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O. Tavdishvili, “Automatic Classification Algorithm for Observable Data Set,” Proceedings of the Institute of Cybernetics, Vol. 3, No. 1-2, 2004, pp. 136-141.

has been cited by the following article:

• TITLE: Quantitative Analysis of Formation of Active Avoidance Behavior in the Hippocampus Coagulated and Intact White Albino Rats

  AUTHORS: Sulkhan N. Tsagareli, Nino G. Archvadze, Otar Tavdishvili

  KEYWORDS: Behavior; Learning; Memory; Active Avoidance; Hippocampus; Neocortex; Unsupervised Clustering

  JOURNAL NAME: Journal of Behavioral and Brain Science, Vol.2 No.1, February 29, 2012

  ABSTRACT: Unsupervised cluster analysis is proposed for analysis of active avoidance formation in three groups of albino rats: 1) intact; 2) with electrolytic lesions of neocortex over the dorsal hippocampus; and 3) with electrolytic lesions of dorsal hippocampus. The term “behavior vector” has been introduced to assess quantitatively the behavior of rats while learning. The proposed approach enables to assess active avoidance behavior in rats simultaneously by all the test parameters: 1) reaction to the light; 2) reaction to the electric irritation; and 3) inter-trial spontaneous behavior. The animals were grouped by their behavioral resemblance through the learning process. The proposed method facilitates the assessment of learning capacities in animals and paves way for getting additional information concerning correlative relationships between their learning skills and other neuroethological and neurobiological parameters.