Abstract: Animals process sensory information according to specific computational rules and, subsequently, form representations of their environments that form the basis for decisions and choices. The specific computational rules used by organisms will often be evolutionarily adaptive by generating higher probabilities of survival, reproduction, and resource acquisition. Experiments with enclosed colonies of bumblebees constrained to foraging on artificial flowers suggest that the bumblebee's cognitive architecture is designed to efficiently exploit floral resources from spatially structured environments given limits on memory and the neuronal processing of information. A non-linear relationship between the biomechanics of nectar extraction and rates of net energetic gain by individual bees may account for sensitivities to both the arithmetic mean and variance in reward distributions in flowers. Heuristic rules that lead to efficient resource exploitation may also lead to subjective misperception of likelihoods. Subjective probability formation may then be viewed as a problem in pattern recognition subject to specific sampling schemes and memory constraints.

Abstract: Horses displaying an oral stereotypy were tested on an instrumental choice paradigm to examine differences in learning from non-stereotypic counterparts. Stereotypic horses are known to have dysfunction of the dorsomedial striatum, and lesion studies have shown that this region may mediate response-outcome learning. The paradigm was specifically applied in order to examine learning that requires maintenance of response-outcome judgements. The non-stereotypic horses learned, over three sessions, to choose a more immediate reinforcer, whereas the stereotypic horses failed to do so. This suggests an initial behavioural correlate for dorsomedial striatum dysregulation in the stereotypy phenotype.

Abstract: Although reinforcement often leads to repetitive, even stereotyped responding, that is not a necessary outcome. When it depends on variations, reinforcement results in responding that is diverse, novel, indeed unpredictable, with distributions sometimes approaching those of a random process. This article reviews evidence for the powerful and precise control by reinforcement over behavioral variability, evidence obtained from human and animal-model studies, and implications of such control. For example, reinforcement of variability facilitates learning of complex new responses, aids problem solving, and may contribute to creativity. Depression and autism are characterized by abnormally repetitive behaviors, but individuals afflicted with such psychopathologies can learn to vary their behaviors when reinforced for so doing. And reinforced variability may help to solve a basic puzzle concerning the nature of voluntary action.

Abstract: The responsiveness of 10 horses and 10 ponies to environmental challenge (represented by an open field test) was assessed using a qualitative approach based on free choice profiling methodology (FCP), which gives observers complete freedom to choose their own descriptive terms. Data were analysed with generalised Procrustes analysis (GPA), a multivariate statistical technique associated with FCP. A cross-validation of the outcomes of this approach to data recorded through quantitative behaviour analysis, and through a questionnaire given to the animals' owner/riding instructor, was also performed using principal component analysis (PCA). Twelve undergraduate students generated their own descriptive vocabularies, by watching 20 horse/pony video clips lasting 2.5 min each. GPA showed that the consensus profile explained a high percentage of variation among the 12 observers, and differed significantly from the mean randomised profile (p < 0.001). Two main dimensions of the consensus profile were identified, explaining 60% and 5.2% of the variation between animals, respectively. The 12 observer word charts interpreting these dimensions were semantically consistent, as they all converged towards the same meaning, albeit using different terms. The most used term to describe the positive end of axis 1 was “quiet”, whereas “attentive” was the best positive descriptor of axis 2. The most frequently used descriptors for the negative ends of axes 1 and 2 were “nervous” and “bored”, respectively. Thus, axis 1 was labelled as “quiet/nervous” and axis 2 was named as “attentive/bored”. A marked effect of animal category was observed on the scores of the animals on the first dimension (p < 0.001). Horses received significantly higher scores, and were thus assessed as more quiet and calm, than ponies. Conversely, ponies tended to receive lower scores on the second dimension (p < 0.12), therefore they appeared less curious and attentive. The results of the PCA showed that the variables from different types of measurement clearly had meaningful relationships. For instance, the variables with the highest loading on the positive end of axis 1 were all indicative of tractable and docile animals, whereas axis 2 showed high loadings on the positive end for variables indicating attentive animals. Qualitative behaviour assessment proved to be an appropriate methodology for the study of horse behavioural responsiveness, in that it provided a multifaceted characterisation of horse behavioural expression that was in agreement with other quantitative and subjective assessments of the animals' behaviour.

Abstract: Operant conditioning and two choice preference tests were used to assess the motivation of horses to be released from straight and from box stalls. The motivations for food, a companion, and release into a paddock were compared when the horses had to work for each commodity at increasing fixed ratios of responses (panel presses) to reward in an equine operant conditioning stall. The motivation for food (mean ± SEM = 258 ± 143) responses was much greater than that for either release (38 ± 32) from a straight stall into a large paddock alone or into a small paddock with another horse (95 ± 41) (P = 0.04). When given a two choice preference test between exercise on a treadmill for 20 min or returning to their box stalls, eight of nine horses chose to return to their stalls. In a two choice preference test six of eight horses in box stalls chose to be released into a paddock alone. Horses were given a series of two choice preference tests to determine how long they preferred to be in a paddock. After 15 min in the paddock the horses were re-tested, but all chose the paddock when released into a paddock with three other horses. They were retested every 15 min until they chose to return to their stalls. They chose to stay out for 35 ± 6 min when other horses were in the paddock but for only 17 ± 2 min when they would be alone. When deprived of stall release for 48 h the horses chose to remain in the paddock with other horses for 54 ± 6 min, but showed no compensatory behavior when they were alone (duration chosen = 16 ± 4 min). These findings indicate that horses are not strongly motivated to exercise alone and will choose not to endure forced exercise on a treadmill. The social context of voluntary exercise is important; horses are willing to stay out of their stalls longer if other horses are present and will show compensatory behavior only if other horses are present. These finding have implications for optimizing turnout time for stalled horses.