Could posture reflect welfare state? A study using geometric morphometrics in riding school horses

Advances in the Clinical Diagnostics to Equine Back Pain: A Review of Imaging and Functional Modalities

Back pain is common in ridden horses. Back diseases in horses include Impinging Dorsal Spinous Processes, Ventral Spondylosis, Osteoarthritis of Articular Process, Intervertebral Discs Disease, Vertebral Fractures, Conformational Abnormalities, Desmopathy of the Supraspinous Ligament, Desmopathy of the Intraspinous Ligament, and Longissimus Muscle Strain. Back pain may also develop as a result of lameness (particularly hindlimb lameness). A poorly fitting saddle and an unbalanced rider are also considered important factors influencing the development of back pain in horses. The conventional diagnosis of equine back pain includes a clinical examination and diagnostic imaging examination using ultrasound, radiography, and thermography. Advanced diagnostic modalities of equine back pain involve the objectification of standard procedures through the use of algometers, a lameness locator, biometric mats, and the geometric morphometrics method. In addition to modern diagnostic methods, such as computed tomography and scintigraphy, advances in the diagnosis of equine back pain include the use of electromyography and functional electrical stimulation. The aim of this review article is to familiarize clinicians with the usefulness and capabilities of conventional diagnostic protocols and advanced diagnostic modalities. Although orthopedic examination and traditional diagnostic methods will remain the foundation of the diagnosis of back diseases, modern methods meet the growing expectations towards high-performance horses and allow for deeper diagnostics and objective monitoring of rehabilitation and training progress.

Development, refinement, and validation of an equine musculoskeletal pain scale

Musculoskeletal disease is a common cause of chronic pain that is often overlooked and inadequately treated, impacting the quality of life of humans and horses alike. Lameness due to musculoskeletal pain is prevalent in horses, but the perception of pain by owners is low compared with veterinary diagnosis. Therefore, this study aims to establish and validate a pain scale for chronic equine orthopaedic pain that is user-friendly for horse owners and veterinarians to facilitate the identification and monitoring of pain in horses. The newly developed musculoskeletal pain scale (MPS) was applied to 154 horses (mean age 20 ± 6.4 years SD) housed at an equine sanctuary, of which 128 (83%) suffered from chronic orthopaedic disease. To complete the MPS, the horses were observed and videotaped from a distance while at rest in their box or enclosure. In addition, they received a complete clinical and orthopaedic exam. The need for veterinary intervention to address pain (assessed and executed by the sanctuary independent from this study) was used as a longitudinal health outcome to determine the MPS's predictive validity. To determine the interrater agreement, the MPS was scored for a randomly selected subset of 30 horses by six additional blinded raters, three equine veterinary practitioners, and three experienced equestrians. An iterative process was used to refine the tool based on improvements in the MPS's correlation with lameness evaluated at the walk and trot, predictive validity for longitudinal health outcomes, and interrater agreement. The intraclass correlation improved from 0.77 of the original MPS to 0.88 of the refined version (95% confidence interval: 0.8-0.94). The refined MPS correlated significantly with lameness at the walk (r = 0.44, p = 0.001) and trot (r = 0.5, p < 0.0001). The refined MPS significantly differed between horses that needed veterinary intervention (mean MPS = 8.6) and those that did not (mean MPS = 5.0, p = 0.0007). In summary, the MPS showed good interrater repeatability between expert and lay scorers, significant correlation with lameness at the walk and trot, and good predictive validity for longitudinal health outcomes, confirming its ability to identify horses with orthopaedic health problems.

The Postural and Body Surface Temperature Response of Leisure Horses to Lunging with Selected Lunging Aids

