Concurrent Encoding of Precision and Prediction Error in Unfolding Auditory Patterns: Insights from MEG

Abstract

Human listeners possess an innate capacity to discern patterns within rapidly evolving auditory sequences. Core questions, at the forefront of ongoing research, focus on the mechanisms through which these representations are acquired and whether the brain prioritizes or suppresses predictable sensory signals. Previous work, using fast sequences (tone-pips presented at a rate of 20Hz), revealed sustained response effects that appear to track the dynamic predictability of the sequence. Here we extend the investigation to slower sequences (4Hz), permitting the isolation of responses to individual tones. Stimuli were 50ms tone-pips, ordered into random (RND) and regular (REG; a repeating pattern of 10 frequencies) sequences; Two timing profiles were created: in fast sequences tone-pips were presented in direct succession (20 Hz); in slow sequences tone-pips were separated by a 200ms silent gap (4 Hz). Naive participants (N=22; both sexes) passively listened to these sequences, while brain responses were recorded using magnetoencephalography (MEG). Results unveiled a heightened magnitude of sustained brain responses in REG when compared to RND patterns. This manifested from three tones after the onset of the pattern repetition, even in the context of slower sequences characterized by extended pattern durations (2500ms). This observation underscores the remarkable implicit sensitivity of the auditory brain to acoustic regularities. Importantly, brain responses evoked by single tones exhibited the opposite pattern - stronger responses to tones in RND compared to REG sequences. The demonstration of simultaneous but opposing sustained and evoked response effects reveals concurrent processes that shape the representation of unfolding auditory patterns. Significance StatementHumans excel at detecting predictable patterns within sound sequences, a process crucial for listening, language processing, and music appreciation. However, questions persist about the underlying neural mechanisms and the specific information monitored by the brain. Our study addresses these questions by analysing magnetoencephalography (MEG) signals from participants exposed to predictable and unpredictable tone-pip patterns. We found that the MEG signal simultaneously captures two crucial aspects of predictability tracking. Firstly, sustained MEG activity, tracking the sequences evolution, dynamically assesses pattern predictability, shedding light on how the brain evaluates reliability. Secondly, phasic MEG activity, reflecting responses to individual events, shows reduced activity to predictable tones, aligning with the idea that the brain efficiently encodes and anticipates upcoming events in predictable contexts.