This article proposes conceptual and research design principles to identify the core neurocognitive mechanisms that support minimal self-consciousness and how this might be attenuated via computational explanations of selfless states using two different induction methods—meditation and psychedelics. As a proof-of-concept of the utility of this framework, we examine how selfless states induced by these methods might elucidate core neurocognitive mechanisms of minimal selfhood, using two broad computational frameworks that instantiate, first, predictive processing and, second, global workspace modeling. This analysis isolates hierarchical flattening and metastable workspace dynamics as core mechanisms in the predictive processing and global workspace frameworks, respectively. We close by first offering several broad but testable predictions that might be used to guide future research and advance our understanding of the neuroscientific basis of minimal self-consciousness and then discussing challenges that remain in this pursuit. (PsycInfo Database Record (c) 2026 APA, all rights reserved)