John J. Varghese

Spikes from compound action potentials in simulated microelectrode recordings

In this paper we demonstrate by simulation, that the spike features apparent in low-impedance deep brain stimulation (DBS) targeting microelectrode recordings (MER) may not reflect the action potentials of individual neurons. Rather, they are more likely to be compound action potentials from a synchronized group of neurons local to the electrode. Initially we simulate the MER by combining the electric fields from a large number of independent neurons surrounding the microelectrode tip. When synchronization is introduced amongst neurons the resulting discernible spikes in an MER are far more likely to relate to compound action potentials from subsets of synchronized neurons than individual action potentials. Different sub-sets of neurons are then synchronized to see how well a conventional spike sorting algorithm can differentiate the compound action potentials from different groups of neurons. These simulations offer insight into the clinical interpretation of DBS MERs used to target deep brain structures.

Theoretical & experimental analysis of the Non Markov Parameter to detect low frequency synchronisation in time series analysis

A theoretical investigation into the behaviour of the Non-Markov Parameter is performed from a signal processing perspective in contrast to previous methodologies based on stochastic processes theory. The results indicate that the NMP can be regarded as an informational metric which is indicative of the degree of low frequency synchronisation in a complex system. These results have deep implications for physiological analysis of biological systems where the presence of sychronisation is often a marker of pathological functioning. The NMP measure is then applied to in vivo micro-electrode recordings from the subthalamic nucleus.