Incorporating lunging into a horse's daily routine aims to enhance fitness, physical condition, and specific skills or exercises when using lunging aids (LAs). To assess the effectiveness of lunging, non-contact technologies like geometric morphometrics and infrared thermography can be employed. This study seeks to evaluate lunging efficiency based on the horse's posture and surface temperature when lunging with different head and neck positions. The study aims to determine if changes in a horse's posture correspond to increased metabolic activity, as indicated by body surface temperature. Thirteen horses included in the study were lunged with chambon (CH), rubber band (RB), and triangle side reins (TRs) as well as with a freely moving head (FMH). Images were taken in visible light and infrared. Principal Component Analysis (PCA) was used to analyze horse posture changes and a Pixel-Counting Protocol (PCP) was used to quantify surface temperature patterns. The horses' posture exhibited contrasting changes, reflected by a changing centroid shape (p < 0.0001) but not size (p > 0.05) when lunged with RB and TRs, but not CH. Different (p < 0.0001) surface temperature patterns were observed during lunging. FMH lunging resulted in lower temperatures over a larger surface, CH induced moderate temperatures on a smaller area, RB caused moderate to high temperatures across a broader surface, and TRs led to higher temperatures over a smaller region. The studied lunging cases returned different (p < 0.0001) surface temperature patterns. Lunging with FMH returned lower temperatures over a larger surface, CH moderate temperatures on a smaller area, RB moderate to high temperatures across a broader surface, and TRs higher temperatures over a smaller region. The proposed methods can be applied to evaluate the efficiency of lunging in horses.

Exploiting morphobiometric and genomic variability of African indigenous camel populations-A review

Camels (Camelus dromedarius) in Africa are adapted to arid and the semi-arid environmental conditions, and are valuable for meat, milk and fiber production. On account of the growing demand for camels in this continent, there is a need for knowledge on their phenotypic and genetic diversity. This is fundamental to sustainable herd management and utilization including the design of appropriate breeding and conservation strategies. We reviewed studies on the phenotypic and genetic characterization, breeding objectives, systems of production, productive and reproductive performances, and pathways for the sustainable rearing and use of camels in Africa. The morphological and genetic diversity, productive and reproductive abilities of African camels suggest the existence of genetic variations that can be utilized for breeds/ecotypes' genetic improvement and conservation. Possible areas of intervention include the establishment of open nucleus and community-based breeding schemes and utilization of modern reproductive technologies for the genetic improvement of milk and meat yields, sustainable management of rangelands, capacity building of the pastoralists and agro-pastoralists, institutional supports, formation of centralized conservation centres and efficient and effective marketing systems.

Going Deeper than Tracking: A Survey of Computer-Vision Based Recognition of Animal Pain and Emotions

Advances in animal motion tracking and pose recognition have been a game changer in the study of animal behavior. Recently, an increasing number of works go ‘deeper’ than tracking, and address automated recognition of animals’ internal states such as emotions and pain with the aim of improving animal welfare, making this a timely moment for a systematization of the field. This paper provides a comprehensive survey of computer vision-based research on recognition of pain and emotional states in animals, addressing both facial and bodily behavior analysis. We summarize the efforts that have been presented so far within this topic—classifying them across different dimensions, highlight challenges and research gaps, and provide best practice recommendations for advancing the field, and some future directions for research.

Accuracy of image analysis for linear zoometric measurements in dromedary camels

The present study was designed to verify the effectiveness of the image analysis method for body measurement in dromedary camel compared to manual measurements as a reference method. To achieve this aim, twenty-one linear body measurements were estimated on 59 adult Sahraoui dromedary camels (22 males and 37 females) with a normal clinical condition by using a measuring stick or vernier caliper (standard method). On the other hand, image analysis on profile, front, or behind photographs was processed using Axiovision Software. Overall mean comparison, relative error, variance, Pearson's correlation coefficient, and coefficient of variance showed that the image analysis method was accurate in relation to the manual measurement. Furthermore, image analysis results indicated relevant accuracy (bias correction factor, C_b ≈1) and precision (Pearson ρ ≈1) which were significantly correlated with the results of the reference method (Lin's concordance correlation coefficients r_ccc ≈ 1). According to Bland-Altman upper and lower limits of agreement, the concordance was estimated between 93.22 and 98.3%. Passing-Bablok regression showed a good relationship between the results of the two methods displaying no significant systematic and proportional bias. The image analysis method for linear body measurements in dromedary camel showed results that are in agreement with the manual measuring method. Therefore, the image analysis could be considered a valid tool for camel conformation trait studies.

