Abstract: Recent research has shown that domestic dogs are particularly good at reading human attentional cues, often outperforming chimpanzees and hand reared wolves [1, 2]. It has been suggested that the close evolutionary relationship between humans and dogs has led to the development of this ability, however very few other species have been studied [3]. We tested the ability of 24 domestic horses to discriminate between an attentive and inattentive person when choosing whom to approach for food. While the attentive person faced forwards, the inattentive person either stood with their body turned 180° away from the subject (body orientation condition), stood with their body facing forwards but their head facing away (head orientation condition) or stood facing forwards but with their eyes closed (eyes closed condition). A fourth, mixed condition was included where the attentive person stood with their body facing away from the subjects but their head turned towards the subject while the inattentive person stood with their body facing the subject but their head turned away. Horses chose the attentive person significantly more often using the body cue (n = 24, k = 19, p = 0.003), the head cue (n = 24, k = 18, p = 0.011), and the eye cue (n = 24, k = 19, p = 0.003) but not the mixed cue (n = 24, k = 13, p = 0.42). In an additional pilot study, horses were tested in an object choice task. A human experimenter cued one of two buckets by either tapping the bucket (tap condition), orienting their body towards the bucket and pointing (body and point condition), pointing while facing forwards (point condition) or orienting their body towards the bucket (body condition). If the subjects chose the correct bucket they were rewarded. Subjects were able to use the tap cue (n = 31, k = 21, p = 0.035), body + point cue (n= 31, k = 21, p = 0.035) and the point cue (n = 30, k = 21, p = 0.021) but not the body cue (n = 31, k = 11, p = 0.076). These results taken together suggest that domestic horses are also very sensitive to human attentional cues, including gaze.
Keywords:
social cognition, animal-human interaction, horses, attention attribution, domestication
1. Hare, B., Brown, M., Williamson, C., and Tomasello, M. (2002). The domestication of social cognition in dogs. Science 298, 1634-1636.
2. Gacsi, M., Miklosi, A., Varga, O., Topal, J., and Csanyi, V. (2004). Are readers of our face readers of our minds` Dogs (Canis familiaris) show situation-dependent recognition of human’s attention. Animal Cognition 7, 144-153.
3. Hare, B., and Tomasello, M. (2005). Human-like social skills in dogs? Trends Cogn. Sci. 9, 439-444.

Abstract: The management of the domestic horse often requires them to be kept in isolation from con-specifics. Installing a picture of a horse (generally head and neck view) with a view to providing surrogate companionship has been shown to reduce the negative impact of this isolation. This study aimed firstly to compare the spontaneous response of horses (N=10) to a 2-D image of a horse’s face (FP) with their response to a comparable abstract 2-D image (AP). Secondly, the spontaneous response of horses (N=20) to a 2-D image of a horse’s face with the ears forward (PFP positive) was compared with the response to a 2-D image of a horse’s face with the ears back (NFP negative). The posters were A1 sized and displayed in the horse’s own stable. In study 1, one poster was displayed for 5 minutes and the horse’s behaviour video-recorded. This was removed and the second poster was displayed for 5 minutes and the behaviour video-recorded. FP was displayed first for 5 of the horses and AP displayed first for the other 5. The video footage was observed and the behaviour of the horses and number of times they touched the poster recorded. For the purpose of identifying the area of the poster that was touched by the horse it was divided into 4 equal quarters (TL, TR, BL, BR). In FP the nose of the horse in the 2-D image was located in BL, eyes and ears in TL, chest and lower neck in BR and upper neck in TR. In AP each area contained similar but unique abstract patterns of comparable colour to FP. Differences in behaviour were found according to which poster was displayed. FP was touched significantly more than AP (p=0.001) and was looked at more often (p=0.008). With FP the horses spent significantly longer with their ears forward (p=0.008) and licking and chewing (p=0.016). When the number of touches per poster area was compared (FP and AP) a significant difference was found in the number of times that BL (nose) and BR (chest/lower neck) were touched (p=0.011). Both areas were touched more frequently on FP, with BL being touched the most. In study 2 the same experimental protocol was used to compare responses to positive (PFP) or negative (NFP) 2-D images of a horse’s face (same horse in both PFP and NFP). Again, differences in behaviour were found in response to the two posters. PFP was touched significantly more than NFP (p=0.002) and on both posters the area BL (nose) was touched more frequently than the other areas (PFP: p=0.02, NFP: p=0.01). More ears back behaviour (p<0.001) and more ear locked on behaviour (p=0.008) was shown with NFP. The results of these studies indicate that horses can recognize 2-D images as con-specifics as well as responding to differences in facial expression. There is now the potential for further investigation into the importance of other visual cues in recognition and social interaction as well as the application of findings to enhance equine welfare.

