Dataset Information

Integrating prospective and retrospective cues to the sense of agency: a multi-study investigation.

ABSTRACT: Sense of agency (SoA) refers to the experience of voluntary control over one's own actions, and, through them, over events in the outside world. Recent accounts suggest that SoA involves an integration of various cues. These include prospective cues, for example, related to the fluency of action selection, and retrospective cues, linked to outcome monitoring. It remains unclear whether these cues may have independent effects on SoA, and, in particular, how their relative contributions may change during instrumental learning. In the present study, we explored these issues by conducting a multi-study analysis of seven published and unpublished studies on the role of prospective cues to the SoA. Our main question was how the effects of selection fluency on SoA might change as information about action-outcome contingencies is gathered. Results show that selection fluency can have a general and consistent influence on the SoA, independent of outcome monitoring. This suggests selection fluency is used as a heuristic cue, to prospectively inform our SoA. In addition, our results show that the influence of selection fluency on SoA may change systematically as action-outcome contingencies are gradually learned. We speculate that dysfluent selection may impair formation of mental associations between action and outcome.

SUBMITTER: Sidarus N

PROVIDER: S-EPMC6007171 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Integrating prospective and retrospective cues to the sense of agency: a multi-study investigation.

Sidarus Nura N Vuorre Matti M Haggard Patrick P

Neuroscience of consciousness 20170530 1

Sense of agency (SoA) refers to the experience of voluntary control over one's own actions, and, through them, over events in the outside world. Recent accounts suggest that SoA involves an integration of various cues. These include prospective cues, for example, related to the fluency of action selection, and retrospective cues, linked to outcome monitoring. It remains unclear whether these cues may have independent effects on SoA, and, in particular, how their relative contributions may change ...[more]

PMID: 30042845

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Project description:When agents interact socially with different intentions (or wills), conflicts are difficult to avoid. Although the means by which social agents can resolve such problems autonomously has not been determined, dynamic characteristics of agency may shed light on underlying mechanisms. Therefore, the current study focused on the sense of agency, a specific aspect of agency referring to congruence between the agent's intention in acting and the outcome, especially in social interaction contexts. Employing predictive coding and active inference as theoretical frameworks of perception and action generation, we hypothesize that regulation of complexity in the evidence lower bound of an agent's model should affect the strength of the agent's sense of agency and should have a significant impact on social interactions. To evaluate this hypothesis, we built a computational model of imitative interaction between a robot and a human via visuo-proprioceptive sensation with a variational Bayes recurrent neural network, and simulated the model in the form of pseudo-imitative interaction using recorded human body movement data, which serve as the counterpart in the interactions. A key feature of the model is that the complexity of each modality can be regulated differently by changing the values of a hyperparameter assigned to each local module of the model. We first searched for an optimal setting of hyperparameters that endow the model with appropriate coordination of multimodal sensation. These searches revealed that complexity of the vision module should be more tightly regulated than that of the proprioception module because of greater uncertainty in visual information flow. Using this optimally trained model as a default model, we investigated how changing the tightness of complexity regulation in the entire network after training affects the strength of the sense of agency during imitative interactions. The results showed that with looser regulation of complexity, an agent tends to act more egocentrically, without adapting to the other. In contrast, with tighter regulation, the agent tends to follow the other by adjusting its intention. We conclude that the tightness of complexity regulation significantly affects the strength of the sense of agency and the dynamics of interactions between agents in social settings.

Dataset Information

Integrating prospective and retrospective cues to the sense of agency: a multi-study investigation.

Publications

Integrating prospective and retrospective cues to the sense of agency: a multi-study investigation.

Similar Datasets

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