부산대학교 도서관

Development of novel approaches to behavioral test data analysis is of considerable importance for both fundamental research and experimental neuropharmacology. Antipsychotic agents used to treat positive and negative symptoms in schizophrenia are of particular interest. Although antipsychotics exert potent effects on animal behavior in simple behavioral tests, they can be difficult to distinguish from other CNS-depressing agents, such as sedatives. In this paper, we propose color coding of video sequences as a method for the analysis of behavioral pattern structure in rats, using the effects of haloperidol, a typical antipsychotic, in the Open field test as an example. The study was carried out on outbred albino male rats weighing 250–300 g. Three-min video sequences of rat behavior in the Open field test were processed using Python and the OpenCV library in the Google Colab 3 environment. Color coding allowed the present (t = 0), near-future (t = 0.33 s), and the more distant-future (t = 1.66 s) location of an animal in the Open field arena to be marked with different colors and overlaid within a single frame. Using the proposed 3-timepoint color coding method, we were able to detect specific effects of haloperidol on animal behavioral patterns, which are undetectable via conventional techniques of behavioral data analysis in the Open field test. This method proved effective for data analysis and processing, and the results were in accordance with other author's data obtained using computerized and conventional visualization techniques. [ABSTRACT FROM AUTHOR]