Predictive Processing Over the Course of Aging: Multiple Timescales of Effective Connectivity

Predictive processing theories describe perception as a dynamic interplay between top-down predictions and bottom-up prediction errors across hierarchical stages of sensory processing. However, it remains unclear how neural connectivity flexibly adapts to changing sensory environments over time, and how these dynamics are influenced by aging. This study investigated how temporal factors on three distinct timescales, as well as age, shape neural responses and connectivity to dynamically changing auditory stimuli. Electroencephalography (EEG) data were recorded from 63 participants aged 18–75 as they listened to sequences of tones, where rare and unexpected “original deviants” became standards over time, and previously standard tones became “reverse deviants.” Event-related potentials (ERPs) were more pronounced for original deviants than reverse deviants. Amplitudes increased on short timescales (seconds) but declined over longer timescales (minutes) and with advancing age. To infer the neural mechanisms underlying these effects, dynamic causal modelling (DCM) was used to analyze effective connectivity. DCM revealed increased descending (top-down) connectivity for original deviants, consistent with a stronger reliance on predictions. Additionally, intrinsic (within-region) connectivity increased over seconds but decreased over minutes, reflecting timescale-dependent neural adaptation. Aging was associated with stronger modulation of descending connectivity by deviant type but weaker modulation by slow dynamics. These results underscore the brain's ability to dynamically adapt to changing sensory environments at multiple timescales and for the first time reveal age-related changes in the dynamics of this adaptation.