Abstract: Abstract
Several comparative research programs have focusedon the cognitive, life history and ecological traits thataccount for variation in brain size. We review one ofthese programs, a program that uses the reported frequencyof behavioral innovation as an operational measureof cognition. In both birds and primates, innovationrate is positively correlated with the relative size of associationareas in the brain, the hyperstriatum ventrale andneostriatum in birds and the isocortex and striatum inprimates. Innovation rate is also positively correlatedwith the taxonomic distribution of tool use, as well asinterspecific differences in learning. Some features ofcognition have thus evolved in a remarkably similar wayin primates and at least six phyletically-independent avianlineages. In birds, innovation rate is associated withthe ability of species to deal with seasonal changes in theenvironment and to establish themselves in new regions,and it also appears to be related to the rate atwhich lineages diversify. Innovation rate provides a usefultool to quantify inter-taxon differences in cognitionand to test classic hypotheses regarding the evolution ofthe brain.

Abstract: Summary Different head?neck positions (HNPs) are used in equestrian sports and are regarded as desirable for training and competition by riders, judges and trainers. Even though some studies have been indicative of hyperflexion having negative effects on horses, this unnatural position is frequently used. In the present study, the influence of different HNPs on physical and psychological stress parameters in the ridden horse was investigated. Heart rate (HR), heart rate variability (HRV) and blood cortisol levels were measured in 18 horses. Low frequency (LF) and high frequency (HF) are power components in the frequency domain measurement of HRV which show the activity of the sympathetic and parasympathetic nervous system. Values were recorded at rest, while riding with a working HNP and while riding with hyperflexion of the horse's head, neck and poll. In addition, rideability and behaviour during the different investigation stages were evaluated by the rider and by an observer. Neither the HR nor the HRV showed a significant difference between working HNP (HR = 105 ± 22/min; LF/HF = 3.89 ± 5.68; LF = 37.28 ± 10.77%) and hyperflexion (HR = 110 ± 18; LF/HF = 1.94 ± 2.21; LF = 38.39 ± 13.01%). Blood cortisol levels revealed a significant increase comparing working HNP (158 ± 60 nm) and hyperflexion (176 ± 64 nm, p = 0.01). The evaluation of rider and observer resulted in clear changes of rideability and behavioural changes for the worse in all parameters collected between a working HNP and hyperflexion. In conclusion, changes of the cortisol blood level as a physical parameter led to the assumption that hyperflexion of head, neck and poll effects a stress reaction in the horse, and observation of the behaviour illustrates adverse effects on the well-being of horses during hyperflexion.

Abstract: There has been relatively little research on the psychological mechanisms of social learning. This may be due, in part, to the practice of distinguishing categories of social learning in relation to ill-defined mechanisms (Davis, 1973; Galef, 1988). This practice both makes it difficult to identify empirically examples of different types of social learning, and gives the false impression that the mechanisms responsible for social learning are clearly understood. It has been proposed that social learning phenomena be subsumed within the categorization scheme currently used by investigators of asocial learning. This scheme distinguishes categories of learning according to observable conditions, namely, the type of experience that gives rise to a change in an animal (single stimulus vs. stimulus-stimulus relationship vs. response-reinforcer relationship), and the type of behaviour in which this change is detected (response evocation vs. learnability) (Rescorla, 1988). Specifically, three alignments have been proposed: (i) stimulus enhancement with single stimulus learning, (ii) observational conditioning with stimulus-stimulus learning, or Pavlovian conditioning, and (iii) observational learning with response-reinforcer learning, or instrumental conditioning. If, as the proposed alignments suggest, the conditions of social and asocial learning are the same, there is some reason to believe that the mechanisms underlying the two sets of phenomena are also the same. This is so if one makes the relatively uncontroversial assumption that phenomena which occur under similar conditions tend to be controlled by similar mechanisms. However, the proposed alignments are intended to be a set of hypotheses, rather than conclusions, about the mechanisms of social learning; as a basis for further research in which animal learning theory is applied to social learning. A concerted attempt to apply animal learning theory to social learning, to find out whether the same mechanisms are responsible for social and asocial learning, could lead both to refinements of the general theory, and to a better understanding of the mechanisms of social learning. There are precedents for these positive developments in research applying animal learning theory to food aversion learning (e.g. Domjan, 1983; Rozin & Schull, 1988) and imprinting (e.g. Bolhuis, de Vox & Kruit, 1990; Hollis, ten Cate & Bateson, 1991). Like social learning, these phenomena almost certainly play distinctive roles in the antogeny of adaptive behaviour, and they are customarily regarded as 'special kinds' of learning (Shettleworth, 1993).(ABSTRACT TRUNCATED AT 400 WORDS)

Abstract: Abstract— We present a study focused on a quantitative estimation of a human-horse dynamic interaction. A set of measures based on magnitude and phase coupling between heartbeat dynamics of both humans and horses in three different conditions is reported: no interaction, visual/olfactory interaction and grooming. Specifically, Magnitude Squared Coherence (MSC), Mean Phase Coherence (MPC) and Dynamic Time Warping (DTW) have been used as estimators of the amount of coupling between human and horse through the analysis of their heart rate variability (HRV) time series in a group of eleven human subjects, and one horse. The rationale behind this study is that the interaction of two complex biological systems go towards a coupling process whose dynamical evolution is modulated by the kind and time duration of the interaction itself. We achieved a congruent and consistent
statistical significant difference for all of the three indices. Moreover, a Nearest Mean Classifier was able to recognize the three classes of interaction with an accuracy greater than 70%. Although preliminary, these encouraging results allow a discrimination of three distinct phases in a real human-animal interaction opening to the characterization of the empirically proven relationship between human and horse.