No Morphological Integration of Dorsal Profiles in the Araucanian Horse (Colombia)

Simple Summary

Morphological modules are structures that have components which covary strongly, but that in turn are relatively independent of other modules, while morphological integration is understood to mean the coordinated morphological variation of the components of a functional whole. Important traits to describe equine breeds are the profiles of different body regions (alloidism). In this research, it was determined if the division between the cervical, dorsal, and rump profiles has a modular basis as well as a morphological integration. A total of 135 digital photographs were booked, in a lateral view (14 females and 121 geldings; age range: 2–20 years), of adult horses, an equine population typical of the floodplain of Arauca, NE Colombia. From each image, 25 reference points (semi-markers) were obtained at the dorsal level of the neck, back, and croup. The modularity hypothesis of different body profiles based on differentiated regions was tested using the RV coefficient, and a two-block partial least-squares analysis was used to assess the level of morphological integration. The results showed that each alloidic group reflected high integration but low modularity. The absence of the fragmentation of the alloidic assemblages would promote the adaptive capacity of the breed by linking coordinated functional responses to similar selection pressures, for example, field work.

Abstract

The aim of this research was to determine if the division between the cervical, dorsal, and croup profiles (three regions commonly assessed for descriptive profile purposes) has a modular basis as well as a morphological integration. For this, a total of 135 digital photographs were obtained, in a lateral view, of adult horses (14 females and 121 geldings; age range: 2–20 years), of the Araucanian breed, an equine population typical of the flooded savannah of Arauca, NE Colombia. From each image, 25 reference points (semi-landmarks) were obtained at the dorsal level of the neck, back, and croup. The hypothesis of the modularity of different body profiles based on differentiated regions was tested using the RV coefficient, and an analysis of two blocks of partial least-squares allowed the evaluation of the level of morphological integration. The results showed that each alloidic group reflected high integration but low modularity. The covariation between the modules was centered mainly on the withers, the loin, and the croup. For the studied profile blocks, no module can be considered. The absence of the fragmentation of the alloidic sets would promote the adaptive capacity of the breed by linking coordinated functional responses to similar selection pressures, e.g., field work. Although the integration between the neck, back, and croup profiles was proven, their modular covariation was low.

Postural behavior recognition of captive nocturnal animals based on deep learning: a case study of Bengal slow loris

The precise identification of postural behavior plays a crucial role in evaluation of animal welfare and captive management. Deep learning technology has been widely used in automatic behavior recognition of wild and domestic fauna species. The Asian slow loris is a group of small, nocturnal primates with a distinctive locomotion mode, and a large number of individuals were confiscated into captive settings due to illegal trade, making the species an ideal as a model for postural behavior monitoring. Captive animals may suffer from being housed in an inappropriate environment and may display abnormal behavior patterns. Traditional data collection methods are time-consuming and laborious, impeding efforts to improve lorises’ captive welfare and to develop effective reintroduction strategies. This study established the first human-labeled postural behavior dataset of slow lorises and used deep learning technology to recognize postural behavior based on object detection and semantic segmentation. The precision of the classification based on YOLOv5 reached 95.1%. The Dilated Residual Networks (DRN) feature extraction network showed the best performance in semantic segmentation, and the classification accuracy reached 95.2%. The results imply that computer automatic identification of postural behavior may offer advantages in assessing animal activity and can be applied to other nocturnal taxa.

Comparison of Donkey, Pony, and Horse Dorsal Profiles and Head Shapes Using Geometric Morphometrics

Since donkey breeding has increased due to their variety of uses, welfare evaluation has become more important. This study aimed to compare donkey, pony, and horse dorsal profiles and head shapes using geometric morphometrics (GM). Photographs of 14 donkeys, 14 ponies, and 14 horses were analyzed using GM, including the sliding semilandmarks method. The variations in the first three principal components (PCs) were PC1: 57.16%, PC2: 16.05%, and PC3: 8.31% for the dorsal profiles and PC1: 44.77%, PC2: 13.46%, and PC3: 7.66% for the head shapes. Both the dorsal profiles and head shapes differed between donkeys and horses (p < 0.0001) but not between donkeys and ponies (p > 0.05). Moreover, both the dorsal profiles and head shapes differed in size between ponies and horses (p < 0.0001) but not in shape (p > 0.05). Higher Mahalanobis and Procrustes distances were noted between donkeys and horses as well between donkeys and ponies than between ponies and horses. The use of geometric morphometrics revealed the differences in the dorsal profiles and head shapes between the studied equids. These differences should be taken into account when adapting welfare scales and methods from horses to donkeys.

