Self-organization of two-dimensional insect neural networks

Amir Ayali, Orit Shefi, Eshel Ben‐Jacob

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


How single neurons self‐organize to form a complex functional system, the neural network, is a fundamental question in developmental neuroscience, computation science, and pattern formation. Two‐dimensional in vitro invertebrate preparations offer an attractive model system to tackle this question due to the large size of the neurons, and their ability to grow in relative isolation as well as to develop elaborate networks. Using cultured locust neurons, we monitor and analyze their morphology and growth process under various density conditions. Neurons are affected by their neuronal vicinity; they actively target neighbor cells, and their overall structure in the 2D plane is oriented or directional in the presence of nearby cells. Connections formed between neurons lead to a process of simplification of the network members morphology. As the network matures the tendency for structural reduction becomes apparent in the neuronal as well as the whole network morphology. The preparation we have developed has vast potential for the study of form‐function relation issues.
Original languageAmerican English
Title of host publicationExperimental Chaos 2001
EditorsO. Shefi
PublisherAmerican Institute of Physics, Melville, New York
StatePublished - 2002


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