Document Type
Thesis
Date of Award
Fall 1-31-2000
Degree Name
Master of Science in Computer Science - (M.S.)
Department
Computer and Information Science
First Advisor
Michael Recce
Second Advisor
James A. McHugh
Third Advisor
Farzan Nadim
Abstract
Various techniques have been considered in the past to identify distinct spike shapes from mulitunit extracellular recording. These techniques involve adaptive filtering techniques or template matching techniques or hierarchical clustering techniques. In this investigation, we have used Principal Component Analysis followed by various clustering techniques to identify distinct spike shapes. The amplitude filter is used to separate spikes from background neuronal activity. The correlation matrix of the spike data is used to compute principal component wave forms. Each spike is thus represented by the coefficients of principal components. Then, We have used agglomorative hierarchical clustering algorithm to perform the initial clustering of the data set. The clustering results are then refined by the application of the Estimation Maximization Algorithm. The Bayesian Information Criteria(BIC) is used to find out best fit of the model to the data set.
Recommended Citation
Rege, Jayesh, "Analysis of clustering algorithms for spike sorting of multiunit extracellular recordings" (2000). Theses. 810.
https://digitalcommons.njit.edu/theses/810
