In a natural setting, adaptive mechanisms constantly modulate the encoding properties of sensory neurons in response to changes in the external environment. Recent experiments have revealed that adaptation affects both the spatiotemporal integration properties and baseline membrane potential of sensory neurons. However, the precise functional role of adaptation remains an open question, due in part to contradictory experimental results. Here, we develop a framework to characterize adaptive encoding, including a cascade model with a time-varying receptive field (reflecting spatiotemporal integration properties) and offset (reflecting baseline membrane potential), and a recursive technique for tracking changes in the model parameters during a single stimulus/response trial. Simulated and experimental responses from retinal neurons are used to track adaptive changes in receptive field structure and offset during nonstationary stimulation. Due to the nonlinear nature of spiking neurons, the parameters of the receptive field and offset must be estimated simultaneously, or changes in the offset (or even in the statistical distribution of the stimulus) can mask, confound, or create the illusion of adaptive changes in the receptive field. Our analysis suggests that these confounding effects may be at the root of the inconsistency in the literature and shows that seemingly conflicting experimental results can be reconciled within our framework.