The nativist-empiricist debate has long organized cognitive science, framing cognitive mechanisms as either innate or learned. Recent advances in controlled rearing and scalable domain-general neural networks now allow this debate to be tested with unprecedented rigor, by raising newborn animals and deep neural networks under tightly matched developmental conditions. Strikingly, when pushed to this empirical limit, the debate does not resolve: the same developmental phenomena support both radical empiricism and radical nativism. We argue that this stalemate reflects a conceptual error. The debate conflates explanatory levels and ontological orientations, with nativists emphasizing stable symbolic structures and empiricists emphasizing the subsymbolic processes that produce those structures. We propose dissolving the dichotomy within a multilevel framework of cognitive development.
Evidence shows that aesthetic evaluations are underpinned by mechanisms in the reward system that compute value for objects of interest. In turn, recent behavioral, computational, and neuroimaging evidence suggests that creativity involves a similar valuation process, as people generate and evaluate the originality and adequacy of their ideas-two standard criteria of creativity. These findings suggest that creativity and aesthetic evaluation may be supported by a domain-general mechanism for computing subjective value. We offer a proposal in which creators' value computations are conveyed by the structure and content of their works and recovered during aesthetic evaluation through shared reward-system mechanisms and associated processes. On this view, creating and appreciating are two related expressions of a shared value-based process.
How a scientific community is organized can affect whether disagreement drives progress or leads to isolation. Students and postdocs are uniquely placed to build communities that bridge theoretical and methodological divides. Drawing on a student-led society in consciousness science, we show how empowering early-career researchers can turn fragmentation into collaboration.
