No abstract

Humans experiencing different background emotional states display contrasting cognitive (e.g. judgement) biases when responding to ambiguous stimuli. We have proposed that such biases may be used as indicators of animal emotional state. Here, we use a spatial judgement task, in which animals are trained to expect food in one location and not another, to determine whether rats in relatively positive or negative emotional states respond differently to ambiguous stimuli of intermediate spatial location. We housed 24 rats with environmental enrichment for seven weeks.Enrichment was removed for half the animals prior to the start of training ('U': unenriched) to induce a relatively negative emotional state, whilst being left in place for the remaining rats ('E': enriched). After six training days, the rats successfully discriminated between the rewarded and unrewarded locations in terms of an increased latency to arrive at the unrewarded location, with no housing treatment difference. The subjects then received three days of testing in which three ambiguous 'probe' locations, intermediate between the rewarded and unrewarded locations, were introduced. There was no difference between the treatments in the rats' judgement of two out of the three probe locations, the exception being when the ambiguous probe was positioned closest to the unrewarded location. This result suggests that rats housed without enrichment, and in an assumed relatively negative emotional state, respond differently to an ambiguous stimulus compared to rats housed with enrichment, providing evidence that cognitive biases may be used to assess animal emotional state in a spatial judgement task. The study of animal emotions is gaining increasing credence within the research community including psychology, neuroscience and behaviour (e.g. Rolls, 2000;LeDoux, 2003;Paul et al., 2005). Furthermore, the assumption that animals experience emotional states is likely to underpin public concern about animal welfare, and investigations of such states are thus of central importance in animal welfare science (e.g. Dawkins, 1990; Dawkins, 2006) There are, however, problems with the existing techniques. For many physiological and behavioural indicators, interpretation is complicated by the fact that the correspondence between a particular measure (e.g. heart rate/locomotory behaviour) and the valence (i.e. positive/negative) of a corresponding emotional state may be unclear. For example, increased heart rate or locomotory behaviour may be recorded during aversive (e.g. predator avoidance) or pleasurable (e.g. sex) activities. In a previous study (Harding et al., 2004), the authors developed a test of judgement bias, one category of cognitive bias (Paul et al., 2005), in which rats were trained to press a lever to gain a food reward after a particular tone had been played (e.g. 2kHz), but to refrain from pressing the lever when a different tone (e.g. 4kHz)was played in order to avoid a burst of white noise. Having learned to discriminate between these two '...

The scientific study of animal emotion is an important emerging discipline in subjects ranging from neuroscience to animal welfare research. In the absence of direct measures of conscious emotion, indirect behavioural and physiological measures are used. However, these may have significant limitations (e.g. indicating emotional arousal but not valence (positivity versus negativity)). A new approach, taking its impetus from human studies, proposes that biases in information processing, and underlying mechanisms relating to the evaluation of reward gains and losses, may reliably reflect emotional valence in animals. In general, people are more sensitive to reward losses than gains, but people in a negative affective state (e.g. depression) are particularly sensitive to losses. This may underlie broader findings such as an enhanced attention to, and memory of, negative events in depressed individuals. Here we show that rats in unenriched housing, who typically exhibit indicators of poorer welfare and a more negative affective state than those in enriched housing, display a prolonged response to a decrease in anticipated food reward, indicating enhanced sensitivity to reward loss. Sensitivity to reward reduction may thus be a valuable new indicator of animal emotion and welfare.

As in humans, 'cognitive biases' in the way in which animals judge ambiguous stimuli may be influenced by emotional state and hence a valuable new indicator of animal emotion. There is increasing evidence that animals experiencing different emotional states following exposure to long-term environmental manipulations show contrasting biases in their judgement of ambiguous stimuli. However, the specific type of induced emotional state is usually unknown. We investigated whether a short-term manipulation of emotional state has a similar effect on cognitive bias, using changes in light intensity; a treatment specifically related to anxiety-induction. Twenty-four male rats were trained to discriminate between two different locations, in either high ('H') or low ('L') light levels. One location was rewarded with palatable food and the other with aversive food. Once the rats had shown spatial discrimination, by running significantly faster to the rewarded location, they were tested with three ambiguous locations intermediate between the rewarded and aversive locations, and their latency to approach each location recorded. Half the rats were tested in the same light levels as during training, the remainder were switched. Rats switched from high to low light levels (putatively the least negative emotional manipulation) ran significantly faster to all three ambiguous probes than those rats switched from low to high light levels (putatively the most negative manipulation). This suggests that the judgement bias technique might be useful as an indicator of short-term changes in anxiety for non-human animals.

No abstract

R2MLwiN is a new package designed to run the multilevel modeling software program MLwiN from within the R environment. It allows for a large range of models to be specified which take account of a multilevel structure, including continuous, binary, proportion, count, ordinal and nominal responses for data structures which are nested, cross-classified and/or exhibit multiple membership. Estimation is available via iterative generalized least squares (IGLS), which yields maximum likelihood estimates, and also via Markov chain Monte Carlo (MCMC) estimation for Bayesian inference. As well as employing MLwiN's own MCMC engine, users can request that MLwiN write BUGS model, data and initial values statements for use with WinBUGS or OpenBUGS (which R2MLwiN automatically calls via rbugs), employing IGLS starting values from MLwiN. Users can also take advantage of MLwiN's graphical user interface: for example to specify models and inspect plots via its interactive equations and graphics windows. R2MLwiN is supported by a large number of examples, reproducing all the analyses conducted in MLwiN's IGLS and MCMC manuals.

The association between visit‐to‐visit systolic blood pressure variability and cardiovascular events has recently received a lot of attention in the cardiovascular literature. But, blood pressure variability is usually estimated on a person‐by‐person basis and is therefore subject to considerable measurement error. We demonstrate that hazard ratios estimated using this approach are subject to bias due to regression dilution, and we propose alternative methods to reduce this bias: a two‐stage method and a joint model. For the two‐stage method, in stage one, repeated measurements are modelled using a mixed effects model with a random component on the residual standard deviation (SD). The mixed effects model is used to estimate the blood pressure SD for each individual, which, in stage two, is used as a covariate in a time‐to‐event model. For the joint model, the mixed effects submodel and time‐to‐event submodel are fitted simultaneously using shared random effects. We illustrate the methods using data from the Atherosclerosis Risk in Communities study.

To determine whether lame broilers are in pain it is necessary to compare measures of lameness and mobility before and after analgesic treatment. Such measures should not be unduly affected by other bird characteristics. This study assessed the performance of lame (gait score, GS 3-4) and non-lame (GS 0-1) broilers using two mobility tests: (i) a novel test to assess broiler ability to access resources when housed in groups (Group Obstacle test); and (ii) a Latency-to-Lie (LTL) test. Outcome test measures included number of obstacle crossings, latency to cross an obstacle, and time taken to sit in shallow water. Associations between outcome test measures and other bird characteristics (established lameness risk-factors), including strain, sex, age, mass, contact dermatitis and pathology, were also investigated. The performance of high-GS and low-GS broilers differed in both mobility tests and no other bird characteristics were as consistent a predictor as lameness. This demonstrates that mobility impairments are closely related to lameness assessed using GS, and that there is a component of lameness that cannot be explained by other bird characteristics (eg being male and heavy). This component may represent pain or discomfort. Both mobility tests are suitable for further application with analgesic testing to classify lameness-associated pain in broilers.