Abstract: Although this bookis focusedon the cognitive neuroscience ofhuman social behaviour, an
understandingofsocial cognition in non-human animals is critical for unravellingthe neural basis of
social cognition in humans as well as the selective pressures that have shapedthe evolution ofcomplex
social cognition. Thanks to methodological limitations, we know little about the relationships between
certain biochemical andelectrophysiological properties ofthe human brain andhow theycompute the
behaviour andmental states ofother individuals. Traditional techniques for examiningneural function
in humans, such as event-relatedpotentials (ERP),positron emission tomography(PET),and
functional magnetic resonance imaging(fMRI),are constrainedbythe fact that subjects are placed
either into an immoveable scanner with a lot ofbackgroundnoise or wiredup with dozens of
electrodes that are sensitive to slight movements. The possibilityofscanningor recordingbrain waves
from two individuals that are physicallyinteractingsociallyis technicallyimpossible at present
(however, see Montague et al, 2002 for a new methodfor simultaneouslyscanningtwo individuals
interactingvia a computer).
The onlywayto understandthe neurocognitive architecture ofhuman social behaviour is to examine
similar social processes in both human andnon-human animal minds andmake comparisons at the
species level. An additional argument is that traditional human socio-cognitive tasks are dependent on
the use ofstories, cartoons andverbal cues andinstructions (Heberlein & Adolphs, this volume)which
themselves will elicit specific neural responses that have to be eliminatedfrom neural responses
specificallyrelatedto mindreading. Therefore, the development ofnon-verbal tasks wouldprovide a
breakthrough for studies in non-linguistic animals, pre-verbal human infants andhuman cognitive
neuroimaging.

Abstract: Several bodies of theory develop the idea that the intelligence of highly social animals – most interestingly, humans is significantly organized around the adaptive problems posed by their sociality. By this “political intelligence” hypothesis, sociality selects for, among other attributes, capacities for “manipulating” information others can gather about one's own future behaviour, and for “mindreading” such manipulations by others. Yet we have little theory about how diverse parameters of the games that social animals play select for political intelligence. We begin to address that with an evolutionary simulation in which agents choose between playing Prisoner's Dilemma and Hawk-Dove games on the basis of the information they can retrieve about each other given four broad information processing capacities. We show that political intelligence – operationally, the aggregate of those four capacities evolves to its highest levels when co-operative games are generally more attractive than conflictual ones, but when conflictual games are at least sometimes also attractive.

Abstract: The evaluation of important parameters for measuring the horses’ cognitive capacities is one of the central topics of the equine behaviour team at Nürtingen-Geislingen University. Social complexity has been said to be one of the settings in which needs for cognitive capacities arise in animals. A variety of studies throughout the last two decades proved the horses’ social complexity to be far more elaborate than previously assumed. Horses form social bonds for the protection of offspring, intervene in encounters of others, identify group mates individually and easily orientate in a fission fusion society.
In such socially complex societies, animals will benefit from learning socially. In many bird and primate species the degree of social complexity correlates nicely with the species abilities for social learning. Social learning was, therefore, argued to be an indicator for elaborate mental capacities in animals. We were delighted to prove that horses actually copy social behaviour and techniques for operating a feeding apparatus from older and higher ranking group members. In a recent study we found young horses, at the age of 3 to 12, to copy the operation of a feeding apparatus from a human demonstrator. Social learning seems to work nicely in horses when the social background of the animals is considered.
The degree to which individual animals adapt to changes in their social or physical environment by finding innovative solution appears to be the other side of the coin, of whether animals adjust to challenges by social learning. It is not very astonishing, that along with the animals’ social complexity and their ability to learn socially also the degree to which they show innovative behaviour was claimed to be one of the most important demonstrations of advanced cognitive capacities. In a recent approach, we started to ask horse owners and horse keepers in many countries to tell us about unusual behaviour of their horses via a web site (http://innovative-behaviour.org). To date, we received 204 cases of innovative behaviour descriptions from which six cases were clear examples of tool use or borderline tool use. We categorized the innovative behaviours into the classes, a) innovations to gain food, b) innovations to gain freedom, c) social innovations, d) innovations to increase maintenance, and e) innovations that could not be clearly assigned to a category. About 20% of the innovative horses showed more than one innovation. These animals could be termed “true innovators”. Again, young horses were more innovative than older ones with the age group 5 – 9 showing the highest number of innovative behaviour descriptions.
In a nutshell, the horses’ cognitive capacities appear to be underestimated throughout the last decades. The horses’ social complexity is far more elaborate than previously assumed, horses learn socially from conspecific and humans, some of them demonstrate innovative behaviour adaptations to their environment and even simple forms of tool use.

