Systemic neurophysiological signals of auditory predictive coding - Muñoz‐Caracuel, Manuel; Muñoz, Vanesa; Ruiz‐Martínez, Francisco J.; Vázquez Morejón, Antonio J.; Gómez, Carlos M. (Psychophysiology, 2024)
Predictive coding framework posits that our brain continuously monitors changes in the environment and updates its predictive models, minimizing prediction errors to efficiently adapt to environmental demands. However, the underlying neurophysiological mechanisms of these predictive phenomena remain unclear. The present study aimed to explore the systemic neurophysiological correlates of predictive coding processes during passive and active auditory processing. Electroencephalography (EEG), functional near‐infrared spectroscopy (fNIRS), and autonomic nervous system (ANS) measures were analyzed using an auditory pattern‐based novelty oddball paradigm. A sample of 32 healthy subjects was recruited. The results showed shared slow evoked potentials between passive and active conditions that could be interpreted as automatic predictive processes of anticipation and updating, independent of conscious attentional effort. A dissociated topography of the cortical hemodynamic activity and distinctive evoked potentials upon auditory pattern violation were also found between both conditions, whereas only conscious perception leading to imperative responses was accompanied by phasic ANS responses. These results suggest a systemic‐level hierarchical reallocation of predictive coding neural resources as a function of contextual demands in the face of sensory stimulation. Principal component analysis permitted to associate the variability of some of the recorded signals. The predictive coding framework posits that our brain is a continuously active inferential system. Our findings provide empirical evidence of shared predictive coding brain signals between passive and active auditory processing that supports this hypothesis and reveals distinct multimodal neurophysiological responses to passively and actively processed prediction errors that suggest a systemic‐level hierarchical optimization of neural resources according to contextual demands in the face of auditory stimulation.