Abstract: The complex housing environment and the close contact between humans and horses in equine sports place high demands on the learning capacity of horses. To date only limited information is available on the learning ability of the horse including higher order cognition. A type of higher order cognition is to perceive and discriminate quantities. Several mammals and birds have shown to be capable of discriminating objects due to their quantity (Brannon and Roitman, 2003). With regard to horses, there are only few studies available concerning their numerosity judgment (Uller and Lewis, 2009) and this ability is discussed controversially (Henselek et al, 2012). Possibly, the legacy of ‘‘Clever Hans’’ overshadowed further research on numerical capacity in horses, a horse to whom several psychologists incorrectly attributed the capacity of symbolic calculation (Pfungst, 1907; Rosenthal, 1965). In the present study we wanted to show whether Shetland ponies are able to transfer a previously learned concept of sameness to a numerosity judgment. The base of the test design was a “matching to sample” task, where the ponies had learned to relate abstract symbols to another which were presented on a LCD screen. Three Shetland ponies, which previously solved the matching to sample task, were tested in two test phases. In the first test phase different quantities of dots were presented (1 vs. 2; 2 vs. 3; 3 vs. 4; 4 vs. 5). To exclude discrimination due to the shape of the stimuli, the dots were varied in size and arrangement. The stimuli were presented in a triangular arrangement on the LCD screen; the sample stimulus was presented in the middle above and the discrimination stimuli in the two lower corners (S+ and S-). The pony received a food reward, by choosing the positive stimulus (S+). When the negative stimulus (S-) was chosen, the pony entered the next trial. Each learning session consisted of 20 decision trials. To investigate whether the numerosity judgment was transferable to mixed geometrical symbols (tri-, rectangle, rhomb, dot and cross) a second test phase was designed. All of the three Shetland ponies met the learning criterion of the first test phase (80% correct responses in two consecutive sessions) within the first eight sessions. One pony could transfer all judgments to the mixed symbols (up to 4 vs. 5), another pony up to 3 vs. 5 and the third on the level 2 vs. 3. These are the first reported findings that ponies are able to discriminate up to five objects. The numerosity judgment seemed to be easier for the ponies when homogenous objects were presented, than in the case of heterogeneous symbols. The reaction of the ponies occurred within few seconds, suggesting that the animals used subitizing for their numerosity judgment.
Keywords:
Cognition, numerical capacity, numerosity judgment, Shetland ponys
References:
Brannon E, Roitman J (2003) Nonverbal representations of time and number in animals and human infants. In: Meck WH (ed) Functional and neural mechanisms of interval timing. CRC Press, Boca Raton, pp 143–182
Henselek Y, Fischer J, Schloegl C (2012) Does the stimulus type influence horses’ performance in a quantity discrimination task? Front Psychol 3:504
Pfungst O (1907) Der Kluge Hans. Ein Beitrag zur nicht-verbalen Kommunikation. 3rd edn. (reprint of the original 1983) Frankfurter Fachbuchhandlung für Psychologie, Frankfurt
Rosenthal R (1965) Clever Hans: the horse of Mr. Von Osten. Holt, Rinehart and Winston, New York
Uller C, Lewis J (2009) Horses (Equus caballus) select the greater of two quantities in small numerical sets. Anim Cogn 12:733–738

Abstract: We examined how the brain organizes interrelated facts during learning and how the facts are subsequently manipulated in a transitive inference (TI) paradigm (e.g., if A<B and B<C, then A<C). This task determined features such as learned facts and behavioral goals, but the learned facts could be organized in any of several ways. For example, if one learns a list by operating on paired items, the pairs may be stored individually as separate facts and reaction time (RT) should decrease with learning. Alternatively, the pairs may be stored as a single, unified list, which may yield a different RT pattern. We characterized RT patterns that occurred as participants learned, by trial and error, the predetermined order of 11 shapes. The task goal was to choose the shape occurring closer to the end of the list, and feedback about correctness was provided during this phase. RT increased even as its variance decreased during learning, suggesting that the learnt knowledge became progressively unified into a single representation, requiring more time to manipulate as participants acquired relational knowledge. After learning, non-adjacent (NA) list items were presented to examine how participants reasoned in a TI task. The task goal also required choosing from each presented pair the item occurring closer to the list end, but without feedback. Participants could solve the TI problems by applying formal logic to the previously learnt pairs of adjacent items; alternatively, they could manipulate a single, unified representation of the list. Shorter RT occurred for NA pairs having more intervening items, supporting the hypothesis that humans employ unified mental representations during TI. The response pattern does not support mental logic solutions of applying inference rules sequentially, which would predict longer RT with more intervening items. We conclude that the brain organizes information in such a way that reflects the relations among the items, even if the facts were learned in an arbitrary order, and that this representation is subsequently used to make inferences.

Abstract: We provide selected examples from the fish literature of phenomena found in fish that are currently being examined in discussions of cognitive abilities and evolution of neocortex size in primates. In the context of social intelligence, we looked at living in individualized groups and corresponding social strategies, social learning and tradition, and co-operative hunting. Regarding environmental intelligence, we searched for examples concerning special foraging skills, tool use, cognitive maps, memory, anti-predator behaviour, and the manipulation of the environment. Most phenomena of interest for primatologists are found in fish as well. We therefore conclude that more detailed studies on decision rules and mechanisms are necessary to test for differences between the cognitive abilities of primates and other taxa. Cognitive research can benefit from future fish studies in three ways: first, as fish are highly variable in their ecology, they can be used to determine the specific ecological factors that select for the evolution of specific cognitive abilities. Second, for the same reason they can be used to investigate the link between cognitive abilities and the enlargement of specific brain areas. Third, decision rules used by fish could be used as 'null-hypotheses' for primatologists looking at how monkeys might make their decisions. Finally, we propose a variety of fish species that we think are most promising as study objects.