Abstract: The benefits to humans of equine-assisted therapy (EAT) have been well-researched, however few studies have analyzed the effects on the horse. Understanding how differing mental states of humans affect the behaviour and response of the horse can assist in providing optimal outcomes for both horse and human. Four humans clinically diagnosed and under care of a psychotherapist for Post-Traumatic Stress Disorder (PTSD) were matched physically to four neurotypical control humans and individually subjected to each of 17 therapy horses loose in a round pen. A professional acting coach instructed the control humans in replicating the physical movements of their paired PTSD individual. Both horses and humans were equipped with a heart rate (HR) monitor recording HR every 5secs. Saliva samples were collected from each horse 30 min before and 30 min after each trial to analyze cortisol concentrations. Each trial consisted of 5 min of baseline observation of the horse alone in the round pen after which the human entered the round pen for 2 min, followed by an additional 5 min of the horse alone. Behavioural observations indicative of stress in the horse (gait, head height, ear orientation, body orientation, distance from the human, latency of approach to the human, vocalizations, and chewing) were retrospectively collected from video recordings of each trial and analyzed using a repeated measures GLIMMIX with Tukey's multiple comparisons for differences between treatments and time periods. Horses moved slower (p < 0.0001), carried their head lower (p < 0.0001), vocalized less (p < 0.0001), and chewed less (p < 0.0001) when any human was present with them in the round pen. Horse HR increased in the presence of the PTSD humans, even after the PTSD human left the pen (p < 0.0001). Since two of the PTSD/control human pairs were experienced with horses and two were not, a post-hoc analysis showed that horses approached quicker (p < 0.016) and stood closer (p < 0.0082) to humans who were experienced with horses. Horse HR was lower when with inexperienced humans (p < 0.0001) whereas inexperienced human HR was higher (p < 0.0001). Horse salivary cortisol did not differ between exposure to PTSD and control humans (p > 0.32). Overall, behavioural and physiological responses of horses to humans are more pronounced based on human experience with horses than whether the human is diagnosed with a mental disorder. This may be a reflection of a directness of movement associated with humans who are experienced with horses that makes the horse more attentive. It appears that horses respond more to physical cues from the human rather than emotional cues. This knowledge is important in tailoring therapy programs and justifying horse responses when interacting with a patient in a therapy setting.

Abstract: To achieve optimal performance in equine sports as well as in leisure not only the physical abilities of the horse should be considered, but also the horse's personality. Besides temperamental aspects, like emotionality, or the horse's reactivity towards humans in handling situations, the learning ability of the horse is another relevant personality trait. To study whether differences in learning performance are consistent over time and whether individual learning performance differs between learning tests or is affected by emotionality, 39 young horses (Dutch Warmblood) were tested repeatedly in two learning tests. An aversive stimulus (AS) was used in one learning test (the avoidance learning test) and a reward was used in the other learning test (the reward learning test). During both learning tests behaviour as well as heart rate were measured. Each test was executed four times, twice when horses were 1 year of age, and twice when they were 2 years of age. Half of the horses received additional physical training from 6 months onwards. In both tests horses could be classified as either performers, i.e. completing the daily session, or as non-performers, i.e. returning to the home environment without having completed the daily session. There were some indications that emotionality might have caused non-performing behaviour, but these indications are not convincing enough to exclude other causes. Furthermore, there seem to be no simple relationships between measures of heart rate, behavioural responses putatively related to emotionality and learning performance. Horses revealed consistent individual learning performances within years in both tests, and in the avoidance learning test also between years. There was no significant correlation between learning performances in the avoidance learning test and the learning performances in the reward learning test. It is concluded that individual learning abilities are consistent over a short time interval for an avoidance learning test and a reward learning test and over a longer time for the avoidance learning test. Furthermore, results indicate that some horses perform better when they have to learn to avoid an aversive stimulus while others perform better when they are rewarded after a correct response. It is suggested that these differences may be relevant to design optimal individual training programmes and methods.