A Dynamic Framework for Auditory Stream Segregation under the ABAB Stimulus Paradigm Based on Single-Unit Extracellular Electrophysiological Recordings

In complex acoustic environments, the auditory system segregates mixed inputs from multiple sound sources into perceptually distinct streams, a process known as auditory stream segregation. Although extensively studied at the neurophysiological level, existing neural metrics typically reflect time-averaged or static representations, lacking a unified framework that jointly captures temporal dynamics and segregation strength. Here, we propose a time-resolved analytical framework for ABAB alternating auditory stimulation based on a minimal temporal unit, the Single AB Unit (Sab), and introduce the Identity Fidelity Index (IFI) to quantify normalized response bias between alternating sound components. We further extend IFI to a time-resolved formulation, IFI(t), enabling continuous tracking of neural response bias over time. Using a generative model based on Laplace tuning functions and Poisson spiking processes, we show that IFI and IFI(t) robustly capture population-level response restructuring induced by frequency separation, and are consistent with classical dip ratio measures. At the population level, we define pIFI(t) and propose a dual-threshold mechanism that accounts for the transition from integrated to segregated percepts. This framework further reveals a coupled relationship between temporal coherence, population response structure, and neural response strength within a unified parameter space. Together, this study provides a unified computational framework for describing neural temporal dynamics and auditory stream segregation, offering a quantitative perspective on the neural coding mechanisms underlying auditory scene analysis.