Linking offline learning mechanisms to anxiety traits

Understanding how we learn about the value and structure of our environment is central to neurocognitive theories of many psychiatric and neurological disorders. Learning processes have been extensively studied during performance of behavioural tasks (online learning) but less so in relation to "resting" (offline) states. A candidate mechanism for such offline learning is "replay," the sequential neural reactivation of past experiences. Notably, value-based learning is especially tied to replay unfolding in reverse order relative to the original experience ("backward replay"). Here, we demonstrate the utility of EEG-based neural decoding for investigating offline learning, and relate it to trait anxiety. Participants were first required to infer sequential relationships among task objects by using a learned rule to reorganise their visual experiences into distinct sequences. Afterwards, they observed that the final object in one of the sequences was associated with a monetary reward and then entered a post-value resting state. During this rest, we found evidence of backward replay for reward-linked object sequences. The strength of such replay was negatively associated with trait anxiety and positively predicted an increased behavioural preference for reward-predictive stimuli. We also found that high-trait-anxiety individuals showed inefficient credit assignment irrespective of reward magnitude, indicating that this effect does not merely reflect reduced reward sensitivity. Together, these findings suggest a potential aberrant replay mechanism during offline learning in individuals with high trait anxiety. More broadly, our approach illustrates the potential of EEG for measuring structured neural representations in vivo, with implications for studying cognition across a range of neuropsychiatric and neurological disorders.