Effects of microinjections of apomorphine and haloperidol into the inferior colliculus on the latent inhibition of the conditioned emotional response

Electrical or chemical stimulation of the inferior colliculus (IC) induces fear-like behaviors. More recently, consistent evidence has shown that electrical stimulation of the central nucleus of the IC supports Pavlovian conditioning and latent inhibition (Li). LI is characterized by retardation in conditioning and also by an impaired ability to ignore irrelevant stimuli, after a non-reinforced pre-exposure to the conditioned stimulus. LI has been proposed as a behavioral model of cognitive abnormalities seen in schizophrenia. The aim of the present study was to determine whether dopaminergic mechanisms in the IC are involved in LI of the conditioned emotional response (CER). To induce LI, a group of rats was pre-exposed (PE) to six tones in two sessions, while rats that were not pre-exposed (NPE) had two sessions without tone presentations. The conditioning consisted of two tone presentations to the animal, followed immediately by a foot shock. PE and NPE rats received IC microinjections of physiological saline, the dopaminergic agonist apomorphine (9.0 mu g/0.5 mu L/side), or the dopaminergic antagonist haloperidol (0.5 mu g/0.5 mu L/side) before both pre-exposure and conditioning. During the test, the PE rats that received saline or haloperidol had a lower suppression of the licking response compared to NPE rats that received vehicle or haloperidol, indicating that latent inhibition was induced. There was no significant difference in the suppression ratio in rats that received apomorphine injections into the IC, indicating reduced latent inhibition. These results suggest that dopamine-mediated mechanisms of the IC are involved in the development of LI. (C) 2008 Elsevier Inc. All rights reserved.

Latent inhibition and autonomic responses: a psychophysiological approach

Latent inhibition, retarded learning after preexposure to the to-be-conditioned stimulus, has been implied as a tool for the investigation of attentional deficits in schizophrenia and related disorders. The present paper reviews research that used Pavlovian conditioning as indexed by autonomic responses (electrodermal, vasomotor, cardiac) to investigate latent inhibition in adult humans. Latent inhibition has been demonstrated repeatedly in healthy subjects in absence of a masking task that is required in other latent inhibition paradigms. Moreover, latent inhibition of Pavlovian conditioning is stimulus-specific and increases with an increased number of preexposure trials which mirrors results from research in animals. A reduction of latent inhibition has been shown in healthy subjects who score high on questionnaire measures of psychosis proneness and in unmedicated schizophrenic patients. The latter result was obtained in a within-subject paradigm that holds promise for research with patient samples. (C) 1997 Elsevier Science B.V.

Latent inhibition and schizophrenia: Pavlovian conditioning of autonomic responses

Latent inhibition (LI) is an important model for understanding cognitive deficits in schizophrenia, Disruption of LI is thought to result from an inability to ignore irrelevant stimuli. The study investigated LI in schizophrenic patients by using Pavlovian conditioning of electrodermal responses in a complete within-subject design. Thirty-two schizophrenic patients, ( 16 acute. unmedicated and 16 medicated patients) and 16 healthy control subjects (matched with respect to age and gender) participated in the study. The experiment consisted of two stages: preexposure and conditioning. During preexposure two visual stimuli were presented, one of which served as the to-be-conditioned stimulus (CSp +) and the other one was the not-to-be-conditioned stimulus (CSp -) during the following conditioning ( = acquisition). During acquisition. two novel visual stimuli (CSn + and CSn -) were introduced. A reaction time task was used as the unconditioned stimulus (US). LI was defined as the difference in response differentiation observed between proexposed and non-preexposed sets of CS + and CS -. During preexposure. the schizophrenic patients did not differ in electrodermal responding from the control subjects, neither concerning the extent of orienting nor the course of habituation. The exposure to novel stimuli at the beginning of the acquisition elicited reduced orienting responses in unmedicated patients compared to medicated patients and control subjects, LI was observed in medicated schizophrenic patients and healthy controls. but not in acute unmedicated patients. Furthermore LI was found to be correlated with the duration of illness: it was attenuated in patients who had suffered their first psychotic episode. (C) 2002 Elsevier Science B.V. All rights reserved.

