A stochastic locomotor control model for the nurse shark, ginglymostoma cirratum
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The locomotor behavior of the nurse shark (Ginglymostoma cirratum) is characterized by 17 variables (frequency and ratios of left, right, and total turns; their radians; straight paths (steps); distance travelled; and velocity) Within each of these variables there is an internal time dependency the structure of which was elaborated together with an improved statistical model predicting their behavior within 90% confidence limits. The model allows for the sensitive detection of subtle locomotor response to sensory stimulation as values of variables may exceed the established confidence limits within minutes after onset of the stimulus.
The locomotor activity is well described by an autoregression time series model and can be predicted by only seven variables. Six of these form two independently operating clusters. The first one consists of: the number of right turns, the distance travelled, and the mean velocity; the second one of: the mean size of right turns, of left turns, and of all turns. The same clustering is obtained independently by a cluster analysis of cross-sections of the seven time series. It is apparent that, among a total of 17 locomotor variables, seven behave as individually independent agents, presumably controlled by seven separate and independent centers. The output of each center can only be predicted by its own behavior. In spite of the individual behavior of the seven variables, their internal structure is similar in important aspects which may result from control by a common command center. The shark locomotor model differs in important aspects from that previously constructed for the goldfish. The interdependence of the locomotor variables in both species may be related to the control mechanisms postulated by von Holst for the coordination of rhythmic fin movements in fishes. A locomotor control model for the nurse shark is proposed.
KeywordsPredictor Variable Time Series Model Locomotor Behavior Carassius Auratus Straight Path
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