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Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
Published on: January 7, 2019
Predictive processes linking sense of agency and fatigue: a novel allostatic framework
Emanuela Pizzolla1,2, Angela Marotta1, Matthew R Longo2
1Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.
Abstract:
The sense of agency and the experience of fatigue are usually treated as separate constructs: one concerning perceived control over action, the other reflecting subjective energetic state. However, both rely on how the brain predicts, evaluates, and updates information about the body and its actions. Despite this conceptual proximity, the two phenomena have rarely been examined together, and no unified framework currently explains why changes in perceived control and perceived effort so often co-occur. The aim of this review was to provide such integrative framework. We first examined behavioral, clinical, and neuroimaging evidence indicating that both agency and fatigue rely on the precision of anticipatory models that guide action and bodily regulation. When predictions align with incoming sensory and interoceptive signals, individuals experience a stable sense of control and low perceived effort. When these predictions become imprecise or mismatched, disruptions can arise in both domains. We then evaluated existing theoretical models for agency and fatigue and highlighted the limitations of accounts that treat the two phenomena independently or assume unidirectional relationships. Building on these limitations, we propose an allostasis-based model in which agency and fatigue emerge from the same anticipatory system governing energy regulation. In this view, perturbations in prediction can propagate across systems, producing parallel disruption in perceived control and effort. This new integrative perspective underscores the need for research designs that assess agency and fatigue jointly and provides a conceptual foundation for understanding their co-occurrence across healthy and clinical populations.
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