Computer Vision for Detection of Body Posture and Behavior of Red Foxes

The behavior of animals is related to their health and welfare status. The latter plays a particular role in animal experiments, where continuous monitoring is essential for animal welfare. In this study, we focus on red foxes in an experimental setting and study their behavior. Although animal behavior is a complex concept, it can be described as a combination of body posture and activity. To measure body posture and activity, video monitoring can be used as a non-invasive and cost-efficient tool. While it is possible to analyze the video data resulting from the experiment manually, this method is time consuming and costly. We therefore use computer vision to detect and track the animals over several days. The detector is based on a neural network architecture. It is trained to detect red foxes and their body postures, i.e., ‘lying’, ‘sitting’, and ‘standing’. The trained algorithm has a mean average precision of 99.91%. The combination of activity and posture results in nearly continuous monitoring of animal behavior. Furthermore, the detector is suitable for real-time evaluation. In conclusion, evaluating the behavior of foxes in an experimental setting using computer vision is a powerful tool for cost-efficient real-time monitoring.

Characteristics of the Donkey's Dorsal Profile in Relation to Its Functional Body Condition Assessment

Simple Summary

Even though animal posture is known to reflect an emotional state, the presence of chronic postures associated with poor welfare has already been investigated in horses. Measuring, quantifying, and comparing postures requires an application of an objective tool, such as geometric morphometrics. This study aimed to use geometric morphometrics to characterize the dorsal profile of donkeys in relation to their individual features. Forty donkeys were photographed and characterized using the body condition score (BCS), fatty neck score (FNS), dental condition score (DCS), sex, and breed. Then, photographs were analyzed using geometric morphometrics and the differences in dorsal profile between the examined criteria were tested. Within the entire set of donkey dorsal profiles, deformation related to BCS and FNS was observed. FNS measurement seems to have the strongest influence on a donkey’s dorsal profile among the examined criteria. Concluding, the donkeys’ body condition affects their dorsal profile, and both FNS and BCS measurements should be considered when the donkeys’ dorsal profiles are investigated. However, to evaluate the link between the dorsal profile and the welfare state of donkeys, more studies are required.

Abstract

As the breeding of donkeys has increased due to different types of use, welfare evaluation importance increases. This equid’s welfare state has been described using body condition indicators and the geometric morphometrics method. However, the dorsal profile has not yet been assessed in donkeys. In this study, the body condition score (BCS), fatty neck score (FNS), dental condition score (DCS), sex, and breed were used as criteria of dorsal profile deformations. Photographs of 40 donkeys were analyzed using geometric morphometrics. Within the entire set of dorsal profiles, the variance of the first three principal components (PCs) was PC1 = 37.41%, PC2 = 23.43%, and PC3 = 13.34%. The dorsal profiles displayed deformation as an effect of FNS and BCS on size (FNS p = 0.012; BCS p = 0.024) and shape (FNS p < 0.0001; BCS p < 0.0001), rather than as an effect of DCS (p < 0.0001), sex (p = 0.0264), and breed (p < 0.0001) only on shape. The highest distances among the categories (Mahalanobis distances: MD ≥ 13.26; Procrustes distances: PD ≥ 0.044) were noted for FNS. The lowest distances were noted between jennets and males (MD = 4.58; PD = 0.012) and between BCS 1 and BCS 2 (MD = 4.70; PD = 0.018). Donkeys’ body condition affects their dorsal profile and both FNS and BCS measurements should be considered when a donkey’s dorsal profile is investigated.

Detecting Welfare in a Non-Verbal Species: Social/Cultural Biases and Difficulties in Horse Welfare Assessment

Simple Summary

There is a paradox about the welfare of horses in the domestic situation: on the one hand, horses are beloved partners for most owners, but on the other hand, scientific studies are converging to show that there is a high prevalence of welfare problems. There seems to be a mismatch between theoretical knowledge and field applications. In this review, we aim at disentangling the possible factors explaining such a paradox. Among them, we consider the impact of anthropomorphic and cultural biases, popular beliefs, but also overexposure to horses with compromised welfare state, which can change owners’ representation of what is a “normal” horse, on the undervaluation of horse welfare state. We suggest that, rather than simply having knowledge on what should be done, identifying the horse welfare state using validated animal-based indicators is essential to identify and promote best practices.

