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Sound waveforms convey information largely via amplitude modulations (AM). A large body of experimental evidence has provided support for a modulation (bandpass) filterbank. Details of this model have varied over time partly reflecting different experimental conditions and diverse datasets from distinct task strategies, contributing uncertainty to the bandwidth measurements and leaving important issues unresolved. We adopt here a solely data-driven measurement approach in which we first demonstrate how different models can be subsumed within a common ‘cascade’ framework, and then proceed to characterize the cascade via system identification analysis using a single stimulus/task specification and hence stable task rules largely unconstrained by any model or parameters. Observers were required to detect a brief change in level superimposed onto random level changes that served as AM noise; the relationship between trial-by-trial noisy fluctuations and corresponding human responses enables targeted identification of distinct cascade elements. The resulting measurements exhibit a dynamic complex picture in which human perception of auditory modulations appears adaptive in nature, evolving from an initial lowpass to bandpass modes (with broad tuning, Q∼1) following repeated stimulus exposure., Author Summary Amplitude modulations are considered the key carriers of intelligible information in auditory signals, and consequently it is of significant interest to discover how they are neurally analyzed and perceptually encoded. A dominant model has emerged from extensive experimental and theoretical studies of this phenomenon. This model posits that amplitude modulations are parsed into channels of different temporal rates via a bank of bandpass filters. Using exclusively data driven approaches with minimal assumptions about the structure of the model, the picture that emerges is of an adaptive process. Initially, human listeners in these tasks perceive modulations as if through a lowpass filter with very low cutoff frequency, which gradually evolves to become a broadly tuned bandpass process at higher modulation frequencies, reflecting the modulations of the target stimuli. This surprising dynamic characteristic emphasizes the plastic nature of modulation analysis in sensory perception.

The phenomenon of visual stability is classically explained by an internal forward model predicting the sensory consequences of an eye movement based on efference copy. However, this model cannot explain why some object displacements go undetected, a phenomenon that may depend on a passive prior belief that the world is stable. With reverse correlation, we investigated saccadic suppression of displacement and found that transsaccadic correspondence operates differently depending on the position of the postsaccadic visual target relative to the primary landing position; when the signal falls within the extent of primary saccadic scatter, observers are less able to remap accurately. Furthermore, we observed that the neural representations driving perceptual and saccadic decisions are similar when saccading to a target, but that the representations driving transsaccadic correspondence are different from those driving secondary saccades.