TY - JOUR
T1 - Estimation of neuronal firing rates with the three-state biological point process model
AU - Zelniker, Emanuel E.
AU - Bradley, Andrew P.
AU - Castner, Joanna E.
AU - Chenery, Helen J.
AU - Copland, David A.
AU - Silburn, Peter A.
PY - 2008/9/30
Y1 - 2008/9/30
N2 - In the subcortex of the human brain, neuronal firing events are stochastic and the inter-arrival times of action potentials (APs) are highly irregular. It has been shown that stimulation of the subthalamic nucleus (STN), a small subcortical structure located within the basal ganglia, can help ameliorate the motor symptoms associated with Parkinson's disease (PD). However, success of image guided stereotactic surgery is reliant upon the refinement of the anatomic target (in this case the STN) based on micro-electrode recordings (MERs) of background activity and firing rate. In practice MERs must be analysed on-line and in real-time. Currently, the most common method of performing on-line MER analysis is a manual thresholding procedure. However, this is subjective in nature and often complicated by the presence of variable amounts of background noise. Therefore, in this paper, we present an automated adaptive thresholding technique, based on a modified 'top-hat' operator, which detects APs exceeding the local background activity. We then go on to model these inter-arrival times using a coupled Poisson process that provides improved estimates of both inter-burst and intra-burst neuronal firing activity in the STN. Crown
AB - In the subcortex of the human brain, neuronal firing events are stochastic and the inter-arrival times of action potentials (APs) are highly irregular. It has been shown that stimulation of the subthalamic nucleus (STN), a small subcortical structure located within the basal ganglia, can help ameliorate the motor symptoms associated with Parkinson's disease (PD). However, success of image guided stereotactic surgery is reliant upon the refinement of the anatomic target (in this case the STN) based on micro-electrode recordings (MERs) of background activity and firing rate. In practice MERs must be analysed on-line and in real-time. Currently, the most common method of performing on-line MER analysis is a manual thresholding procedure. However, this is subjective in nature and often complicated by the presence of variable amounts of background noise. Therefore, in this paper, we present an automated adaptive thresholding technique, based on a modified 'top-hat' operator, which detects APs exceeding the local background activity. We then go on to model these inter-arrival times using a coupled Poisson process that provides improved estimates of both inter-burst and intra-burst neuronal firing activity in the STN. Crown
UR - http://www.scopus.com/inward/record.url?scp=50949117699&partnerID=8YFLogxK
U2 - 10.1016/j.jneumeth.2008.05.026
DO - 10.1016/j.jneumeth.2008.05.026
M3 - Article
C2 - 18598715
AN - SCOPUS:50949117699
SN - 0165-0270
VL - 174
SP - 281
EP - 291
JO - Journal of Neuroscience Methods
JF - Journal of Neuroscience Methods
IS - 2
ER -