Abstract

Horses were domesticated for more than 5000 years and have been one of the most emblematic species living alongside humans. This long-shared history would suggest that horses are well known and well understood, but scientific data raise many concerns about the welfare state of most domestic horses suggesting that many aspects have been largely misunderstood. In the present review, we will examine some of the possible human factors that may explain the huge prevalence of welfare problems, despite horses being of special importance to humans. First of all, as horses are non-verbal, current management practices rely upon what one thinks is good for them, which opens the way to subjective interpretations and projections, based on one’s own subjective experience but probably still more on cultural/social norms and influences, traditions and beliefs. The lack of recognition, identification, or even the misinterpretation of signals are other potential reasons for welfare issues. Lastly, the over-exposure to animals with expressions of compromised welfare may lead to lower sensitivity of owners/professionals. That is why we lastly suggest that instead of simply providing information on what to do, we should promote validated visible indicators that leave less room for personal interpretation.

Shape Analysis as an Additional Tool in Roe Deer (Capreolus capreolus) Management: A New Approach Based on the Relationship between Mandible Shape and Trophic Resources

Simple Summary

In recent years, the numerical increase of the roe deer population in Italy has shifted attention to new tools for the management of these populations. The use of biometric data for a correct assessment of the status of ungulate populations is now a standardized and commonly used procedure. In this study, we tried to verify whether, in addition to biometric analyses, morphometrics could be used as a supplementary tool for roe deer management. The study of geometric morphometry has made a major impact by aiding technological and methodological advances. By using Cartesian coordinates of reference points, this method is capable of capturing morphologically distinct shape variables, which can be used as rapid indicators of the status of populations, and thus have the potential to be very useful for wildlife management.

Abstract

The analysis of body shape variability has always been a central element in biology. More recently, geometric morphometry has developed as a new field in shape analysis, with the aim to study body morphological variations and the identification of their causes. In wildlife management, geometric morphometry could be a useful tool to compare the anatomical structures of an organism and quantify its geometric information in order to relate them to environmental factors, thus identifying the causes and effects of the variation and acting management and/or conservation plans. The aim of our study is to evaluate the relationship between roe deer mandible shape and trophic resources available during autumn and winter. We applied a geometric morphometry approach consisting of a Relative Warp analysis of landmark data in 26 roe deer fawn mandibles. Each sample was assigned to an age category and to an environmental category based on the territory carrying capacity. The mandible shape of samples under 8 months of age is likely influenced by the availability of trophic resources. Our findings suggest that the mandible shape is a reliable instrument to assess resource availability. Geometric morphometry could thus represent an additional tool for roe deer management.

The Physical Activity-Dependent Hematological and Biochemical Changes in School Horses in Comparison to Blood Profiles in Endurance and Race Horses

Blood testing is one of the most important ways to improve performance, facilitate recovery and monitor the training of endurance and race horses. However, little is known about the physical activity-dependent changes of blood parameters in horses used for pleasure and in riding schools. This study aimed to perform routine blood tests for training monitoring of sport horses in three different horse types of use. Then the values of blood indicators were compared between school, endurance and race horses to find similarities in the physical activity-dependent profile. The study was carried out on 15 endurance, 15 race and 15 school healthy horses who underwent the typical effort for their disciplines. The hemogram parameters, creatine phosphokinase (CPK), aspartate aminotransferase (AST), blood lactate (LAC), and total serum protein (TSP) concentrations were measured using the same protocol and equipment. Measurements of main hematological and biochemical physical activity-dependent parameters were conducted before, immediately after and 30 min after training. In school horses, the physical activity-dependent increase of WBC (40.9%) and CPK (76.4%) was similar to endurance horses, whereas an increase of RBC (19.1%), HGB (18.6%) and HCT (19.4%) were more similar to race horses. The moderate effort-dependent increase of LAC concentration (2775%) was lower than in race horses (7526%) and higher than in endurance horses (390%). Limiting the training or work monitoring assessment of school horses to only the endurance or racing blood profile may result in the omission of significant changes in hematological and biochemical parameters.

