Dopaminergic signaling supports auditory social learning.

Sci Rep

Center for Neural Science, New York University, 4 Washington Place, New York, NY, 10003, USA.

Published: June 2021

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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8222360PMC
http://dx.doi.org/10.1038/s41598-021-92524-1DOI Listing

Publication Analysis

Top Keywords

social learning
24
exposure sessions
20
learning
9
explicit reward
8
test dopaminergic
8
dopaminergic signal
8
contributes social
8
discrimination task
8
sessions naïve
8
naïve observer
8

Similar Publications

Learning From Pregnant Women Eating 5 Servings or More of Vegetables Daily: Strategies, Behaviors, and Motivators.

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.

Objective: To explore the context, behaviors, strategies, and motivators of pregnant women who consume 5 servings of vegetables daily.

Methods: Positive deviance study involving Australian pregnant women (9 of 529) identified through a validated food frequency questionnaire. Semistructured interviews explored their strategies, behaviors, and motivators.

View Article and Find Full Text PDF

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 PDF

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 PDF

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 PDF

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.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!