A Dynamic Neural Network Model of the Zebrafish Posterior Lateral Line Sensorimotor Pathway
Year: 2012
Type: dissertation
Abstract: Neural network architecture is an important area of study in Neuroscience, as the possible \ndynamics of a network are highly dependent on its structure. I apply artificial neural \nnetworks, tools from the field of Computer Science, to study the neural anatomy of a larval \nzebrafish Posterior Lateral Line sensorimotor pathway. The goal of this study is to understand \nthe structural constraints a simulated escape response and a simple swimming motion \nplace on network architecture. An artificial neural network, together with realistic stimulus/ \nresponse pairs, is used to simulate a simplified zebrafish brain together with escape \nand swimming behaviors. To characterize the structure of connections in a functioning \nnetwork I examined the distribution of participating neurons in the model brain. I further \nexamined the effects of increasing network size and the number of stimulus/response pairs \non model convergence time and the number of brain neurons participating in activation. I \ndetermined theoretically that 4 brain neurons were always sufficient in generating correct \nescape and swimming responses. This corresponds closely with the Mauthner series in zebrafish \nthought to be responsible for initiating the escape response. The stimulus/response \npairs impose no other significant structural constraints, allowing me to conclude that the \nhighly conserved structure of the zebrafish PLL must result from other processes.
Author: Michael T. Stobb
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2186922285