Statistical methods of analysis and visualization of extracellular microelectrode recordings

Determining neuronal structures during stereotactic surgery in Parkinson's disease (PD) patients is a prerequisite for optimal placement of deep brain stimulation electrodes and/or neuronal ablation. This study describes statistical signal processing methods that automatically analyze microelectrode recordings and display a neurophysiological brainmap of the stereotactic trajectory. The spontaneous signals along the trajectory were recorded during neurosurgery of PD patients and analyzed post surgery. Our approach applies characterizations and visualization of energy, marginal probability density function, power spectral density, the time-domain signal, the autocorrelation function and partial autocorrelation function of the microelectrode recordings at the different depths along the trajectory. These are novel analysis methods of microelectrode recordings and enable neurosurgeons to easily distinguish adjacent brain structures and characteristics within and between the neuronal structures even when spike detection is impossible.