title: Application of principal component analysis for characterizing convergence patterns of inputs in interneurones of the cat forelimb segments.
abstract: We attempted to quantitatively describe a variety of convergence patterns of inputs from peripheral nerves and descending tracts (13 sources) onto interneurones of the cat forelimb segments (C6-C8). To this end we applied principal component analysis using the latency of firing as the parameter of each input. The first 3 principal components thus obtained explained 65% of the total variance of convergence patterns and characterized the input pattern of each cell. The first principal component correlated mainly with inputs from pads and the median nerve, the second with the cortico- and rubro-spinal tracts and the third with the superficial radial nerve.
authors.affiliation: Department of Neurophysiology, Faculty of Medicine, University of Tokyo, Japan.
authors.forename: S
authors.initials: S
authors.lastname: Kitazawa
mesh_terms: D000818:Animals; D002415:Cats; D002540:Cerebral Cortex / Q000166:cytology / Q000502:physiology; D004558:Electric Stimulation; D005552:Forelimb / Q000294:innervation*; D007395:Interneurons / Q000502:physiology*; D011826:Radial Nerve / Q000502:physiology; D013116:Spinal Cord / Q000166:cytology / Q000502:physiology