Title :
Principal component analysis (PCA) of complex spike activity recorded simultaneously from multiple Purkinje cells
Author :
Hu, Qiyu ; Lang, Eric J. ; Sugihara, Izumi
Author_Institution :
Dept. of Physiol. & Biophys., New York Univ., NY, USA
Abstract :
A matrix of microelectrodes is inserted into the layer of Purkinje cells of the cerebellum cortex of a rat. Each wavelet of the cell activity is a burst of positive and negative pulses (complex spike), but interest is only in the onset instants, which are recognized by software from the recorded pulses. Four formats are designed to store and analyze the onset sequences: time-principal-component-analysis (PCA), space-PCA, and unbalanced forward and backward PCAs. Good results are obtained by analyzing the count/bin spikes. Clustering of cells on the plane of eigenvectors 1 and 2 and PCA-invariably are found
Keywords :
bioelectric potentials; brain; cellular biophysics; eigenvalues and eigenfunctions; neurophysiology; vision; wavelet transforms; cerebellum cortex; complex spike activity; eigenvectors; microelectrodes; multiple Purkinje cells; negative pulses; onset sequences; positive pulses; rat; software; time-principal-component-analysis; wavelet; Biophysics; Covariance matrix; Eigenvalues and eigenfunctions; Fires; Microelectrodes; Physiology; Principal component analysis; Sampling methods; Symmetric matrices; Vectors;
Conference_Titel :
Time-Frequency and Time-Scale Analysis, 1992., Proceedings of the IEEE-SP International Symposium
Conference_Location :
Victoria, BC
Print_ISBN :
0-7803-0805-0
DOI :
10.1109/TFTSA.1992.274195
