Active inference integrates perception, decision-making, and learning into a united theoretical framework, providing an efficient way to trade off exploration and exploitation by minimizing (expected) free energy. In this study, we asked how the brain represents values and uncertainties (novelty and variability), and resolves these uncertainties under the active inference framework in the exploration-exploitation trade-off. Twenty-five participants performed a contextual two-armed bandit task, with electroencephalogram (EEG) recordings. By comparing the model evidence for active inference and reinforcement learning models of choice behavior, we show that active inference better explains human decision-making under novelty and variability, which entails exploration or information seeking. The EEG sensor-level results show that the activity in the frontal, central, and parietal regions is associated with novelty, while the activity in the frontal and central brain regions is associated with variability. The EEG source-level results indicate that the expected free energy is encoded in the frontal pole and middle frontal gyrus and uncertainties are encoded in different brain regions but with overlap. Our study dissociates the expected free energy and uncertainties in active inference theory and their neural correlates, speaking to the construct validity of active inference in characterizing cognitive processes of human decisions. It provides behavioral and neural evidence of active inference in decision processes and insights into the neural mechanism of human decisions under uncertainties.

The hippocampus is a complex structure critically involved in numerous behavior-regulating systems. In young adults, multiple overlapping spatial modes along its longitudinal and transverse axes describe the organization of its functional integration with neocortex, extending the traditional framework emphasizing functional differences between sharply segregated hippocampal subregions. Yet, it remains unknown whether these modes (i.e. gradients) persist across the adult human lifespan, and relate to memory and molecular markers associated with brain function and cognition. In two independent samples, we demonstrate that the principal anteroposterior and second-order, mid-to-anterior/posterior hippocampal modes of neocortical functional connectivity, representing distinct dimensions of macroscale cortical organization, manifest across the adult lifespan. Specifically, individual differences in topography of the second-order gradient predicted episodic memory and mirrored dopamine D1 receptor distribution, capturing shared functional and molecular organization. Older age was associated with less distinct transitions along gradients (i.e. increased functional homogeneity). Importantly, a youth-like gradient profile predicted preserved episodic memory – emphasizing age-related gradient dedifferentiation as a marker of cognitive decline. Our results underscore a critical role of mapping multidimensional hippocampal organization in understanding the neural circuits that support memory across the adult lifespan.