Biology subjects

Meesawat, S.

Publications and source records attributed to Meesawat, S..

4 recordsLinked to original sources

bioRxiv2025

Complex modulation of visual attention to 3rd person interactions in wild macaques

Social animals rely on socio-cognitive skills to monitor their social environment and make informed decisions. Yet, visual attention to others interactions in real-life scenes remains understudied, despite evidence for dedicated neuronal networks for the processing of real-life social information and for social interactions in particular. Here, we ask how subject characteristics, interaction valence, and social relationships between subject and stimuli interact to guide overt attention of 56 wild male Assamese macaques to 962 3rd person social scenes that unfolded spontaneously in their vicinity. Social interactions drew more and longer attention than social control scenes lacking the interaction, highlighting the relevance of interaction. The effect of both social bond strength and dominance relations between subject and stimulus on the probability to attend was independently modulated by scene valence. Moreover, beyond reacting to the affordances of the social scene and independent of their social status, males differed in how long they observed the interactions of others. These findings suggest that visual attention is guided by the value an individual associates with different aspects of the social scene based on previous experience in both the agonistic and the affiliative realms and by current threat indicative of complex information integration in the brain.

animal behavior and cognition↗

bioRxiv2025

Age-trajectory of mother-infant relationships in wild Assamese macaques

Maternal care is ubiquitous in mammals, yet its degree and duration vary across taxa. Primate mothers provide extended care, with similar developmental transitions of the mother-infant relationship, though with different paces of change. Ecological conditions can influence the trajectory of this relationship, but data from the wild are still scarce. We used methods from growth studies to quantitatively describe the non-linear age-trajectory of the mother-infant spatial relationship, and the transition from dependent to independent feeding and locomotion in wild Assamese macaques (M. assamensis). We also explored sex differences in the development of the mother-infant relationship. We used a modified Gompertz function to model the combined effect of infant age and sex on mother and infant behaviors extracted from focal observations of 58 infants. Newborns were fully dependent on their mothers for feeding and transportation, with mothers maintaining close proximity. A transitional phase emerged between 1 and 3 months of infant age, marked by a noticeable reduction in the spatial proximity with the mother and a shift in the responsibility for the infants feeding and transportation. During the second half of infancy, the decrease in proximity time slowed down, with infants achieving near-complete locomotion independence, spending the majority of time away from their mothers and feeding independently. No sex differences were found. Our models provided a robust fit for most variables, but we recommend future exploration of alternative nonlinear functions. We interpret the early infant independence observed in our population in the context of the species reproductive strategy.

animal behavior and cognition↗

bioRxiv2024

PriMAT: A robust multi-animal tracking model for primates in the wild

O_LIDetection and tracking of animals is an important first step for automated behavioral studies using videos. Animal tracking is currently done mostly using deep learning frameworks based on keypoints, which show remarkable results in lab settings with fixed cameras, backgrounds, and lighting. However, multi-animal tracking in the wild presents several challenges such as high variability in background and lighting conditions, complex motion, and occlusion. C_LIO_LIWe propose a multi-animal tracking model, PriMAT, for nonhuman primates in the wild. The model learns to detect and track primates and other objects of interest from labeled videos or single images using bounding boxes instead of keypoints. Using bounding boxes significantly facilitates data annotation and robustness. Our one-stage model is conceptually simple but highly flexible, and we add a classification branch that allows us to train individual identification. C_LIO_LITo evaluate the performance of our model, we applied it in two case studies with Assamese macaques (Macaca assamensis) and redfronted lemurs (Eulemur rufifrons) in the wild. We show that with only a few hundred frames labeled with bounding boxes, we can achieve robust tracking results. Combining these results with the classification branch for the lemur videos, our model shows an accuracy of 84% in predicting lemur identities. C_LIO_LIOur approach presents a promising solution for accurately tracking and identifying animals in the wild, offering researchers a tool to study animal behavior in their natural habitats. Our code, models, training images, and evaluation video sequences are publicly available1, facilitating their use for animal behavior analyses and future research in this field. C_LI

animal behavior and cognition↗

bioRxiv2024

New gamma interferon (IFN- g) algorithm for tuberculosis diagnosis in cynomolgus macaques

Tuberculosis (TB) is the first infectious disease to be screened-out from specified pathogen-free cynomolgus macaques (Macaca fascicularis; Mf) using in human pharmaceutical testing. Being either latent or active stage after exposure to the Mycobacterium tuberculosis complex (MTBC), the monkey gamma-interferon release assay (mIGRA) was previously introduced for early TB detection in Mf. However, a high number of indeterminate cases were unexpectedly encountered. The main reasons were a mitogen positive control and an interpretation algorithm. A cohort of 316 Mf exposed to MTBC was tested of two positive mitogen controls [QFT-PHA and a mixture of ConcanavalinA and Pokeweed (ConA+PWM)], and 100 of 316 animals were selected and 26-month followed-up for the establishment of a new mIGRA algorithm for interpretation. As such, the number of indeterminate cases was drastically reduced (80-100%) when the ConA + PWM mixture was used as a positive mitogen control along with a new mIGRA algorithm for interpretation.

microbiology↗