Publications by authors named "Gilles Reymond"
Accurate tracking and analysis of animal behavior is crucial for modern systems neuroscience. However, following freely moving animals in naturalistic, three-dimensional (3D) or nocturnal environments remains a major challenge. Here, we present EthoLoop, a framework for studying the neuroethology of freely roaming animals.
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- Primates, particularly long-tailed macaques, exhibit complex social behaviors influenced by past interactions, demonstrating the potential for reciprocity in their relationships.
- Controlled experiments show these monkeys can reciprocate in a social decision-making task, but mainly in scenarios involving negative outcomes (like receiving an air puff).
- The monkeys' ability to reciprocate depends on witnessing their partner's decisions, indicating that their social interactions are driven by a mix of revenge for negative experiences and gratitude for positive ones.
Article Synopsis
- MDMA was tested for its effects on social behaviors in young male long-tailed macaques, marking the first study of its kind on non-human primates.
- Three doses of MDMA (1.0, 1.5, and 2.0 mg/kg) were administered, revealing significant effects on behaviors like social grooming, foraging, and locomotion.
- Specifically, a 1.5 mg/kg dose increased social grooming, while doses of 1.5 and 2.0 mg/kg decreased foraging, and a 2.0 mg/kg dose increased locomotion, demonstrating MDMA's potential impact on primate social dynamics.
Article Synopsis
- Many primates, particularly long-tailed macaques, engage in solitary object play, which is important for their behavior and social dynamics.
- A study introduced a unique toy to a group of these macaques, revealing that access to the toy created competition reflecting their social hierarchy.
- The findings suggest that object play and social interactions are motivated by different factors, as competition for the toy reduced social contact among the monkeys, similar to how humans perceive competitors as threats.
This article describes a computational model for the sensory perception of self-motion, considered as a compromise between sensory information and physical coherence constraints. This compromise is realized by a dynamic optimization process minimizing a set of cost functions. Measure constraints are expressed as quadratic errors between motion estimates and corresponding sensory signals, using internal models of sensor transfer functions.
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