Explicit rewards are commonly used to reinforce a behavior, a form of learning that engages the dopaminergic neuromodulatory system. In contrast, skill acquisition can display dramatic improvements from a social learning experience, even though the observer receives no explicit reward. Here, we test whether a dopaminergic signal contributes to social learning in naïve gerbils that are exposed to, and learn from, a skilled demonstrator performing an auditory discrimination task. Following five exposure sessions, naïve observer gerbils were allowed to practice the auditory task and their performance was assessed across days. We first tested the effect of an explicit food reward in the observer's compartment that was yoked to the demonstrator's performance during exposure sessions. Naïve observer gerbils with the yoked reward learned the discrimination task significantly faster, as compared to unrewarded observers. The effect of this explicit reward was abolished by administration of a D1/D5 dopamine receptor antagonist during the exposure sessions. Similarly, the D1/D5 antagonist reduced the rate of learning in unrewarded observers. To test whether a dopaminergic signal was sufficient to enhance social learning, we administered a D1/D5 receptor agonist during the exposure sessions in which no reward was present and found that the rate of learning occurred significantly faster. Finally, a quantitative analysis of vocalizations during the exposure sessions suggests one behavioral strategy that contributes to social learning. Together, these results are consistent with a dopamine-dependent reward signal during social learning.
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http://dx.doi.org/10.1038/s41598-021-92524-1 | DOI Listing |
J Nutr Educ Behav
January 2025
School of Medicine, University of Queensland, Brisbane, Queensland, Australia; Women's and Newborn Services, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia.
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J Intellect Disabil Res
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Institute of Public Health, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Background: People with intellectual disabilities (IDs) require more vision care but encounter considerable challenges during eye examinations. Specialised clinics established specifically for people with IDs are generally limited. This study aims to evaluate primary family caregivers' willingness to pay (WTP) for specialised ophthalmology services designed for people with IDs.
View Article and Find Full Text PDFEur J Dent Educ
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Grup de Recerca Educativa en Ciències de la Salut (GRECS), Universitat Pompeu Fabra, Barcelona, Spain.
Introduction: Generic competencies are transferable skills, knowledge and attitudes essential for personal and professional development and not restricted to any particular field. Evidence shows the relevance of incorporating them into the dentistry curriculum. However, defining which competencies to prioritise is complex and requires input from the academic community.
View Article and Find Full Text PDFSensors (Basel)
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Electrical Engineering and Computer Science (EECS), KTH Royal Institute of Technology, 10044 Stockholm, Sweden.
In the era of big data, advanced data processing devices and smart sensors greatly benefit us in many areas. As for each individual user, data sharing can be an essential part of the process of data collection and transmission. However, the issue of constant attacks on data privacy arouses huge concerns among the public.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Software Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
This paper tackles the challenge of accurately segmenting images of Ming-style furniture, an important aspect of China's cultural heritage, to aid in its preservation and analysis. Existing vision foundation models, like the segment anything model (SAM), struggle with the complex structures of Ming furniture due to the need for manual prompts and imprecise segmentation outputs. To address these limitations, we introduce two key innovations: the material attribute prompter (MAP), which automatically generates prompts based on the furniture's material properties, and the structure refinement module (SRM), which enhances segmentation by combining high- and low-level features.
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