Tracking Tremor Frequency in Spike Trains Using the Extended Kalman Filter

Tremor is one of the most disabling symptoms in patients with many movement disorders including Parkinson´s disease (PD) and essential tremor (ET). Neural tremor, which is measured by microelectrodes placed near nerve cells or obtained from brain cells during stereotactic neurosurgery, is due to the fluctuation of the firing rate of neurons. The frequency of this neural tremor varies over time and is nonstationary. We describe a frequency tracking method using the extended Kalman filter (EKF) to estimate the instantaneous tremor frequency (ITF) of binary spike trains detected from microelectrode recordings (MER). The results demonstrate that the EKF can accurately track fluctuations in tremor frequency even though the noise in binary spike trains is not Gaussian