试。结果发现：掩蔽声对神经元放电率的抑制作用在时间上表现为前抑制（41％）、后抑制（9％）和全抑制（50％）三种类型。改变掩蔽声时程时,大部分神经元（72％）的抑制类型不发生改变,但少部分神经元（28％）随掩蔽声时程的增加,大量的后抑制类型转变为前抑制或全抑制类型。此外,超过一半的神经元（58．06％）其强度．放电率函数曲线随掩蔽声时程的改变而发生转变,主要表现为单调型向饱和型转变及饱和型向非单调型转变,这种转变并不随掩蔽声时程增加表现出规律性的变化。结果表明,前掩蔽作用于下丘神经元声反应的时间域和强度域时具有不均衡性,推测不同时程弱前掩蔽声激活的抑制性输入能分化性调制下丘神经元声反应特性。     

Nonmonotonic synaptic excitation and imbalanced inhibition underlying cortical intensity tuning

Intensity-tuned neurons, characterized by their nonmonotonic response-level function, may play important roles in the encoding of sound intensity-related information. The synaptic mechanisms underlying intensity tuning remain unclear. Here, in vivo whole-cell recordings in rat auditory cortex revealed that intensity-tuned neurons, mostly clustered in a posterior zone, receive imbalanced tone-evoked excitatory and inhibitory synaptic inputs. Excitatory inputs exhibit nonmonotonic intensity tuning, whereas with tone intensity increments, the temporally delayed inhibitory inputs increase monotonically in strength. In addition, this delay reduces with the increase of intensity, resulting in an enhanced suppression of excitation at high intensities and a significant sharpening of intensity tuning. In contrast, non-intensity-tuned neurons exhibit covaried excitatory and inhibitory inputs, and the relative time interval between them is stable with intensity increments, resulting in monotonic response-level function. Thus, cortical intensity tuning is primarily determined by excitatory inputs and shaped by cortical inhibition through a dynamic control of excitatory and inhibitory timing.     

Dose-response curve estimation: a semiparametric mixture approach

In the estimation of a dose-response curve, parametric models are straightforward and efficient but subject to model misspecifications; nonparametric methods are robust but less efficient. As a compromise, we propose a semiparametric approach that combines the advantages of parametric and nonparametric curve estimates. In a mixture form, our estimator takes a weighted average of the parametric and nonparametric curve estimates, in which a higher weight is assigned to the estimate with a better model fit. When the parametric model assumption holds, the semiparametric curve estimate converges to the parametric estimate and thus achieves high efficiency; when the parametric model is misspecified, the semiparametric estimate converges to the nonparametric estimate and remains consistent. We also consider an adaptive weighting scheme to allow the weight to vary according to the local fit of the models. We conduct extensive simulation studies to investigate the performance of the proposed methods and illustrate them with two real examples.     

A semiparametric response surface model for assessing drug interaction

Summary .   When multiple drugs are administered simultaneously, investigators are often interested in assessing whether the drug combinations are synergistic, additive, or antagonistic. Existing response surface models are not adequate to capture the complex patterns of drug interactions. We propose a two-component semiparametric response surface model with a parametric function to describe the additive effect of a combination dose and a nonparametric function to capture the departure from the additive effect. The nonparametric function is estimated using the technique developed in thin plate splines, and the pointwise bootstrap confidence interval for this function is constructed. The proposed semiparametric model offers an effective way of formulating the additive effect while allowing the flexibility of modeling a departure from additivity. Example and simulations are given to illustrate that the proposed model provides an excellent estimation for different patterns of interactions between two drugs.     

Relationship between fertility in cattle and the number of inseminated spermatozoa

Five different two-parameter models were fitted to published data from 30 studies to identify an approximate mathematical form of the relationship between fertility in cattle and the number of inseminated spermatozoa. In all cases, the first parameter defines the maximum attainable fertility, and the second scales the dose according to the percentage of the maximum attained. The best model was the hyperbolic dose-response curve used in pharmacology to analyse the effect of drugs. There is evidence that the semen of individual bulls differs in both parameters of the models and that therefore the viability of semen may be multidimensional. This might explain why measures of semen quality have hitherto been found to correlate poorly with fertility. The hypothesis that spermatozoa are subject to the law of mass action at the ovum predicts these and some other aspects of fertility, and indicates that heterospermic inseminations may provide an efficient way of estimating the parameters of semen.     

GABAergic inhibition and the effect of sound direction on rate-intensity functions of inferior collicular neurons of the big brown Bat,Eptesicus fuscus

GABAergic inhibition shapes many auditory response properties of neurons in the inferior colliculus of the big brown bat, Eptesicus fuscus. This study examined the role of GABAergic inhibition on direction-dependent rate-intensity functions of bat inferior collicular neurons. When plotted at three sound directions (60 degrees contralateral, 0 degrees and 60 degrees ipsilateral relative to recording site), most collicular neurons had nonmonotonic and saturated rate-intensity functions at 60 degrees contralateral and 0 degrees but had monotonic rate-intensity functions at 60 degrees ipsilateral. The dynamic range of rate-intensity functions of majority (>90%) of collicular neurons significantly decreased as the sound direction changed from 60 degrees contralateral to 60 degrees ipsilateral. Bicuculline application increased or decreased the dynamic range of IC neurons in different degrees with sound direction and abolished direction-dependent intensity sensitivity of these IC neurons. Possible mechanisms for these observations are discussed.     

