A Dynamic Affective Core to Bind the Contents, Context, and Value of Conscious Experience

The private and dynamic nature of conscious subjective experience poses an empirical challenge that has led neuroscience-based theories about consciousness to note the importance of the hard problem of explaining how subjective phenomenal experience can arise from neural activity but set it aside and focus on the easier problems associated with information representation and behavior. This approach leaves a major gap in our understanding of the neural mechanisms underlying conscious subjective experience and its dynamic nature. However, computational methods integrated with a variety of tools for measuring human brain activity are beginning to link dynamic changes in subjective affect with reproducible neurobehavioral signals in humans. In particular, research applying computational reinforcement learning theory has shown tremendous utility in investigating human choice behavior and the role the dopaminergic system plays in dynamic behavioral control. This research is beginning to reveal an explicit connection between the dynamics of dopaminergic signals and dynamic changes in subjective affect. However, it should be obvious that the dopaminergic system alone is not sufficient to explain all of the complexities of affective dynamics. We review foundational work, highlight current problems and open questions, and propose a Dynamic Affective Core Hypothesis that integrates advances in our understanding of the representation of the content and context of conscious experiences with our nascent understanding about how these representations acquire and retain affective subjective value.