IntroductionTemporal prediction enhances perceptual processing by aligning neural excitability with expected sensory events. While local oscillatory mechanisms are known to support timing, less is understood about how large-scale functional brain networks dynamically coordinate predictive processes. In particular, it remains unclear how functional connectivity (FC)–the integration of information into network hubs–differs during expectation formation (prediction) versus post-target outcome evaluation, and how this varies across levels of predictability.MethodsTo investigate this, we recorded electroencephalographic data (EEG) while participants performed a cued auditory target-detection task with varying temporal predictability (80% and 50%). FC was analyzed using a data-driven approach based on Normalized Directed Transfer Entropy (NDTE) applied to EEG difference waveforms between high- and low-predictability conditions, separately for the post-cue and post-target periods to distinguish prediction and evaluation phases.ResultsBehaviorally, higher temporal predictability facilitated faster reaction times. Event-related potential (ERP) results revealed that implicit temporal predictability primarily modulated later evaluative processes (P3b, frontal negativity), rather than early sensory components, consistent with context updating under uncertainty. FC analyses revealed that the fronto-temporo-parietal network engaged in the prediction phase evolves into a more focal auditory–frontal circuit during the evaluation of the prediction outcomes.DiscussionOur findings highlight that temporal prediction and evaluation are supported by the dynamic interactions among multiple large-scale networks rather than by any single region or pathway, supporting both frontal-dominant and distributed integration models of predictive processing.

Detecting a target sound within a mixture of sounds (referred to as auditory stream segregation) is crucial for perception in natural environments, a skill humans and animals excel at. This study investigates the role of temporal coherence in auditory stream segregation in human newborns using high-density EEG recordings. Sleeping newborns were exposed to temporally coherent auditory tone sequences embedded in random background tones, and their event-related responses were analyzed. The results indicate that newborns can segregate auditory streams based on temporal coherence, suggesting that this stream segregation is driven by automatic mechanisms from birth, as evidenced by brain responses resembling the object-related negativity (ORN) event-related potential (ERP) component. However, discriminating among different signal-to-noise ratios requires further fine-tuning, as evidenced by delayed latencies in neonates compared to adults. These findings indicate that temporal coherence aids in detecting and orienting toward salient stimuli, thereby laying the foundation for the development of abilities such as selective attention and speech perception.