Protesting or justifying? A latent class model for contingent valuation with attitudinal data

This article develops a latent class model for estimating willingness-to-pay for public goods using simultaneously contingent valuation (CV) and attitudinal data capturing protest attitudes related to the lack of trust in public institutions providing those goods. A measure of the social cost associated with protest responses and the consequent loss in potential contributions for providing the public good is proposed. The presence of potential justification biases is further considered, that is, the possibility that for psychological reasons the response to the CV question affects the answers to the attitudinal questions. The results from our empirical application suggest that psychological factors should not be ignored in CV estimation for policy purposes, allowing for a correct identification of protest responses.

Balanced excitation and inhibition: Model based analysis of local field potentials

We have developed a model of the local field potential (LFP) based on the conservation of charge, the independence principle of ionic flows and the classical Hodgkin–Huxley (HH) type intracellular model of synaptic activity. Insights were gained through the simulation of the HH intracellular model on the nonlinear relationship between the balance of synaptic conductances and that of post-synaptic currents. The latter is dependent not only on the former, but also on the temporal lag between the excitatory and inhibitory conductances, as well as the strength of the afferent signal. The proposed LFP model provides a method for decomposing the LFP recordings near the soma of layer IV pyramidal neurons in the barrel cortex of anaesthetised rats into two highly correlated components with opposite polarity. The temporal dynamics and the proportional balance of the two components are comparable to the excitatory and inhibitory post-synaptic currents computed from the HH model. This suggests that the two components of the LFP reflect the underlying excitatory and inhibitory post-synaptic currents of the local neural population. We further used the model to decompose a sequence of evoked LFP responses under repetitive electrical stimulation (5 Hz) of the whisker pad. We found that as neural responses adapted, the excitatory and inhibitory components also adapted proportionately, while the temporal lag between the onsets of the two components increased during frequency adaptation. Our results demonstrated that the balance between neural excitation and inhibition can be investigated using extracellular recordings. Extension of the model to incorporate multiple compartments should allow more quantitative interpretations of surface Electroencephalography (EEG) recordings into components reflecting the excitatory, inhibitory and passive ionic current flows generated by local neural populations.

A General Latent Class Model for Performance Evaluation of Diagnostic Tests in the Absence of a Gold Standard: An Application to Chagas Disease

We propose a new general Bayesian latent class model for evaluation of the performance of multiple diagnostic tests in situations in which no gold standard test exists based on a computationally intensive approach. The modeling represents an interesting and suitable alternative to models with complex structures that involve the general case of several conditionally independent diagnostic tests, covariates, and strata with different disease prevalences. The technique of stratifying the population according to different disease prevalence rates does not add further marked complexity to the modeling, but it makes the model more flexible and interpretable. To illustrate the general model proposed, we evaluate the performance of six diagnostic screening tests for Chagas disease considering some epidemiological variables. Serology at the time of donation (negative, positive, inconclusive) was considered as a factor of stratification in the model. The general model with stratification of the population performed better in comparison with its concurrents without stratification. The group formed by the testing laboratory Biomanguinhos FIOCRUZ-kit (c-ELISA and rec-ELISA) is the best option in the confirmation process by presenting false-negative rate of 0.0002% from the serial scheme. We are 100% sure that the donor is healthy when these two tests have negative results and he is chagasic when they have positive results.

A Mechanistic Latent Variable Model for Estimating Drug Concentrations in the Male Genital Tract

The purpose of this study is to develop statistical methodology to facilitate indirect estimation of the concentration of antiretroviral drugs and viral loads in the prostate gland and the seminal vesicle. The differences in antiretroviral drug concentrations in these organs may lead to suboptimal concentrations in one gland compared to the other. Suboptimal levels of the antiretroviral drugs will not be able to fully suppress the virus in that gland, lead to a source of sexually transmissible virus and increase the chance of selecting for drug resistant virus. This information may be useful selecting antiretroviral drug regimen that will achieve optimal concentrations in most of male genital tract glands. Using fractionally collected semen ejaculates, Lundquist (1949) measured levels of surrogate markers in each fraction that are uniquely produced by specific male accessory glands. To determine the original glandular concentrations of the surrogate markers, Lundquist solved a simultaneous series of linear equations. This method has several limitations. In particular, it does not yield a unique solution, it does not address measurement error, and it disregards inter-subject variability in the parameters. To cope with these limitations, we developed a mechanistic latent variable model based on the physiology of the male genital tract and surrogate markers. We employ a Bayesian approach and perform a sensitivity analysis with regard to the distributional assumptions on the random effects and priors. The model and Bayesian approach is validated on experimental data where the concentration of a drug should be (biologically) differentially distributed between the two glands. In this example, the Bayesian model-based conclusions are found to be robust to model specification and this hierarchical approach leads to more scientifically valid conclusions than the original methodology. In particular, unlike existing methods, the proposed model based approach was not affected by a common form of outliers.

