An automated method to remove artifacts induced by microstimulation in local field potentials recorded from rat somatosensory cortex

Stimulus evoked field potentials are commonly used in studying sensory systems. But, the stimulus induced signals are often contaminated by stimulus artifacts. Especially, microstimulation greatly affects the recorded field potentials. In this paper, we present a novel technique capable of removing the microstimulation induced stimulus artifacts from the recorded sensory signals (local field potentials, LFPs). The algorithm detects the start and the end of the artifact based on signal derivative and removes the artifacts from the recordings. This algorithm overcomes the barrier of artifact shape, duration, and frequency imposed by many existing techniques and provides the flexibility of automatic batch processing of multiple neuronal signals. This technique provides the advantages of being simple, straightforward, and computationally efficient, demonstrating to be an efficient and accurate artifact removal method, as validated by analyzing recordings from the rat somatosensory cortex (S1) using standard borosilicate micropipettes (1 MΩ).