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Dataset results
4 results for “Macaca fuscata”
On following pages: 16. Arunachal Macaque (Macaca munzala); 17. Tibetan Macaque (Macaca thibetana); 18. Stump-tailed Macaque Macaca arctoides); 19. Long-tailed Macaque (Macaca fascicularis); 20. Rhesus Macaque (Macaca mulatta); 21. Japanese Macaque (Macaca fuscata); 22. Taiwanese Macaque (Macaca cyclopis). in Cercopithecidae
On following pages: 16. Arunachal Macaque (Macaca munzala); 17. Tibetan Macaque (Macaca thibetana); 18. Stump-tailed Macaque Macaca arctoides); 19. Long-tailed Macaque (Macaca fascicularis); 20. Rhesus Macaque (Macaca mulatta); 21. Japanese Macaque (Macaca fuscata); 22. Taiwanese Macaque (Macaca cyclopis).
Dataset and codes for "The Warmth of Sarudango: Modelling the Huddling Behaviour of Japanese Macaques (Macaca fuscata)"
<p>Dataset and codes for "<strong><span>The Warmth of Sarudango: Modelling the Huddling Behaviour of Japanese Macaques (<em>Macaca fuscata</em>)"</span></strong></p> <p><strong><span><span>Huddling behaviour is observed across various mammalian and avian species. Huddling, a behaviour wherein animals maintain close physical contact with conspecifics for warmth and social bonding, is widely documented among species in cold environments as a crucial thermoregulatory mechanism. Interestingly, on Shodoshima, Japanese macaques form exceptionally large huddling clusters, often exceeding 50 individuals, a significant deviation from the smaller groups observed in other populations (Arashyama, Katsuyama, Taksakiyama) and climates. This study aims to uncover the mechanisms behind the formation and size of these huddling clusters, proposing that such behaviours can be explained by simple probabilistic rules influenced by environmental conditions, the current cluster size, and individual decisions. Employing a computational model developed in Netlogo, we seek to demonstrate how emergent properties like the formation and dissolution of clusters arise from collective individual actions. We investigate whether the observed differences in huddling behaviour, particularly the larger cluster sizes on Shodoshima compared to those in colder habitats, reflect variations in social tolerance and cohesion. The model incorporates factors such as environmental temperature, cluster size, and individual decision-making, offering insights into the adaptability of social behaviours under environmental pressures. The findings suggest that temperature plays a crucial role in influencing huddling behaviour, with larger clusters forming in colder climates as individuals seek warmth. However, the study also highlights the importance of joining and leaving a cluster in terms of probability in the dynamics of huddling behaviour. We discussed the large clusters on Shodoshima as a result from a combination of environmental factors and a unique social tolerance and cohesion among the macaques. This study contributes to our understanding of complex social phenomena through the lens of self-organisation, illustrating how simple local interactions can give rise to intricate social structures and behaviours.</span></span></strong></p>
Dataset for Influence of ecological and social factors on huddling behaviour and cluster organisation in Japanese macaques (Macaca fuscata)
<p>Dataset for Influence of ecological and social factors on huddling behaviour and cluster organisation in Japanese macaques (Macaca fuscata)</p> <p><span>Huddling behaviour is present in many animal species. This behaviour involves maintaining close physical contact with conspecifics to minimise heat loss and, in general, reduce energy expenditure. Additionally, this behaviour also facilitates complex social interactions within a population. In Japanese macaques, this behaviour is observed in many populations across Japan, including Shodoshima, where huddling clusters can reach up to 100 individuals in winter. Based on several studies on this species, it appears that huddling, or <span> </span>in Japanese, is influenced by both meteorological factors and social relationships between individuals. The objective of this study is to understand the determinants that drive the expression, variation, and organisation of huddling behaviour. Two hypotheses were formulated. The first hypothesis posits that the formation and variations in the size and number of clusters are influenced by meteorological factors, while the second hypothesis suggests that the number and position of individuals within a cluster is related to existing relationships between individuals. To test these, data on the number, size, and individuals composing a cluster were collected, allowing building huddling social networks. Simultaneously, meteorological measurements were taken, along with observations on dominance and grooming interactions between individuals. This allowed us to create several statistical models and social networks for comparison. Our results suggest that the initiation of huddling is mainly related to solar radiation energy, while variations in number and size could be explained by temperature. Moreover, the organisation within a cluster is not random but reflects relationships between individuals. However, it is not a single parameter but rather a combination of social relationships that underpin the organisation of individuals within clusters.</span></p>
Expression data from Rhesus macaques (Macaca fuscata) brain
GEO Series GSE63657. Macaca mulatta; Macaca fuscata. 12 samples. Type: Expression profiling by array.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.