Does Sound Timing Organization Matter? How Time Interval Influences the Perception of Closely Spaced Frequencies

Background/Objectives: Temporal predictability may sharpen our ability to distinguish similar sounds, but whether this relies on attention is unclear. This study examined how temporal structure influences frequency discrimination. Methods: Thirty-six adults completed active (attend) and passive (ignore) listening tasks across three paradigms that varied in temporal structure: oddball (isolated deviants), two-tone frequency discrimination paradigm (pairs comparison), and local irregularity of the local/global paradigm (five-tone sequences, bundles). Stimuli varied in difficulty via small or large frequency deviations. Behavioral responses and subjective ratings were collected during active and passive listening. EEG was recorded to assess mismatch negativity (MMN) (either early MMN (eMMN) or mismatch response (MMR)) and P300 event-related potentials. Results: Under active listening, temporal predictability significantly improved performance, but only for difficult discriminations. The local-irregularity condition yielded higher hit rates and greater perceptual sensitivity (d') than the other paradigms. This benefit was accompanied by enhanced P300, yet participants rated the conditions as equally difficult, indicating no metacognitive awareness. Under passive listening, predictability helped only for easy stimuli, marked by a larger MMR. No reliable change-detection response occurred for difficult sounds when attention was diverted. Conclusions: These findings suggest that the combination of temporal predictability and repeated standard presentation in the local irregularity paradigm can improve frequency discrimination under challenging, attended conditions, with some evidence for partial dissociation between objective performance and subjective awareness. However, substantial individual variability and cross-paradigm confounds caution against strong causal claims. These results are broadly consistent with predictive coding frameworks but require replication with counterbalanced designs and larger deviant trial counts.