Application of temporal self-organizing maps to patterning short-time series of fish behavior responding to environmental stress

Response behaviors of animals to stressors are complicated. Especially, it is difficult to analyze temporal data in addressing the time course development of behavioral states to stressors. Not much study has been conducted in identifying the short-term behavior conditions of indicator organisms responding to stressors. Hence, in the present study, we selected three temporal networks, Temporal Kohonen Map (TKM), Recurrent Self-Organizing Map (RSOM), and Recursive Self-Organizing Map (RecSOM) to characterize the behavior strength of individual fish exposed to Atrazine (ATZ, 0.12 mg/L) for 15 days. The trained networks were able to detect the characteristic behavior strength segments presenting the Stepwise Behavior Response Model (SBRM). TKM was found suitable for detecting strong curves in a short training time, but clustering was limited in grouped segments. In contrast, RecSOM was found to be most suitable for detecting behavior segments with both high and low contrast response under toxic exposure. RecSOM was effective in clustering but could not detect segments with strong changes. Finally, our results presented that the temporal SOMs, especially RecSOMs, were feasible in identifying short-term time series data and could be utilized for on-line monitoring of test organisms under stressful conditions.