Studying the Shape Variations of the Back, the Neck, and the Mandibular Angle of Horses Depending on Specific Feeding Postures Using Geometric Morphometrics

The effects of specific feeding positions upon the horse's shape variations of the back and neck postures as well as the variations of the mandibular angle have never been objectively studied. For this reason, geometric morphometrics was applied. Six horses, aged 14 ± 8 years (mean ± standard deviation, SD), were video-recorded while using three different feeding positions: on the ground-control position (CP); neck held 15 ± 3° below withers height with low hay net position (LP); neck held 15 ± 3° above withers height with high hay net position (HP). Data were analyzed using principal component analysis (PCA), multivariate analysis of variance (MANOVA), and partial least squares (PLS). A mixed model procedure was applied to evaluate differences in the magnitude of the mandibular angle. Whilst differences between individual horses were confirmed by canonical variate analysis (CVA), PCA analysis showed that a characteristic feeding position could also be identified on a group level. During the HP hay net position, the back and neck postures as well the mandibular angle were different compared to those exhibited by horses feeding from CP. In LP hay net position, the back posture more closely resembled those exhibited while feeding from CP; however, no similarity between LP and CP was found for neck posture and mandibular angle. Since only a few degrees of variation of the feeding position can influence back and neck postures, this aspect should be further investigated. The right compromise between horse welfare, horse safety, and management practices need to be further explored and long-term effects should be investigated.

Leveraging Social Learning to Enhance Captive Animal Care and Welfare

From ants to zebras, animals are influenced by the behavior of others. At the simplest level, social support can reduce neophobia, increasing animals’ exploration of novel spaces, foods, and other environmental stimuli. Animals can also learn new skills more quickly and more readily after observing others perform them. How then can we apply animals’ proclivity to socially learn to enhance their care and welfare in captive settings? Here, I review the ways in which animals (selectively) use social information, and propose tactics for leveraging that to refine the behavioral management of captive animals: to enhance socialization techniques, enrichment strategies, and training outcomes. It is also important to consider, however, that social learning does not always promote the uniform expression of new behaviors. There are differences in animals’ likelihood to seek out or use socially provided information, driven by characteristics such as species, rank, age, and personality. Additionally, social learning can result in inexact transmission or the transmission of undesirable behaviors. Thus, understanding when, how, and why animals use social information is key to developing effective strategies to improve how we care for animals across settings and, ultimately, enhance captive animal welfare.

Development and Validation of an Automated Video Tracking Model for Stabled Horses

Simple Summary

Although there are some methods to detect pain in horses, because of bias and time-consumption, those methods are practically challenging. However, in recent years rapidly developed automated tracking methods have proven that computer-based behaviour monitoring is more reliable in many animal species. That is why in this study we aimed to investigate an automated video tracking model for horses in a clinical context. The findings will help to develop the automated detection of daily activity, to meet the ultimate objective of objectively assessing the pain and wellbeing of horses. An initial analysis of the obtained data offers the opportunity to construct an algorithm to track automatically behaviour patterns of horses.

Abstract

Changes in behaviour are often caused by painful conditions. Therefore, the assessment of behaviour is important for the recognition of pain, but also for the assessment of quality of life. Automated detection of movement and the behaviour of a horse in the box stall should represent a significant advancement. In this study, videos of horses in an animal hospital were recorded using an action camera and a time-lapse mode. These videos were processed using the convolutional neural network Loopy for automated prediction of body parts. Development of the model was carried out in several steps, including annotation of the key points, training of the network to generate the model and checking the model for its accuracy. The key points nose, withers and tail are detected with a sensitivity of more than 80% and an error rate between 2 and 7%, depending on the key point. By means of a case study, the possibility of further analysis with the acquired data was investigated. The results will significantly improve the pain recognition of horses and will help to develop algorithms for the automated recognition of behaviour using machine learning.

Mutual interactions between cognition and welfare: The horse as an animal model

Research in cognitive psychology has repeatedly shown how much cognition and emotions are mutually related to one another. Psychological disorders are associated with cognitive (attention, memory and judgment) biases and chronic pain may affect attention, learning or memory. Laboratory studies have provided useful insights about the processes involved but observations about spontaneous animal models, living in different stress/welfare conditions may help understand further how cognition and welfare are interrelated in the « real world ». Domestic horses constitute such a model as they live in a variety of conditions that impact differently their welfare state. In the present review, we try and provide an overview of the scientific literature on cognition and welfare of domestic horses and their interrelationship. We address how emotions and welfare may affect cognitive processes in horses and impact the way they perceive their environment (including work). We propose new methods for assessing the relationship between welfare and cognition and open up the discussion on the evolution of the brain and the part domestication may have played.