Development of a Tumour Growth Inhibition Model to Elucidate the Effects of Ritonavir on Intratumoural Metabolism and Anti-tumour Effect of Docetaxel in a Mouse Model for Hereditary Breast Cancer

In a mouse tumour model for hereditary breast cancer, we previously explored the anti-cancer effects of docetaxel, ritonavir and the combination of both and studied the effect of ritonavir on the intratumoural concentration of docetaxel. The objective of the current study was to apply pharmacokinetic (PK)-pharmacodynamic (PD) modelling on this previous study to further elucidate and quantify the effects of docetaxel when co-administered with ritonavir. PK models of docetaxel and ritonavir in plasma and in tumour were developed. The effect of ritonavir on docetaxel concentration in the systemic circulation of Cyp3a knock-out mice and in the implanted tumour (with inherent Cyp3a expression) was studied, respectively. Subsequently, we designed a tumour growth inhibition model that included the inhibitory effects of both docetaxel and ritonavir. Ritonavir decreased docetaxel systemic clearance with 8% (relative standard error 0.4%) in the co-treated group compared to that in the docetaxel only-treated group. The docetaxel concentration in tumour tissues was significantly increased by ritonavir with mean area under the concentration-time curve 2.5-fold higher when combined with ritonavir. Observed tumour volume profiles in mice could be properly described by the PK/PD model. In the co-treated group, the enhanced anti-tumour effect was mainly due to increased docetaxel tumour concentration; however, we demonstrated a small but significant anti-tumour effect of ritonavir addition (p value <0.001). In conclusion, we showed that the increased anti-tumour effect observed when docetaxel is combined with ritonavir is mainly caused by enhanced docetaxel tumour concentration and to a minor extent by a direct anti-tumour effect of ritonavir.

Using hybrid latent class model for city-HUBs´users behaviour analysis

Data from an attitudinal survey and stated preference ranking experiment conducted in two urban European interchanges (i.e. City-HUBs) in Madrid (Spain) and Thessaloniki (Greece) show that the importance that City-HUBs users attach to the intermodal infrastructure varies strongly as a function of their perceptions of time spent in the interchange (i.e.intermodal transfer and waiting time). A principal components analysis allocates respondents (i.e. city-HUB users) to two classes with substantially different perceptions of time saving when they make a transfer and of time using during their waiting time.

Discovering user access pattern based on probabilistic latent factor model

There has been an increased demand for characterizing user access patterns using web mining techniques since the informative knowledge extracted from web server log files can not only offer benefits for web site structure improvement but also for better understanding of user navigational behavior. In this paper, we present a web usage mining method, which utilize web user usage and page linkage information to capture user access pattern based on Probabilistic Latent Semantic Analysis (PLSA) model. A specific probabilistic model analysis algorithm, EM algorithm, is applied to the integrated usage data to infer the latent semantic factors as well as generate user session clusters for revealing user access patterns. Experiments have been conducted on real world data set to validate the effectiveness of the proposed approach. The results have shown that the presented method is capable of characterizing the latent semantic factors and generating user profile in terms of weighted page vectors, which may reflect the common access interest exhibited by users among same session cluster.

A hierarchical latent variable model for data visualization

Visualization has proven to be a powerful and widely-applicable tool the analysis and interpretation of data. Most visualization algorithms aim to find a projection from the data space down to a two-dimensional visualization space. However, for complex data sets living in a high-dimensional space it is unlikely that a single two-dimensional projection can reveal all of the interesting structure. We therefore introduce a hierarchical visualization algorithm which allows the complete data set to be visualized at the top level, with clusters and sub-clusters of data points visualized at deeper levels. The algorithm is based on a hierarchical mixture of latent variable models, whose parameters are estimated using the expectation-maximization algorithm. We demonstrate the principle of the approach first on a toy data set, and then apply the algorithm to the visualization of a synthetic data set in 12 dimensions obtained from a simulation of multi-phase flows in oil pipelines and to data in 36 dimensions derived from satellite images.