How much is the thought of God (as manifested in the brain) like a thought of something objectively real or something objectively not real? How similar or different are God representations in the brains of believers and nonbelievers? To address these questions, we will leverage new advances in machine learning of neuroimaging data and the technique of representational similarity analysis (RSA). RSA differs from traditional brain imaging. It focuses on mosaic features of neural representation, seeking information in patterned relationships between tens of thousands of “voxels.” Critically, RSA defines a concept representation not by its mosaic alone, but also by its relationship – or "distance" – to other mosaics representing other concepts. RSA has yielded new insights in many areas of cognition, but has not yet been applied to religious concepts. Using RSA to analyze functional magnetic resonance imaging data, we will investigate how God is represented in the brain relative to other entities that are real or not real (e.g. Father, Superman). We will explore whether and how God representations are similar and/or different in the brains of believers and unbelievers. Pairing RSA with analysis of psychological dimensional structure, we aim to further explain why some entities are represented similarly or differently (i.e. what shared psychological dimensions explain similar representation and how these dimensions are manifested in neural patterns). As a product of this work, RSA may substantially extend the research capacity of religion science by identifying an underlying neural representational space where the similarity and distinctness of religious and nonreligious representations can be measured. As another key product, an international conference will support convergence and collaboration in religious cognition research. RSA cannot replace, but may add to, behavioral methods to provide more complete answers about the representational nature of religious concepts.
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