Depressive symptoms are associated with blunted reward learning in social contexts

Safra, Lou; Chevallier, Coralie; Palminteri, Stefano

doi:10.1371/journal.pcbi.1007224

Cited by 36 publications

(27 citation statements)

References 49 publications

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“…The ensuing persistence of imitation may in part explain the strength and pervasiveness of phenomena related to social influence. Future research will determine whether or not imitation is impaired in social and nonsocial psychiatric conditions, such as depression, anxiety, autism, and borderline personality disorder, and whether these hypothetical impairments take the form of shifts in its computational implementation and/or model parameters [ 51 ].…”

Section: Discussionmentioning

confidence: 99%

The actions of others act as a pseudo-reward to drive imitation in the context of social reinforcement learning

et al. 2020

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While there is no doubt that social signals affect human reinforcement learning, there is still no consensus about how this process is computationally implemented. To address this issue, we compared three psychologically plausible hypotheses about the algorithmic implementation of imitation in reinforcement learning. The first hypothesis, decision biasing (DB), postulates that imitation consists in transiently biasing the learner’s action selection without affecting their value function. According to the second hypothesis, model-based imitation (MB), the learner infers the demonstrator’s value function through inverse reinforcement learning and uses it to bias action selection. Finally, according to the third hypothesis, value shaping (VS), the demonstrator’s actions directly affect the learner’s value function. We tested these three hypotheses in 2 experiments (N = 24 and N = 44) featuring a new variant of a social reinforcement learning task. We show through model comparison and model simulation that VS provides the best explanation of learner’s behavior. Results replicated in a third independent experiment featuring a larger cohort and a different design (N = 302). In our experiments, we also manipulated the quality of the demonstrators’ choices and found that learners were able to adapt their imitation rate, so that only skilled demonstrators were imitated. We proposed and tested an efficient meta-learning process to account for this effect, where imitation is regulated by the agreement between the learner and the demonstrator. In sum, our findings provide new insights and perspectives on the computational mechanisms underlying adaptive imitation in human reinforcement learning.

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Section: Discussionmentioning

confidence: 99%

The actions of others act as a pseudo-reward to drive imitation in the context of social reinforcement learning

et al. 2020

Self Cite

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“…Interestingly, with regard to our third main question, this learning bias towards negative information was modulated by the social context and only present when participants were exposed to a potentially judging audience. This distinction has not been explored so far in social anxiety even though the importance of the social context has recently been pointed out for depression 55 . It has been suggested that diminished striatal involvement in the brain’s reward system reflects the lack of a motivational preference for positive social information in social anxiety disorder 56 .…”

Section: Discussionmentioning

confidence: 99%

Negativity-bias in forming beliefs about own abilities

Müller-Pinzler

Czekalla

Mayer

et al. 2019

Sci Rep

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During everyday interactions people constantly receive feedback on their behavior, which shapes their beliefs about themselves. While classic studies in the field of social learning suggest that people have a tendency to learn better from good news (positivity bias) when they perceive little opportunities to immediately improve their own performance, we show updating is biased towards negative information when participants perceive the opportunity to adapt their performance during learning. In three consecutive experiments we applied a computational modeling approach on the subjects’ learning behavior and reveal the negativity bias was specific for learning about own compared to others’ performances and was modulated by prior beliefs about the self, i.e. stronger negativity bias in individuals lower in self-esteem. Social anxiety affected self-related negativity biases only when individuals were exposed to a judging audience thereby potentially explaining the persistence of negative self-images in socially anxious individuals which commonly surfaces in social settings. Self-related belief formation is therefore surprisingly negatively biased in situations suggesting opportunities to improve and this bias is shaped by trait differences in self-esteem and social anxiety.

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“…The ensuing persistence of imitation may in part explain the strength and pervasiveness of phenomena related to social influence. Future research will determine whether or not imitation is impaired in social and non-social psychiatric conditions, such as depression, anxiety, autism and borderline personality disorder, and whether these hypothetical impairments take the form of shifts in its computational implementation and/or model parameters (42).…”

Section: Discussionmentioning

confidence: 99%

Imitation as a model-free process in human reinforcement learning

Najar

Bonnet

Bahrami

et al. 2019

Preprint

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While there is not doubt that social signals affect human reinforcement learning, there is still no consensus about their exact computational implementation. To address this issue, we compared three hypotheses about the algorithmic implementation of imitation in human reinforcement learning. A first hypothesis, decision biasing, postulates that imitation consists in transiently biasing the learner's action selection without affecting her value function. According to the second hypothesis, model-based imitation, the learner infers the demonstrator's value function through inverse reinforcement learning and uses it for action selection. Finally, according to the third hypothesis, value shaping, demonstrator's actions directly affect the learner's value function. We tested these three psychologically plausible hypotheses in two separate experiments (N = 24 and N = 44) featuring a new variant of a social reinforcement learning task, where we manipulated the quantity and the quality of the demonstrator's choices. We show through model comparison that value shaping is favored, which provides a new perspective on how imitation is integrated into human reinforcement learning. Reinforcement Learning | Social Learning | Imitation | Computational cognitive modeling | Decision-making | Meta-learningCorrespondence: anis.najar@ens.fr, stefano.palminteri@ens.fr

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Depressive symptoms are associated with blunted reward learning in social contexts

Cited by 36 publications

References 49 publications

The actions of others act as a pseudo-reward to drive imitation in the context of social reinforcement learning

The actions of others act as a pseudo-reward to drive imitation in the context of social reinforcement learning

Negativity-bias in forming beliefs about own abilities

Imitation as a model-free process in human reinforcement learning

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