Circadian phase and intertrial interval interfere with social recognition memory

A modified version of the social habituation/dis-habituation paradigm was employed to examine social recognition memory in Wistar rats during two opposing (active and inactive) circadian phases, using different intertrial intervals (30 and 60 min). Wheel-running activity was monitored continuously to identify circadian phase. To avoid possible masking effects of the light-dark cycle, the rats were synchronized to a skeleton photoperiod, which allowed testing during different circadian phases under identical lighting conditions. In each trial, an infantile intruder was introduced into an adult`s home-cage for a 5-minute interaction session, and social behaviors were registered. Rats were exposed to 5 trials per day for 4 consecutive days: oil days I and 2, each resident was exposed to the same intruder; on days 3 and 4, each resident was exposed to a different intruder in each trial. I he resident`s social investigatory behavior was more intense when different intruders were presented compared to repeated presentation of the same intruder, suggesting social recognition memory. This effect was stronger when the rats were tested during the inactive phase and when the intertrial interval was 60 min, These findings Suggest that social recognition memory, as evaluated in this modified habituation/dis-habituation paradigm, is influenced by the circadian rhythm phase during which testing is performed, and by intertrial interval. (C) 2008 Elsevier Inc. All rights reserved.

The log-exponentiated Weibull regression model for interval-censored data

In interval-censored survival data, the event of interest is not observed exactly but is only known to occur within some time interval. Such data appear very frequently. In this paper, we are concerned only with parametric forms, and so a location-scale regression model based on the exponentiated Weibull distribution is proposed for modeling interval-censored data. We show that the proposed log-exponentiated Weibull regression model for interval-censored data represents a parametric family of models that include other regression models that are broadly used in lifetime data analysis. Assuming the use of interval-censored data, we employ a frequentist analysis, a jackknife estimator, a parametric bootstrap and a Bayesian analysis for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Furthermore, for different parameter settings, sample sizes and censoring percentages, various simulations are performed; in addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to a modified deviance residual in log-exponentiated Weibull regression models for interval-censored data. (C) 2009 Elsevier B.V. All rights reserved.