Use of multichannel recording electrodes and independent component analysis for target localization in deep brain structures

Deep brain stimulation (DBS) has proven to be an effective treatment for ailments such as Parkinson´s disease. In surgery, localization of the stimulation site in the brain is extremely time-consuming and difficult for the patient. We propose to use multichannel recording electrodes to obtain more information in less time, and array processing techniques to improve the quality of the data received. We present data from the use of independent component analysis (ICA) as a processing technique used for blind source separation (BSS) and noise suppression. The neural signals examined are from the basal ganglia and thalamus regions of rat brain. Data was taken using Michigan silicon electrodes with a single shank and 8 recording sites arrayed around the tip. The distance between sites ranged from 40 to 80 μm in both the horizontal and vertical directions, so overlapping neural data was observed both along and across the electrode. The data was taken in acute surgical procedures on anesthetized rats. We present improvements in signal-to-noise ratio (SNR) from ICA as opposed to raw data, as well as giving examples of isolating signals that were previously not discriminable.