Sensory feedback allows animals to read, react, and adapt to an environment. However, the sensory information received by the body could become overwhelming, thus overloading the brain. Yet, animals are able to process all this information by canceling redundant signals from their surroundings. One species in which this phenomenon has been explored is the Apteronotus leptorhynchu (brown ghost knife fish), a small electric fish that generates a bioelectric field. Sensory signals from electrical sensing organs are passed through granular cerebellar cells, which then feedback onto the primary sensory neurons to cancel low-frequency components of the sensory information. This enables the canceling of redundant sensory information and noise and makes downstream networks more sensitive to changes in sensory input. In this preliminary study, we take the first step of replicating this functionality using a series of neural resonators. Each resonator has a unique preferred frequency and then should feed back onto the sensory signal with a frequency-specific phase delay. Our resonator is a neural “differentiator” from our prior work, which amplifies frequencies up to the cutoff frequency of the network. We propose how sensory feedback cancellation could be incorporated into bioinspired robot control.