  Bidirectional deep brain stimulation (bdDBS) devices capable of recording
differential local field potentials (dLFP) enable neural recordings alongside
clinical therapy. Efforts to identify objective signals of various brain
disorders, or disease readouts, are challenging in dLFP, especially during
active DBS. In this report we identified, characterized, and mitigated a major
source of distortion in dLFP that we introduce as mismatch compression (MC). MC
occurs secondary to impedance mismatches across the dLFP channel resulting in
incomplete rejection of artifacts and downstream amplifier gain compression.
Using in silico and in vitro models we demonstrate that MC accounts for
impedance-related distortions sensitive to DBS amplitude. We then use these
models to develop and validate a mitigation strategy for MC that is provided as
an opensource library for more reliable oscillatory disease readouts.