Primate models for human immunodeficiency virus infection. Evolution of receptor use during pathogenesis

Animal models greatly facilitate understanding of transmission, pathogenesis and immune responses in HIV and SIV infection and provide models for studies on the effect of candidate drugs or vaccines. However, there are several aspects that one should consider when drawing conclusions from results obtained from animal models. First, the genetic relationship of primate lentiviruses cannot be disregarded because it is known that HIV-1 is more closely related to SIV of chimpanzee origin (SIVcpz) than to SIV from sooty mangabey (SIVsm) origin. Nevertheless, SIVsm and SIVmac are the ones most often used as model systems. Second, there are differences in the biological properties, like CXCR4 use and CD4-independent coreceptor use, of HIV and SIV. These differences might be relevant in virus transmission, pathogenesis and in evoking immune responses. Third, in vivo and in vitro selection may influence the results. Neutralizing antibodies may play a role in selection of variant viruses since neutralization sensitive, CD4-independent SIVsm variants seemed to be suppressed in animals that mounted a neutralizing antibody response. It is tempting to speculate that neutralizing antibodies shape the SIV/HIV infection by selecting variants with a more "closed" envelope conformation with consequences for both receptor binding and neutralization sensitivity. The SIV/monkey model, although it has important advantages, may not answer all questions asked about HIV-1 infection in human.     

Errors-in-variables in joint population pharmacokinetic/pharmacodynamic modeling

Pharmacokinetic (PK) models describe the relationship between the administered dose and the concentration of drug (and/or metabolite) in the blood as a function of time. Pharmacodynamic (PD) models describe the relationship between the concentration in the blood (or the dose) and the biologic response. Population PK/PD studies aim to determine the sources of variability in the observed concentrations/responses across groups of individuals. In this article, we consider the joint modeling of PK/PD data. The natural approach is to specify a joint model in which the concentration and response data are simultaneously modeled. Unfortunately, this approach may not be optimal if, due to sparsity of concentration data, an overly simple PK model is specified. As an alternative, we propose an errors-in-variables approach in which the observed-concentration data are assumed to be measured with error without reference to a specific PK model. We give an example of an analysis of PK/PD data obtained following administration of an anticoagulant drug. The study was originally carried out in order to make dosage recommendations. The prior for the distribution of the true concentrations, which may incorporate an individual's covariate information, is derived as a predictive distribution from an earlier study. The errors-in-variables approach is compared with the joint modeling approach and more naive methods in which the observed concentrations, or the separately modeled concentrations, are substituted into the response model. Throughout, a Bayesian approach is taken with implementation via Markov chain Monte Carlo methods.     

Estimating a treatment effect with repeated measurements accounting for varying effectiveness duration

To assess treatment efficacy in clinical trials, certain clinicaloutcomes are repeatedly measured over time for the same subject.The difference in their means may characterize a treatment effect.Since treatment effectiveness lag and saturation times may exist,erosion of treatment effect often occurs during the observationperiod. Instead of using models based on ad hoc parametric orpurely nonparametric time-varying coefficients, we model thetreatment effectiveness durations, which are the time intervalsbetween the lag and saturation times. Then we use some meanresponse models to include such treatment effectiveness durations.Our methodology is demonstrated by simulations and analysisof a landmark HIV/AIDS clinical trial of short-course nevirapineagainst mother-to-child HIV vertical transmission during labourand delivery.     

Interactions between prostaglandins and calcium: the importance of bell-shaped dose-response curves

Biological responses to PGs show two basic forms of dose/response relationship, plateau and bell-types. Although bell-shaped dose/response curves are well documented their possible occurrence is almost always ignored in the design and interpretation of experiments on PGs and related substances. This may lead to serious errors, several types of which are described. The ignoring of a well-documented phenomenon may take place because there is no accepted hypothesis which attempts to explain the bell-type curves. A hypothesis is proposed which accounts for both plateau and bell type responses. It is developed primarily with respect to PG-calcium interactions but may be applicable to some PG-cyclic nucleotide interactions as well. The model leads to precise predictions which can be experimentally tested in many systems.     

A model for analysis of the anesthetic response

When a dose d of an anesthetic is administered intravenously, either sleep will be observed for a period of time or no sleep will occur. We developed a general approach for formulating a model for this response which reduces to a quantal response model if the duration of sleep is ignored. Several specific models illustrate the general formulation. In each case the underlying dose response relationship that corresponds to the quantal response problem is the logistic. To include the duration of sleep in the model we introduced a concept of an "active dose" which is a function of the administered dose and time. We use a set of data from a study of the response of guinea pigs to ketamine for our numerical examples.     

Trimmed logit method for estimating the ED50 in quantal bioassay

Trimmed nonparametric procedures such as the trimmed Spearman-Karber method have been proposed in the literature for overcoming the deficiencies of the probit and logit models in the analysis of quantal bioassay data. However, there are situations where the median effective dose (ED50) is not calculable with the trimmed Spearman-Karber method, but is estimable with a parametric model. Also, it is helpful to have a parametric model for estimating percentiles of the dose-response curve such as the ED10 and ED25. A trimmed logit method that combines the advantages of a parametric model with that of trimming in dealing with heavy-tailed distributions is presented here. These advantages are substantiated with examples of actual bioassay data. Simulation results are presented to support the validity of the trimmed logit method, which has been found to work well in our experience with over 200 data sets. A computer program for computing the ED50 and associated 95% asymptotic confidence interval, based on the trimmed logit method, can be obtained from the authors.